Awareness of musculoskeletal disorders hazards and controls in micro and small businesses in Ontario, Canada
Notice bibliographique
Résumé
OCCUPATIONAL APPLICATIONSPrior evidence indicates that the challenges faced by micro and small businesses to preventing musculoskeletal disorders (MSD) are due largely to a lack of awareness and recognition by business owners. Thus, the purpose of this study was to document the understanding and awareness of MSD hazard identification and controls among micro and small businesses, which was done using in-person surveys. Most of the small business owners and managers we surveyed lacked knowledge regarding appropriate controls for addressing MSD hazards. Traditional administrative controls and reactive approaches dominated workplace strategies, rather than engineering controls or preventative approaches. We argue that prevention strategies need to be communicated with user-friendly guidelines and tools that best suit the nature of micro and small businesses.TECHNICAL ABSTRACT Background: Small businesses do not typically have either the human or financial resources necessary to develop health and safety programs. The traditional cycle of identify, assess, control, and check is challenging for these businesses in terms of general workplace hazards, but is more problematic for musculoskeletal disorder (MSD) related hazards. Purpose: To determine the level of awareness of MSD prevention methods and explore prevention strategies and approaches used by micro and small businesses. Methods: A total of 146 micro and small businesses in the Kitchener-Waterloo area in Ontario, Canada participated in this study. Surveys of owners and managers were completed to assess their knowledge and awareness of MSD, hazard identification, and controls. Results: Over 40% of respondents did not know or were unsure how to identify physical demands in their workplace that might need reduction. Less than 10% of small business respondents suggested that using weights lifted, dimensions, or posture is important in MSD hazard identification. Most respondents (79%) believed they knew how to reduce injury risk; however, administrative controls dominated (57%) the workplace control strategies described, especially “proper lifting,” while engineering controls comprised only 18%. Most approaches to prevent MSD were reactive. There was a preference for traditional forms of information presentation on MSD prevention, such as posters or brochures. Conclusion: There is a lack of awareness among micro and small business regarding MSD hazards and control solutions. Our results suggest that education and support programs for micro and small businesses need to focus on awareness using simple and direct messages, and that prevention activities need to focus on easy, step-by-step guidelines tailored for such businesses.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».