Perinatal mood and anxiety disorders (PMAD) are the most common, yet under-diagnosed and undertreated complication of pregnancy, affecting up to 50% of pregnant and parenting teens. PMAD are a global health issue that can have devastating effects on the mental, physical, emotional, developmental health, and social life of the mother, infant, and family. Adolescents present with similar symptoms of PMAD as their adult counterparts, but also experience isolation from their peer group and lack of resources and coping strategies, as well as difficulty sleeping and lack of concentration and ability to focus. Nurses and nurse practitioners are in an ideal position to assess preexisting risk factors for PMAD. The current applied evidence-based article addresses the diagnosis of PMAD, provides a conceptual framework for understanding the intra- and interpersonal dynamics affecting teens with PMAD, and suggests a new screening tool to guide diagnosis. An easy to recall mnemonic for diagnosis and referral (SAIL AHEAD) is proposed. By using the SAIL AHEAD mnemonic, providers will impact adolescents' parenting success and resiliency, thereby enhancing their future success in life. [Journal of Psychosocial Nursing and Mental Health Services, 55(6), 23-29.].

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http://dx.doi.org/10.3928/02793695-20170519-03DOI Listing

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Article Synopsis
  • Machine learning is used to improve the screening of perinatal mood and anxiety disorders (PMADs), highlighting the need to address biases in electronic health records (EHRs) that can affect predictive models.
  • The study took place from 2020 to 2023 at Cedars-Sinai Medical Center and included birthing patients aged 14 to 59 who had recent births.
  • Multiple machine learning models were assessed for their ability to predict PMAD risks, focusing on fairness and accuracy, specifically comparing outcomes across different racial and ethnic groups.
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Impact of Postpartum Mental Illness Upon Infant Development.

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