Promoting Resilience among Middle-Aged and Older Men Who Have Sex with Men Living with HIV/AIDS in Southern Nevada: An Examination of Facilitators and Challenges from a Social Determinants of Health Perspective
Bibliographic record
Abstract
Most prior research on resilience to HIV/AIDS among middle-aged and older men who have sex with men (MSM) has utilized quantitative methods that employ surveys and scales to measure constructs researchers have used to approximate the concept of resilience to HIV/AIDS. Only a few studies have purposively made efforts to incorporate the input of relevant stakeholders to guide their research on HIV/AIDS resilience and examine the perspectives and lived experiences of middle-aged and older MSM. To address this research gap, we conducted a community-based participatory research qualitative study to examine the perspectives and lived experiences of HIV-positive, middle-aged and older MSM from Southern Nevada in order to identify factors that promote such resilience. We conducted 16 semi-structured interviews with middle-aged and older MSM living with HIV/AIDS from January to April 2022. From our thematic analysis of our interviews, we identified factors that served as facilitators or challenges to the promotion of our participants' HIV/AIDS resilience. We discuss in this article both the facilitators and challenges to our participants' resilience-building as the key themes from our interviews. We recognized that the impacts of these factors were mediated by their strong influence on the social determinants of health that were explicitly relevant to our participants. We offer important insights based on our findings, which could be especially useful to future research on resilience to HIV/AIDS.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".