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Record W2092660927 · doi:10.1002/ajim.20382

Evaluation of a participatory ergonomic intervention aimed at improving musculoskeletal health

2006· article· en· W2092660927 on OpenAlexafffund
Irina Rivilis, Donald C. Cole, Mardon Frazer, Michael Kerr, Richard Wells, Selahadin Ibrahim

Bibliographic record

VenueAmerican Journal of Industrial Medicine · 2006
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsWestern UniversityInstitute for Work & HealthUniversity of WaterlooUniversity of Toronto
FundersWorkplace Safety and Insurance Board
KeywordsMedicinePsychological interventionPhysical therapyHuman factors and ergonomicsMusculoskeletal disorderOccupational safety and healthIntervention (counseling)Musculoskeletal injuryParticipatory ergonomicsWork (physics)Musculoskeletal painNursingPoison controlEnvironmental healthAlternative medicineEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: Participatory ergonomic (PE) interventions have been increasingly utilized to deal with work-related musculoskeletal disorders (WMSD). METHODS: Using a longitudinal quasi-experimental design, a PE process was launched at one depot of a large courier company, with a nearby depot serving as a control. Evaluations focused on 122 employees across the two depots who participated in both pre- and post-questionnaires. An evaluation framework assessed the process of implementation, changes in risk factors, and changes in musculoskeletal health outcomes. Partial and multiple regressions explored the relationships in the evaluation framework. RESULTS: Changes in work organizational factors had a consistent impact upon changes in health outcomes. Greater participation in the process was associated with increased levels of job influence and communication (P = 0.0059 and P = 0.0940 respectively). Improvements in communication levels were associated with reduced pain intensity and improved work role function (WRF) (P = 0.0077 and P = 0.0248 respectively). Lower levels of pain post-intervention were related to greater WRF (P = 0.0493). CONCLUSIONS: A PE approach can improve risk factors related to WMSD, and meaningful worker participation in the process is an important aspect for the success of such interventions.

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)0.009
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.055
GPT teacher head0.367
Teacher spread0.312 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations69
Published2006
Admission routes2
Has abstractyes

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