The essential role of physiotherapists in providing rehabilitation services to people living with HIV in South Africa
Bibliographic record
Abstract
Despite increased access to highly active anti-retroviral therapy (HAART) in South Africa, there remains a high risk of people living with HIV (PLHIV) developing a wide range of disabilities. Physiotherapists are trained to rehabilitate individuals with the disabilities related to HIV. Not only can South African physiotherapists play a significant role in improving the lives of PLHIV, but by responding proactively to the HIV epidemic they can reinforce the relevance and value of the profession in this country at a time when many newly qualified therapists are unable to secure employment. This paper offers recommendations that may help to fuel this response. These ideas include enhancing HIV curricula at a tertiary level, designing and attending continuing education courses on HIV and researching Southern African rehabilitation interventions for HIV at all levels of practice. furthermore, it is vital that physiotherapists are at the forefront of directing multi-disciplinary responses to the rehabilitation of PLHIV in order to influence stakeholders who are responsible for health policy formulation. it is hoped that this paper stimulates discussion and further ideas amongst physiotherapists and other health professionals in order to improve the quality and access to care available to PLHIV in South Africa.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".