Negative symptoms in the clinical high‐risk state for psychosis: Connection with cognition and primacy in impacting functioning
Bibliographic record
Abstract
Aim In the clinical high‐risk (CHR) state for psychosis, both negative symptoms and lower cognitive function have been associated with poorer daily functioning. Recent evidence suggests that negative symptoms share overlapping variability with cognition and may partially mediate the relationship between cognition and functioning. However, the nature of this overlap is unknown, and the reverse mediation model remains untested leaving the precise nature of these associations unclear. Methods In order to clarify these relationships, a sample of community‐dwelling youth meeting CHR criteria was collected from a specialty CHR clinic (n = 91, mean age = 21, 63% male). Bootstrapping methods were then applied in a mediation analysis to test both negative symptoms and cognition as independent variables and mediating variables predicting social and role functioning in CHR individuals. Canonical correlation analysis was used to characterize the overlapping variability between negative symptoms and cognition. Results Support for a primary role of negative symptoms in predicting functioning and cognition was observed. Canonical correlation revealed a single dimension of overlap between the two symptom types ( r = .62), represented by a strong correlation between negative symptoms in general and tasks involving verbal working memory, vigilance and social cognition specifically. A single cognitive factor composed primarily of these tasks was found to predict role functioning (adjusted R 2 = .04). Conclusions The results highlight the importance of considering specific cognitive mechanisms overlapping with negative symptoms in research and rehabilitative practice in CHR populations, as well as the primary importance of targeting negative symptoms.
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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 | 0.001 | 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 | 0.000 |
| 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".