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Association between user engagement and clinical outcomes in smartphone apps for depression and anxiety: A systematic
Jake Linardon1, John Torous2, Mariel Messer1
1SEED Lifespan Strategic Research Centre, School of Psychology, Faculty of Health, Deakin University, Geelong, VIC, Australia.
Abstract:
Apps targeting symptoms of depression and anxiety have a growing evidence base for their efficacy, yet it remains unclear whether increased user engagement is necessary to enhance their benefits. This systematic review and meta-analysis examined the current evidence on the association between engagement and clinical outcomes in trials of depression and anxiety apps. We included original or secondary analyses of randomized trials of apps delivered to participants with elevated depression or anxiety that reported engagement-outcome relationships. Studies were identified through a previous systematic review and an updated search. Twenty-eight studies met inclusion criteria for the systematic review, and 13 were included in the meta-analysis. Qualitative synthesis revealed heterogeneity in how engagement-outcome associations were reported: >40 different engagement metrics were identified, and 57 % of studies examined multiple metrics as predictors. Averaging across engagement and outcome variables, a significant pooled effect was found (r = 0.16; 95 % CI= 0.09, 0.21), indicating that greater engagement was linked to larger symptom improvement. This effect remained significant following publication bias adjustment and when assuming a zero effect for seven studies that reported non-significant associations but no accompanying data (r = 0.11, 95 % CI= 0.06, 0.16). Significant effects were also observed when modeling specific engagement metrics, symptom outcomes, and app characteristics, although few studies contributed to these analyses. Engagement may play a small role in symptom improvement within depression and anxiety apps. Findings highlight the need for better reporting standards, including which theory-driven engagement metrics should be routinely reported in future research.
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