Substance Use Disorder and Delusional Symptoms in Patients with Psychosis
Bibliographic record
Abstract
Background: Delusional thinking and low belief flexibility are important treatment targets in patients with psychotic disorders. Game-based interventions may improve hypothetical reasoning. As co-occurring substance use disorders (SUD) and psychotic disorders are common, the current study explores whether SUD may have an impact on the change of delusional beliefs in patients with psychosis. Methods: This study is a secondary analysis of a longitudinal, assessor blinded, randomised controlled trial, in which 172 patients with positive psychosis symptoms were randomised into an intervention targeting belief flexibility. An improvement over time was found in the Peters et al. Delusion Inventory sub-scales and the Brief Psychiatric Rating Scale outcomes in the treatment group. The current study explores whether co-occurring SUD may have an impact on this change. We used a one-way repeated measures analysis of variance (ANOVA) with SUD present (yes vs no) as the between-subject factor and time as the within-subject factor. As 29% of the patients were not investigated for SUD, we also performed a sensitivity analysis in which we examined the undiagnosed participants as a fully-fledged group, allowing the analysis of all 172 participants. Results: There was no significant effect of SUD. However, an overall significant time effect was observed for distress (F = 18.7, p <0.001), conviction (F = 19.8. p <0.001), preoccupation (F = 15.4, p <0.001) and BPRS (F = 6.3, p = 0.002). This means that all patients improved similarly on their reduction of all dimensions regardless of presenting an active SUD or not. The same analysis with a third group labelled “undiagnosed” almost replicated the above results. Conclusions: The presence of concomitant SUD at baseline does not seem to influence treatment outcomes over time concerning delusional beliefs. Therefore, specialised programs for psychotic disorders can be as effective for patients with concurrent SUD as for patients with psychosis only.
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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 | 0.000 | 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 | 0.001 |
| 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".