Development of a Web-Based Intervention for Middle Managers to Enhance Resilience at the Individual, Team, and Organizational Levels in Health Care Systems: Multiphase Study
Notice bibliographique
Résumé
BACKGROUND: Health care institutions face high systemic risk due to the inherent uncertainty and complexity of their operations. This often leads to stressful incidents impacting the well-being of health care professionals, which can compromise the effectiveness of health care systems. Enhancing resilience among health care professionals is essential for maintaining high-quality care and ensuring patient safety. The role of middle managers is essential to ensure the response capacity of individuals and teams. OBJECTIVE: This study aims to develop a web-based intervention aimed at middle management to enhance individual, team, and organizational resilience. METHODS: An observational study was conducted in 3 phases: design, validation, and pilot study. The study was initiated in February 2022 and concluded in June 2023. Phase 1 involved designing the content for the web-based tool based on a comprehensive review of critical elements around resilience. Phase 2 included validation by an international panel of experts who reviewed the tool and rated it according to a structured grid. They were also encouraged to highlight strengths and areas for improvement. Phase 3 involved piloting the tool with health care professionals in Ecuador to refine the platform and assess its effectiveness. A total of 458 people were invited to participate through the Institutional Course on Continuous Improvement in Health Care Quality and Safety offered by the Ministry of Public Health of Ecuador. RESULTS: The tool, eResiliencia, was structured into 2 main blocks: individual and team resilience and organizational resilience. It included videos, images, PDFs, and links to dynamic graphics and additional texts. Furthermore, 13 (65%) of the 20 experts validated the tool, rating content clarity at an average of 4.5 (SD 0.7) and utility at an average of 4.7 (SD 0.5) out of 5. The average overall satisfaction was 9.3 (SD 0.6) out of 10 points, and feedback on improvements was implemented. A total of 362 health care professionals began the intervention, of which 218 (60.2%) completed preintervention and postintervention questionnaires, with significant knowledge increases (P<.001). Of the 362 health care professionals, 146 (40.3%) completed the satisfaction questionnaire, where overall satisfaction was rated at an average of 9.4 (SD 1.1) out of 10 points. CONCLUSIONS: The eResiliencia web-based platform provides middle managers with resources to enhance resilience among their teams and their components, promoting better well-being and performance, even under highly stressful events. Future research should focus on long-term impacts and practical applications in diverse clinical settings.
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 | 0,012 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».