HIV and Rehabilitation Training Needs of Health Professionals in Canada: Results of a National Survey
Bibliographic record
Abstract
Background: People with HIV experience a range of health-related challenges that rehabilitation services are well-positioned to address. The purpose of this study was to explore professional knowledge and views about HIV rehabilitation among HIV specialists and rehabilitation professionals in Canada.Methods and Findings: We conducted a nationwide cross-sectional postal survey with a random sample of rehabilitation professionals (physical therapists, occupational therapists, speech-language pathologists, and physiatrists) (N = 1058) and the known population of HIV specialists (physicians, nurses, social workers, pharmacists, psychologists, and dietitians) in Canada (N = 214). Two-thirds (67%) of rehabilitation professionals disagreed that rehabilitation professionals possess adequate knowledge and skills to assess and treat people living with HIV. The majority of all respondent groups felt that rehabilitation professionals who work with people living with HIV require specialized HIV training. Approximately one-third (32%) of rehabilitation professionals who had served people living with HIV stated they received some HIV training as part of their professional degree.Conclusions: This was the first national survey to explore HIV specialist and rehabilitation professionals’ knowledge and views about HIV rehabilitation. Findings indicate the need for interprofessional education, training, and mentorship of health professionals to address the gap between the needs of people living with HIV and rehabilitation services provision.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".