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Adherence Reporting in Randomized Controlled Trials Examining Manualized Multisession Online Interventions: Systematic Review of Practices and Proposal for Reporting Standards. | LitMetric

Background: Adherence reflects the extent to which individuals experience or engage with the content of online interventions and poses a major challenge. Neglecting to examine and report adherence and its relation to outcomes can compromise the interpretation of research findings.

Objective: The aim of this systematic review is to analyze how adherence is accounted for in publications and to propose standards for measuring and reporting adherence to online interventions.

Methods: We performed a systematic review of randomized controlled trials on online interventions for the prevention and treatment of common mental disorders (depression, anxiety disorders, substance related disorders, and eating disorders) published between January 2006 and May 2018 and indexed in Medline and Web of Science. We included primary publications on manualized online treatments (more than 1 session and successive access to content) and examined how adherence was reported in these publications.

Results: We identified 216 publications that met our inclusion criteria. Adherence was addressed in 85% of full-text manuscripts, but only in 31% of abstracts. A median of three usage metrics were reported; the most frequently reported usage metric (61%) was intervention completion. Manuscripts published in specialized electronic health journals more frequently included information on the relation of adherence and outcomes.

Conclusions: We found substantial variety in the reporting of adherence and the usage metrics used to operationalize adherence. This limits the comparability of results and impedes the integration of findings from different studies. Based on our findings, we propose reporting standards for future publications on online interventions.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6713038PMC
http://dx.doi.org/10.2196/14181DOI Listing

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