Substance use disorders and suicidality in youth: A systematic review and meta-analysis with a focus on the direction of the association
Bibliographic record
Abstract
BACKGROUND: Reviews and meta-analyses suggest that substance use and suicidality (i.e., suicidal ideations and attempts) are associated in youth, but the direction of this association remains unclear. Theoretically, the secondary psychiatric disorder hypothesis (SPDH) posits that substance use leads to suicidality, while the secondary substance use disorder hypothesis (SSUDH) posits that suicidality leads to substance use. To clarify these associations, this meta-analysis systematically reviewed studies that examined the prospective associations between SUDs and suicidality in youth (age 25 and younger) and compared results according to the direction of the association. METHODS: Web of Science, Embase, PsycINFO, PubMed, Medline and ProQuest Dissertations & Theses Global were searched from inception to March 8, 2020, and 55 effect sizes from 23 samples were included and analyzed using a three-level meta-analysis. RESULTS: SUDs significantly predicted subsequent suicidality (OR = 2.16, 95%CI 1.57-2.97), suicidality significantly predicted subsequent SUDs (OR = 2.16, 95%CI 1.53-3.04), and these effect sizes did not differ (p = 0.49). CONCLUSIONS: Considering that 65% of reviewed studies only examined the SPDH, this review highlights that more attention should be given to the SSUDH, and that studies should examine bidirectional associations between SUDs and suicidality across time. Clinically, because SUDs and suicidality were found to influence each other, results suggest that mental health and SUDs should ideally be detected and treated early, and that co-occurring disorders should be assessed and treated concomitantly.
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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 | 0.013 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.031 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".