Serious Games for Preventing Musculoskeletal Disorders in Occupational Settings: Scoping Review
Notice bibliographique
Résumé
BACKGROUND: Musculoskeletal disorders (MSDs) are a significant health concern in the workplace, and while ergonomic interventions are commonly used, their long-term effectiveness is often questioned. Serious games (SGs), designed to go beyond entertainment, have emerged as a promising tool that may address some of the limitations of traditional interventions, such as the need for sustained impact and greater worker engagement. OBJECTIVE: This review aims to identify and analyze the key characteristics of SGs-including design, gameplay, and expected outcomes-that have been developed for the prevention or mitigation of work-related MSDs. Additionally, it explores the documented effects of SG implementation, assessing their potential contribution to MSD prevention and intervention strategies. METHODS: A scoping review was conducted across 6 scientific databases (APA PsycInfo, Web of Science, Science Direct, MEDLINE, IEEE Xplore, and Google Scholar) to identify relevant studies published up to 2025. The selection process involved a multistep screening, including title and abstract review, followed by full-text assessment by 2 independent reviewers. Studies included were original research articles in English addressing MSD prevention and mitigation. Exclusions applied to studies on nonwork-related MSDs, limited content, duplicates, or repurposed entertainment games or gamification solutions. Data extraction was performed using a standardized form to capture key study characteristics. A 2-level analysis was applied: descriptive analysis, categorizing studies based on study characteristics and primary focus (design, evaluation, or both), and content-based analysis, examining game design, gameplay, expected outcomes, and evaluation methods to provide a structured synthesis of findings. RESULTS: The initial search identified 2700 records, with 15 studies meeting the inclusion criteria. These studies explored diverse applications of SGs for MSD prevention, focusing either on game design and development or on educational impact assessment. Notably, only 2 studies comprehensively addressed both design methodology and educational evaluation. Findings revealed considerable variability in design approaches, technological platforms, gameplay mechanics, and expected outcomes. Additionally, the literature exhibited significant inconsistencies in evaluating SG effectiveness, with methodological limitations affecting comparability. While some studies targeted rehabilitation or occupational health and safety, only a few explicitly focused on MSD prevention, with a predominant emphasis on physical risk factors, whereas psychosocial and organizational aspects remained largely underexplored. CONCLUSIONS: This review highlights the need for standardized protocols and criteria for the design and evaluation of SGs to enable further synthesis and impact measurement. The integration of MSD prevention into SGs remains limited and is often approached indirectly through related themes such as workplace safety or rehabilitation. Future research should focus on developing and validating more comprehensive SG-based interventions and exploring their potential as effective tools in occupational health. The findings indicate a substantial gap in empirical evidence regarding the effectiveness of SGs for MSD prevention, largely due to the disparity in experimental approaches.
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Comment cette classification a été obtenuedéplier
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,001 | 0,001 |
| 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 ».