The Role of the Social Determinants of Health on Engagement in Physical Activity or Exercise among Adults Living with HIV: A Scoping Review
Bibliographic record
Abstract
Physical activity (PA) and exercise are an effective rehabilitation strategy to improve health outcomes among people living with HIV (PLWH). However, engagement in exercise among PLWH can vary. Our aim was to characterize the literature on the role of social determinants of health (SDOH) on engagement in PA or exercise among adults living with HIV. We conducted a scoping review using the Arksey and O’Malley Framework. We searched databases between 1996 and 2021. We included articles that examined PA or exercise among adults with HIV and addressed at least one SDOH from the Public Health Agency of Canada Framework. We extracted data from included articles onto a data extraction charting form, and collated results using content analytical techniques. Of the 11,060 citations, we included 41 articles, with 35 studies involving primary data collection 23 (66%) quantitative, 8 (23%) qualitative, and four (11%) mixed methods. Of the 14,835 participants, 6398 (43%) were women. Gender (n = 24 articles), social support (n = 15), and income and social status (n = 14) were the most commonly reported SDOH in the literature with the majority of studies addressing only one SDOH. Future research should consider the intersection between multiple SDOH to better understand their combined impact on engagement in PA or exercise among PLWH.
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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 | 0.013 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".