Influence of Future Prescribers’ Personal and Clinical Experiences With Opioids on Plans to Treat Patients With Opioid Use Disorder
Bibliographic record
Abstract
CONTEXT: Recreational use of opioids is a growing problem in the United States, particularly in the Midwest. Educators have called for inclusion of pain- and opioid-specific courses in health professional school curricula, yet more research is needed to address future prescribers' beliefs, experiences, and postgraduate plans related to opioids. OBJECTIVE: To examine health professional students' perceived severity of the opioid crisis and opioid-related beliefs, experiences, and postgraduate plans. METHODS: Using a descriptive, cross-sectional design, researchers evaluated health professional students from 3 academic programs (nurse practitioner [NP], physician assistant [PA], and doctor of osteopathic medicine [DO]) using a 25-item survey that assessed perceived opioid crisis severity and opioid-related beliefs, experiences, and postgraduate plans. Demographics of respondents were assessed using descriptive statistics and frequencies. Responses were compared between academic programs with 1-way analysis of variance or Kruskal-Wallis tests, and relationships between students' experiences and postgraduate plans were assessed. RESULTS: A total of 491 students (mean [SD] age, 27.2 [5.4] years; 62.7% female; 68.2% DO students) participated in the survey (response rate, 40.4%). The opioid crisis was perceived to be severely impacting the health care system (mean [SD] score, 79.7 [16.8] out of 100), and most respondents (415 [84.5%]) reported that opioid use affected their communities. Clinical experience varied by program, with NP students (75 [81.5%]) reporting the most experience treating acute overdose. Most respondents (317 [64.6%]) agreed that their postgraduate practice would involve caring for patients addicted to opioids; however, only 232 students (47.3%) felt confident in their ability to treat patients with addiction. Experiences managing acute overdose and handling drug-seeking behavior were positively associated with a belief that postgraduate work would involve working with patients with addiction (U=38,275.5, Z=5.92, P<.001; U=25,346.0, Z=4.94, P<.001) and confidence in treating patients with opioid addictions (U=36,806.5, Z=4.96, P<.001; U=23,765.5, Z=3.66, P<.001). CONCLUSION: Although health professional students had similar beliefs and perceptions regarding the opioid crisis, there were notable differences between academic programs. Students with clinical opioid experiences were more likely to plan on working with patients addicted to opioids and be confident in treating these patients. Thus, the inclusion of experiential learning in the medical curricula may be beneficial for both students and their future patients.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".