The Use of Photovoice Methodology to Assess Health Needs and Identify Opportunities Among Migrant Transgender Women in the U.S.-Mexico Border
- PMID: 35664104
- PMCID: PMC9160798
- DOI: 10.3389/fpubh.2022.865944
The Use of Photovoice Methodology to Assess Health Needs and Identify Opportunities Among Migrant Transgender Women in the U.S.-Mexico Border
Abstract
Psychosocial, social and structural conditions have rarely been studied among transgender women in the U.S.-Mexico Border. This study used Photovoice methodology to empower migrant transgender women of color (TWC) to reflect on realities from their own perspectives and experiences and promote critical dialogue, knowledge, and community action. Sixteen participants documented their daily experiences through photography, engaged in photo-discussions to assess needs and identify opportunities, and developed a community-informed Call to Action. Four major themes emerged from the participants' photographs, discussions, and engagement: (1) mental health, (2) migration experiences and challenges, (3) stigma, discrimination, and resiliency, and (4) impact of the COVID-19 pandemic. Through active community engagement, a Call to Action was developed. A binational advisory committee of decision makers and scholars reviewed a set of recommendations to better respond to the needs of TWC in the U.S.-Mexico Border. Photovoice served as an empowerment tool for TWC to assess the myriad of syndemic conditions, including mental health, stigma, discrimination and COVID-19, affecting them daily and identify initiatives for change.
Keywords: Photovoice; U.S.-Mexico border; health; mental health; migrants; transgender.
Copyright © 2022 Chavez-Baray, Martinez, Chaparro and Moya.
Conflict of interest statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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References
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- Thakur PR. Stress and Resilience For Transgender Women of Color. Phoenix, AZ: ProQuest Information and Learning; (2020).
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