Knowledge, Attitudes, and the Practice of Health Promotion among Physiotherapists in Nigeria
Bibliographic record
Abstract
Purpose: In spite of the growing epidemic of non-communicable diseases in Nigeria and the compelling need for the active participation of physiotherapists in health promotion activities around the world, there is no evidence that physiotherapists in Nigeria are engaged in health promotion activities. This study aimed to investigate the knowledge of, attitudes toward, and practice of health promotion among physiotherapists practising in Nigeria. Method: This was a cross-sectional study. We contacted members of the Nigeria Society of Physiotherapy ( n = 368) by email; the message contained a link to an online questionnaire. Results: A total of 229 (62%) physiotherapists responded. Most demonstrated a good knowledge of health promotion (approximately 70%) and indicated that they often incorporated aspects of health promotion into their patients’ treatment (63%). However, fewer than one-fifth strongly agreed that health promotion was taught in their entry-level programme and had equipped them with the necessary health promotion skills. Conclusions: The majority of the physiotherapists surveyed demonstrated good knowledge and often incorporated health promotion into their routine daily practice. Nevertheless, the respondents stated that their entry-level physiotherapy education had not sufficiently equipped them for health promotion practice. These findings provide a baseline reference that can be used to track capacity building for health promotion practices. The results also highlight important gaps in the physiotherapy entry-level curriculum and the health promotion training needs of physiotherapists in Nigeria.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".