Trial reportJournal of medical Internet research2008
Predicting successful treatment outcome of web-based self-help for problem drinkers: secondary analysis from a randomized controlled trial.
Trial report in Journal of medical Internet research, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
30 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Digitally Delivered Cognitive Behavioral Interventions for Alcohol and Other Drug Use: Meta-Analysis Across Consumption and Psychosocial Outcomes.JMIR mental health · 2026Pooled it
- Effectiveness and treatment moderators of internet interventions for adult problem drinking: An individual patient data meta-analysis of 19 randomised controlled trials.PLoS medicine · 2018Pooled it
- Effectiveness of guided and unguided low-intensity internet interventions for adult alcohol misuse: a meta-analysis.PloS one · 2014Pooled it
- Web-based alcohol intervention for veterans: PTSD, combat exposure, and alcohol outcomes.Psychological trauma : theory, research, practice and policy · 2018Trial
- Young People, Adult Worries: Randomized Controlled Trial and Feasibility Study of the Internet-Based Self-Support Method "Feel the ViBe" for Adolescents and Young Adults Exposed to Family Violence.Journal of medical Internet research · 2017Trial
- Overcoming Addictions, a Web-Based Application, and SMART Recovery, an Online and In-Person Mutual Help Group for Problem Drinkers, Part 2: Six-Month Outcomes of a Randomized Controlled Trial and Qualitative Feedback From Participants.Journal of medical Internet research · 2016Trial
- For whom does it work? moderators of outcome on the effect of a transdiagnostic internet-based maintenance treatment after inpatient psychotherapy: randomized controlled trial.Journal of medical Internet research · 2013Trial
- Trial
- Baseline predictors of treatment outcome in Internet-based alcohol interventions: a recursive partitioning analysis alongside a randomized trial.BMC public health · 2013Trial
- Attrition in web-based treatment for problem drinkers.Journal of medical Internet research · 2011Trial
- Curbing alcohol use in male adults through computer generated personalized advice: randomized controlled trial.Journal of medical Internet research · 2011Trial
- Effectiveness of a web-based intervention for problem drinkers and reasons for dropout: randomized controlled trial.Journal of medical Internet research · 2010Trial
- Is internet-based cognitive behavioral therapy for alcohol use disorder equally effective for men and women? Implications of a secondary analysis of a clinical trial.Frontiers in psychiatry · 2024Article
- Digital health interventions to improve eating behaviour of people with a lower socioeconomic position: a scoping review of behaviour change techniques.BMC nutrition · 2022Article
- Efficacy of a Web-Based Intervention for Depressive Disorders: Three-Arm Randomized Controlled Trial Comparing Guided and Unguided Self-Help With Waitlist Control.JMIR formative research · 2022Article
- Social Equity in the Efficacy of Computer-Based and In-Person Brief Alcohol Interventions Among General Hospital Patients With At-Risk Alcohol Use: A Randomized Controlled Trial.JMIR mental health · 2022Article
- Analysis of E-mental health research: mapping the relationship between information technology and mental healthcare.BMC psychiatry · 2022Article
- Predictors of treatment response in a web-based intervention for cannabis users.Internet interventions · 2019Article
- Predictors of Engagement, Response to Follow Up, and Extent of Alcohol Reduction in Users of a Smartphone App (Drink Less): Secondary Analysis of a Factorial Randomized Controlled Trial.JMIR mHealth and uHealth · 2018Article
- User characteristics of a smartphone app to reduce alcohol consumption.Translational behavioral medicine · 2017Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWeb-based self-help interventions for problem drinking are coming of age. They have shown promising results in terms of cost-effectiveness, and they offer opportunities to reach out on a broad scale to problem drinkers. The question now is whether certain groups of problem drinkers benefit more from such Web-based interventions than others.
objectiveWe sought to identify baseline, client-related predictors of the effectiveness of Drinking Less, a 24/7, free-access, interactive, Web-based self-help intervention without therapist guidance for problem drinkers who want to reduce their alcohol consumption. The intervention is based on cognitive-behavioral and self-control principles.
methodsWe conducted secondary analysis of data from a pragmatic randomized trial with follow-up at 6 and 12 months. Participants (N = 261) were adult problem drinkers in the Dutch general population with a weekly alcohol consumption above 210 g of ethanol for men or 140 g for women, or consumption of at least 60 g (men) or 40 g (women) one or more days a week over the past 3 months. Six baseline participant characteristics were designated as putative predictors of treatment response: (1) gender, (2) education, (3) Internet use competence (sociodemographics), (4) mean weekly alcohol consumption, (5) prior professional help for alcohol problems (level of problem drinking), and (6) participants' expectancies of Web-based interventions for problem drinking. Intention-to-treat (ITT) analyses, using last-observation-carried-forward (LOCF) data, and regression imputation (RI) were performed to deal with loss to follow-up. Statistical tests for interaction terms were conducted and linear regression analysis was performed to investigate whether the participants' characteristics as measured at baseline predicted positive treatment responses at 6- and 12-month follow-ups.
resultsAt 6 months, prior help for alcohol problems predicted a small, marginally significant positive treatment outcome in the RI model only (beta = .18, P = .05, R(2) = .11). At 12 months, females displayed modest predictive power in both imputation models (LOCF: beta = .22, P = .045, R(2) = .02; regression: beta = .27, P = .01, R(2) = .03). Those with higher levels of education exhibited modest predictive power in the LOCF model only (beta = .33, P = .01, R(2) = .03).
conclusionsAlthough female and more highly educated users appeared slightly more likely to derive benefit from the Drinking Less intervention, none of the baseline characteristics we studied persuasively predicted a favorable treatment outcome. The Web-based intervention therefore seems well suited for a heterogeneous group of problem drinkers and could hence be offered as a first-step treatment in a stepped-care approach directed at problem drinkers in the general population.
trial registrationInternational Standard Randomized Controlled Trial Number (ISRCTN): 47285230; http://www.controlled-trials.com/isrctn47285230 (Archived by WebCite at http://www.webcitation.org/5cSR2sMkp).
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.