Experience of Vulnerable Women Narrated through the Body-Mapping Technique.
Jacqueline de SouzaCarla Aparecida Arena VenturaJordana Luiza Gouvêa de OliveiraLoraine Vivian GainoJuliana Cristina Dos Santos MonteiroJaqueline Lemos de OliveiraLeticia Yamawaka de AlmeidaSolina RichterDenise Saint-ArnaultPublished in: International journal of environmental research and public health (2021)
Vulnerable women are considered a priority in public policies and research agendas. It is necessary to understand better the specificities of their daily lives and the meanings they attribute to their experiences, as this undoubtedly contributes to more grounded and culturally appropriate practices. Additionally, innovative techniques in qualitative research are demanded in academia. This narrative research study was carried out with fourteen women from a Brazilian socioeconomically vulnerable neighborhood. We used the body-mapping technique to investigate the experiences of women with mental health disorders or psychosocial distress. The aim was to analyze the self-perception about daily stressors and discuss the feasibility of this technique to facilitate this group's storytelling. Data collection was performed through focus groups, guided by the body-mapping technique steps, and supplemented with individual interviews. Interpersonal conflicts and violence were the main stressors. These strongly impacted the well-being of these women and their children. Some important personal qualities and resilience were identified. Body-mapping played a fundamental role in facilitating storytelling. It amplified the linguistic possibilities for participants to express their feelings and promoted reflections about the present, past, and glimpses into the future.
Keyphrases
- mental health
- polycystic ovary syndrome
- high resolution
- pregnancy outcomes
- healthcare
- physical activity
- high density
- cervical cancer screening
- primary care
- breast cancer risk
- young adults
- mental illness
- systematic review
- climate change
- pregnant women
- type diabetes
- emergency department
- depressive symptoms
- mass spectrometry
- electronic health record
- artificial intelligence