Mobile Interventions Targeting Risky Drinking Among University Students: A Review

Current Addiction Reports

Volumn 3, Issue 2, 2016, Pages 166-174

  Berman, Anne H ^a,b   Gajecki, Mikael ^a   Sinadinovic, Kristina ^a,b   Andersson, Claes ^c  

^a KAROLINSKA INSTITUTE   (Sweden)

^b Stockholm Center for Dependency Disorders   (Sweden)

^c MALMÖ UNIVERSITY   (Sweden)

Author keywords

Alcohol; Automated telephony; Hazardous drinking; Intervention; Review; Smartphone apps; Text messages; University college students

Indexed keywords

EID: 85011719099     PISSN: None     EISSN: 21962952     Source Type: Journal    
DOI: 10.1007/s40429-016-0099-6     Document Type: Review

References (41)

1. Plant MA, Plant ML, Miller P, Gmel G, Kuntsche S. The social consequences of binge drinking: a comparison of young adults in six European countries. J Addict Dis. 2009;28:294–308.
2. Johnston LD, O’Malley PM, Bachman JG, Schulenberg JE. Monitoring the future: national survey results on drug use, 1975–2012. Volume 2: college students and adults ages 19–50. Ann Arbor: Institute of Social Research, University of Michigan; 2013.
3. O’Neill SE, Parra GR, Sher KJ. Clinical relevance of heavy drinking during the college years: cross-sectional and prospective perspectives. Psychol Addict Behav. 2001;15:350.
4. Schuckit MA. Comorbidity between substance use disorders and psychiatric conditions. Addiction. 2006;101:76–88.
5. Larimer ME, Cronce JM. Identification, prevention and treatment: a review of individual-focused strategies to reduce problematic alcohol consumption by college students. J Stud Alcohol Drugs. 2002;148.
6. Larimer ME, Cronce JM. Identification, prevention, and treatment revisited: individual-focused college drinking prevention strategies 1999–2006. Addict Behav. 2007;32:2439–68.
7. Cellucci T, Krogh J, Vik P. Help seeking for alcohol problems in a college population. J Gen Psychol. 2006;133:421–33.
8. Cronce JM, Larimer ME. Individual-focused approaches to the prevention of college student drinking. Alcohol Res Health J Natl Inst Alcohol Abuse Alcohol. 2011;34:210. This is the second part of two landmark qualitative reviews that the authors conducted as part of a National Institute on Alcohol Abuse and Alcoholism initiative on college drinking. The first review referred to research published between 1984 and early 2007, and this second review summarizes evidence accumulated between 2007 and 2010. Included studies were divided into three separate groups: individual-focused preventive interventions (N=36); stand-alone personalized feedback intervention (PFI) and personalized normative feedback (PNF) (N=17); and in person brief motivational interventions (BMI) (N=17). Consistent with the earlier review, the efficacy of BFI combined with PFI and PNF, as well as stand-alone PFI and PNF interventions was strongly supported. The efficacy of alcohol expectancy challenge interventions, feedback-based interventions solely focusing on blood alcohol concentraiton and multicomponent alcohol education-focused interventions including elements of PFI and PNF, were also supported, but with less consistency. No evidence of efficacy was found for programs that only included alcohol education.
9. Leeman RF, Perez E, Nogueira C, DeMartini KS. Very-brief, web-based interventions for reducing alcohol use and related problems among college students: a review. Front Psychiatr. 2015;6.
10. Buscemi J, Murphy JG, Martens MP, McDevitt-Murphy ME, Dennhardt AA, et al. Help-seeking for alcohol-related problems in college students: correlates and preferred resources. Psychol Addict Behav. 2010;24:571.
11. Elliott JC, Carey KB, Bolles JR. Computer-based interventions for college drinking: a qualitative review. Addict Behav. 2008;33:994–1005.
12. Bewick BM, Trusler K, Barkham M, Hill AJ, Cahil J, et al. The effectiveness of web-based interventions designed to decrease alcohol consumption—a systematic review. Prev Med. 2008;47:17–26.
13. Carey KB, Scott-Sheldon LA, Elliott JC, Bolles JR, Carey MP. Computer-delivered interventions to reduce college student drinking: a meta-analysis. Addiction. 2009;104:1807–19.
14. White A, Kavanagh D, Stallman H, Klein B, Kay-Lambkin F, et al. Online alcohol interventions: a systematic review. J Med Internet Res. 2010;12:e62.
15. Riper H, Spek V, Boon B, Conijn B, Kramer J, et al. Effectiveness of E-self-help interventions for curbing adult problem drinking: a meta-analysis. J Med Internet Res. 2011;13:e42.
16. Carey KB, Scott-Sheldon LA, Elliott JC, Garey L, Carey MP. Face-to-face versus computer-delivered alcohol interventions for college drinkers: a meta-analytic review, 1998 to 2010. Clin Psychol Rev. 2012;32:690–703. This meta-analysis includes 48 manuscripts and examined the efficacy of Computer-delivered interventions (CDIs) and face-to-face interventions (FTFIs) in college group populations (N=5237). In comparison to controls, it was established that both CDIs and FTFIs reduced harmful drinking outcomes, but that effects were not maintained for CDIs; in direct comparisons, FTFIs were more effective for quantity and problem measures and for long-term effects. In summary, the meta-analysis shows that both CDIs and FTFIs are effective in reducing harmful drinking outcomes, but that FTFIs still are more effective than CDIs for both quantity and problem measures and in terms of long-term effects.
17. Moreira M, Smith L, Foxcroft D. Social norms interventions to reduce alcohol misuse in university or college students. Cochrane Database of Syst Rev. 2009;8.
18. Hall AK, Cole-Lewis H, Bernhardt JM. Mobile text messaging for health: a systematic review of reviews. Ann Rev Public Health. 2015;36:393. This systematic review of reviews included 15 articles from 2009 to 2014, of which 6 reported or included meta-analyses, covering a total of 89 individual studies. Most of the reviews reported low or moderate evidence for text-message effectiveness in increasing healthy behaviors, primarily self-management of diabetes, increasing physical activity, losing weight, quitting smoking and adhering to HIV medication. Methodological limitations included small samples, brief intervention durations, non-rigorous study designs, and non-representative samples as well as study contexts. Future research should focus on identifying effective intervention components, through iterative study designs, assess long-term effects, test interventions in diverse populations, and evaluate cost-effectiveness.
19. Quanbeck A, Chih M-Y, Isham A, Johnson R, Gustafson D. Mobile delivery of treatment for alcohol use disorders: a review of the literature. Alcohol Res Curr Rev. 2014;36:111.
20. Abu-Hasaballah K, James A, Aseltine RH. Lessons and pitfalls of interactive voice response in medical research. Contemp Clin Trials. 2007;28:593–602.
21. Corkrey R, Parkinson L. Interactive voice response: review of studies 1989–2000. Behav Res Methods Instrum Comput. 2002;34:342–53.
22. Rose GL, MacLean CD, Skelly J, Badger GJ, Ferraro TA, et al. Interactive voice response technology can deliver alcohol screening and brief intervention in primary care. J Gen Intern Med. 2010;25:340–4.
23. Andersson C, Vasiljevic Z, Höglund P, Öjehagen A, Berglund M. Daily automated telephone assessment and intervention improved 1-month outcome in paroled offenders. Int J Offender Ther Comp Criminol: 0306624X14526800. 2014.
24. Mattila E, Lappalainen R, Pärkkä J, Salminen J, Korhonen I. Use of a mobile phone diary for observing weight management and related behaviours. J Telemed Telecare. 2010;16:260–4.
25. Ly K, Carlbring P, Andersson G. Behavioral activation-based guided self-help treatment administered through a smartphone application: study protocol for a randomized controlled trial. Trials. 2012;13:62.
26. Weaver E, Horyniak DR, Jenkinson R, Dietze P, Lim M. “Let’s get Wasted!” and other apps: characteristics, acceptability, and use of alcohol-related smartphone applications. J Med Internet Res. 2013;1.
27. Savic M, Best D, Rodda S, Lubman DI. Exploring the focus and experiences of smartphone applications for addiction recovery. J Addict Dis. 2013;32:310–9.
28. Crane D, Garnett C, Brown J, West R, Michie S. Behavior change techniques in popular alcohol reduction apps: content analysis. J Med Internet Res. 2015;17:e118. This publication analyzed behavior change techniques (BCT) used in 800 alcohol-related apps available in the UK, identifying 662 unique apps. Thirteen percent (n=91) explicitly targeted alcohol reduction; 51 free apps and 10 of the top paid apps were analyzed in greater detail. BCTs occurring most frequently included self-recording (33/61), psychoeducation on the consequences of overconsumption of alcohol as well as abstaining from drinking (26/61), and providing feedback on behavioral performance as a result of the app intervention (25/61). Overall, only a low proportion of the apps could be classified as health-promoting, and these included no more than 3.6 BCTs on average. None of the apps mentioned theory but those that referred to evidence tended to be more popular.
29. Cohn AM, Hunter-Reel D, Hagman BT, Mitchell J. Promoting behavior change from alcohol use through mobile technology: the future of ecological momentary assessment. Alcohol Clin Exp Res. 2011;35:2209–15.
30. Meredith SE, Alessi SM, Petry N. Smartphone applications to reduce alcohol consumption and help patients with alcohol use disorder: a state-of-the-art review. Adv Health Care Technol. 2015;1:47–54.
31. Bendtsen M, Bendtsen P. Feasibility and user perception of a fully automated push-based multiple-session alcohol intervention for university students: randomized controlled trial. J Med Internet Res. 2014;23:e30.
32. Mason M, Benotsch EG, Way T, Kim H, Snipes D. Text messaging to increase readiness to change alcohol use in college students. J Prim Prev. 2014;35:47–52.
33. Moore SC, Crompton K, van Goozen S, van den Bree M, Bunney J, et al. A feasibility study of short message service text messaging as a surveillance tool for alcohol consumption and vehicle for interventions in university students. BMC Public Health. 2013;13.
34. Riordan BC, Conner TS, Flett JAM, Scarf D. A brief orientation week ecological momentary intervention to reduce university student alcohol consumption. J Stud Alcohol Drugs. 2015;76:525–9.
35. Andersson C. Comparison of WEB and interactive voice response (IVR) methods for delivering brief alcohol interventions to hazardous-drinking university students: a randomized controlled trial. Eur Addict Res. 2015;21:240–52.
36. Gajecki M, Berman AH, Sinadinovic K, Rosendahl I, Andersson C. Mobile phone brief intervention applications for risky alcohol use among university students: a randomized controlled study. Addict Sci Clin Pract. 2014;9:11.
37. Witkiewitz K, Desai SA, Bowen S, Leigh BC, Kirouac M, et al. Development and evaluation of a mobile intervention for heavy drinking and smoking among college students. Psychol Addict Behav. 2014;28:639.
38. Wyrick DL, Rulison KL, Fearnow-Kenney M, Milroy JJ, Collins LM. Moving beyond the treatment package approach to developing behavioral interventions: addressing questions that arose during an application of the Multiphase Optimization Strategy (MOST). Transl Behav Med. 2014;4:252–9.
39. Collins LM, Nahum-Shani I, Almirall D. Optimization of behavioral dynamic treatment regimens based on the sequential, multiple assignment, randomized trial (SMART). Clin Trials: 1740774514536795. 2014.
40. Klasnja P, Hekler EB, Shiffman S, Boruvka A, Almirall D, et al. Microrandomized trials: an experimental design for developing just-in-time adaptive interventions. Health Psychol. 2015;34:1220.
41. Dimeff LA, Baer JS, Kivlahan DR, Marlatt G. Brief Alcohol Screening and Intervention for College Students (BASICS). A harm reduction approach. New York: The Guilford Press; 1999.