Real-Time Postural Feedback to Optimize Ergonomics and Musculoskeletal Health in Ophthalmology Residents: A Canadian Pilot Quality Improvement Study
Notice bibliographique
Résumé
Background Musculoskeletal (MSK) pain is a common occupational concern in ophthalmology, often associated with the sustained and ergonomically demanding positions required during clinical and surgical activities. Tasks such as slit-lamp examinations, indirect ophthalmoscopy, and microscope-assisted procedures may contribute to postural strain. Despite this, ergonomics remains an underemphasized component of resident education, even though physical strain during training can influence long-term clinical performance and physician well-being. This pilot study investigates whether the UPRIGHT GO 2, a wearable posture trainer, can improve posture and reduce MSK pain in ophthalmology residents. Methodology This prospective, interventional, proof-of-concept case series recruited five postgraduate year (PGY) 2 to 5 ophthalmology residents at McMaster University. Each participant wore the UPRIGHT GO 2 device over the following four distinct two-week phases: baseline, training, short-term testing, and long-term testing. During the baseline phase, the vibration mode was turned off to establish baseline posture data. In the training phase, the vibration mode was activated with a 30-second delay to provide real-time posture feedback. The short-term testing phase was conducted with the vibration turned off to assess short-term retention effects. The long-term testing phase, also with vibration off, was performed six weeks after short-term testing to evaluate long-term effects. All participants attended a brief standardized educational session before device use, which reviewed ergonomic principles relevant to ophthalmology, including optimal posture during slit-lamp examinations, indirect ophthalmoscopy, and microscope-guided procedures. The primary outcome was the percent time spent in an upright posture. The secondary outcome was MSK pain, assessed using a modified Nordic musculoskeletal and numerical pain rating scale. Results All participants (N = 5, 100%) completed the baseline and training phases, with two residents (n = 2, 40%) completing the full study through long-term testing. The mean proportion of time spent in an upright posture increased from 68.9% at baseline to 78.5% during the training phase, coinciding with the activation of vibration-based feedback. This improvement declined to 66.8% during short-term testing and further to 52.4% at long-term follow-up (n = 2, 40%), suggesting a potential attenuation of effect in the absence of continued reinforcement. MSK pain scores followed a similar pattern: mean scores increased slightly from 6.6 to 7.4 post-baseline, then declined post-training (6.4), post-short-term testing (6.5), and reached their lowest average at long-term follow-up (3.5, n = 2, 40%). All participants demonstrated either stable or improved pain scores, with two residents exhibiting concordant improvements in both posture and pain. These findings suggest that wearable feedback devices may enhance ergonomics and mitigate MSK symptoms among ophthalmology residents when incorporated into clinical training environments. Conclusions The UPRIGHT GO 2, combined with an educational intervention, may provide short-term ergonomic benefit for posture and MSK pain in ophthalmology residents. However, long-term posture retention varied. Limitations include the small sample size and device data fidelity. Larger studies are needed to validate these findings and guide ergonomic strategies in medical training.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».