Factors Influencing Patients’ Experiences of Pain Management in the Emergency Department
Bibliographic record
Abstract
Background Despite management of acute pain, concerns regarding pain are still prevalent in the emergency department (ED). Purpose This study aimed to explore the factors influencing patients’ pain management in a Jordanian ED. Method Fifteen semistructured interviews (N = 15) with purposively selected patients in the ED. Results The thematic analysis uncovered two related themes. The first theme described the stage of “being on ED bed” which encapsulates two subthemes: “bad pain means, bad diagnosis” and “smiley faces versus grumpy faces.” The second theme referred to as “being discharged” including two subthemes, namely, “praying for not paying” and “being grateful to God.” The lack of money to pay for pain management was equally as stressful as pain itself. Patients’ narratives suggest that nursing pain management is a critical time, extending beyond medical management to encompass communication and spirituality. Conclusions The factors influencing the patients’ experience of pain management extend beyond addressing the source of the pain. Consequently, effective communication coupled with respecting patients’ spirituality and socioeconomic concerns is essential to pain management. To enhance patients’ experience of pain management, the ED system should shift toward a patient-centric model.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".