{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T18:26:02Z","timestamp":1783103162875,"version":"3.54.6"},"reference-count":48,"publisher":"BMJ","issue":"2","license":[{"start":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T00:00:00Z","timestamp":1770163200000},"content-version":"unspecified","delay-in-days":3,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Union\u2019s Horizon Europe research and innovation programme","award":["Grant Agreement n.101,057,390"],"award-info":[{"award-number":["Grant Agreement n.101,057,390"]}]}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["BMJ Open"],"accepted":{"date-parts":[[2026,1,15]]},"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Mobile health (mHealth) technologies have become increasingly popular for monitoring mental health symptoms and lifestyle behaviours, and are largely reported to be feasible and acceptable to users. However, to date, the efficacy of such technologies to improve perinatal mental health outcomes has been mixed. Within the perinatal context, much of this work has been done in the context of postpartum depression, stemming from electronic health records as well as cohort studies. There is, however, a dearth of studies focusing on depression in pregnancy, and machine learning-based clinical decision support systems remain underexplored. The HappyMums application has been developed to meet this need, and its use across Europe will be tested in this study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods and analysis<\/jats:title>\n                    <jats:p>A total of 1000 pregnant people currently suffering from, or at risk of, antenatal depression will be recruited across six countries. All participants will be between 13 and 28\u2009weeks\u2019 gestation and will be given access to the new purposefully developed HappyMums mobile application, to use from enrolment until 2\u2009months postpartum. The application leverages passively collected data from smartphone sensors relating to physical activity and behaviour, as well as requiring active engagement from the user to complete mental health questionnaires and \u2018game-like\u2019 activities. Digital data types will be combined with traditional mental health measurement methods, such as standardised questionnaires and interviews, to develop novel predictive models capable of identifying mental health trajectories in women at risk of developing antenatal depression and to test the app\u2019s utility for use as personalised risk prediction and depression identification tool. The primary outcome of this study is to determine what proportion of users will continue to use the mobile application and engage with its tasks and activities at least weekly, while secondary exploratory outcomes include assessing usability of the app and testing the predictive ability of a novel machine learning-based model. These outcomes will, for the first time, be assessed by integrating active as well as passive data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Ethics and dissemination<\/jats:title>\n                    <jats:p>Ethical approval has been granted by local research ethics committees in each recruiting centre. At King\u2019s College London (leading the clinical study), the study was reviewed by the East of England\u2014Essex Research Ethics Committee and granted favourable opinion (REC reference 24\/EE\/0129). All other sites collecting participant data have the study approved for local delivery. Findings relating to the primary and secondary outcomes will be submitted for publication in open access, peer-reviewed journals, as well as presentations at conferences as symposia or posters. Findings will be made available to a non-specialist audience through open access digital mental health magazines and promotion on social media.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Trial registration number<\/jats:title>\n                    <jats:p>\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"clintrialgov\" xlink:href=\"NCT06578845\">NCT06578845<\/jats:ext-link>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/bmjopen-2025-106978","type":"journal-article","created":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T15:41:42Z","timestamp":1770219702000},"page":"e106978","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":1,"title":["HappyMums mobile application study protocol: use of a smartphone application to gather data predictive of antenatal depression"],"prefix":"10.1136","volume":"16","clinical-trial-number":[{"clinical-trial-number":"nct06578845","registry":"10.18810\/clinical-trials-gov"},{"clinical-trial-number":"nct06578845","registry":"10.18810\/clinical-trials-gov"}],"author":[{"given":"Kristi","family":"Priestley","sequence":"first","affiliation":[{"name":"Department of Psychological Medicine, King\u2019s College London Institute of Psychiatry Psychology and Neuroscience, London, England, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-2985-9769","authenticated-orcid":false,"given":"Riddhi","family":"Laijawala","sequence":"additional","affiliation":[{"name":"Department of Psychological Medicine, King\u2019s College London Institute of Psychiatry Psychology and Neuroscience, London, England, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katie","family":"Hazelgrove","sequence":"additional","affiliation":[{"name":"Department of Psychological 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