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. Author manuscript; available in PMC: 2024 Apr 1.
Published in final edited form as: Child Youth Serv Rev. 2023 Feb 3;147:106846. doi: 10.1016/j.childyouth.2023.106846

Avoidance Self-Efficacy: Personal Indicators of Risky Sex and Substance Use among At-Risk Youth

Amanda L Wiese 1, Thomas B Sease 1, Elizabeth D Joseph 1, Jennifer E Becan 1, Kevin Knight 1, Danica K Knight 1
PMCID: PMC9957012  NIHMSID: NIHMS1872734  PMID: 36844888

Abstract

Adolescent substance use (SU) is associated with risky sex behavior and sexually transmitted infections and is a risk factor for subsequent risky sex decisions. Based on a sample of 1,580 youth in residential SU treatment, this study investigated how a static factor (race) and two dynamic personal factors (risk-taking, assertiveness) contributed to adolescents’ perceived ability to avoid high-risk SU and sex behavior (avoidance self-efficacy). Results showed that race correlated with risk-taking and assertiveness, with White youth reporting higher ratings of assertiveness and risk-taking. Self-reported assertiveness and risk-taking also predicted SU and risky sex avoidance. This study underscores the importance of race and personal factors in relation to adolescents’ confidence in avoiding high-risk situations.

Keywords: Adolescents, Self-efficacy, Risk-Taking, Assertiveness, Substance Use, Sexual Health

In 2016, an estimated 1.1 million youth in the United States were diagnosed with a substance use disorder (SUD; Welty et al., 2019), making substance use (SU) behavior a major public health concern. People who initiate SU at an earlier age are at increased risk for developing a SUD (Chen et al., 2009; King & Chassin, 2007; Lopez-Quintero et al., 2011). Substance use during adolescence has been connected to declines in academic functioning (Cox et al., 2007; McCluskey et al., 2002) as well as lasting effects such as impaired psychosocial functioning (Englund et al., 2013; Rohde et al., 2007) and poor adjustment in adulthood (Lynne-Landsman et al., 2010). Recent research indicates that SU can also accelerate adolescents’ sexual debut (Clark et al., 2020). Correspondingly, SU is a risk factor for poor sexual decisions, such as having increased instances of engaging in unprotected sex, a higher number of sexual partners, and a greater likelihood of contracting sexually transmitted infections (e.g., HIV; Elkington, 2010; Tapert et al., 2001; Ritchwood et al., 2015).

Biological, social, and cognitive models have been proposed to explain adolescents’ propensity towards poor decision-making. Biological approaches emphasize the neurobiological changes that occur during adolescence. According to the reward sensitivity model, the early development of the brain’s reward processing systems in tandem with the slower maturation of the cognitive control systems predisposes adolescents for poor decision-making (Steinberg, 2008; Casey et al., 2008; Ernst et al., 2015; Shulman et al., 2016). In alignment with theories in social psychology, adolescents experience heightened social motivation, which makes them acutely concerned with how others perceive and respond to them (e.g., social influence hypothesis; Walker & Andrade, 1996). Social motivation models demonstrate how adolescents are more likely to make poor decisions when in the presence of their peers wherein risky behaviors are highly socially regarded (Crone & Dahl, 2012). According to cognitive theory, decreased metacognitive awareness in conjunction with difficulties regulating emotions contribute to poor decision-making in adolescents (Dansereau et al., 2013). Understanding factors associated with avoidance of frequent risky behavior can inform researchers and clinicians creating interventions designed to improve adolescent decision-making.

1.1. Risky Behavior and Avoidance Self-Efficacy

Adolescents’ SU avoidance self-efficacy, the perceived ability to avoid subsequent drug use, is a protective factor that has been linked to improvements in SU behavior. For example, avoidance self-efficacy has consistently predicted less frequent SU and increased rates of recovery in adult samples (Ilgen et al., 2005; Stephens et al., 1993). Conceptually, SU avoidance self-efficacy can be understood as a localized form of self-efficacy that refers exclusively to situations involving SU. For example, while someone with high generalized self-efficacy may feel confident in their ability to complete a wide range of tasks (e.g., school, work, athletics), SU avoidance self-efficacy encompasses someone’s perceived ability to avoid using substances. Moreover, SU avoidance self-efficacy differs from concepts, such as self-esteem, in that it does not measure how one thinks, feels, or perceives their overall sense of self (see Rosenberg, 1965). In empirical work, refusal response efficacy—defined as a person’s refusal repertoire—was found to be negatively associated with alcohol and marijuana use (Choi et al., 2013). Although confidence in one’s ability to avoid engaging in risky sex behaviors is less frequently examined, a study with a sample of over 1,000 adolescents found that greater risky sex avoidance predicted more safe sexual practices (Rosenthal et al., 1991). Preventive self-efficacy, a concept related to avoidance self-efficacy, refers to one’s confidence in their ability to utilize safe sex practices to protect against HIV. This construct has been found to be negatively correlated with risky sex behavior among adolescents (Lee et al., 2009). Among sexually active adolescents, confidence in one’s ability to decline a sexual partner has been found to be associated with safer sex practices (Rosenthal et al., 1991).

It also is critically important to examine how individual differences impact adolescents’ confidence to avoid high-risk situations. From a developmental perspective, adolescence is a critical period for identity formation (Coll et al., 1996), and ethnic/racial identity (ERI) has been linked to improved psychological outcomes among youth (Rivas-Drake et al., 2014a; Rivas-Drake et al., 2014b). While affiliation with one’s ERI affords certain advantages or protections in some situations (Umaña-Taylor et al., 2014), it has been shown to have negative consequences in the context of ethnic/racial discrimination (ERD; Yip, 2018; Yip et al., 2020). Multiple socioeconomic, health, and psychosocial mediators have been identified that effect the relationships between race and outcomes throughout the life course (Zahodne et al., 2017). For example, among college students, the effects of ERD on health care utilization were mediated by self-efficacy to communicate with physicians (Cavalhieri et al., 2019). Unfortunately, only a handful of studies have explored how adolescents’ ERI may relate to their involvement with SU and risky sex behavior. Of the studies that have, White youth were more likely to engage in SU when compared to Black/African American youth (Johnson et al., 2006). When examining the trajectory across adolescence and early adulthood, White youth reported more SU overall compared to youth from other ethnic backgrounds, and Hispanic youth reported the highest amount of SU in early adolescence (Chen & Jacobson, 2012). Among adolescents who engage in SU, previous research has shown that White youth are more likely to display risky sex behaviors compared to their Black and Hispanic peers, which may be attributed to more stigma in communities of color around risky sex behavior, or greater social supports and religiosity in these communities (Miller & Broman, 2016).

Personal characteristics, such as those described above, potentially impact how people interact with their surroundings, which in turn influences their ability and confidence to avoid high-risk situations. Thus, it may be important to examine the relationships between personal characteristics and avoidance self-efficacy. To that end, the current study investigates how two potential mediators (risk-taking and assertiveness) impact the relationship between a static personal characteristic (i.e., race) and a dynamic personal characteristic (behavioral risk avoidance confidence).

1.2. Potential Mediators: Risk-Taking and Assertiveness

Risk-taking and assertiveness have been implicated in adolescents’ risky behavior. For example, elevated levels of risk-taking, and closely related behaviors (i.e., impulsivity, sensation-seeking), have been linked with increased SU and unsafe sex practices in youth and young adults (Derefinko et al., 2014; Dunlop & Romer, 2010; Jacobus et al., 2013). Namely, adolescents who displayed high risk-taking also reported more SU (Aklin et al., 2005). Adolescents who reported higher impulsivity and sensation-seeking were more likely to engage in risky sex behaviors and have a higher number of casual sex partners (Dir et al., 2014). Conversely, assertiveness is associated with less frequent risky behavior. Adolescents with high levels of assertiveness were less likely to engage in SU behavior (Trudeau et al., 2003; Glaser et al., 2010). Likewise, adolescents with assertive tendencies were less likely to engage in high-risk sex behavior (Granados et al., 2020; Morokoff et al., 2009; Yesmont, 1992). Assertiveness diminishes the relationship between peer pressure and poor decision-making (Epstein et al., 2007), indicating that assertiveness might be a protective factor against risky choices. Importantly, risk-taking and assertiveness are, in theory, two dynamic personal factors that can be altered through targeted intervention. Coupled with their established associations with SU and risky sex avoidance, this makes risk-taking and assertiveness potential targeted goals for adolescent SU and risky sex behavior avoidance programs.

The risk-need-responsivity (RNR) model (Bonta & Andrews, 2007) describes how effective interventions consider the accumulation of a client’s risk factors, needs, and abilities when addressing maladaptive behavior. According to this approach, static risk factors (e.g., age, gender, race) for SU and unsafe sex behaviors are those that cannot be changed through intervention. It is important to explore how static factors are related to clients’ individual needs, so that treatment programming may be adapted and tailored to the specific needs of each individual client. Dynamic risk factors, such as family involvement and decision-making skills, are considered amendable to change. Two such dynamic personal factors that are hypothesized to be relevant for targeted change among adolescents are risk-taking and assertiveness. Notably, youth of varying backgrounds frequently report different levels of risk-taking and assertiveness. For example, researchers have argued that Black and Hispanic youth derive less positive reinforcement from risk-taking, which is possibly due to a smaller perceived “margin for error” than that of their White counterparts (Vaughn et al., 2021). A national survey found that Black and Hispanic adolescents from lower socioeconomic backgrounds show a lower propensity for risk-taking and abuse alcohol less frequently than White youth (Watt, 2005). Collectively, understanding the relationships between static and dynamic personal factors may provide useful information for interventions designed to reduce SU and risky sex behavior in adolescents.

1.3. Current Study

Even though substance use and risky sex behavior in adolescence have been associated with demographic factors such as race, the nature of this relationship must be more closely examined. Namely, a more thorough understanding of how race is associated with adolescents’ confidence to avoid subsequent risky behavior has both theoretical and practical significance. This study examined two related factors (risk-taking and assertiveness) as predictors of SU and risky sex avoidance self-efficacy in a sample of youth in residential SU treatment and examined the possibility of these factors serving as mediators between the association of race and risky behaviors. Considering how static individual differences influence the ways in which youth interact with their environment (Chen & Jacobson, 2012; Johnson et al., 2006; Swendsen et al., 2012), it was hypothesized that White and Black, Indigenous, and people of color (BIPOC) youth in SU treatment would report significantly different levels of risktaking and assertiveness. More specifically, in accordance with past research, BIPOC youth were expected to report less risk-taking compared to their White peers, which in turn would be associated with greater avoidance self-efficacy, regarding both SU and risky sex behavior. Similarly, White youth were expected to report greater assertiveness compared to their BIPOC counterparts, resulting in greater avoidance self-efficacy.

2. Method

2.1. Sample

Data were collected as part of a research project on the Treatment Readiness Induction Program (TRIP) funded by the National Institute on Drug Abuse (NIDA; Grant R01DA013093). The current sample included 2,001 adolescents recruited from eight community based residential SU treatment facilities located across three different states in the United States between 2011 and 2012. After removing 421 participants due to missing data for all variables of interest, 1,580 participants were retained for data analysis. The eight facilities were based in rural (n = 2), suburban (n = 3), and urban (n = 3) communities. All of the facilities utilized a similar therapeutic community treatment model, with cognitive-behavioral treatment philosophies (Becan et al., 2015). The facilities were identified through regional Addiction Technology Transfer Centers and each one agreed to sign Qualified Service Organization Agreements. The agreements required the facilities to implement assessment tools and TRIP as part of their clinical practice and release de-identified youth data. As the assessment and implementation were made standard operating procedure in the facilities, all youth enrolled were eligible for participation. In other words, since all youth in every facility received both TRIP and all of the assessment tools, there was no inclusion or exclusion criteria. Rather, every adolescent at all eight facilities was included in the de-identified data we received as well as subsequent analyses.

The majority of participants were male (69%), ranging in age from 12 to 18 (M = 15.79, SD = 1.07). As shown in Table 1, most participants were Hispanic (60%). The sample was primarily White (39%), and all other race groups were combined to represent those who were BIPOC (61%). Three-fourths (75%) of participants were identified as having a severe SUD, as measured by the TCU Drug Screen II (Institute of Behavioral Research, 2011a). When asked about the substance causing them the most issues in the past 12 months, participants most often reported substances such as marijuana (32%), methamphetamine (13%), and alcohol (11%).

Table 1.

Demographics

Demographic n Percent (%)
Sex
   Male 1087 69%
   Female 493 31%
Hispanic
   No 627 40%
   Yes 948 60%
Race
   American Indian/Alaska Native 28 2%
   Asian 8 1%
   Native Hawaiian/Pacific Islander 8 1%
   Black/African American 141 9%
   White 615 39%
   More than one race 184 12%
   Other 596 38%
Primary Drug
   None 265 18%
   Alcohol 161 11%
   Marijuana 455 32%
   Methamphetamines 187 13%
   Cocaine (by itself) 83 6%
   Heroin (by itself) 88 6%
   Other 200 14%
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Note: Primary drugs selected by less than 5% of respondents were combined into “Other,” including “Hallucinogens/LSD/PCP/Psychedelics/Mushrooms,” “Inhalants,” “Crack/Freebase,” “Heroin and Cocaine (mixed together as Speedball),” “Street Methadone (non-prescription),” “Other Opiates/Opium/Morphine/Demerol,” “Amphetamines (other uppers),” and “Tranquilizers/Barbiturates/Sedatives (downers).”

2.2. Measures

2.2.1. Race

At intake, adolescents completed questionnaires covering demographics and risk factors (TCU Y-RSKForm; Institute of Behavioral Research, 2008). Participants reported their race as either American Indian/Alaska Native, Asian, Native Hawaiian/Pacific Islander, Black/African American, White, more than one race, or other. This variable was re-coded to indicate whether the participant was White or BIPOC. Race was chosen as a predictor in the present study based on the RNR model, which stresses the importance of identifying the relationship between static and dynamic factors, such that treatment programming may be more tailored to meet the individual needs of the population.

2.2.2. Risk-Taking

Risk-taking was assessed using the Risk-Taking subscale on the TCU Social Functioning Form (TCU SOCFORM) and collected at Time 1 (Institute of Behavioral Research, 2010a). The risk-taking scale was originally developed for adults in treatment (see Garner et al., 2007). In order to allow for future comparisons between adult and adolescent samples, the items within the risk-taking scale remained identical to the adult version. The risktaking scale in the present study has previously shown adequate internal consistency (Cronbach’s α = .76; Knight et al., 2014). This 7-item subscale asks participants to report on their behavior using a 5-point Likert scale (1 = Disagree Strongly to 5 = Agree Strongly). Risk-taking scores were calculated by taking the mean of all seven items, with a higher score indicating more risk-taking. Sample items include, “You like to take chances” and ‘You like to do things that are strange or exciting.”

2.2.3. Assertiveness

Assertiveness was measured using the 5-item Assertiveness subscale on the TCU Adolescent Thinking Form B (TCU ADOL THKForm B) and collected at Time 1 (Institute of Behavioral Research, 2010b). The TCU ADOL THKForm B scales were adapted for use with adolescents and addresses thinking styles and thinking errors (see Knight et al., 2014). Using a 5-point Likert scale (1 = Disagree Strongly to 5 = Agree Strongly), participants are asked to respond to items such as, “I am confident that I can express my opinions when others disagree with me” and “I am confident that I can stand firm to someone who is asking me to do something unreasonable.” Scores were calculated by taking the mean of all items, with a higher score indicating greater assertiveness. Past work suggests the assertiveness subscale is reliable (Cronbach’s α = .79; Knight et al., 2014).

2.2.4. Substance Use Avoidance

Substance use avoidance was measured using the 5-item Self-Efficacy: Resist Drug Use scale on the TCU ADOL THKForm B and collected at Time 2 (Institute of Behavioral Research, 2010b). Higher scores are indicative of more confidence in one’s ability to avoid SU. Using a 5-point Likert scale (1 = Disagree Strongly to 5 = Agree Strongly), participants responded to items such as, “I am confident that I can make friends with people who don’t use alcohol/drugs” and “I am confident that I can avoid situations and people where alcohol/drugs are present.” Previous research suggests this scale has strong psychometric properties (Cronbach’s α = .84; Knight et al., 2014).

2.2.5. Risky Sex Avoidance

Risky sex avoidance was measured using the TCU HIV Risk Form (TCU ADOL HVCTForm) and collected at Time 2 (Institute of Behavioral Research, 2011b). This scale was adapted from the TCU HIV Risk Assessment (Simpson et al., 1994). This 3-item scale assesses risky sex avoidance using a 5-point Likert scale (1 = Disagree Strongly to 5 = Agree Strongly). Higher scores on this scale indicate greater confidence in one’s ability to avoid risky sex behaviors in the future. Sample items include, “You are confident that you will always use a condom when having sexual intercourse” and “It is easy for you to talk with a sex partner about using condoms.” This scale is scored by taking the mean of all items. As with the SU avoidance scale, previous research verifies the strong psychometric properties of this measure (Cronbach’s α = .76; Knight et al., 2014).

2.3. Analytic Plan

All analyses listed below were analyzed using SPSS version 25 (IBM, 2017). First, data were analyzed to determine the proportion of youth with missing data at each time point. Missing data were imputed five times using fully conditional specification (the Markov chain Monte Carlo method), after determining that the missing data had occurred at random. Predictive mean matching (Vink et al., 2014; Akmam et al., 2019) was used for all imputation models. Second, correlation analysis was used to examine the associations among the primary variables of interest (see Table 2). Third, in accordance with MacKinnon and Luecken’s (2008) method of mediation, two separate parallel mediation analyses were conducted to examine the indirect effect of the proposed mediating variables (i.e., risk-taking and assertiveness at Time 1) between race predicting SU avoidance and risky sex avoidance (both measured at Time 2). The results reported in this study are based on the analyses of the pooled multiple sets of imputed data (Taljaard et al., 2008).

Table 2.

Correlations, Means, and Standard Deviation for Key Variables

1 2 3 M SD
1. Risk-taking -- -- -- 33.89 6.76
2. Assertiveness .10** -- -- 37.47 7.24
3. Substance Use Avoidance −.10* .34** -- 38.92 7.43
4. Risky Sex Avoidance −.07* .28** .60** 39.64 7.53
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Note.

*

Indicates significance at p < .05,

**

indicates significance at p ≤ .001.

3. Results

3.1. Missing Data

Six hundred and sixty-three adolescents (42%) had complete data at Time 1 (admission) and Time 2 (approximately day 35 of treatment). Data were most commonly missing for Time 2 measures (46%). Missing data at Time 2 was attributed to facility-level limitations; for example, early discharge or scheduling issues associated with changes in staffing or caseloads (Becan et al., 2015). The percentage of missing values across the five variables of interest (race, risky sex avoidance, SU avoidance, risk-taking, and assertiveness) varied from zero to 55. Of the 1,580 participants, 42% had complete data, leaving 917 records (58%) incomplete. The most common pattern of missing data (46%) was missing Time 2 assessment data only (i.e., SU avoidance, risky sex avoidance). Previous analyses examining patterns of missing data in the sample reported that, controlling for demographic variables, assessment measures at Time 1 were not significant predictors of missingness at Time 2 (see Crawley, 2015 for a full review of missing data patterns in the current sample).

Multiple imputation was used to create and analyze five multiply imputed datasets. In the estimation process, the fully conditional specification method (FCS) was designated using predictive mean matching. For comparison, both parallel mediation analyses were performed on the subset of complete cases, and the pattern of results was the same. The results presented in this paper are based on the pooled analyses for each of the two models tested: (1) Mediation Model for Race and SU Avoidance and (2) Mediation Model for Race and Risky Sex Avoidance.

3.2. Predicting Substance Use Avoidance

A parallel mediational model examined whether risk-taking (Mediator 1) and assertiveness (Mediator 2) mediated the relationship between race (dummy-coded: 0 = BIPOC, 1 = White) and SU avoidance (see Figure 1). From the pooled analysis model results, race significantly predicted both risk-taking (a1 path), b = 2.06 (SE = 0.37), t = 5.61, p < .001, with White youth indicating more risk-taking as compared to their BIPOC peers, and assertiveness (a2 path), b = 1.00 (SE = 0.38), t = 2.62, p = .009, with White youth reporting more assertiveness when compared to their BIPOC counterparts. Risk-taking (b1 path) and assertiveness (b2 path) both predicted SU avoidance when controlling for race and the other mediator in the model: risk-taking (b = −0.15 [SE = 0.05], t = 3.06, p = .018); assertiveness (b = 0.35 [SE = 0.05], t = 7.31, p < .001). Follow up tests showed the indirect effects for risk-taking and assertiveness were both significant, as indicated by the Sobel test: risk-taking (z = 2.64, SE = .12, p = .008); assertiveness (z = 2.46, SE = .14, p = .014). Therefore, race had a significant negative indirect effect on avoidance of SU through risk-taking and a positive indirect effect on avoidance of SU through assertiveness.

Figure 1. Indirect Effect of Race on Substance Use Avoidance.

Figure 1

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Note. The indirect effects of race on substance use avoidance through risk-taking and assertiveness. * Indicates significance at p < .05, ** indicates significance at p < .001.

3.3. Predicting Risky Sex Avoidance

A second parallel mediation model examined whether risk-taking and assertiveness mediated the relationship between race (dummy-coded: 0 = BIPOC, 1 = White) and risky sex avoidance (see Figure 2). Results of the a1 and a2 paths were the same as the previous model predicting SU avoidance. Namely, White youth reported greater risk-taking, b = 2.06 (SE = 0.37), t = 5.61, p < .001, and assertiveness, b = 1.00 (SE = 0.38), t = 2.62, p = .009, as compared to BIPOC youth. Moreover, risk-taking also predicted less confidence in refraining from risky sex behavior (b1 path), b = −0.10 (SE = 0.04), t = 2.76, p = .014, and greater assertiveness predicted more confidence in avoiding risky sex behavior (b2 path), b = 0.30 (SE = 0.04), t = 6.75, p < .001. As in the previous model, the indirect paths for both mediators were significant, as indicated by the Sobel test: risk-taking (z = 2.28, SE = .09, p = .023); assertiveness (z = 2.48, SE = .12, p = .014). In summary, race had a significant negative indirect effect on avoidance of risky sex behaviors through risk-taking and a positive indirect effect on avoidance of risky sex behaviors through assertiveness.

Figure 2. Indirect Effect of Race on Risky Sex Avoidance.

Figure 2

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Note. The indirect effects of race on risky sex avoidance through risk-taking and assertiveness. * Indicates significance at p < .05, ** indicates significance at p < .001.

4. Discussion

The findings from the current study were consistent with our predictions and build on findings from previous research. Specifically, compared to BIPOC youth, White adolescents reported higher levels of both assertiveness and risk-taking behaviors. This finding reiterates previous work reporting differences in assertiveness and risk-taking among youth of varying racial backgrounds (Vaughn et al., 2021; Watt, 2005). Further, greater assertiveness contributed to higher levels of avoidance self-efficacy, in terms of both SU and risky sex behavior. In contrast, risk-taking was negatively associated with SU and risky sex avoidance self-efficacy. It is important to note the possibility that race is a proxy for structural and historic biases in society and something that future research should explore. Collectively, these findings add to an existing body of literature emphasizing the positive and negative effects of assertiveness and risk-taking among adolescents who are high risk in SU treatment (Aklin et al., 2005; Dir et al., 2014; Glaser et al., 2010; Granados et al., 2020), respectively. In conjunction with past research, these results suggest assertiveness is a protective factor against risky behavior, whereas risk-taking heightens the likelihood of adolescent SU and risky sex behavior.

The mediational effect of risk-taking and assertiveness on the relationships between race and avoidance self-efficacy adds to the literature by demonstrating how static personal factors (e.g., race) contribute to differences in dynamic factors (e.g., risk-taking, assertiveness), which in turn have the potential to impact adolescents’ responsiveness to treatment. The RNR model states that individual needs should be considered when trying to maximize the effectiveness of treatment. In practice, this includes 1) the identification of personal factors that may impact treatment, and 2) dynamic treatment models that are able to adapt to these personal factors. Regarding the former, the identification of personal differences would ideally occur at admission into treatment. This information could then be used to help guide treatment programs that meet the individual needs of the client. Notably, the RNR model has been criticized for its focus on reducing deficits (e.g., criminogenic needs) rather than emphasizing strengths or protective factors (e.g., self-efficacy). Together, treatment programs that can identify and adapt to unique client needs are likely to be the most effective for youth. These findings suggest that alleged mechanisms impacting the treatment process and outcomes are likely to vary based on ERI. For example, based on the findings of this study, potential race and ethnic group variations in assertiveness and risk-taking need to be considered when providing a tailored, targeted treatment approach to youth who are high risk.

Considering the correlation risk-taking and assertiveness have with avoidance self-efficacy, it may be beneficial for treatment programs to target these behaviors. That is, by simultaneously decreasing risk-taking and increasing assertiveness, youth may be less vulnerable in high-risk situations. Such programs would have great relevance for adolescent populations–given their increased sensitivity to social pressures (Crone & Dahl, 2012). Moreover, risk-taking and assertiveness had identical patterns of effects on youth SU and risky sex avoidance selfefficacy. This suggests that interventions that promote decreased SU behavior may also result in decreased risky sex behavior, and vice versa. For example, the Treatment Readiness and Induction Program (TRIP) includes therapeutic modalities geared towards improving adolescents’ relationship with their peers (Knight et al., 2016). This program effectively reduced problem recognition and improved decision-making and treatment engagement among adolescents who are high risk when compared to standard treatment alone (Becan et al., 2015; Knight et al., 2016).

4.1. Limitations

The present study has noted limitations. First, the study collected data from youth participating in residential SU treatment between 2011 and 2012, potentially limiting the generalizability of the findings to youth in other contexts (e.g., under community supervision). Second, this study was not able to examine racial differences other than White vs. BIPOC, and therefore did not examine other racial backgrounds or ethnicity. The low proportion of females in the sample also precluded an analysis of any differences based on assigned sex at birth. Although some work has directly examined how personal characteristics contribute to differences in SU and risky sex behavior (Chen & Jacobson, 2012; Johnson et al., 2006; Miller & Broman, 2017), more research is needed to uncover how these social determinants may increase, or decrease, youths’ likelihood of engaging in high-risk behavior. Further, future analyses should examine intersectional groups by gender and race to inform intervention strategies. This information could be used to address deficits in resources and provide supplemental support where needed. Third, this study assessed the relationships among race, risk-taking, and assertiveness on self-reported confidence in one’s ability to avoid risky behaviors in the future; whether the current findings extend to overt reductions in future SU and risky sex behavior is an important question for further research. Although previous research has found avoidance self-efficacy is predictive of eventual behavioral avoidance (Choi et al., 2013; Rosenthal et al., 1991), future studies will need to examine the predictive utility of assertiveness and risktaking behavior in terms of overt reductions in subsequent SU and risky sex behavior. Future research in this area should seek to develop interventions and target mechanisms of change that help adolescents build skills that will generalize to high-risk situations, including both SU and risky sex behavior. Examples of other potentially important factors that are likely fruitful areas of research include mental health (e.g., depression, anxiety; Pozuelo et al., 2021), religiosity (Ameri et al., 2017), and peer and family support (Çakar & Tagay, 2017).

4.2. Conclusion

The present study found that risk-taking and assertiveness mediated the relationship between race and avoidance self-efficacy regarding SU and risky sex behavior. These findings imply that race group differences in risk and protective factors should be considered when tailoring prevention and intervention programs for at-risk youth. Specifically, programs may benefit from targeting risk-taking among White youth, while BIPOC youth may benefit more from programs designed to enhance assertiveness. Further research identifying explanatory variables for these racial differences would have practical significance. Based on the findings reported here, race is an important factor in considering youth responsiveness to interventions for SU and risky sex behavior. A “one-size fit all” treatment approach is inconsistent with an emerging body of evidence pointing to apparent differences in SU and risky sex behavior among youth of varying backgrounds.

Highlights.

  • This study examined predictors of substance use and risky sex avoidance

  • White youth reported more risk-taking and assertiveness compared to BIPOC youth

  • In turn, risk-taking and assertiveness were correlated with avoidance self-efficacy

Acknowledgements

All authors contributed to the study conception and design. Data analyses were performed by AW. The first draft of the manuscript was written by AW, with significant help from TS and EJ, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

This project was funded by the National Institute on Drug Abuse (NIDA; grant R01DA013093).

Footnotes

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Conflicts of Interest

We have no conflicts of interest to disclose.

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