Aug 10, 2022 | Volume 12 - Issue 2
Lacey Ricks, Malti Tuttle, Sara E. Ellison
Quantitative methodology was utilized to assess factors influencing veteran school counselors’ decisions to report suspected child abuse. Veteran school counselors were defined as having 6 or more years of experience working as a school counselor within a public or private school. This study is a focused examination of the responses of veteran school counselors from a larger data set. The results of the analysis revealed that academic setting, number of students within the school, and students’ engagement in the free or reduced lunch program were significantly correlated with higher reporting among veteran school counselors. Moreover, veteran school counselors’ self-efficacy levels were moderately correlated with their decision to report. Highly rated reasons for choosing to report suspected child abuse included professional obligation, following school protocol, and concern for the safety of the child. The highest rated reason for choosing not to report was lack of evidence. Implications for training and advocacy for veteran school counselors are discussed.
Keywords: child abuse, reporting, veteran school counselors, self-efficacy, training
In 2019, approximately 4.4 million reports alleging maltreatment were made to U.S. child protective services (U.S. Department of Health & Human Services [HHS] et al., 2021). Of these reports, nearly two thirds were made by professionals who encounter children as a part of their occupation. Child maltreatment is identified as all types of abuse against a child under the age of 18 by a parent, caregiver, or person in a custodial role, and includes physical abuse, sexual abuse, emotional abuse, and neglect (Fortson et al., 2016). Public health emergencies, such as the continued COVID-19 pandemic, increase the risk for child abuse and neglect due to increased stressors (Swedo et al., 2020). Factors such as financial hardship, exacerbated mental health issues, lack of support, and loneliness may contribute to increased caregiver distress, ultimately resulting in negative outcomes for children and adolescents (Collin-Vézina et al., 2020).
The psychological impact of child abuse and neglect on victims can increase the risk of mental health disorders such as depression, anxiety, eating disorders, and post-traumatic stress disorder (Heim et al., 2010; Klassen & Hickman, 2022). Similarly, trauma experienced in childhood is associated with higher rates of long-term physical health issues when compared to individuals with less trauma; these include cancer (2.4 times more likely to develop), diabetes (3.0 times as likely to develop), and stroke (5.8 times more likely to experience; Bellis et al., 2015). Children who are victims of child abuse and neglect may also experience educational difficulties, low self-esteem, and trouble forming and maintaining relationships (Child Welfare Information Gateway, 2019).
Voluntary disclosure of childhood abuse is relatively uncommon; one study found that less than half of adults with histories of abuse reported disclosing the abuse to anyone during childhood, and only 8%–16% of those disclosures resulted in reporting to authorities (McGuire & London, 2020). For this reason, mandated reporting by professionals is an integral piece of child abuse prevention. School counselors, by virtue of their ongoing contact with children, are uniquely positioned to identify and report child abuse (Behun et al., 2019). We recognize that school-based professionals such as teachers, administrators, and other school-based staff are mandated reporters as well. However, for the purpose of this article, we specifically focus on school counselors based on their role, responsibility, and training that best equips them to fulfill this expectation. School counselors have a unique role within the school system and play a critical role in ensuring schools are a safe, caring environment for all students (American School Counselor Association [ASCA], 2017). School counselors also work to identify the impact of abuse and neglect on students as well as ensure the necessary supports for students are in place (ASCA, 2021).
Ethical and Legal Mandates for Reporting Suspected Child Abuse
Although current estimates for the reporting frequency within schools are not available, it appears likely that high numbers of school counselors encounter the decision to report suspected child abuse each year. In fact, a 2019 survey of 262 school counselors indicated that 1,494 cases of child abuse had been reported by participants over a 12-month period (Ricks et al., 2019). Despite the frequency with which it occurs, reporting can be a distressing part of school counselors’ responsibilities (Remley et al., 2017); this could be because of limited knowledge or competency in reporting procedures, unfamiliarity with the law, or potential repercussions for the child (Bryant, 2009; Bryant & Milsom, 2005; Lambie, 2005). Additionally, laws, definitions, and mandates of child abuse and neglect vary by state; therefore, confusion may arise when school counselors relocate to another area (ASCA, 2021; Hogelin, 2013; Lambie, 2005; Tuttle et al., 2019). School counselors need to identify and familiarize themselves with the unique laws in their state in addition to reviewing federal law and ethical codes.
Federally, school counselors are mandated by the Child Abuse Prevention and Treatment Act of 1974, Public Law 93-247, to report suspected abuse and neglect to proper authorities (ASCA, 2021). Failure to report suspected abuse could result in civil or criminal liability (Remley et al., 2017; White & Flynt, 2000). ASCA Ethical Standards echo this mandate, directing school counselors to report suspected child abuse and neglect while protecting the privacy of the student (ASCA, 2022a, A.12.a). School counselors should also assist students who have experienced abuse and neglect by connecting them with appropriate services (ASCA, 2022a). Moreover, school counselors should work to create a safe environment free from abuse, bullying, harassment, and other forms of violence for students while promoting autonomy and justice (ASCA, 2022a).
School Counselors as Advocates in Mandated Reporting
Barrett et al. (2011) recognized school counselors as social justice leaders based on their role to advocate for students who are underserved, disadvantaged, maltreated, or living in abusive situations. Child abuse impacts children and adolescents from every race, socioeconomic status, gender, and age (Lambie, 2005; Tillman et al., 2015). School counselors who are trained to provide culturally sustaining school counseling will work with students and families from all demographics to promote student wellness within their comprehensive school counseling program (ASCA, 2021). As leaders within the school, school counselors, and especially veteran school counselors, can work to educate all stakeholders on the implications of child abuse.
School counselors not only are legally positioned to serve as mandated reporters but also ethically positioned to train school personnel in recognizing and identifying child abuse symptoms and in reporting procedures (Hodges & McDonald, 2019). Training of school personnel, such as teachers, to identify and report suspected child abuse is essential because they are also recognized legally as mandated reporters (Hupe & Stevenson, 2019) and they interact with students daily. It is vital that school counselors advocate for ongoing comprehensive training related to child abuse because their knowledge affects many stakeholders in the school setting (ASCA, 2021; Tuttle et al., 2019).
Self-Efficacy Among Veteran School Counselors
Previous literature from this data set highlighted the reporting behaviors of early career school counselors (Ricks et al., 2019), and a framework was developed to assist new professionals in reporting (Tuttle et al., 2019). However, the child abuse reporting behaviors and needs of veteran school counselors are understudied. Therefore, this article focuses on veteran school counselors. For the purpose of this study, veteran school counselors are considered licensed school counselors having 6 or more years of experience. Professional literature has highlighted the unique needs and experiences of novice counselors as compared to veteran school counselors (Buchanan et al., 2017; Johnson et al., 2017). One study (Mishak, 2007) examined differences in instructional strategies for early career and veteran school counselors in elementary schools in Iowa. Although that study does not specifically address child abuse reporting, it does highlight differences found among the respondents based on their experience level.
One factor supporting the unique needs of veteran school counselors is self-efficacy. Self-efficacy theory posits that an individual’s expectations of mastery are strongly influenced by personal experience and indirect exposure to a phenomenon (Bandura, 1977, 1997). Veteran school counselors, based on their years of experience in a school setting, are likely to have multiple exposures to child abuse reporting. They may have filed reports themselves, spoken to peers about their reporting experiences, or assisted other professionals in the school with reporting. Bandura (1997) suggested that self-efficacy is supported when individuals not only possess the skill and ability to complete a task, but also have the confidence and motivation to execute it.
Veteran school counselors can receive ongoing training from workshops, university courses, webinars, district training, or other professional organizations that may further impact self-efficacy levels. Previous research has shown that as an individual’s knowledge of child abuse increases, their levels of self-efficacy in recognizing or reporting child abuse also increases (Balkaran, 2015; Jordan et al., 2017). However, little research linking school counselors’ self-efficacy levels to child abuse reporting has been published. Despite the paucity of research on this topic, Ricks et al. (2019) found a moderate relationship between early career school counselors’ self-efficacy and their ability to identify types of abuse. Additionally, Tang (2020) found that school counseling supervision increased school counselor self-efficacy; differences between early career and veteran school counselors were not addressed in Tang’s study. Although the positive correlation found by Tang did not directly address child abuse reporting, assisting students with crisis situations was one of the principal components of the analysis. Even though veteran school counselors have experience serving as mandated reporters, they require ongoing professional development in this area to effectively fulfill their roles as advocates in maintaining the welfare and safety of students (ASCA, 2021; Tuttle et al., 2019). Therefore, we seek to utilize this article as a form of advocacy on behalf of veteran school counselors by providing additional research and literature in the field.
Purpose of the Present Study
The purpose of this quantitative study is to examine (a) the prevalence of child abuse reporting by veteran school counselors within the school year; (b) the factors affecting veteran school counselors’ decisions to report or not report suspected child abuse; (c) reasons for reporting or not reporting suspected child abuse by veteran school counselors; and (d) veteran school counselors’ self-efficacy levels related to child abuse reporting. Our intent was to build upon an initial larger study to examine veteran school counselors’ knowledge of procedures and experiences with child abuse reporting. The present study is a focused examination of the data collected from veteran school counselors as part of the primary study, which solicited data from school counselors across their careers related to their experiences with child abuse reporting (see Ricks et al., 2019). Demographic variables were collected from participants to assess their impact on child abuse reporting; see Table 1 for a complete list of variables.


Methods
Multiple correlation and regression analyses were conducted to assess factors influencing veteran school counselors’ decisions to report suspected child abuse. After obtaining IRB approval, the authors recruited school counselors in the Southeastern United States (Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, South Carolina, Tennessee, Texas, Virginia, and West Virginia). Participants were recruited using a professional school counseling association membership list, a southeastern state counseling association listserv, and social media. Participants were informed that participation in the online study was voluntary and that they could withdraw from the study at any time. Participants were also informed that the survey would take between 10–15 minutes and that the information collected in the survey would remain anonymous.
Participants
A total of 848 surveys were collected from participants. Veteran school counselor data was extracted from the total sample and analyzed to assess the unique experiences of these individuals in child abuse reporting. Veteran school counselors were defined as having 6 or more years of experience working as a school counselor within a public or private school. Four hundred and twenty-eight veteran school counselors began the survey, but data from 125 participants was excluded from the analysis for incomplete responses, resulting in a final sample of 303 participants. Most participants (n = 265, 87.5%) reported being licensed/certified as a school counselor. Some participants may not have possessed a license because of working in the private school sector or working on a provisional basis. See Table 1 for all demographic frequencies and percentages related to participants in the study.
Measures
Three measures were selected and employed as part of the larger study. These included the Child Abuse Reporting Questionnaire (Bryant & Milsom, 2005), the School Counselor Self-Efficacy Scale (Bodenhorn & Skaggs, 2005), and the Knowledge of Child Abuse Reporting Questionnaire (Ricks et al., 2019). Each measure is described below as previously reported in Ricks et al. (2019).
Child Abuse Reporting Questionnaire
The Child Abuse Reporting Questionnaire was developed to assess three domains, including school counselor General Information, Training in Child Abuse Reporting, and Child Abuse Reporting Experience (Bryant & Milsom, 2005). In the first section of the questionnaire, Training in Child Abuse Reporting, participants were asked to list where they obtained their knowledge of child abuse reporting and to assess four different types (physical, sexual, neglect, emotional) of child abuse. In the Child Abuse Reporting Experience section, the participants were asked two questions. The first question asked participants to recall the number of suspected child abuse cases they encountered during the preceding school year and the number of child abuse cases they reported. The next question asked participants how many cases of suspected child abuse they did not report. Participants were also asked in the survey to indicate reasons for choosing not to report suspected child abuse cases based on 12 commonly reported barriers or to list other reasons for not reporting the suspected cases. See Table 2 for a complete list of the common reasons given for not reporting suspected child abuse cases. Internal consistency measures were not obtained for this questionnaire because of the demographic nature of assessing participants’ personal experiences with child abuse reporting.
School Counselor Self-Efficacy Scale
The School Counselor Self-Efficacy Scale (SCSE) was used to assess school counselors’ self-efficacy and to link their personal attributes to their career performance (Bodenhorn & Skaggs, 2005). Participants completed Likert scale questions to indicate their confidence in performing school counseling tasks for 43 scale items. An example question would ask school counselors to indicate their confidence in advocating for integration of student academic, career, and personal development into the mission of their school. A rating of 1 indicated not confident and a rating of 5 indicated highly confident. The coefficient alpha for the scale score was found to be .95 (Bodenhorn & Skaggs, 2005). The SCSE subscales include five domains: Personal and Social Development (12 items), Leadership and Assessment (9 items), Career and Academic Development (7 items), Collaboration and Consultation (11 items), and Cultural Acceptance (4 items). The correlations of the subscales ranged from .27 to .43.
Knowledge of Child Abuse Reporting Questionnaire
The Knowledge of Child Abuse Reporting Questionnaire was developed to assess respondents’ knowledge of child abuse reporting and procedures within three areas (Ricks et al., 2019). To develop the survey, the researchers and outside counselor educators reviewed the questionnaire to determine if it clearly measured the constructs. In the first section of the questionnaire, Identifying Types of Abuse, participants’ perceptions of their ability to identify the four different types of child abuse were assessed. To complete this section, participants rated their comfort level using a 4-point Likert scale. A rating of 1 indicated very uncertain and a rating of 4 indicated very certain. The coefficient alpha for the scale score was found to be .902. The Knowledge of Guidelines section assessed participants’ knowledge of the state rules, ASCA Ethical Standards, and child abuse reporting protocol within their current school and district. To complete this section, participants rated their comfort level using a 5-point Likert scale. A rating of 1 indicated not knowledgeable and a rating of 5 indicated extremely knowledgeable. The coefficient alpha for the scale score was found to be .799. Lastly, the Child Abuse Training section assessed where participants received training on general knowledge of child abuse reporting, how to make a referral, and indicators of child abuse. To complete this section, participants selected options from a dropdown menu based on commonly reported agencies or listed an organization not provided. Options included in the survey list were universities or colleges, schools or districts, conferences or workshops, colleagues, journals, professional organizations, or the state department of education.
Data Analysis
SPSS Statistics 27 was used to analyze data within this study. First, a correlation analysis was executed to assess the strength of the relationship across variables. Next, analyses of variance (ANOVAs) were performed to assess the relationship between the number of reported child abuse cases and five demographic variables, which included academic setting (elementary, middle, high); number of students participating in the school’s free or reduced lunch program; number of school counselors working in a school setting; years of experience as a school counselor; and number of students enrolled in a school setting. Lastly, regression analyses were used to determine the relationship between school counselors’ self-efficacy and their decisions to report or not report suspected child abuse cases as well as to assess the relationship between school counselors’ self-efficacy and their certainty in identifying types of abuse.
Results
Suspected and Reported Cases of Abuse
Descriptive statistics generated from the child abuse survey included the participants (N = 303) suspecting 2,289 cases of child abuse during the school year. Scores reported by participants ranged from 0 to 100 (M = 7.71, SD = 10.58). Seven participants omitted this question within the questionnaire. Participants indicated reporting a total of 2,140 cases of suspected child abuse; individual frequency ranged from 0 to 100 (M = 7.21, SD = 10.25). Physical child abuse cases (M = 4.03, SD = 7.12) were reported at a higher rate than cases of neglect (M = 2.72, SD = 5.10), emotional abuse (M = 0.56, SD = 1.52), and sexual abuse (M = 0.57, SD = 1.37).
School Demographics
The relationship between the number of reported child abuse cases and demographic variables was examined using a bivariate correlation. Results indicated a negative correlation between the number of child abuse reports and the academic level of students the school counselor works with (elementary, middle, or high school), r(293) = −.283, p < .001, with elementary school counselors reporting child abuse at a higher rate than high school counselors. An additional negative correlation was found between the number of child abuse reports and the number of school counselors working within the school, r(293) = −.164, p < .001. Results indicated a positive significant relationship between the number of reported child abuse cases and the number of students who participate in the school’s free or reduced lunch program, r(293) = .225, p < .001. Weaker negative relationships were also found between the number of child abuse reports and the participants’ years of experience as a school counselor, r(297) = −.115, p < .05, as well as how many students are enrolled in a school, r(293) = −.127, p < .06. No other significant relationships were found among the variables and reported cases.
An ANOVA was conducted to examine the relationship between the academic level of students (elementary, middle, and high) the participants worked with and the number of child abuse cases reported. Results showed a significant relationship among the variables, f(2, 290) = 13.021, p > .00. A follow-up test was used to evaluate pairwise differences among the means. Results of a Tukey HSD indicated a significant difference between elementary (M = 10.314) and high school (M = 3.58) counselors who reported child abuse. A difference was also found between elementary and middle school (M = 5.86) reporting levels. No other significant differences were found between variables.
An ANOVA was also conducted to evaluate the differences between child abuse reporting and the percentage (0%–25%, 26%–50%, 51%–75%, 76%–100%) of students who participated in free or reduced lunch. Results showed a significant relationship among the variables, f(3, 289) = 5.22, p = .002. A Tukey HSD post hoc test was used to make a pairwise comparison and statistically significant mean differences were found between the 0%–25% (M = 2.33) group and the 51%–75% (M = 7.78) group. Additionally, a difference was found between the 0%–25% group and the 76%–100% (M = 10.12) group. Lastly, a difference was found between the 26%–50% (M = 6.54) group and the 76%–100% group. No other significant differences were found between the groups.
An ANOVA was conducted to examine the relationship between how many school counselors are working in a school setting and the differences in child abuse reporting. Analysis of the ANOVA found no significant difference (p < .05) between the groups (one counselor, M = 8.26; two counselors, M = 7.81; three counselors, M = 7.69; four counselors, M = 5.00; five counselors, M = 2.80; six counselors, M = 2.25; seven counselors, M = 3.50; eight counselors, M = 2.33; more than eight counselors, M = 2.20), but a downward trend can be seen in the number of cases reported with the increase in the number of school counselors within a school.
Likewise, an ANOVA was used to examine the relationship between years of experience as a school counselor and the differences in child abuse reporting, but no significant difference (p < .05) was found between groups (6 to 10 years, M = 8.58; 11 to 20 years, M = 6.36; above 20 years, M = 5.57); however, a slight trend can be seen with participants who have less experience reporting at higher rates. A larger sample size may have yielded significant results, but additional research is needed in this area.
Lastly, an ANOVA was also executed to assess the differences in child abuse reporting and the number of students enrolled in a school setting. A significant difference was found between schools with more than 2,000 students (M = 3.00) and schools with 251–500 students (M = 8.07) as well as schools with 501–750 students (M = 8.63). This difference suggests school counselors who work in schools with more students tend to report child abuse at a lower rate than those who work in smaller schools. A downward trend can be seen in reporting of cases as student numbers increase (751–1,000 students, M = 7.62; 1,001–1,250 students, M = 7.39; 1,251–1,500 students, M = 6.68; 1,501–1,750 students, M = 6.00; 1,751–2,000 students, M = 2.57), with the exception of the 0–250 students (M = 4.82) school classification. Differences in the sample sizes of classification categories could have impacted significance outcomes. No other significant differences were found between the groups.
The Decision to Report
On the Child Abuse Reporting Survey, participants (N = 303) were asked to indicate what factors influenced their decision to report child abuse. Participants indicated the number one factor was following the law (professional obligation; 91.4%, n = 277). Other reasons cited by over half of school counselors included following school policy (68.6%, n = 208), concern for safety of the child (63.4%, n = 192), strong evidence that abuse had occurred (57.1%, n = 173), and the school counselor’s relationship with the child (56.1%, n = 173). See Table 3 for factors influencing child abuse reporting. Further, participants indicated reasons why they chose not to report suspected child abuse. Participants specified inadequate evidence as the primary reason for not reporting suspected child abuse (22.4%, n = 68). Another notable influence included concern that DHS would not investigate the reported case (6.9%, n = 21). See Table 2 for factors influencing the decision not to report child abuse.


Knowledge and Training
On the Knowledge of Child Abuse Reporting Questionnaire, participants were asked to rate how certain they feel about their abilities to identify types of abuse on a 4-point Likert scale with 1 indicating very uncertain and 4 indicating very certain. Participants reported most confidence in their ability to identify physical abuse (M = 3.49, Mdn = 4), followed by neglect (M = 3.30, Mdn = 3), sexual abuse (M = 3.20, Mdn = 3), and emotional abuse (M = 3.06, Mdn = 3). When participants (N = 303) were asked where they gained knowledge about child abuse, most reported receiving training from professional experiences (88.4%, n = 268), mandated reporting training at school (79.5%, n = 241), workshops (72.3%, n = 219), discussion with colleagues (61.4%, n = 186), or literature (58.1%, n = 176). Additionally, participants indicated gaining knowledge from university courses (46.5%, n = 141), media (9.2%, n = 28), or other avenues unlisted in the survey (12.2%, n = 37).
Participants were asked where they received training on how to make a referral for a child abuse case. Most of the school counselors responded that they received the training from a school/district training (87.5%, n = 265), conference/workshop (57.4%, n = 174), or university class (42.9%, n = 130). Other responses included from a colleague (38.9%, n = 118), professional organization (32.7%, n = 99), Department of Education website (20.5%, n = 62), journal (10.9%, n = 33), or other sources (11.2%, n = 34). Lastly, veteran counselors were asked where they received training about the indicators of child abuse. The majority of the respondents reported learning in a school/district training (87.1%, n = 264), conference/workshop (77.9%, n = 236), or university/college course (67.3%, n = 204). Other responses included learning from a professional organization (38%, n = 115), colleague (30%, n = 91), journal (23.4%, n = 71), Department of Education website (21.5%, n = 65), or other sources (9.9%, n = 30).
Veteran school counselors reported that 88.1% (n = 267) of schools/districts provided them with training on local abuse reporting policies. Therefore, 11.9% did not receive training from their local school system. Additionally, 60.1% (n = 182) of the school counselors reported their school/district had a handbook/resource outlining the steps for mandated reporter training within their school system. Consequently, 39.9% of the school counselors reported not having a handbook/resource to reference outlining steps for mandated reporting.
Self-Efficacy and Child Abuse Reporting
A regression analysis was used to examine the relationship between veteran school counselors’ self-efficacy and three variables, including the number of reported child abuse cases, the decision not to report suspicion of child abuse, and certainty in identifying types of child abuse. Results showed the strength of the relationship between self-efficacy and certainty in identifying types of child abuse was moderately related, F(1, 301) = 41.350, p < .01. Over 12% (r2 = 0.121) of the variance of the school counselors’ self-efficacy level was associated with certainty in identifying child abuse. No other significant results were found among the variables. See Table 4 for the regression analysis related to self-efficacy and child abuse reporting.
Discussion
Given the well-documented negative impact of child abuse on the emotional, physical, and academic well-being of children, it is essential to understand how school counselors are trained to identify and report child abuse. Understanding trends and research in child abuse reporting can help schools prepare school counselors and other staff members. It is imperative for veteran school counselors to receive ongoing training to best serve as advocates for students, maintain relevancy in their roles as mandated reporters by staying current on laws and policies, and further their ability to work within their scope of practice. Ongoing training may also help alleviate difficulties that arise because of terminology differing from state to state and district to district (ASCA, 2021; Hogelin, 2013; Lambie, 2005; Tuttle et al., 2019).

In this study, veteran school counselors’ reporting frequency is shown to differ based on various school demographics. Veteran school counselors were specifically targeted in this analysis to examine their experiences related to child abuse reporting. Although these findings may not show direct causation to child abuse reporting among veteran school counselors, they can help us better understand school and school counselor demographics that need to be evaluated further. The findings can also be used to guide professional development training needed for school counselors as well as additional training needs for counselors-in-training.
Elementary school counselors were found to report child abuse at a higher rate than middle or high school counselors; however, this is anticipated because studies show that younger children experience higher rates of maltreatment than older children (HHS et al., 2021). In fact, rates of maltreatment seem to decrease as age increases. Children who are 6 years old have victimization rates of 9.0 per 1,000 children compared to children who are 16 years of age who have a victimization rate of 5.5 per 1,000 children (HHS et al., 2021). Higher maltreatment levels in younger children may be because of increased caregiver burden (Fortson et al., 2016); as children get older, they are better able to care for themselves and avoid parental confrontation. In addition, older students may be more likely to hide abuse and more astute when dealing with disclosure protocol (Bryant & Milsom, 2005). Knowledge of the signs and symptoms of child abuse and neglect can help school counselors identify children suffering from maltreatment.
Within this study on veteran school counselors, a slight trend can be seen with participants with less experience reporting suspected child abuse at a higher rate. Differences of reporting rates by years of experience may be because of higher ego maturity in less experienced school counselors because of more recent training in their graduate programs (Lambie et al., 2011). According to Lambie et al. (2011), ego development predicts an individual’s level of ethical and legal knowledge, which has been found to be higher in counselors-in-training than the average school counselor. Ego development has also been correlated with greater degrees of self-efficacy (Singleton et al., 2021), which can impact school counselors’ actions when making decisions related to child abuse reporting. Tuttle et al. (2019) also emphasized the need for continuous training to increase school counselors’ self-efficacy as mandated reporters, although more research is needed to understand the impact of self-efficacy on school counselor action. These findings highlight the need for continued assessment of training needs for school counselors of various experience levels.
Although age has been associated with varying levels of child abuse victimization, low socioeconomic status within the home environment has also been identified as a high risk factor for child abuse (Bryant, 2009; Bryant & Milsom, 2005; Ricks et al., 2019; Sedlak et al., 2010). Specifically, the higher the percentage of students participating in the school’s free or reduced lunch program, the more child abuse cases the school counselor reported (Bryant, 2009; Bryant & Milsom, 2005; Ricks et al., 2019). Although most children in low-income families do not experience child abuse, one study estimated that 22.5 children per 1,000 in low-income families experience maltreatment as compared to 4.4 per 1,000 in more affluent families (Sedlak et al., 2010). However, it is important to note the disproportionality that exists within child welfare reporting; non-White children and children of low socioeconomic status are reported to child protective services at a higher rate than their peers (Krase, 2015; Luken et al., 2021). School counselors working in low-income schools need to be aware of the increased risk factors of low socioeconomic status as well as the racial and economic disproportionality that occurs within child maltreatment reporting as a result of possible bias. School counselors should work to be aware of potential biases they may hold with regard to over-reporting certain groups of children and under-reporting others (Tillman et al., 2015).
When examining the current practices of veteran school counselors, participants reported professional obligation as the number one reason they reported suspected child abuse. The primary reason given for failing to report suspected abuse was inadequate evidence. These findings are similar to prior research that shows lack of evidence as an influencing factor in school counselors’ decisions not to report suspected abuse (Bryant, 2009; Bryant & Milsom, 2005; Tillman et al., 2015); this is concerning because some cases of abuse may go unreported. As Tuttle et al. (2019) have stated, “the school counselor’s responsibility is to follow legal and ethical obligations as a mandated reporter by reporting all suspected child abuse” (p. 242). Although concern that DHS would not investigate is denoted as an important factor for why school counselors choose not to report, school counselors must recognize they do not have the proper resources or training to lead a child abuse investigation on their own (Tuttle et al., 2019). As a result, school counselors are ethically and legally mandated to report all suspected cases of abuse to the proper authorities defined by their state, school policies, and ethical codes. Failure to report cases could lead to legal ramifications for the school counselor (Remley et al., 2017; White & Flynt, 2000) and continued maltreatment for the student.
School counselors should strive to “understand child abuse and neglect and its impact on children’s social/emotional, physical and mental well-being” (ASCA, 2021, para. 6). Veteran school counselors completing this survey were most confident in their ability to identify physical abuse and less confident in their ability to identify emotional abuse. This finding supports the assertion that types of abuse with visible evidence are more identifiable than other types of abuse such as emotional or sexual abuse (Bryant, 2009; Bryant & Milsom, 2005). Cases of suspected abuse in which a child reports physical abuse are less likely to be reported if there is no evidence of bodily harm (Tillman et al., 2015). Although school counselors report physical abuse as the most easily identifiable type of abuse, child protective services report neglect as the most common type of maltreatment (Child Welfare Information Gateway, 2021).
Results from this study show that veteran school counselors reported receiving their knowledge on child abuse from professional experiences and mandated reporter training at their school; comparatively, early career school counselors reported most of their knowledge came from professional experience and university courses (Ricks et al., 2019). Reported differences were also observed between veteran school counselors and early career school counselors in terms of sources of knowledge on how to make a referral and learn about indicators of abuse (Ricks et al., 2019). Differences may exist because of variable school district policies regarding ongoing mandated reporter training frequency and practices.
When assessing training needs, participants indicated that most veteran school counselors do receive training from their school district on how to make a referral, indicators of child abuse, and local abuse reporting procedures. In fact, 25% more veteran school counselors reported receiving training from their district than early career school counselors (Ricks et al., 2019). Additionally, approximately 40% of veteran school counselors reported not having a handbook or resource to reference outlining the mandated reporting protocol for their district/school. This result is slightly lower than that reported in research on early career school counselors showing approximately half of school counselors not having a handbook/resource (Ricks et al., 2019). The lack of access to a set protocol outlined by the district is concerning because of the inconsistencies that exist within protocols across states and school districts. Confusion may arise as to timeliness and manner of reporting as well as to who must make the actual report (Kenny & McEachern, 2002). As compared to novice school counselors, veteran counselors appear to report receiving training and/or a handbook/resources related to child abuse reporting in higher numbers. Discrepancies in reported training may indicate a delay in training provided to new school counselors or that training on child abuse is not occurring annually. Although the majority of veteran school counselors did report receiving some training from their school districts, it is important to have “established protocols [to] help address concerns over quality control, fear of lawsuits, and the protection of staff in reporting cases, as well as ensure that there are effective steps for helping children” (Crosson-Tower, 2003, p. 29).
Previous research (Kenny & McEachern, 2002) has indicated that school counselors with more years of experience report less adequate pre-service training in child abuse reporting and that school counselors with in-service training in the last 12 months are less concerned about the consequences of making a report (Behun et al., 2019). This might be due to recently trained school counselors having greater awareness about current information and procedures, which supports the need for participation in continuous ongoing education on this topic. Although the veteran school counselors surveyed in this study indicated experience in child abuse reporting, continued updates to the law highlight the need for current and well-defined guidelines within each school system. Ongoing training is recommended for all school counselors to ensure they stay informed on updated protocols and research (Kenny & Abreu, 2016; Tuttle et al., 2019).
Results of the data analysis also indicated a moderately significant relationship between veteran school counselor self-efficacy and their certainty identifying types of abuse. These findings echo other research indicating that school counselors’ self-efficacy levels may influence their decisions to report suspected abuse (Ricks et al., 2019; Tuttle et al., 2019). According to Larson and Daniels (1998), counselor self-efficacy beliefs are the main factor contributing to effective counseling action. Given the impact of counselor self-efficacy on effective action, it is important to understand how self-efficacy impacts school counselors’ decision-making processes. Experience and training are two factors that have been found to increase school counselor self-efficacy (Morrison & Lent, 2018). Veteran school counselors, who already have years of experience on their side, may benefit most from additional training opportunities. Increased support should be provided to all school counselors to enhance their counseling self-efficacy (Schiele et al., 2014) and contribute to positive school counseling outcomes.
Implications
Lack of knowledge related to reporting policies has been identified as a key barrier in reporting child abuse (Kenny, 2001; Petersen et al., 2014). School counselors should advocate for standardization in reporting policies. Understanding each state’s unique child abuse prevention statutes can help school counselors best serve their clients (Remley et al., 2017). Given that laws and definitions pertaining to child abuse and neglect vary among states (ASCA, 2021), school counselors should identify collaborative relationships to navigate these legal and ethical parameters. Key collaborations may include those with the school social worker, the school district’s attorney, law enforcement, child protective services, parents/guardians, and community members (Tuttle et al., 2019). Working together, in conjunction with administration and other school stakeholders, school counselors can help establish or update written guidelines and implement ongoing professional development in mandated reporting within their school district. Additionally, developing a positive working relationship with law enforcement and child protective services can help ensure that child abuse cases are reported and documented properly, which can promote positive outcomes for students and families. Moreover, based on the findings from this research study, school counseling certification organizations (i.e., state departments of education/licensure boards) may want to increase or update current training policies for professional school counselors. An area for further study would be examining school districts’ training and protocols for child abuse reporting.
Higher reporting trends in low socioeconomic settings highlight the need for additional mental health services in low-income school districts. School counselors may need more training on the risk factors associated with poverty as well as to be reminded that abuse occurs in all types of families (Bryant, 2009; Tillman et al., 2015). Practicing school counselors working with students living in poverty are often in schools where there are significantly limited resources. School counselors report that “working in schools with high poverty means academic services and the school counseling program itself are limited” (Ricks et al., 2020, p. 61). More research is needed to assess how to support school counselors working in low-income schools; however, school counselors should remain cognizant and demonstrate cultural competency. It is also important for veteran school counselors to continue to assess self-bias as a factor in identifying and reporting suspected child abuse cases (Tillman et al., 2015). Further, it is essential that school counselors emerge as advocates for students in these low socioeconomic settings by pushing for more resources for mental health services as well as changes to policies that negatively impact students’ success. School counselors can work with a task force or advisory committee within the school to examine current practices on child abuse identification and reporting (Temkin et al., 2020). The task force could look for systemic barriers that are impacting students related to child abuse reporting and trauma support; these include current school policies, reporting procedures, teacher and staff training protocols, school counselor professional development, access to mental health services, community resources, direct and indirect school counseling protocols, and other factors impacting student identification and support.
Given the higher number of child abuse cases in the elementary grade levels, more school counselors are needed to adequately identify child abuse and provide services for these students. Despite these needs, the school counselor-to-student ratio varies in each state and is higher in elementary schools (ASCA, 2022b); the national state averages for the school counselor-to-student ratio in grades kindergarten through eighth ranges from 1:419 to 1:1,135 as compared to 1:164 to 1:347 in grades nine through 12 (ASCA, 2022b). Moreover, 20 states currently have no school counseling mandates that require school counselors to be present within the schools (ASCA, 2022c). Of the 30 states that do have mandated counseling, seven do not have mandated counseling for elementary-level students (ASCA, 2022c). School counselors should advocate for more school counselors within their districts and state. Moreover, school administrations and state departments of education should consider hiring additional school counselors to address ongoing mental health needs. Recent research has shown that as a result of the COVID-19 pandemic, students may be experiencing no motivation to do schoolwork, difficulty concentrating, concern for falling behind in school, concern for getting sick, or other stress-related factors (Styck et al., 2021), as well as an increased risk for child abuse and neglect (Swedo et al., 2020). Elementary school counselors, who are uniquely trained in child development, can implement prevention and intervention programs to address these ongoing needs (ASCA, 2019). Elementary school counselors are essential in providing early intervention and prevention services for students.
Further research is needed in understanding how self-efficacy impacts school counselors’ decision-making process. The variation of confidence in identifying abuse as well as variance in reporting patterns among school counselors with differing years of experience are indicators that further professional development and training is needed within schools. It is also important to examine how school support can increase school counselors’ self-efficacy levels (Schiele et al., 2014). Current research shows that a school counselor’s level of self-efficacy predicts quality of practice and knowledge of evidence-based practices (Schiele et al., 2014).
Limitations
Although measures were used to reduce confounding variables, limitations exist in the methodological design of the study that could impact the validity of the findings. Firstly, this study obtained a sample size from a limited geographic area (Southeastern United States). Secondly, self-reported data was used. Although participants were informed their answers would remain anonymous, they may have answered based on what they perceived as acceptable and appropriate. School counselors may not be inclined to admit they did not report suspected child abuse for fear of legal or ethical violations. Likewise, selective memory may impact participants’ ability to effectively recall events that happened over a year ago. Additionally, many of the participants were White; responses from participants of color were limited. Further research with a more diverse sample would be beneficial to gain a comprehensive understanding of school counselors’ self-efficacy in identifying and reporting child abuse.
Conclusion
School counselors are mandated to report suspected child abuse and neglect cases to authorities and are key school personnel in early detection and recognition of abuse (ASCA, 2021). In this study, differing school demographics were associated with varying reporting practices among veteran school counselors. Continued professional development training, by virtue of its ability to increase veteran school counselors’ self-efficacy and knowledge of identification and reporting protocols, represents a promising possible pathway to improving outcomes among maltreated children.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.
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Lacey Ricks, PhD, NCC, NCSC, is an associate professor at Liberty University. Malti Tuttle, PhD, NCC, NCSC, LPC, is an associate professor at Auburn University. Sara E. Ellison, MS, NCC, LAPC, is a doctoral student at Auburn University. Correspondence may be addressed to Lacey Ricks, 1971 University Blvd, Lynchburg, VA 24515, lricks1@liberty.edu.
Aug 10, 2022 | Author Videos, Volume 12 - Issue 2
Dan Li
Supervisee development is integral to counselor training. Despite the general acknowledgement that supervisors adopt different styles when supervising counselor trainees at varying levels, there is a paucity of studies that (a) measure supervisee levels using reliable and valid psychometric instruments, other than a broad categorization of supervisees based on their training progression (e.g., master’s level vs. doctoral level, practicum vs. internship, counselor trainee vs. postgraduate); and (b) empirically document how the matching of supervisory styles and supervisee levels relates to supervision processes and/or outcomes. The supervisory working alliance is key to the supervision process and outcome. To test the hypothesized moderation effects of supervisee levels on the relationship between supervisory styles and the supervisory working alliance, the author performed a series (n = 16) of moderation analyses with a sample (N = 113) of master’s- and doctoral-level counseling trainees and practitioners. Results suggested that supervisee levels and their three indicators (self and other awareness, motivation, and autonomy) were statistically significant moderators under different contexts. These findings (a) revealed extra intricacies of the relationships among the study variables, (b) shed light on future research directions concerning supervisee development, and (c) encouraged supervisors to adopt a composite of styles to varying degrees to better foster supervisee growth.
Keywords: supervisee development, supervisory styles, supervisory working alliance, supervisee levels, moderation analyses
Clinical supervision is integral to promoting counseling supervisees’ learning (Goodyear, 2014), safeguarding the quality of professional services offered to supervisees’ clients, and gatekeeping the counseling profession (Bernard & Goodyear, 2019). Because supervisors and supervisees are two parties of the tripartite entity of supervision, literature has extensively documented supervisor characteristics (e.g., supervisory styles, self-disclosure, cultural humility), supervisee characteristics (e.g., professional development levels), and the relationship between the two (e.g., supervisory working alliance) as related to supervision processes and outcomes (King et al., 2020; Ladany, Walker, & Melincoff, 2001; Stoltenberg & McNeill, 2010).
Of these relationships, research has consistently revealed a positive correlation between supervisory styles and the supervisory working alliance (Efstation et al., 1990; Heppner & Handley, 1981; Ladany & Lehrman-Waterman, 1999; Ladany, Walker, & Melincoff, 2001). Although such direct positive correlation is theoretically appealing and statistically compelling, there is limited research that further investigates the intricacy of this association, if at all (e.g., whether the direction or strength of this relationship may alter in different contexts). Particularly, abundant supervision literature (Friedlander & Ward, 1984; Li et al., 2018; Li et al., 2019; Li, Duys, & Granello, 2020; Li, Duys, & Vispoel, 2020; Stoltenberg & McNeill, 2010) suggested the adoption of different supervision approaches when working with supervisees at various levels of professional development. Therefore, supervisee levels present as a potential context to examine how supervisory styles relate to the supervisory working alliance.
However, supervisee levels are frequently conceptualized based on supervisees’ training progression (e.g., master’s level vs. doctoral level, practicum vs. internship, counselor trainee vs. postgraduate), which may not accurately approximate where supervisees are. As such, I adopted the Supervisee Levels Questionnaire-Revised (SLQ-R; McNeill et al., 1992), a reliable and valid psychometric instrument, to measure supervisee levels (collectively as an overall assessment and separately with their three indicators) in this study.
Supervisory Styles
Supervisory styles embody a constellation of behavior patterns that supervisors exhibit in establishing a working relationship with supervisees (Hunt, 1971) and are related to the interactional pattern that is fostered by supervisors in a direct or indirect manner (Munson, 1993). Specifically, supervisory styles encompass supervisors’ consistent focus in supervision, the manner in articulating their theoretical orientation, as well as the philosophy of practice and supervision and how it is communicated to supervisees (Munson, 1993). Friedlander and Ward (1984) identified three distinctive factors that correspond to three supervisory styles—attractive, interpersonally sensitive, and task-oriented—as measured by the Supervisory Styles Inventory (SSI) used in the present study. Attractive style supervisors appear to be warm, supportive, friendly, open, and flexible, denoting the collegial dimension of supervision; the interpersonally sensitive style is a relationship-oriented approach, and supervisors of this style tend to be invested, committed, therapeutic, and perceptive; and task-oriented supervisors are content-focused, goal-oriented, thorough, focused, practical, and structured (Friedlander & Ward, 1984). These styles resonate with the consultant, counselor, and teacher roles of the supervisor, respectively, in Bernard’s (1997) discrimination model.
Of the three styles, the interpersonally sensitive and task-oriented styles appear to be empirically distinct from one another and distinct from the attractive style (Shaffer & Friedlander, 2017). For instance, Li, Duys, and Vispoel (2020) studied 34 supervisory dyads and found the interpersonally sensitive style was the only discriminant variable, based on which supervisory dyads exhibited statistically different state-transitional patterns (i.e., movement patterns across six common supervision states). Earlier, Fernando and Hulse-Killacky (2005) also found this same style was the only predictor that uniquely and significantly explained supervisees’ satisfaction with supervision, but the task-oriented style was the only significant predictor in explaining supervisees’ perceived self-efficacy.
Supervisory Working Alliance
Park et al.’s (2019) meta-analysis indicated that the supervisory working alliance was positively related to supervision outcome variables. Bordin (1983) first coined the concept of the supervisory working alliance as a parallel concept to the therapeutic working alliance and introduced the three aspects of the therapeutic working alliance to the alliance in supervision—mutual agreements on the goals, tasks, and bond—which laid the foundation for the adapted Working Alliance Inventory (WAI; Bahrick, 1989) for both supervisors and supervisees. Efstation et al. (1990) instead used three supervisor factors (client focus, rapport, and identification) and two supervisee factors (rapport and client focus) to conceptualize the supervisory working alliance in their Supervisory Working Alliance Inventory (SWAI). In view of the collinearity issue for the goal and task dimensions in the WAI (Hatcher et al., 2020), I adopted the SWAI in the present study.
The working alliance is one of the most robust predictors of outcome in psychotherapy (Norcross, 2011). Although such robust prediction cannot be directly replicated in supervision between the supervisory working alliance and supervision outcome (Goodyear, 2014), scholars (DePue et al., 2016; DePue et al., 2022) have found the supervisory working alliance to be related to the therapeutic working alliance. Specifically, supervisees’ perception of the supervisory working alliance was positively related to their perception of the therapeutic alliance (DePue et al., 2016). However, supervisees’ perception of the supervisory working alliance did not significantly contribute to clients’ perception of the therapeutic working alliance (DePue et al., 2016).
Supervisory Styles and the Supervisory Working Alliance
Extensive research has documented a close relationship between supervisory styles and the supervisory working alliance (Efstation et al., 1990; Heppner & Handley, 1981; Ladany, Walker, & Melincoff, 2001; Shaffer & Friedlander, 2017). Broadly, as supervisees perceived a greater mixture of supervisory styles in their supervisors (i.e., higher ratings on all three styles; Ladany, Marotta, & Muse-Burke, 2001), supervisees were more likely to report a stronger supervisory working alliance (Li et al., 2021). Despite this global positive correlation, when scholars examined each style independently in relation to each dimension of the supervisory working alliance, such statistical significance was not consistent (Ladany, Walker, & Melincoff, 2001). For instance, in Ladany, Walker, and Melincoff’s (2001) study, participants’ perceptions of an attractive style uniquely and significantly accounted for their perceptions of the bond dimension in alliance, whereas both the interpersonally sensitive and task-oriented styles had this unique and significant association with the task dimension in alliance.
The Moderating Role of Supervisee Levels
It is not uncommon for a counselor supervisor to start supervision with an expectation of a supervisory style to use (Hart & Nance, 2003). But supervisors have to decide what to address with the supervisee and adopt the most functional style (Bernard, 1997), which could be subject to a myriad of factors, such as contextual factors (Holloway, 1995), cultural considerations (Li et al., 2018), and supervisees’ developmental levels and needs (Friedlander & Ward, 1984; Stoltenberg & McNeill, 2010), among others. Particularly, in Friedlander and Ward’s (1984) study, supervisory styles were differentially related to supervisees’ experience levels. For example, supervisors reported that they were more task-oriented with practicum students but more attractive and interpersonally sensitive with internship students. This interaction effect was also echoed by practicum students’ higher ratings on the task-oriented style but lower ratings on the interpersonally sensitive style, compared to their internship counterparts (Friedlander & Ward, 1984). Similarly, in the study conducted by Li, Duys, and Granello (2020), supervisory dyads with less experienced supervisees tended to be more preoccupied with foundational competencies (e.g., counseling skills and theories, maintenance of standards of service) than dyads with more experienced supervisees. Consistently, more experienced supervisees in Li et al.’s (2019) study were more likely to display positive social emotional behaviors (e.g., self-disclosure, empathy, reflection of feelings, expanding on supervisors’ ideas, praise) in response to supervisors’ opinions, which in turn were more likely to elicit supervisors’ opinions that helped facilitate supervisees’ growth.
However, supervisees’ developmental levels were not always significantly associated with supervision processes or outcomes. For instance, in Bucky et al.’s (2010) study, doctoral-level supervisees did not rate their supervisor characteristics as related to the supervisory working alliance differently based on their developmental levels. Nevertheless, researchers in that study (Bucky et al., 2010) gauged supervisees’ developmental levels based on supervisees’ training progression (i.e., the current level or year level) as commonly practiced (e.g., practicum vs. internship), which may not accurately capture the actual developmental levels of supervisees. Or supervisee levels may not be strikingly distinct in doctoral programs, at least in that sample. In this study, supervisee levels were conceptualized not only as an overall assessment of where supervisees are but with three dimensions (self and other awareness, motivation, and autonomy) aligned with Stoltenberg and McNeill’s (2010) integrative developmental model (IDM) using the Supervisee Levels Questionnaire-Revised (SLQ-R; McNeill et al., 1992).
Statement of Purpose
Although literature evidenced the overall positive correlation between supervisory styles and the supervisory working alliance, the direction and strength of such a relationship in different contexts warrants additional attention. Particularly, supervisees’ developmental progression entails a flexible mixture of different supervisory styles as suggested theoretically and empirically, but whether and how the relationship between supervisory styles and the supervisory working alliance may vary across different supervisee levels calls for further investigation. To this end, the purpose of the current study was to test the potential moderation effects of supervisee levels on the relationship between supervisory styles and the supervisory working alliance.
Given that supervisees at earlier stages of professional development may need more guidance and support from supervisors, which necessitates a variety of supervision styles that are critical to their perception of the working alliance with their supervisors, I hypothesized that the positive relationship between supervisory styles and the supervisory working alliance would be more sensitive for supervisees at earlier stages of development, compared to their more experienced counterparts. In other words, the positive relationship would be stronger for supervisees at lower levels of professional development and weaker for supervisees at higher levels of professional development.
Method
Participants
The data set of this study is part of a larger national quantitative study with a cross-sectional sample (Li et al., 2021). Yet, researchers have not examined supervisee levels that are crucial to measuring supervisee development using a robust psychometric instrument. The current sample comprised 113 participants (see Table 1), with the majority as master’s-level (n = 54, 47.79%) or doctoral-level students (n = 46, 40.71%). Approximately 17% of participants (n = 19) identified themselves as post-master’s or post-doctoral practitioners or other. Some participants reported both their training and practicing levels (e.g., both as a doctoral student and a post-master’s practitioner), which caused the sample size to be larger than 113 if simply adding the frequencies across the three categories together. Most participants reported their specialty areas in clinical mental health counseling (n = 53, 46.90%), school counseling (n = 43, 38.05%), and counselor education and supervision (n = 27, 23.89%). Because some participants indicated more than one specialty area, the total percentage did not add up to 100.
In this sample, approximately 80% were female (n = 90) and 23 were male (20.35%). At the time of filling out the questionnaire, most of them fell in the 21–30 age range (n = 72, 63.72%), with 19 in the 31–40 range (16.81%), 13 in the 41–50 range (11.50%), and nine beyond 50 years old (7.96%). Participants in this sample predominantly identified themselves as White (n = 97; 85.84%), with eight as Asian (7.08%), five as Black or African American (4.42%), one as American Indian and Alaska Native (0.88%), one as biracial or multiracial (0.88%), and one indicating other (0.88%). Most participants reported their counseling experience as 1 year or less (n = 44, 38.94%) or longer than 3 years (n = 37; 32.74%), with the rest reporting in between (n = 32, 28.31%). See Table 1 for more detailed demographic information.

Procedure
Upon receiving IRB approval, I started collecting data online through Qualtrics in 2017–2018. The recruitment criteria included (a) one is at least 18 years of age by the time of filling out the survey; and (b) one is a student or a practitioner who had supervision experience in the counseling field. I disseminated the recruitment post through several professional networks, including the Counselor Education and Supervision Network-Listserv (CESNET-L) and American Counseling Association (ACA) Connect. In addition to this convenience sampling, I also used snowball sampling because participants were encouraged to share the recruitment post with anyone who they thought might be eligible to participate in the study. The recruitment post contained a survey link that directed potential participants to the informed consent webpage and then a compiled questionnaire webpage.
Instruments
Demographic Questionnaire
The purpose of including this self-constructed Demographic Questionnaire was to report the basic demographic information of participants. Specifically, the questionnaire included the gender, age, race/ethnicity, length of counseling-related work experience, training/practicing level, and training or specialty area of participants.
Supervisory Styles Inventory
The SSI (Friedlander & Ward, 1984) is a 33-item instrument used to measure the degree to which one endorses descriptors representative of each of the three dimensions of supervisory style: Attractive (7 items), Interpersonally Sensitive (8 items), and Task-Oriented (10 items), with the remainder as the filler items (8 items). Participants rate each item along a 7-point Likert scale from 1 (not very) to 7 (very). Higher scores in each dimension mean that one endorses descriptors of a certain supervisory style to a larger extent. Sample items for the Attractive, Interpersonally Sensitive, and Task-Oriented subscales are “supportive,” “perceptive,” and “didactic,” respectively.
Friedlander and Ward (1984) reported the Cronbach’s alphas of the three subscales separately and combined ranged from .76 to .93 (Ns ranging from 105 to 202). Additionally, the item–scale correlations ranged from .70 to .88 for the Attractive subscale, from .51 to .82 for the Interpersonally Sensitive style, and from .38 to .76 for the Task-Oriented scale (N1 = 202, N2 = 183; Friedlander & Ward, 1984). The test-retest reliability (N = 32) for the combined scale was .92; they were .94, .91, and .78 for the Attractive, Interpersonally Sensitive, and Task-Oriented subscales, respectively (Friedlander & Ward, 1984). They also reported the convergent validity based on moderate to high positive relationships (ps < .001) between the SSI and Stenack and Dye’s (1982) measure of supervisor roles (i.e., consultant, counselor, and teacher; N = 90). In the present study, the Cronbach’s alpha was .96 for the Attractive style, .94 for the Interpersonally Sensitive style, .92 for the Task-Oriented style, and .96 for the entire measure.
Supervisory Working Alliance Inventory
The SWAI (Efstation et al., 1990) is used to measure the relationship in counselor supervision. It has both the supervisor and supervisee forms. The supervisee form applied to the current study includes two scales: Rapport (12 items) and Client Focus (7 items). Supervisees indicate the extent to which the behavior described in each item seems characteristic of their work with their supervisors on a 7-point Likert scale, with 1 being almost never and 7 being almost always. Higher scores in the Rapport scale indicate a stronger perceived rapport with their supervisor, and higher scores in the Client Focus scale suggest more attention to issues related to the client in supervision. A sample item for the Rapport scale is “I feel free to mention to my supervisor any troublesome feelings I might have about him/her.” A sample item for the Client Focus scale is “I work with my supervisor on specific goals in the supervisory session.”
Efstation et al. (1990) reported that the alpha coefficient was .90 for Rapport and .77 for Client Focus (N = 178) for the supervisee form. Moreover, the item–scale correlations ranged from .44 to .77 for Rapport, and from .37 to .53 for Client Focus. They used the SSI to obtain initial estimates of convergent and divergent validity for the SWAI (Efstation et al., 1990). As expected, the Client Focus dimension of the SWAI showed moderate correlation (r = .52) with the Task-Oriented style in the SSI supervisee’s form, but low correlation (r = .04) with the Attractive style and low correlation (r = .21) with the Interpersonally Sensitive style. The Rapport dimension from the SWAI had low correlation (r < .00) with the Task-Oriented style of the SSI. In the present study, the Cronbach’s alpha was .95 for Rapport, .90 for Client Focus, and .96 for the entire scale.
Supervisee Levels Questionnaire-Revised
The Supervisee Levels Questionnaire-Revised (SLQ-R; McNeill et al., 1992) is used to measure supervisees’ developmental levels (Stoltenberg & Delworth, 1987). It has 30 items developed around three dimensions: Self and Other Awareness (12 items), Motivation (8 items), and Dependency-Autonomy (10 items). Supervisees can indicate their current behavior along a 7-point Likert scale, with 1 representing never, 2 rarely, 3 sometimes, 4 half the time, 5 often, 6 most of the time, and 7 always. Higher scores (after reverse-scoring for some of the items) in these dimensions reflect higher levels of supervisee development in Self and Other Awareness, Motivation, and Autonomy, respectively. A sample item for the Self and Other Awareness dimension is “I feel genuinely relaxed and comfortable in my counseling/therapy sessions”; a sample item (reverse-scoring) for the Motivation dimension is “The overall quality of my work fluctuates; on some days I do well, on other days, I do poorly”; and a sample item for the Dependency-Autonomy dimension is “I am able to critique counseling tapes and gain insights with minimum help from my supervisor.”
McNeill et al. (1992) reported that the Cronbach alpha coefficients of the SLQ-R (N = 105) were .83, .74, and .64 for the three subscales, respectively, and .88 for the total scores. To assess the construct validity of the SLQ-R, they examined the differences in subscale and total scores across the beginning, intermediate, and advanced groups. Hotelling’s test of significance indicated that the three groups differed significantly both on the total SLQ-R scores, F(2, 102) = 7.37, p < .001, and on a linear combination of SLQ-R subscale scores, F(6, 198) = 2.45, p < .026. In the present study, the Cronbach’s alpha was .89 for Self and Other Awareness, .85 for Motivation, .57 for Autonomy, and .91 for the entire measure.
Data Analysis
To thoroughly test the potential moderation effects of supervisee levels on the relationship between supervisory styles and the supervisory working alliance, I carried out three rounds of moderation analysis in which the supervisory working alliance was always the outcome variable. In the first round (n = 1), supervisory styles as a whole were the predictor, and supervisee levels as a whole were the moderator. The second round (n = 6) involved two series of analyses. In the first series (n = 3), each supervisory style was the predictor, and supervisee levels as a whole were the moderator. In the second series (n = 3), supervisory styles as a whole were the predictor, and each indicator of supervisee levels was the moderator. In the third round (n = 9), each supervisory style was the predictor, and each indicator of supervisee levels was the moderator. Figure 1 presents path diagrams of three rounds of tests and Table 2 lists all tested models (n = 16).


I followed up each significant moderation effect (n = 5) with a simple slopes analysis (Aiken & West, 1991) to interpret the nature of the interaction effect. The PROCESS v4.0 tool in SPSS was employed to perform all these analyses. A total of 166 potential participants accessed the survey, but only 113 of them completed all the study instruments (SSI, SWAI, and SLQ-R) in the present study. To alleviate the impact of significantly incomplete responses, I removed the 53 respondents who left at least one instrument unanswered. The a priori power analysis via G*Power 3.1.9.7 indicated that the minimum sample size would be 55 to detect an interaction effect with a medium effect size (f 2 = .15), given the desired statistical power level of .80 and type I error rate of .05. As such, the ultimate sample size of 113 meets this requirement.
I made the linearity and homoscedasticity assumptions using the zpred vs. zresid plot, which did not show a systematic relationship between the predicted values and the errors in the model (Field, 2017). Provided that participants independently filled out the study survey, I held the assumption of independence that the errors in the model were not dependent on each other. Further screening detected 12 missing values scattered across the three scales, which accounted for 0.13% of the entire 9,266 possible values. To determine the nature of these missing values, I performed the Little’s test (1988), and the results signified that these values were missing completely at random (MCAR; χ2 = 884.185, df = 890, p = .549). Because multiple imputation (MI; Schafer, 1999) can provide unbiased and valid estimates of associations based on information from the available data and can handle MCAR (Pedersen et al., 2017), I adopted MI to replace the missing values before performing further analyses in this study.
Results
Results of this study in part supported my broad hypothesis that the positive relationship between supervisory styles and the supervisory working alliance would be more sensitive for supervisees at earlier stages of development, compared to their more experienced counterparts. Examining each supervisory style and each indicator of supervisee levels independently revealed the intricacy of the relationship between the two constructs.
There were two groups of major findings. First, supervisee levels as a whole were a significant moderator between the interpersonally sensitive style and the supervisory working alliance according to supervisees’ perceptions, ΔR2 = .0272, F(1, 109) = 7.8551, p = .006, with a small to medium effect size
(f 2 = .07; Lorah & Wong, 2018). Specifically, the strength of the relationship between the interpersonally sensitive style and the supervisory working alliance differed based on supervisee levels (see Table 3).

In view of this significant moderation effect, I conducted a simple slopes analysis as a follow-up, which indicated that the simple slopes for 1 standard deviation (SD) below the mean, at the mean, and 1 SD above the mean of supervisee levels were 1.6185, 1.4019, and 1.1853, respectively (see Figure 2). In other words, the interpersonally sensitive style and the supervisory working alliance were positively associated (B = 1.4019, p < .001), but the strength of this correlation decreased as supervisees reported higher levels of professional development. It is worth noting that supervisees at higher developmental levels tended to report a stronger supervisory working alliance in general, compared to those at lower levels. The linear model of the interpersonally sensitive style, supervisee levels, and the product of the two (interpersonally sensitive style × supervisee levels) explained 62.31% (p < .001) of the variance in the supervisory working alliance. A further look into the moderation effect of supervisee levels indicated that statistical significance consistently persisted as each indicator of supervisee levels (self and other awareness, motivation, and autonomy) was independently tested as a moderator between the interpersonally sensitive style and the supervisory working alliance (see Round 3 in Table 2).
Figure 2
Moderation Effect of Supervisee Levels With the Interpersonally Sensitive Style on the Supervisory Working Alliance

Note. N = 113. Predictor = Interpersonally Sensitive Style; Moderator = Supervisee Levels; Outcome = Supervisory Working Alliance. The three lines of color represent three regressions with the interpersonally sensitive style as predictor and the supervisory working alliance as outcome at different supervisee levels. The blue regression line denotes the group in which supervisee levels were one standard deviation (SD) below the mean, the green denotes the group in which supervisee levels were at the mean, and the pink denotes the group in which supervisee levels were one SD above the mean.
The second major finding was about the task-oriented supervisory style. When the three indicators of supervisee levels were independently examined as moderators, it was found that self and other awareness moderated the relationship between the task-oriented style and the supervisory working alliance, ΔR2 = .0311, F(1, 109) = 5.0639, p = .0264, with a small to medium effect size (f 2 = .05; Lorah & Wong, 2018). Similar to the first group of findings, the strength of the relationship between the task-oriented style and the supervisory working alliance varied based on the level of supervisee self and other awareness (one indicator of supervisee levels; see Table 4). A simple slopes analysis signified a consistent pattern—the task-oriented style and the supervisory working alliance were positively correlated, but the strength of this relationship decreased as supervisees rated higher on self and other awareness (see Figure 3). Specifically, the simple slopes for one SD below the mean, at the mean, and one SD above the mean of supervisee self and other awareness were 1.2620, 0.9540, and 0.6460, respectively. The area below the moderator (self and other awareness) value of 13.3857 constituted a region of significance in which the relationship between the task-oriented style and the supervisory working alliance was significant (p < .05; Johnson & Neyman, 1936). The linear model of the task-oriented style, supervisee self and other awareness, and the product of the two (task-oriented style × self and other awareness) accounted for 33.13% (p < .001) of the variance in the supervisory working alliance.
Discussion
Findings of the present study corroborated the positive correlation between supervisory styles and the supervisory working alliance that has been consistently identified in the existing literature (Efstation et al., 1990; Heppner & Handley, 1981; Ladany & Lehrman-Waterman, 1999; Ladany, Walker, & Melincoff, 2001). The intricacy of this relationship was further explored, and the current study confirmed that the strength of such correlation varied across different contexts. Supervisee levels and their three indicators turned out to be significant moderators in five models out of the 16 tested. Explicitly, the positive correlation between the interpersonally sensitive style and the supervisory working alliance was stronger for supervisees at lower levels of professional development but weaker for supervisees at higher levels. Furthermore, this significant moderation effect existed not only when supervisee levels were viewed as an overarching construct but when each indicator of supervisee levels was independently examined. Moreover, this moderation pattern was echoed by the positive association between the task-oriented style and the supervisory working alliance, wherein the correlation was stronger for supervisees at lower levels of self and other awareness (one indicator of supervisee levels) but weaker for those at higher levels of self and other awareness. Notably, supervisees at higher developmental levels (including indicators of supervisee levels) in all models with significant moderation effects reported a stronger supervisory working alliance than did their counterparts at lower levels.
According to developmental theories of supervision, supervisees broadly progress through a series of qualitatively different levels in the process of becoming effective counselors, despite myriad individual idiosyncrasies (Chagnon & Russell, 1995; Stoltenberg & McNeill, 2010). Entry-level supervisees typically focus on their own anxiety, their lack of skills and knowledge, and the likelihood that they are being regularly evaluated (Stoltenberg & McNeill, 2010). Accordingly, beginning supervisees identified supervisor care and concern as one of the most important supervisor variables to allow supervisees to take risks and grow (Jordan, 2007). As such, interpersonally sensitive supervisors who are invested, committed, therapeutic, and perceptive (Friedlander & Ward, 1984) would be easily perceived as relationship-oriented and helpful in rapport building (one indicator of the supervisory working alliance) for supervisees early on in their training. Similarly, task-oriented supervisors are content-focused, goal-oriented, thorough, focused, practical, and structured (Friedlander & Ward, 1984).

Figure 3
Moderation Effect of Self and Other Awareness With the Task-Oriented Style on the Supervisory Working Alliance

Note. N = 113. Predictor = Task-Oriented Style; Moderator = Self and Other Awareness; Outcome = Supervisory Working Alliance. The three lines of color represent three regressions with the task-oriented style as predictor and the supervisory working alliance as outcome at different levels of self and other awareness (one indicator of supervisee levels). The blue regression line denotes the group in which supervisee self and other awareness was one standard deviation (SD) below the mean, the green denotes the group in which supervisee self and other awareness was at the mean, and the pink denotes the group in which supervisee self and other awareness was one SD above the mean.
Task-oriented supervisors can be perceived as particularly helpful and informative with client focus (a second indicator of the supervisory working alliance) for beginning supervisees (as indicated by their lower self and other awareness) who commonly experience substantial anxiety or fear pertaining to their lack of confidence in knowing what to do, being able to do it, and being evaluated by their clients or supervisors (Stoltenberg & McNeill, 2010).
Therefore, supervisees at lower levels of professional development were more likely to report a stronger supervisory working alliance as they perceived more interpersonally sensitive or task-oriented supervisor characteristics. As they progress to higher levels of development with accumulated knowledge, skills, and competencies, supervisees become more aware of clients and themselves, intrinsically and consistently motivated, and autonomous as practitioners (Stoltenberg & McNeill, 2010), which may in part explain why their ratings of the supervisory working alliance were less related to their perceptions of supervisor characteristics but generally higher than supervisees at lower levels of development.
In the present study, the moderator of supervisee levels as a composite score was only significant when the interpersonally sensitive style was the predictor; the moderator of self and other awareness (one indicator of supervisee levels) was also significant when the task-oriented style was the predictor. These findings resonated with the existing literature in that compared to the attractive style, the interpersonally sensitive and task-oriented styles tend to have stronger discriminating effects (Friedlander & Ward, 1984). For instance, practicum and internship students differed significantly in rating the task-oriented and interpersonally sensitive styles of their supervisors, but their perceptions about the attractive style were similar at both levels (Friedlander & Ward, 1984). Li, Duys, and Vispoel (2020) also found that supervisory state–transitional patterns differed significantly only based on the interpersonally sensitive style but not the other two styles.
Implications for Clinical Supervision
The supervisory working alliance is inextricably intertwined with supervisees’ willingness to disclose (Ladany et al., 1996), supervisee satisfaction with clinical supervision (Cheon et al., 2009; Ladany, Ellis, & Friedlander, 1999), supervisee work satisfaction and work-related stress (Sterner, 2009), and therapeutic working alliance (DePue et al., 2016; DePue et al., 2022), among others. Nelson et al. (2001) proposed that a key task in early supervision is to build a strong supervisory working alliance that serves as a foundation to manage future potential dilemmas in supervision, and the ongoing maintenance of this working alliance should be the supervisor’s responsibility throughout the supervisory relationship. Although the three supervisory styles appear to be clear-cut with distinguishable characteristics and roles (Friedlander & Ward, 1984), supervisors are encouraged to adopt a composite of different styles to varying degrees to better serve supervisees’ needs. As revealed by the present study, and also the extant literature (Efstation et al., 1990; Ladany, Walker, & Melincoff, 2001; Li et al., 2021), supervisees were more likely to report a stronger supervisory working alliance as they perceived their supervisors to adopt a mixture of three supervisory styles (i.e., higher overall ratings of supervisory styles).
Particularly, beginning supervisees are characteristic of a strong focus on self, extrinsic motivation, and high dependency on supervisors (Stoltenberg & McNeill, 2010). Supervisors’ emphases on relationship-building (interpersonally sensitive style) and task focus (task-oriented style) would help build a safe, predictable supervision environment and enhance the working alliance with supervisees. Notably, although the strengths of the correlation between the interpersonally sensitive or task-oriented style and the supervisory working alliance were stronger for beginning supervisees, they did not suggest that these styles would not be effective in augmenting the alliance for supervisees at higher levels of professional development. The positive correlations still existed, albeit smoother, for more advanced supervisees, and they reported higher levels of supervisory working alliance in general, which may imply that these styles help maintain the working alliance that has been established early on in supervision.
Another point that is worth noting is that although no significant moderator was detected between the attractive style and the supervisory working alliance in the present study, the attractive style explained the most variance (68.1%, p < .001) in the supervisory working alliance, compared to the interpersonally sensitive (55.9%, p < .001) and task-oriented styles (24.1%, p < .001). This finding made it clear that the warm, supportive, friendly, open, and flexible features of attractive style supervisors are foundational to building and maintaining the supervisory working alliance, which does not differentiate across different levels of supervisees. As such, supervisors are encouraged to bring these qualities to their supervision and make them perceived by supervisees.
Limitations and Future Research
This study is not exempt from limitations that may be addressed in future research. Although two moderators (supervisee levels, self and other awareness) were found to be significant in the present study, the effect sizes of both were small to medium (f 21 = .07 and f 22 = .05), which were lower than the speculated medium effect size (f 2 = .15) during the a priori power analysis. Provided the effect sizes of .07 and .05 for the moderation effect, to achieve the statistical power of .80 with the α error probability of .05, the required sample size would be 115 and 159, respectively. Researchers need to be more mindful when recruiting participants to ensure the sufficient sample size. Additionally, although supervisees were asked to respond to the questionnaires consistently based on their perceptions of one supervisor, a constellation of factors could have affected their perceptions—for example, the timing of a participant’s supervisee status (e.g., currently receiving supervision vs. received supervision in the past), the potential dual role that a participant may be in (e.g., a doctoral student who is both a supervisee and a supervisor), the level of supervision (e.g., practicum, internship), and the length of the supervisory relationship (e.g., 2 months vs. 2 years). Researchers in future studies could also collect more information about participants (e.g., geographic distribution) to help readers better contextualize study results. Also, the current data set was collected in 2017–2018, which would not be able to capture more recent societal, cultural, political, and economic changes (e.g., the COVID-19 pandemic) that could have affected supervisee perceptions.
In the present study, the association between supervisory styles and the supervisory working alliance was examined in the context of different supervisee levels. Indeed, this alliance could be subject to many other factors, such as discussions of cultural variables in supervision (Gatmon et al., 2001), supervisor adherence to ethical guidelines (Ladany & Lehrman-Waterman, 1999), and relational supervision strategies (Shaffer & Friedlander, 2017), among others. Scholars may include more related variables to expand the current model so as to further disentangle the complex relationships among predictors of the supervisory working alliance.
Last, although multiple moderation effects identified in the present study were statistically significant and theoretically coherent, exactly how supervisees experience the supervisory working alliance in relation to different supervisory styles as they proceed along the professional development is less known. A longitudinal track of the same sample using repeated measures or a qualitative inquiry into participants’ lived experiences of the targeted phenomenon could enrich our understanding of the study variables in this research.
Conclusion
Although the positive correlation between supervisory styles and the supervisory working alliance is well documented in the existing literature, the present study examined such relationships specifically in the context of supervisee levels. Both supervisee levels (as a whole) and self and other awareness (one indicator of supervisee levels) appeared to be significant moderators under different contexts. These findings further revealed the intricacies embedded in the broad relationship between supervisory styles and the supervisory working alliance, pointed out future research directions concerning supervisee development, and encouraged supervisors to adopt a composite of styles to varying degrees to better support supervisee growth.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.
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Dan Li, PhD, NCC, LSC (NC, K–12), is an assistant professor of counseling at the University of North Texas. Correspondence may be addressed to Dan Li, Welch Street Complex 2-112, 425 S. Welch St., Denton, TX 76201, Dan.Li@unt.edu.
Jun 27, 2022 | Book Reviews
by Beatriz Sheldon and Albert Sheldon
Beatriz Sheldon, MEd, and her partner, Albert Sheldon, MD, describe their novel therapeutic approach, Complex Integration of Multiple Brain Systems (CIMBS), in this new publication. Throughout the book, references are made to the Sheldons’s 20 years of working together, 15 years of clinical experience, and 10 years of training other practitioners in CIMBS therapy. The authors emphasize that they “are practical, empirical therapists” (p. xvii). The book is seeded with references to scientists who inspire the duo, especially Daniel J. Siegel, Joseph LeDoux, Antonio Domasio, and the late Jaak Panksepp. It must be noted that CIMBS therapy as laid out in this text contains no peer-reviewed qualitative or quantitative studies; instead, the authors utilize vignettes to discuss their methods.
The brain systems referred to in CIMBS are organized into sections much like those of the triune brain model, with an additional peripheral system in the heart, lungs, and intestines. What the triune brain model labels the lizard brain relates to the primary level, the mammal brain is the secondary level, and the human brain is the tertiary level. The Sheldons assign awareness, attention, authority, autonomy, and agency (the “A Team”) to the conscious tertiary level. The secondary level holds nonconscious, inhibitory systems of fear, grief, shame, and guilt. The primary level, also nonconscious, contains the systems of safe, care, connection, sensory, assertive, play, and seeking.
The patient accesses the hidden strengths of the nonconscious mind via the CIMBS therapist’s use of techniques like Transpiring Present Moment, Go the Other Way, and Initial Directed Activation. Transpiring Present Moment is reminiscent of Fritz Perls’s emphasis on the “here-and-now.” Go the Other Way asks the patient to avoid getting bogged down in traumatic memories and instead reach for personal strengths. The CIMBS therapist cultivates the therapeutic alliance using the Therapeutic Attachment Relationship, which includes physical postures that suggest safety, reminding us of Egan’s SOLER stance taught in many counseling programs. This intervention also recommends intense focus on the patient’s micro-expressions as a guide to their conscious and nonconscious processes. Ultimately, the patient will integrate all 20 brain systems effectively and reach Fail-Safe Complex Network, a new, durable neural structure generating improved mental health.
Although the authors refer several times to the text’s internal contradictions or incongruence, the writing has the same appeal as the work of the Sheldons’s mentor, Dan Siegel, who wrote the Foreword. The book asks readers to lean on their intuition, often reminding them to “trust the process.” Nicola Swaine has provided line drawings to clarify central concepts, much as Siegel uses a curled fist to describe the triune brain. The authors relate that this text was written expressly to provide an overview of the Sheldons’s 16-part CIMBS training series (recorded and live) for students and trainees, who will find the glossary and bibliography especially useful.
In the Foreword, Siegel refers to the “cross-disciplinary framework known as interpersonal neurobiology . . . [using] universal principles discovered by independent pursuits of knowledge” (p xii). It would be useful to know which principles are considered universal in this book. Psychology sits forever on the fence between hard and soft science; some declarations of fact are based on microscopic studies of physical structures, and some are useful models that are at least partly philosophical. This text contains both. Neurologists have observed neural repairs and rerouting; thus, neuroplasticity is a demonstrable fact. The Sheldons describe 20 brain systems while noting that “one could certainly make the case for more or fewer systems” (p. 26). Clearly the number and definition of these brain systems can be thought of as helpful metaphors, a bit like Marsha Linehan describes a “wise mind” that is not a physical structure existing in the brain.
Professional counselors who like eclectic methods and enjoy pulling inspiration from many sources will appreciate CIMBS and this flagship text. The authors caution practitioners not to use CIMBS for patients who struggle with borderline personality disorder or dissociative, bipolar, or psychotic disorders. Although the Sheldons encourage clinicians to practice with their highest-functioning patients, the wise professional counselor will first disclose methods and procedures to patients.
Sheldon, B., & Sheldon, A. (2021). Complex integration of multiple brain systems in therapy. W. W. Norton.
Reviewed by: Christine Sheppard, MA, LCPC, NCC
The Professional Counselor
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Jun 13, 2022 | TPC Outstanding Scholar




Shaywanna Harris-Pierre, Christopher T. Belser, Naomi J. Wheeler, and Andrea Dennison received the 2021 Outstanding Scholar Award for Concept/Theory for their article, “A Review of Adverse Childhood Experiences as Factors Influential to Biopsychosocial Development for Young Males of Color.”
Shaywanna Harris-Pierre, PhD, LPC, is an assistant professor of professional counseling at Texas State University. Her research centers on the psychological and physiological impact of trauma and race-based traumatic stress. Dr. Harris-Pierre serves her community through facilitating free workshops for couples where she provides psychoeducation on communication skills. Dr. Harris-Pierre also serves the counseling profession through her position as secretary for the Association for Assessment and Research in Counseling, and her role as an editorial board member for the Journal of Addictions & Offender Counseling, Counseling Outcome Research and Evaluation, and the Journal of Multicultural Counseling and Development.
Christopher T. Belser, PhD, NCC, is an assistant professor in the counselor education program at the University of New Orleans. He earned his PhD in counselor education and supervision at the University of Central Florida and his MEd in school counseling at Louisiana State University. Dr. Belser has experience in Louisiana public and charter schools as a middle school counselor and a high school career coach. His research interests include school counselor preparation/practice and interdisciplinary P–16 STEM career development initiatives. Dr. Belser has delivered dozens of presentations at local, state, national, and international conferences and has published numerous articles and book chapters on counseling and career-related topics. He is the current associate editor of the Journal of Child & Adolescent Counseling, served as Chi Sigma Iota’s 2020–2021 Edwin Herr Fellow, and previously won The Professional Counselor’s 2018 Dissertation Excellence Award.
Naomi J. Wheeler, PhD, NCC, LPC, LMHC, is an assistant professor in counselor education and supervision at Virginia Commonwealth University. Her research builds on her professional and clinical experiences to examine relationship health across the life span, including the role of early life family adversity (such as ACEs) and couple stress as contributors to health disparities. Dr. Wheeler is also the co-director for the Urban Education and Family Center at VCU, which serves as a hub for community-engaged research and program services that address educational attainment, economic mobility, and individual and family well-being for historically marginalized populations living in poverty from a two-generational approach. The Center strives to harness research to improve the quality of life for Black and Latinx families in the greater Richmond area through community-based work.
Andrea Dennison, PhD, is an assistant professor at Texas State University.
Read more about the TPC scholarship awards here.
Jun 13, 2022 | TPC Outstanding Scholar



Fei Shen, Yanhong Liu, and Mansi Brat received the 2021 Outstanding Scholar Award for Quantitative or Qualitative Research for their article, “Attachment, Self-Esteem, and Psychological Distress: A Multiple-Mediator Model.”
Fei Shen, PhD, is a staff therapist at the Barnes Center at the Arch – Counseling at Syracuse University. Her clinical and research interests include attachment and trauma healing. She specifically focuses on understanding the impact and prevention of adverse childhood experiences (ACEs) in marginalized communities, as well as identifying mediating and moderating factors that can protect survivors from the negative effects of trauma.
Yanhong Liu, PhD, NCC, is an associate professor in the Counseling & Human Services Department at Syracuse University. She also serves as the MS in School Counseling P–12 Program Coordinator. Her scholarship centers around marginalized youth and supporting systems. She has published widely and consistently in counseling as well as interdisciplinary journals on the topics of adopted youth, school bullying, school-based programs, and counselor training.
Mansi Brat, PhD, LPC, LMHC, is an adjunct professor at Syracuse University. Dr. Brat’s scholarship focuses on mindfulness-based programs (MBP), social justice, counselor professional identity and advocacy, contemplative sciences, and humanistic psychology. She has published across interdisciplinary journals and is extremely passionate about furthering her research in highlighting the many layers of implicit bias that remain critical in dismantling racism and oppression amongst dominant groups.
Read more about the TPC scholarship awards here.