A Longitudinal Investigation of the Role of Self-Medication in the Development of Comorbid Mood and Drug Use Disorders
Bibliographic record
Abstract
OBJECTIVE: To examine whether self-medication with drugs confers risk of comorbid mood and drug use disorders. METHOD: A longitudinal, nationally representative survey was conducted by the National Institute on Alcohol Abuse and Alcoholism. The National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) assessed DSM-IV-TR psychiatric disorders, self-medication, and sociodemographic variables at 2 time points. A total of 34,653 adult, US participants completed both waves of the survey. Wave 1 was conducted between 2001 and 2002, and Wave 2 interviews took place 3 years later (2004-2005). Logistic regression and population attributable fractions were calculated to obtain estimates of the association between self-medication and incident disorders. RESULTS: Logistic regression analyses revealed that self-medication with drugs conferred a heightened risk of new-onset drug dependence among those with baseline mood disorders (adjusted odds ratio [AOR] = 7.65; 95% CI, 3.70-15.82; P < .001) and accounted for over 25% of incident drug dependence disorders among people with mood disorders. Among those with comorbid mood and drug use disorders at baseline, self-medication with drugs was associated with the persistence of drug abuse (AOR = 2.47; 95% CI, 1.34-4.56; P < .01), accounting for over one-fifth of the persistence of drug use disorders at 3-year follow-up. CONCLUSIONS: Self-medication with drugs among individuals with mood disorders confers substantial risk of developing incident drug dependence and is associated with the persistence of comorbid mood and drug use disorders. These results clarify a pathway that may lead to the development of mood and drug use disorder comorbidity and indicate an at-risk population, with potential points of intervention for prevention of comorbidity.
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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 | 0.003 | 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 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".