Abstract
Background
An Internet-based relapse prevention supplement to adolescent substance abuse treatment programming is a promising modality to reinforce treatment gains and enhance recovery; however, an evidence base is lacking.
Objective
To assess the efficacy of the online Navigating my Journey (NmJ) program.
Methods
129 adolescent-aged participants (ages 13–23) receiving substance abuse treatment participated in a randomized parallel group study comparing two conditions: experimental (NmJ) versus attention control (viewed wellness articles from the Nemours Foundation at their discretion). Participants in the experimental condition were asked to complete 12 core lessons over 3 months. Lesson content was developed to teach evidence-based relapse prevention skills. Data were collected at four time points: baseline, 1-month follow up, 3-month follow up, and 6-month follow up.
Results
We used a linear mixed modeling approach to test for differences between conditions on each outcome. Participants in the experimental condition reported a significantly greater increase in motivation to reduce or not misuse drugs from baseline to 3-month follow up and from baseline to 6-month follow up, compared to the control participants. Participants in the experimental condition also reported a greater decrease in drug use score from baseline to 3-month follow up, compared to the control participants. An analysis of age as a potential moderator suggested that the intervention may be more effective for older adolescents. Greater use of the program was associated with greater self-efficacy and lower self-reported substance use over time.
Conclusions
Relapse prevention treatment with adolescents may be facilitated by theory-based online interventions.
ClinicalTrials.gov Identifier
NCT02125539.
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Notes
Three older participants screened in because they responded “YES” to the screener question “Are you between the ages of 18 and 21?” then reported an age that was 22 or 23. Based on input from consultants, these data were retained for analysis.
An a priori power analysis was conducted to determine the target number of participants required to achieve 80% power assuming a small-to-moderate effect of the intervention. Further details are available upon request.
Acquiescence bias is defined as agreeing or disagreeing to all items on a questionnaire or battery of questionnaires without considering the actual content of the items. The ways the authors identified acquiescent responding are consistent with the definition provided by Furr and Bacharach (2013).
ES is the effect size defined by the difference between conditions in the change in means from one time point to another (e.g., baseline to 3-month follow-up).
“Few” was defined as equal to or less the first 25% of the distribution (≤25th percentile).
“Moderate” was defined as the middle 50% of the distribution (25th percentile through 75th percentile).
“Many” was defined as the top 25% of the distribution (>75th percentile).
References
Allison, P. D. (2012). Handling missing data by maximum likelihood [Statistical Horizons SAS Global Forum]. Retrieved July 1, 2015, from http://www.statisticalhorizons.com/wpcontent/uploads/MissingDataByML.pdf
Carroll, K. M., Easton, C. J., Nich, C., Hunkele, K. A., Neavins, T. M., Sinha, R., et al. (2006). The use of contingency management and motivational/skills-building therapy to treat young adults with marijuana dependence. Journal of Consulting and Clinical Psychology, 74(5), 955–966. doi:10.1037/0022-006X.74.5.955.
Carroll, K. M., Kiluk, B. D., Nich, C., Gordon, M. A., Portnoy, G. A., Marino, D. R., et al. (2014). Computer-assisted delivery of cognitive-behavioral therapy: Efficacy and durability of CBT4CBT among cocaine-dependent individuals maintained on methadone. American Journal of Psychiatry, 171(4), 436–444. doi:10.1176/appi.ajp.2013.13070987.
Cook, R. F., Billings, D. W., Hersch, R. K., Back, A. S., & Hendrickson, A. (2007). A field test of a web-based workplace health promotion program to improve dietary practices, reduce stress, and increase physical activity: Randomized controlled trial. Journal of Medical Internet Research, 9(2), e17. doi:10.2196/jmir.9.2.e17.
Cornelius, J. R., Maisto, S. A., Pollock, N. K., Martin, C. S., Salloum, I. M., Lynch, K. G., et al. (2003). Rapid relapse generally follows treatment for substance use disorders among adolescents. Addictive Behaviors, 28(2), 381–386. doi:10.1016/S0306-4603(01)00247-7.
Cucciare, M. A., Weingardt, K. R., Greene, C. J., & Hoffman, J. (2012). Current trends in using internet and mobile technology to support the treatment of substance use disorders. Current Drug Abuse Reviews, 5(3), 172–177. doi:10.2174/1874473711205030172.
Dirksen, J. (2012). Design for how people learn. Berkeley, CA: New Riders.
Dennis, M., Godley, S. H., Diamond, G., Tims, F. M., Babor, T., Donaldson, J., et al. (2004). The Cannabis Youth Treatment (CYT) Study: Main findings from two randomized trials. Journal of Substance Abuse Treatment, 27(3), 197–213. doi:10.1016/j.jsat.2003.09.005.
Furr, R. M., & Bacharach, V. R. (2013). Psychometrics: An introduction (2nd ed.). Thousand Oaks, CA: Sage.
Garner, B. R., Godley, S. H., & Funk, R. R. (2008). Predictors of early therapeutic alliance among adolescents in substance abuse treatment. Journal of Psychoactive Drugs, 40(1), 55–65.
Godley, M. D., Kahn, J. H., Dennis, M. L., Godley, S. H., & Funk, R. R. (2005). The stability and impact of environmental factors on substance use and problems after adolescent outpatient treatment for cannabis abuse or dependence. Psychology of Addictive Behaviors, 19(1), 62–70. doi:10.1037/0893-164X.19.1.62.
Gonzales, R., Ang, A., Murphy, D., Glik, D., & Anglin, M. (2014). Substance use recovery outcomes among a cohort of youth participating in a mobile-based texting aftercare pilot program. Journal of Substance Abuse Treatment, 47(1), 20–26. doi:10.1038/nature13314.A.
Greenstein, D. K., Franklin, M. E., & McGuffin, P. (1999). Measuring motivation to change: An examination of the University of Rhode Island Change Assessment Questionnaire (URICA) in an adolescent sample. Psychotherapy Theory Research & Practice, 36(1), 47–55.
Harris, N., Brazeau, J. N., Clarkson, A., Brownlee, K., & Rawana, E. P. (2012). Adolescents’ experiences of a strengths-based treatment program for substance abuse. Journal of Psychoactive Drugs, 44(5), 390–397. doi:10.1080/02791072.2012.736822.
Hawley, K. M., & Garland, A. F. (2008). Working alliance in adolescent outpatient therapy: Youth, parent and therapist reports and associations with therapy outcomes. Child & Youth Care Forum, 37(2), 59–74. doi:10.1007/s10566-008-9050-x.
Hendershot, C. S., Witkiewitz, K., George, W. H., & Marlatt, G. A. (2011). Relapse prevention for addictive behaviors. Substance Abuse Treatment, Prevention, and Policy, 6, 17. Retrieved from http://download.springer.com/static/pdf/671/art:10.1186/1747-597X-6-17.pdf?origin, http://substanceabusepolicy.biomedcentral.com/article/10.1186/1747-597X-6-17&token2=exp=1449072165~acl=/static/pdf/671/art%3A10.1186%2
Hendriks, V., van der Schee, E., & Blanken, P. (2012). Matching adolescents with a cannabis use disorder to multidimensional family therapy or cognitive behavioral therapy: Treatment effect moderators in a randomized controlled trial. Drug and Alcohol Dependence, 125(1–2), 119–126. doi:10.1016/j.drugalcdep.2012.03.023.
Jenson, J. M., Wells, E. A., Plotnick, R. D., Hawkins, J. D., & Catalano, R. F. (1993). The effects of skills and intentions to use drugs on posttreatment drug use of adolescents. The American Journal of Drug and Alcohol Abuse, 19(1), 1–18. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/8438825
Kelly, J. F., Myers, M. G., & Brown, S. A. (2000). A multivariate process model of adolescent 12-step attendance and substance use outcome following inpatient treatment. Psychology of Addictive Behaviors, 14(4), 376–389.
Kelly, J. F., Myers, M. G., & Brown, S. A. (2002). Do adolescents affiliate with 12-step groups? A multivariate process model of effects. Journal of Studies on Alcohol, 63(3), 293–304.
Lord, S. E., Trudeau, K. J., Black, R. A., Lorin, L., Cooney, E., Villapiano, A., et al. (2011). CHAT: Development and validation of a computer-delivered, self-report, substance use assessment for adolescents. Substance Use and Misuse, 46(6), 781–794. doi:10.3109/10826084.2010.538119.
Marlatt, G. A., & Gordon, J. R. (1985). Relapse prevention: Maintenance strategies in the treatment of addictive behaviors. New York, NY: Guilford Press.
Marley, S., Bekker, H. L., & Bewick, B. M. (2016). Responding to personalised social norms feedback from a web-based alcohol reduction intervention for students: Analysis of think-aloud verbal protocols. Psychology & Health, 31(9), 1007–10024. doi:10.1080/08870446.2016.1161192.
Martin, G., Wilkinson, D., & Poulos, C. (1995). The drug avoidance self-efficacy scale. Journal of Substance Abuse, 7(2), 151–163.
McConnaughy, E. A., DiClemente, C. C., Prochaska, J. O., & Velicer, W. F. (1989). Stages of change in psychotherapy: A follow-up report. Psychotherapy, 26(4), 494–503.
McConnaughy, E. N., Prochaska, J. O., & Velicer, W. F. (1983). Stages of change in psychotherapy: Measurement and sample profiles. Psychotherapy: Theory, Research and Practice, 20(3), 368–375.
Myers, M., & Brown, S. (1996). The Adolescent Relapse Coping Questionnaire: Psychometric validation. Journal of Studies on Alcohol, 57(1), 40–46.
Myers, M. G., Brown, S. A., & Mott, M. A. (1993). Coping as a predictor of adolescent substance abuse treatment outcome. Journal of Substance Abuse, 5(1), 15–29. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/8329878
National Institute on Drug Abuse. (2012). Principles of drug addiction treatment: A research-based guide (3rd ed.) (NIH Publication No. 12-4180). Retrieved from https://www.drugabuse.gov/publications/principles-drug-addiction-treatment-research-based-guide-third-edition/
National Institute on Drug Abuse. (2014). Principles of adolescent substance use disorder treatment: A research-based guide. Retrieved April 11, 2016, from https://www.drugabuse.gov/sites/default/files/podata_1_17_14.pdf
Power, E., Nishimi, R., & Kizer, K. (Eds.). (2005). Evidence-based treatment practices for substance use disorders. Washington, DC: National Quality Forum.
Sampl, S., & Kadden, R. (2001). Motivational enhancement therapy and cognitive behavioral therapy for adolescent cannabis users: 5 Sessions, Cannabis Youth Treatment (CYT) series (Vol. 1). Rockville, MD: Center for Substance Abuse Treatment, Substance Abuse and Mental Health Services. Retrieved from http://www.evidencebasedpracticenetwork.net/Documents/Met_cbt5_CYT_v1.pdf
Sanchez, R. P., & Bartel, C. M. (2015). The feasibility and acceptability of “Arise”: An online substance abuse relapse prevention program. Games for Health Journal, 4(2), 136–144. doi:10.1089/g4h.2014.0015.
Schabenberger, O. (2005). Introducing the GLIMMIX procedure for generalized linear mixed models. In Proceedings of the thirtieth annual SAS users group international conference. Cary, NC: SAS Institute Inc.
Tracey, T. J., & Kokotovic, A. M. (1989). Factor structure of the Working Alliance Inventory. Psychological Assessment: A Journal of Consulting and Clinical Psychology, 1(3), 207–210. doi:10.1037/1040-3590.1.3.207.
Trudeau, K. J., Ainscough, J., & Charity, S. (2012). Technology in treatment: Are adolescents and counselors interested in online relapse prevention? Child & Youth Care Forum, 41(1), 57–71. doi:10.1007/s10566-011-9154-6.
Vovici Corporation. (2012). Vovici 6. Herndon, VA: Vovici Corporation.
Webb, C., Scudder, M., Kaminer, Y., & Kadden, R. (2002). The motivational enhancement therapy and cognitive behavioral therapy supplement: 7 sessions of cognitive behavioral therapy for adolescent cannabis users, Cannabis Youth Treatment (CYT) series (Vol. 2). DHHS Pub. No. (SMA) 07-3954. Rockville, MD: Center for Substance Abuse Treatment, Substance Abuse and Mental Health Services Administration. Retrieved from http://store.samhsa.gov/shin/content/SMA08-3954/SMA08-3954.pdf
West, A., & Spring, B. (2012). Randomized controlled trials. Retrieved September 23, 2016, from http://www.ebbp.org/course_outlines/rcts.pdf
Wintersteen, M. B., Mensinger, J. L., & Diamond, G. S. (2005). Do gender and racial differences between patient and therapist affect therapeutic alliance and treatment retention in adolescents? Professional Psychology: Research and Practice, 36(4), 400–408. doi:10.1037/0735-7028.36.4.400.
Acknowledgements
The authors would like to thank their funder (NIDA SBIR Grant #2R44DA026645) and their Inflexion colleagues who contributed to the development of the intervention, NavigatingmyJourney.com: Ellen Patterson, Lisa Sawyer, Matt Solano, and Mila Pavek. We are also grateful to the editor and two anonymous reviewers for their very constructive feedback on the original draft. Lastly, thank you to Kelly Manser for her editorial review of this manuscript.
Research Funding
This work was supported by NIDA SBIR Grant #2R44DA026645. The funders had no part in designing the study, the collection of data and its analysis, or in the decision to complete or write this manuscript.
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All authors were salaried employees or paid consultants of the organization that received the NIH SBIR grant to develop and test this program. KT and RB were employees of Inflexxion, Inc., Newton, MA during this project. JK and SS declare that they have no conflict of interest to report. We had a subcontract with Hazelden Publishing to draft content for the intervention program described and tested herein.
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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
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Informed consent was obtained from all individual participants included in the study.
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Trudeau, K.J., Black, R.A., Kamon, J.L. et al. A Randomized Controlled Trial of an Online Relapse Prevention Program for Adolescents in Substance Abuse Treatment. Child Youth Care Forum 46, 437–454 (2017). https://doi.org/10.1007/s10566-016-9387-5
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DOI: https://doi.org/10.1007/s10566-016-9387-5