The Adolescent Substance Use Risk Continuum: A Cultural, Strengths-Based Approach to Case Conceptualization

Alexis Miller, Jennifer M. Cook

Many theories are used to conceptualize adolescent substance use, yet none adequately assist mental health professionals in assessing adolescents’ strengths and risk factors while incorporating cultural factors. The authors reviewed common adolescent substance abuse theories and their strengths and limitations, and offer a new model to conceptualize adolescent substance use: The Adolescent Substance Use Risk Continuum. We posit that this strengths-based continuum enables clinicians to decrease stigma and offer hope to adolescents and their caregivers, as it integrates relevant factors to strengthen families and minimize risk. This model is a tool for counselors to use as they conceptualize client cases, plan treatment and focus counseling interventions. A case study illustrates the model and future research is suggested.


Keywords: adolescents, substance use, case conceptualization, cultural factors, strengths-based


For decades, theorists have worked to understand adolescent behaviors and conceptualize adolescent substance use. These theories have provided a strong base to conceptualize adolescent substance use, yet none integrate important counseling-focused concepts such as strengths and cultural factors. The Adolescent Substance Use Risk Continuum (ASURC) expands upon previous theoretical models and is designed to enhance counselors’ ability to conceptualize adolescent substance use from a strengths-based, stigma-reducing, and culturally sensitive perspective. The ASURC adds to counselors’ abilities to conceptualize adolescent substance use and enhances their abilities to create comprehensive treatment plans and interventions.


Theoretical Underpinnings

The theory of planned behavior (TPB; Ajzen, 1985), social learning theory (SLT; Akers, 1973), social control theory (SCT; Elliott, Huizinga, & Ageton, 1985), and social development theory (SDT; Hawkins & Weis, 1985) are four theories that have been applied to adolescent substance use. The TPB was developed to describe an individual’s behavior in a general sense, while the other three theories were developed to explain deviant and delinquent behavior. Even though these four theories were developed in the 1970s and 1980s and were not developed specifically for adolescent substance use, researchers have applied these theories to predict substance use within this population (Corrigan, Loneck, Videka, & Brown, 2007; Malmberg et al., 2012; Schroeder & Ford, 2012).


The TPB was developed as an expansion of the theory of reasoned action, which describes behavior as contingent upon an individual’s beliefs about a certain behavior and the perceived social pressure on the individual to perform that behavior (Ajzen, 1985). In addition to individual beliefs and perceived social pressure, the TPB adds an additional element to describe behavioral intention: self-efficacy. Self-efficacy refers to one’s perception of control to complete certain behaviors (Ajzen, 1985). Petraitis, Flay, and Miller (1995) introduced two types of self-efficacy related to adolescent substance use: use self-efficacy and refusal self-efficacy. Use self-efficacy consists of adolescents’ beliefs about their ability to obtain alcohol or other drugs, whereas refusal self-efficacy is indicative of adolescents’ beliefs about their abilities to refuse social pressure to use substances (Petraitis et al., 1995).


SLT was developed to explain so-called deviant behavior, and it is heavily influenced by behavioral theories, particularly operant conditioning and reinforcement. Therefore, behavior is learned when it is reinforced (Akers, 1973). The anticipation of either reinforcement or punishment can lead to behavioral increase or decrease, depending on who has the most influence on the adolescent, and who controls the reinforcement or punishment. Delinquent behavior can be influenced and maintained by a variety of sources, including parents, family, peers and school (Petraitis et al., 1995).


Similar to SLT, SCT emphasizes the importance of rewards and punishments in terms of deviant or delinquent behavior (Elliott et al., 1985). The result of either punishment or reinforcement is influenced mainly by an individual’s socialization into what the authors described as conventional society (Elliott et al., 1985). Conventional society points to general societal norms, largely congruent with dominant cultural norms. Therefore, according to SCT, an adolescent with a strong attachment to conventional society would have stronger internal and external controls and would be less motivated to choose delinquent behaviors. Inversely, an adolescent with a weak attachment to conventional society would have weaker internal and external controls and be more likely to engage in deviant behaviors (Elliot et al., 1985).


Hawkins and Weis (1985) integrated SLT and SCT to develop the SDT. The SDT is a developmental model of delinquent behavior that focuses on how adolescents are socialized through family, peers and school. Delinquent behaviors develop when adolescents are not socialized into conventional society appropriately. Opportunities for involvement with conventional individuals are seen as necessary but not sufficient for an individual to develop positive social bonds (Hawkins & Weis, 1985). There are two mediating factors associated with this socialization process toward positive social bonds: skills possessed by an adolescent and reinforcement of the opportunities for involvement (Hawkins & Weis, 1985). Skills that enhance an adolescent’s ability toward social bonds include adolescents’ social skills, or skills needed to interact and form social bonds with others (Hawkins & Weis, 1985). Similar to SLT and SCT, the SDT stresses the need for reinforcement, where behavior must be reinforced to continue (Hawkins & Weis, 1985).


Strengths and Limitations of Theoretical Underpinnings


The aforementioned models have made significant contributions to how counselors conceptualize adolescent substance use. Particularly, these models highlight the role social influences play in adolescent substance use and, accordingly, how social influences impact behavioral factors like reinforcement, punishment and reward (Akers, 1973; Elliot et al., 1985; Hawkins & Weis, 1985; Petraitis et al., 1995). Additionally, all models have been validated empirically to be predictive of adolescent substance use (Corrigan et al., 2007; Malmberg et al., 2012; Schroeder & Ford, 2012). Although these studies provide empirical support for predicting adolescent substance use and highlight social influences and behavioral factors, limitations exist, namely a lack of specificity related to social influences, the use of problematic language, and failure to incorporate cultural factors and contexts. Below, we detail the strengths and limitations of the aforementioned models to provide a rationale for a more encompassing, strengths-based approach to conceptualizing adolescent substance use.


Social Influences

Research has shown that social factors, such as family and peer group, play a mediating role in adolescent substance use in both positive and negative ways (Piko & Kovács, 2010; Van Ryzin, Fosco, & Dishion, 2012). Also, research highlights how important social influences are on adolescents’ substance use. The TPB suggests that substance use is dependent upon the adolescent’s individual attitudes of substance use and perceived social pressure to use substances (Petraitis et al., 1995). SLT and SCT emphasize how behavior, including substance use, is learned through reinforcement or punishment (Akers, 1973 Elliott et al., 1985). Someone in the adolescent’s life has to reward or punish the adolescent’s substance use for it to continue or cease.


Further, the SDT emphasizes the socialization process in regards to deviant behavior in adolescents. According to the SDT, socialization begins within the family unit, where a child has variable opportunities to develop social, cognitive and behavioral skills (Hawkins & Weis, 1985). As a child grows older, ostensibly these skills are reinforced positively within the school setting and peer group (Hawkins & Weis, 1985). However, if children are not socialized appropriately in the family system, children may not develop socially, cognitively and behaviorally as expected. In turn, they may turn to substance use to cope with stressful life events. Further, if adolescents were not socialized appropriately in early childhood, they may be at greater risk to become involved with adolescents who use substances.


While the four theories emphasize social influences as a factor in adolescent substance use, the TPB, SLT and SCT used the term social influences in a general sense only, and do not differentiate between the different types of social influences. There are a variety of social influences, including family, peers, school, sports teams, clubs and religious organizations, and each can have a varied impact on adolescents’ substance use. For example, involvement in religious organizations can protect some adolescents from substance use (Steinman & Zimmerman, 2004), while engagement with sports teams may increase adolescent substance use for others (Farb & Matjasko, 2012). The SDT was the only model discussed that divides socialization into three units: family, peer and school; however, the SDT suggests that family, peer, and school units all go through the same development process, seemingly at the same rate. Presumably, an adolescent is given the same opportunity for involvement with all three units toward the goal of creating healthy social bonds, and these opportunities are influenced by an adolescent’s current social skills and reinforcement from others (Hawkins & Weis, 1985). This adolescent substance use conceptualization can be problematic because it suggests the family, peer group and school all go through the same developmental process simultaneously and fails to recognize that different units can have different influences (some positive, some negative) on an adolescent, and these influences may develop asymmetrically. Further, the SDT proposes that a “social bond” (Hawkins & Weis, 1985, p. 80) to conventional society is a common goal and that adolescents have the social skills in place to create these bonds. Although it is hoped that adolescents will have strong social skills and that their support systems will endeavor to create healthy social bonds, this may not be the case for all adolescents. Further, some adolescents who have strong social skills may use them to procure substances and influence others to use.


Problematic Language

The developers of SLT, SCT, and SDT used the terms deviant behavior, delinquent behavior, and conventional society to describe aspects contained in their theories. In juvenile justice literature, the terms deviant and delinquent point to adolescent behaviors considered to be age-inappropriate and destructive to self and family, as well as illegal (Pope, 1999). However, these terms are not used to simply describe behaviors as they were intended—they have become labels used to classify and marginalize adolescents who have made poor choices and acted in ways incongruent with conventional society (Constantine, 1999). Often, these terms are applied to adolescents who encompass non-dominant cultural identities (e.g., race, social class), which can serve to further oppress and marginalize adolescents who may experience societal and structural inequality. At the very least, these terms define adolescents by choices they have made and may lead to assumptions about who they are, adding additional stigma and shame to worthy individuals who can learn to make different choices, which is incongruent with a strengths-based perspective.


Conventional society is a term used to describe societal norms, determined most often by dominant U.S. cultural groups (Duncan, 1999). Similar to the issues with the terms deviant and delinquent, the term conventional society may not account accurately for cultural nuances and differences that vary from dominant culture expectations, furthering societal and structural oppression, discrimination and inequality clients experience (Constantine, 1999). For example, according to SCT, weak attachment to conventional society contributes to weaker internal and external controls, and an adolescent can develop a weak attachment to conventional society when she experiences a strain between her aspirations and her perceptions of the opportunity to actualize such aspirations. Therefore, through an SCT lens, if this adolescent lives in a low-income neighborhood where crime and unemployment are prevalent, she may be perceived to have a weak attachment to conventional society (Petraitis et al., 1995), without taking into account that her environment is out of sync with conventional society and cultural norms as defined by the dominant culture.


Cultural Factors

The final common limitation of the aforementioned models is the lack of inclusion of cultural influences on adolescents’ substance use. As mentioned previously, these four models highlight the importance of social influences on adolescents’ substance use yet do not specifically take cultural factors into consideration. The TPB discusses social influences in regard to an adolescent’s beliefs and perceived social pressure (Ajzen, 1985); however, there is no mention that these beliefs might be influenced by cultural values and experiences. Similarly, SLT suggests that an adolescent’s deviant behavior is influenced by positive or negative reinforcement received within the social context (Akers, 1973), yet fails to acknowledge that these positive or negative reinforcements are most likely influenced by cultural factors. The SDT outlines the socialization process through three different units (Hawkins & Weis, 1985), all of which exist within cultural contexts that influence adolescents’ substance use, yet the authors do not cite this as a possibility. Similarly, SCT discusses social influences on a systemic level, focusing on adolescent academic and occupational goals (Elliott et al., 1985). Adolescents’ cultural factors can influence their academic and occupational goals, as well as their perception of the likelihood of obtaining these goals. The theme among these four models is that they include factors influenced by culture without specifically mentioning or addressing culture or cultural variations.


We suggest a conceptual model for adolescent substance use that addresses specific social influences, uses inclusive and strengths-based language, and integrates cultural factors. We propose the ASURC as a model to meet this need. The ASURC asserts that while different social contexts are intertwined with one another, they all influence adolescent substance use in distinct ways. Further, the ASURC model uses strengths-based terms to reduce stigma and shame, and empowers clients and their caregivers to make person-affirmative choices. Finally, the ASURC integrates cultural components into all aspects of the model in order to provide appropriate context, acknowledging that adolescent substance use develops in a cultural context.


The Adolescent Substance Use Risk Continuum


     The aforementioned theoretical models contain strengths and limitations and influenced the development of the ASURC model. Prior models emphasized social influence on adolescent substance use, and we emphasize social influences in our model as well. However, we believe that different social systems will have different influences on each adolescent, and each social system develops at its own rate. Further, the included areas are not meant to be predictive of substance use, and can serve both as strengths and risk factors, depending on the individual’s circumstances. The areas featured in our model include: parental and caregiver engagement, relationship between parents and caregivers and adolescent, family history of substance use, biological factors, level of susceptibility to peer pressure, childhood adversity, and academic engagement. While we believe the areas in our model have distinct impacts on adolescents, all areas interact and influence one another, and all areas are influenced by singular and intersecting cultural identities.


The ASURC emphasizes the importance of cultural considerations when conceptualizing adolescent substance use. We used Hays’ (1996) “ADDRESSING” model as a foundation. The included cultural factors are by no means exhaustive; counselors are encouraged to expand this list to work with their clients appropriately. Cultural factors should be considered in terms of the individual, family, community and societal contexts when applied to the ASURC areas. Further, it is important to consider ways in which cultural identities can serve as protective or risk factors, depending on the individual’s dominant and non-dominant cultural identities, and the identities most salient to the client. Client cultural influences are subjective experiences, and counselors should take great care and time to determine their relevance for each client.


Further, the ASURC is a strengths-based approach to conceptualizing adolescent substance use. Previous theories contain the use of problematic language, such as conventional society, deviant behavior, and delinquent behavior, when describing adolescent substance use. We feel the use of this language can lead to stigma and instill a sense of shame for this population. Focusing on strengths while using the ASURC will aid clinicians in fostering a sense of hope while working with this population. Strengths are not a separate component of the model, but rather are incorporated in each aspect of the model.






As the name suggests, the ASURC (Adolescent Substance Use Risk Continuum) is a continuum, ranging from minimal risk to high risk. The continuum starts at minimal risk instead of no risk because substance use and addiction can occur in anyone. Further, a continuum suggests that an adolescent can move bi-directionally along the continuum depending on changes. This potential for movement can instill hope and serve to reduce shame associated with adolescent substance use. To use the ASURC model (see Figure 1), one starts at the bottom of the model and considers how the areas listed serve as adolescent protective or risk factors. When working through these areas, cultural identities are incorporated. These identities are represented above the entire model to indicate how they influence everything underneath them. Cultural factors should be considered from the perspective of the individual, family, community and society as a whole, because their influence could be different in each area. Finally, the counselor determines where the adolescent falls on the risk continuum. Because multiple aspects influence an individual’s location on the continuum, it is important to note the protective and risk factors associated with each of the model’s areas for any specific client. This assessment can assist counselors in developing holistic treatment plans that address not only adolescents’ substance use, but also their strengths and areas that could be enhanced as they strive to eliminate substance use.


Model Components


Cultural Influences

There are many cultural factors to consider when conceptualizing adolescent substance use. The ASURC is based on Hays’ (1996) ADDRESSING model. There are nine overlapping cultural influences included in the ADDRESSING model: age, disability status, religion, ethnicity, socioeconomic status, sexual orientation, indigenous heritage, national origin and gender (Hays, 1996). To these we added race and language. This list is not exhaustive but rather a starting point to consider how culture can be a protective or risk factor for adolescents.


When clinicians consider adolescents’ cultural identities, it is important to do so within individual, family, community and societal contexts. To consider only one context diminishes the multiplicity of adolescents’ experiences, and it can negate the impact these contexts have on them. For example, it is common for societal context to be overlooked in favor of individual experiences due to the importance placed on individualism by the dominant culture (Johnson, 2006). When societal context is neglected, structural inequality may be ignored. Structural inequality denotes the oppression or restrictions non-dominant groups experience when they attempt to access resources, including mental health treatment, which are available without hindrance to dominant culture groups. Structural inequality can impact adolescents’ beliefs about their ability to choose not to use substances and their ability to achieve success and access resources, and can reduce hope about their life circumstances (Hancock, Waites, & Kledaras, 2012).


Religion and spirituality. Religion and spirituality can be a protective factor for adolescents. Higher levels of religious involvement tend to correlate with lower levels of substance use (Mason, Schmidt, & Mennis, 2012). Mason et al. (2012) identified two specific aspects of religiosity associated with lower levels of alcohol and drug use: social religiosity and perceived religious support. Social religiosity refers to public displays of religious behavior, such as church attendance and participation in religious activities; perceived religious support encompasses emotional support one receives from a religious institution as well as tangible support like materials or money donated by a religious organization (Mason et al., 2012). Private religiosity, such as personal importance of religion and individual prayer, was not found to be a protective factor (Mason et al., 2012), suggesting the more social aspects of religion are more beneficial for preventing adolescent substance use. Similarly, religion may be a risk factor when adolescents, such as lesbian, gay, or bisexual (LGB) youth, feel judged, shamed, or shunned by their religious community, which may increase the likelihood of substance use (Barnes & Meyer, 2012).


Ethnicity. Ethnicity is significant because reported substance abuse and dependence rates are higher for people of color than for White people in the population (Substance Abuse and Mental Health Services Administration, 2012). Of the total population of people of color, who represent only 38.5% of the U.S. population, 9,319,277 people reported substance abuse and dependence. This number is particularly staggering when compared to White people, who represent 61.5% of the population, 15,713,373 of whom reported substance abuse and dependence (Substance Abuse and Mental Health Services Administration, 2012). These statistics demonstrate that adolescents of color are more likely to develop substance abuse issues than their White counterparts. However, these statistics do not incorporate issues related to structural inequality, nor do they speak to restricted treatment access or racial groups’ protective factors that could be bolstered. For example, Native Americans, who have the highest statistical rate of substance use, also emphasize spirituality and the importance of the extended family (Sue & Sue, 2013). These factors can serve as protective factors for Native American adolescents. Similarly, researchers have found religious engagement among African American adolescents to be a protective factor (Steinman & Zimmerman, 2004). African American adolescents who attended religious services regularly had lower substance use rates than their peers who did not.


Socioeconomic status. Socioeconomic status (SES), particularly education level, influences substance use in adolescents, and subsequently intersects with race and ethnicity. Adolescents who drop out of high school are more likely to engage in substance use, and lower levels of education are associated with higher prevalence of substance-related diagnoses (Henry, Knight, & Thornberry, 2012). American Indian, Latino, and African American adolescents’ math and reading proficiency rates are less than half of White adolescents, most likely due to structural inequality in low-income schools. Students in these groups are less likely to graduate from high school than their White peers (Henry et al., 2012). Furthermore, living in poverty or low SES are associated with higher risks of substance use, and adolescents from racial minority groups are at a higher risk for living in poverty and low-SES families (Van Wormer & Davis, 2013).


Sexual orientation. Sexual orientation is another cultural factor to consider. The LGB community is at greater risk for substance use compared to heterosexual individuals (Brooks & McHenry, 2009). One explanation for the increased risk in the LGB community may be due to homophobia and heterosexual superiority and internalized homophobia, which can lead individuals in the LGB community to turn to substances as a way to cope (Brooks & McHenry, 2009). Further, gay bars are a mainstay of the LGB community, and even though adolescents may not be allowed to drink legally, bar environments may be integral during adolescents’ coming out process (Brooks & McHenry, 2009). Socialization in a bar environment can lead to adolescent substance use as a way to fit in and cope.


Caregiver Engagement and Adolescent–Caregiver Relationship

Family environment can serve as a protective or risk factor for adolescent substance use. A key factor associated with family environment is parental or caregiver supervision. Strong caregiver supervision has been shown to minimize an adolescent’s risk-taking behavior, such as substance use (Van Ryzin et al., 2012). While caregiver supervision is an important protective factor for adolescents, it also is important for adolescents to be able to experience a sense of autonomy within their family of origin. Allen, Chango, Szwedo, Schad, & Marston (2012) defined autonomy within the family of origin as adolescents’ ability to have opinions and beliefs that differ from their caregiver(s) and can be fostered through a supportive adolescent–caregiver relationship. Positive relationships between caregivers and adolescents can increase self-esteem and healthy coping skills, leading to a decrease in risk-taking behaviors (Piko & Kovács, 2010). According to Piko and Kovács (2010), high levels of both satisfaction and caregiver support perceived by the adolescent define this positive relationship. Further, positive relations within the family can lead to higher levels of family obligation perceived by the adolescent. Family obligation is the perceived importance of spending time together, family unity and family social support; higher levels have been found to deter adolescents from unhealthy risk taking, including the use of alcohol and drugs (Telzer, Fuligni, Lieberman, & Galván, 2013).


Conversely, low caregiver involvement can be a risk factor for adolescent substance use. Adolescents who have low caregiver supervision are more likely to engage with peers who use substances and, subsequently, use substances as a way to find social support (Van Ryzin et al., 2012). Additionally, adolescents who do not have positive relationships with their caregivers have a more difficult time self-regulating their behaviors and increased risk for using substances as a way to cope with stress (Hummel, Shelton, Heron, Moore, & van den Bree, 2013).


Family Substance Abuse History and Biological Risks

Family history of substance use is an additional risk factor for adolescents. Children of parents and caregivers who abuse alcohol are four times more likely to develop an addiction (Van Wormer & Davis, 2013). This risk may be partly due to biological predisposition, and part may be environmental. Scientists have begun to better understand how genes affect substance use disorder development and posit that 40–60% of alcohol use disorders can be explained by genes (Van Wormer & Davis, 2013). It can be difficult to determine whether an individual’s addiction is inherited through genetic composition or is learned via the family environment, or a combination of both. Genetics can include predisposition to impulsivity, and some scientists believe individuals at risk for substance use disorders may be biologically predisposed to overreact to stressful situations and life events. Individuals predisposed genetically to engage in sensation-seeking and impulsive behaviors are more likely to experiment with alcohol and other substances (Van Wormer & Davis, 2013). While biological risk can increase adolescents’ predisposition to develop addiction, it does not necessarily lead to addiction (Van Wormer & Davis, 2013). This message can instill hope and infuse self-efficacy in families who may have a history of substance abuse.


Adolescence is marked by an increase in risk-taking behaviors, which may be associated with developmental biology (Telzer et al., 2013). Adolescents show a heightened response in the ventral striatal, which is part of the brain’s reward system. This heightened response in the ventral striatal can cause adolescents to engage in more reward-seeking behaviors compared to children and adults. Further, adolescents show less activation in pre-frontal regions of the brain, the part of the brain in charge of executive functioning, which can lead to increased risk-taking behaviors (Telzer et al., 2013). Research has shown that an increase in family obligation can lead to decreased sensitivity in the ventral striatal and increased activity in the pre-frontal region of the brain (Telzer et al., 2013). These findings suggest that improved quality in the adolescent–caregiver relationship can jettison substance abuse. Specifically, increased family obligation can help buffer some adolescent biological risks for substance use.


Susceptibility to Peer Influences

Peer relationships can play a role in the development of adolescent substance use. During adolescence, individuals start to spend more time with peer groups than with their families (Piko & Kovács, 2010). Additionally, adolescence is marked by a heightened sense of reward. This focus on reward can lead to an increased desire for adolescents to please their peers, making it more difficult for them to resist peer pressure (Van Ryzin et al., 2012). If adolescents associate with peers who use alcohol and drugs, they are more likely to begin using substances as a way to be accepted by their peer group (Van Ryzin et al., 2012).


Inversely, if adolescents are associated with peers who are not involved in substance use, they are less likely to use substances (Van Ryzin et al., 2012). Moreover, there is a negative correlation between adolescents who are involved in supervised extracurricular activities and substance use (Farb & Matjasko, 2012). Specifically, involvement in school-based activities such as performing arts, leadership groups and clubs is associated with lower rates of substance use (Darling, Caldwell, & Smith, 2005). However, there is a positive correlation between athletics and substance abuse, meaning adolescents involved in athletics are more likely to engage in substance use (Farb & Matjasko, 2012). Researchers believe this positive correlation is due to the subculture of high school athletics that promotes alcohol and drug use (Denault, Poulin, & Pedersen, 2009).


Childhood Adversity

Adolescents who experienced childhood adversity are at greater risk for developing substance use disorders (Benjet, Borges, Medina-Mora, & Méndez, 2013). Childhood adversity refers to family instability such as parental and caregiver mental illness, substance use, and criminal behavior, witnessing domestic violence, and experiencing abuse, neglect, interpersonal loss, and socioeconomic disadvantage. Researchers have suggested that this relationship is due to the self-medication hypothesis, in that adolescents who experience childhood adversity may turn to alcohol and drugs in order to alleviate the pain they encounter as a result of such experiences (Benjet et al., 2013).


Not only are adverse childhood experiences a risk factor for developing substance use disorders, but also for substance use opportunities (Benjet et al., 2013). One possible explanation for such opportunities is the presence of substances in the family environment. For adolescents who experienced child abuse or neglect or who witnessed domestic violence, there is an increased chance that substances were present in their household, making it easier for them to gain access to substances (Benjet et al., 2013).


The absence of childhood adversity can be a protective factor against adolescent substance use (Benjet et al., 2013). Another protective factor in terms of childhood adversity is early intervention (Durlak, Weissberg, Dymnicki, Taylor, & Schellinger, 2011). Early intervention can help children develop healthy coping skills to manage stress. Healthy coping strategies can be implemented to replace more negative coping strategies like substance use (Durlak et al., 2011).


Academic Engagement

Academic engagement can have positive and negative effects on adolescents’ potential substance use. Adolescents who drop out of high school are more likely than their counterparts to engage in substance use (Henry, Knight, & Thornberry, 2012). Further, early school disengagement can be a warning sign to predict high school dropout (Henry et al., 2012). For some adolescents, school engagement can be a protective factor. Particularly, adolescents who experience a positive school climate and have strong school engagement are less likely to use substances (Piko & Kovács, 2010). A positive relationship between adolescents and their teachers can be another protective factor. Previous studies have shown that adolescents who have a positive relationship with their teachers and have a high level of perceived support from teachers are less likely to engage in substance use (Demanet & Van Houtte, 2012).


The case study below provides an example of how clinicians can use the ASURC to conceptualize and plan interventions when working with this population.




Case Study


John is a 14-year-old, biracial male and high school freshman. He lives with his mother and grandmother, both of whom are African American, and they reside in a low socioeconomic neighborhood. Both John’s mother and grandmother work full-time, and his mother works a second job, leaving John unsupervised after school and on the weekends. John’s father, a 38-year-old Puerto Rican male, left the home when John was 4 years old. Prior to his father’s departure, John witnessed domestic violence between his parents. During a fight, John intervened on his mother’s behalf and his father hit him. After this event, John’s mother forbade her husband from living in their home and sought counseling services for her son. After his father left, John had only sporadic visits with him, mainly due to his father’s alcohol use. In addition to John’s father’s alcohol use, there is family history of substance use on his mother’s side. His maternal great-aunts use alcohol, and his maternal uncle uses marijuana daily.


This year, John made the varsity football team and has been spending time with the senior football players after practice during the week and on weekends. In addition to being involved with the football team, John is involved with his church community. At school, John is an average student, earning mostly Bs and Cs, and he reports that he enjoys learning.


John started drinking and smoking cigarettes shortly after joining the football team in order to impress the junior and senior football players. Initially, John was hesitant to drink or smoke; however, after using more frequently, he started to enjoy it and reported feeling more relaxed. Currently, John drinks with his friends on the football team two to three times a week and smokes with them daily. John drinks only when he is with this group of peers, yet he has started to smoke when he is alone.


Over the past two months, John’s grandmother has caught him sneaking back into the house at night smelling like alcohol and cigarettes. The first two times this occurred, John’s grandmother decided not to tell his mother because she believed John when he said it would not happen again. When John’s grandmother caught him a third time, she told his mother. John’s mother was surprised when she heard this news because she believed she and John had a close and honest relationship. Distraught, John’s mother brought him to counseling.





Case Analysis Using the ASURC Model


Conceptualizing this case using the ASURC model reveals that John has both protective and risk factors related to his substance use. In terms of his family environment, John’s mother reports that she and John have a close and honest relationship. This close relationship serves as a protective factor for John because a positive relationship between adolescents and their parents is associated with a decreased risk of adolescent substance use (Piko & Kovács, 2010). Yet, John has minimal supervision at night and on the weekends due to his mother and grandmother’s work schedules. Low caregiver supervision is a risk factor for John because research shows that it is associated with an increased risk of adolescent substance use (Van Ryzin et al., 2012). The family’s low SES impacts John’s low caregiver supervision, and low SES can be associated with a higher risk of substance use (Von Wormer & Davis, 2013).


This year, John joined the football team, and previous research has shown that involvement in athletics in high school can be a risk factor for substance use (Farb & Matjasko, 2012), and adolescents who become associated with peers who use are at an increased likelihood to use (Van Ryzin et al., 2012). Furthermore, adolescence is a period characterized by a heightened sense of reward (Van Ryzin et al., 2012), suggesting that John may have an increased desire to please his peers and difficulty resisting peer pressure. At this point in time, John is drinking only when he is with his friends on the football team, suggesting this peer group is influencing John, yet he has begun smoking alone. Additionally, John is involved in his church community, which serves as a protective factor because being involved in a faith community lowers the risk for substance use in adolescents (Mason et al., 2012). Religious engagement, particularly among African American adolescents, can be a protective factor (Steinman & Zimmerman, 2004), which may be true for John if he identifies with this part of his racial identity as a biracial youth.


The next area of risk and protective factors in the ASURC model is childhood adversity. John witnessed domestic violence between his parents when he was younger, and as a result of attempting to intervene on behalf of his mother, John was hit by his father, a risk factor for adolescent substance use (Benjet et al., 2013). Fortunately, John’s mother sought counseling services for her son after the incident occurred. Early intervention can help offset the negative effects of these experiences (Durlak et al., 2011), and it is possible counseling provided John with healthy coping strategies.


According to the ASURC model, biological factors can impact adolescent substance use. John has a family history of substance use on both his maternal and paternal sides, and genes can play a role in the development of substance use disorders (Van Wormer & Davis, 2013). Further, adolescents experience an increase in risk-taking behaviors due to biological changes associated with adolescence (Telzer et al, 2013), and these changes may cause John to engage in increased risk-taking and pleasure-seeking behaviors.


Higher levels of academic engagement correlate with lower levels of substance use (Henry et al., 2012). John reported that he enjoys learning, suggesting he could have a high level of academic engagement. Nonetheless, John is currently earning Bs and Cs at school, pointing to a disconnection between his motivation to learn and his current grades. This disconnect could be due to associated cultural factors. John is biracial and living in a low socioeconomic neighborhood, and adolescents who live in such neighborhoods and are racial minorities can be at a disadvantage due to structural inequality (Henry et al., 2012).


Case Discussion

When taking all of the risk and protective factors into account, we placed John on the low end of moderate risk using the ASURC model. While John does have various risk factors contributing to his substance use, he also has protective factors that can help to buffer these factors. Further, John’s cultural identities impact him in various areas of the model. In particular, John’s biracial identity and living in a low socioeconomic neighborhood could be risk factors for substance use, while being involved in his church community is a protective factor. It would be important to explore with John how he views his race, SES, and religion, and if he sees them as protective or not. Further, it would be helpful to understand how John views his gender and sexual orientation, and how these identities affect his worldview.


Using the ASURC model to conceptualize John’s case can assist counselors with their interventions with John and his family. While using the model, a counselor is able to assist John and his family to identify current strengths such as positive family relationships, involvement in his church community, and potential for high academic engagement. Identifying these strengths allows John and his caregivers to concretize what is helpful in their situation and allows the counselor to encourage more of these behaviors as tools to strengthen weaker areas. For example, because there are strong family relationships, John’s mother and grandmother can increase their engagement with John when they are away from home via texts or phone calls. Increasing parental engagement will be beneficial for the family, particularly John’s mother and grandmother knowing who John is spending time with because his substance use is heavily influenced by his friendships on the football team. Similarly, because John likes to learn yet is not achieving high grades in school, tutoring programs can be sought to bolster his academic performance and solidify his academic engagement, as well as fill his time with positive activities that may decrease his desire to use. Additionally, it may be helpful to educate John and his caregivers about biological predispositions and risk factors in adolescence. This information can empower John to make positive choices when he understands both that he is not destined to develop an addiction and that he is experiencing normal physical changes. Additionally, it could prove helpful to talk with John and his family about how they might be experiencing structural inequality due to their race and SES. Engaging them in this conversation can normalize their experiences and serve to determine points where advocacy with and on behalf of the family may alleviate some of the strain they experience. Finally, because John’s risk level is on the low end of moderate, structured substance abuse treatment may not be warranted at this time. Interventions could include assessing John’s readiness to stop using and working through a change commitment while strengthening John’s protective factors in an effort to decrease his risk factors.


Future Research


Currently, the ASURC is a conceptual framework yet to be evaluated for efficacy with adolescent populations. Empirical research is needed to determine the model’s viability, validity and efficacy. Further, qualitative research would inform clinicians about the ways in which adolescents and their families felt stronger and more empowered by engaging in counseling practices that use this model’s approach.


Further research can be conducted to evaluate the degree of influence different components of the model have on adolescents with substance use concerns. Also, future research could investigate the relationship the model components have with one another, particularly the interplay of different cultural identities. Research is warranted to determine additional ways in which cultural factors can be used to strengthen clients and their families to mitigate deficit-based research and the pervasive negative cultural messages about non-dominant cultural groups and their struggles with substance use.




     The ASURC is a strengths-based approach focused on identifying protective and risk factors as counselors conceptualize adolescent substance use. While previous theories conceptualized adolescent substance use using strengths, they had limitations, including only discussing social influences in a general sense, use of problematic language, and lack of cultural influences. The ASURC builds upon the strengths of previous models while addressing their limitations. The ASURC model emphasizes the need for a strengths-based approach while working with adolescent populations and focuses on the importance of the consideration of cultural influences during the conceptualization process.


Finally, this model serves as a tool to help guide interventions that best serve adolescents and their families. Using the ASURC model for case conceptualization can help counselors determine the most salient factors of the model to the particular case, which will in turn assist in the treatment planning process. Future research is warranted to determine the viability of the ASURC model as an evidence-based practice.



Conflict of Interest and Funding Disclosure

The authors reported no conflict of interest

or funding contributions for the development

of this manuscript.





Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckmann (Eds.), Action-control: From cognition to behavior (pp. 11−39). New York, NY: Springer.

Akers, R. L. (1973). Deviant behavior: A social learning approach (2nd ed.). Belmont, CA: Wadsworth.

Allen, J. P., Chango, J., Szwedo, D., Schad, M., & Marston, E. (2012). Predictors of susceptibility to peer influence regarding substance use in adolescence. Child Development, 83, 337−350.

Barnes, D. M., & Meyer, I. H. (2012). Religious affiliation, internalized homophobia, and mental health in lesbians, gay men, and bisexuals. American Journal of Orthopsychiatry, 82, 505−515.

Benjet, C., Borges, G., Medina-Mora, M. E., & Méndez, E. (2013). Chronic childhood adversity and stages of substance use involvement in adolescents. Drug and Alcohol Dependence, 131, 85−91.

Brooks, F., & McHenry, B. (2009). A contemporary approach to substance abuse and addiction counseling: A counselor’s guide to application and understanding. Alexandria, VA: American Counseling Association.

Constantine, M. G. (1999). Labeling theory. In J. S. Mio, J. E. Trimble, P. Arredondo, H. E. Cheatham, & D. Sue (Eds.), Key words in multicultural interventions: A dictionary (pp. 169−170). Westport, CT: Greenwood Press.

Corrigan, M. J., Loneck, B., Videka, L., & Brown, M. C. (2007). Moving the risk and protective factor framework toward individualized assessment in adolescent substance abuse prevention. Journal of Child & Adolescent Substance Abuse, 16(3), 17−34. doi:10.1300/J029v16n03_02

Darling, N., Caldwell, L. L., & Smith, R. (2005). Participation in school-based extracurricular activities and adolescent adjustment. Journal of Leisure Research, 37, 51−76.

Demanet, J., & Van Houtte, M. (2012). School belonging and school misconduct: The differing role of teacher and peer attachment. Journal of Youth and Adolescence, 41, 499−514. doi:10.1007/s10964-011-9674-2

Denault, A.-S., Poulin, F., & Pedersen, S. (2009). Intensity of participation in organized youth activities during the high school years: Longitudinal associations with adjustment. Applied Developmental Science, 13(2), 74−87. doi:10.1080/10888690902801459

Duncan, L. (1999). Social norms. In J. S. Mio, J. E. Trimble, P. Arredondo, H. E. Cheatham, & D. Sue (Eds.), Key words in multicultural interventions: A dictionary (pp. 239−240). Westport, CT: Greenwood Press.

Durlak, J. A., Weissberg, R. P., Dymnicki, A. B., Taylor, R. D., & Schellinger, K. B. (2011). The impact of enhancing students’ social and emotional learning: A meta-analysis of school-based universal interventions. Child Development, 82, 405−432. doi:10.1111/j.1467-8624.2010.01564.x

Elliott, D. S., Huizinga, D., & Ageton, S. S. (1985). Explaining delinquency and drug use. Beverly Hills, CA: Sage.

Farb, A. F., & Matjasko, J. L. (2012). Recent advances in research on school-based extracurricular activities and adolescent development. Developmental Review, 32, 1−48. doi:10.1016/j.dr.2011.10.001

Hancock, T. U., Waites, C., & Kledaras, C. G. (2012). Facing structure inequality: Students’ orientation to oppression and practice with oppressed groups. Journal of Social Work Education, 48, 5−25.

Hawkins, J. D., & Weis, J. G. (1985). The social development model: An integrated approach to delinquency prevention. Journal of Primary Prevention, 6, 73−97. doi:10.1007/BF01325432

Hays, P. A. (1996). Addressing the complexities of culture and gender in counseling. Journal of Counseling & Development, 74, 332−338. doi:10.1002/j.1556-6676.1996.tb01876.x

Henry, K. L., Knight, K. E., & Thornberry, T. P. (2012). School disengagement as a predictor of dropout, delin-quency, and problem substance use during adolescence and early adulthood. Journal of Youth and Adolescence, 41(2), 156−166. doi:10.1007/s10964-011-9665-3

Hummel, A., Shelton, K. H., Heron, J., Moore, L., & van den Bree, M. (2013). A systematic review of the relation-ships between family functioning, pubertal timing and adolescent substance use. Addiction, 108, 487−496. doi:10.1111/add.12055

Johnson, A. G. (2006). Privilege, power, and difference (2nd ed.). New York, NY: McGraw-Hill.

Malmberg, M., Overbeek, G., Vermulst, A. A., Monshouwer, K., Vollebergh, W. A., & Engels, R. C. (2012). The

theory of planned behavior: Precursors of marijuana use in early adolescence? Drug and Alcohol Dependence, 123, 22−28. doi:10.1016/j.drugalcdep.2011.10.011

Mason, M. J., Schmidt, C., & Mennis, J. (2012). Dimensions of religiosity and access to religious social capital: Correlates with substance use among urban adolescents. The Journal of Primary Prevention, 33, 229−237. doi:10.1007/s10935-012-0283-y

Petraitis, J., Flay, B. R., & Miller, T. Q. (1995). Reviewing theories of adolescent substance use: Organizing pieces in the puzzle. Psychological Bulletin, 117, 67–86. doi:10.1037/0033-2909.117.1.67

Piko, B. F., & Kovács, E. (2010). Do parents and school matter? Protective factors for adolescent substance use. Addictive Behaviors, 35, 53−56. doi:10.1016/j.addbeh.2009.08.004

Pope, R. L. (1999). Deviance. In J. S. Mio, J. E. Trimble, P. Arredondo, H. E. Cheatham, & D. Sue (Eds.), Key words in multicultural interventions: A dictionary (pp. 92−93). Westport, CT: Greenwood Press.

Schroeder, R. D., & Ford, J. A. (2012). Prescription drug misuse: A test of three competing criminological theories. Journal of Drug Issues, 42, 4−27. doi:10.1177/0022042612436654

Substance Abuse and Mental Health Services Administration. (2012). Results from the 2011 national survey on drug use and health: Summary of national findings. NSDUH, H-44(12−4713). Rockville, MD: Author.

Steinman, K. J., & Zimmerman, M. A. (2004). Religious activity and risk behavior among African American adolescents: Concurrent and developmental effects. American Journal of Community Psychology, 33(3), 151−161. doi:10.1023/

Sue, D. W., & Sue, D. (2013). Counseling the culturally diverse: Theory and practice (6th ed.). New York, NY: John Wiley & Sons, Inc.

Telzer, E. H., Fuligni, A. J., Lieberman, M. D., & Galván, A. (2013). Meaningful family relationships: Neuro-cognitive buffers of adolescent risk taking. Journal of Cognitive Neuroscience, 25, 374−387.

Van Ryzin, M. J., Fosco, G. M., & Dishion, T. J. (2012). Family and peer predictors of substance use from early adolescence to early adulthood: An 11-year prospective analysis. Addictive Behaviors, 37, 1314−1324. doi:10.1016/j.addbeh.2012.06.020

Van Wormer, K., & Davis, D. R. (2013). Addiction treatment: A strengths perspective (3rd ed.). Belmont, CA:




Alexis Miller, NCC, is a professional counselor for the Dual Diagnosis Partial Hospitalization Program at Rogers Memorial Hospital in Madison, WI. Jennifer M. Cook, NCC, is an Assistant Professor at Marquette University. Correspondence can be addressed to Rogers Memorial Hospital, Attn: Alexis Miller, 406 Science Dr., Suite 110, Madison, WI 53711,


An Exploration of the Perceived Impact of Post-Master’s Experience on Doctoral Study in Counselor Education and Supervision

Laura Boyd Farmer, Corrine R. Sackett, Jesse J. Lile, Nancy Bodenhorn, Nadine Hartig, Jasmine Graham, Michelle Ghoston

Using quantitative and qualitative analysis, the perceived impact of post-master’s experience (PME) during counselor education and supervision (CES) doctoral study was examined across five core areas of professional identity development: counseling, supervision, teaching, research and scholarship, and leadership and advocacy. The results showed positive perceptions of the impact of PME in four of the five core areas, with significant relationships between the amount of PME and perceived impact on supervision and leadership and advocacy. Implications inform CES doctoral admissions committees as well as faculty who advise master’s students interested in pursuing a doctoral degree in CES.


Keywords: counselor education and supervision, doctoral study, post-master’s experience, doctoral admissions, professional identity


The master’s degree in counseling serves as the entry-level degree in the field, and students entering a doctoral program in counselor education and supervision (CES) are believed to have already met the standards of an entry-level clinician (Goodrich, Shin, & Smith, 2011). Therefore, the doctoral degree in CES is to prepare counselors for leadership in the profession within a variety of roles including supervision, teaching, research and scholarship, and leadership and advocacy, as well as counseling practice (Bernard, 2006; Council for Accreditation of Counseling and Related Educational Programs [CACREP], 2015; Goodrich et al., 2011; Sackett et al., 2015). Though CACREP (2015) recognizes previous professional experience as one of the doctoral program admission criteria, the counselor education field lacks clear professional standards regarding the amount and type of counseling experience necessary for admittance to doctoral programs (Boes, Ullery, Millner, & Cobia, 1999; Sackett et al., 2015; Schweiger, Henderson, McCaskill, Clawson, & Collins, 2012; Warnke, Bethany, & Hedstrom, 1999). Conventional wisdom may tell us the more post-master’s counseling experience a doctoral applicant has, the more enriched their doctoral experience will be; however, the CES field does not have empirical data for how CES doctoral students perceive the impact of their post-master’s experience (PME) on their doctoral education. Therefore, the purpose of the study was to explore the perceived impact of PME on doctoral study in CES.


In this study, researchers explored the perceived impact of PME across the five core areas of doctoral professional identity development outlined by CACREP (2015; Section 6. B.1-5). The following research questions guided the study: (1) How do advanced doctoral students and recent doctoral graduates perceive the impact of PME on the development of the five core areas of professional identity during doctoral study: counseling, supervision, teaching, research and scholarship, and leadership and advocacy? and (2) Is the amount of PME and the setting of PME related to the perceived impact of PME on the five core areas of professional identity during doctoral study: counseling, supervision, teaching, research and scholarship, and leadership and advocacy? Practically, the results inform CES doctoral admissions committees in considering applicants with and without PME. CES doctoral admissions committees must decide whether and how much PME should be required for admittance to their programs. PME is an important consideration in selecting doctoral students, yet few applicants have this experience (Nelson, Canada, & Lancaster, 2003), making it difficult to require. The results also inform CES faculty who advise master’s students interested in pursuing a doctoral degree. CES faculty members frequently encounter ambitious master’s students who are interested in pursuing a doctoral degree, and one of the many considerations in that conversation is whether and how much PME should be obtained before doctoral study begins. Though PME is deemed important, many CES faculty members advise master’s students to go straight into doctoral study based on factors such as maturity, academics and skill level (Sackett et al., 2015). This is an issue for the field since experience is an important qualification in hiring CES faculty members (Bodenhorn et al., 2014; Rogers, Gill-Wigal, Harrigan, & Abbey-Hines, 1998) and clinical experience informs teaching (Rogers et al., 1998; Sackett et al., 2015), supervision (Sackett et al., 2015), and research (Munson, 1996; Sackett et al., 2015). Thus, exploring further the impact of PME on doctoral students’ development is critical.


Relevant CES Literature on Post-Master’s Experience


     The field of CES lacks clarity regarding the amount or type of counseling experience preferable for incoming doctoral students (Sackett et al., 2015; Schweiger et al., 2012; Warnke et al., 1999). Recently, Swank and Smith-Adcock (2014) found that most CES doctoral programs in their study recommended, rather than required, one to two years of clinical experience for admission, while some suggested licensure for admission. Similarly, Nelson et al. (2003) found that counseling experience was a necessary component to doctoral admissions, though program representatives relayed the difficulty in requiring PME since so few applicants have experience. Twenty of the 25 CACREP-accredited programs in their sample rated successful work experience as a criterion for admission to their doctoral programs. Sixteen of those reported that work experience is always or often helpful in selecting strong doctoral students. CES doctoral programs deem experience is important in admissions, yet CES faculty members often advise master’s students to go immediately into doctoral programs (Sackett et al., 2015). Thus, there will likely continue to be a shortage of experienced doctoral applicants for doctoral admissions committees to choose from. As such, it is critical to explore the impact of PME on the areas of CES study to inform advisors at the master’s level how to advise their students on gaining PME prior to pursuing doctoral work.


Sackett et al. (2015) conducted a recent study to explore how CES faculty are advising master’s-level students interested in doctoral work regarding the amount of PME to obtain beforehand. CES faculty expressed the significant influence of clinical practice on the areas of teaching, research and supervision. Respondents identified the importance of clinical experience in providing for stimulation in research and in establishing credibility in teaching and supervision. Though there was much support for PME in the qualitative findings from this study, many respondents emphasized individual circumstances in evaluating readiness for doctoral work in CES, such as age, maturity, academics and skill level. For other respondents, the experience gained through master’s and doctoral training was enough, especially in cases where students were working in clinical capacities while completing their doctoral degrees. Thus, there is some indication in CES that PME is an important consideration in doctoral student admissions (Nelson et al., 2003; Swank & Smith-Adcock, 2014) and some indication that CES faculty members perceive the importance of PME in the areas of teaching, supervision and research (Sackett et al., 2015). The current study adds to the literature by exploring CES doctoral students’ perceptions of PME on their experiences in doctoral study.


Other Helping Professions’ Literature on PME

Related disciplines are concerned with the question of PME as well. In marriage and family therapy, students with clinical experience have been rated as better clinicians by faculty than those who did not have clinical experience (Piercy et al., 1995). Proctor (1996) and Munson (1996) wrote about opposing viewpoints on whether social work doctoral programs should admit students with limited to no post-master’s in social work (MSW) experience. Proctor’s stance was that requiring post-MSW experience for admission to doctoral programs in social work was a detriment to the field, as it meant the discipline might miss out on students who are research-minded and eager to continue with their education. On the other hand, Munson argued that post-MSW experience is essential for graduates of social work doctoral programs to fulfill the needs of the field, which include building knowledge, conducting practice research and effectively teaching social work practice. In clinical psychology, O’Leary-Sargeant (1996) found academic criteria to be most important in doctoral student admissions, while clinical competence also was important. It appears that determining PME’s place in the priority list for doctoral admissions and its impact on doctoral work is a concern for related disciplines as well.


As there are no clear guidelines for considering PME in doctoral student admissions (Sackett et al., 2015; Schweiger et al., 2012), and empirical studies exploring the doctorate in counselor education are scarce (Goodrich et al., 2011), with none specifically exploring the perceived impact of PME on doctoral students’ experiences, researchers set out to add to the literature in this area. Both doctoral admissions committees and faculty members advising master’s students who wish to pursue doctoral study encounter the dilemma of if and how much PME experience is important to gain prior to pursuing doctoral work. Given this, the purpose of this study was to explore the perceived impact of PME on the five core areas of doctoral professional identity: counseling, supervision, teaching, research and scholarship, and leadership and advocacy.




     To investigate the perceived impact of PME on doctoral study, quantitative and qualitative methods were utilized for their complementarity (Johnson, Onwuegbuzie, & Turner, 2007). The study was guided by the research questions: (1) How do advanced doctoral students and recent doctoral graduates perceive the impact of PME on the development of the five core areas of professional identity during doctoral study: counseling, supervision, teaching, research and scholarship, and leadership and advocacy? and (2) Is the amount of PME and the setting of PME related to the perceived impact of PME on the five core areas of professional identity during doctoral study: counseling, supervision, teaching, research and scholarship, and leadership and advocacy? Institutional Review Board approval was acquired prior to data collection. The researchers asked participants to rate the perceived impact of their PME or lack of PME using an 11-point Likert scale (-5 to +5; strong negative impact to strong positive impact), and analyzed themes using participants’ responses to open-ended questions for the five core areas of doctoral professional identity.



Fifty-nine advanced doctoral students or recent graduates completed an online questionnaire. To define participants’ status to degree completion, all fell into one of three groups: recent doctoral graduates (completed a CES doctoral degree within the last three years), ABD doctoral students (all but dissertation; completed all coursework and were working on dissertation studies), and advanced doctoral students (two years into completing coursework). Among participants, 13 (22%) were recent doctoral graduates, 32 (54%) were ABD doctoral students, and 13 (22%) were advanced doctoral students. One participant did not answer this question.


Participants were asked to indicate the type of setting and experience that best described their PME, checking all items that applied. There were 10 options provided and an option for “other” that included a comment box. Forty-nine percent (n = 29) indicated PME in community-based agencies, 31% (n = 18) worked in K–12 school settings, 20% (n = 12) worked in private practice, and 7% (n = 4) worked in inpatient settings. Four participants indicated post-master’s work in more than one setting. Additionally, 37% (n = 22) indicated that their PME provided experiences working with diverse populations, 31% (n = 18) gained experience working with families, and 24% (n = 14) gained experience working with clients who had substance use issues. Less than 10% of participants indicated other counseling settings and experiences such as play therapy, bilingual counseling, day treatment and in-home counseling.


The 59 participants indicated a range of time spent in PME from zero years up to 19 years before entering doctoral study. Thirty-four percent (n = 20) indicated between zero and one year of experience, 25% (n = 15) between one and three years of experience, 19% (n = 11) between three and five years of experience, 17% (n = 10) between five and 10 years of experience, and 5% (n = 3) indicated more than 10 years of PME prior to entering doctoral study.



Survey links were distributed through two national electronic list-servs, CESNET (the Counselor Education and Supervision NETwork) and COUNSGRAD (for graduate students in counselor education). The study invitation was sent to the listservs on two separate occasions approximately one month apart. Simultaneously, the study invitation was sent to regional Association for Counselor Education and Supervision leaders requesting that it be distributed to their membership lists. Additionally, CACREP liaisons were asked to send the survey link and invitation to their doctoral students. The survey was delivered through SurveyMonkey, a commonly used software product with a secure feature that was used for this research. The following research question was identified to potential participants: How do doctoral students and recent doctoral graduates reflect on how their post-master’s counseling experience or lack of experience impacted their experiences as a doctoral student? A response rate could not be calculated, as it is not possible to identify how many potentially appropriate participants received the research request.


PME Questionnaire

The authors collaborated on identifying questions that would serve to answer the research questions, focusing on five core areas of doctoral professional identity: counseling, supervision, teaching, research and scholarship, and leadership and advocacy. Two questions were asked about each of the five areas. “To what extent do you believe your post-master’s experience impacted your ability to develop [area] skills in your doctoral program?” used an 11-point Likert scale with the end points being (-5) strong negative impact and (+5) strong positive impact. Following the scaling question, an open-ended follow-up question was asked: “Please comment on how your experience impacted your [area] skills, and whether more or less experience would be beneficial.” Basic demographic questions were included regarding the type of experience gained prior to doctoral study, length of doctoral study and year of graduation. A pilot survey was sent to six people: two recent doctoral graduates, two ABD doctoral students, and two advanced doctoral students completing coursework. Feedback was provided on clarity and time involved.


Data Analysis

Quantitative analyses included correlation and multiple linear regression to examine the relationship between the amount of PME obtained and the perceived impact on the five core areas of doctoral study. The research team hypothesized that the amount of PME would predict a positive relationship with the perceived impact on some core areas of doctoral study, although which core areas would be statistically significant were unknown. Therefore, this study represents an exploration of the relationships between previously unexamined variables in the literature.


An independent samples t-test examined the relationship between PME setting (clinical mental health or school) and the perceived impact of PME on the five core areas.  For this analysis, several setting options (community-based agencies, private practice and inpatient hospitals) were combined into one setting labeled “clinical mental health,” which was compared to K–12 school settings (labeled “school”). The research team hypothesized that there would be no statistically significant differences between PME setting and any of the five core areas of doctoral study. There are no prior studies that examine these variables.


For the qualitative analysis, the first, third and fourth authors served as the data analysis team. The data analysis team analyzed responses to the open-ended questions using a constant comparative method described by Anfara, Brown, and Mangione (2002). Additionally, the team used a form of check coding described by Miles and Huberman (1994). The team members independently completed a first iteration of data analysis by assigning open codes for each of the five open-ended questions by reading responses to each item broadly and observing regularities (Anfara et al., 2002). The team members completed a second iteration of analysis, which included comparison within and between codes to establish categories and identify emergent themes. The constant comparative method provided a systematic way to analyze large amounts of data by organizing it into manageable parts first, and then identifying themes and patterns.


For the final step of analysis, the data analysis team rotated through a process of peer review as recommended by Miles and Huberman (1994). For each open-ended question, two team members were assigned as coders and one was assigned the role of peer reviewer. Once the team members arrived at individually derived themes, the team met together to discuss the findings and arrive at consensus for naming themes. During this meeting, the peer reviewer led the discussion by probing and seeking clarification on the original comment wording, thus helping the team to reach consensus for the themes. Consensus was reached when the three team members came to agreement on the final themes. The data analysis team sent the original data and final themes for each of the five core areas to the remaining four authors, who served as additional peer reviewers by examining the analysis.




Quantitative and qualitative analyses were conducted in this study of the perceived impact of PME on the five core areas of doctoral development for advanced doctoral students completing coursework, ABD doctoral students, and recent doctoral graduates. The results are presented in the following sections, with discussion to follow.


Quantitative Results: Correlation, Multiple Regression and Independent Samples T-test

Correlational analysis was used to explore the relationships among all variables: amount of PME obtained (years), and the perceived impact of PME on counseling, supervision, teaching, research and scholarship, and leadership and advocacy. A correlational matrix presents the relationships among the variables in Table 1. Among significant relationships, the amount of PME was related to perceived impact on development in supervision (r(57) = .43, p < .01) and leadership and advocacy (r(57) = .39, p < .01).


Table 1


Correlation Matrix for Main Study Variables


Variables 2–6 represent the perceived impact of PME on the core area of doctoral identity development (counseling, teaching, supervision, research and scholarship, and leadership and advocacy)


Multiple linear regression was used to examine whether the amount of PME (independent variable) predicted the perceived impact of PME on each of the five core areas of doctoral development: counseling, supervision, teaching, research and scholarship, and leadership and advocacy (dependent variables). The results of the regression analysis indicated that amount of PME predicted 38% of variance in the perceived impact of PME (R2 = .38, F (6, 47) = 4.80, p < .01). The amount of PME significantly predicted the perceived impact of PME on two variables: supervision (β = .44, p < .01) and leadership and advocacy (β = .34, p < .05). A post hoc power analysis was conducted utilizing G*Power. With an alpha level of .01, a sample size of 59, and a medium effect size of .61 (Cohen, 1992), achieved power for the multiple linear regression was .98.


Finally, an independent samples t-test was conducted to compare the perceived impact of PME in school PME and clinical mental health PME settings. Results showed a significant difference between school PME (M = 4.43, SD = 1.02) and clinical mental health PME (M = 3.10, SD = 1.89) for the core area of leadership and advocacy (t(51) = -3.26, p = .02), reflecting that doctoral students with PME in schools perceived a significantly higher positive impact of their PME on the development of leadership and advocacy compared to doctoral students with PME in clinical mental health settings.  In other words, both PME settings (school and clinical mental health) perceived a positive impact of their PME on the development of leadership and advocacy. However, doctoral students who had PME as school counselors perceived this experience as having a significantly greater impact on their development in leadership and advocacy than doctoral students who had obtained PME in clinical mental health settings.


The remaining four core areas of doctoral development were not significantly different when comparing PME settings. With an alpha level of .05, a sample size of 59, and a medium effect size of .88 (Cohen, 1992), achieved power for the independent samples t-test was .83.


Qualitative and Descriptive Results: Scaled and Open-Ended Responses

The following results describe respondents’ perceptions about the impact of PME on five core areas of doctoral development: counseling, supervision, teaching, research and scholarship, and leadership and advocacy (CACREP, 2015). Data was gathered for each core area using an 11-point Likert scale (-5 to +5) and was collapsed into five categories for ease of discussion. The categories were: (a) strong positive impact, +4 and +5; (b) weak to moderate positive impact, +1 through +3; (c) no impact, 0; (d) weak to moderate negative impact, -1 through -3; and (e) strong negative impact, -4 and -5. Table 2 reflects the percentage of responses in each core area. Table 3 provides a summary of qualitative themes. In the sections that follow, percentage results are summarized first, followed by a discussion of the qualitative themes within each core area of doctoral development.


Table 2


Descriptive Statistics: Perceived Impact of PME on Core Areas of Doctoral Professional Identity



     Core Area of Doctoral Development: Counseling. A majority of participants (60%) responded that PME had a strong positive impact on their ability to develop counseling skills in their doctoral program. Another 29.3% indicated a weak to moderate positive impact. Five themes emerged from the written responses describing the perceived impact of PME on the development of counseling skills.


     Theme 1: Increased confidence. Developing confidence in one’s counseling skills was frequently discussed as a benefit of having PME prior to doctoral study. Having confidence in the counseling skills already established through practice allowed for even more clinical growth during doctoral study. Many respondents stated they had greater confidence than their peers who lacked PME. Confidence also was viewed as advantageous when being asked to try a new clinical skill or technique: “I was more familiar with multiple clinical skills and my level of comfort when trying new clinical skills was higher than those who did not have the same clinical experience.”


     Theme 2: Integration of theory into practice. Participants described the perceived impact of PME as being useful for helping to integrate theory into practice during doctoral study. While learning theories and reading about concepts establishes a foundation for counseling skills, participants reported that PME provided the context needed to test theoretical understanding in practice. Others commented that having some PME and then returning to the classroom for doctoral study gave them a greater understanding and appetite for theory. Theory was learned more thoroughly with a contextual base of experience upon which to build, as one respondent described:


My experience impacted my counseling skills; however, my experience alone did not help me conceptualize theory. I learned theory much more thoroughly post-master’s (once in doctoral studies) and then was able to identify how I had been using it all along as well as to incorporate new knowledge.


Table 3


Perceived Impact of PME: Qualitative Themes by Core Area of Doctoral Development

     Theme 3: Conceptualizing cases. Case conceptualization was identified as a benefit of having PME. Participants described having greater clinical understanding and ability to apply knowledge as an advantage of PME. Others commented that having a context with which to build upon existing skills was useful and contributed to more complex conceptualizations of clients and problems.


     Theme 4: Honing counseling techniques. Participants reported that their PME refined the counseling techniques they had gained in master’s study, enabling them to expand their repertoire and focus on honing advanced techniques during their doctoral work. One participant expressed feeling greater “comfort when trying new clinical skills” during doctoral study while another stated they were “able to focus on refining higher level skills” in their doctoral program.


     Theme 5: The unique experience of school counselors. There was a notable theme regarding the distinct difference in school counselors’ experience when considering the impact of PME on counseling skill development. Some school counselors commented that they did not regularly use counseling skills while working in schools due to the variety of other responsibilities placed on school counselors. Another respondent stated that clinical supervision was crucial to developing clinical competence and that they did not receive clinical supervision while working as a school counselor. For those doctoral students with PME as school counselors, they expressed they would have benefitted by having more experience in several areas, such as use of the Diagnostic and Statistical Manual of Mental Disorders, dual-diagnosis, and substance use treatment. Some school counselors described using only specific theories in their setting (e.g., reality therapy, cognitive behavioral therapy), and that practicing with a broad range of techniques would have been useful prior to doctoral study.


     Core Area of Doctoral Development: Supervision. The largest group of participants (48.3%) responded that PME had a strong positive impact on their ability to develop supervision skills in their doctoral program. Another group of participants (31%) rated PME as having a weak to moderate positive impact on their supervision skills. Five themes emerged from the written responses describing how PME impacted the development of supervision skills.


     Theme 1: Increased confidence as a doctoral supervisor. Participants reported greater confidence while developing supervision skills as a result of having PME. In general, doctoral students in training are asked to enter into a supervisory relationship with master’s students in training in order to develop supervision skills. Having counseling experience as a professional in the field assisted doctoral students to feel more confident in this new role, as one respondent commented, “I was able to supervise students in my former position, but also I feel the years of experience have given me insight that I can be confident in the information I pass on.”

Alternately, doctoral students who do not have PME are asked to step into the same supervisory role, but may feel inadequately prepared to be in a position of hierarchy and expertise. Most doctoral students who have not had PME have recently graduated from their master’s program; therefore, the difference between the supervisor and supervisee in terms of experience is small. A participant spoke to this struggle: “Naturally clinical supervision and counseling are related. Because of this, it would have helped to have a more solid grasp on my own counseling skills and for me to have personal experiences to draw upon when supervising.”


     Theme 2: Formative experiences in supervision. Through obtaining PME, participants reflected on their initial experiences of receiving supervision as a necessary backdrop for learning how to provide supervision. Whether those initial experiences in supervision were described as positive or negative, participants stated that they learned a great deal about becoming a supervisor through the process of receiving supervision. Initial supervision experiences also were described as either “clinical” in nature or “administrative.” Regardless of the type of supervision received, the experience was regarded as helpful in preparing them for doctoral study to advance their skills as a supervisor.


There were some participants who reported being provided with supervision during their PME and others reported that they lacked supervision. In both instances, participants acknowledged that they valued supervision as a result of their PME. Among those lacking quality supervision, one respondent stated, “My [post-master’s] supervision was mostly administrative and as a result I was at a disadvantage coming into a clinical supervisory environment.” On the other side, one participant described their master’s and doctoral program as providing “lousy supervision” and not regularly attending scheduled supervision meetings. Both experiences capture the sentiment: inadequate supervision, as a graduate student or professional, influences one’s expectations of what defines effective supervision.


     A final benefit of PME described by participants was the ability to understand the supervisee’s experience. Having experienced the position of being a supervisee first-hand enabled a greater understanding of supervisees’ struggles and real-world challenges that are faced when providing counseling. One respondent expressed, “I understood the situations the students were facing since I had recently faced them with my clients (e.g., transportation, childcare, resistance).” Some participants reflected on the experience of building rapport with a supervisor, and how influential this was in their development. Due to these experiences in the field, the importance of strengthening the supervisory relationship and establishing a safe place in the supervision environment were considered paramount. Overall, participants reported that having experience as a supervisee enabled them to realize and appreciate critical aspects of providing effective supervision.


     Theme 3: Providing resources to supervisees. Participants reported that having PME, which often included supervision, enabled them to provide better resources to supervisees as doctoral students. Some of these resources included community resources, referral options, counseling stories, therapeutic tools and techniques, varied perspectives, and a more diverse conceptualization of clients and issues. Here, a respondent illustrates this theme:


[I believe] it is super important to have . . . clinical experience when supervising students in a doctoral program. You have to be able to understand the student’s experience, have experience with many different client populations and modalities, be able to conceptualize client problems, and give students tools to advance their skills.


     Theme 4: Credibility with supervisees. Greater credibility as a supervisor was regarded as an important benefit of having PME. Through the eyes of their supervisee, having more PME was perceived as helpful to establish credibility. This theme included two aspects: the doctoral supervisor having something valuable to offer in supervision, and the supervisee reporting greater confidence in a supervisor who had professional counseling experience. In this quote, a respondent describes feelings of credibility as a supervisor based on their PME: “I am able to understand the intricacies of a school system, thus I can help my students think of problem-solving strategies to work with their students and supervisors.”


     Core Area of Doctoral Development: Teaching. The largest group of participants (38.9%) responded that PME had a strong positive impact on their ability to develop teaching skills in their doctoral program. Another group of participants (33.4%) rated PME as having a weak to moderate positive impact on their teaching skills. A smaller group of participants (22.2%) responded that PME had no impact at all on the development of teaching skills. Four themes emerged from the written responses describing how PME impacted the development of teaching skills.


     Theme 1: Confidence in teaching. Having more confidence was frequently cited as a benefit to having PME and developing teaching skills during doctoral study. Some participants stated that many aspects of counseling involve teaching to a degree; therefore, having PME strengthened the ability to teach in the classroom. On the other side, there were some participants who regretted not having more PME directly related to teaching. One participant wrote, “I wish I had more experience teaching, managing a classroom, developing innovative and attention catching ideas. I know it’s more me than anything else so I need to develop my style more.”

     Theme 2: Providing examples in the classroom. Perhaps the theme with the most support from participants was the perceived benefit of PME in their ability to provide examples while teaching. Those with PME had plenty of practical examples from their experience to draw from, which helped them a great deal while teaching. One participant wrote, “I was able to use examples drawn from my clinical experience to bring certain topics to life. I was also better able to describe some clinical issues and to teach certain skills.” Several participants wrote that they received positive feedback from students about the value of their stories and examples to enhance learning. Some also stated that they felt better prepared to conduct a live role-play in class to bring a technique to life because they had benefitted from PME. One respondent illustrated this idea well: “It’s difficult to teach something you have no experience with. There were others in my cohort who had no real clinical experience prior to starting their doctoral program and they were much less effective as teachers.”


     Theme 3: Developing a new skill. Some participants responded that teaching was an entirely new skill that was unrelated to their PME. For these participants, teaching was a skill that was solely developed during doctoral study, as this respondent wrote: “Teaching was not a part of my post-master’s work. This was an entirely new set of skills I learned in doctoral study. Neither more nor less experience would have made a difference for me in this area.”


     Theme 4: Value of prior teaching experiences. The fourth theme captures the positive impact described by those participants whose PME included teaching experiences prior to pursuing their doctoral degree. In particular, those with school counseling experience described preparing and implementing classroom guidance lessons as a natural comparison to teaching. Some participants had PME that involved providing training and giving presentations, which was also associated with teaching. For these participants, their specific PME had a positive impact on their development as a teacher during doctoral study, as this respondent reported: “Having an education background and then opportunity in my school to perform classroom guidance lessons, while different, still gave me an important opportunity to practice developing lesson plans.”

     Core Area of Doctoral Development: Research and Scholarship. The largest group of participants (46.3%) responded that PME had no impact on their ability to develop research and scholarship skills in their doctoral program. Smaller groups of participants reported a range of weak to moderate to strong positive impact on their research and scholarship development. This was the only area of doctoral development that most participants described as being unrelated to PME. Three themes emerged from the written responses describing how PME impacted the development of research and scholarship.


     Theme 1: No impact on research development. Most participants stated that their ability to develop research skills during their doctoral program was unrelated to having PME in the field. For these participants, research was regarded as an advanced skill unique to doctoral study. Many participants expressed that research and scholarship was not essential in their post-master’s positions, as is relayed in this quote: “Research is one area where [PME] is not as vital.”


     Theme 2: Basic research experiences were useful. A few participants responded that obtaining some basic research experience was useful during the time between master’s and doctoral study. In general, it is necessary for counselors in the field to conduct basic searches for knowledge to support their practice. These searches may take the form of using the Internet to find resources for clients or reviewing text-books or articles when using a particular technique or theory. School counselors discussed their use of online research for building school guidance programs. In addition, some counselors gained basic research skills in their PME through collecting and analyzing data regarding the provision of services or client outcomes. One participant described her experience with a research study:


I worked in a clinical trial of CBT, CBT + medication, and medication only. This exposure really helped me get an idea of what research is possible in mental health . . . so it had a large impact on me. I pursued my doctorate largely because I wanted to engage in research and scholarship.


     Theme 3: Contributed to area of research focus. Participants credited their PME as informing their ability to examine relevant topics for research. Some stated that their PME inspired their area of research focus. One participant noted that by working with specific populations, such as a specific ethnic minority population, “discrepancies and gaps in service” were found and helped the participant think about questions to pursue through research.


     Core Area of Doctoral Development: Leadership and Advocacy. A majority of participants (58.2%) responded that PME had a strong positive impact on their ability to develop leadership and advocacy skills in their doctoral program. Another group of participants (23.7%) rated PME as having a weak to moderate positive impact on their leadership and advocacy skills. Five themes emerged from the written responses describing how PME was perceived to impact the development of leadership and advocacy skills.


     Theme 1: Sense of responsibility to the profession. Participants described a heightened sense of responsibility to provide leadership and advocacy in the counseling field based on their PME. Some acknowledged a feeling of, “This is my job now,” related to the assumption of responsibility as a doctoral student in CES. Assuming greater responsibility was the most common theme discussed by participants, emerging in various forms.

Many participants described a sense of being propelled into leadership and advocacy through their PME. One school counselor wrote, “My job forced me to fight for myself, my students, teachers and parents. It was the best experience because I had to do it, or my job would be ineffective and possibly in jeopardy.” Another participant wrote:

Due to the nature of my job, I was doing a significant amount of advocacy. . . . Many of the kids on my caseload had multiple challenges, such as racial minority status, lack of citizenship, poverty, and/or domestic violence, and it was part of my responsibility to help them address the challenges they faced in all aspects of their lives in order to improve their mental health and functioning in school and at home.

Overall, participants described their PME as the most formative training for developing leadership and advocacy skills. PME provided a sense of purpose and meaning to advocacy and leadership in the counseling profession.

     Theme 2: Awareness of advocacy needs within diverse client populations. Participants responded that a greater awareness of the needs of diverse populations, particularly minority populations, was a result and benefit of their PME. Through working with underrepresented populations, they had a greater appreciation for the need to develop leadership and advocacy skills. One participant also described having a “deeper understanding of the difficulties faced by certain populations within our society,” which laid the groundwork for developing leadership and advocacy skills in the doctoral program. Once involved in a doctoral program, advocacy felt like a way to “join forces with people who care” to address inequities and help marginalized groups. In this way, having exposure to different cultural groups through their PME provided the context for understanding and developing advocacy action strategies.

     Theme 3: Motivation and direction for leadership and advocacy. Participants described that the motivation and direction for their leadership and advocacy work was inspired by the sense of responsibility and the awareness of needs that originated in their PME. In this way, PME helped to pave the way for the focus of their subsequent leadership and advocacy work. Regarding leadership, participants reflected that direct counseling work “consumed them” once in the profession and, as a result, professional development became something that you fit in when you could. Once they re-entered into graduate work as a doctoral student, they valued leadership and professional involvement and could give these aspects of development a more passionate focus. In a way, not having much time for professional development and leadership roles while directly serving clients provided motivation for becoming involved as a doctoral student.

Participants also reported that the presentations they submit to conferences are motivated by the needs they became aware of during their PME. Many credited their PME for helping them develop awareness of the future needs counselors were going to face, which motivated their advocacy for improved counselor training.

     Theme 4: Development of leadership and advocacy skills on-the-job. Many participants described the need to develop leadership and advocacy skills on-the-job during their PME, and how valuable this was to their doctoral work. Participants experienced first-hand the lack of funding and resources in the community and school settings, which forced them to act in creative ways to get clients’ and students’ needs met. In addition, some described working in a position with multiple roles or serving multiple school campuses, which forced them to learn how to initiate programs independently, balance multiple roles, communicate with a variety of stakeholders, and thus develop leadership skills. Advocacy also was essential to develop on-the-job, as described by this participant:

I worked as a bilingual counselor, the only one at my clinic, working with a specific population for a period of time. I had to do a lot of leadership and advocacy work at the clinic to help my supervisors and colleagues understand this specific population and the resources that were available in the community specifically for this population.

     Theme 5: Confidence to speak up. Again, confidence emerged as a theme with regard to developing leadership and advocacy skills during doctoral study. Having PME gave participants the necessary confidence to speak up in classes, in meetings and at conferences. Many reported that they became much more confident about voicing concerns and advocating due to their first-hand knowledge of issues facing counselors in the field, as did this respondent:


I think my post-master’s skills made me more confident about speaking up in meetings and conferences and it enhanced my advocacy skills because I knew what the issues facing clinicians were. It didn’t always make me popular or well understood among counselor educators with little clinical experience, however.


For these respondents, having greater confidence to use one’s voice seemed a natural result of having some years of experience with “boots on the ground” and becoming acclimated to the real-world experience of working as a counselor.




The results from this study help fill a gap identified in the literature regarding clarity in the counselor education field on the amount of counseling experience preferable for incoming doctoral students (Sackett et al., 2015; Schweiger et al., 2012; Warnke et al., 1999). Results of this study indicate that doctoral students and recent doctoral graduates of counselor education programs perceived a positive impact of their PME on doctoral study. The positive impact of PME was described across all five core areas of doctoral development as defined by CACREP (2015; Section 6. B.1-5), yet was particularly strong regarding counseling, supervision, teaching, and leadership and advocacy. Quantitative analysis confirmed a significant predictive relationship between the amount of PME obtained and the perceived impact on development of supervision and leadership and advocacy as doctoral students. While some participants perceived that their PME had a positive impact on the development of research and scholarship, this impact was far less pronounced than in other core areas, and many expressed that their PME had no impact on development in the area of research and scholarship. These findings align with and extend upon previous findings (Sackett et al., 2015) that CES faculty members believe PME informs the supervision, teaching and research of CES doctoral students.


Previous research has noted the strenuous nature of entering CES doctoral studies, with such a transition being marked by fluctuations in both emotion and confidence (Dollarhide, Gibson, & Moss, 2013; Hughes & Kleist, 2005). This transition involves the expansion of professional roles to include that of a counselor, student, educator, supervisor, and researcher and scholar (Dollarhide et al., 2013; Lambie & Vaccaro, 2011; Limberg et al., 2013; West, Bubenzer, Brooks, & Hackney, 1995). A notable theme in the current study was the confidence that participants experienced and attributed to PME. With the tendency for new doctoral students to experience self-doubt in these multiple roles, the confidence gained through PME may help to mobilize internal resources, moving them forward in the developmental process as a CES doctoral student.


Considering all themes that emerged in this study of CES doctoral students and recent graduates, there is strong support for the value of experiential learning that is gained through PME. According to Kolb’s theory of experiential learning, concrete lived experiences provide the basis for reflection; then, from these reflections new information can be assimilated and abstract concepts can be formed (Kolb, 1984). Participants in this study described a common benefit of PME: having a base of experiences as a professional counselor to reflect upon during doctoral study. The process of reflecting on lived experiences as a counselor supports crystallization of knowledge in a doctoral program where additional theories, skills, techniques, and advanced facets of professional identity are developed.


Even though the majority of participants described a positive perceived impact of PME toward doctoral development, there were some who did not perceive as much benefit. This finding is reminiscent of Sackett et al.’s (2015) finding that some CES faculty members reported the counseling experience gained through the master’s and doctoral programs alone is enough and that success in a doctoral program is more reliant on the characteristics of each student. It is possible that learning styles may best predict whether and which master’s students benefit from PME prior to doctoral study. Kolb’s experiential learning theory (1984) stated that individuals have a preference among four modes of the learning cycle: concrete experience, reflective observation, abstract conceptualization and active experimentation. Considering Kolb’s four learning styles, it is possible that those participants who have a preference for abstract conceptualization rely less on lived experiences as a counselor to understand and apply concepts; thus, doctoral students with this preferred learning style might successfully develop in the five core areas of doctoral identity without perceiving any benefits from PME. Future research is needed to examine this hypothesis.


Research and scholarship was the only core area of doctoral professional identity that PME was perceived to have no impact on for a large group of participants (46.3%). This finding may be worth considering for CES faculty who advise master’s students interested in pursuing a doctoral degree. Depending on the master’s student’s career goal, obtaining PME may be less of a priority if aiming for a research faculty position, where teaching and supervision would not be a requirement.


Significance of Supervision, Leadership and Advocacy

A unique finding in this study was the positive, predictive relationship between the amount of PME obtained and the perceived impact on developing one’s identity in the areas of supervision and leadership and advocacy. Specifically, doctoral students who had more years of PME perceived a greater impact on their development in the areas of supervision and leadership and advocacy. For supervision, doctoral students who have not obtained any PME would be stepping into a new role where they are expected to provide teaching, consultation, and support for the skill development of counselors-in-training (Bernard & Goodyear, 2014). Having little to no time between being in the master’s student role of receiving supervision and to the role of providing supervision may present significant challenges. Alternatively, a “master” clinician does not automatically become a “master” supervisor; specialized knowledge and skills are required to develop supervision competency (Bernard & Goodyear, 2014). While obtaining some PME is perceived to significantly impact supervision development, the amount of PME may not be the only factor that influences supervision competence.


Open-ended comments shed further light on the perceived impact of PME and developing leadership and advocacy. Participants commented that through their lived experiences in schools and agencies, PME provided doctoral students with a sense of urgency about the needs of clients and the profession, thus motivating their advocacy work. Participants also acknowledged PME as valuable fodder for understanding their potential as leaders. Through the context of experience as a counselor, participants were better able to understand their ability to impact the profession through leadership and advocacy work as a counselor, supervisor and counselor educator.


Relevance of PME Setting

This study explored whether the setting of PME, school or clinical mental health, was related to the perceived impact of that experience on the five areas of doctoral identity development. The only significant difference in the setting where PME was obtained was in the areas of leadership and advocacy development. Those with school counseling experience perceived a greater impact of PME on leadership and advocacy development. For participants in this study, spending time working in a school system was essential to establishing a sense of oneself as a leader and advocate in school counseling.




While some evidence exists that PME is an important consideration in CES doctoral student admissions (Nelson et al., 2003; Swank & Smith-Adcock, 2014), the current study provides evidence of the perceived impact of PME in professional development as a CES doctoral student, especially in the areas of counseling, supervision, teaching, and leadership and advocacy. Quantitative analysis revealed a significant relationship between the amount of PME and perceived development in supervision and leadership and advocacy. Doctoral admissions committees may consider these findings as they weigh the pros and cons of applicants applying for doctoral study who have differing amounts of PME. Additionally, CES faculty advising master’s students whose ultimate goal is to pursue a doctoral degree may consider these findings as they offer guidance and support to students in the decision-making process.


Across the five core areas of doctoral professional identity development, PME was frequently perceived to boost confidence during doctoral study. However, there were some participants who reported a lack of confidence in the core areas of teaching and research, despite having PME. It would seem that teaching and research represent novel aspects of doctoral identity development, as both skill sets are not always involved in PME as a professional counselor. Research and scholarship is a primary focus of doctoral course content. In fact, the CACREP 2016 standards require CES doctoral students to become proficient in both qualitative and quantitative methodology (CACREP, 2015; Section 6 B.4.), which usually requires the completion of three or more research courses. With regard to teaching, many doctoral students are an integral part of counselor education programs, with roles as co-instructors, teaching assistants and guest lecturers. Yet, development of proficient teaching skills may extend beyond these co-teaching experiences during doctoral study, where vicarious learning and role modeling are heavily relied upon. As some participants in this study described, teaching is likely to be a new area of identity to develop; yet most (72.3%) reported that having years of PME aided their development as a teacher because they had real counseling experience to draw from and ample clinical examples to contextualize course content. Therefore, doctoral admissions committees should strongly consider the value of PME for doctoral applicants as a basis for development as a teacher.


In the current study, a wide variety of PME was represented (from 0–19 years), yet a question remains: How much experience is optimal to obtain? The current study only examined doctoral students’ perceptions. Within one theme in the current study, participants speculated about reaching a point of “diminishing returns,” in which too much time away from an academic setting (attaining PME) could result in a depletion of academic skills. However, two to three years of PME would typically allow CES applicants the opportunity to gain a counseling license, streamlining the career opportunities available to them upon graduation. Sackett at al. (2015) found that many CES faculty members advise master’s students to gain enough experience to earn licensure prior to pursuing doctoral study. For CES graduates who choose to continue practicing counseling in the field, provide supervision, or serve in administrative positions, state licensure is necessary. For CES graduates pursuing a faculty position, Bodenhorn et al. (2014) found that a majority of faculty postings sought applicants with licensure or two to three years of counseling experience. For either post-doctoral trajectory, obtaining at least two to three years of PME may be most beneficial.


Future Research

This study provided an initial exploration of the perceived impact of PME on core areas of identity development as a doctoral student, while privileging the perspective of those doctoral students. Future studies are needed to examine the relationship between post-master’s counseling experience, development during doctoral study, and professional impact as a counselor educator and supervisor. Specifically, studies should explore professional outcomes of counselor educators with varying levels of PME. For example, what are students’ perceptions of faculty members and supervisors with more or less counseling experience? How is the type of institution (high teaching versus high research) related to the amount and benefit of professional counseling experience? Is continued professional practice after earning the CES doctoral degree related to professional success, career satisfaction, teaching evaluations or scholarship productivity? Future research focusing on these issues will add to the literature on this aspect of the CES profession by answering these questions.


Conflict of Interest and Funding Disclosure

The authors reported no conflict of interest

or funding contributions for the development

of this manuscript.




Anfara, V. A., Jr., Brown, K. M., & Mangione, T. L. (2002). Qualitative analysis on stage: Making the research process more public. Educational Researcher, 31(7), 28–38.

Bernard, J. M. (2006). Tracing the development of clinical supervision. The Clinical Supervisor, 24, 3–21. doi:10.1300/J001v24n01_02

Bernard, J. M., & Goodyear, R. K. (2014). Fundamentals of clinical supervision (5th ed.). New York, NY: Pearson.

Bodenhorn, N., Hartig, N., Ghoston, M. R., Graham, J., Lile, J. J., Sackett, C. R., & Farmer, L. B. (2014). Counselor education faculty positions: Requirements and preferences in CESNET announcements 2005–2009. The Journal for Counselor Preparation and Supervision, 6. doi:10.7729/51.1087

Boes, S. R., Ullery, E. K., Millner, V. S., & Cobia, D. C. (1999). Meeting the challenges of completing a counseling

doctoral program. Journal of Humanistic Education & Development, 37(3), 130–144. doi:10.1002/j.2164-4683.1999.tb00415.x

Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155–159.

Council for Accreditation of Counseling and Related Educational Programs. (2015). 2016 CACREP Standards. Council for Accreditation of Counseling and Related Educational Programs. Retrieved from

Dollarhide, C. T., Gibson, D. M., & Moss, J. M. (2013). Professional identity development of counselor education doctoral students. Counselor Education and Supervision, 52, 137–150. doi:10.1002/j.1556-6978.2013.00034.x

Goodrich, K. M., Shin, R. Q., & Smith, L. C. (2011). The doctorate in counselor education. International Journal for the Advancement of Counselling, 33, 184–195. doi:10.1007/s10447-011-9123-7

Hughes, F. R., & Kleist, D. M. (2005). First-semester experiences of counselor education doctoral students. Counselor Education and Supervision, 45, 97–108. doi:10.1002/j.1556-6978.2005.tb00133.x

Johnson, R. B., Onwuegbuzie, A. J., & Turner, L. A. (2007). Toward a definition of mixed methods research. Journal of Mixed Methods Research, 1, 112–133.

Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice-Hall.

Lambie, G. W., & Vaccaro, N. (2011). Doctoral counselor education students’ levels of research self-efficacy, perceptions of the research training environment, and interest in research. Counselor Education and Supervision, 50, 243–258. doi:10.1002/j.1556-6978.2011.tb00122.x

Limberg, D., Bell, H., Super, J. T., Jacobson, L., Fox, J., DePue, M. K., . . . Lambie, G. W. (2013). Professional identity development of counselor education doctoral students: A qualitative investigation. The Professional Counselor, 3, 40–53.

Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook (2nd ed.). Thousand Oaks, CA: Sage.

Munson, C. E. (1996). Should doctoral programs graduate students with fewer than two years of post-MSW practice experience? No! Journal of Social Work Education, 32(2), 167–172.

Nelson, K. W., Canada, R. M., & Lancaster, L. B. (2003). An investigation of nonacademic admission criteria for doctoral-level counselor education and similar professional programs. The Journal of Humanistic Counseling, 42, 3–13.

O’Leary-Sargeant, J. L. (1996). A comparison of the relative ability of measures of interpersonal and academic intelligence in the prediction of clinical competence. Dissertation Abstracts International, 57(04), 2877B. (UMI No. AAG9627243)

Piercy, F. P., Dickey, M., Case, B., Sprenkle, D., Beer, J., Nelson, T., & McCollum, E. (1995). Admissions criteria as predictors of performance in a family therapy doctoral program. The American Journal of Family Therapy, 23, 251–259. doi:10.1080/01926189508251355

Proctor, E. K. (1996). Should doctoral programs graduate students with fewer than two years of post-MSW practice experience? Yes! Journal of Social Work Education, 32(2), 161–167.

Rogers, J. R., Gill-Wigal, J. A., Harrigan, M., & Abbey-Hines, J. (1998). Academic hiring policies and projections: A survey of CACREP- and APA-accredited counseling programs. Counselor Education and Supervision, 37(3), 166–178. doi:10.1002/j.1556-6978.1998.tb00542.x

Sackett, C. R., Hartig, N., Bodenhorn, N., Farmer, L. B., Ghoston, M., Graham, J., & Lile, J. (2015). Advising master’s students pursuing doctoral study: A survey of counselor educators and supervisors. The Professional Counselor, 5, 473–485. doi:10.15241/crs.5.4.473

Schweiger, W. K., Henderson, D. A., McCaskill, K., Clawson, T. W., & Collins, D. R. (2012). Counselor preparation: Programs, faculty, trends (13th ed.). New York, NY: Taylor and Francis.

Swank, J. M., & Smith-Adcock, S. (2014). Gatekeeping during admissions: A survey of counselor education programs. Counselor Education and Supervision, 53, 47–61. doi:10.1002/j.1556-6978.2014.00048.x

Warnke, M. A., Bethany, R. L., & Hedstrom, S. M. (1999). Advising doctoral students seeking counselor education faculty positions. Counselor Education and Supervision, 38, 177–190. doi:10.1002/j.1556-6978.1999.tb00569.x

West, J. D., Bubenzer, D. L., Brooks, D. K., Jr., & Hackney, H. (1995). The doctoral degree in counselor education
and supervision. Journal of Counseling & Development, 74, 174–176. doi:10.1002/j.1556-6676.1995.tb01846.x


Laura Boyd Farmer is an Assistant Professor at Virginia Tech. Corrine R. Sackett is an Assistant Professor at Clemson University. Jesse J. Lile is a couple’s counselor in Boone, NC. Nancy Bodenhorn is an Associate Professor at Virginia Tech. Nadine Hartig is an Associate Professor at Radford University. Jasmine Graham is a Clinical Assistant Professor at Indiana University Purdue University Indianapolis. Michelle Ghoston is an Assistant Professor at Gonzaga University. Correspondence can be addressed to Laura B. Farmer, School of Education (0302), 1750 Kraft Drive, Ste 2000, Blacksburg, VA 24061,


The Impact of Student Success Skills on Students’ Metacognitive Functioning in a Naturalistic School Setting

Brett Zyromski, Melissa Mariani, Boyoung Kim, Sangmin Lee, John Carey

This study evaluated the impact of the Student Success Skills (SSS) classroom curriculum delivered in a naturalistic setting on the metacognitive functioning of 2,725 middle and high school students in Kentucky. SSS was implemented as one intervention to fulfill an Elementary and Secondary School Counseling Grant. Results in students’ self-reports indicated that those who received the intervention demonstrated increased ability to regulate their levels of emotional arousal. No additional significant differences were found. These findings differ from the results of previous outcome studies involving SSS. Implications for implementing SSS in naturalistic school settings and directions for future research are discussed.

Keywords: Student Success Skills, naturalistic, metacognitive functioning, classroom curriculum, emotional arousal

The purpose of this study was to evaluate the impact of the Student Success Skills (SSS) school counseling curriculum (Brigman, Campbell, & Webb, 2004; Brigman & Webb, 2012) delivered in a naturalistic setting on students’ metacognitive functioning. In this case, the authors use the term naturalistic setting to describe a typical school environment, one which lacks the additional supports (e.g., hiring national trainers) that would be present in a more controlled research study. SSS is an evidence-based, school counselor-delivered, social-emotional learning intervention that is designed to support students by teaching them three integral skill sets: (a) cognitive and metacognitive skills (e.g., goal setting, progress monitoring and memory skills); (b) social skills (e.g., interpersonal skills, social problem solving, listening and teamwork skills); and (c) self-regulation skills (e.g., managing attention, motivation and anger). Research has identified this curriculum as important in promoting students’ academic achievement and success in school (Collaborative for Academic, Social, and Emotional Learning, 2015; Webb & Brigman, 2006).
SSS was designed based on reviews of educational psychology research literature that identified critical skills such as information processing, emotional self-management, and positive social skills needed for student success (Bransford, Brown, & Cocking, 1999; Durlak, Weissberg, Dymnicki, Taylor, & Schellinger, 2011; Greenberg et al., 2003; Hattie, Biggs, & Purdie, 1996; Marzano, Pickering, & Pollock, 2001; Masten & Coatsworth, 1998; Wang, Haertel, & Walberg, 1994; Zins, Weissberg, Wang, & Walberg, 2004). The curriculum (Brigman & Webb, 2012) can be delivered in two formats: (1) the SSS classroom program and (2) the SSS small group program (Brigman et al., 2004), both of which are intended for use with students in grades 4 through 12. SSS is a highly structured, manualized program that consists of weekly 45-minute lessons. The classroom format includes five lessons, while the small group program includes eight lessons. Both sets of weekly lessons are intended to be delivered in chronological order over the corresponding number of consecutive weeks. A 45-minute booster session is delivered once a month for 3 months in the spring.

Developers of SSS designed the curriculum to follow a scripted, manualized format; implementers are encouraged to follow the sequencing, format and language provided in order to ensure fidelity of treatment. If practitioners go “off-script” or change the recommended delivery of the lessons, it may result in less favorable outcomes that might not meet the same levels as have been found in past research. That being said, the SSS program comes with detailed manuals that include recommended verbiage, descriptive diagrams and supplemental handouts (Brigman & Webb, 2012). During each lesson, students learn and practice strategies in five distinct areas: (a) goal setting, progress monitoring and success sharing; (b) creating a caring, supportive and encouraging classroom environment;
(c) cognitive and memory skills; (d) calming skills; and (e) building healthy optimism. Specific strategies are taught and practiced each week and are reviewed and reinforced during subsequent lessons. Between lessons, students are encouraged to apply the new strategies that were taught and to work on the academic and personal goals that they set for themselves during the SSS session. Teachers also are expected to cue students to use the strategies during regular classroom lesson time.


Research has established the effectiveness of SSS in several quasi-experimental and experimental studies. SSS implementation has resulted in enhanced academic achievement as measured by standardized achievement tests (Brigman & Campbell, 2003; Brigman, Webb, & Campbell, 2007; C. Campbell & Brigman, 2005; Webb, Brigman, & Campbell, 2005) and district math and reading achievement measures (Lemberger, Selig, Bowers, & Rogers, 2015). Two studies have suggested that the effects of SSS on academic achievement are at least partially mediated by changes in students’ metacognitive functioning (Lemberger & Clemens, 2012; Lemberger et al., 2015). Lemberger and Clemens (2012) found that participation in SSS small groups was associated with improvements in students’ executive functions (as measured by the Behavior Rating Inventory of Executive Function [BRIEF]; Gioia, Isquith, Guy, & Kenworthy, 2000) and increased metacognitive activity (as measured by the Junior Metacognitive Awareness Inventory [Jr. MAI]; Sperling, Howard, Miller, & Murphy, 2002). Lemberger et al. (2015) found that participation in the classroom version of SSS was associated with improvement in executive functions (as measured by the BRIEF-SR; Guy, Isquith, & Gioia, 2004).


While researchers have established the efficacy of SSS in well-controlled research environments, little is known about its effectiveness when delivered in naturalistic settings. The purpose of the present study was to measure the effectiveness of the SSS curriculum when delivered in a naturalistic setting within regularly functioning schools. In this study, SSS was implemented in five schools in a district in Kentucky as part of a school counseling improvement project funded by an Elementary and Secondary School Counseling Demonstration Grant awarded by the U.S. Department of Education. The five middle and high schools collaborated together through a regional educational cooperative to apply for the grant. Demographic information for each school can be found in the Setting section below. The grant funded all necessary SSS curriculum materials and provided support for school counselors in evaluating the impact of the program. However, funding was not available to hire national trainers. National trainers are not a requirement when purchasing a manualized school intervention and many schools do not possess the funds needed to hire national trainers. Thus, this funded project provided an opportunity to evaluate the effectiveness of SSS in a naturalistic school setting.


The primary evaluation question was: When implemented in a naturalistic setting, does SSS impact students’ metacognitive functioning, as determined by (1) knowledge and regulation of cognition as measured by the Junior Metacognitive Awareness Inventory (Jr. MAI; Sperling et al., 2002) and (2) use of skills related to self-direction of learning, support of classmates’ learning, and self-regulation of arousal as measured by the Student Engagement in School Success Skills survey (SESSS; Carey, Brigman, Webb, Villares, & Harrington, 2013)? The secondary question was: Does the magnitude of any changes in metacognitive functioning depend on the degree to which SSS was implemented with fidelity?




Five participating schools were chosen due to their participation in the Elementary and Secondary School Counseling grant. Specific population and demographic data related to all five schools can be found in Table 1.


Table 1


Brief Description of the Five Schools in the Study


School Enrollment& Grades Served Location Ethnicity Rates Gender Rates Socio-Economic Indicators
School 1 1,484 StudentsGrades 9–12 Suburban/Rural African American-0.8%American Indian-0%Asian American-1.2%

European American-95.8%

Hispanic American-0.9%

Two or More Races-1.2%


Female-50.2%Male-49.8% Qualifying for Free
Lunch-28%Qualifying for Reduced Lunch-7.6%
School 2 1,154 StudentsGrades 6–8 Suburban/Rural African American-1.1%American Indian-0.1%Asian American-0.7%

European American-94.1%

Hispanic American-2%

Two or More Races-2%


Female-49%Male-51% Qualifying for Free Lunch-33.5%Qualifying for Reduced Lunch-7.8%
School 3 325 StudentsGrades 7–12 Urban African American-2.8%American Indian-0%Asian American-0.6%

European American-95.1%

Hispanic American-1.2%

Two or More Races-0.3%


Female-54.5%Male-45.5% Qualifying for Free Lunch-68.6%Qualifying for Reduced Lunch-8.6%
School 4 570 StudentsGrades 6–8 Rural African American-1.4%American Indian-0%Asian American-0.2%

European American-97.5%

Hispanic American-0.5%

Two or More Races-0.4%


Female-48.4%Male-51.6% Qualifying for Free Lunch-50.5%Qualifying for Reduced Lunch-7.9%
School 5 471 StudentsGrades 6–8 Urban African American-11.5%American Indian-0.4%Asian American-0.4%

European American-69%

Hispanic American-10%

Two or More Races-7.9%


Female-45.2%Male-54.8% Qualifying for Free Lunch-62.2%Qualifying for Reduced Lunch-6.4%

Note: The demographic categories are listed as reported by the state reporting system.



A total of 2,725 students participated in the study with roughly equal numbers of male (50.1%) and female (49.9%) students. A relatively large percentage of participants (41.2%) qualified for free or reduced lunch. Less than 1% of participants were classified as Limited English Proficient and 11.2% qualified for special education services. In terms of racial and ethnic diversity, the participants were less diverse than desired. Eighty-five percent of participating students identified as White (non-Hispanic), 4% as Multiracial, 6% as African American, and 4% as Hispanic. All other groups combined accounted for the remaining 1% of participants. Proportionally more sixth-, seventh-, and eighth-grade students participated in the study. The percentages of participants by grade were: 20.5% sixth grade; 20.9% seventh grade; 20% eighth grade; 10.7% ninth grade; 9.9% tenth grade; 9.2% eleventh grade; and 8.7% twelfth grade.


Completed Jr. MAI surveys (pretest and posttest) were obtained from 1,565 students (57% of the total). Completed SESSS surveys were obtained from 1,612 students (59% of the total). School counselors were required by the grant to serve as point persons for the delivery and collection of pre- and post-instruments. School counselors also were trained on instrument collection using a structured, scripted protocol. Instruments were administrated in paper format. Although trained in data collection procedures, not all participating school counselors successfully captured both pre- and post-assessments. Issues around successfully collecting paper instruments contributed to the loss of data. For example, 4% of the Jr. MAI surveys were incomplete and 4% of the SESSS surveys were incomplete. Rather than estimating missing data in these instances, it was determined that only data from fully complete instruments would be used in the analyses.


Preparation of the School Counselors

An SSS manual was provided to each of the schools the year prior to implementation of the program. School counselors reviewed the SSS materials and met with the grant project manager to discuss the content and instructional processes associated with the SSS classroom guidance interventions. Again, school counselors within the five schools did not receive formal training from the national SSS trainers on how to implement the curriculum. Formal training was a cost not included in the grant. The lack of formal training reflected the more naturalistic approach to the study. More often than not, school counselors that purchase a manualized program do not have the funding to hire national trainers to guide implementation. School counselors review the manual and follow the manualized program during implementation. This approach was reflected in this study. School counselors at each school used the SSS curriculum manuals and did their best to adhere to the recommended lesson sequence and scripts (Brigman & Webb, 2012). Next, the school counselors at each school conducted a pilot SSS small group in the spring semester, prior to the onset of the whole-school SSS implementation. The intent of the pilot implementation was to ensure that the school counselors were thoroughly familiar with the materials and implementation procedures. After conducting the pilot studies, the school counselors provided 3 hours of SSS training to partner teachers prior to implementation of the whole-school SSS intervention. The teachers in all schools also received a copy of the SSS classroom manual (Brigman & Webb, 2012) to review prior to implementing the curriculum with their students. Delivery of the SSS classroom format began the subsequent fall semester (2013) and concluded the following spring (2014).



Procedures for Delivering SSS and Fidelity Issues

In every school, the school counselors experienced some problems implementing the SSS curriculum with fidelity. Implementing the program with complete fidelity would have reflected the exact scope and sequence scripted within the SSS manual, mainly delivering the program over a 45-minute time period once a week for 5 consecutive weeks. Schools varied from this scope and sequence, resulting in a lack of fidelity of the recommended implementation format for SSS. However, schools adjusted delivery of SSS in a way that reflected their educational priorities, again reflecting a more naturalistic approach than a traditional controlled research study. The primary resistance school counselors encountered related to teachers’ and administrators’ reluctance to lose instructional time as a consequence of in-class implementation of SSS. Each school identified a contextually appropriate approach to addressing this initial resistance to devoting class time to SSS. In two of the schools, teachers (rather than counselors) delivered the SSS curriculum within their own classrooms. In the other three schools, the SSS curriculum was delivered through learning communities (i.e., advisories), which are existing scheduled blocks of time during which teachers facilitate small groups (8–15 students) outside their normal classrooms. For example, a ninth-grade biology teacher might be responsible for leading a group of students across several grades with whom the teacher does not interact outside of this learning community. The manner in which SSS was delivered in each school is detailed below.


School One. The SSS curriculum was not delivered with complete fidelity. Instead, the school leadership determined it was more feasible for teachers to deliver the curriculum through learning communities, once a week for 30 minutes for 10 weeks.


School Two. The SSS curriculum was delivered with reasonable fidelity once a week for 60 minutes over a 5-week period by teachers. However, instead of being delivered in a traditional classroom format, the school leadership determined it more feasible to deliver the curriculum through learning communities.


School Three. SSS was delivered with reasonable fidelity. Five teachers (trained and supervised by the school counselor) delivered the SSS curriculum in the prescribed format detailed in the SSS classroom manual. The five teachers delivered SSS to all students in the school through various courses, including a study skills course (seventh and eighth grades), a social studies course (ninth grade), a biology course (tenth grade), a college readiness course (eleventh grade) and an English course (twelfth grade).


School Four. The SSS curriculum was delivered with reasonable fidelity to all grade levels (sixth through eighth) during social studies courses. The social studies teachers were trained and supervised by the school counselor to deliver the program.


     School Five. The SSS curriculum was not delivered with complete fidelity. The school leadership determined it more feasible to deliver the curriculum through learning communities two to three times a week for 25 minutes for each session over a 5-week period.


Procedures for Collecting SESSS and Jr. MAI Data

Pretest data were collected at the beginning of the 2013 school year and posttest data were collected in late April and early May of the 2013–2014 school year, before the end-of-grade standardized testing ensued. Prior to beginning the project, school counselors completed a Collaborative Institutional Training Initiative to alert them to issues relating to voluntary participation and confidentiality. School counselors were then trained to follow an instrument administration manual (developed for the project) so that they could administer the SESSS and the Jr. MAI in a standardized fashion. They administered the SESSS and the Jr. MAI using standardized, scripted procedures. In order to protect the confidentiality of the students, school counselors changed the student identification numbers for each student by adding a randomly determined number for each school. No other person besides the school counselor knew the number by which the student identification numbers were changed. All data were kept in a locked file cabinet in the primary investigator’s office. Data were entered into a database, which was saved on an encrypted, password-protected hard drive. As an additional safeguard, the data from each school were saved on an external hard drive and transported by hand to the primary investigator’s office.




Junior Metacognitive Awareness Inventory (Jr. MAI)

The present study used the 18-item version of the Junior Metacognitive Awareness Inventory (Jr. MAI; Sperling et al., 2002), a self-report scale that has two subscales that measure students’ knowledge of cognition and regulation of cognition. The Jr. MAI is used to screen learners for potential metacognitive and cognitive strategy interventions. Sperling et al. (2002) developed two versions of the Jr. MAI based on the Metacognitive Awareness Inventory (Schraw & Dennison, 1994). The 12-item version was developed for students in grades 3 through 5, while the 18-item version was developed for older students.


Available evidence suggests that the Jr. MAI and its subscales are reliable. Sperling et al. (2002) reported an internal consistency-based reliability estimate of .82 for the overall scale. Sperling, Richmond, Ramsay, and Klapp (2012) reported an internal consistency reliability of .76 for the knowledge of cognition subscale and .80 for the regulation of cognition subscale. Sperling et al. (2002) found that the Jr. MAI total score (for both versions of the instruments) correlated with other direct measures of student metacognition, but not with teachers’ ratings of students’ metacognitive abilities. Relatedly, Sperling et al. (2012) found the student scores on the 18-item version of the Jr. MAI correlated significantly with their scores on the Swanson Metacognitive Questionnaire (SMQ; Swanson, 1990), their science grade point average and their overall grade point average.  Recently, the 12-item version of the Jr. MAI was used to measure the impact of SSS on students’ metacognitive functioning. Lemberger and Clemens (2012) found that SSS delivered in small group format to fourth- and fifth-grade students resulted in measurable increases in Jr. MAI scores.


Student Engagement in School Success Skills (SESSS) Survey

The study also employed the Student Engagement in School Success Skills (SESSS) survey. The SESSS (Carey et al., 2013) is a 27-item scale that was developed to measure the extent to which students use strategies that have been shown to be related to enhanced academic achievement (Hattie et al., 1996; Masten & Coatsworth, 1998; Wang et al., 1994). The SESSS has three subscales that measure students’ self-direction of learning, support of classmates’ learning and self-regulation of arousal.


Carey et al. (2013) found in an exploratory factor analysis of the SESSS scores of 402 fourth through sixth graders that a four-factor solution provided the best model of scale dimensionality considering both the solution’s clean factor structure and the interpretability of these factors. However, in a confirmatory factor analysis study (Brigman et al., 2014) using SESSS scores from a diverse sample of almost 4,000 fifth-grade students, researchers found that while a four-factor model fit the data well, the scales associated with two subscales correlated so highly (r = .90) as to be indistinguishable. Consequently, the items associated with the two factors were combined and the subsequent three-factor model also proved to better fit the data.


Brigman et al. (2014) suggested that the SESSS is best thought of as having three underlying factors corresponding to self-direction of learning, support of classmates’ learning, and self-regulation of arousal. Based on factor loadings, Brigman et al. (2014) created three SESSS subscales. The self-direction of learning subscale (19 items) reflects the students’ intentional use of cognitive and metacognitive strategies to promote their own learning. The support of classmates’ learning subscale (six items) reflects the students’ intentional use of strategies to help classmates learn effectively. Finally, the self-regulation of arousal subscale (three items) reflects students’ intentional use of strategies to control disabling anxiety and cope with stress.


Available data indicate that the SESSS is a reliable assessment tool. Carey et al. (2014) reported an overall alpha coefficient of 0.91. Furthermore, Villares et al. (2014) reported that the coefficient alphas for the three SESSS subscales (self-direction of learning, support of classmates’ learning and self-regulation of arousal) were .89, .79 and .68, respectively.


Data Analysis

In order to answer the current study’s research questions, the authors conducted separate multivariate analysis of variance (MANOVA) with a repeated measure (pretest-posttest time) for the Jr. MAI and the SESSS. In the Jr. MAI, the two subscales (knowledge of cognition and regulation of cognition) were the dependent variables. For the SESSS MANOVA, the three subscales (self-direction of learning, support of classmates’ learning, self-regulation of arousal) were the dependent variables.


After performing the MANOVAs, follow-up repeated measures of analysis of variance (ANOVA) were conducted, where appropriate, to determine the significance of the pretest-posttest changes for individual subscales. Effect sizes (Cohen, 1988) also were calculated to determine the magnitude of pretest-posttest change in subscale associated with the intervention. For significant subscale changes, effect sizes were compared across schools to ascertain whether the level of fidelity of SSS implementation was related to the intervention’s size of effect.




MANOVA analyses with a repeated measure (pretest-posttest) were performed to determine the differences between Jr. MAI and SESSS subtests across the pretest-posttest time periods in order to answer the primary evaluation question. The primary question was: When implemented in a naturalistic setting, does SSS impact students’ metacognitive functioning, as determined by (1) knowledge and regulation of cognition as measured by the Jr. MAI (Sperling et al., 2002) and (2) use of skills related to self-direction of learning, support of classmates’ learning and self-regulation of arousal as measured by the SESSS (Carey et al., 2013)? The results of these MANOVAs are shown in Table 2. For the Jr. MAI, the repeated measures MANOVA revealed a significant difference (F (1, 1562) = 3267.47, p < .00l) between the two subscales (knowledge of cognition and regulation of cognition). However, no significant difference existed between the pretest and posttest time points. The interaction effect of main effects, subscale and time was not significant.


Table 2


Repeated Measure MANOVA:  Effects of SSS on Students’ Metacognitive Activity


Dependent Measures                          Jr. MAI                        SESSS
Main effects




Interaction effect
Subtest * Time



Note. ***p<.001


     In contrast, SESSS repeated measures MANOVA revealed both a significant main effect of Subscale (F (2, 1610) = 356.24, p < .00l) and a significant interaction effect of Subscale x Time (F (2, 1610) = 28.25, p < .00l). Figure 1 shows that the self-regulation of arousal subscale (subscale 3) corresponded to a significantly greater mean change across time, compared to the self-direction of learning (subscale 1) and the support of classmates’ learning (subscale 2) subscales.


Figure 1. Pre-Post SSS Treatment Changes in Metacognitive Functioning and Success Skill Use: Means for Jr. MAI and SESSS subtests at Pretest (Time 1) and Posttest (Time 2).


Jr. MAI                                                                     SESSS



For Jr. MAI Subtest 1 = Knowledge of Cognition and Subtest 2 = Regulation of Cognition

For SESSS Subtest 1 = Self-Direction of Learning, Subtest 2 = Support of Classmates’ Learning,
and Subtest 3 = Self-Regulation of Arousal


Based on these MANOVA results, authors conducted follow-up repeated measures ANOVAs in order to test the significance of pretest-posttest changes for all three SESSS subscales. Only the SESSS self-regulation of arousal subscale indicated a significant change (F (1, 1610) = 46.147, p < .001) over time, reflecting a self-reported increase in students’ abilities to regulate their levels of potentially debilitating arousal after SSS participation. As shown in Table 3, the effect size of the self-regulation of arousal subscale (Cohen’s d = -.18) pretest-posttest change would be classified as small (Cohen, 1988).



Table 3


Effect Sizes of ANOVAs with Repeated Measures (T1 and T2) for Jr. MAI and SESSS




Cohen’s d






Knowledge of Cognition






Regulation of Cognition






The Self-Direction of Learning






The Support of Classmates’ Learning






The Self-Regulation of Arousal







     The secondary research question was: Does the magnitude of any changes in metacognitive functioning depend on the degree to which SSS was implemented with fidelity? Implementation fidelity was not strongly related to SSS effect size. Cohen’s d effect sizes (Cohen, 1988) were computed for each school to assess the impact of SSS on self-regulation of arousal. Schools 2, 3 and 4 (who had reasonable fidelity of implementation) had effect sizes of .20, .17 and .26 respectively. Schools 1 and 5 (who had the greatest deviation from implementation fidelity) reported effect sizes of .30 and .13, respectively. Therefore, the schools in this study showed considerable variability in effect sizes (.13 to .30). School differences across other factors (e.g., experience levels of SSS leaders, grade levels of students) may have contributed to this variability.


In summary, although significant findings were not found for pre- and posttests related to the Jr. MAI, significant findings were found for the SESSS subscale self-regulation of arousal (p < .001), indicating that students increased their ability to regulate levels of potentially debilitating arousal after participating in the SSS intervention. Examination of Cohen’s d effect sizes suggested that implementation fidelity, or the amount that schools varied from the scope and sequence laid out in the SSS manuals, did not correlate to level of effect size. This result suggests that the SSS intervention resulted in positive outcomes even when practitioners modified the scope and sequence to fit the needs of their setting.




Evaluation Question 1. Does SSS delivered in a naturalistic setting impact students’ metacognitive functioning? The results of the present study suggest that when implemented in a naturalistic setting, SSS can be expected to result in statistically significant increases in students’ abilities to regulate potentially debilitating emotional arousal. These enhanced abilities might reasonably be expected to result in benefits related to improved academic performance (Durlak et al., 2011) and better school behavior (perhaps helping students increase their self-control related to daily interpersonal conflict and stressful events; Galla & Wood, 2015). The overall effect of SSS on emotional self-regulation, while statistically significant, was comparatively small. The present study failed to find evidence that SSS influenced other aspects of students’ metacognitive functioning, including their knowledge of cognition, regulation of cognition, use of strategies related to the self-direction of learning, or use of strategies to support fellow classmates’ learning.


     Evaluation Question 2. Does the magnitude of any changes in metacognitive functioning depend on the degree to which SSS was implemented with fidelity? While the schools in this study showed considerable variability in effect sizes, implementation fidelity was not strongly related to SSS effect size. For example, School 1 scored lowest on implementation fidelity, but demonstrated the greatest effect size (.30). The degree of departure from fidelity was not large enough to detract from SSS’s effect on students’ self-regulation of arousal.


Relationship to Previous SSS Findings

The present study failed to replicate the results of previous studies that found significant effects of SSS on students’ metacognition (Lemberger & Clemens, 2012; Lemberger et al., 2015). While the present study as well as Lemberger and Clemens’ study (2012) both used the Jr. MAI to measure changes in students’ metacognition, the two studies differed in terms of SSS delivery format (classroom vs. small group). The failure to replicate Jr. MAI-measured changes after SSS participation may be related to differences in the format (classroom vs. group) for SSS delivery, or to differences in the delivery context (naturalistic vs. controlled).


While this study and the Lemberger et al. (2015) study both delivered the SSS classroom format, these studies differed in the instruments they used to measure students’ metacognitive functioning (the SESSS and Jr. MAI vs. the BRIEF). Differences in results may be related to differences in instrumentation or to differences in the delivery context (naturalistic vs. controlled).



     A limitation of this study is the use of a one-group pre-post design rather than a quasi-experimental design with a control group. Study researchers were constrained by the practical realities of the school environment, such that it was not feasible to implement SSS in such a way as to result in a comparison group. In addition, researchers were unable to locate similar schools that were willing to have students participate in a comparison group. Since it is not always feasible to employ a control group design, a one-group pre-post design may be used to attempt to replicate the findings of stronger research studies and can point to findings that need to be investigated later using stronger evaluation designs (D. T. Campbell & Stanley, 1963; Shadish, Cook & Campbell, 2001).  The present evaluation, in fact, furthers the understanding of the effects of SSS and highlights directions for future research.


The failure to collect data in some schools resulted in losses of both the Jr. MAI and the SESSS data. Corresponding complete pretest and posttest surveys were obtained from only 57% and 59% of participating students, respectively. While the lack of strong control over data collection can be thought of as an inherent problem in natural setting evaluations, care should be taken in future studies to strengthen data collection processes, as it is difficult to speculate on the impact of the loss of data in this study. Loss of data in smaller studies could be extremely harmful to the validity of the study. In the present study, there was no reason to believe that the loss of data was related to students’ reactivity to the intervention; however, it is possible that this loss impacted the results, and additional studies are needed to address this issue.


Implications for Future Research

It is important to understand the extent and nature of SSS’s impact on students’ metacognitive functioning, whether SSS’s well-established impact on academic performance (Brigman & Campbell, 2003; Brigman, Webb, & Campbell, 2007; C. Campbell & Brigman, 2005; Lemberger et al., 2015; Webb et al., 2005) is mediated by changes in students’ metacognitive functioning or other variables, and whether the impact on academic performance is related to general improvements in all students or an improvement in the functions of specific groups of students. Larger-scale intervention studies are needed to understand relationships between SSS proximal changes in students’ abilities and functioning (e.g., metacognitive functioning, emotional self-regulation, engagement, self-efficacy and motivation) and distal changes in students’ academic performance. It is important to understand which proximal changes in students are mediating their distal improvements in academic performance. It could be that SSS’s effects on academic performance are mediated by one or several of these variables. It also could be that SSS’s effects on academic performance are mediated by relatively broad variables (e.g., self-efficacy) that would be expected to be evident in virtually all students or that are relatively specific (e.g., reductions in debilitating test anxiety) and would be expected to be evident in only some students.


Understanding the mediator(s) of SSS’s effects on academic performance would be useful in identifying the most appropriate target groups for this intervention. As such, future studies are needed to explore whether SSS is most appropriate as a Tier 1 intervention for all students or as a Tier 2 intervention for some groups of “at-risk” students. Given that the results of the present study suggested that SSS helped students who struggled with self-regulation of arousal, it is especially important to examine the effectiveness of SSS as a Tier 2 intervention, specifically for students who demonstrate difficulties with emotional self-regulation. Finally, further research is needed to determine the practical significance of SSS on academic performance when it is implemented in less controlled, more naturalistic settings, and to determine how deviations from implementation fidelity and other contextual factors (e.g., expertise of the SSS leaders) correspond to expected social-emotional and academic achievement-related outcomes.


Implications for Practice

The results of the present study indicated that SSS, even when implemented in a naturalistic school setting (as opposed to a highly controlled setting), can have a positive impact on students’ abilities to regulate their emotional arousal. The magnitude of the overall impact of SSS on students’ ability to regulate arousal appears to be relatively small. However, readers should note that this effect size was computed based on students in the general population, not students experiencing difficulties with emotional self-regulation. It is likely that SSS would have had a larger estimated effect size if the target group of participants was those who had emotional self-regulation difficulties. However, the SSS curriculum positively impacted student outcomes even when the program was not implemented as designed. Though practitioners are encouraged to follow the manual and schedule as recommended, the results are encouraging in that impacts can still be found even if practitioners modify the design.


Conflict of Interest and Funding Disclosure

The authors reported no conflict of interest

for the development of this manuscript.
This project was supported by an Elementary and
Secondary School Counseling Demonstration
Grant project from the Department of Education
no. S215E13422.






Bransford, J. D., Brown, A. L., & Cocking, R. R. (1999). How people learn: Brain, mind, experience, and school. Washington, DC: National Academy Press.

Brigman, G., & Campbell, C. (2003). Helping students improve academic achievement and school success behavior. Professional School Counseling, 7(2), 91–98.

Brigman, G., Campbell, C., & Webb, L. (2004). Student Success Skills: Group counseling manual. Boca Raton, FL: Atlantic Education Consultants.

Brigman, G., & Webb, L. (2012). Student success skills: Classroom manual (3rd ed.). Boca Raton, FL: Atlantic Education Consultants.

Brigman, G., Webb, L., & Campbell, C. (2007). Building skills for school success: Improving the academic and social competence of students. Professional School Counseling, 10, 279–288.

Brigman, G., Wells, C., Webb, L., Villares, E., Carey, J. C., & Harrington, K. (2014). Psychometric properties and confirmatory factor analysis of the student engagement in school success skills. Measurement and Evaluation in Counseling and Development. Advance online publication. doi:10.1177/0748175614544545

Campbell, C., & Brigman, G. (2005). Closing the achievement gap: A structured approach to group counseling. Journal for Specialists in Group Work, 30, 67–82.

Campbell, D. T., & Stanley, J. C. (1963). Experimental and quasi-experimental designs for research. Skokie, IL: Rand McNally.

Carey, J., Brigman, G., Webb, L., Villares, E., & Harrington, K. (2013). Development of an instrument to measure student use of academic success skills: An exploratory factor analysis. Measurement and Evaluation in Counseling and Development, 47, 171–180. doi:10.1177/0748175613505622

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Earlbaum Associates.

Collaborative for Academic, Social, and Emotional Learning. (2015). CASEL guide: Effective social and emotional learning programs. Middle and high school edition. Chicago, IL: Author. Retrieved from

Durlak, J. A., Weissberg, R. P., Dymnicki, A. B., Taylor, R. D., & Schellinger, K. B. (2011). The impact of enhancing students’ social and emotional learning: A meta-analysis of school-based universal interventions. Child Development, 82, 405–432. doi:10.1111/j.1467-8624.2010.01564.x

Galla, B. M., & Wood, J. J. (2015). Trait self-control predicts adolescents’ exposure and reactivity to daily stressful events. Journal of Personality, 83, 69–83.

Gioia, G. A., Isquith, P. K., Guy, S. C., & Kenworthy, L. (2000). Behavior rating inventory of executive function. Odessa, FL: Psychological Assessment Resources.

Greenberg, M. T., Weissberg, R. P., O’Brien, M. U., Zins, J. E., Fredericks, L., Resnik, H., & Elias, M. J. (2003). Enhancing school-based prevention and youth development through coordinated social, emotional, and academic learning. American Psychologist, 58, 466–474. doi:10.1037/0003-066X.58.6-7.466

Guy, S. C., Isquith, P. K., & Gioia, G. A. (2004). Behavior Rating Inventory of Executive Function-Self-Report Version.  Odessa, FL: Psychological Assessment Resources.

Hattie, J., Biggs, J., & Purdie, N. (1996). Effects of learning skills interventions on student learning: A meta-analysis. Review of Educational Research, 66, 99–136. doi:10.3102/00346543066002099

Lemberger, M. E., & Clemens, E. (2012). Connectedness and self-regulation as constructs of the Student Success                         Skills program in inner-city African American elementary school students. Journal of Counseling &                                     Development, 90, 450–458.

Lemberger, M. E., Selig, J. P., Bowers, H., & Rogers, J. E. (2015). Effects of the Student Success Skills program on                         executive functioning skills, feelings of connectedness, and academic achievement in a predominantly                       Hispanic, low-income middle school            district. Journal of Counseling & Development, 93, 25–37.

Marzano, R. J., Pickering, D. J., & Pollock, J. E. (2001). Classroom instruction that works: Research-based strategies                         for increasing student achievement. Alexandria, VA: Association for Supervision and Curriculum                                     Development.

Masten, A. S., & Coatsworth, J. D. (1998). The development of competence in favorable and unfavorable environments: Lessons from research on successful children. American Psychologist, 53, 205–220.

Schraw, G., & Dennison, R. S. (1994). Assessing metacognitive awareness. Contemporary Educational Psychology, 19, 460–475.

Shadish, W., Cook, T., & Campbell, D. (2001). Experimental and quasi-experimental designs for generalized causal inference (2nd ed.). Boston, MA: Cengage.

Sperling, R. A., Howard, B. C., Miller, L. A., & Murphy, C. (2002). Measures of children’s knowledge and regulation of cognition. Contemporary Educational Psychology, 27, 51–79. doi:10.1006/ceps.2001.1091

Sperling, R. A., Richmond, A. S., Ramsay, C. M., & Klapp, M. (2012). The measurement and predictive ability of metacognition in middle school learners. The Journal of Educational Research, 105, 1–7.

Swanson, H. L. (1990). Influence of metacognition and aptitude on problem solving. Journal of Educational Psychology, 82, 306–314.

Villares, E., Colvin, K., Carey, J. C., Webb, L., Brigman, G., & Harrington, K. (2014). Convergent and divergent validity of the Student Engagement in School Success Skills survey. The Professional Counselor, 4, 541–552.

Wang, M. C., Haertel, G. D., & Walberg, H. J. (1994). What helps students learn? Educational Leadership, 51(4), 74–79.

Webb, L., & Brigman, G. (2006). Student success skills: Tools and strategies for improved academic and social outcomes. Professional School Counseling, 10, 112–120.

Webb, L., Brigman, G., & Campbell, C. (2005). Linking school counselors and student success: A replication of the Student Success Skills approach targeting the academic and social competence of students. Professional School Counseling, 8, 407–413.

Zins, J. E., Weissberg, R. P., Wang, M. C., & Walberg, H. J. (2004). Building academic success on social and emotional learning: What does the research say? New York, NY: Teachers College Press.




Brett Zyromski is an Assistant Professor at The Ohio State University. Melissa Mariani is an Assistant Professor at Florida Atlantic University. Boyoung Kim is a Research Professor at Korea University. Sangmin Lee is an Associate Professor at Korea University. John Carey is a Professor at the University of Massachusetts Amherst. This project was supported by an Elementary and Secondary School Counseling Demonstration Grant project from the Department of Education, no. S215E13422. Correspondence can be addressed to Brett Zyromski, Department of Educational Studies, Counselor Education, PAES Building, 305 W. 17th Ave., Columbus, OH, 

Human Sex Trafficking in America: What Counselors Need to Know

Stacey Diane A. Litam

The social justice issue of human sex trafficking is a global form of oppression that places men, women and children at risk for sexual exploitation. Although a body of research exists on the topics of human trafficking, literature specific to the mental health implications for counselors working with this population is limited. Counselors should increase their awareness of the vulnerabilities that place persons at risk of becoming trafficked. Additionally, obtaining a deeper understanding of the indicators and processes through which persons become trafficked is necessary in order to provide appropriate services. Counselors should learn how force, fraud and coercion influence the wellness of trafficked persons. The following article provides an overview of the relevant information pertinent to sex trafficking and addresses the counseling implications for working with sex trafficked survivors.


Keywords: human sex trafficking, sexual exploitation, social justice, trafficked survivors, oppression


The sexual exploitation of men, women and children through sex trafficking continues to occur in the United States and across the globe at an increasingly alarming rate. Despite misconceptions that sex trafficking requires transportation across state or country borders, the majority of victims are domestically trafficked within their own country by persons of the same nationality (Shelley, 2010; U.S. Department of State, 2009). Rates of forced labor are unknown and notoriously difficult to obtain due to methodological deficiencies (Fedina, 2015) and issues related to reporting and victim identification (Chesnay, 2013; Hyland, 2001; Laczko & Gramegna, 2003). However, the International Labour Organization (n.d.) estimates 27 million people become trafficked annually—4.5 million of whom are victims of forced sexual exploitation. Children and adolescents are exceptionally vulnerable to forced entry into the sex trade. The National Center for Missing and Exploited Children (2014) reported that 1 in 5 runaways are at risk for forced sexual exploitation. This represents an increase from an estimated 1 in 6 in 2014 (Polaris, 2016). Additionally, a study conducted by Estes and Weiner (2002) estimated that 326,000 youth are at risk for child trafficking. Counselors must become educated in recognizing the signs of trafficked persons, vulnerabilities to becoming trafficked, and the processes by which persons are forced into sexual exploitation in order to obtain a deeper understanding of the client’s worldview and provide appropriate support.


Existing literature addressing the mental health needs of sex trafficked survivors remains extremely limited (Hossain, Zimmerman, Abas, Light, & Watts, 2010; Tsutsumi, Izutsu, Poudyal, Kato, & Marui, 2008). Instead, the current body of research has focused on the sexual consequences of trafficking-related health issues such as sexually transmitted infections and rates of HIV among trafficked women in Asia (Beyrer, 2001; Beyrer & Stachowiak, 2003; Silverman et al., 2006; Silverman et al., 2007). The following article provides a brief overview of the definition, terms and processes associated with human trafficking. Next, the vulnerabilities and signs that a person has been or is currently being trafficked are presented. Finally, we address the clinical implications of working with trafficked survivors and identify trauma-sensitive interventions. Although female pronouns are used in this article, this detail is not intended to minimize the fact that many cisgender men, as well as lesbian, gay, bisexual and transgender persons, become victims of forced sexual exploitation (Martinez & Kelle, 2013; Oram, Stöckl, Busza, Howard, & Zimmerman, 2012).

Definition, Terms and Processes of Sex Trafficking


Despite the growing awareness of modern day slavery, the act of human trafficking is not a new phenomenon. In Imperial Rome, it has been estimated that between 30–40% of the Roman population was comprised of slaves trafficked from nearby countries such as Thrase, Gaul, Britain and Germany (Collingridge, 2006). In fact, during the height of the Roman Empire, wars were fought solely to procure more slaves (Cahill, 1995; Goldsworthy, 2006). Human trafficking was not limited to European countries. Beginning in 1619, both White and African slaves were taken from their countries and imported to Virginia to help construct the colonies (D. Davis, 2006; Jordan & Walsh, 2007). Human trafficking and modern day slavery are acts of social injustice that have historically exploited men, women and children.


According to the Trafficking Victims Protection Act (U.S. Department of State, 2000), the act of human trafficking refers to the recruitment, harboring, transportation, provision or obtaining of a person for commercial sex through force, fraud or coercion, or in which the person induced to perform a sex act is under 18 years of age. Despite common misconceptions, for an act to be considered sex trafficking, forced movement across the state is not required (U.S. Department of State, 2000). Sex trafficking includes a wide variety of traditionally accepted forms of labor, including commercial sex, exotic dancing and pornography (Logan, Walker, & Hunt, 2009). The following sections address the three components of control associated with human trafficking, namely force, fraud and coercion. Specific strategies used by traffickers to obtain and maintain control also are described.



As defined by the United States Department of Health and Human Services (2012), force pertains to the physical restraint or serious physical harm that traffickers use to obtain and maintain control. According to Chesnay (2013), methods of force are typically used to break down the victim’s spirit. Examples of force as a means of control include rape, physical violence, intimidation, physical confinement and restricted freedom (Williamson & Prior, 2009; Zimmerman et al., 2008). Traffickers may introduce an addiction to an illicit substance or use existing drug or alcohol addictions to force persons into exploitative circumstances (Raphael & Ashley, 2008; Raymond et al., 2002; Whitaker & Hinterlong, 2008; Williamson & Prior, 2009; Zimmerman, 2003). According to findings by Whitaker and Hinterlong (2008), victims’ resistance often leads to additional or more forceful control mechanisms used by traffickers. For example, traffickers may initially use physical or sexual violence and increase the severity (e.g., burning or torturing victims) when disobeyed. Additionally, Whitaker and Hinterlong discovered the presence of gendered patterns of control or the concept that different strategies are used when eliciting compliance from men and women (e.g., use of threats to community members and drug addiction in men, and threats to family relationships and references about the world being dangerous in women). It is important to note that not all trafficked persons experience physical suffering (Aradau, 2004; Belser, 2005).



     Fraud, or the use of false promises to lure persons into the human trafficking industry, is another method used by traffickers to control and exploit their victims (United States Department of Health and Human Services, 2012). Although fraud is typical in labor trafficking scenarios (e.g., women are offered appealing job opportunities overseas as a nanny or model and then forced into prostitution upon arrival), this tactic also is employed within sex trafficking scenarios (Belser, 2005; Whitaker & Hinterlong, 2008). Traffickers may recruit children from low-income families by promising parents that their children will be safer, better cared for and taught a useful skill or trade (Albanese, 2007; U.S. Department of State, 2009). Once recruited, victims enter into debt bondage and are promised freedom upon repayment to traffickers for their services (Williamson et al., 2010). Unfortunately, the result of debt bondage is a never-ending cycle from which victims cannot escape (Chesnay, 2013). Upon incurring a debt, persons in forced labor scenarios become trapped as traffickers enforce high interest rates, withhold payment, and charge for miscellaneous expenses such as the cost for food, transportation, condoms, and other supplies (International Labour Organization, 2005). Albanese (2007) described one case in which traffickers used fraud after recruiting two girls from Vancouver, British Columbia, and transporting them to Hawaii. In this scenario, the traffickers withheld the girl’s passports and threatened to circulate photographs of them engaging in sex acts in order to obtain their compliance. For many victims of forced labor, fraud is a strategy used by traffickers to exploit dreams or hope for a better life (U.S. Department of State, 2009).



     Coercion, or using threats of physical harm or physical restraint against a person, is another context of control associated with human trafficking (United States Department of Health and Human Services, 2012). Coercion can take the form of direct physical violence or be psychological in nature (Logan et al., 2009; U.S. Department of State, 2009). In many cases, traffickers coerce victims by threatening to harm their families if they do not comply with their demands (Whitaker & Hinterlong, 2008; Williamson & Prior, 2009). Coercive tactics can directly exploit cultural beliefs, such as the case described by Whitaker and Hinterlong (2008) in which a victim believed she had to obey a trafficker because he kept a lock of her hair. Homeless youth who lack resources (e.g., food, protection, drugs) become coerced by adults that provide shelter and later demand “payment” in the form of sex (Hagan & McCarthy, 1997, p. 48). Although some victims are controlled by traffickers, others are coerced into sexual exploitation by boyfriends, girlfriends and friends (Hagan & McCarthy, 1997; Widom & Kuhns, 1996). Traffickers may coerce their victim’s compliance through the use of a grooming process (Herman, 1992) in which a connection is forged between victims and their traffickers in order to produce intense loyalty (Priebe & Suhr, 2005). When threats, force or coercion is used for the purpose of exploitation, victim consent is not relevant (Logan, 2007).


     The grooming process. The seasoning, or grooming, process refers to the progression of power used by traffickers to control their victims and, in some cases, forge a trauma bond (Smith, Vardaman, & Snow, 2009). Similar to “Stockholm syndrome,” in which hostages relate to and defend their captors (Smith et al., 2009), trauma bonding is a form of coercive control in which traffickers instill a sense of fear as well as gratitude for being allowed to live (United States Department of Health and Human Services, 2012). As outlined by O’Connor and Healy (2006), the grooming process stages are ensnaring, creating dependence, taking control, and total dominance. During the ensnaring phase, traffickers begin to identify themselves as a trustworthy and valuable person in the victim’s life (O’Connor & Healy, 2006). Traffickers may provide favors, purchase expensive gifts, show affection and enter into a romantic relationship with the victim (Albanese, 2007). For many adolescents, this façade may represent the only affirming, reliable and secure relationship in their lives, and victims quickly find themselves emotionally invested. Next, traffickers create dependence. During this process, victims gradually become separated from their families and friends (O’Connor & Healy, 2006). Traffickers may convince victims that other persons in their lives are unreliable or untrustworthy. At the completion of this stage, victims begin to rely solely on their traffickers for support and become isolated from their previous lives (O’Connor & Healy, 2006). The taking control stage is characterized by a shift in the traffickers’ behavior from caring and supportive to controlling and possessive (O’Connor & Healy, 2006). The trafficker may begin to use threats, violence and drugs as methods of control and dictate whom the victim sees and where she goes (Whitaker & Hinterlong, 2008). At the end of this stage, traffickers may test the victims’ commitment to the relationship and demand that they begin selling commercial sex to prove their love (O’Connor & Healy, 2006). Once victims have become completely dependent on their traffickers and are convinced that the easiest way to earn money and maintain their relationships is through selling sex, total dominance has been achieved (O’Connor & Healy, 2006). Although the grooming process outlined by O’Connor and Healy is a helpful model that represents how many persons become trafficked, these series of stages may not occur in every case. Persons may enter the commercial sex trade through a variety of avenues, and their experiences of becoming trafficked may be consistent with, or distinct from, O’Connor and Healy’s model.


Contexts of Control

Just as variability exists within the stages of grooming, different factors influence whether the grooming process itself results in victim compliance. Traffickers use a variety of recruitment techniques and forms of exploitation to obtain and maintain control (Shelley, 2010). Contexts of control acknowledge the complex associations that influence the relationship between victim and trafficker (Whitaker & Hinterlong, 2008). These factors include the individual resiliencies of trafficked persons, the grooming process, and the methods of force, fraud and coercion used by traffickers (Whitaker & Hinterlong, 2008). According to Whitaker and Hinterlong (2008), the four contexts of control include control-seeking, control mechanisms, controllability and resistance. The context of control-seeking refers to the trafficker’s desire to limit the victims’ choices in order to increase the likelihood that their desires are met (Whitaker & Hinterlong, 2008). Traffickers with higher rates of control-seeking seek more power over victims’ behaviors, appearance and travel (Whitaker & Hinterlong, 2008). They may determine what victims wear, control how they interact with buyers, confine persons to specific locations, identify and enforce a mandatory amount of earnings per day, or withhold passports, money and identifying documents (Whitaker & Hinterlong, 2008; Zimmerman, 2003). Traffickers use control mechanisms (e.g., threats of violence, debt bondage, psychological intimidation and acute violence) to obtain and maintain control of victims, and they may vary depending on the victims’ level of controllability, or capacity to resist due to their social or financial context, cultural or personal beliefs, physical limitations, or other deficiencies (Shelley, 2010; Whitaker & Hinterlong, 2008). Thus, a trafficker may attempt to recruit a young woman by showering her with expensive gifts and affection, but if she demonstrates a low level of controllability (e.g., she has a strong support system, is financially stable, has high self-efficacy), the control mechanisms are less effective (Whitaker & Hinterlong, 2008). Controllability can be further delineated into six subdomains: social, financial, physical, cultural, psychological and institutional (Whitaker & Hinterlong, 2008). Persons with a strong combination across these six subdomains have lower controllability levels and are less likely to become trafficked through the grooming process (Whitaker & Hinterlong, 2008). Because trafficked people are unable to predict or manage events that influence their health and safety, the methods of control in human trafficking are parallel to the characteristics of abuse described in the literature on torture (Saporta & Van der Kolk, 1992).


Vulnerabilities and Risk Factors


     The market for commercial sex represents a diverse avenue that incorporates a wide spectrum of activities and transactions across many settings (Anderson & O’Connell Davidson, 2003). Although survivors of human trafficking are not limited to race, ethnicity, age, gender or socioeconomic status, vulnerabilities such as location, poverty, sexual minority status and childhood trauma history, among other factors, influence higher rates for potential sexual exploitation (Albanese, 2007;  Bales, 2007; Hyland, 2001; Kidd & Liborio, 2011; Martinez & Kelle, 2013). The following section outlines a variety of risk factors that have been linked to entrance into the sex trafficking trade.

Location as Risk Factor

Within the global human trafficking industry, there are origin and destination countries that influence the direction of movement and likelihood that persons become victims of forced sexual exploitation (Bales, 2007). Often, third world countries are origin countries characterized by locations with a large supply of available victims (Bales, 2007). The country may be in a state of conflict and social unrest or have high rates of poverty, government corruption and a lack of viable employment opportunities (Bales, 2007). Because trafficking is strongly linked to rates of poverty and minimal employment opportunities (Loff & Sanghera, 2004), many people willingly go with traffickers believing they will receive better opportunities abroad and can send money home to their families (Chung, 2009). Once recruited from origin countries, survivors are transported to destination countries, characterized by locations with high demand for commercial sex (Bales, 2007). Some locations, such as the United States, are bidirectional countries, in which victims are both recruited and put to work (Farr, 2005).


Although many persons become trafficked across international borders, the majority of victims in the United States are trafficked domestically (U.S. Department of State, 2009), with an increase of minors recruited from the Midwest (Williamson & Prior, 2009). In a study of 13 youth involved with forced sexual exploitation, respondents explained that recruitment occurred on the streets, while walking to friends’ houses, with peers, at corner stores, at malls, at their own homes, and waiting to meet with a probation officer outside the juvenile justice center (Williamson & Prior, 2009). In most cases, youth were approached by someone they knew, a mutual acquaintance, or people they recognized from their community (Williamson & Prior, 2009). Thus, counselors need to become familiar with recruitment cities, destination cities and bidirectional cities (Williamson & Prior, 2009). Recruitment and destination cities respectively refer to locations where persons are obtained and transported to meet the growing demand for commercial sex (K. Davis, 2006). Although victims may become recruited and forced into sexual exploitation in any city across the United States, smaller cities in the Midwest have been linked to increased rates of recruitment (K. Davis, 2006). Recruitment cities share similar characteristics, such as access to numerous highways that facilitate victim transportation to destination cities where demand for commercial sex is greatest (K. Davis, 2006). Once obtained, victims are transported to high-demand locations such as Chicago, Detroit and Las Vegas (Wilson & Dalton, 2007. Additional factors that seem to link location to sex trafficking exist. Previous studies have found increased rates of commercial sexual exploitation in areas with higher ratios of females to males (Rao & Presenti, 2012), in places with legalized prostitution (Cho, Dreher, & Neumayer, 2013), and within areas characterized by large populations of transient males such as military personnel, truckers, tourists, and conventioneers (Estes & Weiner, 2002; Farley & Kelly, 2000).


Interpersonal and Intrapersonal Risk Factors

     In addition to location, other vulnerabilities to becoming trafficked exist, including individual, family, peer-related and environmental factors (Williamson & Prior, 2009). Persons from any socioeconomic background, race or ethnicity may become trafficked (McClain & Garrity, 2010). A study exploring the shared characteristics of adolescent females in the commercial sex industry identified low IQ scores and multiple mental health disorders as common factors (Twill, Green, & Traylor, 2010). History of risky or deviant behavior exposes adolescents to increased risk for becoming trafficked. For example, adolescents selling, buying and using drugs all increase the likelihood of crossing paths with a trafficker (McClain & Garrity, 2010; Walsh & Donaldson, 2010). Additional risk factors such as poverty, unemployment, isolation, low self-efficacy, drug addiction and history of physical and sexual abuse have been linked with entrance into the sex trafficking industry (Bales, 2007; Kidd & Liborio, 2011). Although not all trafficked persons have histories of childhood abuse (Chudakov, Ilan, Belmaker, & Cwikel, 2002), persons forced into sexual exploitation have commonly experienced violence prior to becoming trafficked, which increases their vulnerability to entering the sex trafficking trade and influences the greater likelihood of developing future mental health concerns (Hossain et al., 2010).


Homelessness and Sexual Minority Status as Risk Factors

Runaway, homeless or throwaway children are recruited into trafficking rings and exposed to extreme forms of abuse (Estes & Weiner, 2002). Many are killed as a result of violence or from diseases incurred from their sexual victimization (Estes & Weiner, 2002; Mitchell, Finkelhor, & Wolak, 2010). Adolescents are typically approached by traffickers within 48 hours of living on the street (Jordan, Patel, & Rapp, 2013). Traffickers are predatory in nature and adept at identifying vulnerable persons in need of safety, security and protection (Albanese, 2007; Jordan et al., 2013). LGBT persons are especially at risk of forced sexual exploitation due to increased rates of high-risk behaviors and homelessness (Martinez & Keele, 2013). According to the National Coalition for the Homeless (2009), sexual minority youth are twice as likely to experience sexual abuse before the age of 12 and are 7.4 times more likely to become victims of sexual violence. Counselors working with LGBT adolescents must assess their clients’ histories and explore whether they have engaged in survival sex or substance abuse or have been homeless. Survival sex is characterized by the exchange of sexual acts for shelter, food, money, protection, favors or other resources (Estes & Weiner, 2002; Williams & Frederick, 2009). It is important to note that persons from stable families may become trafficked. Young women may go willingly with friends to parties and become enamored with charming men involved in the sex trafficking trade or become flattered by the attentions of predatory older men (Chesnay, 2013). According to a study conducted by Raphael and Myers-Powell (2010) that interviewed 25 ex-pimps in Chicago, the prime candidate for recruitment was a blonde runaway.


Social Media and Internet Use as Risk Factor

Free access and anonymity with the Internet has created greater opportunity for offenders to purchase sex online where a wider variety of options exist (Chung, 2009; McCarthy, 2010; Raphael & Myers-Powell, 2010). Social media Web sites such as Myspace, Twitter and Facebook have been identified as a frequent tool used by traffickers to recruit adolescents into the sex trafficking trade (Demir, 2010; Jordan et al., 2013; Raphael & Myers-Powell, 2010; Williamson & Prior, 2009). Offenders cited the use of social media Web sites to contact, groom and connect with their victims, whereas online advertisement Web sites such as Craigslist were used to sell their victims (Raphael & Myers-Powell, 2010).


Adolescents with low levels of self-efficacy may be at increased risk for victimization due to higher rates of social media use. According to the Pew Research Center (2013), 74% of adults online use social networking sites, with young adults ages 18 to 29 representing the vast majority of social media users. Research exploring the relationship between social media use and the well-being of young adults has yielded significant findings that promote a deeper understanding of how traffickers select and recruit victims online. A study conducted by Meier and Gray (2014) linked photo activity on Facebook with greater than ideal internalization and self-objectification. Michikyan, Subrahmanyam, and Dennis (2014) additionally discovered that young adults experiencing emotional instability were more strategic in their online self-presentation, presumably to seek reassurance. Social networking site use also has been found to increase levels of self-efficacy, satisfy a need for belonging and improve self-esteem in college-aged students (Gangadharbatla, 2008). Upon examination of these pre-existing vulnerabilities, counselors can acquire a deeper understanding of how the grooming process may result in trauma bonds and entrance into the sex trafficking trade. For at-risk adolescents that lack a strong support system, experience low levels of self-efficacy and seek affirmation through their social media presence, online connections with traffickers may satisfy their deep desires for validation. Because traffickers are predatory in nature and gravitate toward vulnerable persons with low self-efficacy and high rates of controllability, counselors working with adolescents and young adults should provide education on topics related to Internet safety and the consequences of promoting a sexually suggestive online presence.


Possible Signs of Trafficking


Counselors working with at-risk populations (e.g., clients with addictions, and a history of homelessness and trauma) must recognize the possible signs that clients are being trafficked. Because many victims remain invisible to law enforcement (Hyland, 2001) and counselors, the identification and treatment of victims represents one of the greatest challenges in working with this population (McClain & Garrity, 2010). According to Polaris (2015), a variety of indicators exist that may suggest forced exploitation.


Signs of Trafficking in Mental Health Settings

Counselors and other helping professionals should assess clients for signs of trafficking, including instances in which clients are under 18 and providing commercial sex acts, have a controlling older boyfriend, work excessively long or unusual hours, or have few personal possessions (Polaris, 2015). Within behavioral health settings, clients may present as fearful, anxious, depressed, submissive or tense with avoidant eye contact (Polaris, 2015). Trafficked persons rarely seek counseling independently and have likely endured intense, ongoing victimization and may present with depression, dissociative reactions, suicidal ideation, post-traumatic stress disorder, feelings of guilt,  shame and self-mutilation (Chesnay, 2013). Clients also may have histories of solicitation charges, substance use issues, or a need for safe and stable housing, lack a strong support system, and have visible bruises or branding (Chesnay, 2013; Hyland, 2001; Jordan et al., 2013). Branding refers to a method of identification used by traffickers to indicate ownership and may be tattoos or carvings (Jordan et al., 2013; Shared Hope International, 2016). It is the author’s experience that some clients that become addicted to opiates by their oppressors are forced to inject in locations on their bodies that will not detract from their overall marketability as a reusable commodity. In many cases, these locations include the inner thighs or between the fingers or toes. As one anonymous survivor (a client of the author) explained, “Nobody is going to buy someone with track marks.” A trend exists in which offenders trafficking drugs are beginning to traffic people (Shelley, 2010). Whereas drugs can be sold once, people can be sold repeatedly and thus represent a more profitable and less risky business venture (Neville & Martinez, 2004; Shelley, 2010).


Signs of Trafficking in Medical Settings

Trafficked persons may present in health care settings, although these instances occur at a low rate. Persons are only allowed to seek medical attention when traffickers believe their condition prevents monetary gain, at which point they can become disposable (Chesnay, 2013; Neville & Martinez, 2004). Medical issues associated with trafficked survivors within health care settings may include sexually transmitted infections, pregnancy, history of unsafe abortions, chronic pain, malnutrition, substance use issues, and sleep deprivation (Chesnay, 2013; Estes & Weiner, 2002). Counselors and medical professionals may additionally note that trafficked survivors struggle during a mental status exam (Chesnay, 2013). Due to a combination of working long hours, exhaustion, and frequent transportation to and from locations, trafficked persons may respond incorrectly to questions regarding time, place and person (Chesnay, 2013).


Signs of Trafficking in School Settings

School counselors need to be mindful of signs that students are being trafficked. Adolescents may be trafficked out of their own homes and transported to and from school by their oppressor (U.S. Department of Education, 2013). Possible signs that students are being trafficked within educational settings include references to frequent travel to other cities, signs of bruising, presence of depression, anxiety, or fear, coached or rehearsed responses to questions, and inappropriate dress based on weather conditions (U.S. Department of Education, 2013). Additionally, school counselors need to be mindful of children who have significantly older boyfriends or girlfriends, describe concern for the safety of family members if they disclose, or care for children that are not family members (U.S. Department of Education, 2013). When a child is being sex trafficked, they may be absent from school or miss periods of time while being sold to other communities (Williamson & Prior, 2009).


Challenges of Working With Trafficked Clients


Counselors may experience feelings of frustration and helplessness upon discovery that clients are rarely willing to leave their traffickers despite their dire situations. It is important to remember that many adolescents who become sex trafficked experience neurological effects from childhood physical, emotional and sexual trauma that inhibits their abilities to make pragmatic choices or escape their traffickers (Reid & Jones, 2011). The presence of chronic fear can inflict barriers to cognitive processing and decision making, which explains why some survivors do not escape when the opportunity arises (Loewenstein, Weber, Hsee, & Welch, 2001; Logan, Walker, Jordan, & Leukefelt, 2006). Due to the familiarity of unhealthy relationships and the lack of self-efficacy required to pursue change, childhood victims of sexual trauma are more likely to accept situations characterized by abuse (Reid & Jones, 2011). Counselors are encouraged to seek supervision, connect with colleagues and practice regular self-care routines in order to avoid experiencing burnout, secondary trauma, and compassion fatigue when working with this population.


Counselors working with trafficked clients are often faced with a series of challenges since an intervention modality specific to sex trafficked survivors has not yet been developed (Jordan et al., 2013). Although a small body of research exists on the health consequences associated with human trafficking, limited research has explored the mental health consequences of trafficking (Hossain et al., 2010; Tsutsumi et al., 2008). Current treatments are borrowed from evidence-based interventions originally developed for post-traumatic stress disorder and survivors of domestic violence, slavery and captivity (Jordan et al., 2013).


Assess Client’s Current State

Whether providing individual or group counseling to sex trafficked clients, several treatment considerations should be examined. First, counselors should assess whether the client is currently being trafficked or whether a sex trafficking history exists. Naturally, the counselor’s role will differ significantly depending on the client’s present situation. In the author’s experience, clients that are currently trafficked rarely seek mental health services independently. Instead, clients may present to counseling as the result of court mandates associated with drug or solicitation charges. Clients that are currently trafficked often resist help from mental health providers and avoid reporting due to well-founded fears of physical violence or threats of retribution if they disclose their situation (Flores, 2010). Therefore, building strong rapport with sex trafficked clients is critical (Chesnay, 2013). Because of the fraud and deception used by traffickers during the grooming process, many trafficked persons demonstrate marked difficulty with trusting others (Belser, 2005). It is essential that counselors build trust with the client by demonstrating unconditional positive regard, empathy and authenticity. Counselors may support clients by developing individualized safety plans and sharing valuable resources (e.g., The National Human Trafficking Hotline: 1-888-373-7888). Once a strong therapeutic relationship has been established, counselors may begin pursuing a variety of counseling goals, including psychoeducation, supporting clients through the stages of personal change, engaging in group counseling, medication management, addressing substance use issues, and promoting reintegration through education and job training.


Counselors working with sex trafficked survivors must assess whether the client has access to necessary resources, including housing, food, water, shelter and medicine. Ensuring that survivors are equipped with safe and stable homes minimizes the likelihood that they are simply returning to the same endangering conditions (Feingold, 2005). Counselors should work with sex trafficked clients to explore the circumstances that increased their risk for sexual exploitation. Once the situations are identified, counselors must work collaboratively with clients to create a sustainable maintenance promotion plan. Chesnay (2013) explained that once basic physiological needs and safe housing are obtained, mental health professionals can begin reframing the client’s worldview from “victim” to “survivor” to “thriving survivor.”


Asking Helpful Questions

In addition to taking the client’s trafficking situation into consideration, it is important to remain mindful of the language used when working with this population. Clients will rarely, if ever, identify with the term trafficked and also are likely to struggle with identifying their partner and protector as a pimp or trafficker (Chesnay, 2013). Trafficked clients may explain that they are working to help their boyfriends (Priebe & Suhr, 2005). Counselors and other mental health professionals are encouraged to accept the client’s identified terms and work within their individual framework (Chesnay, 2013).


Providing psychoeducation on the process, rates and prevalence of sex trafficking may be beneficial for clients to promote insight. Educational modalities that shift pertinent information from general to specific may be helpful in gradually exposing clients to difficult concepts. Counselors should work collaboratively with clients to identify salient issues and validate their experiences to promote recognition and exploration on the effects of trafficking. Counselors may use statements such as, “Many young adolescents living on the streets feel scared and find someone to protect and care for them. I wonder whether this is true for you?” Or, “Some people care so much about their partners that they feel obligated to prove their love and begin doing things they are not really comfortable with. I am curious whether this has been your experience as well?” Offering opportunities for clients to disclose information in a safe, nonjudgmental and accepting environment can increase client insight, promote counselor awareness of client history and facilitate therapeutic growth. Additionally, counselors should determine whether clients have access to safe and stable housing. If basic physiological needs are not met, clients may struggle to focus on higher order needs such as developing a safety plan or emotion regulation.


Assess Client’s Stage of Change

For clients that are currently trafficked, the stages of change outlined by Norcross, Krebs, and Prochaska (2011) may be a helpful tool for examining clients’ willingness to engage in counseling. Clients in the precontemplation stage may respond positively to counseling strategies aimed at increasing education and awareness. When clients present in the stage of contemplation, counselors may be most supportive by exploring client ambivalence. Counselors may facilitate costs and benefits analyses with the client regarding their current predicaments. Regardless of the client’s stage of change it is important that counselors do not force the client to leave their oppressor. This may put the client, their families and other loved ones at risk (Flores, 2010). Instead, counselors must listen, affirm and provide the client with resources such as the trafficking hotline and empower them to call when ready. It is important that counselors assess the severity and duration of trafficking-related abuse and recognize how these experiences influence recovery time (Hossain et al., 2010). In a sample of 204 trafficked girls and women, the presence of sexual violence during a trafficking experience had an independent effect on mental health symptoms (Hossain et al., 2010). Hossain and colleagues (2010) concluded that persons trafficked for longer periods of time have an increased likelihood of abusive episodes and prolonged feelings of entrapment, alienation, loss of control, humiliation and helplessness—all of which are associated with developing mental health disorders in the future. Counselors can better accommodate the needs of persons that have been trafficked for longer periods of time by providing longer duration post-trafficking care.


Assess Entrance Into Trafficking

Other treatment considerations pertain to the process through which clients became trafficked. Clients recruited and controlled through a grooming process may struggle to identify their captors as oppressors due to the presence of a trauma bond (United States Department of Health and Human Services, n.d.). Cases also exist in which clients have been trafficked by family members or sold to traffickers by their parents (Shelley, 2010). In some instances, adolescents and children are forced into sexual exploitation by their parents or siblings in order to support drug addictions or to avoid financial burdens (Estes & Weiner, 2002). One survivor, a client of the author, reported that a family member diagnosed with schizoaffective disorder trafficked her for a period of 2 months. The client described how the family member would hold a firearm to his neck and threaten to commit suicide if she did not provide him with heroin. The client explained how she felt forced to complete commercial sex acts with drug dealers, as this strategy was the quickest and easiest way to obtain illicit substances within her impoverished community. Counselors should work to identify their biases regarding how persons are trafficked, and by whom, in order to identify survivors and provide appropriate services.


Counseling Sex Trafficked Clients


     Counselors working with sex trafficked survivors should be prepared to employ a variety of trauma-sensitive interventions to support the individual needs of each client. Trauma-sensitive interventions identify safety as the foundation for working with persons to eliminate self-harm, develop trustworthy relationships, overcome challenges, promote wellness and remove themselves from dangerous situations (Najavits, 2002). Helping traumatized clients to regain a sense of control is critical (Goodman & Calderon, 2012). For example, counselors may use mindfulness-based activities such as body scans and body awareness exercises to help clients differentiate between current and past experiences (Rothschild, 2000). Counselors can use other mindfulness techniques, such as focusing on the present and emphasizing the mind-body connection, to help clients identify and reduce the somatic symptoms of arousal when no threats are present (Goodman & Calderon, 2012). Finally, counselors can help clients practice imagining, and returning attention to, comforting images to increase their sense of safety and decrease arousal (Goodman & Calderon, 2012). Ideally, counselors will empower their clients to redefine their lives not by their pasts, but by their futures (Chesnay, 2013).

Creative Interventions

     Creative-based interventions are especially powerful with sex trafficked clients because they provide opportunities for clients to make choices. For clients who have long been told what to do and have lived according to their trafficker’s demands, the presentation of choices and sense of control may represent an exciting and difficult challenge. Creative arts interventions have received a great deal of empirical support for clients presenting with trauma. Research that investigated resiliency has identified the importance of creativity, humor, flexibility, and movement as effective interventions to improve traumatized clients’ self-esteem, hope and prosocial behaviors (Johnson, Lahad, & Gray, 2009; Lahad, 2000; Raynor, 2002). Additionally, therapeutic art has been shown to be efficacious for work with clients presenting with emotional disturbances, grief and loss, low self-efficacy, depression, post-traumatic stress disorder, anxiety, and feelings of guilt and shame (Johnson et al., 2009; Slayton, D’Archer, & Kaplan, 2010). Creative interventions can be used to help clients reframe ideas, shift perspectives, externalize emotions and gain deeper understanding of events (Bradley, Whiting, Hendricks, Parr, & Jones, 2008). According to Lev-Weisel (1998), clients that struggle to find words to describe their traumatic experiences may prefer creative interventions as a means of expression. Counselors can integrate the use of creative and expressive interventions using mandalas or other art mediums to support clients in promoting openness while providing a sense of structure. Future areas of research are needed to determine the efficacy of creative interventions specific to clients with a history of sex trafficking.


Cognitive Behavioral Therapies

     Clients with a history of sex trafficking can benefit from cognitive behavioral therapies due to their internalization of derogatory labels (Hickle & Roe-Sepowitz, 2014). Counselors working with trafficked clients can identify and challenge these labels in order to decrease the presence of shame and other meta-emotions (e.g., anger at oneself for feeling shame). Additional evidence-based counseling interventions that may be useful for sex trafficked client populations include Eye Movement Desensitization and Reprocessing with adults (Maxfield, 2003; Shapiro, 1989) and trauma-focused cognitive behavioral therapy with children (Cohen, Berliner, & Mannarino, 2010; Cohen, Mannarino, Berliner, & Deblinger, 2000). The use of dialectical trauma-focused cognitive behavioral therapy is effective with both children (Racco & Vis, 2015) and adults with histories of trauma and post-traumatic stress disorder (Wagner, Rizvi, & Harned, 2007). Although trauma-focused cognitive behavioral therapy and dialectical trauma-focused cognitive behavioral therapy have not been tested specifically for sex trafficked populations, research indicates that these modalities are successful in helping children overcome histories of trauma and abuse (Classen, Koopman, Nevill-Manning, & Spiegel, 2001; Cohen & Mannarino, 1997). Future research studies should investigate the efficacy of cognitive behavioral therapies with sex trafficking survivors in order to standardize appropriate treatment methods for this unique population.


Group Counseling

     Providing survivors of forced sexual exploitation with an opportunity to participate in group counseling can empower persons to share similar experiences while creating a sense of community and support (Hickle & Roe-Sepowitz, 2014). Peer support is a crucial component for treatment since bearing witness to the similar lived experiences of other survivors provides a unique dimension of support and sense of universality (Chesnay, 2013). Counselors working with trafficked persons may focus on accomplishing a variety of treatment goals, including feeling identification, establishing safety, addressing substance use, countering internalized stigma and labels, providing psychoeducation and establishing healthy boundaries. Shame can be reduced by prompting discussions about taboo and stigmatizing topics within group settings (Hickle & Roe-Sepowitz, 2014). Many trafficked survivors have upheld the belief that they are the only ones who have been trafficked by parents, have engaged in survival sex, or who have been forced into sexual exploitation by boyfriends or girlfriends. According to Estes and Weiner (2002), boys that performed oral sex on adult males as a result of forced sexual exploitation experienced a profound sense of shame. Addressing these foci of shame can help clients recognize the universality of their experiences, build rapport with peers and facilitate trust in the group setting. Counselors should listen openly to the client’s stories of shame and receive them with empathy in order to dispel their negativistic beliefs. Psychoeducation within group settings can be used to explain how traffickers use coercion and other techniques to recruit young women (Hickle & Roe-Sepowitz, 2014).


Expressive techniques that allow group members to process trauma experiences without dissociating from the event are beneficial in promoting therapeutic growth (Hickle & Roe-Sepowitz, 2014). Clients can use markers, colored pencils and other artistic mediums to draw, color or write on an outlined body where they feel specific emotions such as pain, shame, anger, fear and guilt (Hickle & Roe-Sepowitz, 2014). Words and pictures from magazines also can be used to represent emotions or past and present states of mind and facilitate the healing process. The author has facilitated mask exercises within group settings to support trafficked clients in identifying and processing their ideal and actual selves. Once completed, the pictures and masks can be processed with other group members and similar or different experiences, emotions and challenges can be discussed.




Although social and cultural norms, poverty, gendered inequality and childhood history represent important vulnerability factors, the social injustice known as sex trafficking could not occur without the demand for sexual exploitation (Matheson & Finkel, 2013). A deeper understanding is needed to comprehend how persons become trafficked (Whitaker & Hinterlong, 2008). Additionally, a dearth of research remains that identifies specific evidence-based and trauma-sensitive modalities developed specifically for sex trafficked survivors (Chesnay, 2013; Jordan et al., 2013). The experiences, challenges and reflections of the author have been presented with the intention of providing education, support and guidance to other counselors serving this unique population. Regardless of which counseling tools are used, establishing and building a strong therapeutic alliance is a valuable tool that counselors can employ to support sex trafficked persons (Chesnay, 2013). Although challenging at times, establishing rapport requires a nonjudgmental attitude and a willingness to bear witness to clients’ experiences, without pointing out what survivors could have done differently (Chesnay, 2013).


It is important to remember that trafficked persons are often survivors of long-term childhood trauma characterized by instability within the home, childhood sexual trauma and community violence (Bales, 2007; Hossain et al., 2010; Kidd & Liborio, 2011; Williamson & Prior, 2009). Many adolescents were targeted, recruited and trafficked due to pre-existing vulnerabilities and high controllability factors (Whitaker & Hinterlong, 2008). Counselors are tasked with a unique position to provide corrective relational experiences characterized by the nonjudgmental acceptance, support and affirmation desperately needed by this population. Fewer resources and services exist for trafficked survivors than for victims of any other crime (Clawson, Dutch, & Cummings, 2006). Counselors should connect sex trafficked survivors to necessary social service supports, including case management services, safe and stable housing, and services aimed at supporting the successful reintegration of clients into the community through education and job training (Williamson & Prior, 2009). Future areas of research should explore the profiles of traffickers and standardize how mental health and medical providers can better identify, serve, protect, and support trafficked survivors (Bales, 2005). Finally, counselors are called to continue promoting awareness on the prevalence and signs of sex trafficked survivors. Increasing awareness and decreasing demand for sexually exploited persons are the fundamental steps necessary to end the human rights violation of sex trafficking (Chung, 2009; Kotrla, 2010).


Conflict of Interest and Funding Disclosure

The authors reported no conflict of interest

or funding contributions for the development

of this manuscript.





Albanese, J. (2007). Commercial sexual exploitation of children: What do we know and what do we do about it? Retrieved from

Anderson, B., & O’Connell Davidson, J. (2003). Is trafficking in human beings demand driven? A multi-country pilot study. Retrieved from

Aradau, C. (2004). The perverse politics of four-letter words: Risk and pity in the securitisation of human trafficking. Millennium Journal of International Studies, 33, 251–277.

Bales, K. (2005). Understanding global slavery: A reader. Berkeley, CA: University of California Press.

Bales, K. (2007). What predicts human trafficking? International Journal of Comparative and Applied Criminal Justice, 31, 269–279. doi:10.1080/01924036.2007.9678771

Belser, P. (2005). Forced labor and human trafficking: Estimating the profits. Retrieved from

Beyrer, C. (2001). Shan women and girls and the sex industry in Southeast Asia: Political causes and human rights implications. Social Science & Medicine, 53, 543–550.

Beyrer, C., & Stachowiak, J. (2003). Health consequences of trafficking of women and girls in Southeast Asia. The Brown Journal of World Affairs, 10, 105–117.

Bradley, L. J., Whiting, P., Hendricks, B., Parr, G., & Jones, E. G., Jr. (2008). The use of expressive techniques in counseling. Journal of Creativity in Mental Health, 3, 44–59.

Cahill, T. (1995). How the Irish saved civilization: The untold story of Ireland’s heroic role from the fall of Rome to the rise      of Medieval Europe (The Hinges of History). New York: Random House.

Chesnay, M. D. (2013). Psychiatric-mental health nurses and the sex trafficking pandemic. Issues in Mental Health Nursing, 34, 901–907. doi:10.3109/01612849.2013.857200

Cho, S. Y., Dreher, A., & Neumayer, E. (2013). Does legalized prostitution increase human trafficking? World                    Development, 41, 67–82.

Chudakov, B., Ilan, K., Belmaker, R. H., & Cwikel, J. (2002). The motivation and mental health of sex workers.                 Journal of Sex and Marital Therapy, 28, 305–315. doi:10.1080/00926230290001439

Chung, R. C-Y. (2009). Cultural perspectives on child trafficking, human rights & social justice: A model for psychologists. Counselling Psychology Quarterly, 22,85–96.

Classen, C., Koopman, C., Nevill-Manning, K., & Spiegel, D. (2001). A preliminary report comparing trauma-focused and present-focused group therapy against a wait-listed condition among childhood sexual abuse survivors with PTSD. Journal of Aggression, Maltreatment & Trauma, 4, 265–288.

Clawson, H. J., Dutch, N., & Cummings, M. (2006). Law enforcement response to human trafficking and the implica-tions for victims: Current practices and lessons learned. Retrieved from

Cohen, J. A., Berliner, L., & Mannarino, A. (2010). Trauma focused CBT for children with co-occurring trauma and behavior problems. Child Abuse & Neglect, 34, 215–224.

Cohen, J. A., & Mannarino, A. P. (1997). A treatment study for sexually abused preschool children: Outcome during a one-year follow-up. Journal of the American Academy of Child & Adolescent Psychiatry, 36, 1228–1235.

Cohen, J. A., Mannarino, A. P., Berliner, L., & Deblinger, E. (2000). Trauma-focused cognitive behavioral therapy for children and adolescents: An empirical update. Journal of Interpersonal Violence, 15, 1202–1223.

Collingridge, V. (2006). Boudica: The life and legends of Britain’s warrior queen. Woodstock, NY: Overlook Press.

Davis, D. B. (2006). Inhuman bondage: The rise and fall of slavery in the New World. New York, NY: Oxford University Press.

Davis, K. Y. S. (2006). Human trafficking and modern day slavery in Ohio. Washington, DC: Polaris Project. Retrieved from

Demir, O. O. (2010). Methods of sex trafficking: Findings of a case study in Turkey. Global Crime, 11, 314–335.

Estes, R. J., & Weiner, N. A. (2002). The commercial sexual exploitation of children in the U.S., Canada, and Mexico. Retrieved from

Farley, M., & Kelly, V. (2000). Prostitution: A critical review of the medical and social sciences literature. Women & Criminal Justice, 11(4), 29–64.

Farr, K. (2005). Sex trafficking: The global market in women and children. New York, NY: Worth.

Fedina, L. (2015). Use and misuse of research in books on sex trafficking: Implications for interdisciplinary

research, practitioners, and advocates. Trauma, Violence, and Abuse, 16, 188–198. doi:10.1177/1524838014523337

Feingold, D. A. (2005). Human trafficking. Foreign Policy, 150, 26–30.

Flores, T. (2010). The slave across the street: The true story of how an American teen survived the world of human trafficking. Boise, ID: Ampelon.

Gangadharbatla, H. (2008). Facebook me: Collective self-esteem, need to belong, and internet self-efficacy as predictors of the iGeneration’s attitudes toward social networking sites. Journal of Interactive Advertising, 8(2), 1–28.

Goldsworthy, A. (2006). Caesar: Life of a colossus. New Haven, CT: Yale University Press.

Goodman, R. D., & Calderon, A. M. (2012). The use of mindfulness in trauma counseling. Journal of Mental Health Counseling, 34(3), 254–268.

Hagan, J., & McCarthy, B. (1997). Mean streets: Youth crime and homelessness. Cambridge, England: Cambridge University Press.

Herman, J. L. (1992). Trauma and recovery: The aftermath of violence—from domestic abuse to political terror. New                         York, NY: Basic Books.

Hickle, K. E., & Roe-Sepowitz, D. E. (2014). Putting the pieces back together: A group intervention for sexually exploited adolescent girls. Social Work with Groups, 37, 99–113. doi:10.1080/01609513.2013.8233838

Hossain, M., Zimmerman, C., Abas, M., Light, M., & Watts, C. (2010). The relationship of trauma to mental disorders among trafficked and sexually exploited girls and women. American Journal of Public Health, 100, 2442–2449.

Hyland, K. E. (2001). Protecting human victims of trafficking: An American framework. Berkeley Women’s Law Journal, 16, 29–71.

International Labour Organization. (n.d.). Forced labour, modern slavery and human trafficking. Retrieved from–en/index.htm

International Labour Organization. (2005). Global report on forced labour in Asia: Debt bondage, trafficking and state-

            imposed forced labour. Retrieved from


Johnson, D. R., Lahad, M., & Gray, A. (2009). Creative therapies for adults. In E. B. Foa, T. M. Keane, M. J. Fried-

man, & J. A. Cohen (Eds.), Effective treatments for PTSD. Practice guidelines from the International Society for Traumatic Stress Studies (pp. 479–490). New York, NY: Guilford Press.

Jordan, D., & Walsh, M. (2007). White cargo: The forgotten history of Britain’s white slaves in America. New York: New York University Press.

Jordan, J., Patel, B., & Rapp, L. (2013). Domestic minor sex trafficking; A social work perspective on misidentifi-cation, victims, buyers, traffickers, treatment, and reform of current practice. The Journal of Human Behavior in the Social Environment, 23, 356–369.

Kidd, S. A., & Liborio, R. M. C. (2011). Sex trade involvement in Sao Paulo, Brazil, and Toronto, Canada: Narra-tives of social exclusion and fragmented identities. Youth & Society, 43, 982–1009.

Kotrla, K. (2010). Domestic minor sex trafficking in the United States. The National Association of Social Workers, 55, 181–187.

Laczko, F., & Gramegna, M. A. (2003). Developing better indicators of human trafficking. The Brown Journal of World Affairs, 10, 179–194.

Lahad, M. (2000). Darkness over the abyss: Supervising crisis intervention teams following disaster. Traumatology, 6, 273–293.

Lev-Weisel, R. (1998). Use of drawing technique to encourage verbalization in adult survivor of sexual abuse. The Arts in Psychotherapy, 25, 257–262.

Loewenstein, G., Weber, E. U., Hsee, C. K., & Welch, N. (2001). Risk as feelings. Psychology Bulletin, 127, 267–286.

Loff, B., & Sanghera, J. (2004). Distortions and difficulties in data for trafficking, The Lancet, 363, 566.

Logan, T. (2007). Human trafficking in Kentucky. Retrieved from

Logan, T. K., Walker, R., & Hunt, G. (2009). Understanding human trafficking in the United States. Trauma, Violence, and Abuse, 10(3), 3–30. doi:10.11777/15249=838008327262

Logan, T. K., Walker, R., Jordan, C. E., & Leukefelt, C. (2006). Women and victimization: Contributing factors, inter-ventions, and implications. Washington, DC: American Psychological Association.

Martinez, O., & Kelle, G. (2013). Sex trafficking of LGBT individuals: A call for service provision, research, and action. International Law News, 42(4), 1–6.

Matheson, C. M., & Finkel, R. (2013). Sex trafficking and the Vancouver winter Olympic games: Perceptions and preventative measures. Tourism Management, 36, 613–628.

Maxfield, L. (2003). Clinical implications and recommendations arising from EMDR research findings. Journal of Trauma Practice, 2, 61–81.

McCarthy, J. A. (2010). Internet sexual activity: A comparison between contact and non-contact child pornography offenders. Journal of Sexual Aggression, 16, 181–195.

McClain, N. M., & Garrity, S. E., (2010). Sex trafficking and the exploitation of adolescents. The Journal of Obstetric, Gynecologic, & Neonatal Nursing, 40, 243–252. doi:10.1111/j.1552-6909.2011.01221.x

Meier, E. P., & Gray, J. (2014). Facebook photo activity associated with body image disturbance in adolescent girls. Cyberpsychology, Behavior, and Social Networking, 17, 199–206. doi:10.1089/cyber.2013.0305

Michikyan, M., Subrahmanyam, K., & Dennis, J. (2014). Can you tell who I am? Neuroticism, extraversion, and online self-presentation among young adults. Computers in Human Behavior, 33, 179–183.

Mitchell, K. J., Finkelhor, D., & Wolak, J. (2010). Conceptualizing juvenile prostitution as child maltreatment:

Findings from the national juvenile prostitution study. Child Maltreatment, 15, 18–36. doi:10.1177/1077559509349443

Najavits, L. M. (2002). Seeking safety: A treatment manual for PTSD and substance abuse. New York, NY: Guilford Press.

National Center for Missing and Exploited Children. (2014). Child sex trafficking. Retrieved from

National Coalition for the Homeless. (2009). LGBT Homeless. Retrieved from

Neville, S., & Martinez, S. (2004). The law of human trafficking. What legal aid providers should know. Clearing-house Review Journal of Poverty Law and Policy, 37, 551–556.

Norcross, J. C., Krebs, P. M., & Prochaska, J. O. (2011). Stages of change. Journal of Clinical Psychology, 67, 143–154. doi:10.1002/jclp.20758

O’Connor, M., & Healy, G. (2006) The links between prostitution and sex trafficking: A briefing handbook. Retrieved from

Oram, S., Stöckl, H., Busza, J., Howard, L. M., & Zimmerman, C. (2012). Prevalence and risk of violence and the physical, mental, and sexual health problems associated with human trafficking: Systematic review. PLOS Medicine, 9(5), 1–13. doi:10.1371/journal.pmed.1001224

Pew Research Center. (2013). Social networking fact sheet. Retrieved from

Polaris. (2015). Recognize the signs. Retrieved from

Polaris. (2016). 2015 NHTRC annual report. Washington, DC: Author. Retrieved from https://humantrafficking

Priebe, A., & Suhr, C. (2005). Hidden in plain view: The commercial sexual exploitation of girls in Atlanta. Atlanta, GA: The Atlanta Women’s Agenda.

Racco, A., & Vis, J.-A. (2015). Evidence based trauma treatment for children and youth. Child and Adolescent Social Work Journal, 32, 121–129.

Rao, S., & Presenti, C. (2012). Understanding human trafficking origin: A cross-country empirical analysis. Feminist Economics, 18, 231–263.

Raphael, J., & Ashley, J. (2008). Domestic sex trafficking of Chicago women and girls. Retrieved from

Raphael, J., & Myers-Powell, B. (2010). From victims to victimizers: Interview with 25 ex-pimps in Chicago. Retrieved from

Raymond, J. G., D’Cunha, J., Dzuhayatin, S. R., Hynes, H. P., Rodriguez, Z. R., & Santos, A. (2002). A comparative study of women trafficked in the migration process: Patterns, profiles, and health consequences of sexual exploita-tion in five countries (Indonesia, the Philippines, Thailand, Venezuela, and the United States). Belgium: Coalition Against Trafficking in Women. Retrieved from

Raynor, C. M. (2002). The role of play in the recovery process. In W. N. Zubenko & J. A. Capozzoli (Eds.), Children and disasters: A practical guide to healing and recovery (pp. 124–134). New York, NY: Oxford University Press.

Reid, J. A., & Jones, S. (2011). Exploited vulnerability: Legal and psychological perspectives on child sex traffick-ing victims. Victims & Offenders, 6, 207–231. doi:10.1080/15564884.2011.557327

Rothschild, B. (2000). The body remembers. New York, NY: W. W. Norton.

Saporta, J. A., & Van der Kolk, B. A. (1992). Psychobiological consequences of trauma. In M. Basoglu (Ed.), Torture and its consequences: Current treatment approaches (pp. 151–181). Cambridge, England: Cambridge University Press.

Shapiro, F. (1989). Efficacy of the eye movement desensitization procedure in the treatment of traumatic memories. Journal of Traumatic Stress, 2, 199–223. doi:10.1002/jts.2490020207

Shared Hope International. (2016). Trafficking terms. Retrieved from


Shelley, L. (2010). Human trafficking: A global perspective. New York: Cambridge Universitiy Press

Silverman, J. G., Decker, M. R., Gupta, J., Maheshwari, A., Patel, V., & Raj, A. (2006). HIV prevalence and pre-dictors among rescued sex-trafficked women and girls in Mumbai, India. Journal of Acquired Immune Deficiency Syndromes, 43, 588–593.

Silverman, J. G., Decker, M. R., Gupta, J., Maheshwari, A., Willis, B. M., & Raj, A. (2007). HIV prevalence and predictors of infection in sex-trafficked Nepalese girls and women. Journal of the American Medical Association, 298, 536–542.

Slayton, S. C., D’Archer, J., & Kaplan, F. (2010). Outcome studies on the efficacy of art therapy: A review of find-ings. Art Therapy: Journal of the American Art Therapy Association, 27(3), 108–119.

Smith, L., Vardaman, S., & Snow, M. (2009). The national report on domestic minor sex trafficking: America’s prostitu-ted children. Retrieved from

Tsutsumi, A., Izutsu, T., Poudyal, A. K., Kato, S., & Marui, E. (2008). Mental health of female survivors of human trafficking in Nepal. Social Science & Medicine, 66, 1841–1847.

Twill, S. E., Green, D. M., & Traylor, A. (2010). A descriptive study on sexually exploited children in residential treatment. Child & Youth Care Forum, 39, 187–199. doi:10.1007/s10566-010-9098-2

U.S. Department of Education. (2013). Human trafficking of children in the United States: A fact sheet for schools. Re-trieved from

U.S. Department of Health and Human Services. (2012). Fact sheet: Human trafficking. Retrieved from

U.S. Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation. (n.d.). Human trafficking into and within the United States: A review of the literature. Retrieved from

U.S. Department of State. (2000). Victims of trafficking and violence protection act of 2000. Retrieved from

U.S. Department of State. (2009). Trafficking in persons report 2010. Washington, DC: Author. Retrieved from

Wagner, A. W., Rizvi, S. L., & Harned, M. S. (2007). Applications of dialectical behavior therapy to the treatment of complex trauma-related problems: When one case formulation does not fit all. Journal of Traumatic Stress, 20, 391–400.

Walsh, S. M., & Donaldson, R. E. (2010). Invited commentary: National safe place: Meeting the immediate needs of runaway and homeless youth. Journal of Youth and Adolescence, 39, 437–445.

Whitaker, M. P., & Hinterlong, J. (2008). Contexts of control: Modern slavery in the United States. Social Develop-ment Issues, 30(3), 27–41.

Widom, C. S., & Kuhns, J. B. (1996). Childhood victimization and subsequent risk for promiscuity, prostitution, and teenage pregnancy: A prospective study. American Journal of Public Health, 86, 1607–1612.

Williams, L. M., & Frederick, M. E. (2009). Pathways into and out of commercial sexual victimization of children: Understanding and responding to sexually exploited teens. Lowell, MA: University of Massachusetts Lowell. Retrieved from

Williamson, C., Karandikar-Chheda, S., Barrows, J., Smouse, T., Kelly, G., Swartz, G., . . . Tame, C. (2010). Ohio trafficking in persons study commission research and analysis sub-committee report on the prevalence of human trafficking in Ohio. Retrieved from

Williamson, C., & Prior, M. (2009). Domestic minor sex trafficking: A network of underground players in the Midwest. Journal of Child & Adolescent Trauma, 2, 46–61.

Wilson, J. M., & Dalton, E. (2007). Human trafficking in Ohio: Markets, responses, and considerations. Retrieved from

Zimmerman, C. (2003). The health risks and consequences of trafficking in women and adolescents: Findings from a European study. London, England: London School of Hygiene & Tropical Medicine. Retrieved from

Zimmerman, C., Hossain, M., Yun, K., Gajdadziev, V., Guzun, N., Tchomarova, M., . . . Watts, C. (2008). The
health of trafficked women: A survey of women entering posttrafficking services in Europe. American Journal of Public Health, 98, 55–59.


Stacey Diane A. Litam is a doctoral candidate at Kent State University and a mental health counselor at Moore Counseling and Mediation Services Inc. Correspondence can be addressed to Stacey Litam, Moore Counseling and Mediation Services, 4600 Carnegie Avenue, Cleveland, Ohio 44103,

The Common Factors Discrimination Model: An Integrated Approach to Counselor Supervision

A. Elizabeth Crunk, Sejal M. Barden

Numerous models of clinical supervision have been developed; however, there is little empirical support indicating that any one model is superior. Therefore, common factors approaches to supervision integrate essential components that are shared among counseling and supervision models. The purpose of this paper is to present an innovative model of clinical supervision, the Common Factors Discrimination Model (CFDM), which integrates the common factors of counseling and supervision approaches with the specific factors of Bernard’s discrimination model for a structured approach to common factors supervision. Strategies and recommendations for implementing the CFDM in clinical supervision are discussed.

Keywords: supervision, common factors, specific factors, discrimination model, counselor education

Clinical supervision is a cornerstone of counselor training (Barnett, Erickson Cornish, Goodyear, & Lichtenberg, 2007) and serves the cardinal functions of providing support and instruction to supervisees while ensuring the welfare of clients and the counseling profession (Bernard & Goodyear, 2014). Numerous models of clinical supervision have been developed, varying in emphasis from models based on theories of psychotherapy, to those that focus on the developmental needs of the supervisee, to models that emphasize the process of supervision and the various roles of the supervisor (Bernard & Goodyear, 2014). However, despite the abundance of available supervision models, there is little evidence to support that any one approach is superior to another (Morgan & Sprenkle, 2007; Storm, Todd, Sprenkle, & Morgan, 2001). Thus, a growing body of clinical supervision literature underscores a need for strategies that integrate the most effective elements of supervision models into a parsimonious approach rather than emphasizing differences between models (Lampropoulos, 2002; Milne, Aylott, Fitzpatrick, & Ellis, 2008; Morgan & Sprenkle, 2007; Watkins, Budge, & Callahan, 2015). Common factors models of supervision bridge the various approaches to supervision by identifying the essential components that are shared across models, such as the supervisory relationship, the provision of feedback, and supervisee acquisition of new knowledge and skills (Milne et al., 2008; Morgan & Sprenkle, 2007). Other common factors approaches to supervision draw on psychotherapy outcome research, aiming to extrapolate common factors of counseling and psychotherapy—such as the therapeutic relationship and the instillation of hope—to clinical supervision approaches (Lampropoulos, 2002; Watkins et al., 2015)

Although reviews of the supervision literature allude to commonalities among supervision approaches (Bernard & Goodyear, 2014), there is a dearth of published literature offering practical strategies for bridging common factors of counseling and supervision. Perhaps even more limited is literature that addresses the necessary convergence of both common and specific factors, or the integration of common factors of supervision with particular interventions that are applied in various supervision approaches (e.g., role-playing or Socratic questioning; Watkins et al., 2015). In a recent article, Watkins and colleagues (2015) proposed a supervision model that extrapolates Wampold and Budge’s (2012) psychotherapy relationship model to specific factors of supervision, encouraging supervisors to apply such relationship common factors to some form of supervision. However, there remains a need for a structured approach to supervision that integrates the common factors of counseling and supervision with the specific factors of commonly used, empirically supported models of clinical supervision.

Because the common factors are, by definition, elements that are shared among theories of counseling and supervision, it can be argued that common factors approaches can be applied to almost any supervision model. However, we argue for the integration of common factors with the discrimination model for several reasons. First, the relationship has been found to be the essential common factor shared among counseling (Lambert & Barley, 2001; Norcross & Lambert, 2014) and supervision approaches, and is often cited as the most critical element of effective supervision and other change-inducing relationships, such as counseling, teaching and coaching (Lampropoulos, 2002; Ramos-Sánchez et al., 2002). The supervisory roles of teacher, counselor and consultant are built into the discrimination model, providing supervisors with natural avenues for fostering a strong supervisory relationship. However, the proposed Common Factors Discrimination Model (CFDM) expands on the discrimination model by providing specific recommendations for how supervisors might use such roles as opportunities for developing and maintaining the supervisory relationship. Second, we consider Bernard’s (1979, 1997) discrimination model to lend itself well to common factors approaches to supervision, as both are concerned with process aspects of supervision, such as tailoring supervision interventions to the needs of the supervisee. Finally, because the discrimination model is widely used by practicing supervisors (Timm, 2015), common factors approaches are likely to fit naturally with customary supervision practices of more experienced supervisors who espouse the discrimination model, yet the CFDM is concise enough for novice supervisors to grasp and apply. Thus, the purpose of this manuscript is to build on Watkins and colleagues’ (2015) model by presenting the CFDM, an innovative approach to supervision that converges common factors identified in both counseling and supervision and integrates them with the specific factors of Bernard’s (1979, 1997) discrimination model. Specifically, we will (a) review the relevant literature on common factors approaches to counseling and supervision and the discrimination model; (b) provide a rationale for a model of supervision that integrates the specific factors of the discrimination model with a common factors approach; and (c) offer strategies and recommendations for applying the CFDM in clinical supervision.

The Common Factors Approach

The notion of therapeutic common factors resulted from psychotherapy outcome research suggesting that psychotherapies yield equivalent outcomes when compared against each other and, thus, what makes psychotherapy effective is not the differences between therapies, but rather the commonalities among them (Lambert, 1986). Wampold’s (2001) landmark research revealed that the theoretical approach utilized by the therapist (e.g., psychodynamic therapy) explained less than 1% of therapy outcome. In light of these findings, researchers and clinicians have been urged to minimize the importance placed on specific clinical techniques and interventions; instead, an emphasis on the commonalities among therapies that are associated with positive outcomes (Norcross & Lambert, 2011), such as the therapeutic alliance, empathy, positive regard, and collaboration within the therapeutic relationship (Norcross & Lambert, 2014; Norcross & Wampold, 2011), is more useful for describing therapeutic changes.

Among the most influential common factors approaches is Lambert’s model of therapeutic factors (see Lambert & Barley, 2001, for a review). Although lacking in stringent meta-analytic or statistical methods, Lambert and Barley (2001) presented four primary factors that are shared among therapeutic approaches (with the percentage that each factor contributes to therapy outcome indicated): (a) extratherapeutic factors (i.e., factors associated with the client, as well as his or her environment; 40%); (b) common factors (i.e., relationship factors such as empathy, warmth, positive regard, supporting the client in taking risks; 30%); (c) placebo, hope, and expectancy factors (i.e., the client’s hope and expectancy for improvement, as well as trust in the treatment; 15%); and (d) skills/techniques factors (i.e., components specific to various therapies, such as empty chair or relaxation techniques; 15%). Although a variety of common factors have been identified in the psychotherapy outcome research, numerous meta-analyses have identified the therapeutic relationship as the sine qua non (Norcross & Lambert, 2011, p. 12) of common factors that account for positive outcomes irrespective of the specific treatment utilized (Norcross & Wampold, 2011). They stated: “although we deplore the mindless dichotomy between relationship and method in psychotherapy, we also need to publicly proclaim what decades of research have discovered and what tens of thousands of relational therapists have witnessed: The relationship can heal” (Norcross & Lambert, 2014, p. 400).

Although the common factors are necessary for producing positive counseling outcomes, this does not mean that specific factors are irrelevant (Norcross & Lambert, 2011). On the contrary, prior research indicates that engaging in specific treatment interventions is associated with the working alliance and with positive counseling outcomes (Tryon & Winograd, 2011; Wampold & Budge, 2012). Watkins and colleagues (2015) noted that treatment interventions are necessary in maintaining client hope and expectations for positive counseling outcomes, stating, “The specific ingredients create benefits through the common factor of expectations, and respecting that interdependent common/specific factor dynamic is vital to treatment outcome” (p. 221).

Common Factors Approaches to Supervision

Although the concept of common factors in counseling and psychotherapy is not a new one and has been the focus of considerable empirical research (Frank, 1982; Lambert & Barley, 2001; Lambert & Ogles, 2004; Rosenzweig, 1936), applying the common factors approach to clinical supervision is relatively novel (Morgan & Sprenkle, 2007). Counseling and clinical supervision are distinct interventions; however, Milne (2006) makes a case for extrapolating findings from psychotherapy research to supervision, as both share common structures and properties of education, skill development, problem-solving and the working alliance. Furthermore, Bernard and Goodyear (2014) noted, “because therapy and supervision are so closely linked, developments in psychotherapy theory inevitably will affect supervision models” (p. 59).

Despite frequent reference to the similarities among supervision models, literature that specifically addresses common factors of supervision approaches is scarce (Bernard & Goodyear, 2014). In our review of the supervision literature, we identified five articles that endorsed common factors approaches to supervision and counselor training (Castonguay, 2000; Lampropoulos, 2002; Milne et al., 2008; Morgan & Sprenkle, 2007; Watkins et al., 2015). Following Castonguay’s (2000) seminal work on training in psychotherapy integration, Lampropoulos (2002) was among the first to address the parallels that exist between common factors of both counseling and supervision, advocating for a theoretically eclectic approach to supervision and for the prescriptive matching of common factors to supervisee needs. For example, Lampropoulos (2002) suggested that supervisors might integrate psychodynamic theory as a means of increasing supervisees’ awareness of countertransference and attachment patterns, or cognitive theory in order to restructure supervisees’ unhelpful thoughts about counseling and supervision.

In contrast to Lampropoulos’s (2002) model, which extrapolates common factors of counseling to supervision, Morgan and Sprenkle (2007) and Milne and colleagues (2008) endorsed approaches that bridge similarities between supervision models. Morgan and Sprenkle (2007) identified a number of common factors among models of supervision, grouping these factors into the following three dimensions falling on their respective continua: (a) emphasis, ranging from specific clinical competence to general professional competence; (b) specificity, ranging from the idiosyncratic needs of supervisees and clients to the general needs of the profession as a whole; and (c) supervisory relationship, ranging from collaborative to directive. The authors (Morgan & Sprenkle, 2007) then proposed a model of supervision that applies these three dimensions of supervision to the supervisor roles of coach, teacher, mentor and administrator. In contrast, Milne and colleagues (2008) conducted a best evidence synthesis of the supervision literature to summarize the current state of empirical research on supervision practices and applied their findings to a basic model of supervision. Although both models (Milne et al., 2008; Morgan & Sprenkle, 2007) contributed viable descriptive models of common factors approaches to supervision, they were limited in providing specific strategies for supervisors to employ in a given situation. Furthermore, neither model specifically addressed the intersection of common factors of counseling and common factors of supervision. Thus, noting that common factors of counseling and specific factors of supervision approaches are interdependently related, Watkins and colleagues (2015) proposed a common/specific factors model, designating the supervisory relationship as the crowning common factor and encouraging supervisors to apply this relationship-centered model to the specific factors of “some form of supervision” (Watkins et al., 2015, p. 226). Following Watkins and colleagues’ recommendations, we therefore present an integrated approach to supervision by applying the common factors of counseling and supervision to the specific factors of the discrimination model.

 The Discrimination Model

The discrimination model (Bernard, 1979, 1997) provides a conceptualization of clinical supervision as both an educational and a relationship process (Bernard & Goodyear, 2014; Borders & Brown, 2005). In essence, the discrimination model involves the dual functions of assessing the supervisee’s skills and choosing a supervisor role for addressing the supervisee’s needs and goals. The supervisee is assessed on three skill areas, or foci: (a) intervention (observable behaviors that the supervisee demonstrates in session, such as demonstration of skills and interventions); (b) conceptualization (cognitive processes, such as the supervisee’s ability to recognize the client’s themes and patterns, as well as the supervisee’s level of understanding of what is taking place in session); and (c) personalization (supervisee self-awareness and ability to adapt his or her own personal style of counseling while maintaining aware-ness of personal issues and countertransference). Furthermore, over 30 years ago, Lanning (1986) proposed the addition of assessing the supervisee’s professional behaviors, such as how the supervisee approaches legal and ethical issues.

When the supervisor has assessed the supervisee’s skill level in each of the three foci, the supervisor utilizing the discrimination model assumes the appropriate role for addressing the supervisee’s needs and goals: (a) teacher (assumed when the supervisor perceives that the supervisee requires instruction or direct feedback); (b) counselor (appropriate for when the supervisor aims to increase supervisee reflectivity, or to process the supervisee’s internal reality and experiences related to his or her professional development or work as a counselor); or (c) consultant (a more collaborative role that is assumed when the supervisor deems it appropriate for the supervisee to think and act more independently, or when the supervisor aims to encourage the supervisee to trust his or her own insights). It is important to note that the supervisor does not take on the singular form of any of the three roles, but rather makes use of the knowledge and skills that are characteristic of each role (Borders & Brown, 2005). The discrimination model is situation-specific; therefore, supervisor roles and foci of assessment might change within a supervision session and across sessions. Consequently, supervisors are advised to remain attuned to the supervisee’s needs in order to attend to his or her most pressing focus area and to assume the most suitable role for addressing these needs rather than displaying strict adherence to a preferred focus or role (Bernard & Goodyear, 2014).

The discrimination model is considered to be an accessible, empirically validated model for supervisors and can be adapted in complexity depending on the supervisor’s level of readiness (Bernard & Goodyear, 2014; Borders & Brown, 2005). Using multidimentional scaling in an empirical study of the discrimination model, Ellis and Dell (1986) provided validation for both the teacher and counselor roles, although the consultant role did not emerge as a distinct role. Their findings are consistent with other studies that provided support for the teacher and counselor roles, but not for the consultant role (Glidden & Tracey, 1992; Goodyear, Abadie, & Efros, 1984; Stenack & Dye, 1982). Thus, the consultant role might be more difficult to distinguish from the teaching and counseling roles, perhaps, as Bernard and Goodyear (2014) noted, because the consultant role requires supervisors to put aside their position of expert or therapist and act more collaboratively with their supervisees. Ellis and Dell provided an alternate (and conflicting) explanation, suggesting that consultation might be an underlying component of both the teaching and counseling roles. These findings indicate a need for future research and possible modification of the discrimination model; however, the discrimination model is generally supported by empirical research.

Rationale for an Integrated Model

Watkins and colleagues (2015) stated: “Akin to the ‘great psychotherapy debate’ about effectiveness (Wampold, 2001), a ‘great psychotherapy supervision debate’ about effectiveness is eminently likely” (p. 17). Several cross-cutting models of clinical supervision have been proposed (Milne et al., 2008; Morgan & Sprenkle, 2007), as well as models that extrapolate common factors of counseling to supervision practices (Lampropoulos, 2002; Watkins et al., 2015); however, there has yet to be a model that systematically converges both. Given the abundance of empirical support for common factors in counseling, we have conceptualized a new model, the CFDM, to integrate a supervision approach that is grounded in effective counseling and supervision practices. Furthermore, Watkins and colleagues encouraged supervisors to apply common factors of counseling to the specific factors of some form of supervision; however, to our knowledge, no such model integrating common factors with the specific factors of an empirically supported model of supervision has been published. Thus, the CFDM combines essential factors of supervision models, converges them with common factors of counseling approaches, and applies them to the specific factors of Bernard’s (1979, 1997) discrimination model for a structured approach that bridges effective elements of both counseling and supervision.

Bernard and Goodyear (2014) pointed to the supervisory relationship as one of the most essential factors in supervision; however, a major criticism of the discrimination model is that the model itself does not thoroughly address the supervisory relationship (Beinart, 2004). Similarly, Freeman and McHenry (1996) found that supervisors ranked the development of clinical skills as their top goal for supervising counselors-in-training and identified that supervision involves taking on the roles of teacher, challenger and supporter, but relationship building did not surface as an emphasis of counselor supervision (Bell, Hagedorn, & Robinson, 2016). Thus, the CFDM builds on the discrimination model by incorporating tenets of the supervisory relationship that are consistent with common factors of counseling and supervision, such as the working alliance (Bordin, 1983), the real relationship (Watkins, 2015), and the instillation of hope (Lambert & Barley, 2001; Lampropoulos, 2002). Historically, the supervision literature suggests that novice supervisors, in particular, might manage feelings of self-doubt and uncertainty by employing a highly structured supervision style, focusing on providing supervisees with feedback on counseling techniques or client diagnosis and placing less emphasis on attending to the supervisory relationship (Hess, 1986; Hess & Hess, 1983). Furthermore, whereas building rapport is a top priority in many therapeutic relationships, counselor supervisors might prioritize other factors instead, such as scheduling, paperwork, and evaluation, before establishing a relationship with the supervisee (Bell et al., 2016). Because the discrimination model is a widely used approach to supervision (Timm, 2015), experienced counselors who wish to incorporate common factors of supervision and counseling into their customary supervision practice will likely find the CFDM to be an intuitive supervision approach. The following section provides a description of the four primary tenets of the CFDM, as well as strategies and recommendations for applying the CFDM in supervision.

The Common Factors Discrimination Model

The CFDM is an innovative model of supervision that aims to integrate the common factors of counseling and supervision with the specific factors of Bernard’s (1979, 1997) discrimination model for a structured, relationship-centered approach to clinical supervision. The CFDM builds on existing supervision models that extrapolate common factors of counseling to supervision practices (Lampropoulos, 2002; Watkins et al., 2015). The CFDM also draws on the discrimination model (Bernard, 1979, 1997) as a method of assessing supervisee needs and tailoring feedback and support accordingly. Although the melding of common factors with the discrimination model has yet to be empirically tested as an integrated approach to supervision, both approaches have received substantial empirical support as standalone models. Empirical research supports common factors approaches to counseling and other change-inducing relationships; however, the CFDM’s underpinnings in the more prescriptive discrimination model provide a structured approach to common factors supervision. In addition, there is evidence to suggest the effectiveness of common factors approaches across cultures (Dewell & Owen, 2015).

We have proposed a model that combines effective common factors of counseling and supervision with the specific factors of Bernard’s (1979, 1997) widely used, empirically supported and accessible discrimination model for a structured approach to common factors supervision. The primary tenets of the CFDM were derived by reviewing the literature on common factors models of supervision and purposively selecting the most common elements, including: (a) development and maintenance of a strong supervisory relationship, (b) supervisee acquisition of new knowledge and skills, (c) supervisee self-awareness and self-reflection, and (d) assessment of supervisees’ needs and the provision of feedback based on the tenets of Bernard’s (1979, 1997) discrimination model. The following section provides a brief fictional case illustration followed by specific strategies for applying the CFDM to supervision. Specific examples for matching common factors with tenets of the discrimination model are provided in Table 1, based on an illustrative case example, followed by a discussion of the primary tenets of the case to the CFDM.


Case Illustration

André, a master’s student in mental health counseling, is completing his first semester of clinical practicum at his university’s community counseling center. Although André demonstrates competency across many clinical and professional domains, as a novice counselor trainee he struggles with reflecting feeling with clients in session. His supervisor has noticed that André tends to sidestep emotional topics in session and, instead of reflecting feeling, responds to emotional content by asking the client unrelated questions or by changing the subject. In the few instances in which he has attempted to reflect feeling, André has been inaccurate in his reflections, undershooting the intensity of the client’s feelings or misreading the client’s emotions altogether. This has sometimes led to tension and frustration between André and his clients. Using the CFDM, his supervisor might utilize the following strategies in supervision with André. In the following section, the case of André is discussed, integrating the primary tenets of the CFDM.


Application of the CFDM

The Supervisory Relationship

Bernard and Goodyear (2014) suggested that the supervisory relationship is a critical factor in effective supervision, regardless of the model of supervision that is followed. Thus, the central tenet of the CFDM is the development of a collaborative supervisory relationship that is characterized by the Rogerian conditions of empathy, genuineness, and unconditional positive regard (Lampropoulos, 2002). Utilizing the CFDM with André, the supervisor approaches her supervisory roles of teacher, counselor and consultant with warmth and acceptance as she addresses André’s difficulty reflecting feeling with his client, rather than using a confrontational or critical approach. Furthermore, she explores with André his personal experiences with emotion, taking into consideration his background and cultural factors that could play a role in his relationship with emotion.

The real relationship. The real relationship (Lampropoulos, 2002; Watkins, 2015) refers to a supervisory relationship that is unaltered by transference or countertransference and is characterized by empathy, warmth, genuineness, unconditional positive regard and trust. The expression of humor and optimism also is recommended in developing a common factors-influenced supervisory relationship. Extrapolating from Gelso’s (2014) tripartite model of the psychotherapy relationship, Watkins (2015) defined the real relationship as “the personal relationship between supervisor and supervisee marked by the extent to which each is genuine with the other and perceives/experiences the other in ways that befit the other” (p. 146). Factors of the real relationship are critical in supervision, as they allow supervisees to develop trust in the supervisory relationship and provide safety for supervisees to disclose vulnerabilities, mistakes and personal concerns (Storm et al., 2001).

Because the evaluative and hierarchical nature of supervision might make the supervisory relationship vulnerable to supervisory ruptures (Burke, Goodyear, & Guzzardo, 1998; Nelson & Friedlander, 2001; Safran, Muran, Stevens, & Rothman, 2007), the CFDM utilizes a collaborative evaluation process (Rønnestad & Skovholt, 1993), in which supervisees have the opportunity to practice evaluating their skills independently throughout their training either by journaling or by completing an evaluation form about their session and submitting their self-evaluation to their supervisor. Supervisee self-evaluations are then processed in supervision. The CFDM supervisor in the case illustration might use this strategy with André to allow him to raise self-awareness and to receive regular feedback on his skills. Furthermore, assuming the teacher role of the discrimination model, his supervisor might direct André to conduct a self-assessment of his reflections of feeling following each session, which he could bring into supervision to discuss and receive her feedback.

Because the supervisory relationship is the central tenet of the CFDM, it is advisable to evaluate and monitor the relationship throughout supervision. Furthermore, Lampropoulos (2002) recommended that supervisors identify and attempt to repair ruptures as soon as possible, as ruptures can be deleterious to supervision process and outcome. One such measure for evaluation of the supervisory relationship is the Supervisory Relationship Questionnaire (SRQ; Palomo, Beinart, & Cooper, 2010), a 67-item assessment of the supervisee’s perceptions of the supervisory relationship. Other plausible measures include the Working Alliance Inventory (Bahrick, 1990) and the Revised Relationship Inventory (Schacht, Howe, & Berman, 1988). Allowing André to assess the supervisory relationship and give his supervisor feedback can provide insight into André’s perception of their relationship and can allow the supervisor to consider making changes in her approach, if necessary. This also conveys to André that his feedback is valuable and that their supervisory relationship is collaborative.

The working alliance. The working alliance in supervision refers to the collaborative development of goals and tasks for supervision (Bordin, 1983; Constantino, Castonguay, & Schut, 2002; Lampropoulos, 2002). The working alliance is established in the CFDM by collaboratively developing a supervision contract between the supervisor and the supervisee (Lampropoulos, 2002) at the very beginning of the supervisory relationship. Goals for supervision that are addressed in the contract include evaluating supervisees’ strengths and areas for growth and identifying specific skills to be learned, as well as issues related to supervisee theoretical orientation. The tasks used to reach these goals can include process notes, live supervision, and interpersonal process recall (IPR; Kagan & Kagan, 1997) as a collaborative approach to processing André’s strengths and areas for growth, and for facilitating André’s self-reflection and self-awareness. The purpose of these tasks is to provide structure and opportunities for instruction, feedback, and evaluation, while allowing the supervisee to engage in self-evaluation, application of new skills, corrective action, and exploration of alternative approaches. The CFDM draws from the discrimination model when developing the contract as a means of evaluating supervisee’s three levels of foci (i.e., intervention, conceptualization and personalization). For example, when developing the supervision contract with André, the supervisor would consider André’s current level of competency with regard to techniques and clinical skills, case conceptualization skills, and self-awareness and personal style.

Instillation of hope and the creation of expectations. Frank and Frank (1991) noted the impact of positive expectations and hope in effecting change in counseling. Placebo, hope and expectancy factors emerged as a single common factor among most counseling approaches, with Lambert and Barley (2001) noting that instillation of hope accounts for 15% of client outcome. Watkins (1996) addressed the issue of demoralization in supervision, stating that beginning counselors can experience poor self-efficacy and might feel overwhelmed as they navigate their professional identity development. Watkins (1996) stated that supervisors are able to utilize the supervisory relationship as a means of encouraging supervisees and providing structure within the relationship to foster hope. Recently, Watkins and colleagues (2015) endorsed the creation of expectations and the provision of some method of supervision as a pathway by which supervisee change occurs. CFDM supervisors can incorporate hope and expectancy into supervision by using the consultant role of the discrimination model to explain to supervisees the process of supervision, and by collaborating with supervisees to provide supervision that builds on those expectations. Practical tools that André’s supervisor might implement to promote hope and positive expectations include developing a supervision contract with André or providing him with a professional disclosure statement in order to explain the process of supervision and to set supervisory rituals in motion (Watkins et al., 2015). Lampropoulos (2002) also suggested setting short- and long-term goals with supervisees as a means of instilling hope.

Supervisee Self-Awareness and Self-Reflection

An additional tenet of the CFDM is supervisee self-reflection concerning issues that influence professional development (Lampropoulos, 2002). CFDM supervision emphasizes the importance of encouraging supervisees to explore their strengths and areas for growth, and personal issues that might affect their work in counseling, as well as their therapeutic styles (Lampropoulos, 2002; Milne et al., 2008). The CFDM attempts to facilitate supervisee self-reflection by implementing strategies such as collaborative evaluation and the supervision contract (discussed above). Furthermore, the CFDM utilizes IPR (Kagan & Kagan, 1997), in which the supervisor and supervisee watch videotape of a supervisee’s counseling session together, pausing the tape at moments that either the supervisor or supervisee deems critical for further inquiry and processing. Taking on the role of counselor, the supervisor utilized IPR to explore what André was experiencing during that moment of the counseling session that might have prevented him from demonstrating reflection. Consistent with the common factors model, the supervisor confronted André with warmth, empathy and acceptance.

Acquisition of Knowledge and Skills

According to the discrimination model (Bernard, 1979, 1997), one of the primary roles of the supervisor is that of teacher. Thus, in addition to providing support and feedback, supervisors are in a position to impart knowledge and to facilitate supervisees’ acquisition of skills—a factor of supervision that surfaces in the majority of supervision models (Milne et al., 2008; Morgan & Sprenkle, 2007). Lampropoulos (2002) stated that supervisees might learn through direct instruction, through shaping (i.e., gradual learning of a desired behavior) and through their own personal experience. In addition, supervisees have opportunities to learn by imitating the behaviors of their supervisors and other counselors (Lampropoulos, 2002). Given that skills and techniques factors account for 15% of counseling outcome (Lambert & Barley, 2001), supervisors are in a position to model skills and techniques of counseling in supervision as a means of fostering supervisee learning and skill acquisition. Integrating common factors with the discrimination model, André’s supervisor might take on the role of teacher to watch a video clip with André of a recent counseling session in which André struggled to reflect feeling, directing him to role-play with his supervisor other ways that he could respond to his client when emotional content is disclosed. André’s supervisor also could provide him with a list of “feeling words” or other relevant resources in order to help him to increase his awareness of emotion and to broaden his feelings vocabulary.

Assessment of Supervisee Needs and the Provision of Feedback

A final tenet of the CFDM is assessment of supervisee needs and the provision of feedback utilizing the roles and foci presented in the discrimination model. Using the CFDM, the supervisor would implement tailoring (also referred to in the counseling literature as prescriptive matching)—or adapting supervision to fit the characteristics, worldviews and preferences of the supervisee—as would be done with clients in common factors approaches to counseling (Norcross & Halgin, 1997). In their review of the literature on clinical supervision, Goodyear and Bernard (1998) identified attending to supervisees’ individual differences as an essential component of effective supervision. Furthermore, tailoring is inherent in the discrimination model, which recommends matching the supervisor’s role to supervisee needs (Bernard, 1979, 1997). As a beginning clinician, André might express a greater need for structured, directive supervision compared to more experienced supervisees (Stoltenberg, McNeill, & Crethar, 1994). Because André self-disclosed his perception of emotion and how this relates to his identity as a male, his supervisor should include this in her conceptualization of André and how he approaches work with clients. Furthermore, this is a value that she might continue exploring with André in future supervision sessions if it could have an impact on his clinical work with clients. Multiple supervision models have recommended matching supervision to the supervisee’s therapeutic approach and cognitive and learning styles (e.g., level of cognitive complexity; Loganbill, Hardy, & Delworth, 1982; Stoltenberg, 1981), and Norcross and Halgin (1997) suggested beginning the supervisory relationship with a needs assessment to determine the supervisee’s unique needs, goals and preferences for supervision. Although tailoring can pose unique challenges for supervisors providing triadic or group supervision, individual differences such as supervisees’ level of experience, learning goals, gender and ethnicity can be taken into account in these formats.

Table 1

CFDM: Examples of DM Focus and Role Intersections and Common Factors Strategies (CFS)

Supervisor Roles (DM)
Supervision Focus Area (DM) and CFS




Intervention André reports that he is uncertain of how to perform a lethality assessment. André struggles to reflect feeling and meaning with clients. André is interested in using children’s books in session with elementary-aged children.
Common Factors Strategy: Supervisor teaches André the necessary steps of assessing for lethality, then the dyad engage in a role play in which the supervisee tests his new knowledge by performing a lethality assessment with the supervisee acting as the client.(Acquisition of New Knowledge and Skills) Supervisor asks André to reflect on the fact that he demonstrates empathy toward his clients while in supervision but struggles to show empathy by reflecting feeling and meaning in session.(Self-Exploration, Awareness, and Insight) Supervisor provides André with resources for using bibliotherapy in child counseling and offers to help the supervisee brainstorm methods for utilizing this intervention in counseling.(Acquisition of Knowledge and Skills)
Conceptualization André struggles to provide client with accurate diagnosis. André perceives himself as being an ineffective counselor because he has difficulty choosing interventions in session. André requests more information on client stages of change.
Common Factors Strategy: Supervisor and André practice diagnosing fictional clients using case studies from a DSM-5casebook. Supervisor then assigns André homework to practice completing a few case studies independently. Supervisor and André review and discuss André’s answers collaboratively during following supervision session.(Acquisition of Knowledge and Skills) Supervisor reflects supervisee’s feelings of inadequacy, offers encouragement, and normalizes the developmental challenges of supervisees. (Supervisory Relationship – Instillation of Hope and Raising of Expectations) Supervisor assists supervisee with locating information on client stages of change and discusses with supervisee the idea of conceptualizing client’s progress in counseling within the context of the client’s stage of change. (Acquisition of Knowledge of Skills)
Personalization André exhibits behaviors that resemble racial microaggressions. André’s performance anxiety causes him to appear distracted in session. André shares that a client reminds him of his deceased mother.
Common Factors Strategy: Supervisor reviews videotape of session with André and identifies an instance in which he exhibits a microaggression toward client. Supervisor gives André feedback on microaggressions and encourages André to engage in self-reflection on personal biases. (Provision of Feedback) Supervisor reflects André’s feelings of anxiety and asks André to reflect on how his anxiety may be affecting his work with clients. (Supervisory Relationship – The Real Relationship) Supervisor offers to help André process countertransference and communicates to André that he has handled the situation ethically and professionally by sharing with his supervisor his feelings of countertransference toward his client. (Supervisory Relationship and Provision of Feedback)

Practical Challenges and Limitations

Utilization of the CFDM might pose challenges that warrant discussion. For example, the CFDM might intensify the parallel process due to its similarities to the structures and processes of counseling. Moreover, CFDM’s parallels to counseling might blur the lines between supervision and counseling, making it important for supervisors to clearly delineate the role and functions of supervision. Thus, the CFDM endorses utilizing the Rogerian condition of genuineness to facilitate an open, collaborative discussion between the supervisor and supervisee when potentially problematic issues of parallel processing arise in supervision. Furthermore, the CFDM might be vulnerable to challenges in dual relationships, as the various discrimination model roles that the supervisor might assume could blur the lines between the supervisory relationship versus other relationships that the supervisor might have with the supervisee, such as that of instructor. Therefore, supervisors utilizing the CFDM are encouraged to have an open discussion with supervisees from the beginning of supervision concerning the purposes, limitations and boundaries of the supervisory relationship. Such conversations can be facilitated with the use of a professional disclosure statement that outlines the supervisor’s roles (Blackwell, Strohmer, Belcas, & Burton, 2002; Cobia & Boes, 2000).

Because the central tenet of the CFDM is the identified supervisory relationship, a potential challenge that is perhaps inherent in the CFDM is addressing weaknesses and ruptures in the supervisory relationship. The CFDM might also be challenging for supervisors or supervisees who inherently struggle to establish strong supervisory and therapeutic relationships. Supervisees who demonstrate limited ability to establish a strong therapeutic relationship might benefit from direct instruction on behavioral skills that facilitate the therapeutic relationship, such as reflections of feeling and meaning. Lampropoulos (2002) recommended that gatekeeping measures be implemented for students who consistently demonstrate deficiency in establishing a strong therapeutic relationship with clients. Finally, outcome research is indicated to examine the validity of applying common factors principles of psychotherapy to clinical supervision, as well as the empirical merit of an integrated common factors and discrimination model of supervision.


The supervision literature abounds with approaches for supervising counselors; however, there is little evidence that any one approach outperforms another. Common factors approaches to counseling and supervision draw on the components that are shared among models for a parsimonious approach that places emphasis on the factors that are essential in producing positive counseling and supervision outcomes. However, although such factors are necessary, they are not sufficient for yielding positive change. Therefore, Watkins and colleagues (2015) noted the necessity of applying the specific factors of some form of supervision to a common factors approach. We have responded to this call by presenting the CDFM, which integrates the specific factors of Bernard’s (1979, 1997) discrimination model with the most common elements of counseling and supervision approaches: (a) the supervisory relationship, (b) supervisee acquisition of new knowledge and skills, (c) supervisee self-awareness and self-reflection, and (d) assessment of supervisees’ needs and the delivery of feedback according to the tenets of the discrimination model.

Conflict of Interest and Funding Disclosure

The authors reported no conflict of interest or funding contributions for the development of this manuscript.


Bahrick, A. S. (1990). Role induction for counselor trainees: Effects on the supervisory working alliance. Disser-tation Abstracts International, 51, 1484B.

Barnett, J. E., Erickson Cornish, J. A., Goodyear, R. K., & Lichtenberg, J. W. (2007). Commentaries on the ethical and effective practice of clinical supervision. Professional Psychology: Research and Practice, 38, 268–275. doi:10.1037/0735-7028.38.3.268

Beinart, H. (2004). Models of supervision and the supervisory relationship and their evidence base. In I. Fleming & L. Steen (Eds.), Supervision and clinical psychology: Theory, practice, and perspectives (pp. 36–50). New York, NY: Brunner-Routledge.

Bell, H., Hagedorn, W. B., & Robinson, E. H. M. (2016). An exploration of supervisory and therapeutic relation-ships and client outcomes. Counselor Education and Supervision, 55, 182–197. doi:10.1002/ceas.12044

Bernard, J. M. (1979). Supervisor training: A discrimination model. Counselor Education and Supervision, 19, 60–68. doi:10.1002/j.1556-6978.1979.tb00906.x

Bernard, J. M. (1997). The discrimination model. In C. E. Watkins, Jr., Handbook of psychotherapy supervision (pp. 310–327). New York, NY: Wiley.

Bernard, J. M., & Goodyear, R. K. (2014). Fundamentals of clinical supervision (5th ed.). Upper Saddle River, NJ: Pearson Education.

Blackwell, T. L., Strohmer, D. C., Belcas, E. M., & Burton, K. A. (2002). Ethics in rehabilitation counselor super-vision. Rehabilitation Counseling Bulletin, 45, 240–247. doi:10.1177/00343552020450040701

Borders, L. D., & Brown, L. L. (2005). The new handbook of counseling supervision. New York, NY: Routledge.

Bordin, E. S. (1983). A working alliance based model of supervision. The Counseling Psychologist, 11, 35–42. doi:10.1177/0011000083111007

Burke, W. R., Goodyear, R. K., & Guzzardo, C. R. (1998). Weakenings and repairs in supervisory alliances: A multiple-case study. American Journal of Psychotherapy, 52, 450–462.

Castonguay, L. G. (2000). A common factors approach to psychotherapy training. Journal of Psychotherapy Integration, 10, 263–282. doi:10.1023/A:1009496929012

Cobia, D. C., & Boes, S. R. (2000). Professional disclosure statements and formal plans for supervision: Two strategies for minimizing the risk of ethical conflicts in post-master’s supervision. Journal of Counseling & Development, 78, 293–296. doi:10.1002/j.1556-6676.2000.tb01910.x

Constantino, M. J., Castonguay, L. G., & Schut, A. J. (2002). The working alliance: A flagship for the “scientist-practitioner” model in psychotherapy. In G. S. Tryon (Ed.), Counseling based on process research: Applying what we know (pp. 81–131). Boston, MA: Allyn & Bacon.

Dewell, J. A., & Owen, J. (2015). Addressing mental health disparities with Asian American clients: Examining the generalizability of the common factors model. Journal of Counseling & Development, 93, 80–87.

Ellis, M. V., & Dell, D. M. (1986). Dimensionality of supervisor roles: Supervisors’ perceptions of supervision. Journal of Counseling Psychology, 33, 282–291. doi:10.1037/0022-0167.33.3.282

Frank, J. D. (1982). Therapeutic components shared by all psychotherapies. In J. H. Harvey & M. M. Parks (Eds.), Psychotherapy research and behavior change: 1981 Master Lecture Series. Washington, DC: American Psychological Association.

Frank, J. D., & Frank, J. B. (1991). Persuasion and healing: A comparative study of psychotherapy (3rd ed.). Baltimore, MD: Johns Hopkins University Press.

Freeman, B., & McHenry, S. (1996). Clinical supervision of counselors-in-training: A nationwide survey of idea

delivery, goals, and theoretical influences. Counselor Education and Supervision, 36, 144–158. doi:10.1002/j.1556-6978.1996.tb00382.x

Gelso, C. (2014). A tripartite model of the therapeutic relationship: Theory, research, and practice. Psycho-therapy Research, 24, 117–131. doi:10.1080/10503307.2013.845920

Glidden, C. E., & Tracey, T. J. (1992). A multidimensional scaling analysis of supervisory dimensions and their perceived relevance across trainee experience levels. Professional Psychology: Research and Practice, 23, 151–157. doi:10.1037/0735-7028.23.2.151

Goodyear, R. K., Abadie, P. D., & Efros, F. (1984). Supervisory theory into practice: Differential perceptions of

supervision by Ekstein, Ellis, Polster, and Rogers. Journal of Counseling Psychology, 31, 228–237. doi:10.1037/0022-0167.31.2.228

Goodyear, R. K., & Bernard, J. M. (1998). Clinical supervision: Lessons from the literature. Counselor Education and Supervision, 38, 6–22. doi:10.1002/j.1556-6978.1998.tb00553.x

Hess, A. K. (1986). Growth in supervision: Stages of supervisee and supervisor development. The Clinical Supervisor, 4, 51–68. doi:10.1300/J001v04n01_04

Hess, A. K., & Hess, K. A. (1983). Psychotherapy supervision: A survey of internship training practices. Profess-ional Psychology: Research and Practice, 14, 504–513. doi:10.1037/0735-7028.14.4.504

Kagan, H. K., & Kagan, N. I. (1997). Interpersonal process recall: Influencing human interaction. In C. E. Watkins, Jr. (Ed.), Handbook of psychotherapy supervision (pp. 296–309). New York, NY: Wiley.

Lambert, M. J. (1986). Implications of psychotherapy outcome research for eclectic psychotherapy. In J. C. Norcross (Ed.), Handbook of eclectic psychotherapy (pp. 436–462). New York, NY: Brunner-Mazel.

Lambert, M. J., & Barley, D. E. (2001). Research summary on the therapeutic relationship and psychotherapy outcome. Psychotherapy, 38, 357–361.

Lambert, M. J., & Ogles, B. M. (2004). The efficacy and effectiveness of psychotherapy. In M. J. Lambert (Ed.), Bergin & Garfield’s handbook of psychotherapy and behavior change (5th ed., pp. 139–193). New York, NY: Wiley.

Lampropoulos, G. K. (2002). A common factors view of counseling supervision process. The Clinical Supervisor, 21, 77–95. doi:10.1300/J001v21n01_06

Lanning, W. (1986). Development of the supervisor emphasis rating form. Counselor Education and Supervision, 25, 191–196. doi:10.1002/j.1556-6978.1986.tb00667.x

Loganbill, C., Hardy, E., & Delworth, U. (1982). Supervision: A conceptual model. The Counseling Psychologist, 10, 3–42. doi:10.1177/0011000082101002

Milne, D. L. (2006). Developing clinical supervision through reasoned analogies with therapy. Clinical Psychology & Psychotherapy, 13, 215–222. doi:10.1002/cpp.489

Milne, D. L., Aylott, H., Fitzpatrick, H., & Ellis, M. V. (2008). How does clinical supervision work? Using a “best evidence synthesis” approach to construct a basic model of supervision. The Clinical Supervisor, 27, 170–190. doi:10.1080/07325220802487915

Morgan, M. M., & Sprenkle, D. H. (2007). Toward a common-factors approach to supervision. Journal of Marital and Family Therapy, 33, 1–17. doi:10.1111/j.1752-0606.2007.00001.x

Nelson, M. L., & Friedlander, M. L. (2001). A close look at conflictual supervisory relationships: The trainee’s perspective. Journal of Counseling Psychology, 48, 384–395. doi:10.1037/0022-0167.48.4.384

Norcross, J. C., & Halgin, R. P. (1997). Integrative approaches to psychotherapy supervision. In C. E. Watkins, Jr. (Ed.), Handbook of psychotherapy supervision (pp. 203–222). New York, NY: Wiley.

Norcross, J. C., & Lambert, M. J. (2011). Evidence-based therapy relationships. In J. C. Norcross (Ed.), Psycho-therapy relationships that work: Evidence-based responsiveness (2nd ed.) (pp. 3–21). New York, NY: Oxford University Press.

Norcross, J. C., & Lambert, M. J. (2014). Relationship science and practice in psychotherapy: Closing commentary. Psychotherapy, 51, 398–403. doi:10.1037/a0037418

Norcross, J. C., & Wampold, B. E. (2011). Evidence-based therapy relationships: Research conclusions and clinical practices. Psychotherapy, 48, 98–102. doi:10.1037/a0022161

Palomo, M., Beinart, H., & Cooper, M. J. (2010). Development and validation of the Supervisory Relationship Questionnaire (SRQ) in UK trainee clinical psychologists. British Journal of Clinical Psychology, 49, 131–149. doi:10.1348/014466509X441033

Ramos-Sánchez, L., Esnil, E., Goodwin, A., Riggs, S., Touster, L. O., Wright, L. K., . . . Rodolfa, E. (2002). Negative supervisory events: Effects on supervision and supervisory alliance. Professional Psychology: Research and Practice33, 197–202.

Rønnestad, M. H., & Skovholt, T. M. (1993). Supervision of beginning and advanced graduate students of

counseling and psychotherapy. Journal of Counseling & Development, 71, 396–405. doi:10.1002/j.1556-6676.1993.tb02655.x

Rosenzweig, S. (1936). Some implicit common factors in diverse methods of psychotherapy. American Journal of Orthopsychiatry, 6, 412–415. doi:10.1111/j.1939-0025.1936.tb05248.x

Safran, J. D., Muran, J. C., Stevens, C., & Rothman, M. (2007). A relational approach to supervision: Addressing ruptures in the alliance. In C. A. Falender & E. P. Shafranske (Eds.), Casebook for clinical supervision: A competency-based approach (pp. 137–157). Washington, DC: American Psychological Association.

Schacht, A. J., Howe, H. E., & Berman, J. J. (1988). A short form of the Barrett-Lennard relationship inventory for supervisory relationships. Psychological Reports, 63, 699–706. doi:10.2466/pr0.1988.63.3.699

Stenack, R. J., & Dye, H. A. (1982). Behavioral descriptions of counseling supervision roles. Counselor Education and Supervision, 21, 295–304. doi:10.1002/j.1556-6978.1982.tb01692.x

Stoltenberg, C. (1981). Approaching supervision from a developmental perspective: The counselor complexity model. Journal of Counseling Psychology, 28, 59–65. doi:10.1037/0022-0167.28.1.59

Stoltenberg, C. D., McNeill, B. W., & Crethar, H. C. (1994). Changes in supervision as counselors and therapists gain experience: A review. Professional Psychology: Research and Practice, 25, 416–449.

Storm, C. L., Todd, T. C., Sprenkle, D. H., & Morgan, M. M. (2001). Gaps between MFT supervision assumptions and common practice: Suggested best practices. Journal of Marital and Family Therapy, 27, 227–239. doi:10.1111/j.1752-0606.2001.tb01159.x

Timm, M. (2015). Creating a preferred counselor identity in supervision: A new application of Bernard’s dis-crimination model. The Clinical Supervisor, 34, 115–125. doi:10.1080/07325223.2015.1021499

Tryon, G. S., & Winograd, G. (2011). Goal consensus and collaboration. In J. C. Norcross (Ed.), Psychotherapy relationships that work: Evidence-based responsiveness (pp. 153–167). New York, NY: Oxford University Press. doi:10.1093/acprof:oso/9780199737208.003.0007

Wampold, B. E. (2001). The great psychotherapy debate: Models, methods, and findings. Mahwah, NJ: Lawrence Erlbaum Associates.

Wampold, B. E., & Budge, S. L. (2012). The 2011 Leona Tyler Award address: The relationship—and its relation-ship to the common and specific factors of psychotherapy. The Counseling Psychologist, 40, 601–623. doi:10.1177/0011000011432709

Watkins, C. E., Jr. (1996). On demoralization and awe in psychotherapy supervision. The Clinical Supervisor, 14, 139–148. doi:10.1300/J001v14n01_10

Watkins, C. E., Jr. (2015). Extrapolating Gelso’s tripartite model of the psychotherapy relationship to the psycho-therapy supervision relationship: A potential common factors perspective. Journal of Psychotherapy Integration, 25, 143–157. doi:10.1037/a0038882

Watkins, C. E., Jr., Budge, S. L., & Callahan, J. L. (2015). Common and specific factors converging in psycho-therapy supervision: A supervisory extrapolation of the Wampold/Budge psychotherapy relationship model. Journal of Psychotherapy Integration, 25, 214–235. doi:10.1037/a0039561

A. Elizabeth Crunk is a doctoral candidate at the University of Central Florida. Sejal M. Barden is an Assistant Professor at the University of Central Florida. Correspondence can be addressed to Elizabeth Crunk, University of Central Florida, College of Education and Human Performance, Department of Child, Family, and Community Sciences, 4000 Central Florida Blvd., P.O. Box 161250, Orlando, FL 32816-1250,

Moving Beyond Debate: Support for CACREP’s Standard Requiring 60 Credit Hours for School Counseling Programs

Clare Merlin, Timothy Pagano, Amanda George, Cassandra Zanone, Benjamin Newman

The Council for Accreditation of Counseling and Related Educational Programs (CACREP) recently released its 2016 standards. Included in these standards is a requirement for school counseling master’s programs to have a minimum of 60 credit hours by the year 2020. This credit hour requirement is an increase from the previous 48-hour requirement and has caused considerable debate in the counselor education field. In this article, the authors assert that the credit hour increase will lead to positive or neutral effects for school counseling programs and benefit the field of school counseling as a whole. This claim is supported by historical examples, anticipated benefits to school counseling, and findings from a pilot study with school counseling programs that previously transitioned to 60 credit hours (N = 22).


Keywords: CACREP, accreditation, school counseling, counselor education, credit hours


The unification of the counseling profession is an aspiration long held within the field (American Counseling Association, 2009; Bobby, 2013; Simmons, 2003). However, historic differences in Council for Accreditation of Counseling and Related Educational Programs (CACREP) standards for completion of a counseling degree complicate a singular identity for the profession. Without a unified expectation of degree requirements, professionals who identify as “counselors” struggle to find a consentient definition for the counseling role. In order to reach unification in the field, it is necessary for counseling organizations and professionals to agree on the minimum credit requirements needed to obtain a counseling degree (Bobby, 2013; Williams, Milsom, Nassar-McMillan, & Pope, 2012).


Minimum credit requirements for a school counseling degree gained recent attention as CACREP released updated standards in 2016, including a new standard (1.J.) requiring 60 semester credit hours for all counseling specializations, including school counseling, rather than the previous 48-credit hour requirement (CACREP, 2015). CACREP designed this standard to create unity among program specialties so that all specialties—addictions counseling, career counseling, clinical mental health counseling, clinical rehabilitation counseling, college counseling and student affairs, marriage, couple, and family counseling, and school counseling—require the same number of credit hours (CACREP, 2015; Williams et al., 2012).


The publication of standard 1.J. has implications for numerous counselor education programs. In 2014, the authors researched the 229 CACREP-accredited school counseling programs in existence  at the time and found that 170 programs, or 74%, required less than 60 credit hours for program completion. Similarly, in a study examining school counselor education programs (N = 126), Perusse, Poynton, Parzych, and Goodnough (2015) found that programs ranged in credit hour requirements from 30 to 67 semester credit hours, with an average of 49.6 credit hours. Sixty-one percent of program coordinators surveyed indicated that they required between 48 and 59 credit hours, whereas only 18% required 60 to 67 credit hours, and 14% required 36 to 45 credit hours. Although only 57% of the sample surveyed was CACREP-accredited, the percentage of participants requiring less than 60 credit hours in their programs in 2015 (75%) indicates that for these programs to become CACREP-accredited or reaccredited, many program coordinators will need to increase credit hours to 60 to meet standard 1.J.


Despite CACREP’s intentions for unification via standard 1.J., the standard’s implications for school counseling programs across the country have led to debate among counselor educators. In this article, the authors acknowledge concerns over the standard’s implications but suggest that an increase in required credit hours for CACREP-accredited school counseling programs will ultimately benefit school counseling programs and the school counseling field as a whole. The authors support this claim with a review of the history of CACREP and credit hour increases, prior research on the topic, results of a pilot study with programs that previously transitioned to 60 credit hours, and anticipated benefits for the school counseling field.




CACREP began in 1981 as a partnership between the Association for Counselor Education and

Supervision (ACES) and the American Personnel and Guidance Association, now known as the American Counseling Association (ACA; Bobby, 2013; Urofsky, Bobby, & Ritchie, 2013). This formation resulted when leaders from ACES, the American School Counselor Association (ASCA), the American College Personnel Association, and American Personnel and Guidance Association created comprehensive accreditation standards for counseling programs (Urofsky et al., 2013). Prior to the formation of CACREP in 1981, the only accreditation for counseling programs was provided by ACES on a voluntary basis (CACREP, 2017).


CACREP was formed to address three purposes: (a) to create guidelines reflecting expectations of the counseling profession, (b) to promote professionalism in counseling, and (c) to increase credibility in the profession (Adams, 2006; Bobby, 1992). More than 30 years later, the central mission of CACREP remains promoting the profession of counseling and related fields via “the development of preparation standards; the encouragement of excellence in program development; and the accreditation of professional preparation programs” (CACREP, 2017, para. 54). Through this process, CACREP provides accreditation to individual programs at the master’s and doctoral levels (CACREP, 2014).


Each area of CACREP accreditation maintains different programmatic standards in addition to a core set of general standards required of all counseling programs. CACREP designed the school counseling standards to prepare graduates to work with K–12 students to effectively address their personal/social, academic and career concerns (CACREP, 2015). CACREP standards appear increasingly valuable as leaders in the counseling profession seek a unified professional identity, particularly in light of the widely varying state licensing standards for counselors (Mascari & Webber, 2013). The CACREP standards serve as universal guidelines of best practices in educating future counselors. Moreover, researched benefits of attending a CACREP-accredited counseling program instead of a non-accredited program may include “increased internship and job opportunities, improved student quality, helpfulness in private practice, increased faculty professional involvement and publishing, and acceptance into a counselor education doctoral program” (Mascari & Webber, 2013, p. 20).


CACREP standards appear particularly relevant in the school counseling profession. In a study of 187 school counselors, on average, participants rated the CACREP school counseling standards as “highly” or “very highly” important to school counseling (Holcomb-McCoy, Bryan, & Rahill, 2002). This finding indicates support for the value of CACREP school counseling standards to the field of school counseling (Branthoover, Desmond, & Bruno, 2010), which is important, given that school counseling programs are the most represented master’s counseling specialty among CACREP-
accredited programs. School counseling programs comprise 36% of all CACREP-accredited programs, nearly 10% more than clinical mental health counseling programs (CACREP, 2016a).


Standards Changes

Despite research on the perceived value and benefits of CACREP standards, multiple facets of CACREP have proven controversial within the counseling profession. These controversies serve as proverbial lightning rods, creating conversation among leaders in the field (Schmidt, 1999). Historically, debate emerged in counselor education due to standards revisions. As in most professions, CACREP regularly modifies its standards to account for changes in the field of counseling (Adams, 2006). To modify the standards, a CACREP standards Revisions Committee formulates revised standards, releases the standards to the public for a comment period, and revises standards according to public feedback. They then release a second draft of revised standards, allow for public comment, and revise the standards accordingly before releasing a final set of revised standards (Williams et al., 2012). Periodic revisions of CACREP standards help counseling leaders address the current and future training needs of professional counselors (Bobby & Urofsky, 2008). These modifications are integral to the development of the counseling profession and parallel other helping professions that regularly revise training standards (Adams, 2006).


     2009 Standards changes. One standards change controversy stems from the counseling profession developing a professional identity independent from counseling psychology and other counseling-
related fields. CACREP 2009 standard I.W.2. indicated that core faculty members preferably are trained in Counselor Education and Supervision doctoral programs (CACREP, 2009).


Research conducted shortly after the standard was published in 2009 demonstrated mixed opinions on the standards change—55% of the 180 counselor educators surveyed agreed or strongly agreed with the standard and 45% disagreed or strongly disagreed with it (Cannon & Cooper, 2010). Although counseling leaders may be attempting to move the field toward unification with standards like I.W.2., standards changes will not transpire without debate in the field.


Around the same time, a second debate emerged when proposed 2009 CACREP standards required community counseling programs to become clinical mental health counseling programs with 60 credit hours, rather than the previous 48-hour community counseling requirement, in order to become accredited (CACREP, 2009). This standard eventually became part of the 2009 CACREP standards, but not before raising fractured dialogue among counselor educators (Henriksen, Van Wiesner, & Kinsworthy, 2008). Henriksen et al. (2008) found opinions among 51 counselor educators in the state of Texas were nearly evenly divided about the issue—49% preferred to keep a 48-credit hour minimum, and 51% preferred a switch to a 60-hour minimum.


Similarly, Cannon and Cooper (2010) surveyed 295 CACREP counselor educators and found that attitudes toward the 2009 standards changes were mixed. They found attitudes toward the credit hour increase differed between community counseling counselor educators and clinical mental health counselor educators. Twenty-seven percent of community counselor educators agreed or strongly agreed with the 48-credit hour requirement, whereas only 4% of clinical mental health counselor educators agreed with the same requirement. Across all participants, 31% indicated satisfaction with the 2009 standard revisions, 38% disagreed or strongly disagreed that they were satisfied with the revisions, and 31% reported indecision. Similar disagreement over standards changes emerged six years later around the 2016 CACREP standards.


2016 Standards changes. On May 12, 2015, CACREP released the 2016 Standards, effective July 1, 2016. These standards are the product of a review process in which a Standards Revision Committee comprised of counselor educators from across the country examined if and how the CACREP Standards needed to be changed to meet the shifting needs of the counseling profession. They also focused on “simplifying, clarifying, and consolidating the existing standards” in their revisions (CACREP, 2012, para. 1). CACREP released the first draft of the 2016 Standards in September 2012 and allowed for public comment. They revised the Standards according to feedback, released the revised draft for further public comment, and revised the standards once more (Williams et al., 2012). The Standards Revision Committee then submitted a final Standards draft to the CACREP Board of Directors for adoption. It was adopted and released in May 2015 (CACREP, 2016b).


The 2016 CACREP standards suggest more equitable education among the different counseling specializations with regard to the required number of credits a student must accrue in order to graduate (CACREP, 2015).  For example, although the 2009 CACREP standards required that the addictions counseling, clinical mental health counseling, and marriage, couple, and family counseling programs had a minimum of 60 semester credit hours, the school counseling, career counseling, and student affairs and college counseling programs required only a minimum of 48 semester credit hours (CACREP, 2009). The proposed 2016 Standards, however, require that all degree programs have a minimum of 60 credit hours by 2020 (CACREP, 2015). In time, these changes aim to unify all counseling specializations (Williams et al., 2012). Such an increase in credits aligns with CACREP’s mission of developing standards that better the profession and affirm a unified identity (Bobby, 2013).


When CACREP published proposed standard 1.J., requiring school counseling programs to have a minimum of 60 credit hours by 2020 (CACREP, 2015), debate arose. At the 2013 ACES School Counseling Interest Network meeting, counselor educators expressed concern about the proposed standard (Transforming School Counseling and College Access Interest Network [TSCCAIN], 2013). Some attendees asserted that mandating an increase to 60 credit hours would disenfranchise low-income students. Attendees argued that an increase in program costs and subsequently, tuition costs, could make counseling less practically desirable to otherwise qualified prospective students. Additionally, some counselor educators stated that increasing the number of credits for school counseling programs would place an undue burden on the training programs themselves by forcing these programs to hire more faculty members to teach additional courses. However, some counselor educators expressed support for the proposed credit hour increase, suggesting the standard could lead to higher quality applicants to school counseling programs and ultimately produce better qualified professionals in the field (TSCCAIN, 2013).


Although concerns about the outcomes of transitioning to 60 credit hours are understandable, when compared to the gains that can be made by increasing credit hours, standard 1.J. appears warranted. Three pieces of evidence support this claim: existing research on credit hour increases, data from a pilot study, and anticipated benefits to the school counseling field.


Existing Research


To date, no research has explored the implications of changing school counseling credit hour requirements from 48 to 60; however, it is beneficial to explore other fields of study to understand trends, long-term effects and the manner in which other researchers have studied this topic. Previous studies either focused on non-counseling fields (T. K. Fagan, personal communication, November 1, 2014) or are in school counseling-related fields, but the research is significantly outdated (Barkley & Percy, 1984; Hollis, 1998).


More than 30 years ago, Barkley and Percy (1984) explored enrollment in counselor education programs. As the most recent individuals to publish on this topic, their research still warrants attention. Barkley and Percy’s study examined the declining rate of applications to counselor education programs (N = 90) in the United States at that time. They used correlation research to examine whether or not relationships existed between the number of applications to programs, program accreditation status, and whether programs had increased credit hours between 1975 and 1983. Barkley and Percy found that although accredited programs in their sample (n = 8) had more applicants than non-accredited programs (n = 77), those that increased credit hours (n = 39) encountered fewer applicants than those that did not (n = 37). They hypothesized that applicants to lower credit hour programs were more interested in attending lower credit requirement schools than higher credit requirement schools (Barkley & Percy, 1984; Hollis, 1998). They found that these relationships were weak, however, and concluded: “There is no evidence from this study to support a hypothesis that seeking accreditation and/or moderate increases in credit hour requirements results in declining enrollments” (Barkley & Percy, 1984, pp. 23–24).


In the related field of school psychology, the National Association of School Psychologists (NASP) is a professional association recognized by the National Council for the Accreditation of Teacher Education as a specialized professional association. NASP began reviewing and approving school psychology programs in 1988. In 2011, approximately 70% of school psychology programs in the United States were NASP-approved (Prus & Strein, 2011). When the NASP credit hour requirement for school psychology programs changed from a master’s degree to a 60-credit hour Educational Specialist (Ed.S.) requirement, programs that adjusted to meet this new requirement received a comparable amount of applications (T. K. Fagan, personal communication, November 1, 2014). This outcome in school psychology suggests that school counseling programs increasing to 60 credit hours also may receive similar numbers of applicants after increasing to 60 credits as they did before increasing credit hours.


Although little research addresses differences between counseling programs before and after credit hour changes, research on CACREP-accredited programs and non-accredited programs may indicate potential differences, given that, on average, accredited programs require more credit hours than non-accredited programs (Hollis, 1998; Mascari & Webber, 2013). In 1998, Hollis compared admissions data from 104 mental health counseling programs and found that on average, CACREP-accredited programs required students to have higher grade point averages for admission (3.02) than non-accredited programs (2.91). Minimum GRE scores for admissions were nearly the same, but graduation rates differed. Despite similar average enrollments across programs, CACREP-accredited programs graduate more students on average than non-accredited programs (Hollis, 1998). This research may indicate potential differences in graduation rates and admission standards between programs with higher and lower credit hour requirements.


These three examples suggest that credit hour increases do not lead to poorer outcomes for programs and may in fact enhance the overall educative experience. Though findings did not include conclusive evidence of benefits from increasing credit hours, the studies showed that after programs increased credit hours, they encountered similar admissions outcomes (Barkley & Percy, 1984; T. K. Fagan, personal communication, November 1, 2014) or improved graduation rates (Hollis, 1998) compared to those measures before increasing credit hours. Consequently, there is no research base to conclude that increasing counseling program credit hours is harmful to counseling programs in admissions or graduation rates.


Pilot Study


Although existing research is consistent, it is outdated. To understand the potential outcomes school counseling programs encounter when they increase credit hours, the authors conducted a pilot study to explore the admissions and job placement data of CACREP-accredited school counseling master’s programs that previously transitioned to 60 credit hours. In 2014, 59 (26%) of the 229 school counseling CACREP-accredited programs required 60 credits or more for program graduates. This number constitutes more than one quarter of all CACREP-accredited school counseling programs, despite CACREP requiring only 48 credit hours at the time. Furthermore, it supports Hollis’ (1998) assertion that counseling programs often increase their required credit hours before higher standards are established. These increases may symbolize support for and valuing of increased credit hours for the benefit of program graduates. The authors collected admissions and job placement data from CACREP program liaisons (henceforth, “participants”) whose school counseling programs previously transitioned to 60 credit hours. They also explored the participants’ perceptions regarding whether transitioning to 60 credit hours impacted program admissions and graduate job placement rates. Though the study was a pilot with limited sample size (N = 22), the exploratory data may prove insightful for school counseling faculty members looking to transition programs to 60 credit hours.  These data also may be helpful for researchers to understand the potential impact of credit hour transitions on programs.


Participants provided data via a 26-item electronic questionnaire. Twenty-four questions addressed quantity of applications, quality of applications (measured by enrolled students’ undergraduate grade point average [GPA], GRE scores, racial demographics, gender demographics, international demographics, and out-of-state demographics [Cassuto, 2016]), and graduate job placement rates. Two open-ended questions explored participants’ perspectives on the topic. The questions read: “From your perspective, what, if any, impact did the transition to a 60-credit graduation requirement for master’s school counseling programs at your institution have on the quantity, quality and diversity of applicants?” and, “What (if any) feedback on the survey would you like to provide to the researchers?”


Positive and Neutral Outcomes

CACREP standard 1.J. established equal credit hour requirements in order to create unity among counseling specialties, thus leading to positive effects for the profession (Williams et al., 2012). In their pilot study, the authors found that all participants contributing program data (n = 7) experienced positive or neutral effects in some items measuring admissions quality, admissions quantity or graduate job placement rates after transitioning to 60 credit hours. Although data indicated mixed experiences for two items, enrolled students’ undergraduate GPAs and GRE scores, in the majority of items participants encountered only positive and neutral effects. These items were: racial diversity of enrolled students, number of enrolled international students, number of enrolled out-of-state students, and job placement rates of program graduates.


Participants who provided comments to open-ended questions (n = 22) contributed further insights on these positive outcomes after transitioning to 60 credit hours. Nine participants explicitly stated that transitioning to a 60-credit hour minimum had a positive impact on their school counseling master’s programs. For example, one participant stated that the 60-credit hour program format “brought better applicants,” and another participant said, “I believe our student applicant pool increased in size as well as improved in quality of applicant.” A third participant indicated the following as a result of changing to 60 credit hours:


The quality of our program increased as did our enrollment. We anticipated an initial drop in enrollment that never materialized. Students told us that they preferred the comprehensive training they would get with a 60-hour program and selected us over other 48-hour programs. Our program grew as a result of moving to 60 hours.


This feedback suggests that for this participant’s program, transitioning to 60 credit hours clearly led to positive results.


Six participants responded to open-ended questions indicating neutral outcomes from transitioning to 60 credit hours. They stated that they did not believe their programs’ transition to a 60-credit hour minimum had an impact on admissions or job placement rates. For example, one participant noted, “The transition from 48 to 60 hours seemed to have no effect whatsoever on the quantity and quality and/or diversity of applicants.” Another participant described the change as having “little to no negative impact” on their program, and another described it as having “minimal impact.” The latter participant wrote, “I see no significant change in applicant qualifications.”


It is notable that three of the items that did not change for any participants—quantity of enrolled international students, quantity of enrolled out-of-state students, and enrolled students’ racial diversity—are items measuring program diversity. This finding suggests that for the participants in this pilot study, the credit hour transition did not impact applicant diversity to their school counseling programs. This may counter the notion that requiring 60 credit hours for program completion will disenfranchise certain students due to increased tuition (TSCCAIN, 2013). In addition, previous research indicates variables such as financial aid packages, faculty contact with prospective students, diverse student populations, and faculty diversity influence the recruitment of diverse students (Guiffrida & Douthit, 2010; Shin, Smith, Goodrich, & LaRosa, 2011; Talleyrand, Chung, & Bemak, 2006). These variables may be more impactful on recruiting diverse students than program credit hours.


Negative Outcomes

Despite the professed intent of CACREP standard 1.J. (Williams et al., 2012), some counselor educators speculated that such credit hour increases would have negative effects on school counseling programs (TSCCAIN, 2013). Of all participants in the pilot study whose programs transitioned to a 60-credit hour requirement, none expressed perceptions that increasing their credit hours led to negative outcomes. This finding suggests opposition to arguments that increasing to 60 credit hours will result in harmful effects in programs. The fact that 22 study participants commented on their transitions to 60 credit hours and none expressed the belief that transitioning caused negative outcomes appears noteworthy.


Descriptive statistics of program data showed that only one item, enrolled students’ gender diversity, decreased or stayed the same when participants’ programs transitioned to 60 credit hours. Although this finding may indicate worsening gender disparity in counseling, recent statistics demonstrate a consistent discrepancy in the number of male and female individuals in the counseling profession (Evans, 2013). According to data from ACA, males consistently comprised only 26–29% of the ACA membership between 2002 and 2012 (Evans, 2013). Given the consistency of these percentages over time, it is reasonable that the participants in this study saw gender diversity decrease or stay the same despite transitioning to 60 credit hours because the construct is one that is stable over time and may not have been impacted by credit hour increases. Similarly, CACREP’s 2015 Annual Report authors noted that only 18% of students enrolled in CACREP programs are male (CACREP, 2016a), adding additional legitimacy to a concern for gender disproportionality in counseling overall and disaffirming concern for decreased gender diversity due to credit hour increases.


Program Factors Impacting Outcomes

In the debate over increasing school counseling program credit hours, dialogue centered on the impact that a credit hour increase might have on programs. However, pilot study findings indicated that when programs previously transitioned to 60 credit hours, program-specific characteristics likely had a greater impact on transition outcomes than the transition itself.  For example, multiple participants indicated that current events during the time of their credit hour transition appeared to impact their program admissions and student job placement rate more than the actual credit hour transition. As one participant explained:


I don’t think the 60 credits had any impact. The year we moved to 60 was right when the economy went bust, so all of our programs experienced a drop in applicants. We tend to be pretty consistent in the quality of our applicants overall as well as in the relative diversity of our applicants.


Other participants noted that their original number of credit hours prior to transitioning to 60 credits likely impacted their program outcomes after transitioning. Several participants worked in school counseling programs that transitioned from 55 or 57 credit hours to 60 credits. They stated that increasing their program requirements by just a few credit hours did not appear to impact their program admissions or graduate job placement rate.


     Another participant indicated school counselors in their state are paid a higher salary if they graduate from 60-credit hour programs. Therefore, offering a school counseling program with a 60-credit hour track helped market the program, the participant reported. If school counseling faculty members work in states in which school counselors receive higher salaries for earning 60 credit hours, then a credit hour increase may lead to more positive changes in admissions than negative ones.


Lastly, hosting other counseling specialties (e.g., clinical mental health, addictions) at a university may impact a school counseling program and its transition to 60 credit hours. One participant noted that their school counseling program increased to a 60-credit hour minimum because the other counseling programs at their institution already required 60 credit hours. This participant said, “We decided to move all programs to 60 hours rather than have the difference in concentrations (in part due to perceptions of why one concentration would require more than the other).” If faculty members are increasing credit hours for school counseling programs at institutions in which other counseling programs already required 60 credit hours, the credit increase may be more widely accepted by potential applicants and lead to neutral or positive outcomes in admissions.


According to pilot study participants, each of these program factors impacted the effects their programs encountered after changing to 60 or more credit hours. Counselor educators leading school counseling programs that have not yet transitioned to 60 credit hours may take note of the factors and examine their own programs’ characteristics that may impact transition outcomes. Counselor educators would benefit from reflecting on the context and characteristics of their programs before concluding that increasing to 60 credit hours will be problematic.


Benefits to School Counselors


As the field of school counseling has evolved, so has the preparation of school counselors-in-training. Such preparation has evolved from an emphasis on vocational guidance (Cinotti, 2014), to training on comprehensive programming (ASCA, 2012; DeKruyf, Auger, & Trice-Black, 2013), to training on leadership and advocacy to create systemic change in schools (Ockerman, Patrikakou, & Feiker Hollenbeck, 2015). Researchers, counselor educators and school counselors are frequently calling for even better training. Recent calls include better preparation in instructional techniques to effectively conduct classroom guidance lessons (Ohrt, Blalock, & Limberg, 2016), collaborative coursework with educational leadership students (Beck, 2016; DeSimone & Roberts, 2016), preparation specific to working in urban areas (Hannon, 2016), suicide assessment practice (Douglas & Wachter-Morris, 2015), training in navigating professional identity issues (Gilbride, Goodrich, & Luke, 2016; Scarborough & Luke, 2008) and improved training in Response to Intervention to advance school counseling services (Ockerman et al., 2015).


In creating CACREP standard 1.J., CACREP has created an opportunity for counselor educators to add coursework that meets these calls and better prepares school counselors-in-training for the needs they will encounter in schools. Counselor educators may want to consider adding courses on the preparation topics called for, such as consultation in school counseling (Ockerman et al., 2015), leadership in school counseling (Beck, 2016; DeSimone & Roberts, 2016), and conducting classroom guidance lessons (Ohrt et al., 2016). In better training future school counselors in these areas, counselor educators can enhance the expertise of school counselors graduating from their programs, and ultimately better support K–12 students.


Lastly, CACREP’s standard 1.J. holds the potential to benefit the school counseling field as a whole. School counselors serve as both counselors and educators in schools and often receive mixed messages about this dual role (Cinotti, 2014). CACREP’s previous school counseling credit hour requirements may have contributed to school counselor role confusion, suggesting that school counselors were not as well-trained as clinical mental health counselors or counselors in other specialties requiring 60 credit hours. In establishing the same credit hour requirements for all counseling programs, CACREP has asserted that school counselors are equally as well-prepared as their colleagues in clinical mental health, marriage and family counseling, addictions counseling, and other specialties. Such an affirmation lends support to the professional standing of school counselors in the counseling field.


Future Research


     With the recent release of the 2016 CACREP standards and the inclusion of standard 1.J. requiring 60 credit hours for school counseling programs, faculty members who work at programs with less than 60 credit hours may want to look to the 59 programs that have already transitioned to 60 credit hours as models for transition. Although counselor educators have understandable concerns about the impact that a credit hour increase may have on school counseling programs, previous research and the authors’ pilot study findings provide limited support for these concerns. Instead, research indicates that on average, school counseling programs may encounter improved outcomes in programs admissions and graduate job placement rates or similar outcomes to those experienced before increasing credit hours. Future research on programs that transition to 60 credits will prove valuable in confirming these outcomes.


To conduct this research, researchers will need longitudinal program data, including ongoing admissions and job placement data, from universities. In collecting data for their pilot study, the authors learned that many school counseling programs do not maintain continuous data on admissions and job placement. Of the 34 participants who initially responded to the pilot study questionnaire, 27 participants could not provide complete quantitative data on program admissions or job placement rates. Many of these participants noted that they were unable to do so because such data were unavailable. Some participants reported that transitioning to 60 credit hours so long ago inhibited them from finding and submitting data; seven participants indicated that they transitioned to 60 credit hours more than 15 years ago.


Reasons for unavailable data varied, but most had to do with the absence of data-keeping over time. One participant wrote, “I apologize that I don’t have concrete data for you. It’s a long time ago that we changed to 60 hours (8 years). I was not program director then.” Another participant explained, “We transitioned almost 30 years ago . . . and it would be impossible to get the information to you.” A different participant highlighted that aggregate data-keeping presented a challenge. They wrote, “I am sorry I cannot answer the first part of this survey. Because we have a counselor-first identity, all program admission processes are in aggregate—we do not have separate data for community counseling students, clinical mental health counseling students, and school counseling students.”


These data-keeping challenges pose an obstacle for future research on the impact of credit hour changes on counseling programs. They also support Shin and colleagues’ (2011) findings that counselor education programs often do not maintain admissions data. In their survey research study of 114 CACREP liaisons, Shin et al. found that although some participants reported maintaining admissions and student race and ethnicity data for up to 20 years, other programs reported keeping this data for as little as one year. Moreover, 57% of participants reported not retaining information on prospective students that declined admission to their programs. Although these data may or may not be related to the impact that credit hour changes have on counseling programs, these data-keeping percentages suggest that counseling programs could benefit from collecting and maintaining data in more thorough and consistent ways.


When conducting research on credit hour increases, researchers may also want to examine data points other than admissions and job placement. When counselor educators devote added credit hours to new coursework, they can consider how this coursework will benefit counselors-in-training, then measure those benefits. For example, if counselor educators devote extra credit hours to coursework in advanced techniques, they should collect and maintain data on the counseling techniques of counselors-in-training before and after transitioning to 60 credit hours. If counselor educators create extra coursework in consultation in schools, advocacy or leadership, these skills can be assessed in students before and after creating the courses. Evaluations from employers of alumni can also be examined to explore if counselor ratings improve after increasing credit hours.


If researchers are to better understand the impact that credit hour changes have on counseling programs, it is imperative that counselor educators regularly collect and store data on program outcomes. If counselor educators can begin doing so before credit hour changes take effect, they may be able to track trends in program outcomes associated with the credit hour changes over time. Researchers would be wise to begin longitudinal studies with programs in order to collect data on an ongoing basis and determine if the credit hour change has any effect. This research could prove useful in informing future CACREP standards, including potential credit hour changes. As Barkley and Percy (1984) recommended more than three decades ago, “Counselor education programs [ought to] begin keeping data on applications, acceptances, and enrollments. . . . These factors are too important to the life of most counselor education programs not to have accurate data readily available” (p. 25).




     In the three and half decades since CACREP was established, credit hour increases for accredited programs have been met with divided reactions from counselor educators (Cannon & Cooper, 2010; Henriksen et al., 2008; TSCCAIN, 2013). The publication of CACREP’s 2016 Standards is no exception. Counselor educators are wise to consider the program implications of any new standard, including standard 1.J. However, to date, no research provides cause to believe that this standard will significantly contribute to negative school counseling program outcomes. To the contrary, previous research indicates program outcomes will improve or stay the same after increasing credit hours, and findings from the authors’ pilot study reflect similarly. Future research can provide further valuable insights on the impact of credit hour increases on counseling programs.


Conflict of Interest and Funding Disclosure
This research study was conducted by the authors and was supported in part by a CACREP Student Research Grant. The article is the sole work of the authors and does not necessarily reflect the beliefs or ideas of CACREP, the CACREP Board of Directors, or CACREP staff.






Adams, S. A. (2006). Does CACREP accreditation make a difference? A look at NCE results and answers. Journal of Professional Counseling: Practice, Theory & Research, 34, 60–76.

American Counseling Association. (2009, January 20). 20/20 statement of principles advances the profession. Retrieved from

American School Counseling Association. (2012). ASCA national model: A framework for school counseling programs (3rd ed.). Alexandria, VA: Author.

Barkley, W., & Percy, R. (1984). Accreditation status, credit hours, and enrollments in master’s degree programs in counseling. Paper presented at the annual convention of the American Association for Counseling and Development, Houston, TX.

Beck, M. J. (2016). Bolstering the preparation of school counselor–principal teams for work with LGBT youth: Recommendations for preparation programs. Journal of LGBT Issues in Counseling, 10, 2–15.

Bobby, C. L. (1992). CACREP accreditation: Setting the standard for counselor preparation. ERIC Digest. (ED 347 470). Ann Arbor, MI: ERIC/CAPS.

Bobby, C. L. (2013). The evolution of specialties in the CACREP standards: CACREP’s role in unifying the profession. Journal of Counseling & Development, 91, 35–43. doi:10.1002/j.1556-6676.2013.00068.x

Bobby, C. L., & Urofsky, R. I. (2008). CACREP adopts new standards. Counseling Today, 51(2), 59–60. doi:10.1002/j.1556-6676.2013.00064.x

Branthoover, H., Desmond, K. J., & Bruno, M. L. (2010). Strategies to operationalize CACREP standards in school counselor education. The Journal of Counselor Preparation & Supervision, 2, 37–47.

Cannon, E., & Cooper, J. (2010). Clinical mental health counseling: A national survey of counselor educators. Journal of Mental Health Counseling, 32, 236–246.

Cassuto, L. (2016, January 31). Inside the graduate-admissions process. The Chronicle of Higher Education. Retrieved from

Cinotti, D. (2014). Competing professional identity models in school counseling: A historical perspective and commentary. The Professional Counselor, 4, 417–425. doi:10.15241/dc.4.5.417

Council for Accreditation of Counseling and Related Educational Programs. (2009). 2009 CACREP accreditation manual. Alexandria, VA: Author.

Council for Accreditation of Counseling and Related Educational Programs. (2012). March 2012 Standards Revision Committee Update. Retrieved from

Council for Accreditation of Counseling and Related Educational Programs. (2014). What is CACREP? Retrieved from

Council for Accreditation of Counseling and Related Educational Programs. (2015). 2016 CACREP standards. Retrieved from

Council for Accreditation of Counseling and Related Educational Programs. (2016a). Annual Report 2015. Retrieved from

Council for Accreditation of Counseling and Related Educational Programs. (2016b). Directory. Retrieved from

Council for Accreditation of Counseling and Related Educational Programs. (2017). About CACREP: A brief history. Retrieved from

DeKruyf, L., Auger, R. W., & Trice-Black, S. (2013). The role of school counselors in meeting students’ mental health needs: Examining issues of professional identity. Professional School Counseling, 16, 271–282.

DeSimone, J. R., & Roberts, L. A. (2016). Fostering collaboration between preservice educational leadership and school counseling graduate candidates. The Journal of Counselor Preparation and Supervision, 8(2), 12–27. doi:10.7729/82.1081

Douglas, K. A., & Wachter Morris, C. A. (2015). Assessing counselors’ self-efficacy in suicide assessment and intervention. Counseling Outcome Research and Evaluation, 6, 58–69.

Evans, M. P. (2013). Men in counseling: A content analysis of the Journal of Counseling & Development and Counselor Education and Supervision 1981–2011. Journal of Counseling & Development, 91, 467–474. doi:10.1002/j.i 556-6676.2013.00119.x

Gilbride, D. D., Goodrich, K. M., & Luke, M. (2016). The professional peer membership of school counselors and the resources used within their decision-making. The Journal of Counselor Preparation and Supervision, 8(2). Retrieved from

Guiffrida, D. A., & Douthit, K. Z. (2010). The Black student experience at predominantly White colleges: Implications for school and college counselors. Journal of Counseling & Development, 88, 311–318. doi:10.1002/j.1556-6678.2010.tb00027.x

Hannon, M. D. (2016). Professional development needs of urban school counselors: A review of the literature. The Journal of Counselor Preparation and Supervision, 8, 139–154. doi:10.7729/82.1171

Henriksen, R. C., Jr., Van Wiesner, V., III, & Kinsworthy, S. (2008). Counselor educators’ perceptions of training requirements. Journal of Professional Counseling: Practice, Theory, & Research, 36, 52–70.

Holcomb-McCoy, C., Bryan, J., & Rahill, S. (2002). Importance of the CACREP school counseling standards: School counselors’ perceptions. Professional School Counseling, 6, 112–119.

Hollis, J. W. (1998). Is CACREP accreditation making a difference in mental health counselor preparation? Journal of Mental Health Counseling, 20, 89–92.

Mascari, J. B., & Webber, J. (2013). CACREP accreditation: A solution to license portability and counselor identity problems. Journal of Counseling & Development, 91, 15–25. doi:10.1002/j.1556-6676.2013.00066.x

Ockerman, M. S., Patrikakou, E., & Feiker Hollenbeck, A. (2015). Preparation of school counselors and response to intervention: A profession at the crossroads. The Journal of Counselor Preparation and Supervision, 7, 161–184. doi:10.7729/73.1106

Ohrt, J. H., Blalock, S., & Limberg, D. (2016). Preparing school counselors-in-training to conduct large group developmental guidance: Evaluation of an instructional model. The Journal for Specialists in Group Work, 41, 96–116. doi:10.1080/01933922.2016.1146377

Perusse, R., Poynton, T. A., Parzych, J. L., & Goodnough, G. E. (2015). Changes over time in Masters level school counselor education programs. The Journal of Counselor Preparation and Supervision, 7(3), 1–22. doi:10.7729/73.1072

Prus, J. S., & Strein, W. (2011). Issues and trends in the accreditation of school psychology programs in the United States. Psychology in the Schools, 48, 887–900.

Scarborough, J. L., & Luke, M. (2008). School counselors walking the walk and talking the talk: A grounded theory of effective program implementation. Professional School Counseling, 11, 404–416.

Schmidt, J. J. (1999). Two decades of CACREP and what do we know? Counselor Education and Supervision, 39, 34–45. doi:10.1002/j.1556-6978.1999.tb01788.x

Shin, R. Q., Smith, L. C., Goodrich, K. M., & LaRosa, N. D. (2011). Attending to diversity representation among Council for Accreditation of Counseling and Related Educational Programs (CACREP) master’s programs: A pilot study. International Journal for the Advancement of Counselling, 33, 113–126.


Simmons, J. (2003). A golden opportunity: The 1950s. In D. R. Coy, V. L. Sheeley, & D. W. Engels (Eds.), American Counseling Association: A 50-year history 1952–2002 (pp. 9–12). Alexandria, VA: American Counseling Association.

Talleyrand, R. M., Chung, R. C.-Y., & Bemak, F. (2006). Incorporating social justice in counselor training programs: A case study example. In R. L. Toporek, L. H. Gerstein, N. A. Fouad, G. Roysircar, & T. Israel (Eds.), The handbook for social justice in counseling psychology: Leadership, vision, and action (pp. 44–58). Thousand Oaks, CA: Sage.

Transforming School Counseling and College Access Interest Network. (2013, October). Minutes of the TSCCAIN Meeting. Denver, CO.

Urofsky, R. I., Bobby, C. L., & Ritchie, M. (2013). Introduction to Special Section. Journal of Counseling & Development, 91, 3–5. doi:10.1002/j.1556-6676.2013.00064.x

Williams, D. J., Milsom, A., Nassar-McMillan, S., & Pope, V. T. (2012). 2016 CACREP standards revision committee at turn one. Counseling Today, 55(5), 56.


Clare Merlin, NCC, is an Assistant Professor at the University of North Carolina at Charlotte. Timothy Pagano, NCC, is a doctoral candidate at the University of North Dakota. Amanda George, NCC, is a Professional School Counselor for Loudon County Public Schools in Sterling, VA. Cassandra Zanone, NCC, is a J.D. candidate at the University of California at Los Angeles. Benjamin Newman, NCC, is a doctoral student at the College of William and Mary. Correspondence can be addressed to Clare Merlin, 9201 University City Boulevard, Charlotte, NC, 28223,