The association of medical cannabis use with quality of life in Illinois’ opioid alternative pilot program
Bibliographic record
Abstract
BACKGROUND: In Illinois, the Opioid Alternative Pilot Program (OAPP) was launched to expand access to medical cannabis to use as a direct substitute for opioids. Although therapeutic benefits have been reported in reducing opioid use, there is an absence of literature that examines how medical cannabis use impacts an individual's quality of life (QoL). This study examines the association of medical cannabis use with QoL among the first enrollees in OAPP. METHODS: A survey was sent to enrollees between February and July 2019. Cannabis users (n=626) were compared to non-users (n=234) to determine whether there was an association between cannabis use within the past year and QoL. Ordered logistic regression and backwards stepwise regression modelling was used. RESULTS: Across the study sample of 860 participants, the average age was 47 years; 60 % of the cohort was male; 72 % were not of Hispanic, Latino, or Spanish origin; 67 % were married. Across the entire study sample, the average perceived QoL was 2.86 (between 'Good' and 'Fair'), with no statistically significant difference in QoL between the two groups (non-users: 2.85; cannabis users: 2.86; p=0.92). Logistic regression reported cannabis use within the past year did not have a statistically significant association with QoL (OR=1.33, 95% confidence interval, 0.85 to 2.08, p=0.21). DISCUSSION: Overall, there was no significant association between cannabis use within the past year and QoL. This may be attributed to pain being a qualifying condition to enter the program.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".