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Predicting perinata...
Predicting perinatal health outcomes using smartphone-based digital phenotyping and machine learning in a prospective Swedish cohort (Mom2B) : study protocol
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- Bilal, Ayesha (author)
- Uppsala universitet,WoMHeR (Centre for Women’s Mental Health during the Reproductive Lifespan),Cervenka: Psykiatri
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- Fransson, Emma, PhD, 1973- (author)
- Karolinska Institutet,Uppsala universitet,Obstetrisk och reproduktiv hälsoforskning,Karolinska Inst, Ctr Translat Microbiome Res, Dept Microbiol Tumor & Cell Biol, Stockholm, Sweden.
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- Bränn, Emma, 1988- (author)
- Uppsala universitet,Obstetrisk och reproduktiv hälsoforskning
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- Eriksson, Allison (author)
- Uppsala universitet,Obstetrisk och reproduktiv hälsoforskning,WoMHeR (Centre for Women’s Mental Health during the Reproductive Lifespan)
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- Zhong, Mengyu (author)
- Uppsala universitet,Avdelningen för visuell information och interaktion,WoMHeR (Centre for Women’s Mental Health during the Reproductive Lifespan)
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- Gidén, Karin (author)
- Uppsala universitet,Obstetrisk och reproduktiv hälsoforskning
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- Elofsson, Ulf (author)
- Uppsala universitet,Obstetrisk och reproduktiv hälsoforskning,Cervenka: Psykiatri
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- Axfors, Cathrine (author)
- Uppsala universitet,Obstetrisk och reproduktiv hälsoforskning
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- Skalkidou, Alkistis, 1977- (author)
- Uppsala universitet,Obstetrisk och reproduktiv hälsoforskning
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- Papadopoulos, Fotios, 1976- (author)
- Uppsala universitet,Cervenka: Psykiatri
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(creator_code:org_t)
- 2022-04-27
- 2022
- English.
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In: BMJ Open. - : BMJ Publishing Group Ltd. - 2044-6055. ; 12:4
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Abstract
Subject headings
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- Introduction: Perinatal complications, such as perinatal depression and preterm birth, are major causes of morbidity and mortality for the mother and the child. Prediction of high risk can allow for early delivery of existing interventions for prevention. This ongoing study aims to use digital phenotyping data from the Mom2B smartphone application to develop models to predict women at high risk for mental and somatic complications.Methods and analysis: All Swedish-speaking women over 18 years, who are either pregnant or within 3 months postpartum are eligible to participate by downloading the Mom2B smartphone app. We aim to recruit at least 5000 participants with completed outcome measures. Throughout the pregnancy and within the first year postpartum, both active and passive data are collected via the app in an effort to establish a participant's digital phenotype. Active data collection consists of surveys related to participant background information, mental and physical health, lifestyle, and social circumstances, as well as voice recordings. Participants' general smartphone activity, geographical movement patterns, social media activity and cognitive patterns can be estimated through passive data collection from smartphone sensors and activity logs. The outcomes will be measured using surveys, such as the Edinburgh Postnatal Depression Scale, and through linkage to national registers, from where information on registered clinical diagnoses and received care, including prescribed medication, can be obtained. Advanced machine learning and deep learning techniques will be applied to these multimodal data in order to develop accurate algorithms for the prediction of perinatal depression and preterm birth. In this way, earlier intervention may be possible.Ethics and dissemination: Ethical approval has been obtained from the Swedish Ethical Review Authority (dnr: 2019/01170, with amendments), and the project fully fulfils the General Data Protection Regulation (GDPR) requirements. All participants provide consent to participate and can withdraw their participation at any time. Results from this project will be disseminated in international peer-reviewed journals and presented in relevant conferences.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Reproduktionsmedicin och gynekologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Obstetrics, Gynaecology and Reproductive Medicine (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Psykiatri (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Psychiatry (hsv//eng)
Keyword
- depression & mood disorders
- mental health
- maternal medicine
- perinatology
- preventive medicine
- anxiety disorders
Publication and Content Type
- ref (subject category)
- art (subject category)
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BMJ Open
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- By the author/editor
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Bilal, Ayesha
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Fransson, Emma, ...
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Bränn, Emma, 198 ...
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Eriksson, Alliso ...
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Zhong, Mengyu
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Gidén, Karin
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Elofsson, Ulf
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Axfors, Cathrine
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Skalkidou, Alkis ...
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Papadopoulos, Fo ...
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- About the subject
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- MEDICAL AND HEALTH SCIENCES
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MEDICAL AND HEAL ...
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and Clinical Medicin ...
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and Obstetrics Gynae ...
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- MEDICAL AND HEALTH SCIENCES
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MEDICAL AND HEAL ...
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and Psychiatry
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BMJ Open
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Uppsala University
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Karolinska Institutet