Measuring the Influence of Curricular Content and Personal Stories on Substance Use Stigma
Bibliographic record
Abstract
Background: Understanding of the lived experience is an important educational strategy for improving attitudes toward stigmatized patient groups. This study evaluated the influence of a personal story intervention on nursing students' attitudes toward people who use opioids and measured attitudinal change from students' regular mental health and addictions curriculum. Method: This study used a single-group longitudinal design. Stigma outcomes were measured using the Opening Minds Provider Attitudes Toward Opioid Use Scale. Mean scores were analyzed for four time periods: control, social contact intervention, curricular component, and 3-month follow-up. Qualitative feedback also was collected. Results: Stigma scores improved significantly from pre- to postsocial contact intervention. No differences were observed for curricular content, control period, or follow-up. Qualitative findings suggest the personal story was associated with positive student-reported attitudes. Conclusion: Integrating personal story interventions with traditional curriculum elements is a promising educational approach for improving perceptions and behaviors of nursing students toward people who use drugs. [ J Nurs Educ . 2022;61(5):264–267.]
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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 | 0.004 | 0.022 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".