Our aim was to explore intersectional tensions affecting Asian-Indian immigrant women’s mental health.
Mental health is a serious and globally prevalent health care issue, though certain groups—such as immigrants—are specifically vulnerable to experiencing negative mental health consequences. Immigration alone is known to cause stress that can affect mental health, yet literature is lacking on AI immigrant mental health needs and preferences for care in the US. However, recent studies have identified AI women, both English and those with Punjabi language preference, to be at high risk of experiencing mental health issues (Roberts, Mann, Montgomery 2016; Roberts, Mann, Montgomery, 2015). The confluence of immigration stress and gender discrimination from within the community and the dominant society predisposes AI immigrants, especially women, to mental health issues. Within the US, AI immigrants are one of the fastest growing minority groups , with many residing in California, including Punjabi AI immigrants (Chandra, Arora, Mehta, Asnaani, & Radhakrishnan 2015).
AI women are particularly vulnerable to experiencing mental health challenges. In addition to typical immigration related stressors such as language barriers, adjusting to minority status and facing discrimination, learning to navigate different education and health care systems, and finding employment, women must also contend with gendered roles, family structure, and intergenerational tensions to a greater extent than their male AI immigrant counterparts. Gender role related factors, such as fertility expectations, shaped by prevailing cultural norms have also been associated with mental health issues (Singh & Bhayana 2015). Thus, AI immigrant women face conflicting social values (Indian vs US), and the combined intersectional effects of gender, race, and class and as a result experience multiple tensions putting them at risk for mental health issues.
In our current era of global migration, using the socio-historical understanding that an intersectional framework provides, of the issues faced by a vulnerable subgroup of AI immigrant women is particularly relevant to addressing the pressing mental health needs.
A community-engaged research approach was used to guide the research design and data collection. As part of a larger study, “Understanding HER PAIN” and in collaboration with Sikh community members, we used convenience sampling, to recruit male and female participants to complete an anonymous survey during events at Gurdwaras (Sikh churches) in Central California. Quantitative data analyses for this paper were conducted with female respondents only (N= 217) and used SPSS 24. For model building purposes, we conducted correlations between independent variables which included standard demographics, a set of intersectionality variables, and depression and anxiety, with our dependent variable, attitudes towards women. Using only significant variables, in addition to mental health variables, we then ran hierarchical linear regression models exploring the additive contribution of these independent variables. Qualitative data collected to contextualize our population’s experiences (which were audio recorded, transcribed verbatim, and coded using grounded theory methods), were then aligned with quantitative results.
Survey language preference, years spent in the United States, education, living jointly with family, integration, number of live births, ability to choose family planning methods, and negative religious coping were significantly correlated with attitudes towards women. Block 1 included education, years in the US, survey language, and living in a joint family, and explained 14% of the model variance; only language was significant. When negative religious coping and integration were added in block 2, 22% of the variance was explained and language, integration, and negative religious coping were significant. In block 3 we added reproductive variables (live births and choosing family planning methods), which accounted for 29% of the variance. Language, integration, live births and choosing family planning methods remained significant. In the final block, depression and anxiety were added; 33% of the variance was explained, and language, integration, live births, choosing family planning methods, depression, and anxiety were significant. Emerging themes highlighted the intergenerational expectation differences for gendered roles, and conflicts experienced between sociocultural expectations and dominant society.
The aim of intersectional analysis is to reveal meaningful distinctions and similarities in order to overcome discriminations and put the conditions in place for all people to fully enjoy their human rights. Nurses involved in direct patient care who understand these tensions affecting the women they serve can be more effective in clinical care provided. It is critical to note that cultural values supersede language proficiency and generational status. Our findings clearly show that there is more to the story than may be readily apparent. Taking time to allow patients to express preferences and concerns will enhance communication and quality of care for culturally diverse women.