Developing consensus to enhance perinatal mental health through a model of integrated care: Delphi study.
Christine H K OuZachary DalyMichelle CarterWendy A HallEnav Z ZusmanAngela RussolilloSheila DuffyEmily K JenkinsPublished in: PloS one (2024)
Perinatal mental illness is an important public health issue, with one in five birthing persons experiencing clinically significant symptoms of anxiety and/or depression during pregnancy or the postpartum period. The purpose of this study was to develop a consensus-based model of integrated perinatal mental health care to enhance service delivery and improve parent and family outcomes. We conducted a three-round Delphi study using online surveys to reach consensus (≥75% agreement) on key domains and indicators of integrated perinatal mental health care. We invited modifications to indicators and domains during each round and shared a summary of results with participants following rounds one and two. Descriptive statistics were generated for quantitative data and a thematic analysis of qualitative data was undertaken. Study participants included professional experts in perinatal mental health (e.g., clinicians, researchers) (n = 36) and people with lived experience of perinatal mental illness within the past 5 years from across Canada (e.g., patients, family members) (n = 11). Consensus was reached and all nine domains of the proposed model for integrated perinatal mental health care were retained. Qualitative results informed the modification of indicators and development of an additional domain and indicators capturing the need for antiracist, culturally safe care. The development of an integrated model of perinatal mental health benefitted from diverse expertise to guide the focus of included domains and indicators. Engaging in a consensus-building process helps to create the conditions for change within health services.
Keyphrases
- mental health
- mental illness
- pregnant women
- public health
- healthcare
- palliative care
- systematic review
- type diabetes
- depressive symptoms
- social media
- ejection fraction
- prognostic factors
- chronic kidney disease
- big data
- chronic pain
- artificial intelligence
- weight loss
- adipose tissue
- affordable care act
- health insurance