Building Resilience in Trauma Care at a Sub-Saharan African Tertiary Center: A Longitudinal Assessment of Multidisciplinary Trauma and Disaster Team Response Training Impact
Notice bibliographique
Résumé
Objective: To evaluate the long-term impact of the Trauma and Disaster Team Response (TDTR) course-supported by McGill University's Center for Global Surgery (CGS) and endorsed by the United Nations Institute for Training and Research's Surgical Hub-on Tanzanian clinicians' self-assessed confidence in trauma care skills taught in 2023. Background: Locally led, context-specific team training, such as the TDTR course, is essential in resource-limited settings to strengthen trauma care systems, prepare for unforeseeable natural or man-made disasters, and reduce preventable injury-related harm. In 2023, a 3-day, simulation-based, multidisciplinary TDTR course was conducted to equip Tanzanian clinicians with essential trauma management skills. Methods: This longitudinal cohort study tracked participants of the 2023 TDTR course. That year, in collaboration with the CGS, faculty from Tanzania's Muhimbili Orthopedic Institute trained 22 clinicians, including surgeons, residents, anesthetists, general physicians, and nurses. Participants completed self-assessments before and immediately after the course, evaluating their confidence in general skills (leadership, teamwork, and communication) and trauma-specific competencies. In 2025, the same questionnaires were emailed to all 22 trainees for a 2-year follow-up. Additionally, a separate questionnaire was sent to the 8 course instructors, inviting them to provide feedback on the course's long-term impact. Reminders were sent to nonresponders after 3 weeks. Instructor feedback was collected through structured surveys and open-ended questions, and was analyzed thematically to assess perceptions of participant progress, team dynamics, and areas for improvement. Changes in trainee confidence scores across the 3 time points (precourse, postcourse, and 2-year follow-up) were analyzed using mean comparisons and mixed-effects models. Results: < 0.05). Participants perceived a 4.5% reduction in trauma-related deaths, which was corroborated by supervising instructors, who also highlighted observed improvements in care quality, teamwork, and outcomes. While the perceived reduction in trauma-related mortality is notable, it is based on subjective assessment and cannot be solely attributed to the training without further controlled analysis. Furthermore, trainees and instructors emphasized the need for regular refresher sessions. Conclusions: The TDTR course was associated with sustained improvements in self-assessed trauma care confidence and perceived enhancements in clinical outcomes over 2 years. These findings underscore the value of ongoing, team-based training in resource-limited settings. However, regular refresher courses and future studies using objective performance measures are essential to confirm and quantify the long-term clinical impact.
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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 | 0,003 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 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 ».