Multidimensional Influences on Prenatal Cannabis Use: A Mixed Methods Study

Abstract

Background: Rates of prenatal cannabis use (PCU) have more than doubled in recent years, disproportionately impacting birthing people with lower incomes and mental health conditions. Existing PCU research is fragmented, marked by methodological challenges, and constrained by a complicated socio-political landscape. To understand and address PCU, research is needed to (1) measure PCU in a way that reflects real-world patterns, (2) identify multidimensional influences on PCU, and (3) center the perspectives of birthing people who use cannabis. Methods: This mixed-methods study analyzed secondary qualitative and quantitative data from pregnant cannabis users enrolled in a community-based program in Wisconsin. Quantitative data were analyzed longitudinally using generalized estimating equations (GEE), and reflexive thematic analysis was used to analyze qualitative data. A mixed methods convergent parallel design integrated the findings. The study was guided by a new conceptual framework, drawing from the Integrated Behavioral Model and Lifecourse Theory. Results: In quantitative analyses, levels of preconception cannabis use and concurrent tobacco use emerged as the most significant predictors of PCU patterns over the prenatal period. Qualitative findings underscored the impact of mental health and stress as primary drivers of PCU. Notably, social factors were influential in both quantitative and qualitative analyses, highlighting their critical role in shaping cannabis use behaviors during pregnancy. Significance: This study is one of the few that used GEE to measure prenatal cannabis use, centered perspectives and experiences of birthing people, and used mixed methods to integrate findings, leading to a more complete picture of this critical maternal and child health issue. The findings from this study carry important implications across several domains, including (1) improving measurement strategies, (2) expanding access to unbiased and scientifically based information, (3) designing equitable clinical and community interventions, (4) cross-sector collaboration, (5) informing policy changes, and (6) prioritizing participatory approaches.