Digital health technologies for self-identification of the risk of perinatal mental illness: a systematic review - Sophie Hafner; Yui Hidaka; Jean Lillian Paul; Christine Hörtnagl; Ingrid Zechmeister-Koss (Frontiers in Public Health, 2026)
Background Perinatal mental illness affects up to 20% of mothers and 10% of fathers and is associated with adverse parental and child outcomes. Digital health technologies enabling self-identification of perinatal mental illness risk may improve early detection and reduce access barriers. This systematic review evaluated the effectiveness and safety of digital health technologies for self-identification of the risk of perinatal mental illness and examined social, organizational, and legal aspects relevant to their implementation. Methods A systematic review with narrative synthesis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 statement and Cochrane Handbook for Systematic Reviews of Interventions. Searches were performed in PubMed, CINAHL, Web of Science, PsycINFO, and the Cochrane Library, complemented by gray literature screening and hand search. Methodological quality was assessed using established appraisal tools for the primary outcomes. Results Of 2,762 records identified, seven publications were included. Only one prospective cohort study evaluated effectiveness, showing fair to moderate agreement between digital and conventional methods, with increased risk of bias. Safety data were limited as well. Six studies consistently reported favorable user-related outcomes. No empirical evidence addressed organizational or legal implementation aspects. Discussion Despite consistently positive user-related findings, robust evidence on effectiveness, safety, and system-level implementation is lacking. High-quality research is required before responsible integration into routine perinatal mental healthcare can be considered. Systematic review registration https://doi.org/10.17605/OSF.IO/H78YQ .