Drug dependence epidemiology in palliative care medicinal cannabis trials
Bibliographic record
Abstract
OBJECTIVES: Drug dependence is becoming increasingly common and meeting palliative care patients with substance use disorders is inevitable. However, data on substance use in these patients are lacking. This study aims to evaluate the prevalence of drug dependence in palliative care patients with advanced cancer and correlate with symptom distress and opioid use. METHODS: Palliative care patients with advanced cancer interested in participation in a medicinal cannabis trial were required to complete Alcohol, Smoking and Substance Involvement Screening Test (ASSIST), Edmonton Symptom Assessment Scale (ESAS) and record of concomitant medications including baseline opioid use as part of the eligibility screen. RESULTS: Of the 182 participants, 167 (92%) reported lifetime alcohol and 132/182 (73%) lifetime tobacco use. No participant reached the threshold criteria for high risk of drug dependence with majority being low risk. There was no correlation between ASSIST score, ESAS and oral morphine equivalent. CONCLUSION: This study identified alcohol and tobacco as the main substances used in this group of patients and that most were of very low risk for drug dependence. This suggests routine drug screening for palliative care patient may not be justified, but the high possibility of questionnaire bias is acknowledged.
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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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.005 | 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".