Mitigating Risks and Building Resilience to HIV/AIDS: Perspectives of HIV-Negative, Middle-Aged and Older Men Who Have Sex with Men
Bibliographic record
Abstract
Purpose : Although ample research has been conducted on resilience to HIV/AIDS, most studies have utilized quantitative methods and focused almost exclusively on people living with HIV/AIDS. A relatively untapped source of knowledge is the perspectives of HIV-negative, middle-aged and older men who have sex with men (MSM) who have been navigating risks and building resilience to HIV/AIDS since the 1980s. Our qualitative, community-based participatory research study examined the perspectives of HIV-negative, middle-aged and older MSM on factors that helped mitigate the risks of and build resilience to HIV/AIDS. Methods : In collaboration with community-based organizations, fourteen participants were recruited for in-depth interviews. Participants were aged 40 or older, identified as HIV-negative MSM, and resided in Ontario, Canada. Thematic analysis of interviews revealed salient themes. Results : Three themes were identified: (1) individual attributes (e.g., self-awareness/control), (2) protective relational factors (e.g., meaningful sexual relationships), and (3) community-based resources (e.g., competent healthcare/service providers). Conclusion : HIV-negative, middle-aged and older MSM recognized factors that helped mitigate risks of contracting and build resilience to HIV/AIDS based on their own lived experiences. Some of these factors have not been explicitly identified or extensively discussed in extant academic literature, and are worth considering in the development of community-based HIV/AIDS prevention and intervention programs.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".