Sowing the seeds of doubt: a narrative review on metacognitive training in schizophrenia
Bibliographic record
Abstract
The present article provides a narrative review of empirical studies on metacognitive training in psychosis (MCT). MCT represents an amalgam of cognitive-behavioral therapy (CBT), cognitive remediation (CRT) and psychoeducation. The intervention is available in either a group (MCT) or an individualized (MCT+) format. By sowing the seeds of doubt in a playful and entertaining fashion, the program targets positive symptoms, particularly delusions. It aims to raise patients' awareness for common cognitive traps or biases (e.g., jumping to conclusions, overconfidence in errors, bias against disconfirmatory evidence) that are implicated in the formation and maintenance of psychosis. The majority of studies confirm that MCT meets its core aim, the reduction of delusions. Problems (e.g., potential allegiance effects) and knowledge gaps (i.e., outcome predictors) are highlighted. The preliminary data suggest that the individual MCT format is especially effective in addressing symptoms, cognitive biases and insight. We conclude that MCT appears to be a worthwhile complement to pharmacotherapy.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".