Comorbidity of Anxiety and Depression with Substance Use Disorders
Bibliographic record
Abstract
The comorbidity of substance use disorders (SUDs) with anxiety and depression is the focus of substantial research attention and approached from myriad perspectives. This chapter focuses on the resultant complex research literature, first providing an overview of epidemiologic studies that have examined the prevalence of co-occurrence of SUDs (including alcohol and other drug use disorders) with anxiety and depressive disorders, as well as clinical correlates of these forms of comorbidity. Next, theoretical models of the onset and maintenance of emotional disorder–SUD comorbidity are considered, followed by a review of various types of studies evaluating these theoretical models (studies focusing on order-of-onset, the independent versus substance-induced disorder distinction, self-reported motives for use, genetic epidemiology, and experimental studies). Distinctions and commonalities between anxiety–SUD associations and depression–SUD associations are examined throughout. The chapter concludes by examining treatment implications of this comorbidity and suggests future directions for this burgeoning field.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".