Emily Sallee, Abraham Cazares-Cervantes, Kok-Mun Ng
Suicide is the second leading cause of death in adolescents (ages 12–19) in the United States, and more work is needed to shed light on the interpersonal protective factors associated with adolescent suicidality. To address this gap in the empirical literature, we examined the application of the Interpersonal Theory of Suicide (IPTS) to the middle adolescent population. We analyzed survey data using the 2017 Oregon Healthy Teen dataset, which included 10,703 students in 11th grade. Binary logistic regressions were used to examine the extent to which the IPTS constructs of perceived burdensomeness and thwarted belongingness predicted middle adolescent suicide ideation and attempt. Findings indicate that three of the five proxy items were statistically significant in each model, with consistent mediators for each. These findings have the potential to guide development of appropriate treatment strategies based on the interpersonal constructs of the IPTS for clinicians working with this population.
Keywords: adolescents, suicide ideation, suicide attempt, suicidality, Interpersonal Theory of Suicide
Suicide is a leading cause of death worldwide, spanning across all ages, ethnicities, genders, cultures, and religions. In the United States from 2000 to 2015, suicide rates increased 28%, with 44,193 people dying by suicide yearly, equating to about one death every 12 minutes. Nationally, statistics now identify suicide as the second leading cause of death in adolescent populations (Centers for Disease Control and Prevention [CDC], 2017). Specific to the state of Oregon, over 500 youth between the ages of 10–24 were hospitalized each year because of self-harm, including suicide attempts. In 2017 alone, more than 750 youth were hospitalized and 107 suicides were completed; considering that many ideations and attempts do not result in hospitalization, it is likely that there were more Oregonian youth who had attempted suicide but were never hospitalized, and an even greater number who had contemplated suicide (Oregon Suicide Prevention, n.d.).
Unfortunately, studies on suicide, particularly adolescent suicide, are rarely driven by theory. This results in a lack of integration between research findings and clinical practice (King et al., 2018). Clinicians working with the adolescent population are in need of research- and evidence-based practices ready for implementation. Although the Interpersonal Theory of Suicide (IPTS; Joiner et al., 2009) was initially developed for and then applied to adult populations, it has the potential to inform clinicians in preventative and intervention efforts in other populations, offering an evidence-based framework to understand and address suicide prevention and intervention. In an earlier study (Sallee et al., 2021), we found evidence to support its use with the early adolescent (ages 11–14) population. The present study utilizes the IPTS as a framework to examine the interpersonal drivers of suicidality among middle adolescents (ages 14–17) in Oregon.
Joiner et al.’s (2009) IPTS offers a theoretical lens to explain suicide ideation and behavior in three dynamic constructs: perceived burdensomeness, thwarted belongingness, and acquired capability. The first two are influential in suicidal desire. The dynamicity of the constructs is related to the fluctuation of interpersonal needs and cognitions over time. Together they contribute to significant risk for suicide ideation. Acquired capability is static and believed to develop in response to exposure to provocative, painful, and/or violent experiences, overpowering the human survival need of self-preservation. Acquired capability, in tandem with thwarted belongingness and perceived burdensomeness, results in a high risk for suicidal behavior/attempt (King et al., 2018).
This field of research uses terms like suicide ideation, suicidal behavior, suicidology, self-harm, self-injury, and self-inflicted death to describe the thoughts and behaviors of a person ending their own life. The CDC defines suicide ideation within a broader class of behavior called self-directed violence, referring to “behaviors directed at oneself that deliberately results in injury or the potential for injury . . . [it] may be suicidal or non-suicidal in nature” (Stone et al., 2017, p. 7). The intent of suicidal self-directed violence is death, while the intent of non-suicidal self-directed violence is not. A suicide attempt may or may not result in death or other injuries. Because we held a particular interest in adolescent suicide ideation and behavior, its differentiation of lethal intent from non-suicidal self-injury (NSSI) led us to leave NSSI ideation and/or behavior out of the scope of the study. However, recent studies addressing IPTS have included self-harm as an indicator of acquired capability (e.g., Barzilay et al., 2019) and should be included in future studies involving this construct.
Suicide ideation and attempt in adolescent populations is a serious public health concern in the United States that is growing in frequency and intensity every year. National statistics suggest that 17.2% of adolescents have experienced or currently experience suicide ideation, and 7.4% of adolescents have made a suicide attempt (CDC, 2017). Despite this growing health concern, most research in this body of work has focused primarily on adult populations (Horton et al., 2016; Stone et al., 2017). Limitations in the extant empirical literature include a lack of emphasis on theory as well as a lack of quantitative research on large samples in non-inpatient treatment settings (Czyz et al., 2015; Horton et al., 2016; Miller et al., 2014). In clinical practice, this challenges mental health practitioners’ ability to rely on evidence to serve their clients. Becker et al. (2020) found significant evidence of the applicability of IPTS to a large undergraduate (ages 18–29) population, suggesting that the interpersonal constructs might be applicable to younger non-inpatient groups. Based on the IPTS, this study examined the extent to which a specific set of interpersonal predictors of perceived burdensomeness and thwarted belonging were associated with suicide ideation and attempt in a large non-clinical sample of middle adolescents.
Adolescents and Suicidality
Adolescence marks the developmental period between childhood and adulthood, corresponding to the time from pubertal onset to guardian independence. This period is associated with increased risk-taking behaviors as well as increased emotional reactivity, occurring in the context of developmental changes influenced by external and internal factors that elicit and reinforce behaviors. Cognitively, over the course of adolescence, the prefrontal cortex of the brain continues to develop and is responsible for impulse control and delayed gratification in favor of more goal-directed choices and behaviors (Jaworska & MacQueen, 2015). One apparent risk factor for suicide ideation and behavior in adolescents is their impaired decision-making. In addition, this developmental period also accounts for half of all emotional and behavioral disorder diagnoses and the highest rates of suicide with subsequent higher risks for suicidal behavior during their lifetime (Wyman, 2014). Wasserman et al. (2015) metabolized research supporting the theory that most pathological changes occur in childhood and adolescence, suggesting that it is during this developmental time period that prevention and intervention is imperative, as the adolescent years themselves prove to be a risk factor for suicide ideation and behavior.
The typical age of 11th grade students is 16 or 17, and these students are characterized as being in the developmental period known as “middle adolescence.” By this age, puberty is typically completed for both males and females, and adolescents begin setting long-term goals, concurrently becoming more interested in the meaning of life and moral reasoning. They experience an increased drive for independence and increased self-involvement. During the overall developmental stage of adolescence, youth must adjust to their physically and sexually maturing bodies and feelings; define their personal sense of identity and adopt a personal value system; renegotiate their relationships with parents, family, and caregivers; and develop stable and productive peer relationships (Teipel, 2013).
Of relevance to the present study, it is important to note that according to Teipel (2013), adolescents in 11th grade (ages 16–17) experience an increased concern with their appearances and bodies, incorporating a personal sense of masculinity or femininity into their identities and establishing values and preferences of sexual behavior. This period of self-involvement results in high expectations of self and low self-concept, coinciding with an increased drive for peer acceptance and reliance (American Academy of Child & Adolescent Psychiatry, 2021). Additionally, as the typical adolescent is tasked with gaining autonomy and independence from the nuclear family, they will likely experience periods of sadness as the psychological loss, not so unlike grief, takes place (Teipel, 2013). Adolescents in the 11th grade school environment are preparing for the final year of high school and potentially postsecondary education after graduation, creating unique stressors related to increasing autonomy and independence as they approach the formidable ascent into adulthood.
Theories of suicide have evolved over the past 70 years to reflect research and societal influences and implications, yet they all seem to agree that “perceived disruption of interpersonal relationships may serve as one potential mechanism of the association between child maltreatment and [suicide ideation]” (Miller et al., 2014, p. 999). Durkheim and Simpson (1951) suggested that suicide was the result of social causes like isolation, altruism, and anger/frustration. Behavioral theorists like Lester (1987) believed that suicide was a learned behavior, resulting from adverse childhood experiences and psychosocial environmental factors. Schneidman (1993) thought suicidal behaviors were motivated by the desire to escape emotional pain caused by the lack of socially supportive and nurturing relationships. Joiner’s IPTS focuses on the importance of interpersonal relationships, characterized by the confluence of two negative interpersonal states (i.e., perceived burdensomeness and thwarted belongingness; Miller et al., 2014).
The present study was guided by several gaps in the literature related to the application of the IPTS to adolescent populations. Initially, the IPTS was constructed by Joiner and his colleagues (2009) through studying adults engaging in suicidal behaviors. Since its development, the theory has been studied primarily in its application to adult and college student populations (Horton et al., 2016). The lack of research on the application of the IPTS to non-inpatient adolescents may suggest its incompatibility to the uniqueness of adolescent suicidality; however, Horton et al. (2016) argued that the constructs of the theory are relevant in adolescence regardless of setting and presentation, though they may manifest in slightly different ways based on differences in developmental context. As such, they proposed that perceived burdensomeness in adolescents may manifest as low academic competency or social disconnection and thwarted belongingness may manifest as social isolation from peers or poor family cohesion. Adolescence is also a developmental period when children may begin to engage in health-risk behaviors, are particularly prone to impulsivity because of the immature nature of their prefrontal cortex, and have the increased pressure of peer behavior on their own, as well as a sense of invulnerability to consequences (Horton et al., 2016). Though adolescent suicide–related research based on the IPTS to date remains sparse, the theory’s focus on the dynamic constructs of perceived burdensomeness and thwarted belongingness appears attractive in consideration of potential application to preventative and responsive efforts.
Perceived burdensomeness is characterized by self-hatred and the belief that one is a burden to others, including family and friends, leading to the idea that they would be better off without them. It deals with the misperceptions of being a liability for family and intimate peers. As a dynamic interpersonal construct, it responds well to both interpersonal and intrapersonal interventions. However, although perceived burdensomeness responds more slowly to intervention, it may be a more significant predictor of suicide ideation and behavior than thwarted belongingness. There is also research that suggests that thwarted belongingness and perceived burdensomeness are more enmeshed in adolescents, suggesting that only one of the dynamic interpersonal constructs is necessary to be coupled with acquired capability and lead to suicidal behavior (Chu et al., 2016; Joiner et al., 2012; Stewart et al., 2017).
Thwarted belongingness is a dynamic condition of social disconnection described by the interpersonal state of loneliness in which the psychological need to belong is not met. Of the two dynamic interpersonal constructs within the IPTS that respond to both interpersonal and intrapersonal interventions (thwarted belongingness and perceived burdensomeness), research suggests that thwarted belongingness may be easier to treat and respond more quickly to intervention than perceived burdensomeness (Chu et al., 2016; Joiner et al., 2012; Stewart et al., 2017). It has been well established that positive and negative effects of close relationships are particularly formative in the adolescent years, and therein lies the difficult developmental task of establishing strong peer relationships while also maintaining familial bonds (Miller et al., 2014). Relatedly, adolescents with histories of abuse or other maltreatment are at particular risk. It has been shown that low perceived quality of family and peer connectedness and belonging contribute to thwarted belongingness and its dynamic interpersonal state.
Acquired capability is a static construct in the IPTS, describing a decrease in or lack of fear about death and an elevated tolerance of physical pain. It is suggested to be developed through repeated exposure to painful and provocative events (Chu et al., 2016; Joiner et al., 2012; Stewart et al., 2017). Stewart et al. (2017) characterized it as “the combination of increased pain tolerance and decreased fear of death [that] results in progression from suicide intent to suicidal behavior, culminating in a suicide attempt” (p. 438). This construct’s combination of pain tolerance and fearlessness about death is significant in current conversations around adolescents engaging in violent video games, which could correlate to fearlessness about death but not necessarily pain tolerance (Stewart et al., 2017). Acquired capability as the combination of pain tolerance and fearlessness is also significant to other mental health disorders, including anorexia nervosa, in which risk factors for suicide ideation and behavior are prevalent and are characterized by increased pain tolerance and fearlessness about death.
According to the IPTS, these three constructs are proximal to suicidal behavior. Horton et al. (2016) suggested that “an important strength of the theory is that it explains the lower frequency of more severe levels of suicidality (such as suicide attempt) compared to less severe levels (such as passive suicide ideation)” (p. 1134) because it is the combination of the three constructs that leads to suicidal behavior. The theory also posits that the difference between passive and active suicide ideation is the difference between the presence of one or both of the dynamic interpersonal states of thwarted belongingness and perceived burdensomeness. In other words, one dynamic interpersonal construct suggests passive ideation, two suggest active ideation, and all three constructs lead to suicidal behavior.
Purpose of the Present Study
Most previous studies that applied the IPTS to suicidal adolescents of this specific age group only addressed inpatient populations (e.g., Czyz et al., 2015; Horton et al., 2016; Miller et al., 2014). However, our recent study (Sallee et al., 2021) indicated support for using this theory in understanding suicide ideation and attempts among non-inpatient early adolescents. Specifically, the findings revealed significance in multiple mediators representing the IPTS constructs of perceived burdensomeness and thwarted belongingness. The significant drivers for suicide ideation included emotional/mental health and feeling sad/hopeless as the proxy items for perceived burdensomeness, and not straight and bullied as the proxy items for thwarted belongingness. Similarly, the significant drivers for suicide attempt included emotional/mental health and feeling sad/hopeless as the proxy items for perceived burdensomeness, and non-binary and bullied as the proxy items for thwarted belongingness. The current study extends the efforts of using the IPTS in studying suicidality among adolescents to an older age range (ages 16–17). Using the theory to examine suicidal behavior among middle adolescents in school settings can potentially extend its utility and inform practitioners who are working with youth in this age group who struggle with suicide ideation and behavior in various settings such as mental health and medical.
Based on the IPTS, the focus of this study was to examine the extent to which the interpersonal constructs of perceived burdensomeness and thwarted belongingness predict adolescent suicide ideation and attempt. In consideration of the aforementioned needs and gaps in this field of study, we formulated two research questions: 1) To what extent do feelings of perceived burdensomeness and thwarted belongingness predict suicide ideation among 11th grade students (a middle adolescent population) in Oregon? and 2) To what extent do feelings of perceived burdensomeness and thwarted belongingness predict suicide attempts among 11th grade students (a middle adolescent population) in Oregon? We hypothesized that the two dynamic IPTS constructs would both statistically significantly predict suicide ideation and suicide attempts in this population.
A dataset of 10,703 participants was selected from the randomized weighted sample of 11,895 students in 11th grade who participated in the 2017 Oregon Healthy Teen (OHT) survey, a comprehensive assessment measuring risk factors and assets shown to impact successful development (Oregon Health Authority [OHA], 2017). This dataset was selected for its representation of middle adolescents at the cusp of a monumental transition in life—finishing K–12 education and embarking on what is to come. Participants’ ages ranged from 16 to 17 years (M = 16.7 years). In terms of gender identity, 48.9% self-identified as female, 45.6% as male, and 5.5% as non-binary/gender nonconforming, which included those who identified as “transgender, gender nonconforming, genderqueer, gender fluid, intersex/intergender, or something else.” Among the participants, 85.9% spoke English at home. The racial/ethnic composition was as follows: 62.9% White, 25% Hispanic/Latino, 3.6% Asian, 2.2% Black or African American, 5.5% other, and 0.8% multiple.
We conducted a secondary analysis of archival survey data collected in the 2017 OHT survey. The 2017 OHT study utilized a probability design (i.e., all participants’ datasets had equal chances to be selected for the sample) to minimize possible selection biases and a randomization process (lottery method or computer-generated random list) to minimize sampling error with stratification of school regions. The survey was administered by school officials during one designated school period, utilizing standardized procedures to protect student privacy and facilitate anonymous participation. The researchers obtained IRB approval prior to requesting and receiving the data in SPSS format from the OHA.
The OHT Dataset
The OHT survey has origins in the Youth Risk Behavior Survey, a biennial national survey developed by the CDC. The 2017 OHT survey, administered to volunteering eighth and 11th grade students with a school response rate of 83% (R. Boyd personal communication, February 22, 2019), was chosen for this study because it explores a variety of health-related items, including suicidality, and has additional items deemed suitable for proxy descriptors of the IPTS constructs. The 11th grade dataset was selected for the study to target this specific developmental period because of its characteristic of impaired decision-making serving as a risk factor for ideation and behavior. Additionally, adolescents who experience suicidality during this age range are at a higher risk of suicide ideation and attempt in subsequent life stages compared to adolescents who did not experience suicidality at this time (Wyman, 2014).
In this study, the dynamic interpersonal constructs of the IPTS—perceived burdensomeness and thwarted belongingness—served as variables predicting the two outcome variables of suicide ideation and suicide behavior/attempt. The third construct of the IPTS, acquired capability, was not included as a predictor variable because of its staticity and ineffective response to intervention. We were also unable to locate items in the OHT survey that could be used as proxy items for acquired capability. The two predictor variables were measured with proxy items in the OHT survey (OHA, 2017). The proxy items for each predictor variable were chosen based on empirical research (Horton et al., 2016; Miller et al., 2014; Seelman & Walker, 2018; Zhao et al., 2010). Both outcome variables (suicide ideation and suicide behavior/attempt) were direct questions in the survey, surveyed as follows: 1) “During the past 12 months, did you ever seriously consider attempting suicide?” (Yes/No), and 2) “During the past 12 months, how many times did you actually attempt suicide?” (0, 1 time, 2 or 3 times, 4 or 5 times, 6 or more times). The second question was recorded to combine any number of times larger than zero, reflecting the response that either the participant had not attempted suicide (0) or had attempted suicide (1).
As previously noted, the selection of proxy items was based on previous empirical research on suicidality, adolescent suicidality, and the IPTS (Horton et al., 2016; Miller et al., 2014; Seelman & Walker, 2018; Zhao et al., 2010). The proxy items selected for this specific study differed slightly from the researchers’ previous study with a younger population (early adolescents) because of the developmentally appropriate differences in the eighth and 11th grade OHT survey tools.
The first predictor variable (perceived burdensomeness) was measured with two proxy survey items: emotional/mental health and sad/hopeless feelings. Emotional/mental health was chosen as a proxy item for the predictor variable of perceived burdensomeness because of the research connecting mental health challenges to emotional strain in the family setting, suggesting a potential perception of being a burden on loved ones (Miller et al., 2014). The survey item for emotional/mental health read: “Would you say that in general your emotional and mental health . . .” with the answer options including: 1) Excellent, 2) Very good, 3) Good, 4) Fair, and 5) Poor. The proxy item of sad/hopeless feelings was chosen because of its inclusion in the definition of perceived burdensomeness but exclusion from many studies of the IPTS (Horton et al., 2016). The survey item for sad/hopeless feelings read: “During the past 12 months, did you ever feel so sad or hopeless almost every day for two weeks or more in a row that you stopped doing some usual activities?” with the answer options of simply Yes or No.
The second predictor variable (thwarted belongingness) was measured with three proxy survey items: sexual orientation, sexual identity, and volunteering (inverse). As previously described, thwarted belongingness constitutes the interpersonal state of loneliness and lack of social connection. Sexual orientation and sexual identity were chosen as proxy items for the variable of thwarted belongingness because sexual minority students experience higher rates of bullying and a greater likelihood of suicidal behaviors (Seelman & Walker, 2018); gay, lesbian, and bisexual adolescents attempt suicide at 2 to 6 times the rate of non–gay, lesbian, and bisexual adolescents, suggesting that a sexual minority status is in itself a risk factor for suicidal behaviors, and a child identifying as gay, lesbian, or bisexual and/or as a non-cisgender youth may experience feelings of thwarted belongingness among a peer group (Zhao et al., 2010). The survey item for sexual orientation read: “Do you think of yourself as . . .” with the answer options including: 1) Lesbian or gay; 2) Straight, that is, not lesbian or gay; 3) Bisexual; 4) Something else (Specify); and 5) Don’t know/Not sure. The survey item for sexual identity read: “How do you identify? (Select one or more responses)” with the answer options including: 1) Female, 2) Male, 3) Transgender,
4) Gender nonconforming/Genderqueer, 5) Intersex/Intergender, 6) Something else fits better (Specify), 7) I am not sure of my gender identity, and 8) I do not know what this question is asking. Volunteering (inverse) was chosen because of its suggestion of contributing to society and feeling a sense of belonging and value within the community. The survey item for volunteering read: “I volunteer to help others in my community” with the answer options including: 1) Very much true, 2) Pretty much true, 3) A little true, and 4) Not at all true. Data from this final question was inversely recoded in order to be comparable to the other proxy items.
The CDC utilized existing empirical literature to analyze the self-reported survey data, assessing for cognitive and situational factors that might affect the validity of adolescent self-reporting of behaviors. Through analysis, it was determined that self-reports are in fact affected by both cognitive and situational factors, but the factors do not threaten the validity of self-reports of each behavior equally (Brener et al., 2013).
This study addresses what impact the predictor variables of perceived burdensomeness and thwarted belongingness have on the outcome variables of suicide ideation and suicide attempt in this particular adolescent population. The selected proxy items had variable answer options (ranging from binary choice to a 7-point Likert scale), so each proxy item for the predictor variables was individually entered with the intention of disaggregating to assess whether or not different combinations of the variables are better predictors of the outcome variables.
The two outcome variables were surveyed as follows: (a) suicide ideation (“During the past 12 months, did you ever seriously consider attempting suicide?”) and (b) suicide attempt (“During the past 12 months, how many times did you actually attempt suicide?”; OHA, 2017). The second question was recoded to allow both questions to be assessed on a binary scale (no/yes), with no equaling 0 and yes equaling 1.
With binary scaled data for the outcome variables, we decided to utilize a binomial logistic regression statistical test to assess the research questions. Additionally, each predictor variable was separately analyzed in order to isolate each outcome variable and consider how the predictor variables influenced each other.
In sum, we examined the descriptive statistics of the survey, created variables based on the selected proxy survey items, and tested the assumptions for utilizing a binomial logistic regression statistical test. Finally, we executed two logistic regression models to determine the relationships between the predictor variables and the two outcome variables—suicide ideation and suicide attempt.
Table 1 presents the descriptive statistics of the study variables. Although 11,868 students in the 11th grade completed the 2017 OHT survey, data from only 10,703 students were included in the analysis because of recording and data collection errors on those excluded from the analyses, due to missing or incomplete data. Therefore, the descriptive statistics of the study variables reported in the table reflect the data of the 10,703 students applicable for use in the logistic regression model of this study. Given the large sample size, we utilized a p-value threshold of less than 0.01.
||M or %a
||SD (if applicable)
|Felt Sad/Hopeless (Yes)
a Some variables were reported as means, and some variables were reported as percentages.
A binomial logistic regression was conducted to quantify the effects of the individual proxy items measuring the predictor variables of perceived burdensomeness and thwarted belongingness on students experiencing suicide ideation (Research Question 1). All five proxy items were entered into the model for the outcome variable. During the data screening process, two proxy items were eliminated (i.e., non-binary, volunteer), as they did not indicate significant results. Regression results indicated the overall model of the three remaining predictors (emotional/mental health, felt sad/hopeless, not straight) was statistically reliable in distinguishing between 11th grade students who did not experience suicide ideation and those who did (Nagelkerke R2 = .413; p < .001). As such, the suicide ideation model was deemed statistically significant—X2(5) = 3104.194—with an overall positive predictive value of 85.5%.
Of the two proxy items for the perceived burdensomeness variable, both proved to be statistically significant (Table 2). Specifically, increased poor emotional/mental health was related to the increased likelihood and occurrence of suicide ideation. Additionally, participants who reported feeling sad or hopeless for at least 2 weeks were over twice as likely to experience suicide ideation than those who did not report feeling sad or hopeless. Of the three proxy items for the thwarted belongingness variable, only one proved to be statistically significant: Students who reported as not straight were more than twice as likely to experience suicide ideation as students who reported as straight.
Logistic Regression Predicting Likelihood of Suicide Ideation
Similarly, a binomial logistic regression test was conducted to determine the effects of the proxy items measuring the predictor variables of perceived burdensomeness and thwarted belongingness on suicide attempt (Research Question 2). Again, all five items were entered into the model for the outcome variable of suicide attempt. During the data screening process, two proxy items were eliminated (i.e., non-binary, volunteer), as they did not indicate significant results. Regression results indicated that the overall model of the three remaining predictors (emotional/mental health, felt sad/hopeless, not straight) was statistically reliable in distinguishing between 11th grade students who did not attempt suicide and those who did (Nagelkerke R2 = .271; p < .001). The suicide attempt model was deemed statistically significant—X2(5) = 1182.692—with an overall positive predictive value of 93.4%. Both proxy items for the perceived burdensomeness variable proved to be statistically significant (Table 3).
Based on the overall regression analyses, increased poor emotional/mental health was related to the increased likelihood and occurrence of suicide attempt; however, students who reported feeling sad or hopeless for at least 2 weeks were nearly twice as likely to attempt suicide than students who did not report feeling sad or hopeless. Of the three proxy items for the thwarted belongingness variable, only one proved to be statistically significant (Table 3). Students who reported as not straight were nearly twice as likely as students who reported as straight to attempt suicide.
Logistic Regression Predicting Likelihood of Suicide Attempt
|| < .001
|| < .001
|| < .001
|| < .001
These results indicated that there were significant similarities between the predictors of suicide ideation and suicide attempt, supporting our hypotheses. The proxy items that comprised perceived burdensomeness (poor emotional health [odds = 1.820] and feeling sad/hopeless [odds = 6.410]) in conjunction with the proxy item that comprised thwarted belongingness (not straight [odds = 1.704]) all factored into increased likelihood of suicide ideation and suicide attempt. In other words, the mediators of suicide ideation were similar to the mediators of suicide attempt.
In discussing the results of the study, it is important to first contextualize the descriptive statistics, as we were studying and applying results to adolescent students in Oregon. The dataset reports 18% of the participants as experiencing suicide ideation, which equates to 1,927 students in the 11th grade. This statistic for suicide ideation is a little higher than the national percentage of 17.2% (CDC, 2017). The dataset also reports 6.6% of the participants as attempting suicide, which equates to 703 students in the 11th grade. This statistic for suicide attempt is a little lower than the national 7.4% (CDC, 2017). In terms of our dataset, Oregon 11th graders were slightly higher than expected for suicide ideation and slightly lower than expected for suicide attempt.
Results from our binomial logistic regression analyses uncovered a model supporting our hypothesis that perceived burdensomeness and thwarted belongingness would significantly predict suicide ideation and attempt in 11th grade students. Further, both variables representing perceived burdensomeness were statistically significant for both suicide ideation and attempt, as was one of the three proxy variables representing thwarted belongingness. These findings align with the IPTS, proposing that perceived burdensomeness and thwarted belongingness are not only important predictors of suicidal behaviors, but are significant elements for both ideation and attempt (with the addition of acquired capability for attempt; Horton et al., 2016; King et al., 2018).
Though not a predetermined hypothesis, it seems reasonable to expect that there would be fewer predictors of suicide attempt, condensed from the predictors of suicide ideation, but that is not the case in our findings. It begs the question: What variables drove students in this population from ideation to attempt? According to the data, 18% of the 11th graders experienced suicide ideation, but only 6.6% reported being driven to attempt suicide. The IPTS would suggest that the missing component was a measure of acquired capability that moves a person from ideation to attempt (Joiner et al., 2009). According to the IPTS (Joiner et al., 2009), experiencing perceived burdensomeness and thwarted belongingness without acquired capability leads to suicide ideation, but the presence of acquired capability is needed to result in suicide attempt. This will be discussed further as a limitation of this study.
These results corroborate previous literature on adolescence and suicidality. Horton et al. (2016) described adolescent perceived burdensomeness as social disconnection and adolescent thwarted belongingness as social isolation from peers. As previously described, with regard to poor emotional/mental health and feeling sad/hopeless, Jaworska and MacQueen (2015) highlighted the increased reactivity of adolescence, and Wyman (2014) indicated that half of the diagnoses of emotional and behavioral disorders take place during this age period (highlighting the importance of mental health clinicians being aware of these findings). With regard to not being straight, this time period also includes establishing values and preferences for sexual behavior and affective orientation (Teipel, 2013). These results also corroborate our previous findings on the application of the IPTS to early adolescents (ages 13–14), suggesting similar significant mediators for both suicide ideation (perceived burdensomeness: emotional/mental health, feeling sad/hopeless; thwarted belongingness: not straight, bullied) and suicide attempt (perceived burdensomeness: emotional/mental health, feeling sad/hopeless; thwarted belongingness: non-binary, bullied; Sallee et al., 2021).
Relative to the literature on suicidality and its role in our selection of proxy items within the OHT survey, research on the connection between poor emotional/mental health and emotional strain in the family setting supports our findings of its significance within the predictor variable of perceived burdensomeness (Miller et al., 2014). The significance of feeling sad/hopeless is supported by previous research discussing its inclusion in the definition of perceived burdensomeness itself (Horton et al., 2016). Sexual minority students experience higher rates of suicidal behaviors, attempting suicide at rates of 2 to 6 times that of straight adolescents (Seelman & Walker, 2018; Zhao et al., 2010). Our findings support this body of research in the significance of being not straight in relation to mental health wellness.
The other proxy predictors examined—being non-binary and volunteering—were not statistically predictive of suicidal behavior. This may be due in part to the developmental tasks and goals characteristic of the period of middle adolescence, or the proxy items themselves may not be significant indicators of the predictor variables in the study, or the wrong indicators were chosen or were conceptualized inaccurately. If that is the case, there would be concerns regarding the construct validity of these indicators and subsequent measures, and because that cannot be proven otherwise, it is a considerable limitation to the study. If the developmental tasks and goals of middle adolescence provide the most insight into the insignificance of being non-binary and volunteering, it is important to consider the developmental period of self-involvement resulting in high expectations of self in combination with low self-concept, impacting an increased drive for peer acceptance (American Academy of Child & Adolescent Psychiatry, 2021). Eleventh grade students are also preparing for their final year of high school and making plans for what their lives will look like after graduation, requiring a high degree of autonomy and independence. It is interesting to consider the insignificant predictors through this developmental lens. Although 11th grade students are seeking peer acceptance, being non-binary may not be a driver because of developing autonomy and independence.
We consider how the findings of this study might relate to research indicating a higher rate of suicide for sexual/gender minorities compared to youth from historically well-represented communities (Teipel, 2013), but perhaps disaggregating sexual/gender minority and focusing on non-binary youth in particular may impact that conversation. Volunteering could prove to be a protective factor but drive for peer acceptance and reliance on peers may determine whether or not a student in the 11th grade chooses to volunteer as opposed to self-motivation or fulfillment.
Limitations and Suggestions for Future Research
Several limitations must be considered when evaluating the findings of this study. First, because of their correlational nature, we were unable to draw any causal conclusions from the results. Relatedly, the results from this study, despite being based on a large sample, described 11th grade students in Oregon who elected to take the survey and had a complete dataset necessary for analysis; the sample was one of convenience, and the extraction of missing datasets impacted the researchers’ ability to gauge the sample’s ability to represent the whole population. As such, generalization of the results to the larger population of adolescents is limited.
Additionally, the data was taken retrospectively from a survey managed by a state government agency; it would have been preferable for us to have input on the questions included in the 2017 OHT survey. Instead, we were forced to select best-fit proxy items that might or might not have been most representative of the predictor variables. Relatedly, and as previously mentioned, there is cause to question the construct validity of these measures, particularly because the selected proxy items do not correlate to other measures of thwarted belongingness in particular. Because we relied on the 2017 OHT survey data, the models for examining the IPTS constructs were incomplete. Lastly, there is a lack of data about unique stressors experienced by students of color related to their social locations, particularly valuable because 25% of the participants were Hispanic/Latino.
Based on our results, despite the limitations previously discussed, there are a variety of avenues for further research on this topic. The first avenue would be to analyze similar data from another state survey or the national Youth Risk Behavior Survey. This would allow researchers to compare results with this study in order to offer more supported generalization to the adolescent population. Another avenue would be to revisit this dataset and theory to consider how they might apply to other behaviors of the adolescent population, such as NSSI and school violence. Further research could revisit this study by creating a survey that would more fully target the interpersonal constructs of the IPTS or create a qualitative or mixed-methods study incorporating additional data sources to examine more in-depth the suicide-related factors and experiences during adolescence.
Another avenue for future research may be to examine additional prospective mediators that may predict the evolution from ideation to attempt because our results presented the exact same predictors for both. Finally, a valuable possibility for future research would be to study factors that might differentially affect students of color and adolescents from sexual minority groups.
This particular study offers valuable support for the application of the IPTS in working with middle adolescents as well as useful implications for targeting specific interpersonal needs when working with this population. Perceived burdensomeness and thwarted belongingness may be significant construct predictors of suicide ideation and attempt in adolescents according to the findings. Implications for clinical mental health counselors and other professionals working with this population support the importance of taking a systemic and unique approach to working with adolescents and their families that prioritizes and addresses these specific interpersonal needs individually and collectively.
Specific interventions addressing adolescent interpersonal needs of perceived burdensomeness and thwarted belongingness include an array of clinical practices, such as using a suicide screener as part of intake assessments or well-child checks that include items related to these two constructs. Existing suicide intervention modalities need to incorporate and/or integrate the constructs of the IPTS, utilizing counseling goals and interventions that specifically target belongingness and personal value. Further, clinicians must have a basic understanding of the developmental tasks of this period to attend to an adolescent’s stable and productive peer relationships, adoption of personal value systems, and renegotiation of relationships with parents/caregivers, realizing that this transitional stage is also characterized by feelings of grief and loss (Teipel, 2013).
Group counseling is an effective and efficient modality through which a mental health professional can bring together a number of adolescents and facilitate sessions normalizing these developmental tasks and associated feelings. Mental health literacy and bibliotherapy can be used in combination with group counseling, as research has demonstrated their effectiveness on providing structure in the group process, educating adolescents, and fostering connections among the group (Mumbauer & Kelchner, 2017). Groups can also offer parents and caregivers a safe space to navigate family complexities around adolescent suicidality and learn ways to promote a sense of belonging and reduce feelings of burdensomeness among adolescents.
Broader systemic outreach can involve community mental health providers and other professionals collaborating with school stakeholders to offer services such as parent workshops and educator professional development opportunities on understanding suicidality and evidence-based prevention, intervention, and postvention. Partnering with school stakeholders can include consulting on systemic interventions and programming, such as individual student behavior plans, IEPs, and 504 plans, in addition to school- or grade-wide postsecondary transition activities. These consultation and collaboration efforts are often interdependent, in the sense that clinical professionals gain referrals from school stakeholders, and school stakeholders help inform the work of clinical professionals with their adolescent clients.
Through engaging parents, families, school personnel, and their adolescent clients, clinical mental health counselors can work holistically to prevent and intervene in suicidal behaviors by targeting fulfillment and development of interpersonal needs. These findings may have the potential to inform laws and policies through legislative efforts to address adolescent suicide. Clinical mental health counselors have a professional obligation to utilize outcome data to advocate for systemic change to impact clients (Montague et al., 2016), and in this context they may also draw on these findings to provide information to society to assist in advocacy efforts and extend recommendations to professionals working with this population.
The findings of our study support the application of the IPTS in understanding suicidality among middle adolescents, particularly in the ideation model, and are significant in several ways. First, the IPTS has the potential to inform therapeutic interventions in clinical settings, as well as parents and social institutions (e.g., schools and youth development centers), on how best to support youth who experience suicidality. Another focus of our study was on interpersonal factors that are dynamic, rather than static risk factors that may not necessarily be venues for intervention and change for clinicians (e.g., family factors). Third, adolescent clients engaging in suicide ideation and behaviors require interventions that are unique from their adult counterparts and often require environmental and familial interventions as well as individual. Lastly, our findings may serve to provide information to society to assist in advocacy efforts and recommendations for serving adolescent populations within all systems, including laws and policies to address adolescent suicide. Overall, the findings of our study underscore the uniqueness and complexity of this developmental period of adolescence and the importance of theory- and research-based practices. We hope that our findings will inform mental health clinicians, educators, school counselors, parents, and policymakers in their efforts to meet adolescent mental health needs.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.
American Academy of Child & Adolescent Psychiatry. (2021). Facts for families guide. https://www.aacap.org/AACAP/Families_and_Youth/Facts_for_Families/Layout/FFF_Guide-01.aspx
Barzilay, S., Apter, A., Snir, A., Carli, V., Hoven, C. W., Sarchiapone, M., Hadlaczky, G., Balazs, J., Kereszteny, A., Brunner, R., Kaess, M., Bobes, J., Saiz, P. A., Cosman, D., Haring, C., Banzer, R., McMahon, E., Keeley, H., Kahn, J.-P., . . . Wasserman, D. (2019). A longitudinal examination of the interpersonal theory of suicide and effects of school-based suicide prevention interventions in a multinational study of adolescents. Journal of Child Psychology and Psychiatry, 60(10), 1104–1111. https://doi.org/10.1111/jcpp.13119
Becker, S. P., Foster, J. A., & Luebbe, A. M. (2020). A test of the interpersonal theory of suicide in college students. Journal of Affective Disorders, 260, 73–76. https://doi.org/10.1010/j/jad.2019.09.005
Brener, N. D., Kann, L., Shanklin, S., Kinchen, S., Eaton, D. K., Hawkins, J., & Flint, K. H. (2013, March 1). Methodology of the Youth Risk Behavior Surveillance System—2013. Recommendations and Reports, 62(1), 1–23. Centers for Disease Control and Prevention. https://www.cdc.gov/mmwr/preview/mmwrhtml/rr6201a1.htm
Centers for Disease Control and Prevention. (2017). Trends in the prevalence of suicide-related behaviors. National YRBS: 1991–2017. https://www.cdc.gov/healthyyouth/data/yrbs/pdf/trends/2017_suicide_trend_yrbs.pdf
Chu, C., Rogers, M. L., & Joiner, T. E. (2016). Cross-sectional and temporal association between non-suicidal self-injury and suicidal ideation in young adults: The explanatory roles of thwarted belongingness and perceived burdensomeness. Psychiatry Research, 246, 573–580. https://doi.org/10.1016/j.psychres.2016.07.061
Czyz, E. K., Berona, J., & King, C. A. (2015). A prospective examination of the interpersonal-psychological theory of suicidal behavior among psychiatric adolescent inpatients. Suicide and Life-Threatening Behavior, 45(2), 243–260. https://doi.org/10.1111/sltb.12125
Durkheim, É. (1951). Suicide: A study in sociology. Free Press.
Horton, S. E., Hughes, J. L., King, J. D., Kennard, B. D., Westers, N. J., Mayes, T. L., & Stewart, S. M. (2016). Preliminary examination of the interpersonal psychological theory of suicide in an adolescent clinical sample, Journal of Abnormal Child Psychology, 44, 1133–1144. https://doi.org/10.1007/s10802-015-0109-5
Jaworska, N., & MacQueen, G. (2015). Adolescence as a unique developmental period. Journal of Psychiatry & Neuroscience, 40(5), 291–293. https://doi.org/10.1503/jpn.150268
Joiner, T. E., Ribeiro, J. D., & Silva, C. (2012). Nonsuicidal self-injury, suicidal behavior, and their co-occurrence as viewed through the lens of the interpersonal theory of suicide. Current Directions in Psychological Science, 21(5), 342–347. https://doi.org/10.1177/0963721412454873
Joiner, T. E., Van Orden, K. A., Witte, T. K., & Rudd, M. D. (2009). The interpersonal theory of suicide: Guidance for working with suicidal clients. American Psychological Association.
King, J. D., Horton, S. E., Hughes, J. L, Eaddy, M., Kennard, B. D., Emslie, G. J., & Stewart, S. M. (2018, June). The interpersonal–psychological theory of suicide in adolescents: A preliminary report of changes following treatment. Suicide and Life-Threatening Behavior, 48(3), 294–304. https://doi.org/10.1111/sltb.12352
Lester, D. (1987). Murders and suicide: Are they polar opposites? Behavioral Sciences & the Law, 5(1), 49–60.
Miller, A. B., Adams, L. M., Esposito-Smythers, C., Thompson, R., & Proctor, L. J. (2014). Parents and friendships: A longitudinal examination of interpersonal mediators of the relationship between child maltreatment and suicidal ideation. Psychiatry Research, 220(3), 998–1006. https://doi.org/10.1016/j.psychres.2014.10.009
Montague, K. T., Cassidy, R. R., & Liles, R. G. (2016). Counselor training in suicide assessment, prevention, and management. In G. R. Walz & J. C. Bleuer (Eds). Ideas and research you can use: VISTAS 2016. https://bit.ly/Vistas2016
Mumbauer, J., & Kelchner, V. (2017). Promoting mental health literacy through bibliotherapy in school-based settings. Professional School Counseling, 21(1), 85–94. https://doi.org/10.5330/1096-2409-21.1.85
Oregon Health Authority. (2017). Oregon Healthy Teens Survey. https://bit.ly/OHTsurvey2017
Oregon Suicide Prevention. (n.d.). Youth. https://www.oregonsuicideprevention.org/community/youth
Sallee, E., Ng, K.-M., & Cazares-Cervantes, A. (2021). Interpersonal predictors of suicide ideation and attempt among early adolescents. Professional School Counseling, 25(1), 1–11. https://doi.org/10.1177/2156759X211018653
Schneidman, D. (1993). 1993 health care reforms at the state level: An update. Bulletin of the American College of Surgeons, 78(12), 17–22. https://pubmed.ncbi.nlm.nih.gov/10130176
Seelman, K. L, & Walker, M. B. (2018). Do anti-bullying laws reduce in-school victimization, fear-based absenteeism, and suicidality for lesbian, gay, bisexual, and questioning youth. Journal of Youth and Adolescence, 47, 2301–2319. https://doi.org/10.1007/s10964-018-0904-8
Stewart, S. M., Eaddy, M., Horton, S. E., Hughes, J., & Kennard, B. (2017). The validity of the interpersonal theory of suicide in adolescence: A review. Journal of Clinical Child and Adolescent Psychology, 46(3), 437–449. https://doi.org/10.1080/15374416.2015.1020542
Stone, D., Holland, K., Bartholow, B., Crosby, A., Davis, S., & Wilkins, N. (2017). Preventing suicide: A technical package of policy, programs, and practices. National Center for Injury Prevention and Control, Centers for Disease Control and Prevention. https://www.cdc.gov/violenceprevention/pdf/suicidetechnicalpackage.pdf
Teipel, K. (2013, June). Understanding adolescence: Seeing through a developmental lens. State Adolescent Health Resource Center. http://www.amchp.org/programsandtopics/AdolescentHealth/projects/Documents
Wasserman, D., Hoven, C. W., Wasserman, C., Wall, M., Eisenberg, R., Hadlaczky, G., Kelleher, I., Sarchiapone, M., Apter, A., Balazs, J., Bobes, J., Brunner, R., Corcoran, P., Cosman, D., Guillemin, F., Haring, C., Iosue, M., Kaess, M., Kahn, J.-P., . . . Carli, V. (2015). School-based suicide prevention programmes: The SEYLE cluster-randomized, controlled trial. The Lancet, 385(9977), 1536–1544. https://doi.org/10.1016/S0140-6736(14)61213-7
Wyman, P. A. (2014). Developmental approach to prevent adolescent suicides: Research pathways to effective upstream preventative interventions. American Journal of Preventative Medicine, 47(3S2), S251–S256. https://doi.org/10.1016/ampere.2014.05.039
Zhao, Y., Montoro, R., Igartua, K., & Thombs, B. D. (2010). Suicidal ideation and attempt among adolescents reporting “unsure” sexual identity or heterosexual identity plus same-sex attraction or behavior: Forgotten groups? Journal of the American Academy of Child & Adolescent Psychiatry, 49(2), 104–113.
Emily Sallee, PhD, BC-TMH, LSC, PCLC, is an assistant professor at the University of Montana. Abraham Cazares-Cervantes, PhD, LSC, is an assistant clinical professor at Oregon State University. Kok-Mun Ng, PhD, NCC, ACS, LPC, is a professor at Oregon State University. Correspondence may be addressed to Emily Sallee, 32 Campus Drive #335, Missoula, MT 59834, firstname.lastname@example.org.
Melissa Sitton, Tina Du Rocher Schudlich, Christina Byrne, Chase M. Ochrach, Seneca E. A. Erwin
A family systems framework guided our investigation of self-injurious behavior (SIB) in adolescents. As part of a larger study, we collected data examining SIB and family functioning from 29 adolescents (Mage = 15.66) and their caregivers. These adolescents with traits of borderline personality disorder were seeking counseling from community-based practitioners specializing in dialectical behavior therapy. Our primary aim was to better understand the family environment of these adolescents. A second aim was to elucidate interrelations among family communication, roles, problem-solving, affective involvement, affective responsiveness, behavioral control, and conflict and SIB. We found a high rate of SIB among adolescent participants. There was significant congruence between adolescent and caregiver reports of the family environment, with families demonstrating unhealthy levels of functioning in several indicators of family environment. The latent variable of family functioning significantly predicted nonsuicidal and ambivalent SIB. Counselors working with adolescents should consider family functioning when assessing risk for SIB.
Keywords: self-injurious behavior, adolescents, family systems, borderline personality disorder, family functioning
Although emotion dysregulation and unstable personal relationships are common for adolescents, those with symptoms of borderline personality disorder (BPD) often report more extreme experiences (A. L. Miller et al., 2008). BPD is characterized by impaired or unstable emotional and social functioning (American Psychiatric Association, 2013). Individuals with BPD—especially adolescents—may experience impairments in daily functioning as well as within interpersonal relationships (Chanen et al., 2007).
Linehan’s (1993) biosocial theory proposed that BPD can result from an individual’s biological predisposition toward emotion dysregulation and a social environment that amplifies this vulnerability. Given that adolescents spend a substantial amount of time with their family, it is important to examine an adolescent’s familial environment to understand the etiology of BPD symptoms; such examination requires a framework like family systems theory, which emphasizes the relationships between family members rather than focusing on the individual members themselves (Goldenberg & Goldenberg, 2013); this includes family communication, roles, problem-solving, affective involvement, affective responsiveness, and behavioral control (I. W. Miller et al., 2000).
Self-Injurious Behavior (SIB)
Regrettably, it is common for adolescents with BPD to engage in SIB (Kaess et al., 2014). SIB is an umbrella term for all purposeful, self-inflicted acts of bodily harm, whether the intent is suicidal, nonsuicidal (i.e., nonsuicidal self-injury), or ambivalent (i.e., neither strictly suicidal nor nonsuicidal). In fact, SIB is one diagnostic criteria for BPD in adolescents and adults.
Although originally developed to explain the etiology of BPD, the biosocial theory has been applied to the development of SIB as well (Crowell et al., 2009). Countless studies have examined the role of emotion dysregulation and affective reinforcement in SIB, but it is important to also consider the influence of social variables. Indeed, in their four-function model, Nock and Prinstein (2004, 2005) suggested that both affective and social variables can positively and negatively reinforce nonsuicidal SIB. Similarly, Joiner’s (2005) interpersonal theory of suicidal SIB posited that social variables (particularly thwarted belongingness and perceived burdensomeness) drive the desire for suicide. Thus, although there are clear links between affective variables and SIB, social variables are also relevant. For adolescents, an important social variable related to SIB is family environment. From the family systems approach, adolescent SIB is best understood when rooted in the context of family environment. As Levenkron (1998) suggested, “the ways in which all the family members relate to each other… [is] the fuel that drives [SIB]” (pp. 125–126).
Although limited in number, some previous studies have examined family environment and SIB in adolescents. For example, Halstead et al. (2014) found that SIB was related to dysfunctional family environments. Studies have also found relationships between adolescent SIB and familial communication (Halstead et al., 2014; Latina et al., 2015) and conflict (Huang et al., 2017). Additionally, Adrian et al. (2011) demonstrated a link between stress and failure to meet expectations of familial roles. To our knowledge, no studies to date have examined SIB and familial problem-solving, affective involvement, affective responsiveness, and behavioral control. However, studies have linked SIB to an individual’s lack of problem-solving skills (Walker et al., 2017), ability to regulate affective responses (Adrian et al., 2011), and behavioral control related to impulsivity and compulsivity (Hamza et al., 2015).
Despite the clear influence of family members on SIB (Halstead et al., 2014) and the significant amount of time adolescents tend to spend with family members, more research is needed to evaluate family environment in relation to SIB. Specifically, we investigated the families of treatment-seeking adolescents with traits of BPD who engage in SIB. Our objectives were to: (a) assess family environment using multiple indicators of family functioning, (b) assess SIB in these treatment-seeking adolescents, including SIB done with suicidal intent, nonsuicidal intent, and ambivalence toward life, and (c) evaluate family functioning as a statistical predictor of lifetime SIB.
Participants and Procedure
We used data from a larger ongoing, unpublished study on dialectical behavior therapy. In the larger study, participants were adolescents and young adults who sought counseling from community-based clinicians specializing in dialectical behavior therapy. Participants sought counseling for symptoms of BPD, particularly SIB. The counselors recruited participants for the research study by explaining voluntary research participation during their standard intake process for new clients at the clinic. The counselors also obtained informed consent for research from the participants. The counselors collaborated with researchers at a local university for this larger study, and the university’s IRB approved the study.
For the current study, we used the existing pretest data from the adolescents only (N = 29; Mage = 15.66, SDage = 1.34, age range = 13–18). A majority of the adolescent sample (82.8%; n = 24) reported no previous experience with counseling. This sample was predominately Caucasian (82.8%; n = 24) and most adolescents identified as female (89.7%; n = 26).
Caregiver participants (N = 29) were involved in the adolescents’ treatment and the accompanying research study. Most caregiver participants were the biological mother (81.5%; n = 22) or adoptive mother (7.4%; n = 2). However, a few adolescents were accompanied by an extended family member (7.4%; n = 2) or their biological father (3.7%; n = 1). A majority of adolescents reported that at least one of their caregivers had attended some (22.2%; n = 6) or all (29.6%; n = 8) of college, or some (3.7%; n = 1) or all (29.6%; n = 8) of graduate school.
Most adolescents reported they currently lived with both biological parents (58.6%; n = 17) or at least one biological parent (31.0%; n = 9), though some lived with non-biological parents or caregivers (10.3%; n = 3). Most adolescents (86.2%; n = 25) also reported having at least one sibling; 58.6% of adolescents (n = 17) reported having at least one biological brother, 37.9% had at least one biological sister (n = 11), and 24.1% had a half- or step-sibling (n = 7). One-way analysis of variance (ANOVA) tests demonstrated that adolescents did not differ in total SIB based on family characteristics (e.g., number of siblings, number of employed caregivers; all values of p > .05).
The Family Assessment Device (FAD; Epstein et al., 1983) is a 53-item measure with a 4-point Likert scale used to rate agreement with statements about how the adolescents’ family members interact and relate to each other (e.g., “After our family tries to solve a problem, we usually discuss whether it worked or not”). Both adolescents and caregivers completed the FAD. Subscales of the FAD assess six dimensions of family functioning, including family problem-solving, roles, communication, affective responsiveness, affective involvement, and behavioral control. The scores for each subscale are averaged, with higher scores indicating worse functioning and more problems within families. The FAD has good test-retest reliability and construct validity (I. W. Miller et al., 1985). In this study, the reliability of the FAD was excellent for both samples (Cronbach’s alpha = .95 for adolescents and .96 for caregivers).
The Conflict Behavior Questionnaire (CBQ; Prinz et al., 1979) assesses self-reported familial interactions within the past two weeks. The CBQ has both an adolescent and a caregiver version; both versions consist of 20 true/false items. Scores can range from 0 to 20, with higher scores indicating more conflict between caregiver and adolescent. Studies have shown that CBQ scores delineated between distressed and non-distressed families (Robin & Foster, 1989). The CBQ has good internal consistency and test-retest reliability (Rallis et al., 2015; Robin & Foster, 1989), as well as construct validity (Prinz et al., 1979). In the current study, the reliability of the CBQ was excellent for both samples (Cronbach’s alpha = .88 for adolescents and .92 for caregivers).
Self-Injurious Behavior (SIB)
We used the Lifetime Suicide Attempt Self-Injury Interview (LSASI; Linehan & Comtois, 1996) to assess participants’ history of SIB, including frequency, method, and intent. Using 20 items, the LSASI asks participants to report the dates of the most recent and most severe SIB, as well as their lifetime frequency of 11 different methods of SIB with suicidal intent, without suicidal intent, and with ambivalence. Participants also report the total frequency of each SIB method (combining suicidal, nonsuicidal, and ambivalent), and the number of times medical treatment was received for the SIB method. Higher scores indicate more SIB in the past. In the current study, reliability across all SIB intent types (four variables: suicidal SIB, nonsuicidal SIB, ambivalent SIB, and total SIB) was .65. Because the LSASI was designed for clinical use rather than research, to our knowledge there are no existing studies demonstrating the reliability or validity of the LSASI. Notably, this measure was already in use at the counseling clinic, and the decision to use it for this research study was counselor-driven.
As part of our preliminary analyses, we first tested all variables for the assumptions of analysis. Specifically, when examining the skew and kurtosis of the composite variables, we used ± 2 as our acceptable range of values. Following advice from Tabachnick and Fidell (2019), we transformed variables that did not meet our criteria for normality.
To better understand family functioning, we conducted descriptive analyses for all seven predictive variables (problem-solving, communication, roles, affective responsiveness, affective involvement, behavioral control, and conflict) separately for adolescent and caregiver scores. We assessed the degree of healthy family functioning using I. W. Miller et al.’s (1985) suggested cut-off scores, which can be used to distinguish between healthy and unhealthy family environments. We also conducted paired sample t-tests to compare the adolescent and caregiver reports of family functioning.
Next, we tested the fit of our theoretical model of family functioning using structural equation modeling (SEM) with maximum likelihood as the method of estimation. We used multiple fit indices to assess the model fit. Specifically, the chi-square statistic assesses absolute model fit, demonstrating good fit when not statistically significant. The chi-square test can also be used to compare the relative fit of two models. Additionally, comparative fit index (CFI), root mean square error of approximation (RMSEA), and standardized root-mean-square residual (SRMR) are all indicators of model fit, with 0.95 or higher, 0.05 or lower, and 0.08 or lower indicating good fit, respectively (for more information on SEM fit indices, see Hooper et al., 2008). Notably, Iacobucci (2010) suggested that researchers can use SEM and establish good model fit even with small samples.
We also conducted descriptive analyses of the participants’ self-reported SIB. We left these variables raw (untransformed) to evaluate how participants viewed their own SIB. We examined the specific SIB methods that participants reported using (e.g., cutting, burning) as well as three outcome variables (suicidal SIB, nonsuicidal SIB, and ambivalent SIB; all transformed because of issues with skew and kurtosis).
Lastly, we used SEM to predict SIB with the proposed model of family functioning. Given our small sample size, we conducted this analysis separately for suicidal SIB, nonsuicidal SIB, and ambivalent SIB. We set alpha at .05 for each model; given the small sample size, we did not apply corrections to the alpha for the multiple analyses.
We used SPSS 24.0 and Amos 24 to analyze our data. Because this study was primarily descriptive, we conducted multiple analyses to better understand the family environment of treatment-seeking adolescents, experiences of SIB for adolescents, and the role of family environment in adolescent engagement in SIB.
Family Characteristics and Functioning
Means, standard deviations, and range of scores for the family functioning variables are shown in Table 1. With the exception of the caregiver reports on affective responsiveness and behavioral control, both adolescent and caregiver reports on every subscale of the FAD fell above the McMaster clinical cut-off (see Table 1) described by I. W. Miller et al.’s (1985) cut-off scores, indicating on average all of the families demonstrated unhealthy functioning. It is worth noting that adolescents and their caregivers reported similar levels in five of the seven indicators of family functioning from the FAD and CBQ (e.g., there was no statistical difference between the two reports, all values of p > .05). As shown in Table 1, adolescent and caregiver reports only statistically differed for behavioral control (t = 4.23, p < .001) and communication (t = 2.96, p = .006). Specifically, adolescents reported higher levels of both behavioral control and communication; these high levels are considered indicative of unhealthy or distressed families (I. W. Miller et al., 1985).
Descriptive Statistics and Group Comparisons of Family Functioning Variables as Reported by Adolescents and Caregivers
Note. Cut-Off = McMaster Cut-Off score; Affective Resp. = Affective responsiveness; Affective Inv. = Affective involvement; Behav. Control = Behavioral control.
We used SEM to test the fit of our theory-driven, congeneric model of family functioning using seven subscales from each source (14 variables; seven for adolescents and seven for caregivers, with the error terms of each subscale correlated between the two sources) to predict family functioning as reported by each source (two latent variables; one for adolescents and one for caregivers). The absolute fit of the model was marginal: χ2(69) = 104.39, p = .004, CFI = 0.79, RMSEA = 0.14, SRMR = 0.14.
In order to reduce variables in our theoretical model, we averaged adolescent and caregiver reports for problem-solving, roles, affective responsiveness, affective involvement, and conflict because these did not statistically differ (all values of p > .05). However, we kept the two reports as separate predictors for communication and behavioral control. This left us with nine predictor variables for subsequent analysis (five averaged predictors and four single-source predictors).
Next, we used SEM to test the fit of the simplified model with the nine observed variables and one latent variable of family functioning. We found that the absolute model fit of this simplified model was acceptable overall. Specifically, the fit indices mostly indicated good fit (χ2 = 33.11, p = .194, CFI = 0.93, SRMR = 0.08), though one fit index suggested poor fit (RMSEA = 0.09). Differences in the chi-squares of our two models showed the simplified model was statistically better than the initial model: χ2(42) = 71.28, p = .003. Thus, we selected the simplified model as the final model of family functioning (see Figure 1). See Table 2 for descriptive analyses of the nine predictors in the final model. All variables were positively related to family functioning. The strongest predictors of family functioning in this model were affective responsiveness (average of adolescent and caregiver report; β = .85, B = 1.04, SE B = 0.21, p < .001, R2 = .72), affective involvement (averaged; β = .72, B = 0.88, SE B = 0.22, p < .001, R2 = .51), and problem-solving (averaged; β = .82, R2 = .67; this was the constrained parameter used to identify the regression model).
The Output Structural Regression Model of Family Functioning Developed Using SEM
Note. The large circle represents a latent variable, boxes are measured variables, small circles (with “e”) are error terms, and solid lines show regression paths. The numbers on paths are the standardized path coefficients, and the offset values on endogenous variables are the R² effect sizes. (AD) = adolescent report; (C) = caregiver report; (avg.) = averaged score of adolescent and caregiver report.
Descriptive Analyses of Predictors of Family Functioning
|Behavioral Control (AD)
|Behavioral Control (C)
Note. (AD) = adolescent report; (C) = caregiver report.
Adolescent Engagement in SIB
All adolescents reported engaging in SIB in their lifetime, and the average lifetime frequency of SIB was 438.72 (SD = 1,216.65, range = 1–6,079; transformed to address normality: M = 4.41, SD = 1.80). Specifically, most participants reported engaging in nonsuicidal SIB (n = 26) and using it with higher frequency than SIB with other intent (i.e., suicidal or ambivalent SIB), with a lifetime average of 340.16 (SD = 975.22, range = 0–4,565; transformed: M = 3.49, SD = 2.25). Many adolescents also reported engaging in ambivalent SIB (n = 18), with moderate average frequency rates (M = 22.28, SD = 52.02, range = 0–248; transformed: M = 1.62, SD = 1.69). Lastly, fewer adolescents reported engaging in suicidal SIB (n = 18), with the lowest average lifetime frequency (M = 7.34, SD = 25.03, range = 0–136; transformed: M = 0.97, SD = 0.95). See Table 3 for descriptive information on SIB methods (e.g., cutting) used by adolescents in our sample. On average, participants used 3.78 (SD = 2.15) methods of SIB in their lifetime.
Descriptive Statistics for All Self-Injurious Behavior Completed in One’s Lifetime (N = 29)
||n of Severe Cases
Note. The descriptive statistics are based on the total self-injurious behavior, combining acts completed with suicidal intent, nonsuicidal intent, and ambivalence. Other = adolescent-reported participating in a type of self-injury that was not listed; Jumping = jumping from a high place to cause injury; Severe Cases = requiring medical treatment.
a The frequency that adolescents reported engaging in the various methods of self-injury.
Predicting SIB With Family Functioning
To understand the relationships between family functioning and SIB, we conducted correlational analyses of the three outcome variables and nine predictors. As shown in Table 4, problem-solving was moderately associated with ambivalent SIB (r = .44 , p = .018), conflict was moderately associated with nonsuicidal SIB (r = .38 , p = .049), and adolescent-reported communication was moderately to strongly associated with all three SIB variables (suicidal r = .61, p < .001; nonsuicidal r = .47, p = .011; ambivalent r = .56, p = .002). All associations were positive (see Table 4), meaning that worse family functioning scores were associated with more SIB.
Bivariate Correlations Between Predictor Variables
|1. Nonsuicidal SIB
|2. Ambivalent SIB
|3. Suicidal SIB
|6. Affect. Resp.
|7. Affect. Involv.
|9. Comm. (AD)
|10. Comm. (C)
|11. Beh. Cont. (AD)
|12. Beh. Cont. (C)
Note. SIB = self-injurious behavior; Affect. Resp. = Affective Responsiveness; Affect. Involv. = Affective Involvement; Comm. = Communication; (AD) = adolescent report; (C) = caregiver report; Beh. Cont. = Behavioral Control.
* p < .05. ** p < .01. *** p < .001.
Next, we used SEM to predict SIB with our simplified model of family functioning. We tested three SIB outcomes separately because of concerns with sample size. For all models predicting SIB, we freed all FAD factors (problem-solving, roles, affective responsiveness, affective involvement, adolescent-reported communication and behavioral control, and caregiver-reported communication and behavioral control) to correlate because variables from the same measure are likely to be related.
The model predicting nonsuicidal SIB had good absolute fit: χ2(7) = 4.28, p = .747, CFI = 1.00, RMSEA = 0.00, SRMR = 0.04. In all, family functioning explains 20% of the variance in nonsuicidal SIB. See Figure 2 for the standardized path coefficients between family functioning variables, the latent variable of family functioning, and nonsuicidal SIB. Notably, family functioning predicted nonsuicidal SIB:
β = .44, B = 1.27, SE B = 0.62, p = .039. Based on effect sizes (see Figure 2), the strongest predictors were problem-solving (averaged; β = .79, B = 0.90, SE B = 0.03, p = .008, R² = .62), communication (adolescent-reported; β = .55, B = 0.05, SE B = 0.03, p = .034, R² = .31), and conflict (averaged; β = .84, R² = .71; this was the constrained parameter used to identify the regression model).
The model predicting ambivalent SIB had good absolute fit: χ²(7) = 5.69, p = .577, CFI = 1.00, RMSEA = 0.00, SRMR = 0.04. In all, family functioning explains 33% of the variance in ambivalent SIB. See Figure 3 for the standardized path coefficients between family functioning variables, the latent variable of family functioning, and ambivalent SIB. Notably, family functioning predicted ambivalent SIB: β = .58, B = 1.04, SE B = 0.46, p = .025. Based on effect sizes (see Figure 3), the strongest predictors were problem-solving (averaged; β = .94, B = 0.15, SE B = 0.07, p = .022, R² = .89), communication (adolescent-reported; β = .83, B = 0.11, SE B = 0.05, p = .030, R² = .69), and affective responsiveness (averaged; β = .69, B = 0.13, SE B = 0.07, p = .049, R² = .47).
The Output Structural Regression Model of Nonsuicidal SIB Developed Using SEM
Note. The numbers on paths are the standardized path coefficients, and the offset values on endogenous variables are the R2 effect sizes. (AD) = adolescent report; (C) = caregiver report; (avg.) = averaged score of adolescent and caregiver report.
The Output Structural Regression Model of Ambivalent SIB Developed Using SEM
Note. The numbers on paths are the standardized path coefficients, and the offset values on endogenous variables are the R² effect sizes. (AD) = adolescent report; (C) = caregiver report; (avg.) = averaged score of adolescent and caregiver report.
Lastly, the model using family functioning to predict suicidal SIB was not able to successfully converge because of reaching the iteration limit, possibly because of the small sample size. After examining the suggested modification indices, the model was still not able to converge. Thus, we concluded that the suicidal SIB model was a poor model, meaning that family functioning alone was not predictive of suicidal SIB in our sample.
The goals of the current study were to examine the family environment of adolescents seeking treatment for symptoms of BPD, as well as their experiences of SIB, and to better understand what aspects of family functioning relate to SIB. Unique strengths of this study include the emphasis on assessing models of family functioning as it relates to SIB and exploring differences between SIB intent types (suicidal SIB, nonsuicidal SIB, and SIB with ambivalence toward life). Further, because participants were clients seeking counseling from community-based master’s-level clinicians and no clients were excluded from participating in this study, results may generalize to other community samples.
We found that adolescents and caregivers often reported family functioning scores that met criteria for distressed families. Interestingly, adolescents and caregivers agreed on a majority of the subscales of family functioning, suggesting that the distress is mutually experienced. Adolescents and their caregivers only differed on reports of behavioral control (e.g., “[my family does not] hold any rules or standards”) and communication (e.g., “when someone [in my family] is upset the others know why”). This self-reported familial distress supports the social component of the biosocial theory (Linehan, 1993) in that the adolescents with traits of BPD engaged in SIB and experienced unhealthy family environments. Additionally, we found high lifetime rates of SIB in our sample of adolescents. As in previous studies (e.g., Anestis et al., 2015), adolescents in the current study engaged in nonsuicidal SIB more frequently than suicidal or ambivalent SIB, and cutting was the most common method.
Notably, our model of family functioning successfully predicted higher levels of both nonsuicidal SIB and ambivalent SIB. In particular, problem-solving, conflict, and adolescent-reported communication had consistently large effect sizes, suggesting that these subscales contributed more to SIB than other subscales. Although no previous studies have examined adolescent SIB and familial problem-solving to our knowledge, the findings that SIB was related to familial conflict (Huang et al., 2017) and communication (Halstead et al., 2014) corroborate the results of previous studies.
The success of the family functioning model in predicting SIB aligns with family systems theory. Specifically, adolescents in our sample may engage in SIB as a coping skill because their family lacks healthy problem-solving skills and thus models poor coping (which aligns with a description by Halstead et al., 2014). Additionally, adolescent SIB may function to temporarily end conflict in the family because it diverts the family’s attention away from the immediate problems. For example, Oldershaw et al. (2008) found that parents avoided conflict and felt like they were “walking on eggshells” (p. 142) after learning of their adolescents’ SIB. Another possible explanation is that the adolescents in our sample may serve as scapegoats within their family, acting as a focal point of a disturbed family system. From a structural family systems perspective, when there are problems within family subsystem relationships, oftentimes the child—typically the most vulnerable one—becomes the focus of the family’s problems (Wetchler, 2003); this trend is consistent with our findings.
It is worth noting that family functioning alone did not sufficiently predict suicidal SIB. One possible explanation is that our family functioning variables did not encompass the factors of thwarted belongingness and perceived burdensomeness, both of which Joiner (2005) suggested may lead to suicide.
Limitations and Future Directions
A strength of this study is that the results may generalize to other real-world settings in which adolescent clients seek counseling services from community-based master’s-level clinicians who specialize in dialectical behavior therapy. However, this ecological validity comes with some relative limitations.
One notable limitation of this study is that we examined family functioning at one point in time, when the adolescent was beginning treatment. Given this single timepoint, we are unable to fully describe the relationship between family functioning and SIB. Considering the biosocial theory, it seems likely that the distressed family environment preceded the SIB; however, it is possible that the SIB caused greater familial distress. Therefore, it would be useful to assess changes in family functioning and SIB across time.
Another limitation is our SIB measure; as Crowell et al. (2013) explained, the LSASI is commonly used in clinical practice but not often in research. In addition to issues with reliability, the LSASI is a lifetime measure as opposed to one focusing on recent behavior. Although all participants reported engaging in SIB in the past year, it is unclear how recently they engaged in SIB relative to the time of the study. Despite the benefit of creating more variability in the data by allowing participants to report their specific frequency of SIB, the alternative of a dichotomous variable of current SIB might be more compatible with our measures of current family functioning.
Additionally, the small sample size limits the power of our analyses as well as the generalizability of our results. A small sample increases the likelihood of a Type II error, meaning an increased likelihood of not finding significant results. However, it is notable that we found statistically significant results (e.g., good model fit of family functioning) despite our low power. Nevertheless, replication studies with much larger samples are needed.
Implications for Practice
Our findings suggest that family functioning is related to SIB in adolescents, particularly nonsuicidal and ambivalent SIB. Although counselors often include families when working with young children, it is common for counselors to work with adolescents individually. This practice is consistent with state laws allowing adolescents to consent to their own mental health treatment, and there are many presenting concerns and situations in which individual counseling may be the most effective modality. However, the connection between family functioning and SIB in adolescents in our sample indicates that it may be important to include family members in treating adolescent SIB; in fact, dialectical behavior therapy for adolescents (originally adapted by A. L. Miller et al., 1997) encourages family involvement in treatment. Counselors therefore need to educate parents and caregivers who may be reluctant to engage in the counseling process with their teen that SIB is an issue for which their participation in counseling could make a positive difference in treatment outcome. Further, from a family systems perspective, it can be challenging for teens to successfully use the coping skills and strategies they learn in counseling if the rest of the family system remains unchanged. Including at least some family members may therefore help adolescents maintain changes gained through the counseling process.
When including family members in counseling with adolescents who have engaged in nonsuicidal and ambivalent SIB, findings from our study suggest that three important targets for assessment and intervention include the domains of familial problem-solving, familial conflict, and adolescent-reported communication. Two of these, conflict and communication, were previously identified in the literature, and our study supports those findings. Our study newly identified familial problem-solving as an additional important predictor of SIB in adolescents. Counselors must keep in mind, however, that these variables were not sufficient in predicting suicidal SIB in adolescents. For these teens, we encourage the use of a broader assessment that includes elements of Joiner et al.’s (2009) interpersonal theory of suicide, especially the crucial interpersonal constructs of thwarted belongingness and perceived burdensomeness.
Based on our findings, it appears there is a relationship between engagement in SIB (especially nonsuicidal and ambivalent SIB) and familial environment for community-based treatment-seeking adolescents with traits of BPD. Additionally, both adolescents and their caregivers in our sample reported distressed levels of multiple indicators of family functioning, suggesting the need for family-based intervention. Counselors and service providers should consider multiple markers of family environment (particularly problem-solving, conflict, and adolescent-reported communication) when assessing risk for and treatment of adolescent SIB.
Conflict of Interest and Funding Disclosure
This study was partially funded by a grant from
Western Washington University awarded to
Dr. Christina Byrne. The authors reported no
conflict of interest for the development of this manuscript.
Adrian, M., Zeman, J., Erdley, C., Lisa, L., & Sim, L. (2011). Emotional dysregulation and interpersonal
difficulties as risk factors for nonsuicidal self-injury in adolescent girls. Journal of Abnormal Child
Psychology, 39(3), 389–400. https://doi.org/10.1007/s10802-010-9465-3
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.).
Anestis, M. D., Khazem, L. R., & Law, K. C. (2015). How many times and how many ways: The impact of number of nonsuicidal self-injury methods on the relationship between nonsuicidal self-injury frequency and suicidal behavior. Suicide and Life-Threatening Behavior, 45(2), 164–177. https://doi.org/10.1111/sltb.12120
Chanen, A. M., Jovev, M., & Jackson, H. J. (2007). Adaptive functioning and psychiatric symptoms in adolescents with borderline personality disorder. The Journal of Clinical Psychiatry, 68(2), 297–306.
Crowell, S. E., Baucom, B. R., McCauley, E., Potapova, N. V., Fitelson, M., Barth, H., Smith, C. J., & Beauchaine, T. P. (2013). Mechanisms of contextual risk for adolescent self-injury: Invalidation and conflict escalation in mother–child interactions. Journal of Clinical Child & Adolescent Psychology, 42(4), 467–480. https://doi.org/10.1080/15374416.2013.785360
Crowell, S. E., Beauchaine, T. P., & Linehan, M. M. (2009). A biosocial developmental model of borderline personality: Elaborating and extending Linehan’s theory. Psychological Bulletin, 135(3), 495–510. https://doi.org/10.1037/a0015616
Epstein, N. B., Baldwin, L. M., & Bishop, D. S. (1983). The McMaster Family Assessment Device. Journal of Marital and Family Therapy, 9(2), 171–180. https://doi.org/10.1111/j.1752-0606.1983.tb01497.x
Goldenberg, H., & Goldenberg, I. (2013). Family therapy: An overview (8th ed.). Brooks/Cole.
Halstead, R. O., Pavkov, T. W., Hecker, L. L., & Seliner, M. M. (2014). Family dynamics and self-injury behaviors: A correlation analysis. Journal of Marital and Family Therapy, 40(2), 246–259.
Hamza, C. A., Willoughby, T., & Heffer, T. (2015). Impulsivity and nonsuicidal self-injury: A review and meta-analysis. Clinical Psychology Review, 38, 13–24. https://doi.org/10.1016/j.cpr.2015.02.010
Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods, 6(1), 53–60. https://doi.org/10.21427/D7CF7R
Huang, Y.-H., Liu, H.-C., Sun, F.-J., Tsai, F.-J., Huang, K.-Y., Chen, T.-C., Huang, Y.-P., & Liu, S.-I. (2017). Relationship between predictors of incident deliberate self-harm and suicide attempts among adolescents. Journal of Adolescent Health, 60(5), 612–618. https://doi.org/10.1016/j.jadohealth.2016.12.005
Iacobucci, D. (2010). Structural equations modeling: Fit indices, sample size, and advanced topics. Journal of Consumer Psychology, 20(1), 90–98. https://doi.org/10.1016/j.jcps.2009.09.003
Joiner, T. E. (2005). Why people die by suicide. Harvard University Press.
Joiner, T. E., Jr., Van Orden, K. A., Witte, T. K., & Rudd, M. D. (2009). The interpersonal theory of suicide: Guidance for working with suicidal clients. American Psychological Association. https://doi.org/10.1037/11869-000
Kaess, M., Brunner, R., & Chanen, A. (2014). Borderline personality disorder in adolescence. Pediatrics, 134(4), 782–793. https://doi.org/10.1542/peds.2013-3677
Latina, D., Giannotta, F., & Rabaglietti, E. (2015). Do friends’ co-rumination and communication with parents prevent depressed adolescents from self-harm? Journal of Applied Developmental Psychology, 41, 120–128. https://doi.org/10.1016/j.appdev.2015.10.001
Levenkron, S. (1998). Cutting: Understanding and overcoming self-mutilation. W. W. Norton.
Linehan, M. M. (1993). Cognitive-behavioral treatment of borderline personality disorder. Guilford.
Linehan, M. M., & Comtois, K. A. (1996). Lifetime parasuicide count. Unpublished manuscript, Department of Psychology, University of Washington, Seattle, Washington.
Miller, A. L., Muehlenkamp, J. J., & Jacobson, C. M. (2008). Fact or fiction: Diagnosing borderline personality disorder in adolescents. Clinical Psychology Review, 28(6), 969–981. https://doi.org/10.1016/j.cpr.2008.02.004
Miller, A. L., Rathus, J. H., Linehan, M. M., Wetzler, S., & Leigh, E. (1997). Dialectical behavior therapy adapted for suicidal adolescents. Journal of Practical Psychiatry and Behavioral Health, 3(2), 78–86.
Miller, I. W., Epstein, N. B., Bishop, D. S., & Keitner, G. I. (1985). The McMaster Family Assessment Device: Reliability and validity. Journal of Marital and Family Therapy, 11(4), 345–356.
Miller, I. W., Ryan, C. E., Keitner, G. I., Bishop, D. S., & Epstein, N. B. (2000). The McMaster approach to families: Theory, assessment, treatment and research. Journal of Family Therapy, 22(2), 168–189.
Nock, M. K., & Prinstein, M. J. (2004). A functional approach to the assessment of self-mutilative behavior. Journal of Consulting and Clinical Psychology, 72(5), 885–890. https://doi.org/10.1037/0022-006X.72.5.885
Nock, M. K., & Prinstein, M. J. (2005). Contextual features and behavioral functions of self-mutilation among adolescents. Journal of Abnormal Psychology, 114(1), 140–146. https://doi.org/10.1037/0021-843X.114.1.140
Oldershaw, A., Richards, C., Simic, M., & Schmidt, U. (2008). Parents’ perspectives on adolescent self-harm: Qualitative study. The British Journal of Psychiatry, 193(2), 140–144. https://doi.org/10.1192/bjp.bp.107.045930
Prinz, R. J., Foster, S. L., Kent, R. N., & O’Leary, K. D. (1979). Multivariate assessment of conflict in distressed and nondistressed mother–adolescent dyads. Journal of Applied Behavior Analysis, 12(4), 691–700.
Rallis, B. A., Esposito-Smythers, C., & Mehlenbeck, R. (2015). Family environment as a moderator of the association between conduct disorder and suicidality. Journal of Aggression, Maltreatment & Trauma, 24(2), 150–168. https://doi.org/10.1080/10926771.2015.997909
Robin, A. L., & Foster, S. L. (1989). Negotiating parent–adolescent conflict: A behavioral–family systems approach. Guilford.
Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). Pearson Education.
Walker, K. L., Hirsch, J. K., Chang, E. C., & Jeglic, E. L. (2017). Non-suicidal self-injury and suicidal behavior in a diverse sample: The moderating role of social problem-solving ability. International Journal of Mental Health and Addiction, 15(3), 471–484. https://doi.org./10.1007/s11469-017-9755-x
Wetchler, J. L. (2003). Structural family therapy. In L. L. Hecker & J. L. Wetchler (Eds.), An introduction to marriage
and family therapy (pp. 63–93). Haworth Clinical Practice Press.
Melissa Sitton, MS, is a doctoral student at Southern Methodist University. Tina Du Rocher Schudlich, PhD, MHP, is a professor at Western Washington University. Christina Byrne, PhD, is an associate professor at Western Washington University. Chase M. Ochrach, MS, is a doctoral student at the University of Wisconsin–Madison. Seneca E. A. Erwin, BS, is a doctoral student at the University of Northern Colorado. Correspondence may be addressed to Tina Du Rocher Schudlich, 516 High St., MS 9172, Bellingham, WA 98225, email@example.com.
Alexis Miller, Jennifer M. Cook
Many theories are used to conceptualize adolescent substance use, yet none adequately assist mental health professionals in assessing adolescents’ strengths and risk factors while incorporating cultural factors. The authors reviewed common adolescent substance abuse theories and their strengths and limitations, and offer a new model to conceptualize adolescent substance use: The Adolescent Substance Use Risk Continuum. We posit that this strengths-based continuum enables clinicians to decrease stigma and offer hope to adolescents and their caregivers, as it integrates relevant factors to strengthen families and minimize risk. This model is a tool for counselors to use as they conceptualize client cases, plan treatment and focus counseling interventions. A case study illustrates the model and future research is suggested.
Keywords: adolescents, substance use, case conceptualization, cultural factors, strengths-based
For decades, theorists have worked to understand adolescent behaviors and conceptualize adolescent substance use. These theories have provided a strong base to conceptualize adolescent substance use, yet none integrate important counseling-focused concepts such as strengths and cultural factors. The Adolescent Substance Use Risk Continuum (ASURC) expands upon previous theoretical models and is designed to enhance counselors’ ability to conceptualize adolescent substance use from a strengths-based, stigma-reducing, and culturally sensitive perspective. The ASURC adds to counselors’ abilities to conceptualize adolescent substance use and enhances their abilities to create comprehensive treatment plans and interventions.
The theory of planned behavior (TPB; Ajzen, 1985), social learning theory (SLT; Akers, 1973), social control theory (SCT; Elliott, Huizinga, & Ageton, 1985), and social development theory (SDT; Hawkins & Weis, 1985) are four theories that have been applied to adolescent substance use. The TPB was developed to describe an individual’s behavior in a general sense, while the other three theories were developed to explain deviant and delinquent behavior. Even though these four theories were developed in the 1970s and 1980s and were not developed specifically for adolescent substance use, researchers have applied these theories to predict substance use within this population (Corrigan, Loneck, Videka, & Brown, 2007; Malmberg et al., 2012; Schroeder & Ford, 2012).
The TPB was developed as an expansion of the theory of reasoned action, which describes behavior as contingent upon an individual’s beliefs about a certain behavior and the perceived social pressure on the individual to perform that behavior (Ajzen, 1985). In addition to individual beliefs and perceived social pressure, the TPB adds an additional element to describe behavioral intention: self-efficacy. Self-efficacy refers to one’s perception of control to complete certain behaviors (Ajzen, 1985). Petraitis, Flay, and Miller (1995) introduced two types of self-efficacy related to adolescent substance use: use self-efficacy and refusal self-efficacy. Use self-efficacy consists of adolescents’ beliefs about their ability to obtain alcohol or other drugs, whereas refusal self-efficacy is indicative of adolescents’ beliefs about their abilities to refuse social pressure to use substances (Petraitis et al., 1995).
SLT was developed to explain so-called deviant behavior, and it is heavily influenced by behavioral theories, particularly operant conditioning and reinforcement. Therefore, behavior is learned when it is reinforced (Akers, 1973). The anticipation of either reinforcement or punishment can lead to behavioral increase or decrease, depending on who has the most influence on the adolescent, and who controls the reinforcement or punishment. Delinquent behavior can be influenced and maintained by a variety of sources, including parents, family, peers and school (Petraitis et al., 1995).
Similar to SLT, SCT emphasizes the importance of rewards and punishments in terms of deviant or delinquent behavior (Elliott et al., 1985). The result of either punishment or reinforcement is influenced mainly by an individual’s socialization into what the authors described as conventional society (Elliott et al., 1985). Conventional society points to general societal norms, largely congruent with dominant cultural norms. Therefore, according to SCT, an adolescent with a strong attachment to conventional society would have stronger internal and external controls and would be less motivated to choose delinquent behaviors. Inversely, an adolescent with a weak attachment to conventional society would have weaker internal and external controls and be more likely to engage in deviant behaviors (Elliot et al., 1985).
Hawkins and Weis (1985) integrated SLT and SCT to develop the SDT. The SDT is a developmental model of delinquent behavior that focuses on how adolescents are socialized through family, peers and school. Delinquent behaviors develop when adolescents are not socialized into conventional society appropriately. Opportunities for involvement with conventional individuals are seen as necessary but not sufficient for an individual to develop positive social bonds (Hawkins & Weis, 1985). There are two mediating factors associated with this socialization process toward positive social bonds: skills possessed by an adolescent and reinforcement of the opportunities for involvement (Hawkins & Weis, 1985). Skills that enhance an adolescent’s ability toward social bonds include adolescents’ social skills, or skills needed to interact and form social bonds with others (Hawkins & Weis, 1985). Similar to SLT and SCT, the SDT stresses the need for reinforcement, where behavior must be reinforced to continue (Hawkins & Weis, 1985).
Strengths and Limitations of Theoretical Underpinnings
The aforementioned models have made significant contributions to how counselors conceptualize adolescent substance use. Particularly, these models highlight the role social influences play in adolescent substance use and, accordingly, how social influences impact behavioral factors like reinforcement, punishment and reward (Akers, 1973; Elliot et al., 1985; Hawkins & Weis, 1985; Petraitis et al., 1995). Additionally, all models have been validated empirically to be predictive of adolescent substance use (Corrigan et al., 2007; Malmberg et al., 2012; Schroeder & Ford, 2012). Although these studies provide empirical support for predicting adolescent substance use and highlight social influences and behavioral factors, limitations exist, namely a lack of specificity related to social influences, the use of problematic language, and failure to incorporate cultural factors and contexts. Below, we detail the strengths and limitations of the aforementioned models to provide a rationale for a more encompassing, strengths-based approach to conceptualizing adolescent substance use.
Research has shown that social factors, such as family and peer group, play a mediating role in adolescent substance use in both positive and negative ways (Piko & Kovács, 2010; Van Ryzin, Fosco, & Dishion, 2012). Also, research highlights how important social influences are on adolescents’ substance use. The TPB suggests that substance use is dependent upon the adolescent’s individual attitudes of substance use and perceived social pressure to use substances (Petraitis et al., 1995). SLT and SCT emphasize how behavior, including substance use, is learned through reinforcement or punishment (Akers, 1973 Elliott et al., 1985). Someone in the adolescent’s life has to reward or punish the adolescent’s substance use for it to continue or cease.
Further, the SDT emphasizes the socialization process in regards to deviant behavior in adolescents. According to the SDT, socialization begins within the family unit, where a child has variable opportunities to develop social, cognitive and behavioral skills (Hawkins & Weis, 1985). As a child grows older, ostensibly these skills are reinforced positively within the school setting and peer group (Hawkins & Weis, 1985). However, if children are not socialized appropriately in the family system, children may not develop socially, cognitively and behaviorally as expected. In turn, they may turn to substance use to cope with stressful life events. Further, if adolescents were not socialized appropriately in early childhood, they may be at greater risk to become involved with adolescents who use substances.
While the four theories emphasize social influences as a factor in adolescent substance use, the TPB, SLT and SCT used the term social influences in a general sense only, and do not differentiate between the different types of social influences. There are a variety of social influences, including family, peers, school, sports teams, clubs and religious organizations, and each can have a varied impact on adolescents’ substance use. For example, involvement in religious organizations can protect some adolescents from substance use (Steinman & Zimmerman, 2004), while engagement with sports teams may increase adolescent substance use for others (Farb & Matjasko, 2012). The SDT was the only model discussed that divides socialization into three units: family, peer and school; however, the SDT suggests that family, peer, and school units all go through the same development process, seemingly at the same rate. Presumably, an adolescent is given the same opportunity for involvement with all three units toward the goal of creating healthy social bonds, and these opportunities are influenced by an adolescent’s current social skills and reinforcement from others (Hawkins & Weis, 1985). This adolescent substance use conceptualization can be problematic because it suggests the family, peer group and school all go through the same developmental process simultaneously and fails to recognize that different units can have different influences (some positive, some negative) on an adolescent, and these influences may develop asymmetrically. Further, the SDT proposes that a “social bond” (Hawkins & Weis, 1985, p. 80) to conventional society is a common goal and that adolescents have the social skills in place to create these bonds. Although it is hoped that adolescents will have strong social skills and that their support systems will endeavor to create healthy social bonds, this may not be the case for all adolescents. Further, some adolescents who have strong social skills may use them to procure substances and influence others to use.
The developers of SLT, SCT, and SDT used the terms deviant behavior, delinquent behavior, and conventional society to describe aspects contained in their theories. In juvenile justice literature, the terms deviant and delinquent point to adolescent behaviors considered to be age-inappropriate and destructive to self and family, as well as illegal (Pope, 1999). However, these terms are not used to simply describe behaviors as they were intended—they have become labels used to classify and marginalize adolescents who have made poor choices and acted in ways incongruent with conventional society (Constantine, 1999). Often, these terms are applied to adolescents who encompass non-dominant cultural identities (e.g., race, social class), which can serve to further oppress and marginalize adolescents who may experience societal and structural inequality. At the very least, these terms define adolescents by choices they have made and may lead to assumptions about who they are, adding additional stigma and shame to worthy individuals who can learn to make different choices, which is incongruent with a strengths-based perspective.
Conventional society is a term used to describe societal norms, determined most often by dominant U.S. cultural groups (Duncan, 1999). Similar to the issues with the terms deviant and delinquent, the term conventional society may not account accurately for cultural nuances and differences that vary from dominant culture expectations, furthering societal and structural oppression, discrimination and inequality clients experience (Constantine, 1999). For example, according to SCT, weak attachment to conventional society contributes to weaker internal and external controls, and an adolescent can develop a weak attachment to conventional society when she experiences a strain between her aspirations and her perceptions of the opportunity to actualize such aspirations. Therefore, through an SCT lens, if this adolescent lives in a low-income neighborhood where crime and unemployment are prevalent, she may be perceived to have a weak attachment to conventional society (Petraitis et al., 1995), without taking into account that her environment is out of sync with conventional society and cultural norms as defined by the dominant culture.
The final common limitation of the aforementioned models is the lack of inclusion of cultural influences on adolescents’ substance use. As mentioned previously, these four models highlight the importance of social influences on adolescents’ substance use yet do not specifically take cultural factors into consideration. The TPB discusses social influences in regard to an adolescent’s beliefs and perceived social pressure (Ajzen, 1985); however, there is no mention that these beliefs might be influenced by cultural values and experiences. Similarly, SLT suggests that an adolescent’s deviant behavior is influenced by positive or negative reinforcement received within the social context (Akers, 1973), yet fails to acknowledge that these positive or negative reinforcements are most likely influenced by cultural factors. The SDT outlines the socialization process through three different units (Hawkins & Weis, 1985), all of which exist within cultural contexts that influence adolescents’ substance use, yet the authors do not cite this as a possibility. Similarly, SCT discusses social influences on a systemic level, focusing on adolescent academic and occupational goals (Elliott et al., 1985). Adolescents’ cultural factors can influence their academic and occupational goals, as well as their perception of the likelihood of obtaining these goals. The theme among these four models is that they include factors influenced by culture without specifically mentioning or addressing culture or cultural variations.
We suggest a conceptual model for adolescent substance use that addresses specific social influences, uses inclusive and strengths-based language, and integrates cultural factors. We propose the ASURC as a model to meet this need. The ASURC asserts that while different social contexts are intertwined with one another, they all influence adolescent substance use in distinct ways. Further, the ASURC model uses strengths-based terms to reduce stigma and shame, and empowers clients and their caregivers to make person-affirmative choices. Finally, the ASURC integrates cultural components into all aspects of the model in order to provide appropriate context, acknowledging that adolescent substance use develops in a cultural context.
The Adolescent Substance Use Risk Continuum
The aforementioned theoretical models contain strengths and limitations and influenced the development of the ASURC model. Prior models emphasized social influence on adolescent substance use, and we emphasize social influences in our model as well. However, we believe that different social systems will have different influences on each adolescent, and each social system develops at its own rate. Further, the included areas are not meant to be predictive of substance use, and can serve both as strengths and risk factors, depending on the individual’s circumstances. The areas featured in our model include: parental and caregiver engagement, relationship between parents and caregivers and adolescent, family history of substance use, biological factors, level of susceptibility to peer pressure, childhood adversity, and academic engagement. While we believe the areas in our model have distinct impacts on adolescents, all areas interact and influence one another, and all areas are influenced by singular and intersecting cultural identities.
The ASURC emphasizes the importance of cultural considerations when conceptualizing adolescent substance use. We used Hays’ (1996) “ADDRESSING” model as a foundation. The included cultural factors are by no means exhaustive; counselors are encouraged to expand this list to work with their clients appropriately. Cultural factors should be considered in terms of the individual, family, community and societal contexts when applied to the ASURC areas. Further, it is important to consider ways in which cultural identities can serve as protective or risk factors, depending on the individual’s dominant and non-dominant cultural identities, and the identities most salient to the client. Client cultural influences are subjective experiences, and counselors should take great care and time to determine their relevance for each client.
Further, the ASURC is a strengths-based approach to conceptualizing adolescent substance use. Previous theories contain the use of problematic language, such as conventional society, deviant behavior, and delinquent behavior, when describing adolescent substance use. We feel the use of this language can lead to stigma and instill a sense of shame for this population. Focusing on strengths while using the ASURC will aid clinicians in fostering a sense of hope while working with this population. Strengths are not a separate component of the model, but rather are incorporated in each aspect of the model.
As the name suggests, the ASURC (Adolescent Substance Use Risk Continuum) is a continuum, ranging from minimal risk to high risk. The continuum starts at minimal risk instead of no risk because substance use and addiction can occur in anyone. Further, a continuum suggests that an adolescent can move bi-directionally along the continuum depending on changes. This potential for movement can instill hope and serve to reduce shame associated with adolescent substance use. To use the ASURC model (see Figure 1), one starts at the bottom of the model and considers how the areas listed serve as adolescent protective or risk factors. When working through these areas, cultural identities are incorporated. These identities are represented above the entire model to indicate how they influence everything underneath them. Cultural factors should be considered from the perspective of the individual, family, community and society as a whole, because their influence could be different in each area. Finally, the counselor determines where the adolescent falls on the risk continuum. Because multiple aspects influence an individual’s location on the continuum, it is important to note the protective and risk factors associated with each of the model’s areas for any specific client. This assessment can assist counselors in developing holistic treatment plans that address not only adolescents’ substance use, but also their strengths and areas that could be enhanced as they strive to eliminate substance use.
There are many cultural factors to consider when conceptualizing adolescent substance use. The ASURC is based on Hays’ (1996) ADDRESSING model. There are nine overlapping cultural influences included in the ADDRESSING model: age, disability status, religion, ethnicity, socioeconomic status, sexual orientation, indigenous heritage, national origin and gender (Hays, 1996). To these we added race and language. This list is not exhaustive but rather a starting point to consider how culture can be a protective or risk factor for adolescents.
When clinicians consider adolescents’ cultural identities, it is important to do so within individual, family, community and societal contexts. To consider only one context diminishes the multiplicity of adolescents’ experiences, and it can negate the impact these contexts have on them. For example, it is common for societal context to be overlooked in favor of individual experiences due to the importance placed on individualism by the dominant culture (Johnson, 2006). When societal context is neglected, structural inequality may be ignored. Structural inequality denotes the oppression or restrictions non-dominant groups experience when they attempt to access resources, including mental health treatment, which are available without hindrance to dominant culture groups. Structural inequality can impact adolescents’ beliefs about their ability to choose not to use substances and their ability to achieve success and access resources, and can reduce hope about their life circumstances (Hancock, Waites, & Kledaras, 2012).
Religion and spirituality. Religion and spirituality can be a protective factor for adolescents. Higher levels of religious involvement tend to correlate with lower levels of substance use (Mason, Schmidt, & Mennis, 2012). Mason et al. (2012) identified two specific aspects of religiosity associated with lower levels of alcohol and drug use: social religiosity and perceived religious support. Social religiosity refers to public displays of religious behavior, such as church attendance and participation in religious activities; perceived religious support encompasses emotional support one receives from a religious institution as well as tangible support like materials or money donated by a religious organization (Mason et al., 2012). Private religiosity, such as personal importance of religion and individual prayer, was not found to be a protective factor (Mason et al., 2012), suggesting the more social aspects of religion are more beneficial for preventing adolescent substance use. Similarly, religion may be a risk factor when adolescents, such as lesbian, gay, or bisexual (LGB) youth, feel judged, shamed, or shunned by their religious community, which may increase the likelihood of substance use (Barnes & Meyer, 2012).
Ethnicity. Ethnicity is significant because reported substance abuse and dependence rates are higher for people of color than for White people in the population (Substance Abuse and Mental Health Services Administration, 2012). Of the total population of people of color, who represent only 38.5% of the U.S. population, 9,319,277 people reported substance abuse and dependence. This number is particularly staggering when compared to White people, who represent 61.5% of the population, 15,713,373 of whom reported substance abuse and dependence (Substance Abuse and Mental Health Services Administration, 2012). These statistics demonstrate that adolescents of color are more likely to develop substance abuse issues than their White counterparts. However, these statistics do not incorporate issues related to structural inequality, nor do they speak to restricted treatment access or racial groups’ protective factors that could be bolstered. For example, Native Americans, who have the highest statistical rate of substance use, also emphasize spirituality and the importance of the extended family (Sue & Sue, 2013). These factors can serve as protective factors for Native American adolescents. Similarly, researchers have found religious engagement among African American adolescents to be a protective factor (Steinman & Zimmerman, 2004). African American adolescents who attended religious services regularly had lower substance use rates than their peers who did not.
Socioeconomic status. Socioeconomic status (SES), particularly education level, influences substance use in adolescents, and subsequently intersects with race and ethnicity. Adolescents who drop out of high school are more likely to engage in substance use, and lower levels of education are associated with higher prevalence of substance-related diagnoses (Henry, Knight, & Thornberry, 2012). American Indian, Latino, and African American adolescents’ math and reading proficiency rates are less than half of White adolescents, most likely due to structural inequality in low-income schools. Students in these groups are less likely to graduate from high school than their White peers (Henry et al., 2012). Furthermore, living in poverty or low SES are associated with higher risks of substance use, and adolescents from racial minority groups are at a higher risk for living in poverty and low-SES families (Van Wormer & Davis, 2013).
Sexual orientation. Sexual orientation is another cultural factor to consider. The LGB community is at greater risk for substance use compared to heterosexual individuals (Brooks & McHenry, 2009). One explanation for the increased risk in the LGB community may be due to homophobia and heterosexual superiority and internalized homophobia, which can lead individuals in the LGB community to turn to substances as a way to cope (Brooks & McHenry, 2009). Further, gay bars are a mainstay of the LGB community, and even though adolescents may not be allowed to drink legally, bar environments may be integral during adolescents’ coming out process (Brooks & McHenry, 2009). Socialization in a bar environment can lead to adolescent substance use as a way to fit in and cope.
Caregiver Engagement and Adolescent–Caregiver Relationship
Family environment can serve as a protective or risk factor for adolescent substance use. A key factor associated with family environment is parental or caregiver supervision. Strong caregiver supervision has been shown to minimize an adolescent’s risk-taking behavior, such as substance use (Van Ryzin et al., 2012). While caregiver supervision is an important protective factor for adolescents, it also is important for adolescents to be able to experience a sense of autonomy within their family of origin. Allen, Chango, Szwedo, Schad, & Marston (2012) defined autonomy within the family of origin as adolescents’ ability to have opinions and beliefs that differ from their caregiver(s) and can be fostered through a supportive adolescent–caregiver relationship. Positive relationships between caregivers and adolescents can increase self-esteem and healthy coping skills, leading to a decrease in risk-taking behaviors (Piko & Kovács, 2010). According to Piko and Kovács (2010), high levels of both satisfaction and caregiver support perceived by the adolescent define this positive relationship. Further, positive relations within the family can lead to higher levels of family obligation perceived by the adolescent. Family obligation is the perceived importance of spending time together, family unity and family social support; higher levels have been found to deter adolescents from unhealthy risk taking, including the use of alcohol and drugs (Telzer, Fuligni, Lieberman, & Galván, 2013).
Conversely, low caregiver involvement can be a risk factor for adolescent substance use. Adolescents who have low caregiver supervision are more likely to engage with peers who use substances and, subsequently, use substances as a way to find social support (Van Ryzin et al., 2012). Additionally, adolescents who do not have positive relationships with their caregivers have a more difficult time self-regulating their behaviors and increased risk for using substances as a way to cope with stress (Hummel, Shelton, Heron, Moore, & van den Bree, 2013).
Family Substance Abuse History and Biological Risks
Family history of substance use is an additional risk factor for adolescents. Children of parents and caregivers who abuse alcohol are four times more likely to develop an addiction (Van Wormer & Davis, 2013). This risk may be partly due to biological predisposition, and part may be environmental. Scientists have begun to better understand how genes affect substance use disorder development and posit that 40–60% of alcohol use disorders can be explained by genes (Van Wormer & Davis, 2013). It can be difficult to determine whether an individual’s addiction is inherited through genetic composition or is learned via the family environment, or a combination of both. Genetics can include predisposition to impulsivity, and some scientists believe individuals at risk for substance use disorders may be biologically predisposed to overreact to stressful situations and life events. Individuals predisposed genetically to engage in sensation-seeking and impulsive behaviors are more likely to experiment with alcohol and other substances (Van Wormer & Davis, 2013). While biological risk can increase adolescents’ predisposition to develop addiction, it does not necessarily lead to addiction (Van Wormer & Davis, 2013). This message can instill hope and infuse self-efficacy in families who may have a history of substance abuse.
Adolescence is marked by an increase in risk-taking behaviors, which may be associated with developmental biology (Telzer et al., 2013). Adolescents show a heightened response in the ventral striatal, which is part of the brain’s reward system. This heightened response in the ventral striatal can cause adolescents to engage in more reward-seeking behaviors compared to children and adults. Further, adolescents show less activation in pre-frontal regions of the brain, the part of the brain in charge of executive functioning, which can lead to increased risk-taking behaviors (Telzer et al., 2013). Research has shown that an increase in family obligation can lead to decreased sensitivity in the ventral striatal and increased activity in the pre-frontal region of the brain (Telzer et al., 2013). These findings suggest that improved quality in the adolescent–caregiver relationship can jettison substance abuse. Specifically, increased family obligation can help buffer some adolescent biological risks for substance use.
Susceptibility to Peer Influences
Peer relationships can play a role in the development of adolescent substance use. During adolescence, individuals start to spend more time with peer groups than with their families (Piko & Kovács, 2010). Additionally, adolescence is marked by a heightened sense of reward. This focus on reward can lead to an increased desire for adolescents to please their peers, making it more difficult for them to resist peer pressure (Van Ryzin et al., 2012). If adolescents associate with peers who use alcohol and drugs, they are more likely to begin using substances as a way to be accepted by their peer group (Van Ryzin et al., 2012).
Inversely, if adolescents are associated with peers who are not involved in substance use, they are less likely to use substances (Van Ryzin et al., 2012). Moreover, there is a negative correlation between adolescents who are involved in supervised extracurricular activities and substance use (Farb & Matjasko, 2012). Specifically, involvement in school-based activities such as performing arts, leadership groups and clubs is associated with lower rates of substance use (Darling, Caldwell, & Smith, 2005). However, there is a positive correlation between athletics and substance abuse, meaning adolescents involved in athletics are more likely to engage in substance use (Farb & Matjasko, 2012). Researchers believe this positive correlation is due to the subculture of high school athletics that promotes alcohol and drug use (Denault, Poulin, & Pedersen, 2009).
Adolescents who experienced childhood adversity are at greater risk for developing substance use disorders (Benjet, Borges, Medina-Mora, & Méndez, 2013). Childhood adversity refers to family instability such as parental and caregiver mental illness, substance use, and criminal behavior, witnessing domestic violence, and experiencing abuse, neglect, interpersonal loss, and socioeconomic disadvantage. Researchers have suggested that this relationship is due to the self-medication hypothesis, in that adolescents who experience childhood adversity may turn to alcohol and drugs in order to alleviate the pain they encounter as a result of such experiences (Benjet et al., 2013).
Not only are adverse childhood experiences a risk factor for developing substance use disorders, but also for substance use opportunities (Benjet et al., 2013). One possible explanation for such opportunities is the presence of substances in the family environment. For adolescents who experienced child abuse or neglect or who witnessed domestic violence, there is an increased chance that substances were present in their household, making it easier for them to gain access to substances (Benjet et al., 2013).
The absence of childhood adversity can be a protective factor against adolescent substance use (Benjet et al., 2013). Another protective factor in terms of childhood adversity is early intervention (Durlak, Weissberg, Dymnicki, Taylor, & Schellinger, 2011). Early intervention can help children develop healthy coping skills to manage stress. Healthy coping strategies can be implemented to replace more negative coping strategies like substance use (Durlak et al., 2011).
Academic engagement can have positive and negative effects on adolescents’ potential substance use. Adolescents who drop out of high school are more likely than their counterparts to engage in substance use (Henry, Knight, & Thornberry, 2012). Further, early school disengagement can be a warning sign to predict high school dropout (Henry et al., 2012). For some adolescents, school engagement can be a protective factor. Particularly, adolescents who experience a positive school climate and have strong school engagement are less likely to use substances (Piko & Kovács, 2010). A positive relationship between adolescents and their teachers can be another protective factor. Previous studies have shown that adolescents who have a positive relationship with their teachers and have a high level of perceived support from teachers are less likely to engage in substance use (Demanet & Van Houtte, 2012).
The case study below provides an example of how clinicians can use the ASURC to conceptualize and plan interventions when working with this population.
John is a 14-year-old, biracial male and high school freshman. He lives with his mother and grandmother, both of whom are African American, and they reside in a low socioeconomic neighborhood. Both John’s mother and grandmother work full-time, and his mother works a second job, leaving John unsupervised after school and on the weekends. John’s father, a 38-year-old Puerto Rican male, left the home when John was 4 years old. Prior to his father’s departure, John witnessed domestic violence between his parents. During a fight, John intervened on his mother’s behalf and his father hit him. After this event, John’s mother forbade her husband from living in their home and sought counseling services for her son. After his father left, John had only sporadic visits with him, mainly due to his father’s alcohol use. In addition to John’s father’s alcohol use, there is family history of substance use on his mother’s side. His maternal great-aunts use alcohol, and his maternal uncle uses marijuana daily.
This year, John made the varsity football team and has been spending time with the senior football players after practice during the week and on weekends. In addition to being involved with the football team, John is involved with his church community. At school, John is an average student, earning mostly Bs and Cs, and he reports that he enjoys learning.
John started drinking and smoking cigarettes shortly after joining the football team in order to impress the junior and senior football players. Initially, John was hesitant to drink or smoke; however, after using more frequently, he started to enjoy it and reported feeling more relaxed. Currently, John drinks with his friends on the football team two to three times a week and smokes with them daily. John drinks only when he is with this group of peers, yet he has started to smoke when he is alone.
Over the past two months, John’s grandmother has caught him sneaking back into the house at night smelling like alcohol and cigarettes. The first two times this occurred, John’s grandmother decided not to tell his mother because she believed John when he said it would not happen again. When John’s grandmother caught him a third time, she told his mother. John’s mother was surprised when she heard this news because she believed she and John had a close and honest relationship. Distraught, John’s mother brought him to counseling.
Case Analysis Using the ASURC Model
Conceptualizing this case using the ASURC model reveals that John has both protective and risk factors related to his substance use. In terms of his family environment, John’s mother reports that she and John have a close and honest relationship. This close relationship serves as a protective factor for John because a positive relationship between adolescents and their parents is associated with a decreased risk of adolescent substance use (Piko & Kovács, 2010). Yet, John has minimal supervision at night and on the weekends due to his mother and grandmother’s work schedules. Low caregiver supervision is a risk factor for John because research shows that it is associated with an increased risk of adolescent substance use (Van Ryzin et al., 2012). The family’s low SES impacts John’s low caregiver supervision, and low SES can be associated with a higher risk of substance use (Von Wormer & Davis, 2013).
This year, John joined the football team, and previous research has shown that involvement in athletics in high school can be a risk factor for substance use (Farb & Matjasko, 2012), and adolescents who become associated with peers who use are at an increased likelihood to use (Van Ryzin et al., 2012). Furthermore, adolescence is a period characterized by a heightened sense of reward (Van Ryzin et al., 2012), suggesting that John may have an increased desire to please his peers and difficulty resisting peer pressure. At this point in time, John is drinking only when he is with his friends on the football team, suggesting this peer group is influencing John, yet he has begun smoking alone. Additionally, John is involved in his church community, which serves as a protective factor because being involved in a faith community lowers the risk for substance use in adolescents (Mason et al., 2012). Religious engagement, particularly among African American adolescents, can be a protective factor (Steinman & Zimmerman, 2004), which may be true for John if he identifies with this part of his racial identity as a biracial youth.
The next area of risk and protective factors in the ASURC model is childhood adversity. John witnessed domestic violence between his parents when he was younger, and as a result of attempting to intervene on behalf of his mother, John was hit by his father, a risk factor for adolescent substance use (Benjet et al., 2013). Fortunately, John’s mother sought counseling services for her son after the incident occurred. Early intervention can help offset the negative effects of these experiences (Durlak et al., 2011), and it is possible counseling provided John with healthy coping strategies.
According to the ASURC model, biological factors can impact adolescent substance use. John has a family history of substance use on both his maternal and paternal sides, and genes can play a role in the development of substance use disorders (Van Wormer & Davis, 2013). Further, adolescents experience an increase in risk-taking behaviors due to biological changes associated with adolescence (Telzer et al, 2013), and these changes may cause John to engage in increased risk-taking and pleasure-seeking behaviors.
Higher levels of academic engagement correlate with lower levels of substance use (Henry et al., 2012). John reported that he enjoys learning, suggesting he could have a high level of academic engagement. Nonetheless, John is currently earning Bs and Cs at school, pointing to a disconnection between his motivation to learn and his current grades. This disconnect could be due to associated cultural factors. John is biracial and living in a low socioeconomic neighborhood, and adolescents who live in such neighborhoods and are racial minorities can be at a disadvantage due to structural inequality (Henry et al., 2012).
When taking all of the risk and protective factors into account, we placed John on the low end of moderate risk using the ASURC model. While John does have various risk factors contributing to his substance use, he also has protective factors that can help to buffer these factors. Further, John’s cultural identities impact him in various areas of the model. In particular, John’s biracial identity and living in a low socioeconomic neighborhood could be risk factors for substance use, while being involved in his church community is a protective factor. It would be important to explore with John how he views his race, SES, and religion, and if he sees them as protective or not. Further, it would be helpful to understand how John views his gender and sexual orientation, and how these identities affect his worldview.
Using the ASURC model to conceptualize John’s case can assist counselors with their interventions with John and his family. While using the model, a counselor is able to assist John and his family to identify current strengths such as positive family relationships, involvement in his church community, and potential for high academic engagement. Identifying these strengths allows John and his caregivers to concretize what is helpful in their situation and allows the counselor to encourage more of these behaviors as tools to strengthen weaker areas. For example, because there are strong family relationships, John’s mother and grandmother can increase their engagement with John when they are away from home via texts or phone calls. Increasing parental engagement will be beneficial for the family, particularly John’s mother and grandmother knowing who John is spending time with because his substance use is heavily influenced by his friendships on the football team. Similarly, because John likes to learn yet is not achieving high grades in school, tutoring programs can be sought to bolster his academic performance and solidify his academic engagement, as well as fill his time with positive activities that may decrease his desire to use. Additionally, it may be helpful to educate John and his caregivers about biological predispositions and risk factors in adolescence. This information can empower John to make positive choices when he understands both that he is not destined to develop an addiction and that he is experiencing normal physical changes. Additionally, it could prove helpful to talk with John and his family about how they might be experiencing structural inequality due to their race and SES. Engaging them in this conversation can normalize their experiences and serve to determine points where advocacy with and on behalf of the family may alleviate some of the strain they experience. Finally, because John’s risk level is on the low end of moderate, structured substance abuse treatment may not be warranted at this time. Interventions could include assessing John’s readiness to stop using and working through a change commitment while strengthening John’s protective factors in an effort to decrease his risk factors.
Currently, the ASURC is a conceptual framework yet to be evaluated for efficacy with adolescent populations. Empirical research is needed to determine the model’s viability, validity and efficacy. Further, qualitative research would inform clinicians about the ways in which adolescents and their families felt stronger and more empowered by engaging in counseling practices that use this model’s approach.
Further research can be conducted to evaluate the degree of influence different components of the model have on adolescents with substance use concerns. Also, future research could investigate the relationship the model components have with one another, particularly the interplay of different cultural identities. Research is warranted to determine additional ways in which cultural factors can be used to strengthen clients and their families to mitigate deficit-based research and the pervasive negative cultural messages about non-dominant cultural groups and their struggles with substance use.
The ASURC is a strengths-based approach focused on identifying protective and risk factors as counselors conceptualize adolescent substance use. While previous theories conceptualized adolescent substance use using strengths, they had limitations, including only discussing social influences in a general sense, use of problematic language, and lack of cultural influences. The ASURC builds upon the strengths of previous models while addressing their limitations. The ASURC model emphasizes the need for a strengths-based approach while working with adolescent populations and focuses on the importance of the consideration of cultural influences during the conceptualization process.
Finally, this model serves as a tool to help guide interventions that best serve adolescents and their families. Using the ASURC model for case conceptualization can help counselors determine the most salient factors of the model to the particular case, which will in turn assist in the treatment planning process. Future research is warranted to determine the viability of the ASURC model as an evidence-based practice.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckmann (Eds.), Action-control: From cognition to behavior (pp. 11−39). New York, NY: Springer.
Akers, R. L. (1973). Deviant behavior: A social learning approach (2nd ed.). Belmont, CA: Wadsworth.
Allen, J. P., Chango, J., Szwedo, D., Schad, M., & Marston, E. (2012). Predictors of susceptibility to peer influence regarding substance use in adolescence. Child Development, 83, 337−350.
Barnes, D. M., & Meyer, I. H. (2012). Religious affiliation, internalized homophobia, and mental health in lesbians, gay men, and bisexuals. American Journal of Orthopsychiatry, 82, 505−515.
Benjet, C., Borges, G., Medina-Mora, M. E., & Méndez, E. (2013). Chronic childhood adversity and stages of substance use involvement in adolescents. Drug and Alcohol Dependence, 131, 85−91.
Brooks, F., & McHenry, B. (2009). A contemporary approach to substance abuse and addiction counseling: A counselor’s guide to application and understanding. Alexandria, VA: American Counseling Association.
Constantine, M. G. (1999). Labeling theory. In J. S. Mio, J. E. Trimble, P. Arredondo, H. E. Cheatham, & D. Sue (Eds.), Key words in multicultural interventions: A dictionary (pp. 169−170). Westport, CT: Greenwood Press.
Corrigan, M. J., Loneck, B., Videka, L., & Brown, M. C. (2007). Moving the risk and protective factor framework toward individualized assessment in adolescent substance abuse prevention. Journal of Child & Adolescent Substance Abuse, 16(3), 17−34. doi:10.1300/J029v16n03_02
Darling, N., Caldwell, L. L., & Smith, R. (2005). Participation in school-based extracurricular activities and adolescent adjustment. Journal of Leisure Research, 37, 51−76.
Demanet, J., & Van Houtte, M. (2012). School belonging and school misconduct: The differing role of teacher and peer attachment. Journal of Youth and Adolescence, 41, 499−514. doi:10.1007/s10964-011-9674-2
Denault, A.-S., Poulin, F., & Pedersen, S. (2009). Intensity of participation in organized youth activities during the high school years: Longitudinal associations with adjustment. Applied Developmental Science, 13(2), 74−87. doi:10.1080/10888690902801459
Duncan, L. (1999). Social norms. In J. S. Mio, J. E. Trimble, P. Arredondo, H. E. Cheatham, & D. Sue (Eds.), Key words in multicultural interventions: A dictionary (pp. 239−240). Westport, CT: Greenwood Press.
Durlak, J. A., Weissberg, R. P., Dymnicki, A. B., Taylor, R. D., & Schellinger, K. B. (2011). The impact of enhancing students’ social and emotional learning: A meta-analysis of school-based universal interventions. Child Development, 82, 405−432. doi:10.1111/j.1467-8624.2010.01564.x
Elliott, D. S., Huizinga, D., & Ageton, S. S. (1985). Explaining delinquency and drug use. Beverly Hills, CA: Sage.
Farb, A. F., & Matjasko, J. L. (2012). Recent advances in research on school-based extracurricular activities and adolescent development. Developmental Review, 32, 1−48. doi:10.1016/j.dr.2011.10.001
Hancock, T. U., Waites, C., & Kledaras, C. G. (2012). Facing structure inequality: Students’ orientation to oppression and practice with oppressed groups. Journal of Social Work Education, 48, 5−25.
Hawkins, J. D., & Weis, J. G. (1985). The social development model: An integrated approach to delinquency prevention. Journal of Primary Prevention, 6, 73−97. doi:10.1007/BF01325432
Hays, P. A. (1996). Addressing the complexities of culture and gender in counseling. Journal of Counseling & Development, 74, 332−338. doi:10.1002/j.1556-6676.1996.tb01876.x
Henry, K. L., Knight, K. E., & Thornberry, T. P. (2012). School disengagement as a predictor of dropout, delin-quency, and problem substance use during adolescence and early adulthood. Journal of Youth and Adolescence, 41(2), 156−166. doi:10.1007/s10964-011-9665-3
Hummel, A., Shelton, K. H., Heron, J., Moore, L., & van den Bree, M. (2013). A systematic review of the relation-ships between family functioning, pubertal timing and adolescent substance use. Addiction, 108, 487−496. doi:10.1111/add.12055
Johnson, A. G. (2006). Privilege, power, and difference (2nd ed.). New York, NY: McGraw-Hill.
Malmberg, M., Overbeek, G., Vermulst, A. A., Monshouwer, K., Vollebergh, W. A., & Engels, R. C. (2012). The
theory of planned behavior: Precursors of marijuana use in early adolescence? Drug and Alcohol Dependence, 123, 22−28. doi:10.1016/j.drugalcdep.2011.10.011
Mason, M. J., Schmidt, C., & Mennis, J. (2012). Dimensions of religiosity and access to religious social capital: Correlates with substance use among urban adolescents. The Journal of Primary Prevention, 33, 229−237. doi:10.1007/s10935-012-0283-y
Petraitis, J., Flay, B. R., & Miller, T. Q. (1995). Reviewing theories of adolescent substance use: Organizing pieces in the puzzle. Psychological Bulletin, 117, 67–86. doi:10.1037/0033-2909.117.1.67
Piko, B. F., & Kovács, E. (2010). Do parents and school matter? Protective factors for adolescent substance use. Addictive Behaviors, 35, 53−56. doi:10.1016/j.addbeh.2009.08.004
Pope, R. L. (1999). Deviance. In J. S. Mio, J. E. Trimble, P. Arredondo, H. E. Cheatham, & D. Sue (Eds.), Key words in multicultural interventions: A dictionary (pp. 92−93). Westport, CT: Greenwood Press.
Schroeder, R. D., & Ford, J. A. (2012). Prescription drug misuse: A test of three competing criminological theories. Journal of Drug Issues, 42, 4−27. doi:10.1177/0022042612436654
Substance Abuse and Mental Health Services Administration. (2012). Results from the 2011 national survey on drug use and health: Summary of national findings. NSDUH, H-44(12−4713). Rockville, MD: Author.
Steinman, K. J., & Zimmerman, M. A. (2004). Religious activity and risk behavior among African American adolescents: Concurrent and developmental effects. American Journal of Community Psychology, 33(3), 151−161. doi:10.1023/B:AJCP.0000027002.93526.bb
Sue, D. W., & Sue, D. (2013). Counseling the culturally diverse: Theory and practice (6th ed.). New York, NY: John Wiley & Sons, Inc.
Telzer, E. H., Fuligni, A. J., Lieberman, M. D., & Galván, A. (2013). Meaningful family relationships: Neuro-cognitive buffers of adolescent risk taking. Journal of Cognitive Neuroscience, 25, 374−387.
Van Ryzin, M. J., Fosco, G. M., & Dishion, T. J. (2012). Family and peer predictors of substance use from early adolescence to early adulthood: An 11-year prospective analysis. Addictive Behaviors, 37, 1314−1324. doi:10.1016/j.addbeh.2012.06.020
Van Wormer, K., & Davis, D. R. (2013). Addiction treatment: A strengths perspective (3rd ed.). Belmont, CA:
Alexis Miller, NCC, is a professional counselor for the Dual Diagnosis Partial Hospitalization Program at Rogers Memorial Hospital in Madison, WI. Jennifer M. Cook, NCC, is an Assistant Professor at Marquette University. Correspondence can be addressed to Rogers Memorial Hospital, Attn: Alexis Miller, 406 Science Dr., Suite 110, Madison, WI 53711, firstname.lastname@example.org.
Jacqueline M. Swank, Peter Huber
Employment preparation and life skill development are crucial in assisting students identified as having emotional and behavioral disabilities with successfully transitioning to adulthood following high school. This article outlines four initiatives that a school counselor developed with other school personnel to promote work skills, life skills, and social and emotional development, which include (a) a school vegetable garden, (b) a raised worm bed, (c) a sewing group, and (d) community collaboration. The authors also discuss implications for school counselors and recommendations for future research.
Keywords: school counseling, life skills, transition, disabilities, adolescents
High school counselors, teachers and other school personnel are in the unique position of providing resources to help students transition from high school to early adulthood. This transition may involve preparation for college or development of employment skills for students who plan to enter the workforce rather than attend college. Life skill development (e.g., communication, problem-solving skills, financial management) is also crucial for young people as they transition out of high school.
The transition from high school to adulthood can be especially difficult for students with emotional and behavioral disabilities (EBD). The Individuals with Disabilities Education Act (IDEA, 2004) defines the term emotional disturbance as follows:
A condition exhibiting one or more of the following characteristics over a long period of time and to a marked degree that adversely affects a child’s educational performance: (a) an inability to learn that cannot be explained by intellectual, sensory, or health factors; (b) an inability to build or maintain satisfactory interpersonal relationships with peers and teachers; (c) inappropriate types of behavior or feelings under normal circumstances; (d) a general pervasive mood of unhappiness or depression; (e) a tendency to develop physical symptoms or fears associated with personal or school problems.
Specifically in Florida, where the innovative program discussed in this article was developed, a student with an emotional or behavioral disability is defined as having “persistent (is not sufficiently responsive to implemented evidence-based interventions) and consistent emotional or behavioral responses that adversely affect performance in the educational environment that cannot be attributed to age, culture, gender, or ethnicity” (Exceptional Student Education Eligibility for Students with Emotional/Behavioral Disabilities, 2009, para.1). In 2000, researchers reported that approximately 230,081 children and adolescents in the United States were receiving services within the serious emotional disturbances category, with an estimated 1.15% within the age range of 13–16 years old (Cameto, Wagner, Newman, Blackorby, & Javitz, 2000). These students often have multiple obstacles to overcome including (a) social, (b) emotional, (c) academic, and (d) environmental challenges (Lehman, Clark, Bullis, Rinkin, & Castellanos, 2002). Therefore, it is crucial to create programs to assist these students in developing the knowledge and skills needed to make a successful transition to adulthood.
Transitioning to adulthood may involve continued education or full-time employment. However, young people in general are often ill-prepared to enter the workforce (Burgstahler, 2001); therefore, it is imperative that schools provide job training to help prepare students who plan to enter the workforce following high school. In regard to students with disabilities, the IDEA Amendments of 1997 and the IDEA of 2004 outline the responsibility of schools to help high school students transition to adulthood. Specifically, IDEA requires schools to begin transition planning for students with disabilities by age 14 and to have transition services specified within a student’s Individual Education Program (IEP) by age 16 (Sabbatino & Macrine, 2007). However, the development of a transition plan alone does not necessarily lead to successful employment following high school (Sabbatino & Macrine, 2007); therefore, it is incumbent upon schools to focus on implementing programs designed to assist students with successfully transitioning to adulthood.
Employment Preparation and Life Skill Development
Researchers have examined factors that contribute to the success of students with disabilities following high school. Test et al. (2009) examined the literature and identified 16 in-school predictors of post-high school success: (a) career awareness, (b) community experiences, (c) exit exam requirements/diploma, (d) general education, (e) interagency collaboration, (f) occupational courses, (g) paid work experience, (h) parental involvement, (i) program of study, (j) self-determination and advocacy, (k) self-care/independent living, (l) social skills, (m) student support, (n) transition program, (o) vocational education, and (p) work-study. Additionally, Gore, Kadish, and Aseltine (2003) interviewed young adults who had graduated from high school two years prior to the study to examine how taking a career major in school affects early career work orientation and experience. The researchers found that participation in a program that bridges education to future employment was predictive of more optimistic views about future career aspirations two years later.
Researchers also have examined the relationship between career decisions following high school and mental health. Aseltine and Gore (2005) interviewed seniors and recent high school dropouts and then interviewed them again two years later to examine the psychosocial functioning of individuals following high school. The findings suggested that individuals who attended additional schooling or engaged in full-time employment following high school reported a more positive quality of life and had lower levels of depression, concluding that engagement in structured activities (schooling or employment) on a full-time basis following graduation contributed to greater psychological functioning. This research was not focused specifically on individuals with EBD; however, the findings suggest a relationship between successful post-high school transition and positive psychosocial functioning.
The National Longitudinal Transition Study-2 (NLTS2) was designed to examine the post-high school experiences of individuals with disabilities. Wagner, Newman, Cameto, Levine, and Garza (2006) reported that students within the emotional disturbances category had the lowest (56%) school completion rate, except for individuals within the categories of intellectual disabilities and multiple disabilities. Additionally, approximately 60% of individuals within the emotional disturbances category were employed at some point; however, only about half (30%) were employed after two years. Also, approximately 20% were enrolled in postsecondary education. Furthermore, in regards to involvement with the legal system, 75% had been stopped by the police for a non-traffic related offense, 58% had been arrested at minimum one time, and 43% had been on probation or parole. The percentage of these students involved in programs designed to promote graduation and foster a successful transition to adulthood is unknown; however, the low graduation rate, low employment rate, and high incident of legal involvement constitutes a need for the establishment of interventions.
Zigmond (2006) examined the career decisions of individuals with severe emotional and behavioral disorders spanning a two-year period following graduation or dropping out of an alternative high school. About half of the participants were employed at each of the five data collection periods (3, 6, 12, 18 and 24 months); however, only three of the 15 who had a job at the three-month point had the same job at the 24-month mark. These findings indicate a higher rate of employment when compared to the NLTS2 findings; however, due to the small sample size in this study, the findings should be interpreted with caution. Nevertheless, Zigmond presents a need for future research to examine the effectiveness of alternative schooling programs on successful transition to adulthood for individuals with EBD. Additionally, Carran, Kerins and Murray (2005) examined the success of individuals who had a positive discharge (graduation) or negative discharge (dropping out) from an alternative school designed for students with EBD over a three-year period. Students who received a positive discharge were more likely to maintain employment and were less likely to be arrested; however, the employment rate declined by year three. The findings of Carran et al. (2005) indicate a positive correlation between successful completion of high school and transition to adulthood; however, further research is needed to determine the long-term benefits of high school training for individuals with EBD. Yet implementing programs in high schools focused on the needs of students with EBD appears to support these individuals in their successful transition to adulthood.
Employment preparation and life skill development are especially important for students with EBD because, in addition to experiencing multiple obstacles in transitioning to adulthood, these individuals may not meet eligibility requirements for vocational rehabilitation following graduation; therefore, students with EBD may lack the needed support and experience to be successful in seeking employment (Carter, Trainor, Ditchman, & Owens, 2011). Additionally, students with EBD may benefit from services designed to foster self-determination, a crucial skill in transitioning to adulthood (Carter, Lane, Pierson, & Glaeser, 2006). Self-determination includes the ability to identify strengths and interests, advocate for oneself (connected to the ability to interact with others [i.e., social skills]), set goals, and evaluate progress in achieving goals (Carter, Trainor, Owens, Swedeen, & Sun, 2010). Therefore, a comprehensive transition program for students with EBD would encompass the development of job skills, self-determination, and social and life skills.
School counselors are crucial in helping develop and implement programs that assist students with transitioning to adulthood. Counselors have an understanding of the developmental needs of students (Granello & Sears, 1999). This knowledge is essential in establishing a successful program. Additionally, school counselors develop and facilitate initiatives within comprehensive school counseling programs guided by the American School Counselor Association (ASCA, 2012) National Model and the ASCA (2004) National Standards for Students, which emphasize academic, career, and social and personal development. Furthermore, in program development, the counselor is instrumental in coordinating school personnel (teachers, administrators and support staff) and community partners to work toward helping students transition successfully.
A clear need exists for the development of programs for high school students with EBD to facilitate skill development that assists them with successfully transitioning to adulthood. In this article, we, the authors, outline initiatives developed to address this need. We discuss program goals, sustainability, and some preliminary findings regarding program effectiveness.
An Innovative School Program
The second author is a school counselor at a Title I school serving K–12 students who are identified as ESE/EBD (Exceptional Student Education with Emotional and Behavioral Disabilities). This tier three school offers special education interventions for the most severe students with ESE/EBD residing in the county. The student population is approximately 70% African American, 29% Caucasian and 1% Hispanic. Eighty-four percent of the students are male and 26% are female. Additionally, 95% of the students receive free or reduced lunch. Most students reside in single-parent homes and many have been “sheltered” as wards of the state, with several students having “relative caregivers.” Twelve percent of the students are currently in foster care or group homes and 13% have been adopted out of foster care. Approximately 4%– 9% of the students are considered homeless under the McKinnley-Vento Act.
During the past five years, the second author has observed the transitional difficulties of students. The observations mirror the research on the transition of students identified as ESE/EBD. The students lack social and vocational skills, and exhibit psychological symptoms consistent with their disabilities. The majority of students drop out of school, and many have arrest records and often reoffend after they leave school. A limited number of these students have jobs or are attending general education programs (GED), some are homeless, and some have reported suicidal ideation and suicide attempts. These transitional realities have motivated personnel to brainstorm strategies to address the educational, vocational and transitional needs of students, in hope of preventing current and future students from experiencing the same dismal transition.
The program initiatives were designed to help students (a) learn job skills and obtain vocational education, (b) promote social skills, (c) foster self-determination, and (d) develop life skills. Each of these goals is an in-school predictor of post-high school success identified by Test et al. (2009). After establishing the program goals, the school counselor identified areas of interest within the student body, in order to obtain the students’ interest in the program. Furthermore, the school counselor identified resources to obtain funding and support. Each component of the program was started with seed money provided through small grants. However, after each program component was initiated, it was necessary to develop a plan to sustain the project due to the lack of ongoing funding. Thus, a sustainability plan was integrated within the program initiatives.
The four program initiatives include (a) a school vegetable garden, (b) a raised worm bed, (c) sewing for success, and (d) community collaboration. The program is grounded within two established transitional models discussed by Rutkowski, Daston, VanKuiken, and Riehle (2006). Both models emphasize hands-on experience in developing job skills. The first three program components use the adapted career and technical model framework, which provides both a simulated and real worksite model. This model provides students with the opportunity to develop job skills and obtain work experience, while having the direct support of school personnel. The fourth program component is grounded within the work-study model. Within this framework, students receive instruction in the school and then enter the community to obtain work experience. The program encompasses both models to allow students to transition from the adapted career and technical model to the work-study model after they have developed the skills and experience to help them be successful in community employment.
Creating a program that encompasses both models has several advantages. First, students gradually increase their exposure to work. This approach may decrease anxiety and encourage students to try new things because they are initially surrounded by school personnel who are encouraging and supportive during this process. Additionally, the school establishes strong collaborations with community partners and increases the potential for student success by first training students in the school. Thus, the school establishes a system that promotes success for the students, the school and community partners.
School vegetable garden. The first initiative developed was the school vegetable garden. The garden is designed to provide high school students with experiences to develop immediate employment-related skills on campus through engagement in all aspects of planning, maintaining and harvesting a garden. Students develop skills in preparing the soil, planning for and selecting types of plants to grow, planting and caring for plants, and harvesting and selling the produce. The garden project allows school personnel to teach and reinforce several work-related skills. Students learn responsibility through their daily commitment to the garden, which has tangible consequences if not attended to on a regular basis (e.g., plants dying, garden becoming overgrown with weeds, produce rotting). The commitment required for the garden is directly related to employee responsibilities (e.g., arriving at work on time, completing tasks consistently to the best of one’s ability). Additionally, students develop social skills through collaboration to maintain the garden, working as team members as if for an employer. Students also obtain life skills (e.g., problem solving) by addressing various issues within the garden (e.g., insects eating the plants, weather conditions) and managing finances through the generation of funds (by selling produce) to sustain the garden. Furthermore, students learn customer service skills through interactions with customers when selling produce. Finally, students develop self-determination skills by identifying strengths in managing the garden and evaluating their progress. Thus, the garden initiative provides opportunities for students to develop skills in each of the areas outlined for the program: job skills and vocational education, social skills, life skills and self-determination.
The garden also provides a metaphor for students’ personal growth and development, as well as opportunities to promote students’ successes. For example, school counselors can discuss the importance of having nutrient-rich soil to build a foundation for growing healthy, hearty plants, and then connect this metaphor to specific areas within the students’ lives where they are developing a solid foundation for their lives. School personnel also encourage students and promote positive self-esteem by identifying students’ garden accomplishments. The garden produces tangible results through vegetable growth, and students are able to recognize concrete outcomes throughout their ongoing garden experience. Thus, the initiative provides opportunities for students to develop self-awareness and foster a healthy self-concept.
Raised worm bed. The worm bed was developed to provide direct benefits to the vegetable garden and the sustainability of the program. Additionally, students expressed interest in this project. The worm bed promotes sustainability of the garden by providing needed compost (casings). Additionally, students can sell the earthworms, providing financial assistance for the program. The costs of developing the worm garden are minimized by having students develop the beds, which support the development of job skills and vocational training through planning, designing and construction. Likewise, the construction of the worm beds fosters the development of social skills and life skills through teamwork, problem solving and financial management (e.g., maximizing the resources available).
Sewing for success. The program experienced an increase in the number of female students, and efforts to have them work in the garden were often met with resistance. The sewing initiative was designed to capture the interest of female students. However, male students also showed an interest in the sewing initiative. This project was combined with a project to support the school’s clothing bank (sorting, laundering and repairing clothes), which was established by the school to provide clothing to students in need. The school accepts donations from the community and maintains the clothing bank for students.
Maintaining the clothing bank helps students develop life skills as they learn how to do laundry and repair clothes. Students also develop organizational skills. In addition to maintaining the clothing bank, students create sewing products that they sell (e.g., bags, purses, scarves), which supports the development of job skills (sewing) and life skills (customer service). The school staff reported that a majority of the students, both female and male, express enjoyment with this initiative. Some students reported that the program is more relevant for them, while others reported that it complements the garden, especially on days with inclement weather. Thus, the sewing initiative has enhanced the other initiatives encompassed within the program.
Community collaboration. Researchers emphasize the importance of community partnerships in developing transition programs (Lehman et al., 2002). Active engagement with community resources promotes opportunities to continue to learn pro-social behaviors and work skills, vocational education and aptitude beyond the school. This initiative—grounded within the work-study model—provides opportunities for community work experience while maintaining school support. Students also have the opportunity to pursue an Option 2 diploma, which requires work placement in an on-the-job training or community-based training experience for at least six months. Placement sites have included garden centers, fast-food restaurants and grocery stores.
Community partnerships provide great opportunities for students; however, establishing placements that are a good fit for the student and the business is a vital and crucial consideration. Employers are often not equipped to provide training and supervision to support the students’ needs, given the nature of their disabilities and the relative instability of their living situations. Other limiting issues include the number of work hours available and transportation needs for the students. Thus, these experiences require continuous efforts in locating, developing and maintaining work placements. Furthermore, the program must adequately prepare the students for placements and provide ongoing support for the students and their employers.
Implications for School Counselors
The on-campus experiences provide opportunities for school counselors and teachers to work together to support students in developing work aptitude, as well as emotional regulation and self-control. Successful program completion leads to eligibility for pursuit of an Option 2 diploma. The initiatives also foster patience and persistence since maintenance of the garden is required while the crops are growing and other projects must be completed. Through this experience, students learn that rewards are not always instant and that time and hard work is necessary if one is to accomplish goals. Such awareness may serve to support a successful transition to work in the community upon program completion. Developing general work skills, a strong work ethic and social skills may assist individuals with obtaining jobs in various areas following high school.
The program supports academic learning by providing a link between practical career preparation and education. Science and math lessons, in accordance with state educational standards, are developed for middle and high school students. These lessons emphasize real-life educational experiences. The lessons focus on career awareness while supporting education and the transitional goals of the program. Students also learn important sequencing skills working in the garden that carry over to classroom learning. Further, the program supports the development of social skills and self-determination skills. Students learn to work together cooperatively and practice interacting with others when selling the garden produce, sewing products and earthworms. Additionally, the students have the opportunity to identify their interests, recognize their strengths, and evaluate their goals. Opportunities to experience success in both an educational and work setting support the development of a healthy self-esteem. Finally, the program fosters life skill development through budget planning and use of available monies. Thus, the initiatives are integral to the work of both the school counselor in facilitating a comprehensive school counseling program (ASCA, 2012) and the teacher in teaching academic subjects.
In addition to the program students, the greater school community, including the student body and staff, benefit because the vegetable and worm gardens are visible for the entire school community. Teachers can use the garden as a reference point to educate all students about plant growth and biological systems. The clothing bank provides a service to help meet the basic needs of all students. It also offers the opportunity for increased empathy and the intrinsic satisfaction of helping others through civic involvement. Furthermore, the program promotes a positive atmosphere for growth and development, which may foster excitement about learning. The program, through a focus on a positive, collaborative learning atmosphere, has the potential to nurture excitement about active learning and dedicated participation in one’s own learning.
The community also benefits from the program. Most importantly, student success may lead to the future integration of productive citizens into the community. By producing products specifically for the immediate community market, students develop a sense of community ownership and support for the program. Likewise, community partners have the opportunity to expand their workforce without incurring tremendous training expenses, while receiving continued management support from school personnel.
Despite the program benefits, there are also challenges. Program sustainability is an ongoing challenge that has intensified with budget cuts. The program initiatives were initially grant funded; however, the grants did not provide funding for sustainability. To address the challenges, the program formed an advisory board composed of school personnel, students and community partners who defined the priorities of the program, provided oversight, and reported progress to the School Advisory Committee. The board was instrumental in brainstorming and implementing sustainability strategies. At the board’s suggestion, students began marketing products grown and created through the program as a way to generate program funds. Another strategy involved obtaining additional grant funding to construct a tool shed, irrigation system and greenhouse. A greenhouse allows for starter plant production and reduces vegetable garden costs. The starter plants, when sold as another program product, generate additional income. Furthermore, the board sought to develop strong collaborations within the community to obtain donations and support. As another way to develop strong community–program collaboration, the board opted to solicit funds from the surrounding community.
Students identified as ESE/EBD, by the nature of their disability, are presented with challenges. While on campus, the program uses the school’s behavioral supports and interventions such as point sheets and rewards for appropriate behaviors. In addition, students have opportunities to process their experiences with the school counselor and other staff. These interventions reinforce appropriate pro-social behavior supportive of job skill development and aptitude. Additionally, the point system provides data to measure a student’s readiness to transition to an Option 2 diploma, or postgraduation education and/or vocational training (e.g., Job Corp).
Conversely, the supports, rewards, and interventions are different within the community placement sites, creating a challenge for students transitioning to work outside the campus environment. However, students do experience job site support and reinforcement as they “prove” themselves at the worksites. This real-world treatment thus encourages development of transition strategies to use following the completion of high school.
A perennial challenge encompasses obtaining adequate funding to sustain the initiatives. Adequate financial support is needed in order to offer a stipend to students working on campus. This is an incentive for students and supports efforts to adequately prepare them for community work placements. In spite of funding fluctuations, a dedicated effort is made for successful work placement and maintenance of incentives to reward appropriate skill development and job success.
Although the program has experienced challenges and is relatively small (enrolling 10–15 students each year), some preliminary success has been identified within the program. Within the past school year, the program doubled the number of graduates. Additionally, the program had three students re-enroll who had previously withdrawn, one of the three graduating at the end of the school year. No students withdrew from the program during the year, and behavioral referrals were down 50% while students’ grade point average (GPA) increased by 0.17 points. Furthermore, students reported that they enjoyed the program and the job training experience. Some students stated that they would have dropped out of school if it were not for the program initiatives. Thus, the program appears to be promising in addressing counseling and academic goals. However, future research is needed to further examine the effectiveness of the program. Future research may include collecting pre/post data, further exploring perceptions (e.g., students, parents, school staff, community employers) about the program, and examining the longitudinal effects of the program.
In conclusion, IDEA (2004) requires schools to create transition plans for students with disabilities; however, Sabbatino and Macrine (2007) emphasize that this is not sufficient to promote a successful transition to adulthood. Therefore, programs are needed to promote the success of students with ESE/EBD. The design and implementation of programs requires collaboration between school counselors, teachers, administrators, support staff, students, families and community stakeholders. Additionally, program implementation requires time, funding and other resources. Despite these challenges, researchers have indicated that focusing on crucial in-school predictors may lead to success following high school (Test et al., 2009). Thus, this article presents a promising program for working with students with ESE/EBD. However, future research is needed to examine the initiatives presented in this article and determine how they might be used to help students become productive citizens.
American School Counselor Association. (2004). ASCA National Standards for Students. Alexandria, VA: Author.
American School Counselor Association. (2012). The ASCA National Model: A framework for school counseling
programs (3rd ed.). Alexandria, VA: Author.
Aseltine, R. H. Jr., & Gore, S. (2005). Work, postsecondary education, and psychological functioning following the
transition from high school. Journal of Adolescent Research. 20(6), 615–639. doi: 10.1177/0743558405279360
Burgstahler, S. (2001). A collaborative model to promote career success for students with disabilities. Journal of Vocational Rehabilitation, 16, 209–215.
Cameto, R., Wagner, M., Newman, L., Blackorby, J., & Javitz, H. (2000). National Longitudinal Transition Study II (NLTS2). Menlo Park, CA: SRI International. Retrieved from http://www.nlts2.org/studymeth/nlts2_sampling_plan2.pdf
Carran, D., Kerins, M., & Murray, S. (2005). Three-year outcomes from positively and negatively discharged EDB students from nonpublic special education facilities. Behavioral Disorders, 30, 119–134. Retrieved
Carter, E. W., Lane, K. L., Pierson, M. R., & Glaeser, B. (2006). Self-determination skills and opportunities of transition-age youth with emotional disturbance and learning disabilities. Exceptional Children, 72, 333–346.
Carter, E. W., Trainor, A. A., Ditchman, N., & Owens, L. (2011). A pilot study connecting youth with emotional or behavioral difficulties to summer work experiences. Career Development for Exceptional Individuals,
34(2), 95–106. doi: 10.1177/0885728810395745
Carter, E. W., Trainor, A. A., Owens, L., Swedeen, B., & Sun, Y. (2010). Self-determination prospects of youth with high-incidence disabilities: Divergent perspectives and related factors. Journal of Emotional and Behavioral Disorders, 18(2), 67–81. doi: 10.1177/1063426609332605
Exceptional Student Education Eligibility for Students with Emotional/Behavioral Disabilities, F.A.C. §§ 6A-6.03016 (2009).
Gore, S., Kadish, S., & Aseltine, R. H. Jr. (2003). Career centered high school education and post-high school career adaptation. American Journal of Community Psychology, 32, 77–88.
Granello, D., & Sears, S. (1999). The School to Work Opportunities Act and the role of the school counselor. Professional School Counseling, 3, 108–115.
Individuals With Disabilities Education Act Amendments of 1997, 20 U.S.C. § 1400 et seq. (1997).
Individuals With Disabilities Education Act of 2004, 20 U.S.C. §1400 et seq. (2004).
Lehman, C. M., Clark, H. B., Bullis, M., Rinkin, J., & Castellanos, L. A. (2002). Transition from school to adult life: Empowering youth through community ownership and accountability. Journal of Child and Family Studies, 11(1), 127–141. doi:10.1023/A:1014727930549
Rutkowski, S., Daston, M., Van Kuiken, D., & Riehle, E. (2006). Project SEARCH: A demand-side model of high school transition. Journal of Vocational Rehabilitation, 25, 85–96. Retrieved from: http://www.iospress.nl/journal/journal-of-vocational-rehabilitation
Sabbatino, E. D., & Macrine, S. L. (2007). Start on success: A model transition program for high school students with disabilities. Preventing School Failure: Alternative Education for Children and Youth, 52, 33–39. doi:10.3200/PSFL.52.1.33-40
Test, D. W., Mazzotti, V. L., Mustian, A. L., Fowler, C. H., Kortering, L., & Kohler, P. (2009). Evidence-based secondary transition predictors for improving postschool outcomes for students with disabilities. Career Development for Exceptional Individuals, 32(3), 160–181. doi: 10.1177/0885728809346960
Wagner, M., Newman, L., Cameto, R., Levine, P., & Garza, N. (2006). An overview of findings from wave 2 of the National Longitudinal Transition Study-2 (NLTS2). Menlo Park, CA: SRI International. Retrieved from http://www.nlts2.org/reports/2006_08/nlts2_report_2006_08_complete.pdf
Zigmond, N. (2006). Twenty-four months after high school: Paths taken by youth diagnosed with severe emotional and behavioral disorders. Journal of Emotional and Behavioral Disorders, 14(2), 99–107. doi:10.1177/10634266060140020601
Jacqueline M. Swank is an Assistant Professor in the College of Education at the University of Florida. Peter Huber is a school counselor at the A. Quinn Jones Exceptional Student Center, Alachua County Public Schools, Gainesville, FL. Correspondence can be addressed to Jacqueline M. Swank, University of Florida, College of Education, SHDOSE, 1215 Norman Hall, P.O. Box 117049, Gainesville, FL 32611, email@example.com.
Vivian H. Wright, Joy J. Burnham
This study sought to develop meaningful and engaging virtual cyberbullying scenarios in digital environments that reflect the educational needs of today’s adolescents. In order to inform and script these scenarios, a three-stage study was implemented with middle schools. This paper describes how data collected in each stage informed the cyberbullying scenarios’ development. The authors share implications for educational use in middle school counseling.
Keywords: cyberbullying, technology, adolescents, middle school counseling, digital environments
Today’s adolescents are often referred to as the Net Generation (Tapscott, 1998) because they communicate with each other through a multitude of digital and electronic technologies, including the Internet, social networking tools (e.g., Twitter, Facebook, MySpace), cell phones, and online games. Because these digital and electronic tools function as the “lifeline to their peer group” (Keith & Martin, 2005, p. 226), adults can underestimate the importance of technology to adolescents. While the expansion and availability of technology offer many positive benefits to our youth (e.g., educational and social benefits), access to the Internet and mobile technologies have the potential to render negative effects, including increased incidences of cyberbullying.
Cyberbullying is a form of bullying, yet unlike the traditional schoolyard bully, the cyberbully lurks in online spaces, often unseen and anonymous. Cyberbullies misuse technology (e.g., they impersonate others, share embarrassing information and photos, threaten, gossip, and fight online) (Willard, 2006). With the use of technology, the cyber landscape has expanded into easy and continuous access, and is described as operating like “the Wild West once did, where anything goes” (Hoff & Mitchell, 2009, p. 661). In this light, youth can engage in computer-related activities without boundaries or parental supervision.
While negative assertions about technology are disconcerting and cannot be ignored, online and mobile technologies continue to evolve and present positive and beneficial ways to teach the students of today and tomorrow. With the value of technologies in mind, the obstacles in cyberspace and the virtual world need to be addressed. Thus, for teachers, principals, and school counselors, an overarching challenge is presented by such questions as: (1) How do we teach students to protect themselves in digital environments and prevent negative interactions such as cyberbullying? and (2) How can technology be used as a vehicle to educate adolescents and to raise their awareness of cyberbullying?
The purposes of this study were threefold: (1) to use adolescent feedback to script and create cyberbullying video scenarios in a safe, virtual environment; (2) to offer free access to the videos for educational use; and, (3) to raise awareness of cyberbullying and to underline the need for prevention. This study focused on middle school students because the literature has shown a peak in cyberbullying during these school years (Beale & Hall, 2007; Cassidy, Jackson, & Brown, 2009; Hinduja & Patchin, 2008; Kowalski & Limber, 2007; Li, 2007; Pelligrini & Bartini, 2000; Williams & Guerra, 2007). Because few studies have recreated cyberbullying situations, assessing the effectiveness of such scenarios in the field of education is important. Addressing this gap can provide valuable, alternative educational methods to school counselors and other mental health professionals, as well as parents, school administrators and teachers (Carney, 2008; Wright, Burnham, Inman, & Ogorchock, 2009).
Review of the Literature
Virtual worlds, digital videos, and gaming can supplement education, making concepts that are abstract or difficult to understand interesting, relevant, and concrete through modeling and interaction (Williamson & Facer, 2004). Virtual technologies also provide students with a safe place that replicates the real world, allowing for ongoing educational interactions (Paperny & Starn, 1989). Yet, research on the use of virtual worlds, digital videos, and gaming to teach adolescents about cyberbullying is limited (Wright et al., 2009), even though technology has been effectively used to teach skills and train youth.
Several published studies have illustrated the value of virtual technology. For example, Cobb et al. (2002) reported that completing tasks in a virtual social café helped adolescents and adults with Asperger’s syndrome improve their social skills. Similarly, Padgett, Strickland, and Coles (2006) reported success in using a virtual reality game to teach five children with fetal alcohol syndrome fire safety skills. In another study, Amon and Campbell (2008) used a virtual game to teach relaxation skills to children with attention-deficit/hyperactivity disorder (AD/HD). Researchers also have reported success in using virtual scenarios and simulations to raise awareness of concepts, including the development of professional skills in teacher education graduate programs (Collins, Cook-Cottone, Robinson, & Sullivan, 2004), improving attitudes for decreasing teenage pregnancy (Paperny & Starn, 1989) and coping with fears such as public speaking (Slater, Pertaub, & Steed, 1999) and flying (Krijn et al., 2007).
Using a Virtual Environment to Create Cyberbullying Scenarios
The virtual world environment was chosen for this study because of a significant need to provide access to factual and authentic cyberbullying scenarios in an environment that was safe and one that would not compromise the well-being, psychological health, or rights of youth. Studies have suggested that using a virtual environment can be a valuable and safer alternative for conducting research (Zoll, Enz, Schaub, Aylett, & Paiva, 2006) and may make collecting sensitive data more appealing in educational research. Further, researchers have reported that interactions in virtual environments “are governed by the same social norms as social interactions in the physical world” (Yee, Bailenson, Urbanek, Chang, & Merget, 2007, p. 119), making it possible to compare the virtual interactions with interactions in the real world. Finally, adolescents are often motivated to learn about issues and concepts through video or computer games rather than through traditional instructional methods (Ritterfeld & Weber, 2006). With these factors in mind, we reiterated an interest in using virtual world scenarios to raise awareness of cyberbullying and to simultaneously offer an “attractive, but also a potentially powerful means of getting the attention of adolescents” (Wright et al., 2009, p. 40). Having cyberbullying videos to prompt discussion among youth offers school counselors, as well as classroom teachers, additional ways to deal with the challenges they face with cyberbullying.
Choosing Second Life
Second Life (SL) was chosen as the virtual environment for this current study because it “dominates the virtual world landscape” (Warburton, 2009, p. 423) in education. Linden Lab launched SL in 2003. The immersive, three-dimensional (3-D) virtual environment of SL offers users an opportunity to create or re-create situations, interactions and experiences through the use of avatars, which are animated figures that represent real people. Complete communities, schools and businesses have been recreated in SL. Although educators have benefited from specific Linden Lab invitations to explore SL for teaching, learning and research (O’Conner & Sakshaug, 2009), SL and other virtual communities (e.g., Active Worlds, WebKinz) are considered new innovations on the technological landscape. In recent years, researchers have collected anecdotal and empirical data related to virtual environments including potential uses and effectiveness in role-play and student-centered learning (Inman, Wright, & Hartman, 2010).
Second Life Challenges
Second Life offers users the ability to create virtual content that replicates the real world, truly providing a “second life” (hence, the name). However, creation within SL is not without its challenges (O’Conner & Sakshaug, 2009). The challenges often faced with SL are multifaceted. First and foremost, there is a learning curve for a developer to overcome before creating objects and simulations within the SL environment (Luo & Kemp, 2008; O’Conner & Sakshaug, 2009). Warburton (2009) noted that “even simple things can take a long time” and may require “multiple skills” (p. 423). Furthermore, SL computing requirements are high; if developers are not using high-capacity computers (e.g., fast processors, graphics cards) and broadband Internet (e.g., cable or DSL connections or faster), they could experience difficulty with such problems as operating the SL software, intermittent freezes, and software system failure. Institutional financial support of SL-designed environments is advantageous, although not always available.
With the need for virtual environment scenarios to combat cyberbullying, this study included three stages of data collection with middle school students in one school district in the southeast. Data from the first two stages (i.e., a quantitative cyberbullying survey and a focus group, respectively) informed the scripts of the cyberbullying scenarios produced from this present study. The goal for each scenario was to most accurately reflect the students’ beliefs about and experiences in cyberbullying and address their perceived needs for cyberbullying education and prevention. The present study included the following steps: (1) scripting and building the cyberbullying scenarios, (2) using screen-capturing software to capture the videos, and (3) saving the videos as separate files. By following this plan, the researchers maintained a “safe” environment for the students by screen-capturing the scenarios created in SL, thus preventing the students’ need to go online to view the scenarios.
After Institutional Review Board (IRB) and school system approval, the researchers worked with five middle school principals to conduct this study. Approximately 450 middle school students in Grades 7 and 8 (ages 12–14) were invited to participate in the quantitative study, which was the first stage of data collection. Of the invited students, 114 returned signed parental informed consents and assented to take part in the study. Of the 114 students, 50 were male and 64 were female; 73 were in 8th Grade, with the remaining participants in 7th Grade. The racial backgrounds included: 33 White students, 67 African-American students, 3 Hispanic/Latino students, 2 Asian-American students, and 9 who did not identify their racial background.
At the end of the survey, the respondents indicated a willingness to participate in subsequent stages of the study. From these, the researchers recruited a convenience sample of 20 students from two of the five middle schools (one high-poverty school; one low-poverty school) to participate in the qualitative study, stage two of our data collection. Of the invited, 13 students participated from two schools. School A included seven students (4 boys, 3 girls) and racial backgrounds were: 1 White student, 5 African-American students, and 1 Hispanic student. School B included six students (4 boys, 2 girls) and racial backgrounds were: 4 White students and 2 African-American students.
Lastly, two 8th Grade students (1 White male and 1 White female) who indicated willingness to participate in all stages of the study were recruited to view the pilot cyberbullying scenarios, which were scripted and informed by data collected in the first two stages of this research study. Both students viewed the scenarios individually and provided feedback to assist with final editing of the videos.
For the first stage of the study, the researchers were given permission to adapt Li’s (2007) Cyberbullying Survey. Data included middle school students’ responses to various cyberbullying questions (e.g., “Have you been cyberbullied?” “Do you know a cyberbully?” and “Where did cyberbullying most often occur?”). Contextual examples were given in each question, such as for “have you been cyberbullied?” examples included e-mail, Facebook, cell phone, online video, chat rooms, and virtual games.
For the focus group stage, facilitators generated discussions between the participants about how they recognized, defined and responded to cyberbullying. For example, questions included: “If you or someone you know have been cyberbullied, how have you/they been cyberbullied?” “What did you/they do immediately after you/they were cyberbullied?” “Did you/they tell someone? Retaliate online?” After this stage, cyberbullying scenarios were developed based on the data gathered from this aspect of the study.
Following the development of the cyberbullying scenarios, the researchers sought to record participants’ reactions and comments as they watched the two video scenarios created as a result of data collected in the first two stages of data collection. Following the participants’ individual viewing of the scenarios, the researchers also asked specific questions (e.g., scenarios’ clarity, misinterpretations experienced, the setting of the scenarios, and perceived value of the scenarios in cyberbullying education for middle school students).
The researchers worked at a major university in the southeastern U.S. where an effort to develop a teaching and research presence within SL was ongoing. The College of Education at the institution had “land” within SL and developed teaching and research spaces within the virtual environment. Several of the university’s computer-based honors students were involved in this development and partnered with university professors to conduct research while simultaneously receiving college credit. The researchers were assigned two honor students who were asked to develop counseling-related scenarios in SL.
To ensure cultural sensitivity, the researchers also consulted with an African-American colleague who works with high- poverty schools. Feedback from the colleague was sought to determine whether or not the language and scenarios were realistic and applicable. In addition, after the SL developers rendered the videos, two additional colleagues (a counselor with expertise in multicultural education and an instructional technology expert) reviewed the videos. These discussions helped to validate the scripting choices and ensure appropriateness and cultural sensitivity for use with middle school students.
The researchers triangulated the focus group and survey data (Stages I and II) to inform the development of the cyberbullying scenarios and to script the two scenarios. In order to achieve meaningful scenarios that reflected the educational needs of the adolescents, we drew heavily upon data from the focus groups to ensure that the scenarios reflected the students’ voices (e.g., language use), their actions (e.g., reactions to cyberbullying situations, linguistics), and the technologies they most used (e.g., social networking) while also providing the needed educational messages.
The data revealed a need for two separate scenarios (i.e., one with a behaviorally-based concept and one with an educational concept). Informed through the focus group data, the behaviorally-based scenario focused on “how gossip escalated into cyberbullying” as two girls wrote on each other’s “wall” on Facebook. Data from the first two stages of data collection indicated a need for adults and educators to better understand how to educate and raise awareness of cyberbullying prevention; therefore, the educationally-based scenario focused on a discussion between a school counselor and a middle school-aged boy who sought advice on how to cope with an online joke that “got out of hand” or escalated.
Once the two scenarios were completed and the videos rendered, we recruited two 8th Grade participants (one male, one female) from the pool of middle school students to participate in the current study. The participants viewed the videos in the presence of two faculty members and one graduate student. The researchers examined the students’ reactions and nonverbal behaviors as they viewed the scenarios. Following each student’s viewing, they were asked specific questions regarding the scenario’s clarity, its setting, the length, and any misinterpretations the students might have about each scenario.
Scenario I, “Mark Goes to the Counselor,” was the educationally-based video (i.e., the school counselor listens to a student regarding a Facebook joke that escalated into a problem). Based on focus group feedback from adolescents, this educational scenario fulfilled a need for adults and counselors to be more aware of how to prevent cyberbullying.
While the students viewed “Mark Goes to the Counselor,” they pointed out minor problems with the rendered scenario. For example, the male participant (Rick) was distracted by the avatar’s movements. He stated that the counselor’s hand movements were “awkward.” Rick’s other major concern had to do with the buildings in the scenario, noting that they “looked too academic” as compared to a middle school setting. The female participant (Bridget) was not as distracted by the avatar’s movements. She noted that the scenario seemed “realistic” to her. From the researchers’ observations, the scenario engaged the participants. In the ensuing discussions following the scenario, both students noted the educational value of the scenario for their peers.
Because “Mark Goes to the Counselor” had an interactive segment at the end which posed questions related to cyberbullying, the students also critiqued this part of the video. Reponses from both students included information about the appropriateness and usefulness of the questions. The students believed that the questions would generate discussions about cyberbullying prevention and how to “deal with it (cyberbullying).”
Data also informed the scripting of second scenario, “Aisha and LaTosha on Facebook.” This behaviorally-based scenario focused on two adolescent African-American girls who were involved in online gossiping (via Facebook) which quickly escalated into a cyberbullying incident. The social network, Facebook, was chosen for this scenario because it is recognized as the most popular social networking medium (see online data collection venues which monitor web traffic such as Nielsen, Compete, ComScore, and others) and remains popular among adolescents.
For this scenario, capturing the texting exchange between the girls was important to illustrate how the gossip escalated. However, a texting exchange presented problems for the scenarios’ developers. Basically, the initial text messaging exchange that was sought for the “Aisha and LaTosha on Facebook” video was illegible and difficult to understand on the first attempt. Thus, the scenario had to be reworked prior to the students’ viewing.
About two months later, the same male and female participants (n = 2) agreed to critique the second video. While viewing “Aisha and LaTosha on Facebook” on a laptop, the male participant (Rick) paused the video frequently, pointing out technical issues he noticed. For example, a few seconds into viewing he commented on “bad timing” between the sound of the avatars’ typing and the typing movements the girls made on the computers. Moments later, he paused again, this time pointing to a cursor which was located over the text. He noted how difficult it was to read one of the girl’s texts as she posted on the Facebook wall. Rick also believed that some of the text and punctuation was “too grammatically correct.” He remarked, “teens don’t use that” giving a specific example of using a “w” with a slash (/) mark (w/) versus typing the word “with” and that teenagers use “u” for you. He stated that we should make the “grammar more teen-like.” Rick also commented that it would be more likely for the two girls to have this type of conversation (i.e., depicted in the scenario) in “chat” versus “posting on each other’s wall in Facebook.”
Another video quality issue was resolved with participant feedback. While the second scenario was written to focus on the conversation of two girls and their gossip, a third girl (Sierra) also was present at the beginning of the scenario. Rick believed that Sierra’s presence was confusing and thought she should be removed.
Upon completion of the video, Rick had additional comments regarding the actual scenario production. After viewing, we asked if Rick believed the scenario made sense. He said “yes” and that he could “follow along.” We also asked Rick what message he received from the scenario. This question caused him some difficulty and after being prompted a second time, he stated that the scenario depicted how “gossip starts” and illustrated how students should not “jump to conclusions so quickly.” Lastly, we asked Rick his opinion regarding our choice to use Facebook in the scenario versus other social networking sites. Rick emphatically agreed that Facebook was the right choice. He stated, “…no one uses MySpace anymore.”
Bridget, also in 8th grade, watched most of the video without conversation. She had one comment while viewing the “Aisha and LaTosha on Facebook” video, but waited until viewing the video completely before making additional comments. Her initial comment concerned a portion of the script in which one of the girls threatened to get some people together to “jump you.” Bridget laughed quietly as she viewed that portion of the video and remarked, “I’ve heard people say that.” Bridget focused less on the technology in her analysis; however, she did comment that at times the video was “a little blurry” and that the avatars’ movements were “a little fakish.” She also put forth the idea that the video needed a transition at the end (i.e., the first version of the video ended abruptly).
Bridget inquired about how we came up with the idea and thought it was “neat.” Similar to Rick, Bridget also struggled to answer the question: “What was the message in this video?” Once more, we asked a series of questions before an answer was given. After several prompts, Bridget stated, “…students should not accuse people of stuff.” We also asked, would this scenario prompt you to discuss cyberbullying? She noted “maybe.” We asked, “Can teachers and/or counselors successfully use this scenario in a group setting with middle school students to discuss cyberbullying?” She answered “yes” and that the scenario seemed “realistic.” Bridget believed the scenario would be very helpful in education because acting it out in person “would be awkward.” She stated that this video “… has elements in it that kids see all the time.” When asked about technological distractions in the video, Bridget indicated that the television in the video needed a better screen, (i.e., “something natural on it”) and it would be nice to have some music in the background for the two girls.
The two students had some level of disagreement in their critiques. Unlike Rick, who indicated that the scenario was more appropriate for 6th grade, Bridget believed that it “sounded like an 8th grade conversation and would probably be good for 7th graders, but “6th graders talk differently.” Bridget also liked the wall-to-wall design in Facebook and did not agree with Rick that the girls’ conversation should occur, instead, through the Facebook chat tool. The way the text was typed was also okay with Bridget; although she noted how she “typed nicely.” Further, the appearance of Facebook was fine with her, and she believed that the attire on the girls was appropriate. She was in agreement with Rick about removing the girl, Sierra, from the video. Both saw her presence as confusing. She also aligned with Rick on the view that “all students used Facebook instead of MySpace.”
From this session, it was apparent that revisions were necessary with the “Aisha and LaTosha on Facebook” scenario. While Rick and Bridget affirmed that the scenario was realistic, when the video ended both were unclear of the overall message of the video (i.e., they needed prompting twice to articulate the message of the video). The interactions with the two middle school students made it clear that some questions added to the video would facilitate interactive discussions among youth. We discussed potential questions with both students. By incorporating the language from the data and student input after watching the videos, we developed the following questions: (1) Whose fault was this fight? (2) If someone is mean to you and spreading rumors, what could you do instead of doing what Aisha and LaTosha did? (3) How would you respond to Aisha? (4) When should you get an adult involved? Who can you turn to for help? And, (5) What are some other steps you could take to make sure this type of situation doesn’t happen to you?
After Rick and Bridget reviewed the video, a list of technical changes for the developers to make on the “Aisha and LaTosha on Facebook” scenario was assembled. They included:
1. Review the punctuation and grammar; make some modifications to better fit with punctuation and grammar that teens do and do not use. (Although the script was initially written using actual statements from adolescents who participated in our focus groups, we realized additional modifications could be made, such as using “w/” instead of with and “u” for you).
2. Revise the first part of the script, eliminating the character, Sierra.
3. The avatars frequently correct typing errors; change this to ensure that the typing text is more “teen-like” and less concerned with spelling errors.
4. Add questions at the end of the video for class or one-on-one discussions (i.e., an educational component for teachers and counselors).
5. Add music to the background at Aisha and LaTosha’s homes.
6. Put a realistic scene on the television.
7. Add a transition at the end; the scenario ended too abruptly—fade to black at the end and then bring up the questions.
The participants also discussed how the argument between Aisha and LaTosha should take place (i.e., via Facebook chat or “wall-to-wall”). While Rick seemed adamant about using chat features of Facebook, Bridget was not as concerned, believing that similar conversations do take place wall-to-wall. After much discussion, we decided to keep the text interaction between the two girls as wall-to-wall postings since the production in the virtual world would be clearer to read, based on previous problems experienced by the developers.
As noted earlier, cyberbullying is a growing concern for today’s adolescents. The purpose of this study was to use data to inform the scripting of two counseling scenarios that could be used for cyberbullying prevention with middle school students. Using a virtual environment to “act out” the scripts and later capturing the scenarios for off-line viewing was intentional and purposeful. While research on using virtual environments to teach cyberbullying prevention is limited (Wright et al., 2009), the use of virtual worlds to teach other skills and concepts has been successful (Amon & Campbell, 2008; Cobb et al., 2002). Further, using virtual worlds can offer a safe place to conduct scenarios of sensitive content (such as cyberbullying) (Zoll et al., 2006) while allowing for real world replications that can be engaging (Paperny & Starn, 1989). Thus, the intent of developing the scenarios was to provide a safe, alternative educational method for counselors and other helping professionals, as well as parents, to use in cyberbullying education and prevention, while assuring that the well-being and rights of youth are upheld.
There were limitations to this study. First, this study focused on one school system in one state, thus generalizability to other middle schools is questionable. Second, video feedback from a more diverse population of students (e.g., African-American girl, feedback from 6th and 7th grade students) would have been helpful.
The data informed our production and scripting, thus allowing the students’ voices to emerge in these scenarios. We believe reflecting the students’ voices, their actions, and the technologies they most use throughout the scenarios’ development provides further engagement in what can be more “teen-like” and meaningful to this specific audience. In the future, another phase of this study is needed. Feedback from school counselors, teachers, and students in diverse school settings will inform the researchers about the usefulness of the videos and whether or not additional videos are merited. It will be important to evaluate the effectiveness of the videos in terms of capturing students’ attention and facilitating useful discussions about cyberbullying. If additional videos are made in the future, we would make modifications. For example, we would seek diverse school populations for each phase of the study and note the potential differences across students in grades 6–8.
We learned several lessons from this study that can inform future studies. (1) Iterations of the videos take time. Based on the data, both scenarios were reworked to reflect student participant input and concern; (2) Although working in a virtual environment presents challenges to researchers, we believe it can be a viable and safe medium to educate adolescents about cyberbullying prevention; (3) Creating fluid movements in SL can be problematic (e.g., awkward movements of avatars were sometimes distracting to the students); (4) By capturing the videos for off-line viewing, the scenarios can be utilized in multiple educational settings (e.g.. lecture, small groups, large groups, or individual viewing sessions); and (5) Videos offer “ice-breakers” to generate further discussions about cyberbullying prevention and intervention.
Implications for School Counselors
Cyberbullying-related deaths have continued to rise in recent years (e.g., Jesse Logan [Starr, 2009] and Hope Witsell [Inbar, 2009]) in 2009, Phoebe Prince in 2010 [McCabe, 2010], Tyler Clementi [Freidman, 2010], Natasha MacBryde [Loveland, 2011], and Britney Tongel [Leskin, 2011] and Amanda Cummings [Calabrese, 2012], in 2011 and 2012, respectively). With the fact that many of the given cases reached the point of suicide in high school underlines the need to focus on cyberbullying interventions in middle school, where literature has noted it peaks (Beale & Hall, 2007; Cassidy et al., 2009; Hinduja & Patchin, 2008; Kowalski & Limber, 2007; Li, 2007; Pelligrini & Bartini, 2000; Williams & Guerra, 2007). Reaching students before cyberbullying gets to the point that adolescents would consider suicide is critical.
This study is important because adolescents’ use of digital tools will continue to grow and evolve as technology tools (i.e., smart phones, mobile devices, social networking tools) become more accessible. Counselors, educators and parents cannot underestimate technology’s importance in adolescents’ lives. Instead, adults need to seek positive uses of technology for educational and social purposes, as well as prevention and intervention. We believe this study offers familiar technologies that students use everyday (e.g., videos in this study, Facebook) to raise awareness of cyberbullying and its consequences. Other commonly used tools also could be leveraged in similar educational endeavors (e.g., Facebook groups, Twitter) in the future, assuming the voices of adolescents are considered.
Amon, K., & Campbell, A. (2008). Can children with AD/HD learn relaxation and breathing techniques through biofeedback video games? Australian Journal of Educational and Developmental Psychology, 8, 72–84.
Beale, A., & Hall, K. (2007, September/October). Cyberbullying: What school administrators (and parents) can do. The Clearing House, 81, 8–12.
Calabrese, E. (2012, January). Anguished farewell for bullied suicide girl. New York Post. Retrieved from http://www.nypost.com/p/news/local/staten_island/anguishedfarewell_for_bullied_suicide_KYWBZakipv4BUzI85muvDI#ixzz1nSxKy8jn
Carney, J. (2008). Perceptions of bullying and associated trauma during adolescence. Professional School Counseling, 11, 179–187.
Cassidy, W., Jackson, M., & Brown, K. (2009). Sticks and stones can break my bones, but how can pixels hurt me? Students’ experiences with cyber-bullying. School Psychology International, 30, 383–402. doi: 10:1177/0143034309106948
Cobb, S., Beardon, L., Eastgate, R., Glover, T., Kerr, S., Neale, H.,… Wilson, J. (2002). Applied virtual environments to support learning of social interaction skills in users with Asperger’s Syndrome. Digital Creativity, 13, 11–22.
Collins, J. L., Cook-Cottone, C. P., Robinson, J. S., & Sullivan, R. R. (2004). Technology and new directions in professional development: Applications of digital video, peer review, and self-reflection. Journal of Educational Technology Systems, 33, 131–146.
Friedman, E. (2010). Victim of secret dorm sex tape posts Facebook goodbye, jumps to his death. ABC News. Retrieved from http://abcnews.go.com/US/victim-secret-dorm-sex-tape-commits-suicide/story?id=11758716#.T0hwCMzm87E
Hinduja, S., & Patchin, J. W. (2008). Cyberbullying: An exploratory analysis of factors related to offending and victimization, Deviant Behavior, 29, 129–156.
Hoff, D., & Mitchell, S. (2009). Cyberbullying causes, effects, and remedies. Journal of Educational Administration, 47, 652–665.
Inbar, M. (2009). ‘Sexting’ bullying cited in teen’s suicide: 13-year-old Hope Witsell hanged herself after topless photos circulated. Retrieved from http://wwwmsnbc.msn.com/id/34236377/ns/today-today_people/
Inman, C., Wright, V., & Hartman, J. (2010). Use of Second Life in K–12 and higher education: A review of research. Journal of Interactive Online Learning, 9(1). Retrieved from http://www.ncolr.org/jiol/issues/showissue.cfm?volID=9&IssueID=28
Keith, S., & Martin, M. (2005). Cyber-bullying: Creating a culture of respect in a cyber world. Reclaiming Children and Youth, 13, 224–228.
Kowalski, R., & Limber, S. (2007). Electronic bullying among middle school students. Journal of Adolescent Health, 41, 822–830.
Krijn, M., Emmelkemp, P. M. G., Olafsson, R. P., Bouwman, M., Van Gerwen, L. J., Spinhoven, P., Schuemie, M. J., & van der Mast, C.A.P.G. (2007). Fear of flying treatment methods: Virtual reality exposure vs. cognitive behavioral therapy. Aviation, Space, and Environmental Medicine, 78, 121–128.
Leskin, T. (2011, February). Another senseless cyberbullying suicide… Britney Tongel. Retrieved from http://blog.pcpandora.com/2011/02/24/another-senseless-cyberbullying-suicide%E2%80%A6-britney-tongel/
Li, Q. (2007). New bottle but old wine: A research of cyberbullying in schools. Computers in Human Behavior, 23, 1777–1791.
Loveland, M. (2011, January). Teen commits suicide after being cyberbullied, received harrassing messages on Formspring. Retrieved from http://www.scribbal.com/2011/07/teen-commits-suicide-after-being-cyberbullied-recieved-harrassing-messages-on-formspring/
Luo, L., & Kemp, J. (2008) Second Life: Exploring the immersive instructional venue for library and information science education. Journal of Education for Library and Information Science 49, 147–166.
McCabe, K. (2010, January). Teen’s suicide prompts a look at bullying. The Boston Globe. Retrieved from http://www.boston.com/news/local/massachusetts/articles/2010/01/24/teens_suicide_prompts_a_look_at_bullying/
O’Conner, E., & Sakshaug, L. (2009). Preparing for Second Life: Two teacher educators reflect on their initial foray into virtual teaching and learning. Journal of Educational Technology Systems, 37, 259–271.
Padgett, L. S., Strickland, D., & Coles, C. D. (2006). Case study: Using a virtual reality computer game to teach fire safety skills to children diagnosed with fetal alcohol syndrome. Journal of Pediatric Psychology, 31, 65–70. doi: 10.1093/jpepsy/jsj030
Paperny, D. M., & Starn, J. R. (1989). Adolescent pregnancy prevention by health education computer games: Computer-assisted instruction of knowledge and attitudes. Pediatrics, 83, 742–752.
Pellegrini, A., & Bartini, M. (2000). A longitudinal study of bullying, victimization, and peer affiliation during the transition from primary school to middle school. American Educational Research Journal, 37(3), 699–725.
Ritterfeld, U., & Weber, R. (2006). Video games for education and entertainment. In P. Vorderer & J. Bryant (Eds.), Playing video games: Motives, responses, and consequences (pp. 399–413). Mahweh, NJ: Lawrence Erlbaum.
Slater, M., Pertaub, D. P., & Steed, A. (1999). Public speaking in virtual reality: Facing an audience of avatars. IEEE Computer Graphics and Application, 19, 6–9. doi: 10.1109/38.749116
Starr, C. (2009). Parents should learn what sexting is and how to prevent it. Retrieved http://www.associatedcontent.com/article/1538742/jesse_logan_committed_suicide_after.html
Tapscott, D. (1998). Growing up digital: The rise of the Net Generation. New York, NY: McGraw-Hill.
Warburton, S. (2009). Second Life in higher education: Assessing the potential for and the barriers to deploying virtual worlds in learning and teaching. British Journal of Educational Technology, 40, 414–426.
Willard, N. (2006, April). Flame retardant: Cyberbullies torment their victims 24/7. School Library Journal, 54–56.
Williams, K., & Guerra, N. (2007). Prevalence and predictors of Internet bullying. Journal of Adolescent Health, 41(6), Supplemental 1, S14–S21.
Williamson, B., & Facer, K. (2004). More than ‘just a game’: The implications for schools of children’s computer games communities. Education, Communication, and Information, 4 (2/3), 255–270. doi: 10.1080/14636310412331304708
Wright, V. H., Burnham, J. J., Inman, C. T., & Ogorchock, H. N. (2009). Cyberbullying: Using virtual scenarios to educate and raise awareness. Journal of Computing in Teacher Education, 26, 23–30.
Yee, M. S., Bailenson, J. N., Urbanek, M., Chang, F., & Merget, D. (2007). The unbearable likeness of being digital: The persistence of nonverbal social norms in online virtual environments. CyberPsychology and Behavior, 10, 115–121.
Zoll, C., Enz, S., Schaub, H., Aylett, R., & Paiva, A. (2006, April). Fighting bullying with the help of autonomous agents in a virtual school environment. Paper presented at the 7th International Conference on Cognitive Modeling, Trieste, Italy.
Vivian H. Wright is an Associate Professor of Instructional Technology at the University of Alabama. Joy J. Burnham, NCC, is an Associate Professor of Counselor Education at the University of Alabama. Correspondence can be addressed to Vivian H. Wright, The University of Alabama, Box 870232, Tuscaloosa, AL 35487, firstname.lastname@example.org.