The Drinker's Check-up: 12-Month outcomes of a controlled clinical trial of a stand-alone software program for problem drinkers

Brown University, Providence, Rhode Island, United States
Journal of Substance Abuse Treatment (Impact Factor: 3.14). 04/2005; 28(2):159-69. DOI: 10.1016/j.jsat.2004.12.002
Source: PubMed


Sixty-one problem drinkers were randomly assigned to either immediate treatment or a 4-week wait-list control group. Treatment consisted of a computer-based brief motivational intervention, the Drinker's Check-up (DCU). Outcomes strongly support the experimental hypotheses and long-term effectiveness of the treatment. Overall, participants reduced the quantity and frequency of drinking by 50%, and had similar reductions in alcohol-related problems that were sustained through 12-month follow-up. The DCU seems to be effective in enhancing problem drinkers' motivation for change.

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Available from: Reid K Hester, Dec 20, 2013
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    • "On the other hand, there is some evidence that people will OUP UNCORRECTED PROOF – FIRSTPROOFS, Thu Jul 17 2014, NEWGEN book.indb 553 7/18/2014 1:22:01 PM accept computer-based assessment and feedback programs (Lustria et al., 2009), which can be as effective as interventions delivered by a person (Hester et al., 2005). Computer-based interventions can easily be reproduced and delivered over the Internet, on mobile devices, or in community-based waiting rooms. "
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    ABSTRACT: Cyberpsychology is a recent branch of psychology whose main research objects are the processes of change induced by new technologies. Some of these processes are related to and involve a variety of affective processes. The discipline’s overlap with affective computing and human-computer interaction in general are significant, yet its psychological origins suggests that the research communities have somewhat different focus. In this chapter we review these histories, and discuss the similarities and differences that are currently found in the two bodies of literature. We focus in particular on how technologies can be used to help people change behavior in both clinical situations (cybertherapy) and in personal development (positive technology/computing and smart health).
    The Oxford Handbook of Affective Computing, Edited by Calvo R., D'Mello S., Gratch J., Kappas A., 01/2015: chapter CyberPsychology and Affective Computing: pages 547-558; Oxford University Press., ISBN: 9780199942237
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    • " (Hester et al. 2005) and Check Your Drinking ( (Cunningham et al. 2009). "
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    ABSTRACT: With an estimated 90 percent or more of alcohol use disorders going untreated (Substance Abuse and Mental Health Services Administration 2012), the search for interventions that easily, effectively, and economi-cally reach more people has become a priority. The landmark 1990 report, Broadening the Base of Treatment for Alcohol Problems (Institute of Medicine 1990), refocused alcohol treatment research toward an emphasis on developing, standardizing, and disseminating new behavioral thera-pies to expand the reach of alcohol treatment. A particularly exciting development on this front has been the creation of computerized versions of interventions shown to be effective in clinical settings.
    Alcohol research : current reviews 09/2014; 36(1):127-130.
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    • "However, as there was no significant (p > .05) main effect or interaction effect of the Action subscale, and because the inclusion of the Action subscale did not substantively influence the main effect of experimental condition observed, the simpler Fischer’s exact test is presented in this paper. Data missing at follow-up were not replaced to mimic the treatment of missing data employed in studies evaluating brief interventions of this type with waiting list control designs [18] and because attrition was not judged likely to be problematica. "
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    ABSTRACT: Employing waiting list control designs in psychological and behavioral intervention research may artificially inflate intervention effect estimates. This exploratory randomized controlled trial tested this proposition in a study employing a brief intervention for problem drinkers, one domain of research in which waiting list control designs are used. All participants (N = 185) were provided with brief personalized feedback intervention materials after being randomly allocated either to be told that they were in the intervention condition and that this was the intervention or to be told that they were in the waiting list control condition and that they would receive access to the intervention in four weeks with this information provided in the meantime. A total of 157 participants (85%) were followed-up after 4 weeks. Between-group differences were found in one of four outcomes (proportion within safe drinking guidelines). An interaction was identified between experimental manipulation and stage of change at study entry such that participant change was arrested among those more ready to change and told they were on the waiting list. Trials with waiting list control conditions may overestimate treatment effects, though the extent of any such bias appears likely to vary between study populations. Arguably they should only be used where this threat to valid inference has been carefully assessed.
    BMC Medical Research Methodology 12/2013; 13(1):150. DOI:10.1186/1471-2288-13-150 · 2.27 Impact Factor
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