Abstract

BackgroundEngagement with digital behavior change interventions (DBCIs) is considered a prerequisite for intervention efficacy. However, in many trials on DBCIs, participants use the intervention either only little or not at all.ObjectiveTo analyze engagement with a web-based intervention to reduce harmful drinking, we explored (1) whether engagement with a web-based alcohol intervention is related to drinking outcomes, (2) which user characteristics are associated with measures of engagement, and (3) whether reported outcomes are associated with data captured by voluntary intervention questionnaires.MethodsWe analyzed data of the intervention arm of a randomized controlled trial on a DBCI to reduce risky alcohol consumption. Data were collected at baseline (T0), after 90 days (T1), and at the end of the 180-day usage period (T2). Engagement with the intervention was measured via system usage data as well as self-reported usage. Drinking behavior was measured as average daily alcohol consumption as well as the number of binge drinking days. User characteristics included demographics, baseline drinking behavior, readiness to change, alcohol-related outcome expectancies, and alcohol abstinence self-efficacy. Following a bivariate approach, we performed two-tailed Welch’s t tests and Wilcoxon signed rank/Mann-Whitney U tests or calculated correlation coefficients.ResultsThe data of 306 users were analyzed. Time spent engaging with the intervention as measured by system usage did not match self-reported usage. Higher self-reported usage was associated with higher reductions in average daily alcohol consumption (T1: ρ=0.39, P<.001; T2: ρ=0.29, P=.015) and in binge drinking days (T1: ρ=0.62, P<.001; T2: ρ=0.3, P=.006). Higher usage was reported from users who were single (T1: P<.001; T2: P<.001), users without children (T1: P<.001; T2: P<.001), users who did not start or finish secondary education (T1: P<.001; T2: P<.001), users without academic education (T1: P<.001; T2: P<.001), and those who worked (T1: P=.001; T2: P=.004). Relationships between self-reported usage and clinical or psychological baseline characteristics were complex. For system usage, the findings were mixed. Reductions in drinking captured by intervention questionnaires were associated with reported outcomes.ConclusionsThough self-reported usage could be consistently linked to better outcomes and multiple user characteristics, our findings add to the overall inconclusive evidence that can be found throughout the literature. Our findings indicate potential benefits of self-reports as measures of engagement and intervention questionnaires as a basis for tailoring of intervention content. Future studies should adopt a theory-driven approach to engagement research utilizing psychometrically sound self-report questionnaires and include short ecological momentary assessments within the DBCIs.Trial RegistrationGerman Clinical Trials Register DRKS00006104; https://tinyurl.com/y22oc5jo

Highlights

  • In many trials on self-guided digital behavior change interventions (DBCIs), a substantial proportion of participants use the intervention only little or not at all [1]

  • Though self-reported usage could be consistently linked to better outcomes and multiple user characteristics, our findings add to the overall inconclusive evidence that can be found throughout the literature

  • Since we found more drinking days and more binge drinking days (BDDs) at baseline to be positively related to engagement but no relationship for average daily alcohol consumption, our results on baseline problem severity add to the mixed findings of previous studies [11,17]

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Summary

Introduction

In many trials on self-guided digital behavior change interventions (DBCIs), a substantial proportion of participants use the intervention only little or not at all [1]. This phenomenon might limit the validity of trial results, since some form of engagement with the intervention is assumed to be a condition for its efficacy [2]. Perski et al [6] found that the behavioral sciences focus on quantitative aspects of engagement, conceptualizing it as the amount of usage over time. Engagement with digital behavior change interventions (DBCIs) is considered a prerequisite for intervention efficacy. In many trials on DBCIs, participants use the intervention either only little or not at all

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