Abstract
ABSTRACTBackgroundThe ability for digital mental health interventions (DMHI) to reduce mental health disparities relies on recruitment of research participants with diverse sociodemographic and self-identity characteristics. Despite its importance, sociodemographic reporting in research is often limited, and the state of reporting practices in DMHI research in particular has not been comprehensively reviewed.ObjectivesTo characterize the state of sociodemographic data reported in randomized controlled trials (RCTs) of app-based DMHIs published globally from 2007 to 2022.MethodsA scoping review of RCTs of app-based DMHIs examined reporting frequency for 16 sociodemographic domains (i.e., Gender) and common category options within each domain (i.e., woman). The search queried five electronic databases. 5079 records were screened and 299 articles were included.ResultsOn average, studies reported 4.64 (SD = 1.79; range 0 - 9) of 16 sociodemographic domains. The most common were Age (97%) and Education (67%). The least common were Housing Situation (6%), Residency/Location (5%), Veteran Status (4%), Number of Children (3%), Sexual Orientation (2%), Disability Status (2%), and Food Security (<1%). Gender or Sex was reported in 98% of studies: Gender only (51%), Sex only (28%), both (<1%), Gender/Sex reported but unspecified (18%). Race or Ethnicity was reported in 48% of studies: Race only (14%), Ethnicity only (14%), both (10%), Race/Ethnicity reported but unspecified (10%).ConclusionsThis review describes widespread underreporting of sociodemographic information in RCTs of app-based DMHIs published from 2007 to 2022. Reporting was often incomplete (i.e., % female only), unclear (i.e., conflation of Gender/Sex), and limited (i.e., only options representing majority groups were reported). Trends suggest reporting somewhat improved in recent years. Diverse participant populations must be welcomed and described in DMHI research to broaden learnings and generalizability of results; a prerequisite of DMHI’s potential to reduce disparities in mental healthcare.STRENGTHS AND LIMITATIONS OF THIS STUDYThis study is the first of its kind to assess global sociodemographic reporting practices in RCTs of treatment outcomes research for app-based DMHIsThis review was both large and comprehensive, screening over 5000 articles leading to the inclusion of nearly 300 articles spanning the entire lifespan of app-based DMHIs and extracting data for a wide array of 16 sociodemographic domainsArticle inclusion criteria allowed for a broad range of DMHI studies, including populations with both clinical and sub-clinical conditionsIt was not feasible to report on the sociodemographic composition of each study sample due to the large number of studies included in the review and the breadth of domains evaluatedThis review is descriptive, and did not formally assess statistical differences in reporting practices between different sub-groups or time periods, or provide any assessment of barriers, facilitators, or solutions to the issues identified
Publisher
Cold Spring Harbor Laboratory