Profiles of Individuals with Cannabis-Related Disorders
Bibliographic record
Abstract
Background: Profiles of individuals with cannabis-related disorders (CRD) in specialized addiction treatment centers serving high-need patients have not been identified. This longitudinal study developed a typology for 9,836 individuals with CRD attending Quebec (Canada) addiction treatment centers in 2012–2013. Methods: Data on sociodemographic, clinical and service use variables were extracted from several databases for the years 1996–1997 to 2014–2015. Individual profiles were produced using Latent Class Analysis and compared predicting health outcomes on emergency department (ED) use, hospitalizations and suicidal behaviors for 2015–2016. Results: Six profiles were identified: 1-Older individuals, many living in couples and working, with moderate health problems, receiving intensive general practitioner (GP) care and high continuity of physician care; 2-Older individuals with chronic CRD, multiple social and health problems, and low health service use (chronic CRD referred to experiencing CRD for several years; social problems related to homelessness, unemployment, having criminal records or living alone); 3-Students with few social and health problems, and low health service use; 4-Young adults, many working, with few health problems, least health service use and continuity of physician care; 5-Youth, many working but some criminal offenders, with 1 or 2 years of CRD, few health problems and high addiction treatment center use; and 6-Older individuals with chronic CRD and multiple social and health problems, high health service use and continuity of physician care. Profiles 6 and 2 had the worst health outcomes. Conclusions: For Profiles 2 to 5, outreach and motivational services should be prioritized, integrated health and criminal justice services for profile 5 and, for Profiles 2 and 6, assertive community treatments. Screening, brief intervention and referrals to addiction treatment centers may also be encouraged for individuals with CRD, particularly those in Profile 2. This cohort had high social and health needs relative to services received, suggesting continued need for care.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".