Bearing (Aguantando) With Intimate Partner Violence: A Grounded Theory Study of Self-Silencing Among Hispanic Women Who Experienced Intimate Partner Violence.
Maria Jose BaezaJoseph P De SantisRosina CianelliNicholas MethenyNatalia VillegasPublished in: Qualitative health research (2024)
Hispanic women who experience intimate partner violence (IPV) face unique disparities. They have poorer health outcomes and are less likely to seek help than their non-Hispanic counterparts. When women remain in relationships where IPV occurs and refuse to disclose or seek treatment, they may resort to self-silencing, which can also worsen health outcomes. The purpose of this study was to develop a theory that explains how self-silencing evolves among Hispanic women who experience IPV. Participants were recruited from two research studies focused on Hispanic women's health, and from snowball sampling, which involved referrals by previously registered participants. Data were collected via Zoom® and included individual interviews. A total of 25 women participated in this study. Analysis followed constructive grounded theory levels of analysis described by Charmaz and constant comparative methods described by Glaser and Strauss. A grounded theory entitled Bearing (Aguantando) With Intimate Partner Violence emerged from the data. The theory explains the main strategy Hispanic women use to deal with violence while remaining in a relationship where IPV occurs. The theory is constructed of four categories with subcategories. The results of this study provide an initial framework to understand the self-silencing process among Hispanic women who experience IPV. In addition, this study identifies different levels of interventions that can be useful for researchers and healthcare providers to promote Hispanic women's ability to become empowered, use their voices, and seek help.
Keyphrases
- intimate partner violence
- polycystic ovary syndrome
- healthcare
- pregnancy outcomes
- cervical cancer screening
- african american
- mental health
- type diabetes
- public health
- gene expression
- physical activity
- dna methylation
- insulin resistance
- machine learning
- adipose tissue
- climate change
- metabolic syndrome
- risk assessment
- human health