Meta-analytic prevalence of comorbid mental disorders in individuals at clinical high risk of psychosis: the case for transdiagnostic assessment
Bibliographic record
Abstract
Abstract Comorbid mental disorders in subjects at clinical high risk for psychosis (CHR-P) may impact preventive care. We conducted a PRISMA/MOOSE-compliant systematic meta-analysis, searching PubMed/PsycInfo up to June 21st, 2021 for observational studies/randomized controlled trials reporting on comorbid DSM/ICD-mental disorders in CHR-P subjects ( protocol ). The primary and secondary outcomes were baseline and follow-up prevalence of comorbid mental disorders. We also explored the association of comorbid mental disorders compared with CHR-P versus psychotic/non-psychotic control groups, their impact on baseline functioning and transition to psychosis. We conducted random-effects meta-analyses, meta-regression, and assessed heterogeneity/publication bias/quality (Newcastle Ottawa Scale, NOS). We included 312 studies (largest meta-analyzed sample = 7834, any anxiety disorder, mean age = 19.98 (3.40), females = 43.88%, overall NOS > 6 in 77.6% of studies). The prevalence was 0.78 (95% CI = 0.73–0.82, k = 29) for any comorbid non-psychotic mental disorder, 0.60 (95% CI = 0.36–0.84, k = 3) for anxiety/mood disorders, 0.44 (95% CI = 0.39–0.49, k = 48) for any mood disorders, 0.38 (95% CI = 0.33–0.42, k = 50) for any depressive disorder/episode, 0.34 (95% CI = 0.30–0.38, k = 69) for any anxiety disorder, 0.30 (95% CI 0.25–0.35, k = 35) for major depressive disorders, 0.29 (95% CI, 0.08–0.51, k = 3) for any trauma-related disorder, 0.23 (95% CI = 0.17–0.28, k = 24) for any personality disorder, and <0.23 in other mental disorders (I 2 > 50% in 71.01% estimates). The prevalence of any comorbid mental disorder decreased over time (0.51, 95% CI = 0.25–0.77 over 96 months), except any substance use which increased (0.19, 95% CI = 0.00–0.39, k = 2, >96 months). Compared with controls, the CHR-P status was associated with a higher prevalence of anxiety, schizotypal personality, panic, and alcohol use disorders (OR from 2.90 to 1.54 versus without psychosis), a higher prevalence of anxiety/mood disorders (OR = 9.30 to 2.02) and lower prevalence of any substance use disorder (OR = 0.41, versus psychosis). Higher baseline prevalence of alcohol use disorder/schizotypal personality disorder was negatively associated with baseline functioning (beta from −0.40 to −0.15), while dysthymic disorder/generalized anxiety disorder with higher functioning (beta 0.59 to 1.49). Higher baseline prevalence of any mood disorder/generalized anxiety disorder/agoraphobia (beta from −2.39 to −0.27) was negatively associated with transition to psychosis. In conclusion, over three-quarters of CHR-P subjects have comorbid mental disorders, which modulate baseline functionig and transition to psychosis. Transdiagnostic mental health assessment should be warranted in subjects at CHR-P.
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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 | 0.074 | 0.157 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.062 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".