Applying machine learning methods to psychosocial screening data to improve identification of prenatal depression: Implications for clinical practice and research

[1]  Che Ngufor,et al.  Introduction to Machine Learning in Obstetrics and Gynecology , 2022, Obstetrics and gynecology.

[2]  M. Lobel,et al.  Saving time, signaling trust: Using the PROMOTE self-report screening instrument to enhance prenatal care quality and therapeutic relationships , 2022, PEC innovation.

[3]  P. Djurić,et al.  Missingness patterns in a comprehensive instrument identifying psychosocial and substance use risk in antenatal care , 2021, Journal of reproductive and infant psychology.

[4]  P. Cuijpers,et al.  Psychological treatment of perinatal depression: a meta-analysis , 2021, Psychological Medicine.

[5]  Deepti R. Bathula,et al.  Predicting women with depressive symptoms postpartum with machine learning methods , 2021, Scientific Reports.

[6]  Abraham Weizman,et al.  Development and validation of a machine learning‐based postpartum depression prediction model: A nationwide cohort study , 2020, Depression and anxiety.

[7]  B. Levis,et al.  Accuracy of the Edinburgh Postnatal Depression Scale (EPDS) for screening to detect major depression among pregnant and postpartum women: systematic review and meta-analysis of individual participant data , 2020, BMJ.

[8]  Leslie L. Harrison,et al.  Vital Signs: Postpartum Depressive Symptoms and Provider Discussions About Perinatal Depression — United States, 2018 , 2020, MMWR. Morbidity and mortality weekly report.

[9]  Han Liu,et al.  Machine Learning Models for the Prediction of Postpartum Depression: Application and Comparison Based on a Cohort Study , 2019, JMIR medical informatics.

[10]  K. Coxon,et al.  Assessing mental health during pregnancy: An exploratory qualitative study of midwives' perceptions. , 2020, Midwifery.

[11]  M Mofizul Islam,et al.  Barriers and facilitators in antenatal settings to screening and referral of pregnant women who use alcohol or other drugs: A qualitative study of midwives' experience. , 2019, Midwifery.

[12]  J. Gollan,et al.  Screening and Treatment After Implementation of a Universal Perinatal Depression Screening Program. , 2019, Obstetrics and gynecology.

[13]  G. Saade,et al.  Trajectories of antenatal depression and adverse pregnancy outcomes: 87 , 2019, American journal of obstetrics and gynecology.

[14]  ACOG Committee Opinion No. 757: Screening for Perinatal Depression. , 2018, Obstetrics and gynecology.

[15]  D. Waters,et al.  Barriers to antenatal psychosocial assessment and depression screening in private hospital settings. , 2017, Women and birth : journal of the Australian College of Midwives.

[16]  T. Field.  Prenatal Depression Risk Factors, Developmental Effects and Interventions: A Review. , 2017, Journal of pregnancy and child health.

[17]  F. Bahlmann,et al.  Risk and protective factors for antepartum and postpartum depression: a prospective study , 2016, Journal of psychosomatic obstetrics and gynaecology.

[18]  Elizabeth R. Peterson,et al.  A review of longitudinal studies on antenatal and postnatal depression , 2016, Archives of Women's Mental Health.

[19]  K. Turner,et al.  Midwives and women's views on using UK recommended depression case finding questions in antenatal care. , 2016, Midwifery.

[20]  J. Najman,et al.  A systematic review and meta-analysis of the association between unintended pregnancy and perinatal depression. , 2016, Journal of affective disorders.

[21]  E. Accortt,et al.  Prenatal Depression and Adverse Birth Outcomes: An Updated Systematic Review , 2015, Maternal and Child Health Journal.

[22]  G. Bonsel,et al.  Patient Versus Professional Based Psychosocial Risk Factor Screening for Adverse Pregnancy Outcomes , 2014, Maternal and Child Health Journal.

[23]  D. Davalos,et al.  Untreated prenatal maternal depression and the potential risks to offspring: a review , 2012, Archives of Women's Mental Health.

[24]  Constantine Frangakis,et al.  Multiple imputation by chained equations: what is it and how does it work? , 2011, International journal of methods in psychiatric research.

[25]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[26]  J. Webster,et al.  Screening for Partner Violence: Direct Questioning or Self-Report? , 2004, Obstetrics and gynecology.

[27]  B. Nuwayhid,et al.  A comparison of standardized measures of psychosocial variables with single-item screening measures used in an urban obstetric clinic. , 2002, Journal of obstetric, gynecologic, and neonatal nursing : JOGNN.

[28]  J. Cox,et al.  Detection of Postnatal Depression , 1987, British Journal of Psychiatry.

[29]  Brandon M. Greenwell,et al.  Interpretable Machine Learning , 2019, Hands-On Machine Learning with R.

[30]  M. O’Hara,et al.  Perinatal mental illness: definition, description and aetiology. , 2014, Best practice & research. Clinical obstetrics & gynaecology.

[31]  D. Midmer,et al.  Assessing antenatal psychosocial health. Randomized controlled trial of two versions of the ALPHA form. , 2004, Canadian family physician Medecin de famille canadien.