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. Author manuscript; available in PMC: 2016 Jan 5.
Published in final edited form as: Psychol Addict Behav. 2015 Jul 13;29(4):969–977. doi: 10.1037/adb0000096

The Influence of Cultural Variables on Treatment Retention and Engagement in a Sample of Mexican American Adolescent Males with Substance Use Disorders

Jason J Burrow-Sanchez 1, Kimberly Meyers 1, Carolina Corrales 1, Cynthia Ortiz Jensen 1
PMCID: PMC4701593  NIHMSID: NIHMS692730  PMID: 26168226

Abstract

Adolescent substance abuse is a serious public health concern, and in response to this problem, a number of effective treatment approaches have been developed. Despite this, retaining and engaging adolescents in treatment are two major challenges continuously faced by practitioners and clinical researchers. Low retention and engagement rates are especially salient for ethnic minority adolescents because they are at high risk for underutilization of substance abuse treatment compared to their White peers. Latino adolescents, in particular, are part of the fastest growing ethnic minority group in the U.S. and experience high rates of substance use disorders. Heretofore, the empirical examination of cultural factors that influence treatment retention and engagement has been lacking in the literature. The goal of this study was to investigate the influence of the cultural variables ethnic identity, familism and acculturation on the retention and engagement of Latino adolescents participating in substance abuse treatment. This study utilized data collected from a sample of Latino adolescent males (N=96), predominantly of Mexican descent, and largely recruited from the juvenile justice system. Analysis was conducted using generalized regression models for count variables. Results indicated that higher levels of exploration, a subfactor of ethnic identity, and familism were predictive of attendance and engagement. In contrast, higher levels of Anglo orientation, a subfactor of acculturation, were predictive of lower treatment attendance and engagement. Clinical implications for the variables of ethnic identity, acculturation, and familism as well as suggestions for future research are discussed.

Keywords: treatment retention, treatment engagement, Latino adolescents, familism, ethnic identity, acculturation

Adolescent substance abuse is a serious public health problem with almost 10% of youth, ages 12-17, reporting the use of illicit drugs and 7% of these youth meeting criteria for a substance use disorder as indicated from national survey collected by the Substance Abuse and Mental Health Services Administration (SAMHSA, 2012). In response to this problem, a number of effective treatment approaches have been developed and tested for adolescents over the past two decades (Waldron & Turner, 2008; Williams & Chang, 2000). However, retaining and engaging adolescents in treatment are two major challenges continuously faced by practitioners and clinical researchers. These issues are especially salient for ethnic minority adolescents because they remain at high risk for underutilization of substance abuse treatment compared to their White peers (Alegria, Carson, Goncalves, & Keefe, 2011).

As one of the largest ethnic minority groups, Latinos comprise more than 51 million people with the majority (65%) being of Mexican descent and a third of its population under the age of 18 (Pew Research Center, 2011). These adolescents report higher rates of substance use disorders (14%) compared to their White (12.7%) or African American (7%) peers as indicated by the Center on Addiction and Substance Abuse (CASA, 2011). They are also more likely than White youth to be referred and mandated to attend substance abuse treatment from the criminal justice system (Shillington & Clapp, 2003). Latino adolescents, however, are less likely to complete substance abuse treatment compared to their White counterparts (Saloner, Carson, & Le Cook, 2014). Thus, it is important to understand the factors that influence treatment retention and engagement for adolescents, in general, and Latino adolescents, in particular.

Precise definitions of treatment retention and engagement are difficult to operationalize because these variables are defined differently across studies and the format of treatment provided: residential, inpatient or outpatient. In one of the more comprehensive studies of adolescent substance abuse treatment, Hser and colleagues (2001) examined data from a geographically diverse sample of almost 1,200 adolescents from four cities in the United States who participated in residential, acute inpatient or outpatient substance abuse treatment. Across these treatment modalities, marijuana and alcohol were the most frequently used substances, and about half the sample also reported some use of hard drugs (i.e., cocaine, hallucinogens, stimulants). Treatment retention was examined for each modality and defined as 90 days or more for residential and outpatient, and as 21 days for acute inpatient. Retention rates were highest for adolescents who received inpatient (63.7%) and residential (58.4%) treatment, and lowest for those in outpatient treatment (27.1%). After controlling for treatment type and baseline severity of drug use, Hser and colleagues found that longer time spent in treatment was associated with better overall outcomes for adolescents. This positive correlation between treatment retention and outcome is a robust finding that has been replicated in substance abuse treatment studies with adults and adolescents (Brady & Ashery, 2005; Garner et al., 2009; Greenfield et al., 2007; Simpson, Joe, & Brown, 1997). Unfortunately, Hser and colleagues found the lowest retention rates for the treatment modality that youth in the U.S. are most likely to receive, that is, outpatient treatment (SAMHSA, 2009).

Operational definitions of treatment engagement are also difficult to find in the literature because many studies do not provide clear definitions of engagement, or confound the definition of the construct with treatment attendance (see Pullman et al., 2013; Staudt, 2007). However, some researchers suggest that measuring a behavior, such as treatment participation, is important when assessing engagement (see Joe, Simpson, & Broome, 1999; Staudt, 2007; Staudt, Lodato, & Hickman, 2012). For example, Stein and colleagues (2006) measured engagement in a sample of 130 incarcerated adolescents largely through assessing their participation in one of two assigned treatment conditions for substance abuse. While agreed upon definitions across studies are lacking, there is support to suggest that attendance and participation are valid measures of treatment retention and engagement, respectively. Next, we examine the general factors that influence retention and engagement in substance abuse treatment for adolescents.

General Factors that Influence Retention and Engagement

In general, the severity of pretreatment substance use and the presence of an externalizing disorder are factors that have been found to influence the amount of time adolescents spend in treatment. In the adult literature, greater substance use severity at treatment admission is typically related to poorer treatment outcomes (SAMHSA, 2014a; Tiet, Ilgen, Byrnes, Harris, & Finney, 2007), but this is not consistently the case with adolescents. In other words, pretreatment substance use severity on its own does not consistently predict lower levels of treatment retention for adolescents (Latimer, Newcomb, Winters, & Stinchfield, 2000). Rather, it appears that pretreatment substance use severity in the presence of an externalizing disorder (i.e. Attention Deficit Hyperactivity Disorder, Conduct Disorder) is a stronger predictor of lower treatment retention for adolescents, especially in samples recruited from juvenile justice (see Austin & Wagner, 2010; Grella, Hser, Joshi, & Rounds-Bryant, 2001; Shane, Jasiukaitis, & Green, 2003). In fact, adolescents in the juvenile justice system tend to have higher rates of externalizing disorders, as well as substance use problems, compared to youth in the general population (Chassin, 2008; Rosenblatt, Rosenblatt, & Biggs, 2000). Most of the studies on treatment retention and engagement have largely been conducted with samples of White adolescents and excluded the investigation of cultural variables when diverse youth are included in the sample. Additionally, more of a focus on juvenile justice is needed because this system serves as one of the primary referral sources for adolescents to substance abuse treatment (Ozechowski & Waldron, 2008). For example, data from the 2011 Treatment Episode Data Set for discharges (TEDS-D) indicates that approximately half of all youth, ages 12-20, discharged from publically funded substance abuse treatment were referred from the justice system (SAMHSA, 2014b). In sum, research that investigates how cultural variables influence treatment retention and engagement in juvenile justice involved ethnic minority youth is needed.

Ethnic Minority Youth

As previously mentioned, racial and ethnic minority youth are less likely to be retained in substance abuse treatment compared to their White counterparts (Jacobson, Robinson, & Bluthenthal, 2007; Saloner et al., 2014; Vourakis, 2005), although the reasons for these differences are not clear. Some have suggested that cultural variables play a role in substance abuse treatment retention and completion for ethnic minority youth (see Austin & Wagner, 2006; Castro & Alarcon, 2002), although heretofore the empirical evidence underlying this assumption has been lacking. For example, we were only able to locate two empirical studies, both by Austin and Wagner (2006; 2010), that directly examined the influence of cultural variables on treatment retention.1 In the 2010 study, the researchers’ investigated the influence of cultural and general variables on treatment attrition with a sample (N=453) of Latino2 (Domestic and Foreign Born) and African American adolescents receiving substance abuse treatment. The adolescents in their sample received substance abuse treatment as part of their involvement with juvenile justice. Contrary to the researchers’ expectations, none of the cultural variables tested (i.e., acculturation, perceived discrimination or racial/ethnic identity) influenced treatment completion, but rather, some of the general variables were influential across racial and ethnic subgroups. For example, they found that not being placed on a waiting list and lack of a conduct disorder diagnosis influenced treatment completion for those Latino adolescents of U.S. and foreign birth, respectively. In light of the results from the Austin and Wager studies, the influence of cultural variables on substance abuse treatment retention and engagement has yet to be examined in adolescents of Mexican descent who represent the largest Latino subgroup.

Salient Cultural Variables for Latino Youth

Three of the most salient cultural variables in relation to substance use and mental health for Latino adolescents include ethnic identity, familism and acculturation (Castro & Alarcon, 2002; Umaña-Taylor & Updegraff, 2007; Vega & Gil, 1999). First, ethnic identity or a Latino adolescent's sense of belonging to a particular ethnic group has been linked to mental health and substance use outcomes. For example, a stronger sense of ethnic identity is generally related to lower levels of psychological distress and substance use for Latino adolescents (Felix-Ortiz & Newcomb, 1995; Phinney & Ong, 2007; Umaña-Taylor, 2011). Second, familism is the sense of obligation and perceived support Latino adolescents experience within their families (Sabogal, Marin, Otero-Sabogal, & Marin, 1987). This cultural variable is relevant because Latino families with higher levels of familism do not generally condone the use of substances by its members (Vega, 1990). Finally, acculturation is considered a bi-dimensional process that involves the orientation Latino adolescents have toward being part of dominant and non-dominant cultures simultaneously (Berry, 1980; Berry, Phinney, Sam, & Vedder, 2006). In general, the majority of research findings indicate a positive correlation between acculturation and rates of substance use for Latino adolescents (De La Rosa, Vega, & Radisch, 2000; Ebin et al., 2001; Lawton & Gerdes, 2014; Vega & Gil, 1999), while a few researchers have found a negative correlation, or no association, between these two variables (Miller, 2011; Zamboanga, Schwartz, Jarvis, & Van Tyne, 2009). In sum, all three of these cultural variables have been linked to substance use behavior and may assist in explaining treatment retention and engagement for Latino adolescents.

Purpose of Current Study and Hypotheses

The purpose of the current study is to investigate the influence that cultural variables have in explaining treatment retention and engagement in sample of male Latino adolescents, primarily of Mexican descent, and largely recruited from juvenile justice. The study of Mexican American adolescent males with substance use problems involved in juvenile justice is a pressing need because they are overrepresented in this system (Mendel, 2011). For example, approximately 72% of the 1.5 million youth who have contact with the U.S. juvenile justice system each year are male (Puzzanchera, Adams, & Hockenberry, 2012) and it is estimated that 20% of these youth are Latino (Mendel, 2011). Further, more than half (56%) of the male youth in juvenile justice are estimated to have a substance use problem (Chassin, 2008). Our hypotheses are designed to test the influence that the cultural variables of ethnic identity, familism, and acculturation have on treatment retention and engagement. We include these specific cultural variables due to the links that have been identified with emotional/behavioral functioning and substance use behavior (Castro & Alarcon, 2002; Umaña-Taylor, 2011; Umaña-Taylor & Updegraff, 2007; Vega & Gil, 1999) for Latino youth. For the first hypothesis, we predict that cultural variables will influence treatment retention in the following ways: a) higher levels of ethnic identity and familism will positively influence retention, whereas b) higher levels of acculturation will negatively influence retention. Similarly, for the second hypothesis we predict that cultural variables will influence treatment engagement in the following ways: a) higher levels of ethnic identity and familism will positively influence engagement, whereas b) higher levels of acculturation will negatively influence engagement. The hypotheses are based on prior findings in the research literature that suggest higher levels of ethnic identity and familism serve as protective factors, whereas higher levels of acculturation serve as a risk factor in relation to substance use behavior for Latino adolescents (Lawton & Gerdes, 2014; Umaña-Taylor, 2011; Vega, 1990; Vega & Gil, 1999); we extrapolate these prior research findings to investigate their role in explaining treatment retention and engagement.

Method

Description of Participants

Adolescents in this study (N=96) were recruited as part of a larger set of studies examining the cultural accommodation of substance abuse treatment for Latino adolescents and randomly assigned to one of two group-based cognitive-behavioral treatment conditions for substance abuse (see Burrow-Sánchez, Minami, & Hops, 2015; Burrow-Sánchez & Wrona, 2012). The original data included nine females but information from these cases were dropped due to the limited ability to generalize from such a small sample of female adolescents, as well as the fact that male adolescents are overrepresented in juvenile justice (Mendel, 2011; Puzzanchera et al., 2012). Part of the inclusion criteria for the larger set of studies was that all adolescents were between the ages of 13-18, identified as Latino or Hispanic and met DSM-IV-TR (American Psychiatric Association, 2000) diagnostic criteria for a substance abuse or dependence disorder within the past 12 months. Adolescents were paid $20 via gift cards for completing the baseline assessments. Participants under the age of 18 were required to provide assent and parental consent prior to participation; all participant procedures for this study were approved by the Institutional Review Board at the institution of the first author.

Description of Treatment

The two treatment conditions consisted of either a standard cognitive-behavioral treatment (S-CBT) or its culturally accommodated cognitive-behavioral (A-CBT) equivalent; in general, both treatments were similar except that the A-CBT integrated cultural variables relevant to Latino adolescents. Treatment groups met weekly for 90-minutes over 12-week periods. The reader is referred to our prior work (see Burrow-Sánchez, Martinez, Hops, & Wrona, 2011; Burrow-Sánchez, Minami, et al., 2015; Burrow-Sánchez & Wrona, 2012) for greater detail of the larger treatment studies, in general, and descriptions of the treatments, in particular.

Measures

All measures described below were available from their respective authors or publishers in English and Spanish and administered by trained bilingual research assistants. The majority of adolescents (98%) preferred completing the measures and verbal interactions with staff in English.

Timeline Follow Back (TLFB)

Substance use for all participants was measured using the TLFB (Sobell & Sobell, 1992) which is a semi-structured interview that records substance use over a specified period of time. The TLFB utilizes a calendar format to help individuals remember their history and patterns of substance use. It has been used extensively with adolescents and appropriate psychometric properties have been established (Dennis, Funk, Godley, Godley, & Waldron, 2004; Sobell & Sobell, 2003). The number of days alcohol and other drugs (excluding tobacco) were used in the 90 days prior to baseline assessment was calculated for the analysis in the current study; to reduce skew, this variable was log-transformed prior to analysis.

Youth Self-Report (YSR) – Externalizing Scale

The YSR is a well-used instrument with adolescent samples to measure behavioral problems across a number of domains (Achenbach, Dumenci, & Rescorla, 2002; Achenbach & Rescorla, 2001). The YSR consists of 112 items and participants are asked to rate their responses to potential behavioral problems on a 3-point Likert-type scale that ranges from “0-Not True” to “2-Very True or Often True” based on the past six months. From the complete YSR measure nine subscales and three overall scales can be derived. While the complete measure was administered to adolescents, only the externalizing scale (EXT) was used in the analysis for the present study. Examples of items from the externalizing scale include: “I drink alcohol without my parents’ approval” and “I destroy my own things.” Internal consistency for adolescents on the EXT scale was α = .868.

The Multi Ethnic Identity Measure (MEIM)

The MEIM is a widely used measure of ethnic identity for adolescents (Phinney, 1992; Phinney & Ong, 2007). A modified 12-item version of the MEIM was used in this study that has been tested via confirmatory factor analysis with Latino adolescents (see Burrow-Sánchez, 2014). The items asked adolescent participants to indicate their attitudes and behaviors related to their ethnic identity group on a “1 – Disagree” to “5 – Agree” scale. Contemporary views of ethnic identity consider it to be a bi-dimensional construct and Phinney and Ong (2007) suggest that the measure be scored by reducing it to two 3-item subscales: a commitment (COM; items 6, 7, and 12) scale that measures a sense of personal affiliation to an ethnic group and an exploration (EXP; items 1, 2, and 8) scale that measures behavior related to seeking information about an ethnic group. An example of an item from the COM scale is, “I feel I identify with the ethnic group I belong to,” and an example of an item from the EXP scale is, “I have dedicated time to find out more about my ethnic group, such as history, tradition, and customs.” Following the suggestion provided by Phinney and Ong scores from six items were extracted from the larger measure and then averaged to produce two 3-item scores for each participant. Internal consistency for the exploration and commitment subscales in the current study was α = .730 and α = .778, respectively.

Familism Scale (FS)

The FS is a 14-items instrument used to measure the construct of familism based on the factors of obligations, perceived support, and family as referents (Sabogal et al., 1987). Versions of this scale have been used in prior research with Latino youth (see Lorenzo-Blanco, Unger, Ritt-Olson, Soto, & Baezconde-Garbanati, 2013; Morcillo et al., 2011; Unger et al., 2002). Participants rate their agreement to items on a scale ranging from “1 – Very Much in Disagreement” to “5 – Very Much in Agreement.” Examples of items from the scale include: “Children should live in their parents’ home until they get married” and “A person should share his/her home with uncles, aunts, or first cousins if they are in need.” Scores from individual items were averaged to obtain a total score. Internal consistency for this sample was α = .820.

Acculturation Rating Scale for Mexican Americans-II (ARSMA-II)

The ARSMA-II is one of the most widely used measures of acculturation for Latino adults and adolescents (Cuéllar, Arnold, & Maldonado, 1995). It has demonstrated good reliability and strong construct and discriminant validity in research with Mexican American samples (Cuéllar et al., 1995) and has been tested via confirmatory factor analysis for Latino adolescents with substance use disorders (see Burrow-Sánchez, Ortiz-Jensen, Coralles, & Meyers, 2015). Participants rate their responses to items on a scale ranging from “1 – Not at all” to “5 – Extremely often or always.” The 13-item Anglo Oriented Subscale (AOS) and the 17-item Mexican Oriented Subscale (MOS) were scored separately for participants by averaging the items on each subscale in accordance with Cuéllar et al., (1995) and a bi-dimensional view of acculturation (Berry, 2006). Examples of items from each scale include: AOS “I have difficulty accepting some ideas held by some Mexican Americans” and MOS “My friends, while I was growing up, were of Mexican origin.” Internal consistency was α = .707 and α = .850 for AOS and MOS subscales, respectively. Cuéllar et al. also provides a linear method for calculating an overall acculturation score by subtracting participant mean scores of the AOS from the MOS; the participants’ acculturation score is then used to place them in one of five categories across a continuum that ranges from less acculturated on one end to more highly acculturated on the other with those more toward the center labeled as bi-cultural. For the sake of parsimony, we chose to collapse the five categories into three which resulted in placing the sample in the following categories: 39% were more Mexican oriented or less acculturated, 48% were bi-cultural, and 14% were more Anglo oriented or highly acculturated.

Retention - Number of Sessions Attended

Retention was measured by the total number of treatment sessions attended by each adolescent. A session was considered to be attended if the adolescent was present for the majority of the 90-mintue treatment session, typically 75-minutes or more. Attendance was closely monitored and recorded by therapists at the end of each session. Participant attendance was also discussed as part of the weekly supervision provided to therapists. The mean (SD) and median number of treatment sessions attended were 8.95 (3.16) and 10, respectively; range 0-12.

Engagement - Number of Practice Sheets Completed

Engagement was measured by the total number of practice sheets completed by each adolescent over the course of treatment. Practice sheets were administered to adolescents by therapists at 11 of the 12 treatment sessions. The sheets provided adolescents with an opportunity to practice treatment-related skills between sessions and then report on their progress at the next session; successful completion of practice sheets required the adolescents’ attention to the in-session treatment content as well as application of material outside of session. The completion of practice sheets was used as a behavioral indicator of adolescent participation in treatment. Practice sheets were provided to adolescents on standard 8.5×11 inch sheets of paper that could be completed with a pen or pencil. A practice sheet was considered complete if the therapist judged that the majority of it, typically 75% or more, had reasonably been completed by an adolescent. Therapists also judged the quality of work on practice sheets compared to that typically expected given a particular adolescents’ chronological age and, if known, reading ability. Practice sheet completion was also discussed as part of the weekly supervision provided to therapists. The mean (SD) and median number of practice sheets completed were 5.08 (3.11) and 5, respectively; range 0-11.

Analytical Plan

The dependent measures in this study (i.e., total number of sessions attended and number of practice sheets completed) are count variables. These types of variables generally follow a Poisson, rather than a normal, distribution and are most appropriately analyzed using generalized linear methods (see Coxe, West, & Aiken, 2009). The independent variables in this study are covariates (i.e., baseline substance use and externalizing behavior) and baseline cultural variables of interest (i.e., ethnic identity, familism, acculturation). More specifically, the following predictors (in order and coded by measure acronym): treatment condition (TXC), age, TLFB, EXT, EXP, COM, FS, AOS, and MOS were used in the regressions. Controlling for baseline substance use and externalizing behavior in the generalized regression models allowed us test for the variance in outcomes attributed to the cultural variables of interest. We grand mean centered all predictors with the exception of TXC to ease interpretation of the models (Hedeker & Gibbons, 2006); TXC was included as a covariate in all models to control for any influence that assignment to a specific treatment condition had on participant outcomes. Two generalized linear regressions were conducted in order to test each dependent variable (i.e., retention or engagement) but the same independent variables were included in both models. Further, the subscales for ethnic identity and acculturation were included in the models so that these constructs could be tested bi-dimensionally; this type of bi-dimensional analysis is frequently suggested in the literature but infrequently conducted in practice (see Burrow-Sánchez, Ortiz-Jensen, et al., 2015; Phinney & Ong, 2007).

Results

Preliminary Analyses

The mean age of adolescents in the analysis was 15.29 (SD=1.31) and the majority had parents of Mexican descent (77%; see Table 1 for more participant demographics). The majority of study referrals was received from juvenile justice probation officers (68%) or case managers (30%) and was mandated (69%) to attend substance abuse treatment. Finally, 55% and 45% of adolescents met DSM-IV-R criteria for a substance abuse or dependence disorder, respectively, within the past 12 months. See Table 1 for additional participant demographics.

Table 1.

Participant Demographics (N=96)

Variable Mean (SD) or Percent
Adolescent Demographics
    Mean Age 15.29 (1.31)
    Mean Grade 10 (1.31)
    Language Spoken at Home
        Spanish 68%
        English 17%
        Both 11%
    Birth Country
        U.S. 63%
        Mexico 34%
        Othera 3%
Parent Demographics
    Mother Birth Country
        Mexico 73%
        U.S. 16%
        Othera 10%
        Unknown 1%
    Father Birth Country
        Mexico 81%
        U.S. 4%
        Othera 10%
        Unknown 4%
Annual Family Income
    $25,000 or less 73%
    $25,000-$45,0000 20%
    $45,000 or more 6%
    Did not respond 1%
Drug Use at Baseline
    Alcohol 71%
    Marijuana 88%
    Tobacco 52%
    Otherb 44%
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Note.

a

Other = South American country

b

Other = hallucinogens, cocaine, opiates, inhalants, prescription meds, etc.

Predictors of Retention and Engagement

Inspection of the means (8.73 and 4.92) and variances (10.66 and 9.61) for retention and engagement, respectively, indicated they were not equal and that dispersion was present (see Stroup, 2013). Minor violations of the mean-variance equality assumption (i.e., low dispersion) can be addressed with a Poisson model that includes a dispersion correction factor but larger violations generally require the use of a negative binomial model. Following this logic, we conducted a Poisson regression for the retention DV and a negative binomial regression with the engagement DV.

The first model included retention as the DV and the fit statistics indicated a Pearson χ2 of 95.06 (df = 86, Pearson χ2/df = 1.11); the Pearson value over its degrees of freedom is an indicator of overall model fit with ratios closer to 1 reflecting a perfect fit. To account for minor dispersion in the DV we included a Pearson correction factor in the model that adjusts standard errors. Results of the analysis are presented in Table 2 and indicate that EXP (β = 0.04, p = .03), and FS (β = 0.01, p =.0007) significantly predicted retention as did Anglo orientation (β = −0.20, p = .006) but in the opposite direction. Poisson models produce coefficients that are interpreted as the predicted logarithm of counts of the DV (see Coxe et al., 2009). For example, coefficients for the first model represent the predicted change in the logarithm of counts for retention for a 1-unit change in the predictor; however, exponentiation of the coefficients places them on the scale of the original count variable (i.e., number of sessions attended) and subsequently eases interpretation. Therefore, the exponentiated coefficients (see Table 2) are used for the interpretation of all model results. The value of the intercept in model predicts that participants will attend 8.03 sessions when all other terms are zero. However, for Poisson-based analysis, the remaining terms in the model represent a multiplicative change in the DV for a 1-unit change in the predictor (see Coxe et al., 2009). Applied to model one, this indicates that for every 1-unit change in EXP the number of sessions attended is multiplied by a factor of 1.04; thus, for every 1-unit change in EXP participants are predicted to attend 8.35 (i.e., 8.03 × 1.04 = 8.35) treatment sessions. Similarly, for every 1-unit change in FS participants are predicted to attend 8.11 (i.e., 8.03 × 1.01 = 8.12) treatment sessions. In contrast, a 1-unit change in AOS predicts that participants will attend 6.58 (i.e., 8.03 × 0.82 = 6.58) treatment sessions.

Table 2.

Poisson Model for Treatment Retention

Parameter Estimate SE EXP (E)a 95% Confidence Interval
Lower Bound Upper Bound
Intercept 2.08*** 0.12 8.03 1.85 2.32
TXCb 0.06 0.08 1.06 −0.09 0.21
Age 0.001 0.03 1.00 −0.06 0.06
TLFBc −0.09 0.07 0.92 −0.23 0.06
EXTd 0.0004 0.005 1.00 −0.009 0.009
EXPe 0.04* 0.02 1.04 0.003 0.07
COMf 0.001 0.02 1.00 −0.03 0.03
FSh 0.01** 0.005 1.01 0.003 0.02
AOSi −0.20** 0.07 0.82 −0.35 −0.06
MOSj −0.008 0.06 0.99 −0.12 0.11
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*

p<.05

**

p<.01

***

p<.0001

Note.

a

Exponentiation of the estimate

b

TXC = Treatment Condition

c

TLFB = number of days (log transformed) used alcohol or other drugs (excluding tobacco) in past 90 reported at baseline assessment

d

EXT = externalizing scale of the Youth Self Report

e

EXP = exploration subscale

f

COM = commitment subscale

h

FS = familism scale

i

AOS = Anglo Orientation Scale

j

MOS = Mexican Orientation Scale.

The second model included the same predictors as the first, but the DV was changed to engagement and a negative binomial regression was used due to the rationale presented above. The second model produced a Pearson χ2 of 89.79 (df = 86, Pearson χ2/df = 1.04). The exponentiated value of the intercept (see Table 3) indicates that participants are predicted to complete 4.36 practice sheets when all other terms are zero. For every 1-unit change in EXP participants are predicted to complete 4.71 practice sheets (i.e., 4.36 × 1.08 = 4.71). In contrast, for 1-unit changes in TLFB and AOS participants are predicted to complete 3.4 (i.e., 4.36 × 0.78 = 3.4) and 3.1 (i.e., 4.36 × 0.71 = 3.1) practice sheets, respectively.

Table 3.

Negative Binomial Model for Treatment Engagement

Parameter Estimate SE EXP (E)a 95% Confidence Interval
Lower Bound Upper Bound
Intercept 1.47*** 0.20 4.36 1.08 1.86
TXCb 0.07 0.13 1.07 −0.18 0.32
Age 0.05 0.05 1.05 −0.05 0.15
TLFBc −0.25* 0.12 0.78 −0.49 −0.008
EXTd −0.0008 0.004 1.00 −0.02 0.01
EXPe 0.08* 0.03 1.08 0.02 0.13
COMf 0.03 0.03 1.03 −0.02 0.09
FSh 0.01** 0.008 1.01 −0.004 0.03
AOSi −0.35** 0.13 0.71 −0.59 −0.10
MOSj 0.03 0.10 1.03 −0.16 0.23
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*

p<.05

**

p<.01

***

p<.0001

Note.

a

Exponentiation of the estimate

b

TXC = Treatment Condition

c

TLFB = number of days (log transformed) used alcohol or other drugs (excluding tobacco) in past 90 reported at baseline assessment

d

EXT = externalizing scale of the Youth Self Report

e

EXP = exploration subscale

f

COM = commitment subscale

h

FS = familism scale

i

AOS = Anglo Orientation Scale

j

MOS = Mexican Orientation Scale

Discussion

The goal of the current study was to investigate how cultural variables influence retention and engagement in substance abuse treatment for a sample of Latino adolescents primarily of Mexican descent and largely recruited from juvenile justice. Overall, the results indicated that adolescents who were in the exploration phase of ethnic identity, and reported a stronger sense of familism, had higher rates of retention and engagement in substance abuse treatment. In contrast, adolescents who reported higher levels of acculturation to the dominant culture (i.e., Anglo orientation) had lower rates of retention and engagement in treatment.

The exploration component of ethnic identity, rather than the commitment component, positively influenced treatment retention and engagement. These findings may be due, in part, to the fact that adolescence is a critical period of development when youth are faced with many tasks and challenges that encourage exploration of their identities. However, youth from ethnic minority backgrounds must accomplish the typical developmental tasks of adolescence while concurrently exploring their sense of self as a member of a non-dominant group (Erikson, 1997; Umaña-Taylor & Updegraff, 2007). In other words, adolescence is a key time for ethnic minority youth to seek out information regarding their identity as a person and as a member of an ethnic group. The treatment groups attended by adolescents in the current study were entirely composed of youth who identified as Latino/Hispanic and largely of Mexican descent which may have served to provide safe venues for exploring ethnic identity, which subsequently promoted higher retention and engagement. In contrast, it may not be reasonable to expect that Latino youth in middle adolescence (i.e., ages 14 to 16) have yet developed a strong commitment to their ethnic identity because exploration may be more salient during this developmental period (Berry et al., 2006).

Familism also positively influenced treatment retention and engagement for adolescents in our sample. These findings may suggest that Latino families who continue to exert a positive influence on their children during adolescence may buffer some of the negative effects attributed to peers (Dishion & Owen, 2002; Duncan, Duncan, & Hops, 1994; Umaña-Taylor & Guimond, 2010). More specifically, families with higher levels of familism may view drug use by its members from a collective prospective, rather than viewing it as an individual problem (Vega, 1990; Vega & Gil, 1999). Following this logic, the family system may exert pressure and provide support for its adolescent members to resolve the drug problem (i.e., attend and engage in treatment) because it viewed as affecting the entire family.

In contrast to findings just described, higher levels of affiliation to the dominant culture (i.e., Anglo orientation) negatively influenced treatment retention and engagement for adolescents in the study whereas affiliation to the Mexican culture was unrelated to retention or engagement. These findings may suggest that Mexican American adolescents with more affiliation toward the dominant culture experience less connection and cohesion from participating in treatment groups with their less acculturated peers. The level of cohesion is an important element to consider in group treatment participation and outcomes (see Burlingame, McClendon, & Alonso, 2011), and subsequently, less connection with peers could lead to lower motivation to attend and engage in treatment. Based on the combined ARSMA-II scores slightly more than 60% of the sample were in bicultural (48%) or highly acculturated (14%) categories compared to 39% in the less acculturated category. These proportions suggest that, overall, the sample was more highly acculturated which could help to explain the lack of findings for the Mexican orientation scale.

Finally, we found that higher baseline levels of substance use negatively influenced treatment engagement for adolescents in the study. This finding is partially consistent with other research (see Grella et al., 2001; Shane et al., 2003), and may suggest that adolescents with severe pretreatment substance use problems require more intensive engagement strategies than standard outpatient treatments typically provide (see Ozechowski & Waldron, 2008). This is important to consider with the fact that adolescents are most likely to receive outpatient treatment for substance abuse problems (SAMHSA, 2009). We also found that externalizing behavior did not predict either treatment retention or engagement for adolescents. This may be due to the fact that the adolescents in our study were not formally diagnosed with an externalizing disorder, and subsequently, their externalizing behaviors may not have reached a threshold to influence retention and engagement similar to other studies (Austin & Wagner, 2010; Grella et al., 2001; Shane et al., 2003).

Findings from the current study suggest two important clinical implications that we encourage practitioners to consider. First, we found that specific cultural variables do indeed influence treatment retention and engagement for Latino adolescents. Based on these findings, practitioners may want to consider measuring cultural variables for Latino adolescents as part of a pretreatment assessment. For example, scores on measures of cultural variables, such as ethnic identity and acculturation, may assist practitioners in assigning adolescents to treatment groups with peers who share similar cultural perspectives. Second, the study findings suggest that placing adolescents together in groups who all share common identity labels, such as Latino or Hispanic, may not always be the best approach. This second implication underscores the point that differences in perspective can exist even when adolescents share a common racial or ethnic identity label. For example, a practitioner cannot assume that two adolescents who both identify as Latino share the same perspective, orientation or world-view toward their culture of origin or the host culture. It may be that ethnic minority adolescents benefit more from being in treatment groups with peers who share similar cultural perspectives rather than similar identity labels.

As with any study there are certain limitations that need to be considered. First, the sample size in this study was modest, which limits the statistical power we had to detect the influence of cultural variables, and thus, recommend that future research be conducted with larger samples of Latino adolescents. Second, adolescents in this study were primarily of Mexican descent, male, and juvenile justice involved which limits generalizability to other Latino subgroups (e.g., Puerto Rican, Cuban) and females who do not have contact with the justice system. Future research that includes females and samples from other Latino subgroups that are not justice-involved is needed to replicate the current findings. In addition, future research that examines the influence of cultural variables on treatment outcomes for other racial and ethnic minority adolescent groups (e.g., African American, American Indian) is needed. Finally, this study focused on group-based outpatient treatment and other studies should be conducted that investigate the influence of cultural variables for other treatment modalities (i.e., individual, family) and settings (i.e., residential, in-patient) for racial and ethnic minority adolescents.

The goal of the current study was to investigate the influence of specific cultural variables on treatment retention and engagement in sample of male Latino adolescents, primarily of Mexican descent, and largely recruited from juvenile justice. The major results of the study indicated that adolescents in the exploration phase of ethnic identity, and reporting higher levels of familism, had higher retention and were more engaged in treatment. In contrast, adolescents who reported more orientation toward the dominant culture (i.e., Anglo orientation) had lower retention and were less engaged. Clinical implications of these findings suggest that practitioners may want to consider cultural perspectives in addition to identity labels (e.g., Latino, Hispanic) when assigning Latino adolescents to group treatments. Future research should replicate the findings in the current study with larger samples of adolescents from both genders and across other Latino subgroups (e.g., Puerto Rican, Cuban).

Acknowledgements

This research was supported by Award Number K23DA019914 from the National Institute on Drug Abuse awarded to the first author. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Drug Abuse or the National Institutes of Health.

The authors wish to thank all members of the Validating Interventions for Diverse Adolescents (VIDA) Research Team at the University of Utah.

Footnotes

1

Both studies utilized portions of the same sample and we only report on the most recent study; however, findings from both studies did not indicate a relation between cultural variables and treatment attrition/retention.

2

The authors did not explicitly indicate in either study the Latino subgroup composition of their samples. Since the samples were recruited in the Southwest portion of the U.S. (i.e., Florida) it is assumed they were mostly of Puerto Rican or Cuban descent.

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