Patterns and Predictors of Treatment Seeking After Onset of a Substance Use Disorder
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: We studied survey respondents aged 18 through 54 years to determine consistent predictors of treatment seeking after onset of a DSM-III-R substance use disorder. METHODS: Survey populations included a regional sample in Ontario (n = 6261), a national sample in the United States (n = 5388), and local samples in Fresno, Calif (n = 2874) and Mexico City, Mexico (n = 1734). The analysis examined the effects of demographics, symptoms, and types of substances on treatment seeking. RESULTS: Between 50% (Ontario) and 85% (Fresno) of people with substance use disorders seek treatment but the time lag between onset and treatment seeking averages a decade or more. Consistent predictors of treatment seeking include: (1) late onset of disorder (odds ratio [OR], 3.8; 95% confidence interval [CI], 2.6-5.6 for late [> or =30 years] vs early [1-15 years] age at first symptom of disorder); (2) recency of cohort (OR, 3.4; 95% CI, 2.3-5.0 for most recent [aged 15-24 years at interview] vs earliest [aged > or =45 years] cohorts); (3) 4 specific dependence symptoms (using larger amounts than intended, unsuccessful attempts to cut down use, tolerance, and withdrawal symptoms), with ORs ranging between 1.6 (95% CI, 1.3-2.0) and 2.7 (95% CI, 2.1-3.6) for people with vs without these symptoms; and (4) use vs nonuse of cocaine (OR, 2.1; 95% CI, 1.6-2.7) and heroin (OR, 2.6; 95% CI, 1.1-6.0). CONCLUSIONS: Although most people with substance use disorders eventually seek treatment, treatment seeking often occurs a decade or more after the onset of symptoms of disorder. While treatment seeking has increased in recent years, it is not clear whether this is because of increased access, increased demand, increased societal pressures, or other factors.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it