The cognitive model of negative symptoms: a systematic review and meta-analysis of the dysfunctional belief systems associated with negative symptoms in schizophrenia spectrum disorders
Bibliographic record
Abstract
Abstract Background The hypothesized cognitive model of negative symptoms, proposed nearly twenty years ago, is the most prevalent psychological framework for conceptualizing negative symptoms in schizophrenia spectrum disorders (SSDs). The aim of this study was to comprehensively validate the model for the first time, specifically by quantifying the relationships between negative symptom severity and all related dysfunctional beliefs. Methods A systematic search was conducted using MEDLINE and PsychINFO, supplemented by manual reviews of reference lists and Google Scholar. Eligible studies were peer-reviewed with data on the direct cross-sectional association between negative symptoms and at least one relevant dysfunctional belief in SSD patients. Screening and data extraction were completed by independent reviewers. Random-effects meta-analyses were performed to pool effect size estimates of z -transformed Pearson’s r correlations. Moderators of these relationships, as well as subset analyses for negative symptom domains and measurement instruments, were also assessed. Results Significant effects emerged for the relationships between negative symptoms and defeatist performance beliefs (k = 38, n = 2808), r = 0.23 (95% CI, 0.18–0.27), asocial beliefs (k = 8, n = 578), r = 0.21 (95% CI, 0.12–0.28), low expectancies for success (k = 55, n = 5664), r = −0.21 (95% CI, −0.15 – −0.26), low expectancies for pleasure (k = 5, n = 249), r = −0.19 (95% CI, −0.06 – −0.31), and internalized stigma (k = 81, n = 9766), r = 0.17 (95% CI, 0.12–0.22), but not perception of limited resources (k = 10, n = 463), r = 0.08 (95% CI, −0.13 – 0.27). Conclusions This meta-analysis provides support for the cognitive model of negative symptoms. The identification of specific dysfunctional beliefs associated with negative symptoms is essential for the development of precision-based cognitive-behavioral interventions.
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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 | 0.018 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.023 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".