Examining Predictors and Outcomes of U.S. Quality Maternity Leave
Abstract
Maternity leave includes the time that mothers take off from work to care for their baby and heal after childbirth. Despite the growth of mothers in the U.S. workforce, the U.S. lags behind other countries in offering paid maternity leave, resulting in poor quality leave for working mothers. Scholars have continually examined maternity leave as an objective construct and this method of measurement, while important, may be inadequate in capturing mothers’ experiences. Quality maternity leave (QML) is a novel construct that captures mothers’ subjective leave experiences and includes time off, benefits, coworker support, flexibility, and an absence of workplace discrimination and microaggressions. However, little is known regarding individual predictors and outcomes of QML. Therefore, I will discuss prevalent societal-level, work-level, and individuallevel predictors of QML and well-being and work-related outcomes of QML. I will also integrate these into a conceptual framework that researchers can use understand what may affect and result from QML. This review has important practical implications for US policymakers and organizations regarding their support of mothers in society and the workplace. Future research should continue to build on this framework to ensure that mothers are provided the QML they need to thrive.
Degree
Ph.D.
Advisors
Deemer, Purdue University.
Subject Area
Clinical psychology|Labor relations|Mental health|Psychology
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