2011
DOI: 10.2196/jmir.1811
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Attrition in Web-Based Treatment for Problem Drinkers

Abstract: BackgroundWeb-based interventions for problem drinking are effective but characterized by high rates of attrition. There is a need to better understand attrition rates in order to improve the completion rates and the success of Web-based treatment programs.ObjectiveThe objectives of our study were to (1) examine attrition prevalence and pretreatment predictors of attrition in a sample of open-access users of a Web-based program for problem drinkers, and (2) to further explore attrition data from our randomized… Show more

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Cited by 79 publications
(75 citation statements)
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References 43 publications
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“…As a study designed to test acceptability in disadvantaged smokers, it was expected that attrition rates would be high. Attrition rates for this study are similar to other interventions on disadvantaged populations (Frack et al, 1997; Goldade et al, 2011; Matthews et al, 2006; Postel et al, 2011; Zeller et al, 2004). Future studies on mindfulness-based smoking interventions could benefit in terms of statistical power from recruitment of less disadvantaged populations and potential of exclusion of smokers who have temporary housing, no cell phones, or who have limited means of transportation.…”
Section: Discussionsupporting
confidence: 69%
“…As a study designed to test acceptability in disadvantaged smokers, it was expected that attrition rates would be high. Attrition rates for this study are similar to other interventions on disadvantaged populations (Frack et al, 1997; Goldade et al, 2011; Matthews et al, 2006; Postel et al, 2011; Zeller et al, 2004). Future studies on mindfulness-based smoking interventions could benefit in terms of statistical power from recruitment of less disadvantaged populations and potential of exclusion of smokers who have temporary housing, no cell phones, or who have limited means of transportation.…”
Section: Discussionsupporting
confidence: 69%
“…Rather than counting how many people drop out before the end of treatment, we think it is more important to focus on the number of sessions completed, and by whom (in combination with reach and effectiveness). Therefore, our conclusions differ slightly from the conclusion of Postel [111]. The criterion for success in eHealth is not to keep participants until the end of treatment, but to keep them long enough to achieve a clinically significant effect on the relevant health behavior.…”
Section: Discussioncontrasting
confidence: 89%
“…For example, in a sample of problem drinkers, enrolled in a 12 session Web-based intervention, a dropout rate of 45% was reported, and the authors concluded that “the challenge of Web-based alcohol treatment programs no longer seems to be their effectiveness but keeping participants involved until the end of the treatment program” [111]. In terms of number of sessions (73) the current intervention is probably the most comprehensive of its class [20-22].…”
Section: Discussionmentioning
confidence: 99%
“…Attrition rates tend to be high in e-health studies, 76 including studies evaluating the effectiveness of e-SBI for reducing excessive drinking. 77 To address this problem, many studies conducted intent-to-treat analyses (i.e., applying non-completers baseline data at follow-up), with results that were similar to participants who were retained. Lastly, this review synthesizes literature that was published by October of 2011, consistent with the evidence available when e-SBI was presented to the Task Force.…”
Section: Discussionmentioning
confidence: 99%