Contextualising women's mental distress and coping strategies in the time of AIDS: A rural South African case study
Bibliographic record
Abstract
Increasing attention is paid to impacts of HIV/AIDS on women's mental health, often framed by decontextualized psychiatric understandings of emotional distress and treatment. We contribute to the small qualitative literature extending these findings through exploring HIV/AIDS--affected women's own accounts of their distress-focusing on the impacts of social context, and women's efforts to cope outside of medical support services. Nineteen in-depth interviews were conducted with women experiencing depression or anxiety-like symptoms in a wider study of services in KwaZulu-Natal, South Africa. Thematic analysis was framed by Summerfield's emphasis on contexts and resilience. Women highlighted family conflicts (particularly abandonment by men), community-level violence, poverty and HIV/AIDS as drivers of distress. Whilst HIV/AIDS placed significant burdens on women, poverty and relationship difficulties were more central in their accounts. Four coping mechanisms were identified. Women drew on indigenous local resources in their psychological re-framing of negative situations, and their mobilisation of emotional and financial support from inter-personal networks, churches and HIV support groups. Less commonly, they sought expert advice from traditional healers, medical services or social workers, but access to these was limited. Though all tried to supplement government grants with income generation efforts, only a minority regarded these as successful. Findings support ongoing efforts to bolster strained mental health services with support groups, which often offer valuable emotional and practical support. Without parallel poverty alleviation strategies, however, support groups may sometimes offer little more than encouraging passive acceptance of the inevitability of suffering--potentially exacerbating the hopelessness underpinning women's distress.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".