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Record W1802952367 · doi:10.3233/wor-2008-00720

Evaluation of selected ergonomic assessment tools for use in providing job accommodation for people with inflammatory arthritis

2008· article· en· W1802952367 on OpenAlexaff
Judy Village, Catherine L. Backman, Diane Lacaille

Bibliographic record

VenueWork · 2008
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsArthritis Research Centre of CanadaUniversity of British Columbia
Fundersnot available
KeywordsAccommodationHuman factors and ergonomicsWork (physics)Risk assessmentRehabilitationPsychological interventionRisk analysis (engineering)Job analysisComputer scienceMedicinePoison controlPsychologyPhysical therapyEngineeringJob satisfactionMedical emergencyNursingComputer security

Abstract

fetched live from OpenAlex

Inflammatory arthritis (IA) is a leading cause of work disability, especially for those with jobs involving repetitive, hand-intensive or manual work. Ergonomic interventions may mediate against job loss. Our objective was to identify desirable features of an ergonomic tool for use in providing job accommodation for people with IA, and to evaluate a selection of ergonomic and rehabilitation tools against these features. Eight desirable features were compared across 16 assessment tools. None of the tools met all the pre-determined features. Ergonomic assessment tools should incorporate objective assessment of risk factors together with subjective perceptions of symptom aggravation, and identify risk factors that may not currently be causing problems, but may increase risk of aggravation or injury in the future. To accommodate the needs of people with IA, the tool should allow for evaluation of risks and generation of solutions without a worksite visit in situations where the client does not want to disclose their illness. Finally, an assessment tool needs to be applicable to a wide range of worksites, easy to use, valid, and reliable. Against these criteria, it appears that there is a lack of appropriate ergonomic assessment tools for use in people with IA.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.259

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.041
GPT teacher head0.310
Teacher spread0.269 · 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 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

Citations10
Published2008
Admission routes1
Has abstractyes

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