Evaluating the effectiveness of the Emergency Neurological Life Support educational framework in low-income countries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: The Emergency Neurological Life Support (ENLS) is an educational initiative designed to improve the acute management of neurological injuries. However, the applicability of the course in low-income countries in unknown. We evaluated the impact of the course on knowledge, decision-making skills and preparedness to manage neurological emergencies in a resource-limited country. Methods: A prospective cohort study design was implemented for the first ENLS course held in Asia. Knowledge and decision-making skills for neurological emergencies were assessed at baseline, post-course and at 6 months following course completion. To determine perceived knowledge and preparedness, data were collected using surveys administered immediately post-course and 6 months later. Results: A total of 34 acute care physicians from across Nepal attended the course. Knowledge and decision-making skills significantly improved following the course (p=0.0008). Knowledge and decision-making skills remained significantly improved after 6 months, compared with before the course (p=0.02), with no significant loss of skills immediately following the course to the 6-month follow-up (p=0.16). At 6 months, the willingness to participate in continuing medical education activities remained evident, with 77% (10/13) of participants reporting a change in their clinical practice and decision-making, with the repeated use of ENLS protocols as the main driver of change. Conclusions: Using the ENLS framework, neurocritical care education can be delivered in low-income countries to improve knowledge uptake, with evidence of knowledge retention up to 6 months.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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