Sparklinglight Transactions on Artificial Intelligence and Quantum Computing
Abstract
Abstract
Depression is a leading mental health disorder. Depression occurring during the perinatal and postpartum periods has become highly prevalent throughout the world, impacting 5-10% of women during (van de Loo et al., 2018) and 9-23.5% postpartum (Bauman et al., 2020). Proper diagnosis and treatment of perinatal and postpartum depression (PPD) is crucial, as depression can lead to poor outcomes including relationship complications and negatively affect child development (Slomain, 2019). The implementation of screening tools can help identify women at risk based on their signs and symptoms of PPD (Bauman et al., 2020). The primary goal of this project was to implement a standardized tool at a telehealth company for all providers to use to screen for perinatal and PPD and to provide further education to these providers regarding PPD. Pre and post-intervention questionnaires were utilized to assess the change in providers\u27 knowledge and attitudes regarding PPD following an educational session on PPD. Prior to the educational sessions, 36% of participants felt strongly comfortable in addressing mental health concerns with this population, and 73% felt strongly comfortable in the post-survey. Additionally, there was an improvement in identifying signs and symptoms of depression, as well as increased comfortability with treating this patient population. Education on PPD and the introduction of evidence-based screening guidelines provide valuable tools for providers to use when caring for populations impacted by postpartum depression. The implementation of a postpartum depression screening tool can help providers deliver high-quality and holistic care to both new and expecting mothers
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