Building Resilience in Trauma Care at a Sub-Saharan African Tertiary Center: A Longitudinal Assessment of Multidisciplinary Trauma and Disaster Team Response Training Impact
Why this work is in the frame
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Bibliographic record
Abstract
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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it