Preparedness for Practice: Physiotherapists View on an Undergraduate Programme in KwaZulu-Natal, South Africa
Bibliographic record
Abstract
Background: Community service physiotherapists need to be fit for clinical practice while addressing the evolving socio-cultural and economic health care challenges that face South African health systems. The introduction of community service for health care professions over a decade ago influenced education at tertiary institutions. The rhetoric remains as to the preparedness of physiotherapists for service delivery in a demanding primary health care setting. Objectives: The study explored perceptions of preparedness of physiotherapists for clinical practice in their community service year. Method: A qualitative approach using semi-structured interviews were used to understand perceptions of preparedness for community service by professional physiotherapists. Results: Thirty nine physiotherapists who graduated at a University in Kwazulu-Natal, South Africa were recruited using snowball sampling. Data was analysed using conventional content analysis and yielded four dominant themes i.e. (1) facilitators of preparedness for community service, (2) inhibitors to perceived preparedness for community service, (3) curriculum review and (4) personal impact of community service. Conclusions: Although, physiotherapists believed that community service contributed to their confidence as professionals, graduates deemed that physiotherapy programmes need a curriculum that is geared toward specific South African needs such as primary health care. Physiotherapists also believed that the undergraduate curricula should address global health care needs to prepare the new generation of health care professionals for global significance.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".