Effects of metacognitive training (MCT) on social cognition for schizophrenia spectrum and related psychotic disorders: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Individuals with schizophrenia spectrum and related psychotic disorders (SSD) experience significant impairments in social cognition that impede functioning. Social cognition is a multidimensional construct consisting of four domains: 1. theory of mind, 2. emotion processing, 3. attributional style and 4. social perception. Metacognitive training (MCT) is an intervention designed to target cognitive biases in psychosis containing two modules addressing social cognition. Methods A systematic review and meta-analysis was conducted to investigate the effects of MCT on social cognition and two of its domains: theory of mind and emotion processing. Ten electronic databases were scoured from 2007 to 1 February 2022 for MCT studies reporting social cognition outcomes for people with SSD (1050 identified, 282 assessed). Effect sizes were calculated using Cohen's d in R. Results Nine studies were included in the meta-analysis ( n MCT = 212, n control = 194). MCT had a small but positive effect on global social cognition ( d = 0.28 [95% CI 0.07–0.49]) and theory of mind ( d = 0.27 [95% CI 0.01–0.52]). MCT showed no evidence of an effect on emotion processing ( d = 0.03 [95% CI –0.26 to 0.32]). Conclusion MCT has a small but significant effect on social cognition for people with SSD. Our results add to other recent meta-analyses showing significant effects of MCT on clinically relevant outcomes such as positive symptoms, cognitive biases and cognitive insight. We recommend that future studies on MCT report outcomes on all four domains of social cognition. Trial Registration PROSPERO (in the process of registration) available at https://www.crd.york.ac.uk/prospero/#recordDetails
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".