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An individual participant data meta-analysis of predictors of adherence to internet-based interventions for depression
Vrije Universiteit Amsterdam, Netherlands.
Vrije Universiteit Amsterdam, Netherlands; University of Amsterdam, Netherlands.
Vrije Universiteit Amsterdam, Netherlands; Université Paris Cité, France.
Vrije Universiteit Amsterdam, Netherlands; Technical University of Munich, Germany.
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2026 (English)In: Nature Mental Health, E-ISSN 2731-6076, Vol. 4, p. 1452-1462Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer Nature, 2026. Vol. 4, p. 1452-1462
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Psychiatry
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URN: urn:nbn:se:lnu:diva-149071DOI: 10.1038/s44220-026-00707-4ISI: 001842554500001Scopus ID: 2-s2.0-105046728242OAI: oai:DiVA.org:lnu-149071DiVA, id: diva2:2092961
Available from: 2026-08-17 Created: 2026-08-17 Last updated: 2026-09-14Bibliographically approved

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Kaldo, Viktor

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