First Year Student Pharmacists’ Views on the Opioid Epidemic
Bibliographic record
Abstract
Objective To determine first-year student pharmacists’ views on the opioid epidemic. Methods First-year pharmacy students were asked to complete an online survey to assess their views and opinions on the current opioid crisis using Likert-scale type questions. Results Forty-four pharmacy students were surveyed, and all participants completed survey questions, 100% response rate. Majority of participants were female (N=34, 77.3%), with more than half of participants falling in the age range of 18-24 (N=25, 56.8%). Geographically, most of the participants home residences are in other states out of the DC, Maryland, Virginia (N=25, 56.9%). In addition, majority of participants worked before starting pharmacy school (N=42, 95.5%) and a majority had a pharmacy and healthrelated occupations before pharmacy school (N=36; 81.9%). Most study participants reported an annual income of less than $10,000 (N=17, 38.6%) and obtained a bachelor’s degree (N=26, 59.1%). Majority of participants strongly agree that the opioid epidemic is becoming a severe crisis for society (N=42; 95.5%) and that opioid should be readily available when it is medically necessary to people (N=27; 61.4%). When asked if they know anyone personally who suffers from the opioid crisis, over three-quarter (N=34; 77.3%) said no. However, over two-third (N=29; 65.9%) of participants said that they have taken opioids in the past themselves to relieve pain. Although, almost all of them strongly agree that prescription opioids are addictive (N=42; 95.5.%); about eighty percent (N=35; 79.5%) agree that taking opioids is an effective way to alleviate severe pain. Conclusion Our results indicate that pharmacy students perceive the opioid epidemic as a crisis and despite their views that opioids are addictive and knowing someone who suffers from opioid use disorder, they believe opioids are a clinically effective way to alleviate pain.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".