Knowledge, Beliefs, and Attitudes of Emergency Nurses Toward People With Chronic Pain
Bibliographic record
Abstract
More and more people suffering from chronic pain (CP) utilize the emergency department (ED). However, their needs are not properly addressed. Stigmatization toward people with CP can partially explain this gap. Most studies in the ED have been focused on measuring nurses' pain management knowledge in general, not negative attitudes toward CP. Hence, understanding of the determinants of the stigma related to CP is needed. The objectives of this study were to (a) describe the knowledge, beliefs, and attitudes of ED nurses toward people suffering from CP and (b) identify nurses' characteristics associated with these perceptions. A cross-sectional web-based survey design was conducted using the KnowPain-12 questionnaire and the Chronic Pain Myth Scale. A total of 571 participants from 20 different states across the United States were recruited among whom 482 completed the entire survey. The sample included about one third of the ED nurses suffering from CP. Negative beliefs and attitudes toward people with CP were present in a considerable proportion of participants (up to 64%), even in nurses suffering from CP (up to 47.5%). Nevertheless, our results suggest that higher levels of education and suffering from CP were associated with better beliefs and attitudes toward people with CP. The ED presents an increased risk of stigmatization of people with CP as compared with the general population. Identifying determinants of the stigma associated with CP is crucial, as it will help tailoring awareness and educational campaigns. In addition, CP patients utilizing the ED often have complex needs which are difficult to address in this clinical environment. This situation can contribute to negative beliefs and attitudes. Given the scarcity of specialized care clinics for this population, health-care stakeholders should devise solutions to improve continuity of care in primary care settings and between the latter and ED.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".