Linking health promotion with physiotherapy for low back pain: A review
Bibliographic record
Abstract
OBJECTIVE: The objectives of this paper are: (i) to present the results of a descriptive literature review highlighting conceptual and practical links between the fields of physiotherapy and health promotion, and (ii) to provide recommendations based on this review of the literature in order to contribute towards the improvement of physiotherapists' interventions with people presenting low back pain. METHODS: A literature review of publications in the fields of health promotion, public health, physiotherapy and rehabilitation. The concepts of health and empowerment are discussed. Health promotion strategies used in the field of physiotherapy are also reported. RESULTS: The results of the literature review indicate that conceptualizations of health differ between the fields of health promotion and physiotherapy, although there are some common points. Empowerment, a central concept in health promotion, is probably not facilitated in physiotherapy interventions based on the biomedical model. Health education is the most used health promotion strategy in physiotherapy practice. Recommendations are put forward. CONCLUSION: In the future, further efforts should be made towards linking the principles and practices of health promotion with physiotherapy. This may help improve physiotherapists' interventions with people presenting low back pain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".