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Record W2166980133 · doi:10.2340/16501977-0208

Linking health promotion with physiotherapy for low back pain: A review

2008· review· en· W2166980133 on OpenAlexaff
Kadija Perreault

Bibliographic record

VenueJournal of Rehabilitation Medicine · 2008
Typereview
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsHealth promotionPsychological interventionEmpowermentMedicinePromotion (chess)Physical therapyRehabilitationNursingPublic healthPolitical science

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.556
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.037
GPT teacher head0.405
Teacher spread0.367 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations27
Published2008
Admission routes1
Has abstractyes

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