Testing Mediational Processes of Substance Use Relapse Among Youth Who Participated in a Mobile Texting Aftercare Project

Abstract

Background:

The goal of this paper is to advance the understanding of mechanisms of action involved in behavioral-driven aftercare interventions for substance use disorders (SUDs) among youth populations. This paper reports data from a study that measured the impact of an aftercare intervention on primary substance use relapse among youth who completed treatment in Los Angeles County for SUDs.¹ The aftercare intervention, Project ESQYIR-Educating and Supporting inQuisitive Youth In Recovery, utilized text messaging to monitor relapse and recovery processes, provide feedback, reminders, support, and education among youth from SUD specialty settings during the initial three-month period following treatment completion.

Method:

Mediational modeling informed by Baron and Kenny was used to examine the extent to which select recovery processes including participation in extracurricular activities and self-help, were impacted by the texting intervention, and if such processes helped sustain recovery and prevent primary substance use relapse.² The data come from a two-group randomized controlled pilot study¹ testing the initial efficacy of a mobile health texting aftercare intervention among 80 youth (M_age= 20.7, SD = 3.5, range: 14-26 years) who volunteered to participate after completing SUD treatment between 2012 and 2013.

Results:

Among the two recovery processes examined in the mediational modeling, only involvement in extracurricular activities mediated the effects of the texting aftercare intervention on reductions in primary substance use relapse; not self-help participation.

Conclusion:

Findings from this pilot study offer greater understanding about potential recovery-related mechanisms of action of mobile aftercare interventions. Mobile texting was found to promote increased engagement in recovery-related behaviors such as participation in extracurricular activities, which mediated the effects of the mobile aftercare intervention on decreasing primary substance use relapse. Findings suggest mobile approaches may be effective for increasing adherence to a wide-array of recovery behavioral regiments among youth populations challenged by complex behavioral issues.

INTRODUCTION

Recovery from substance use disorders [SUDs] is a complex phenomenon, especially among youth populations under the age of 24 years old. In 2016, approximately half a million youth ages 12 to 25 received treatment for substance use issues at a specialty facility in the United States.³ Treatment studies that investigate post-treatment youth outcomes indicate that although benefits exist, (i.e., positive changes in substance use and psychosocial outcomes) such benefits quickly diminish post-treatment.⁴ Studies show that 65-70% of youth relapse to their primary drug(s) during the initial 3 months after treatment and two-thirds move in and out of treatment during the subsequent year, with relapse rates rising to 80% within the 12-month post-treatment period.^4-7 Hence, increasing the rate of recovery from SUDs among youth is a long-standing public health goal.

Historically, the SUD system of care has operated under a federal block grant funding platform that primarily covers prevention and specialty treatment services. For this reason, services for treating SUDs have been limited in scope, consisting of short-lived clinical regiments that target “completion” and “abstinence” as gold standard outcomes, with recovery support services being limited to participation in community-based, mutual, self-aid recovery groups.^8,9 These groups are peer-directed by individuals in recovery and structurally not set up as clinical interventions. Although there are not many well-established or systematic attempts at evaluating the effectiveness of these mutual self-aid recovery programs, a growing base of research has been accumulating on mediators or “mechanisms” of participating in mutual aid/support groups that lead to positive recovery outcomes (i.e., enhanced social support, replacing substance-using friends/networks with non-using networks, strengthened commitment to abstinence, and greater spiritual and altruistic focus).¹⁰ Despite the potential benefits, less than 10% of youth participate in these mutual self-aid recovery groups.¹¹ Factors contributing to low participation/adherence and early termination in recovery aftercare services among youth include stigma and shame related to legal and moral implications of having a SUD, underlying notions of life-long disease, total abstinence, a one-size-fits-all approach to recovery, and relinquishing personal control associated with traditional recovery 12-step models.^11-14 Such recovery support models place individuals in a disease state rather than a wellness state, and give youth an identity of lifelong addiction.^13,15,16

In recognition of SUD recovery challenges the field has faced, there have been various attempts at improving the SUD system of care in terms of recovery support. The Substance Abuse and Mental Health Services Administration (SAMHSA) has established a working definition of SUD recovery that is characterized as a process of self-directed lifestyle change geared towards the pursuit of health and wellness that is highly personal (i.e., can occur through many pathways), with potential setbacks that are associated with life events/experiences.¹⁷ This working definition of recovery provides insight about what effective aftercare services should look like, such as aiming to promote continual growth and improvement in one’s health and wellness, facilitating ongoing monitoring, and building in clinical intervention set points to address any setbacks that may occur.¹⁸ Furthermore, it places the emphasis not on sobriety alone, but on the development and maintenance of health and the social processes of the recovery lifestyle, such as engaging in alternative health-promoting behaviors, which ultimately increases an individual’s intrinsic desire for sobriety.¹⁸

Currently, in the state of California, under the Medicaid 1115 Waiver pilot program, individuals in SUD treatment are now eligible to receive fully-covered recovery support services under the Drug Medi-Cal Organized Delivery System effort taking place. These recovery support services are alternative approaches to the traditional mutual self-help recovery groups and are based on the current definition of recovery as an individual process that address important dimensions of recovery beyond sobriety: health/wellness, community, and purpose. These recovery support services have been shown to be effective practices for both youth and adult populations alike by empirical research.^19-26 See Table 1 for the types of recovery support services now included in Drug Medi-Cal Service delivery benefit packages to youth and adults receiving SUD treatment.

Table 1.

Recovery Support Services

Outpatient Counseling	individual or group services
Recovery Monitoring	recovery coaching, monitoring
Substance Abuse Assistance	peer-to-peer services and relapse prevention
Family Support	linkages to childcare, parent education, child development support services, family/marriage education
Support Groups	linkages to self-help and support, spiritual and faith- based support
Education and Job Skills	linkages to life skills, employment services, job training, and education services)
Ancillary Services	linkages to housing assistance, transportation, case management, individual services coordination

One area of growing interest is the uptake of recovery support services among youth populations. A theme in youth aftercare research literature is that developmental and cultural factors play a large role in influencing the low participation, poor compliance, and early termination/drop out commonly observed among youth populations,^11,16,27 which greatly correlate with relapse risk (ranging from 65-80%) during the initial year post-SUD treatment.^5,25,28 Examining the extant literature, alternative aftercare approaches that have been developed for youth have focused on addressing important “relapse risk factors” that have been identified in treatment outcome studies, including: 1) addressing cognitive risk factors, such as intrinsic motivation for change; 2) addressing emotional risk factors, such as coping skills for relapse prevention; 3) addressing behavioral risk factors, such as engagement in prosocial, positive alternative behaviors, i.e., self-help and extracurricular activities; and 4) addressing social support that facilitates recovery.^19,29-35

Given this, there has been increasing attention to developing interventions that promote the engagement in alternative recovery lifestyle behaviors that encourage participation in non-drug using activities, commonly referenced as positive social and community activities or prosocial activities among youth.^36-38 Involvement in prosocial activities are encouraged given that research supports that recovery-relapse patterns of use and treatment-re-entry is linked to being exposed to “high risk” environments without ongoing “structure.”^39,40 Specifically, research shows that critical intervention elements for facilitating personal control over behavior change (self-regulation) reinforces the adoption of alternative healthy behaviors.⁴¹

Significant advances in the use of technology, such as web-based applications, e-learning, text-messaging, and mobile apps within health care settings have been used for addressing complex chronic diseases and promoting wellness among youth, given the widespread use of technology within this population.^42-45 Exploring recovery needs among treatment-involved youth, research has found that mobile texting for aftercare using an individualized wellness care approach is highly feasible and culturally appropriate for youth.¹ Gonzales et al. subsequently developed Project ESQYIR-Educating and Supporting inQuisitive Youth in Recovery, a mobile texting aftercare program that emphasizes recovery as a behavior change process that is self-determined to align with youth-based conceptualizations of SUD recovery.^1,12,13 Project ESQYIR adapted key empirical components of effective self-management aftercare programs used in health care disease management programs to address SUD recovery remission complexities among youth.⁴⁶ Project ESQYIR, a randomized controlled pilot study, was conducted among youth who completed treatment for SUDs and showed initial efficacy for reducing substance use relapse and sustaining effects over time from study admission to 3-month, 6-month, and 9-month follow-ups.^1,47

This paper will explore and identify important mechanisms of aftercare interventions that mediate the positive outcomes observed in this study. Specifically, in a mediational modeling analysis, the following predictive pathways are tested: 1) does the intervention lead to greater participation in self-help and extracurricular activities?; 2) do these two factors predict substance use outcomes?; and 3) if the first two are true, do self-help attendance and extracurricular activities mediate the positive effect of the intervention on SUD outcomes? The theoretical underpinnings of the mediational model are shown in Figure 1.

FIGURE 1.

Theoretical mediational model.

METHOD

Participants

A total of 80 youth (mean age = 20.4, SD = 3.5, range 14-26 years old) voluntarily participated in Project ESQYIR after completing treatment for SUDs from community-based outpatient and residential programs in Southern California between 2012 and 2014. Most youth were male (71.3%), Caucasian (42.5%) or Latino (37.5%) and received treatment for the following primary SUDs: marijuana (36.3%), methamphetamine (28.7%), cocaine (16.3%), heroin (11.3%), prescription drugs (5.0%), and alcohol (2.5%). Follow-up retention rates at discharge for the pilot study approximated 95%. Table 2 provides demographic and behavioral details associated with youth who participated in the pilot aftercare program.

Table 2:

Participant Characteristics

	Texting Group (N=40)	Aftercare as Usual Group (N=40)
Age: Average age of the youth participants was 20.7 (SD = 3.50), ranging from 14 to 26 years old.	22.13 (54.03%) SD = 3.09 Range: 15-29	18.83 (45.97%) SD = 3.09 Range: 14-26
Gender
Female	15 (37.5%)	8 (19.5%)
Male	25 (62.5%)	33 (80.5%)
Ethnicity
Latino	10 (25.0%)	20 (48.8%)
Non-Latino White	22 (55.0%)	13 (31.7%)
Black	4 (10.0%)	4 (9.8%)
Asian	3 (7.5%)	4 (9.8%)
Am Indian	1 (2.5%)	0 (0.0%)
Employed (%)	16 (40.0%)	14 (34.1%)
Primary Substance Use (%)*
Marijuana	9 (22.5%)	20 (48.8%)
Heroin	5 (12.5%)	4 (9.8%)
Meth	15 (37.5%)	8 (19.5%)
Cocaine	6 (15.0%)	7 (17.1%)
Alcohol	2 (5.0%)	1 (2.4%)
Other	3 (7.5%)	1 (2.4%)
Current Tobacco Use (%)	24 (60.0%)	28 (68.3%)

^*Percent that reported primary substance use measured at SUD treatment completion.

Procedures

Under the approval of the Institutional Review Board (IRB) of Azusa Pacific University, youth were recruited to participate in the pilot aftercare project using the following inclusion criteria: 1) identified as “youth” (either adolescent or young adult); 2) a candidate for transitioning into aftercare (i.e., completing their prescribed SUD treatment regimen) as determined by the youth’s SUD counselor; and 3) owned a mobile phone with SMS texting capabilities. Exclusion criteria included: unwilling to comply with the aftercare study procedures, such as responding to a daily text of monitoring and receiving feedback, reminders, support and education; and evidence of psychiatric/medical conditions that warranted further primary treatment. Recruitment into the aftercare project consisted of IRB-approved study flyers posted throughout SUD treatment facilities and regular announcements by research staff at the facilities. Study staff met with interested youth and parents on-site in a private office to conduct eligibility screening and obtain study consents. After consenting, youth were randomized using a random number generator to one of two study conditions: the mobile texting intervention group (n=40) or an aftercare-as-usual comparison group (n=40).

Mobile Texting Intervention Group.

Youth assigned to the mobile texting intervention group received text messages throughout the 12 week duration of the aftercare program that included the following disease management components: monitoring, feedback, reminders, support/education.

The mobile texting intervention protocol consisted of sending text messages within each of these components following a specific schedule over a 12-week time frame (see Table 3). The content and schedule of the texting intervention was determined using prior feasibility research with youth in treatment about perceptions and needs.⁴⁸ Each of the texting intervention components contained a pre-developed text message sent automatically, once per day, at pre-determined times. As shown in Table 3, under the monitoring component, the text message asked the youth about different areas of relapse symptoms that are important to SUD remission, i.e., abstinence self-efficacy/confidence, negative mood, stress, recovery behaviors, and continued substance use. These monitoring texts were sent each day at 4:00pm. After the youth responded to the monitoring text, they received a “feedback” text that included positive appraisal, motivational, or inspirational/encouragement. Feedback texts were randomly selected from a message bank based on pre-determined rules to follow their responses. An example of a monitoring-feedback scenario for recovery behaviors-recovery promotion would be: [Monitoring text] “How many days in the past week did u feel stressed or have negative emotions (Text 0-7)?” Participant texts back a 3. [Feedback text] “Think about 2 good things in ur life right now – write them down and focus on those. Ignore everything else.” Reminder texts were sent daily at 12:00 pm. These texts reminded them of the recovery definition: “Today’s a new day in your recovery – think about the lifestyle behavior change goal you are working on…” followed by a recovery tip focused on promoting “alternative recovery lifestyle behaviors” that are considered non-drug using prosocial and community activities, which reinforce SAMHSA’s current definition of recovery. An example of a reminder health wellness tip included: “Write out negative thoughts on a piece of paper, then rip it up!” The support component consisted of a weekend text sent on Saturdays to promote participation in positive, prosocial activities, including self-help groups and extracurricular activities, like skate parks, hiking trails, local YMCAs and parks, farmers’ markets, art museums, etc. tied to their specific geographic areas (using zip codes near their residence), as well as a monthly call by a health coach to discuss case management needs. The education component consisted of weekend texts sent on Sundays specific to the primary substance the youth received treatment for. These social support and educational weekend texts were sent randomly between 9:00am and 9:00pm. Other features of the texting intervention consisted of automated prompts for reminding youth who did not respond to a monitoring text at 7:00pm and 10:00pm the same day. Last, satisfaction texts were sent weekly to participants who remained in the program, asking them to rate their satisfaction with the texts.

Table 3:

Project ESQYIR mHealth Texting Aftercare Program Domain areas of SUD Relapse Self-Management

Monitoring Component	Feedback Component	Reminder Component	Social Support Component	Education Component
Daily Texts sent at 4pm monitoring Relapse Symptoms in important areas related to SUD Remission among Youth: Abstinence Self-efficacy Negative mood Stress Recovery behaviors Continued substance use	Daily Feedback Texts sent after monitoring receipt to youth responses framed around clinically supported evidence based practices that support relapse prevention, including motivational enhancement and coping using: Positive Appraisal Motivational or Inspirational Encouragement Stress management or coping tips	Daily Texts sent at noon reminding youth about recovery definition (lifestyle change in important recovery dimensions including: Career/vocation Healthy living Community (volunteering) Personal meaning (gratitude)	Weekend Texts sent on Saturdays to promote engagement in recovery support behaviors: self help youth specific groups as well as extracurricular activities tailored to the participant’s geographic area. In addition, monthly calls by health coach to discuss areas of recovery needs (case management)	Weekend Text sent on Sundays to provide education tailored to the youths’ primary substance use disorder they completed treatment for.

Aftercare-As-Usual Control Group.

The control group consisted of youth who received standard aftercare as usual provided by the SUD treatment program, which primarily consisted of participation in mutual self-help/12-step groups within the local community. Given that this was the standard of care, no participant received less than treatment-as-usual as a result of being assigned to this condition.

Measures

For this paper, data obtained from study aftercare admission at baseline and study aftercare discharge at 12 weeks included the following variables:

Independent variable.

Treatment condition was a dichotomous variable including either mobile texting intervention [“1”] or aftercare as usual control [“2”], obtained by randomization study records.

Dependent variable.

Relapse from the primary substance that youth received SUD treatment for was the dependent variable, measured dichotomously in terms of any use in the past month during the assessment data point [“0” for no use or “1” for use] as assessed by the Teen Addiction Severity Index⁴⁹ and validated by urinalysis collected from disposable testing cups with temperature strips that were analyzed for methamphetamine/amphetamines, cocaine, opiates, marijuana, and benzodiazepines at the time of data collection. Specifically, relapse to primary substance of abuse was coded as 1 (use) if they had a positive urine screen and self-reported any use in the past month or 0 (no use) if they had a negative urine screen and did not self-report any use in the past month. This method of operationalization allowed for ensuring concordance testing between self-report and urine screens. In the case of a discrepancy between the self-report and the urinalysis, the results from the urinalysis would be used to determine relapse. Research supports good psychometric properties of the T-ASI with strong reliability and validity with the average correlation across scales being 0.78.^49,50 Although the outcome variable is dichotomous, in this analysis it was treated as continuous. For instance, a single individual’s outcome is either “yes” or “no,” but for a group, the individual outcomes can be combined to indicate the probability. For example, if 5 out of 10 people in the control relapse, then the probability of relapsing is .5. This approach is a common practice in psychometrics, especially in item response theory (IRT) and Rasch modeling. Data like the example given above is treated as continuous so that a probabilistic inference can be made (e.g. what is the probability that the individual will experience relapse?).^51,52

Mediating Variables.

The two mediators, participation in self-help and extracurricular activities, were measured by the Brief Addiction Monitor.⁵³ The BAM measure was developed to monitor patient progress of recovery from substance abuse.⁵³ The measure consists of substance use, risk, and protective dimensions. The substance use dimension includes items that measure continued alcohol and drug use; the risk factor dimension measures craving, sleep problems, mood issues, risky situations, and interpersonal problems; and the protective dimension measures aspects of self-help, spirituality, work, school, and income. Research has reported excellent test-retest reliability of BAM (ICC=0.7) and excellent predictive validity for the substance use and risk factor dimensions (Wald chi-square = 4.261; p < .05).⁵³ The specific questions used for this paper to measure prosocial, positive alternative recovery behaviors includes self-help participation as measured by: “In the past 30 days, how many days did you attend self-help meetings like AA or NA to support your recovery?” and involvement in extracurricular activities as measured by: “In the past 30 days, how many days have you done things to help meet your recovery goals such as participating in any extracurricular activities other than AA/NA?”

Statistical Analysis

All analyses were conducted with JMP Pro Version 14⁵⁴ based on 2-tailed tests with p < .05 as the Alpha level. Post hoc power analysis for mixed modeling was conducted in PASS version 14.⁵⁵ Mixed modeling, also known as multilevel modeling or hierarchical linear modeling (HLM), was performed to explore relationships and differences between independent and dependent variables described across different time points (from baseline to discharge). For analyzing longitudinal data, mixed modeling is considered superior to repeated measures ANOVA because the latter must assume compound symmetry, whereas HLM allows the analyst to specify many different forms of covariance structure. In addition, mixed modeling can make accurate estimates despite missing data, while repeated measures use listwise deletion, resulting in bias and lower statistical power.^56-58

Additionally, Baron and Kenny’s approach was employed to test the mediational effects of the predictive pathways.² The mediator was defined as the variable between the dependent (DV) and the independent variables (IV) on a causal pathway. While the cause and effect relationship is unclear, the mediator can explain how and why the IV influences the DV. In this case, in addition to the hypothesis about the effect of the IV on the DV, there are multiple paths and hypotheses among the DV, the IV, and the mediator. Baron and Kenny’s approach examines these hypotheses using the divide and conquer strategy.² Rather than testing all paths and hypotheses simultaneously in one single analysis, the mediation is tested through three models: independent variable predicting the dependent variable; independent variable predicting the mediator; independent variable and mediator predicting the dependent variable. Despite criticism surrounding Baron and Kenny’s method, the research team determined that it is the most appropriate choice for this exploratory study. Alternative methods were considered, including path analysis (structural equation modeling [SEM]), Sobel test, and the empirical M-test. However, given the sample size for SEM is demanding, running SEM for the current data set could render an unstable model. Additionally, the Sobel test would be too restrictive given its strong parametric assumptions and the empirical M-test would have been cumbersome to implement.⁵⁹ It is important to point out that according to Kenny, Kashy, and Bolge, the essential steps in affirming the mediation effect are Steps 2 and 3.⁶⁰ Step 4 does not have to be met unless the expectation is for complete mediation. Hence, in this exploratory study the authors were not intending to look for a full moderating effect, but rather were open to potentially full or partial moderation.

RESULTS

Step 1: Is there a significant relationship between primary substance use outcomes and condition (control vs. intervention)?

Youth participants in the texting aftercare intervention were less likely to relapse from their primary substance between baseline and discharge compared to those in the aftercare-as-usual control condition, F(1, 76.9)=4.22, p = 0.043, with an interaction effect of time and condition, F(1, 74.5)=15.6, p = 0.001. In other words, the probabilities of substance use between the control and the intervention groups are not consistent across time. From baseline to discharge, the control’s probability of substance use increased, where probability of substance use of the intervention group decreased. This interaction is depicted in Figure 2.

FIGURE 2.

The interaction between the condition and the time factors.

Step 2: Is there a significant relationship between condition (control vs. intervention) and potential mediators (self-help and extracurricular activities)?

Youth participants in both conditions reported similar levels of self-help participation and extracurricular activities at baseline. There was no significant difference between the two groups in terms of self-help (t(78) = 1.36, 95%CI (--1.40, 7.50), p = 0.1768) and extracurricular activities (t(78) = −1.03, 95%CI (−6.96, 2.21), p = 0.3057). However, the texting intervention group was more involved in self-help than the control group at discharge, t(1, 76.5) = 4.02, p = 0.048 (see Figure 3a). Further, youth in the mobile texting intervention group reported significantly increased involvement in extracurricular activities from baseline to discharge compared to youth in the control group, who had declining involvement, F(1, 77.1) = 10.41, p = 0.001 (see Figure 3b).

FIGURE 3a.

Self-help means between different conditions across baseline and discharge.

FIGURE 3b.

Extracurricular activity means between different conditions across baseline and discharge.

Step 3: Is there a significant relationship between primary substance use relapse outcomes and the potential mediators (self-help and extracurricular activities)?

Youth reporting greater involvement in both of the proposed mediators (self-help and extracurricular activities) had less primary substance use relapse between baseline and discharge. However, significant effects were only observed for the extracurricular recovery process variable, F(1, 144.1) = 7.91, p = 0.005, but not the self-help recovery process variable, F(1, 138.7) = 3.29, p = 0.07.

Step 4: Does the effect of the condition on the substance use outcome disappear at the presence of the mediator?

The final step estimated both the effects of the intervention on the mediators (step 2) and the effects of mediators on primary substance use relapse (step 3) in the same mixed model. If a mediation effect presents, the effect of condition on substance use would disappear when the mediator is included in the model. Table 4 shows that when study condition and the two recovery process variables are considered in modeling, only extracurricular activity emerged as a significant predictor (mediator) of primary substance use relapse, with both study condition and self-help participation not significant predictors of the outcome. The two potential mediators are also examined separately in order to see their unique contribution of the potential moderators to the model. Table 5 indicates that when condition and self-help were included, only condition was found to be significant (p = .0489) and self-help did not contribute to the outcome of substance use (p = .2372), meaning that the condition trumps the effect of self-help rather than the other way around. When the effect of the condition on the substance use outcome does not disappear at the presence of self-help, this possible moderator can be ruled out. Table 6 shows that when condition and extracurricular activities were taken into account concurrently, both yielded significant results. Although the effect of the condition on the outcome variable did not disappear in spite of the presence of extracurricular activity, the condition did not trump extracurricular activity. This implies that both the primary independent variable and the possible moderator had contribution to the outcome in terms of variance explained. As mentioned before, when the condition in Step 4 is not fully met, at most only a partial moderation can be declared. In conclusion, the data suggest that there is a partial mediation effect, but not complete mediation. Specifically, extracurricular activity is a possible moderator but self-help is not. Figure 4 illustrates the conceptual paths of the mediation.

Table 4.

A model of three predictors of primary drug use.

Variable	DF	F Ratio	P
Condition	1, 76.3	3.5338448	0.0639
Self-help	1, 132.3	0.1470601	0.7020
Extracurricular Activities	1, 139.5	6.763389	0.0103*

Table 5.

A model of two predictors (condition & self-help) of primary drug use.

Variable	DF	F Ratio	p
Condition	1, 75.6	4.0063643	0.0489*
self-help	1, 131.1	1.4102575	0.2372

Table 6.

A model of two predictors (condition & ECA) of primary drug use.

Variable	DF	F Ratio	p
Condition	1, 76.2	4.5813445	0.0355*
Extracurricular Activities	1, 145.2	7.0862019	0.0086*

FIGURE 4.

Final model with extracurricular activities as the moderator between texting intervention and primary drug use.

DISCUSSION

There is increased interest in developing effective aftercare programs that engage youth in recovery support services to sustain behavioral changes achieved during formal treatment.²⁵ The use of mobile texting for delivering such aftercare interventions is a promising approach in the medical and mental health field for youth. Given that youth comprise the “digital natives” and are facile with this technology, mobile interventions provide a developmentally and culturally appropriate tool for recovering youth.⁶¹ Additionally, mobile texting aftercare interventions address important engagement/participation barriers, including competing time demands that interfere with aftercare attendance, issues of stigma post-treatment that prevent aftercare participation, and finding suitable sobriety-supportive social contexts that move beyond traditional self-help programs.

By employing the five components of a disease self-management framework,⁴⁶ Project ESQYIR encouraged and promoted extracurricular involvement through both the reminder and social support components¹. In the reminder component, experimental participants received texts reminding them to maintain focus on a prosocial recovery lifestyle, through which extracurricular activities were encouraged. Furthermore, in the social support component, texts prompted specific extracurricular groups and activities tailored to the participant’s geographic area. Within this mediation model, the effect of the predictor (i.e. texting condition of Project ESQYIR) on the proposed mediator (i.e., extracurricular participation) was facilitated primarily by texts addressing these two self-management components as was observed in Step 2 of the present analysis.

Step 3 of this meditation analysis confirms other studies’ findings that adolescent participation in extracurricular or organized group activities buffers against substance use.^62-64 There are perspectives and models which offer explanations for why engagement in prosocial behaviors (i.e., extracurricular activities) facilitates this effect. One such explanation comes from an ecological perspective, which recognizes the dynamic and complex intrapersonal, interpersonal, community and policy factors that can influence health behaviors.^65,66 From this perspective, pro-social extracurricular activities offer youth constructive, often structured and monitored, social environments that can contribute toward the reduction of substance use.^66-68 The Social Developmental Model, which is a synthesis of control theory, social learning theory and differential association theory, also helps explain the prosocial (protective) and antisocial (risk) pathways that occur throughout developmental youth periods.^68,69 Utilizing this model, extracurricular activities provide youth with opportunities that help them avoid drug-using tendencies and connect to prosocial influences that reinforce recovery-oriented beliefs and behaviors. Lastly, empowerment theory stresses the importance of allowing youth to access community resources on their own and not simply obtain a referral for resource utilization.^70,71 With its focus on wellness, Project ESQYIR, aimed to build youth empowerment by promoting their involvement in prosocial extracurricular activities in their respective communities on their own, which is correlated with one’s overall intrinsic motivation to achieve personal health goals.

The relationship between health improvement and engagement in wellness-type activities has long been supported by research across the fields of behavioral medicine, health psychology, and public health.⁴⁴ Without such participation, more than half of individuals suffering from complex behavioral issues (i.e., obesity/weight management, diabetes, depression, disordered eating, and HIV) will discontinue their clinically recommended regimens.⁴² As such, aftercare interventions for SUDs that promote participation in recovery behaviors should be effective at helping individuals self-manage complex behaviors by adopting alternative pro-social lifestyles that counteract old behavioral habits associated with poor health, especially if delivered by mobile applications, like Project ESQYIR was designed to do.^43,72-80

Findings from the mediational modeling found that despite the importance of pro-social activities associated with self-help involvement that is traditionally promoted by the SUD field,⁸¹ participation in self-help among the youth sample did not serve as a significant mechanism of action of the mobile texting aftercare intervention as initially anticipated. The utility of self-help groups among youth has been an ongoing discussion in the field.^82,83 A growing body of research focuses on the extent to which youth actually participate in self-help, particularly 12 step AA/NA, the perceived benefits of participation, and the characteristics of youth who appear to benefit from involvement.^84,85 A major area of this work has also focused on youth “perceptions” of the need for such services and the value-based clashes with the tenants of traditional self-help programs with youth culture that exist.^12,86-89 A basic premise and foundational requirement for most self-help groups is identification with the shared ailment or struggle of the group.⁹⁰ This experience may trigger dissonance among youth who are ambivalent about their problem behaviors and who are sensitive to the negative stereotype of being in recovery.⁷⁵

From a neurodevelopmental perspective, the reduced executive control and hedonic sensitivity due to increased incentive salience for which youths’ substance using behaviors are initially reinforced may provide an explanation for why the prosocial behaviors associated with extracurricular activities was the only observed mechanism.^91,92 One study found that among youth (adolescents and emerging young adults), nearly half endorsed forced-choice reasons for quitting drinking or using, representing a sense of interpersonal obligation as a primary motivator.⁹³ It could very well be the case that a majority of youth who find themselves in SUD treatment and self-help groups do so to appease counselors, family members, and probation officers, but lack an authentic desire or readiness to change.⁹⁴ While prosocial extracurricular activities facilitate short-term incentive salience and have appeal even for those who are only extrinsically motivated to participate in their recovery, youth, developmentally, lack the cognitive capacity (rationality and futuristic thinking) to truly value self-help approaches that entail investing in long-term recovery participation to acquire lasting, positive change. Given this lack of appeal or perceived need for self-help by youth, harm reduction recovery models may be more desirable and promising alternative approaches for youth than the total-abstinence recovery models.

Limitations

Caution should be taken when interpreting the results of this exploratory study for several reasons: 1) the findings are based on a small pilot study; 2) the youth sample is limited to those who completed treatment and self-selected to participate; and 3) although participants were randomly assigned to each condition, there was a higher proportion of participants in the target condition reporting methamphetamine as the primary substance used (37%) whereas a majority (48.8%) reporting marijuana use in the control condition. Future studies may utilize a randomized block design to account for important differences that may affect outcomes, such as substance use type or substance use severity. Additionally, the single item measure for extracurricular participation did not assess duration or intensity and therefore a threshold which begins impacting primary outcomes cannot be established. In addition, this study did not look at specific extracurricular activities that are important for youth in recovery, but a generic emphasis on positive pro-social activities that are commonly referenced in the larger literature among youth. Lastly, the study included a methodological limitation with a lack of a mobile control condition which limited our ability to examine effects of exposure to alternative mobile texting interventions; however, it should be noted that this was a pilot study that sought the initial efficacy and feasibility of mobile texting for aftercare compared to standard aftercare as usual.

Summary

Overall, these findings are important given that little is known empirically about important mechanisms of action associated with such novel aftercare interventions for youth in SUD recovery. More research is needed on investigating these recovery processes or mechanisms of action of aftercare interventions among youth, specifically, among youth with co-occurring mental health and medical disorders (i.e., how such processes may serve as agents of improvement among youth challenged by co-occurring mental health and medical issues). There is growing evidence supporting the relationship between poor recovery outcomes and co-occurring psychopathology linked to emotional dysregulation associated with depression, anxiety, and trauma.^95,96 As such, future research should examine the differential effects mental health symptom severity on recovery outcomes and the potential buffer of prosocial activities.

Findings are also important for the SUD treatment and recovery communities to adapt their treatment and discharge planning protocols to counter youths’ natural propensity to resist self-help programs. For instance, SUD treatment providers and self-help groups need to develop better access to rewarding and enjoyable experiences that will make participation more attractive.⁹⁷ Given that the sample included in the aftercare study was comprised of “treatment completers,” it could be assumed that these youth were highly motivated, goal-oriented, and receptive to self-help participation. In particular, implementation research can examine the performance of SUD treatment systems and their treatment and discharge planning protocols related to initiating recovery support services. For instance, important questions exist, including: when and how do SUD treatment providers advocate for youth to participate in recovery support activities? Is there normative messaging included during the assessment, treatment, and discharge phases regarding the importance of participating in recovery support activities? Answers to these questions can help the field better understand larger system issues associated with care continuity and holding systems accountable for ensuring treatment gains/success. ⁹⁷