An individual participant data meta-analysis of predictors of adherence to internet-based interventions for depression

Internet-based psychological interventions can effectively reduce depressive symptoms in adults, but adherence remains challenging. In this preregistered individual participant data meta-analysis, we examined predictors of treatment adherence. We searched PubMed, Embase and PsycINFO on 6 February 2024 for randomized trials of internet-based interventions among adults with elevated depressive symptoms. We conducted a one-stage logit-link multilevel beta regression, with adherence defined as the proportion of completed modules post-intervention. This study included 71 trials (85 treatment arms, 8,082 participants). Lower adherence was associated with younger age (β = 0.005, standard error (SE) 0.002, P = 0.028), male gender (β = −0.163, SE 0.053, P = 0.002), lower education (β = −0.133, SE 0.05, P = 0.008) and employment (β = −0.113, SE 0.054, P = 0.037). No significant interactions were found between individual predictors and intervention format (guided versus self-guided). Higher adherence was associated with lower post-intervention depression severity, adjusting for baseline severity (β = −0.30, SE 0.04, P < 0.001). Identifying subgroups at risk of low adherence may inform targeted strategies to improve engagement and clinical effectiveness.