top of page
Green logo cropped org green.png

Dec, 2013

Volume 3,

Issue 3

Review: Web-based brief interventions for young adolescent alcohol and drug abusers - a systematic review

Hanne Tønnesen 1, Henriettae Ståhlbrandt 2, Bolette Pedersen 1

About the Authors: 

  1. Promotion Centre, Bispebjerg/Frb University Hospital, University of Copenhagen, Copenhagen, Denmark & Lund University, Skåne University Hospital, Malmö, Sweden. 

  2. Clinical Health Promotion Centre, Lund University, Skåne University Hospital, Malmö, Sweden


Background Adolescents’ use of alcohol, cannabis and other psychoactive substances has significantly increased in European countries. Parallel to this web-based screening and brief intervention have been disseminated. An important question is if it is based on evidence for effect? Therefore, the aim of this review is to evaluate the evidence for effect.

Method A systematic literature search was performed on randomised trials in the following databases: MEDLINE, the Cochrane Central Register of Controlled Trials (CENTRAL) and EMBASE – supplemented by hand search. The target group of young adolescents was defined as 16 to 18 years old.

Results Overall, 35 papers were identified as randomised trials on web-based screening and/or intervention concerning alcohol and drug among young people; however the only identifiable randomised trial to evaluate the young adolescents was a published protocol describing an ongoing study.

Conclusion Young adolescents might benefit from web-based screening and brief intervention on alcohol and drugs; however an effects remains to be established in high quality studies.


Adolescents’ use of alcohol, cigarettes, cannabis and other psychoactive substances has significantly increased in European countries since the 1990s (1). The use of alcohol, cannabis, or both, can have severe consequences for adolescents and young people in different domains, including health problems, intentional injuries, traffic violation, early sexual activity, sexual and/or physical abuse (2). Early onset of alcohol use is also a major risk factor for later alcohol dependence or alcohol use disorder (3-5). Similar to alcohol, cannabis consumption in adolescence can also affect the brain development and have long-lasting behavioural consequences that involve dependence. Other health issues are chronic bronchitis and related histopathological changes, impairments of attention and memory as well as dependence (6). Cannabis use is associated with later depression, increased likelihood for psychosis development and might lead to the use of more harmful drugs in vulnerable
subjects (7;8). Finally, the combined use of psychoactive substances holds specific dangers, such as an increased severity of effects and heightened toxicity, depending on certain characteristics of the user
 like existence of tolerance, the route of administration and the quantity and purity of drugs (1).

One especially wellestablished approach in the field of hazardous alcohol consumption are brief interventions. Internationally, there is a large body of research on brief intervention approaches in alcoholabusing adults (9;10). While positive research results on brief interventions in heavy drinking adults are abundant, research focusing on brief interventions for adolescents with alcohol or other drug problems has been scarce. This is surprising given the fact that such studies have been called for since the mid nineties (11). But in the last few years, the body of evidence in this area has increased (12-14); although these findings are limited by small sample sizes.

Interestingly, the web-based models of brief intervention for young poly-drug users have been widely disseminated; especially targeting the young adolescents consuming alcohol and cannabis.
The question that still remains is if these models are supported by evidence for the young adolescents between 16-18 years of age? The aim of this systematic review was therefore to assess the effect of web-based brief intervention for this group of drug and alcohol abusers in randomised designs.

Search methods
The literature search was performed in the following databases: MEDLINE, the Cochrane Central Register of Controlled Trials (CENTRAL) and EMBASE. The search strategy included adolescent* OR young OR teenag* OR child* OR high school OR freshmen AND Alc* OR
Beer OR Wine OR Spir* OR Liq* OR Breezer* OR ethanol OR Drug* OR narco* OR medic* OR Cannabis Or Extacy OR amphetamin* OR heroin* OR morphin* OR Opiat* OR hallucinog* OR Cocain* OR Substance*OR Abus* O
R misus* OR depend* OR addict* OR intox* OR ebrie*AND Web* OR online OR Computer-based OR inter-active AND Brief Intervention OR Motivational interview* OR Stages of change OR Changing process AND Outcome* OR Effect* OR Follow-up OR Withdrawal OR Abstinence OR Reduct*. The last updated search was performed 28 Nov 2013. No time or language restrictions were set. Full paper articles, abstracts as well as study protocol were considered. Titles and abstracts were screened to exclude any clearly irrelevant papers as well as duplicate papers. All potentially relevant papers, abstracts and protocols were assessed in accordance with the inclusion and exclusion criteria. Also reference lists and related
articles from the included papers were hand-search to identify other relevant studies. 


Only randomised clinical trials (RCTs) were included. The target group was the young adolescents aging 16-18 years Studies including young or adolescent drug users/abusers and alcohol abusers were considered. Nonrandomised trials, reviews and other types of secondary literature were excluded. Other exclusion criteria were wrong population (e.g. adults), type of intervention (e.g. smoking cessation) or setting (e.g. not web-based). Studies were included if they provided data on the population and age, description of the web-based alcohol and/or drug intervention and comparator(s) and adequately reported alcohol/drug outcomes at follow-up. Interventions of interest were web-based brief alcohol and/or drug interventions focusing on moderation or cessation of their problematic substance use. Comparators could be screening or assessment only or other types of interventions (e.g. leaflets, in-person brief interventions).

Search outcome
The database search resulted in 107 papers of which 16 were duplicates. Fifty papers were excluded after screening of titles and abstracts, while another 8 papers were included after hand search. A total of 57 full article papers were assessed according to the inclusion and exclusion criteria (see trial profile in figure 1). A total of 35 papers were included in the review (15-49).


Study characteristics
Characteristics of the 35 RCTs are presented in table 1 (Appendix). The majority of the studies originated from the United States (n=24). The remaining were from New Zealand (n=4), the Netherlands (n=3), Sweden (n=2), United Kingdom (n=1) or multiple countries (n=1). The trials were published from 2004 to 2013. The 35 studies had a total of 21,433 participants (ranging from 17to 5,227). Most studies were conducted among college or university students. The age range was from 14 to 29 years, and only one paper (a protocol) matched our specific criteria regarding the target group at 16-18 years of age (15). Four study protocols were included; three concerning web-based alcohol interventions (24;45;46) and one poly-drug intervention programme (15). Among the 31 full papers articles, one trial focused on marijuana use exclusively (30) and the remaining were web-based brief alcohol interventions. The most common comparator was assessment/screening only. Follow-up was conducted after 4 weeks (n=16), 6 weeks (n=1), 2 months (n=4), 3 months (n=10), 5 months (n=2), 6 months (n=11), 12 months (n=5), 18 months (n=1) and 24 months (n=1). In 23 trials the patients were compensated for participation in terms of money, vouchers, course credit or entry to a lottery.

Alcohol and drug outcomes
Eight trials found no effect of the interventions on alcohol outcomes (16-19;33;34;44;47). The remaining trials found significant reductions in alcohol intake or alcoholrelated consequences, but in some the effect was limited to specific subgroups (21;38;41) or secondary outcomes (39:40). Finally, the effect of web-based personalised feedback on marijuana use was only significant for the selected group having a family history of drug problems (30).

Evidence for the effect on alcohol and drug outcomes following brief interventions was mixed, and none of the included studies specifically assessed the effect among the 16-18 year olds, except for one ongoing trial targeting poly-drug use among teenagers (15). This project WISEteens (“Web-based Screening and Brief Intervention for Substance using Teens”) aims at reducing these risks by creating and evaluating a web-based brief intervention (web-BI) that will motivate adolescents with risky consumption patterns to moderate or cease their problematic substance use, and to seek referral to treatment if necessary.

Also, since most of the studies were conducted among older college or university students, generalisation of the effect to adolescents is not straightforward. The majo methodological problem in all the web-based studies was that the alcohol and drug outcomes were self-reported without further validation. This may have damaged the validity of the results, especially since underreporting of alcohol and drug use is common in general, and increasing with higher consumption (50). Thus, the underreporting may not influence the intervention and control groups similarly. Validation may be improved by attendance or follow-up visits that allow for the use of biochemical validation, the risk of course being a lower follow-up rate due to extra time spent and unwillingness to for example provide blood or urine tests.


The effectiveness of internet-based psychotherapeutic interventions in general was most recently examined in a meta-analysis by Barak and colleagues (51). The authors included 92 studies involving 9,764 clients treated for a variety of problems, and reported an overall medium effect size. For substance use problems, literature on web-based interventions is only just evolving. Copeland
& Martin found signs of effectiveness of web-based interventions in this specific area (52). In a more recent investigation, only one of 10 studies matched inclusion criteria and could not prove efficacy, although the authors found that web-based interventions were generally well received (53). In contrast to this, another review that included 17 studies focused on internet- and computerbased
interventions for college drinking, found promising results for web-based approaches to substance consumption reduction (54).


Computer-based intervention seems attractive for young people, because screening and brief intervention in health care are often limited by constrained resources. A qualitative study identified several barriers that complicate screening for young people’s problematic substance use in primary care: insufficient time, lack of training in how to manage a positive screen, insufficient time to manage a positive result during the visit, lack of treatment resources and tenacious parents who would not leave the room for a confidential discussion (55). Adolescents report concerns regarding confidentiality, lack of information about services, unsuitable appointments and opening times, unfriendly environment and staff, difficult access due to geographical barriers, language barriers and difficulties to obtain parental consent (56). In a European study, factors were identified that lowered adolescents` access to primary care: older age (than aged 8-11), lower level of parental education, and lower socioeconomic status (57). Due to these barriers to health care for adolescents or vulnerable subgroups of adolescents, alternative and low-threshold ways of delivering screening and brief intervention could be attractive. However, this review has shown that evidence has to be established on the effect for young adolescents with alcohol and drug abuse through high quality studies with sufficient validation of the outcomes.

In conclusion, young adolescents might benefit from internet-based screening and brief intervention on alcohol and drugs; however, randomised trials have not yet been performed for this important group.

The two senior researchers PhD Helena Hansson and PhD Ulla Zetterlund are acknowledged for technical support regarding web-based screening and brief intervention among young adolescents.


The project was supported financially by a grant from EU


Contributions details
HT and HS designed the study,

HT and BP performed the research, collected and analyzed data,

HT and BP wrote the paper, and HT, HS and BP edited the paper.

(1) EMCDDA. Annual Report: The State of the Drug Problem. Lisbon: European Monitoring Centre for Drugs and Drug Addiction; 2009.
(2) Newbury-birch D, Walker J, Avery L, et al. Impact of alcohol consumption on young people a systematic review of published reviews; 2009.
(3) Dawson DA, Goldstein RB, Chou SP, Ruan WJ, Grant BF. Age at first drink and the first incidence of adult-onset DSM-IV alcohol use disorders. Alcohol. Clin. Exp. Res. 2008; 32:2149–60.
(4) Grant BF, Stinson FS, Harford TC. Age at onset of alcohol use and DSM-IV alcohol abuse and dependence: a 12-year follow-up. J. Subst. Abuse 2001; 13:493–504.
(5) Hingson RW, Heeren T, Winter MR. Age at drinking onset and alcohol dependence: age at onset, duration, and severity. Arch. Pediatr. Adolesc. Med. 2006; 160:739–46.
(6) Fernández-Ruiz J, Paz Viveros M, Ramos JA, Lundqvist T. Cognitive consequences of cannabis use: Comparison with abuse of stimulants and heroin with regard to attention, memory and executive functions. Pharmacol. Biochem. Behav. 2005; 81:319–330.
(7) Rubino T, Parolaro D. Long lasting consequences of cannabis exposure in adolescence. Mol. Cell. Endocrinol. 2008; 286(1-2 Suppl 1):S108–13.
(8) Trezza V, Cuomo V, Vanderschuren LJMJ. Cannabis and the developing brain: insights from behavior. Eur. J. Pharmacol. 2008; 585:441–52.
(9) Anderson P, Baumberg B. Alcohol in Europe: A Public Health Perspective.; 2006.
(10) Moyer A, Finney JW, Swearingen CE, Vergun P. Brief interventions for alcohol problems: a meta-analytic review of controlled investigations in treatment-seeking and non-treatment-seeking populations. Addiction 2002; 97:279–92.
(11) Werner MJ. Principles of brief intervention for adolescent alcohol, tobacco, and other drug use. Pediatr. Clin. North Am. 1995; 42:335–49.
(12) Tevyaw TO, Monti PM. Motivational enhancement and other brief interventions for adolescent substance abuse: foundations, applications and evaluations. Addiction. 2004; 99 Suppl 2:63–75.
(13) Tait RJ, Hulse GK. A systematic review of the effectiveness of brief interventions with substance using adolescents by type of drug. Drug Alcohol Rev. 2003; 22:337–46. Available at: Accessed November 27, 2013.
(14) Toumbourou JW, Stockwell T, Neighbors C, Marlatt GA, Sturge J, Rehm J. Interventions to reduce harm associated with adolescent substance use. Lancet. 2007; 369:1391–401.
(15) Arnaud N, Bröning S, Drechsel M, Thomasius R, Baldus C. Web-based screening and brief intervention for poly-drug use among teenagers: study protocol of a multicentre two-arm randomized controlled trial. BMC Public Health. 2012; 12:826.
(16) Barnett NP, Murphy JG, Colby SM, Monti PM. Efficacy of counselor vs. computer-delivered intervention with mandated college students. Addict. Behav. 2007; 32:2529-48.
(17) Bendtsen P, McCambridge J, Bendtsen M, Karlsson N, Nilsen P. Effectiveness of a proactive mail-based alcohol Internet intervention for university students: dismantling the assessment and feedback components in a randomized controlled trial. J. Med. Internet Res. 2012; 14:e142.
(18) Bewick BM, Trusler K, Mulhern B, Barkham M, Hill AJ. The feasibility and effectiveness of a web-based personalised feedback and social norms alcohol intervention in UK university students: a randomised control trial. Addict. Behav. 2008; 33:1192–8.
(19) Butler LH, Correia CJ. Brief alcohol intervention with college student drinkers: face-to-face versus computerized feedback. Psychol. Addict. Behav. 2009; 23:163–7.
(20) Carey KB, Carey MP, Maisto SA, Henson JM. Computer Versus In-Person Intervention for Students Violating Campus Alcohol Policy. J Consult Clin Psychol. 2009; 77:74–87.
(21) Croom K, Lewis D, Marchell T, et al. Impact of an online alcohol education course on behavior and harm for incoming first-year college students: short-term evaluation of a randomized trial. J Am. Coll. Health. 2009; 57:445–54.

(22) Doumas DM, Hannah E. Preventing high-risk drinking in youth in the workplace: a web-based normative feedback program. J. Subst. Abuse Treat. 2008; 34:263–71.
(23) Doumas DM, McKinley LL, Book P. Evaluation of two Web-based alcohol interventions
for mandated college students. J. Subst. Abuse Treat. 2009; 36:65–74.

(24) Elgán TH, Hansson H, Zetterlind U, Kartengren N, Leifman H. Design of a Webbased individual coping and alcohol-intervention program (web-ICAIP) for children of parents with alcohol problems: study protocol for a randomized controlled trial. BMC Public Health. 2012; 12:35.
(25) Hendershot CS, Otto JM, Collins SE, Liang T, Wall TL. Evaluation of a brief web-based genetic feedback intervention for reducing alcohol-related health risks associated with ALDH2. Ann. Behav. Med. 2010; 40:77–88.
(26) Kypri K, Saunders JB, Williams SM, et al. Web-based screening and brief intervention for hazardous drinking: a double-blind randomized controlled trial. Addiction. 2004; 99:1410–7.
(27) Kypri K, Langley JD, Saunders JB, Cashell-Smith ML, Herbison P. Randomized controlled trial of web-based alcohol screening and brief intervention in primary care. Arch. Intern. Med. 2008; 168:530–6.
(28) Kypri K, Hallett J, Howat P, et al. Randomized controlled trial of proactive webbased alcohol screening and brief intervention for university students. Arch. Intern. Med. 2009; 169:1508–14.
(29) Kypri K, McCambridge J, Vater T, et al. Web-based alcohol intervention for Māori university students: double-blind, multi-site randomized controlled trial. Addiction. 2013; 108:331–8.
(30) Lee CM, Neighbors C, Kilmer JR, Larimer ME. A brief, web-based personalized feedback selective intervention for college student marijuana use: a randomized clinical trial. Psychol. Addict. Behav. 2010; 24:265–73.
(31) Lewis MA, Neighbors C. Optimizing personalized normative feedback: the use of gender-specific referents. J. Stud. Alcohol Drugs. 2007; 68:228–37.
(32) Lewis MA, Neighbors C, Oster-Aaland L, Kirkeby BS, Larimer ME. Indicated prevention for incoming freshmen: personalized normative feedback and highrisk drinking. Addict. Behav. 2007; 32:2495–508.
(33) Maio RF, Shope JT, Blow FC, et al. A randomized controlled trial of an emergency department-based interactive computer program to prevent alcohol misuse among injured adolescents. Ann. Emerg. Med. 2005; 45:420–9.
(34) Moore MJ, Soderquist J, Werch C. Feasibility and efficacy of a binge drinking prevention intervention for college students delivered via the Internet versus postal mail. J Am. Coll. Health. 2005; 54:38–44.
(35) Murphy JG, Dennhardt A a, Skidmore JR, Martens MP, McDevitt-Murphy ME. Computerized versus motivational interviewing alcohol interventions: impact on discrepancy, motivation, and drinking. Psychol. Addict. Behav. 2010;24(4):628–39.
(36) Neighbors C, Larimer ME, Lewis M a. Targeting misperceptions of descriptive drinking norms: efficacy of a computer-delivered personalized normative feedback intervention. J. Consult. Clin. Psychol. 2004; 72:434–47.
(37) Neighbors C, Lewis MA, Bergstrom RL, Larimer ME. Being controlled by normative influences: self-determination as a moderator of a normative feedback alcohol intervention. Health Psychol. 2006; 25:571–9.
(38) Neighbors C, Lee CM, Lewis MA, Fossos N, Walter T. Internet-based personalized feedback to reduce 21st-birthday drinking: a randomized controlled trial of an event-specific prevention intervention. J. Consult. Clin. Psychol. 2009; 77:51–63.
(39) Neighbors C, Lewis MA, Atkins DC, et al. Efficacy of web-based personalized normative feedback: a two-year randomized controlled trial. J. Consult. Clin. Psychol. 2010; 78:898–911.
(40) Neighbors C, Lee CM, Atkins DC, et al. A randomized controlled trial of eventspecific prevention strategies for reducing problematic drinking associated with 21st birthday celebrations. J. Consult. Clin. Psychol. 2012; 80:850–62.
(41) Palfai TP, Zisserson R, Saitz R. Using personalized feedback to reduce alcohol use among hazardous drinking college students: the moderating effect of alcoholrelated negative consequences. Addict. Behav. 2011; 36:539–42.
(42) Paschall MJ, Antin T, Ringwalt CL, Saltz RF. Evaluation of an Internet-based alcohol misuse prevention course for college freshmen: findings of a randomized multi-campus trial. Am. J. Prev. Med. 2011; 41:300–8.
(43) Saitz R, Palfai TP, Freedner N, et al. Screening and brief intervention online for college students: the ihealth study. Alcohol Alcohol. 2007; 42:28–36.
(44) Spijkerman R, Roek M a E, Vermulst A, Lemmers L, Huiberts A, Engels RCME. Effectiveness of a web-based brief alcohol intervention and added value of normative feedback in reducing underage drinking: a randomized controlled trial. J. Med. Internet Res. 2010; 12:e65.
(45) Voogt CV, Poelen EA, Kleinjan M, Lemmers LA, Engels RC. Targeting young drinkers online: the effectiveness of a web-based brief alcohol intervention in reducing heavy drinking among college students: study protocol of a two-arm parallel group randomized controlled trial. BMC Public Health. 2011; 11:231.
(46) Voogt CV, Poelen EA, Lemmers LA, Engels RC. The effectiveness of a webbased brief alcohol intervention in reducing heavy drinking among adolescents aged 15 to 20 years with a low educational background: study protocol for a randomized controlled trial. Trials. 2012; 13:83.

(47) Walters ST, Vader AM, Harris TR, Field CA, Jouriles EN. Dismantling motivational interviewing and feedback for college drinkers: a randomized clinical trial. J. Consult. Clin. Psychol. 2009; 77:64–73.
(48) Weitzel JA, Bernhardt JM, Usdan S, Mays D, Glanz K. Using wireless handheld computers and tailored text messaging to reduce negative consequences of drinking alcohol. J. Stud. Alcohol Drugs. 2007; 68:534–7.
(49) Bersamin M, Paschall MJ, Fearnow-Kenney M, Wyrick D. Effectiveness of a Web-based alcohol-misuse and harm-prevention course among high- and low-risk students. J Am. Coll. Health. 2007; 55:247–54.
(50) Brener ND, Billy JO., Grady WR. Assessment of factors affecting the validity of self-reported health-risk behavior among adolescents: evidence from the scientific literature. J. Adolesc. Heal. 2003; 33:436–457.
(51) Barak A, Hen L, Boniel-Nissim M, Shapira N. A Comprehensive Review and a Meta-Analysis of the Effectiveness of Internet-Based Psychotherapeutic Interventions. J. Technol. Hum. Serv. 2008; 26:109–160.
(52) Copeland J, Martin G. Web-based interventions for substance use disorders: a qualitative review. J. Subst. Abuse Treat. 2004; 26:109–16.
(53) Bewick BM, Trusler K, Barkham M, Hill AJ, Cahill J, Mulhern B. The effectiveness of web-based interventions designed to decrease alcohol consumption--a systematic review. Prev. Med. (Baltim). 2008; 47:17–26.
(54) Elliott JC, Carey KB, Bolles JR. Computer-based interventions for college drinking: a qualitative review. Addict. Behav. 2008; 33:994–1005.
(55) Van Hook S, Harris SK, Brooks T, et al. The “Six T’s”: barriers to screening teens for substance abuse in primary care. J. Adolesc. Health. 2007; 40:456–61.
(56) McPherson A. Adolescents in primary care. BMJ. 2005; 330:465–7.
(57) Berra S, Tebé C, Erhart M, et al. Correlates of use of health care services by children and adolescents from 11 European countries. Med. Care. 2009; 47:161–7.

bottom of page