Anxiety, mood disorders and injection risk behaviors among cocaine users: Results from the COSMO study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Despite being common among cocaine users, mental health problems and their relationship with HIV and hepatitis C high risk injection behaviors are poorly documented. This study was undertaken to examine the relationships between mood and anxiety disorders and the sharing of drug injection equipment among cocaine users who inject drugs. METHODS: The sample was drawn from a prospective cohort study and comprised of 387 participants. The outcome of interest was "sharing injection material" in the past 3 months. The presence of mood and anxiety disorders during the past year was assessed using the CIDI questionnaire. Statistical analyses were conducted on baseline data using logistic regression. RESULTS: Most participants were male (84.5%) and were aged 25 or over (92.2%); 43.0% qualified for an anxiety disorder diagnosis and 29.3% for a mood disorder diagnosis. Participants with anxiety disorders were more likely to share needles (Adjusted Odds Ratio [AOR]: 2.13, 95%CI: 1.15-3.96) and other injection material (AOR: 1.81, 95%CI: 1.12-2.92). No significant association was found between mood disorders and sharing behaviors. DISCUSSION AND CONCLUSIONS: Primary anxiety disorders but not mood disorders increases injection risk behaviors among cocaine users. These results bring to light another negative outcome of mental health comorbidity in this vulnerable population. SCIENTIFIC SIGNIFICANCE: This study underlines the need to fine-tune therapeutic approaches targeting specific mental health problems in individuals with cocaine use disorders. Longitudinal studies that assess impulsivity and other correlates of psychiatric disorders are needed to examine underlying mechanisms of high risk injection behaviors in comorbid populations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".