The Influence of Addiction Risk on Nursing Students’ Expectations of Patients’ Pain Reports: A Clinical Vignette Approach
Bibliographic record
Abstract
OBJECTIVE: To examine the influence of addiction risk (substance abuse history [SAH]) and pain relief (PR) on nursing and non-nursing students' perceptions of pain in a postoperative vignette patient. METHODS: Using a 2 x 2 design, the independent variables SAH (present/+, absent/-) and PR (adequate, little) were varied systematically to produce four vignettes. Participants were randomly assigned to receive one of the four vignettes that described a 45-year-old man after a total hip replacement. Participants rated the vignette patient's experienced and reported pain intensity (PI) on a 0 mm to 100 mm visual analogue scale and addiction risk on a 0 mm to 100 mm visual analogue scale. A pain congruence (PC) score was calculated (PC = reported PI -- experienced PI), and was interpreted as congruent (+/-2 mm) or incongruent (+2 mm to +100 mm for expected pain over-reporting; -2 mm to -100 mm for expected pain under-reporting). RESULTS: Responses from undergraduate nursing (n=89) and non-nursing (n=88) students were analyzed. The estimated addiction risk was significantly lower in nursing (14% to 45%) versus non-nursing students (50%). Nursing students' mean PC scores were not significantly altered by SAH alone. Expectations of pain over-reporting were observed under conditions of SAH+/adequate PR, but not SAH+/little PR. In non-nursing students, SAH and PR were significant and independent factors influencing mean PC scores in the direction of pain over-reporting. CONCLUSION: Under most conditions, nursing students expected pain under-reporting by the postoperative vignette patient. However, nursing students did expect pain to be over-reported when addiction risk was high and PR was adequate. These data suggest that nursing students' expectations regarding pain over- and under-reporting were sensitive to perceptions of addiction risk, but involved additional factors (eg, level of PR).
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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 | 0.013 | 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 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".