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Exploring intersectionality in psychoneuroendocrinology research: A systematic review
Natalie A Green1, Mariana Rodrigues2, Stephanie Espinoza Perez2
1Silver School of Social Work, New York University, New York, NY, USA; Department of Social & Behavioral Sciences, New York University School of Global Public Health, New York, NY, USA.
Purpose:
While more fields are recognizing the importance of an intersectionality framework and the need to incorporate it into scientific research, conceptual and methodological challenges still arise. Thus, in this review we aim to systematically review the application of the intersectionality framework within the existing psychoneuroendocrinology literature.
Methods:
A search was conducted on PubMed, APA PsycNet, CINAHL, Web of Science, Scopus, and Google Scholar between July and September of 2024 using specific keywords related to intersectionality and psychoneuroendocrinology.
Results:
Thirty-two studies proposed intersectionality-related concepts in their study. However, only two-thirds defined intersectionality or integrated such a framework as a part of their methodological strategy. Out of existing psychoneuroendocrinology fields, four topics emerged, including: women's health, mental health, inflammation, and cardiovascular disease (CVD).
Conclusion:
Studies using an intersectionality framework must move beyond subgroup analysis and examining identities such as race and gender to include other salient aspects such as immigration status, disability or health status. Furthermore, more efforts need to be made to disentangle race and ethnicity as well as gender and sex. Future research priorities were identified, including (1) developing a comprehensive strategy for incorporating an intersectionality framework throughout all the study stages, (2) integrating additional dimensions of identities and power structures, and (3) utilizing different statistical analytical strategies beyond traditional analysis, such as Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA).
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