ÉVALUATION DES FACTEURS DE RISQUE DE TROUBLES MUSCULO-SQUELETTIQUES : COMPARAISON DE MÉTHODES D'OBSERVATION ET PERCEPTION DES TRAVAILLEURS
Bibliographic record
Abstract
RESUME Les troubles musculo-squelettiques constituent un probleme de taille dans la majorite des pays industrialises. Selon les chiffres de l’Enquete sur les conditions de travail, d’emploi et de sante et de securite du travail, recemment publiee, un quebecois sur cinq (20,5%) souffrirait de troubles musculo-squelettiques (TMS) lies au travail. Les TMS comptent pour 38% des lesions indemnisees par la Commission de la Sante et de la securite du travail. L’intervention ergonomique visant la reduction de l’exposition aux facteurs de risque de TMS demeure la meilleure strategie de prevention et cette intervention est subordonnee a l’identification de ces facteurs de risque. La litterature recente en ergonomie propose une variete de methodes d’observations ayant ete developpees afin d’estimer l’exposition aux facteurs de risque de TMS. Elles ont pour objectif de supporter la prise en charge de la prevention des TMS en entreprise. Toutefois, cette litterature offre encore peu de recherches appliquees mettant a l’epreuve ces methodes sur le terrain pour comparer les resultats qu’elles produisent. Cette these realise une analyse comparative des resultats obtenus a partir de 11 methodes d’evaluation des facteurs de risque de TMS basees sur l’observation et etudie le lien entre la declaration de la douleur et la perception des travailleurs quant a l’evaluation de leur poste de travail. Les resultats de 21 indices tires des 11 methodes ont ete compares par groupes homogenes. Au total, 224 postes de travail ont ete evalues, dans 18 entreprises provenant de secteurs d’activite economique varies. Les donnees ont ete recueillies a partir de videos et de mesures prises aux postes. Un questionnaire fut egalement administre aux sujets ayant participe a l’etude, comportant des questions sur leurs caracteristiques personnelles generales, leur perception des facteurs de risque lies a l’ergonomie ainsi que sur les douleurs ressenties au cours des 12 derniers mois et des sept derniers jours precedant la collecte de donnees.----------ABSTRACT The prevalence of musculoskeletal disorders (MSDs) in workplaces is a major problem. According to the recently published Enquete sur les conditions de travail, d’emploi et de sante et de securite du travail, one in five Quebeckers (20,5%) suffer from MSDs. MSDs represent 38% of all injuries compensated by Quebec’s worker compensation board. Given the significant impacts of MSDs, industries need to work on prevention. The scientific literature shows that intervention to reduce exposure to MSD risk factors is the best prevention strategy. Recent literature in ergonomics offers a variety of observation methods for MSDs risk factors assessment. Some were developed with the intention of supporting industry-led MSDs prevention efforts and provide important guidelines for the implementation of occupational health and safety strategies. Yet, the existing literature showcases little applied research that tests these methods in the field to compare the results they produce. This doctoral thesis performs a comparative analysis of results obtained from 11 methods of MSDs risk factors assessment based on observation, and studies the relationship between the declaration of pain and perceptions of workers regarding the assessment of their workstations. The results of 21 indices from the 11 observation-based methods are compared in homogeneous groups. In total, 224 workstations were evaluated, involving 567 different tasks in 18 firms from various sectors of the economy. Data were gathered using video and measurements taken at the workstations. A questionnaire on the musculoskeletal pain experienced in various body regions, during the 12 months and seven days prior to the data collection, was also administered to employees participating in the study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".