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    Internet and computer based interventions for cannabis use: A meta-analysis

    193695_193695.pdf (401.7Kb)
    Access Status
    Open access
    Authors
    Tait, Robert
    Spijkerman, R.
    Riper, H.
    Date
    2013
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Tait, Robert J. and Spijkerman, Renske and Riper, Heleen. 2013. Internet and computer based interventions for cannabis use: A meta-analysis. Drug and Alcohol Dependence. 133: pp. 295-304.
    Source Title
    Drug and Alcohol Dependence
    DOI
    10.1016/j.drugalcdep.2013.05.012
    ISSN
    03768716
    Remarks

    NOTICE: this is the author’s version of a work that was accepted for publication in Drug and Alcohol Dependence. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Drug and Alcohol Dependence, Vol. 133 (2013). DOI: 10.1016/j.drugalcdep.2013.05.012

    URI
    http://hdl.handle.net/20.500.11937/36404
    Collection
    • Curtin Research Publications
    Abstract

    Background: Worldwide, cannabis is the most prevalently used illegal drug and creates demand for prevention and treatment services that cannot be fulfilled using conventional approaches. Computer and Internet-based interventions may have the potential to meet this need. Therefore, we systematically reviewed the literature and conducted a meta-analysis on the effectiveness of this approach in reducing the frequency of cannabis use. Methods: We systematically searched online databases (Medline, PubMed, PsychINFO, Embase) for eligible studies and conducted a meta-analysis. Studies had to use a randomized design, be delivered either via the Internet or computer and report separate outcomes for cannabis use. The principal outcome measure was the frequency of cannabis use. Results: Data were extracted from 10 studies and the meta-analysis involved 10 comparisons with 4,125 participants. The overall effect size was small but significant, g = 0.16 (95% confidence interval (CI) 0.09-0.22 P < 0.001) at post-treatment. Subgroup analyses did not reveal significant subgroup differences for key factors including type of analysis (intention-to-treat, completers only), type of control (active, waitlist), age group (11-16, 17+ years), gender composition (female only, mixed), type of intervention (prevention, ‘treatment’), guided versus unguided programs, mode of delivery (Internet, computer), individual versus family dyad and venue (home, research setting). Also, no significant moderation effects were found for number of sessions and time to follow-up. Finally, there was no evidence of publication bias. Conclusions: Internet and computer interventions appear to be effective in reducing cannabis use in the short-term albeit based on data from few studies and across diverse samples.

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