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Record W2052764428 · doi:10.1097/jom.0b013e31829889c1

The Healthy LifeWorks Project

2013· article· en· W2052764428 on OpenAlexaffabout
Sandra Curwin, Jane Allt, Claudine Szpilfogel, Lydia Makrides

Bibliographic record

VenueJournal of Occupational and Environmental Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicinePhysical therapyMusculoskeletal disorderMusculoskeletal injuryHuman factors and ergonomicsOccupational safety and healthMusculoskeletal painMusculoskeletal diseasePoison controlEnvironmental healthAlternative medicineInternal medicinePathology

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this study was to determine the effect of a comprehensive workplace wellness program on the prevalence and severity of musculoskeletal disorders in a Canadian government department. METHODS: The Healthy LifeWorks program was developed, implemented, and evaluated over a 4-year period. A total of 233 employees completed the Nordic Musculoskeletal Questionnaire before and after the program to determine the prevalence and severity of musculoskeletal disorders. RESULTS: There was an approximately 10% decrease in the 12-month prevalence of musculoskeletal disorders, ranging from 4% for hip/thigh problems to 12% for lower and upper back problems. The proportion of people reporting that a musculoskeletal disorder interfered with their normal work during the past 12 months decreased from 83% to 46%. CONCLUSIONS: Comprehensive wellness, including educational sessions on posture, ergonomics, and joint health, results in improved musculoskeletal health.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.724
Threshold uncertainty score0.554

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.002

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 head0.018
GPT teacher head0.308
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations11
Published2013
Admission routes2
Has abstractyes

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