Knowledge, attitudes, and practices of Cameroonian physicians with regards to pain management at the emergency department: a multicenter cross-sectional study
Bibliographic record
Abstract
Abstract Introduction: Pain is the most frequent presenting complaint in patients consulting or admitted to the emergency department (ED). Thus, its acute management is often done by physicians working in the ED. These practitioners are often general practitioners and not emergency medicine physicians in resource-poor settings. Hence, a mastery of pain management by these physicians may be important in relieving acute pain. We aimed to assess the knowledge, to determine the attitudes and practices of physicians in the management of pain in EDs of Cameroon. Methods: We carried out a prospective analytic cross-sectional study over four months in the year 2018. We enrolled all consenting physicians who were neither emergency medicine doctors nor anesthesiologists working at the EDs of five tertiary hospitals of Cameroon. Using a 30-item structured questionnaire, data on the knowledge, attitudes, and practices of pain management at the ED by these clinicians were studied. We used an externally validated score to assess the knowledge as either poor, insufficient, moderate or good. Results: A total of 58 physicians were included; 18 interns and 39 general practitioners. Their mean age was 28.6 ± 3 years and their average number of years of practice was 2.9 years. The level of knowledge was rated “poor” in 77.6% of physicians. Being a general practitioner was significantly associated with a poor level of knowledge (p=0.02; OR=5.1). We found a negative and significant correlation between knowledge and years of practice (p=0.04; r2= 0.06). More than three-quarter (82.8%) of participants used a pain scale to evaluate the severity of pain. The most used scale being the Visual Analog scale (56.9%). The most frequently used analgesic was paracetamol (98.3%), although only 3.5% of physicians correctly knew its half-life, delay of onset of action and duration of action. Conclusion: These findings suggest that physicians in EDs of Cameroon have poor knowledge and suboptimal practices in pain management. General practice and a greater number of professional experience seemed to favour these attitudes. Overall, there is an urgent need for refresher courses in acute pain management for physicians working in these resource-limited EDs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".