Knowledge and (Ab)Use in Connection with Novel Psychoactive Substances: A Cross-Sectional Analysis of Iraqi Medical Students
Bibliographic record
Abstract
BACKGROUND: The extent of (ab)use of the Novel Psychoactive substances has been thoroughly mapped in the developed world, particularly in the US, Canada, UK, Western Europe, Australia, and New Zealand. However, there are still untapped geographic locations particularly in the developing world including the Middle East.MATERIALS AND METHODS: This study is observational in nature and cross-sectional in design; it is based on a survey that will aim is to estimate the level of knowledge and the extent of (ab)use of psychoactive substances, traditional and novel, in a population of undergraduate medical students from Iraq. There will be an implementation of inferential statistical analyses for the purpose of hypothesis testing. Ethical approvals were granted from the College of Medicine at the University of Baghdad and the University of Hertfordshire.RESULTS: There was some degree of knowledge in connection with psychoactive substances among a population of medical students. However, the extent of (ab)use is still minimal when compared to that of the developed countries. In general, the knowledge and the extent of NPS (ab)use did not vary substantially as the students progressed through the medical college.CONCLUSION: The use of observational analytic tools for assessing the diffusion of the phenomenon of psychoactive and novel psychoactive substances is indispensable. The extent of knowledge and (ab)use of NPS in the Middle East may still be considered minute or insignificant. Further analyses are required in the Middle East; different populations are to be targeted including; students, academics, researchers, medical and paramedical staff, psychiatric patients, prisoners, military and para-military organisations, and even terrorists.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".