Hot and cold executive functions in youth with psychotic symptoms
Bibliographic record
Abstract
BACKGROUND: Psychotic symptoms are common in children and adolescents and may be early manifestations of liability to severe mental illness (SMI), including schizophrenia. SMI and psychotic symptoms are associated with impairment in executive functions. However, previous studies have not differentiated between 'cold' and 'hot' executive functions. We hypothesized that the propensity for psychotic symptoms is specifically associated with impairment in 'hot' executive functions, such as decision-making in the context of uncertain rewards and losses. METHODS: In a cohort of 156 youth (mean age 12.5, range 7-24 years) enriched for familial risk of SMI, we measured cold and hot executive functions with the spatial working memory (SWM) task (total errors) and the Cambridge Gambling Task (decision-making), respectively. We assessed psychotic symptoms using the semi-structured Kiddie Schedule for Affective Disorders and Schizophrenia interview, Structured Interview for Prodromal Syndromes, Funny Feelings, and Schizophrenia Proneness Instrument - Child and Youth version. RESULTS: In total 69 (44.23%) youth reported psychotic symptoms on one or more assessments. Cold executive functioning, indexed with SWM errors, was not significantly related to psychotic symptoms [odds ratio (OR) 1.36, 95% confidence interval (CI) 0.85-2.17, p = 0.204). Poor hot executive functioning, indexed as decision-making score, was associated with psychotic symptoms after adjustment for age, sex and familial clustering (OR 2.37, 95% CI 1.25-4.50, p = 0.008). The association between worse hot executive functions and psychotic symptoms remained significant in sensitivity analyses controlling for general cognitive ability and cold executive functions. CONCLUSIONS: Impaired hot executive functions may be an indicator of risk and a target for pre-emptive early interventions in youth.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".