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Record W2098071036 · doi:10.2340/16501977-0204

Stretching to reduce work-related musculoskeletal disorders: A systematic review

2008· review· en· W2098071036 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Rehabilitation Medicine · 2008
Typereview
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychological interventionMedicinePhysical therapyWork-related musculoskeletal disordersMusculoskeletal disorderPopulationPhysical medicine and rehabilitationMEDLINEMusculoskeletal painHuman factors and ergonomicsPoison controlPsychiatryEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVE: This article reviewed the literature to clarify the physiological effects and benefits of, and misconceptions about, stretches used to reduce musculoskeletal disorders. METHODS: Nine databases were reviewed to identify studies exploring the effectiveness of stretching to prevent work-related musculoskeletal disorders. Included studies were reviewed and their methodological quality was assessed using the PEDro scale. RESULTS: The physiological effects of stretches may contribute to reducing discomfort and pain. However, if other measures are not in place to remediate their causes, stretches may suppress awareness of risks, resulting in more debilitating injuries. If inadequately performed, stretches may also cause or aggravate injuries. Careful analysis and stretching program design are required before implementing stretches. Seven studies evaluating the effectiveness of stretching to prevent musculoskeletal disorders in different occupations were identified and reviewed. CONCLUSION: The studies provided mixed findings, but demonstrated some beneficial effect of stretching in preventing work-related musculoskeletal disorders. However, due to the relatively low methodological quality of the studies available in the literature, future studies are necessary for a definite response. Future studies should minimize threats to internal and external validity, have control groups, use appropriate follow-up periods, and present a more detailed description of the interventions and worker population.

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.

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)0.003
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.268
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.002
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 head0.017
GPT teacher head0.379
Teacher spread0.362 · 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