JMIR Publications

ABSTRACT

Background:

Engagement with Digital Behavior Change Interventions (DBCI) is considered a prerequisite for intervention efficacy. In many trials on DBCIs, however, participants use the intervention only little or not at all.

Objective:

We aimed to explore (1) whether engagement with a web-based alcohol intervention is related to drinking outcomes, (2) which user demographics and clinical or psychological baseline characteristics are associated with measures of engagement and (3) whether reported outcomes are associated with data captured by voluntary intervention-questionnaires.

Methods:

We analyzed data of the intervention arm of a randomized controlled trial (RCT) on a DBCI to reduce risky alcohol consumption. Data was 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. Psychological baseline characteristics included readiness to change, alcohol related outcome expectancies and alcohol abstinence self-efficacy. Following a bivariate approach, we performed two-tailed Welch’s T-Tests, Wilcoxon-Mann-Whitney-Tests or calculated correlation coefficients respectively.

Results:

Data of 306 users was analyzed. Time spent engaging with the intervention as measured by system usage, data did not match self-reported usage. Higher self-reported usage was associated with higher reductions in average daily alcohol consumption (T1: ρ = .39, P < .001; T2: ρ = .29, P =.015) and in binge drinking days (T1: ρ = .62, P < .001; T2: ρ = .3, P =.006). Higher usage was reported from singles (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 work (T1: P = .001; T2: P = .004). Relationships between self-reported usage and clinical or psychological baseline characteristics were complex. For system-usage data findings were mixed. Reductions in drinking captured by intervention-questionnaires were associated with reported outcomes.

Conclusions:

We discuss why self-reported usage could be consistently linked to changes in drinking behavior, while system usage data was not. Also, we propose potential explanations for the complex relationships between engagement and clinical as well as psychological variables. We conclude that self-reports of engagement are a promising topic for future research and short ecological momentary assessments of engagement and of behavior change might aid the tailoring of intervention content.