Background: Perinatal mental illnesses affect up to 20% of mothers and 10% of fathers worldwide, posing risks to both parents and infants. Early detection is crucial to improve outcomes, yet barriers such as stigma and access to care persist. Digital health technologies may facilitate self-identification, offering a promising alternative for early detection of this disease.

Aim: The aim of this systematic review was to assess the effectiveness and safety as primary outcomes and implementation considerations of digital health technologies for self-identification of the risk of perinatal mental illness, with a focus on social, organisational, and legal aspects as secondary outcomes.

Methods: Following a systematic review approach, a systematic literature search on this topic was conducted using a previously formulated search strategy in the online databases PubMed, CINAHL, Web of Science, PsycINFO and The Cochrane Library to identify studies between 2014 and 2024. Data extraction and quality assessment were performed using appropriate critical appraisal tools.

Results: Six studies and one review were included, covering mobile applications, web platforms, and text-based interventions. Nevertheless, no generalisable statements could be made for the primary clinical results on effectiveness and safety, as only one study of limited quality could be included in this review. The non-clinical secondary results showed good acceptance and usability, but with very heterogeneous study data and some limitations as well. Regarding the organisational and legal aspects, no relevant and appropriate literature could be found.

Conclusion: Digital self-identification tools for assessing the risk of perinatal mental illness show potential to overcome barriers, to improve mental health and accessibility but require further high-quality research to proof effectiveness and safety, to further establish regulatory frameworks and organizational pathways.