Association of Neurocognition With Transition to Psychosis
Bibliographic record
Abstract
IMPORTANCE: Neurocognition is a central characteristic of schizophrenia and other psychotic disorders. Identifying the pattern and severity of neurocognitive functioning during the "near-psychotic," clinical high-risk (CHR) state of psychosis is necessary to develop accurate risk factors for psychosis and more effective and potentially preventive treatments. OBJECTIVES: To identify core neurocognitive dysfunctions associated with the CHR phase, measure the ability of neurocognitive tests to predict transition to psychosis, and determine if neurocognitive deficits are robust or explained by potential confounders. DESIGN, SETTING, AND PARTICIPANTS: In this case-control study across 8 sites, baseline neurocognitive data were collected from January 2009 to April 2013 in the second phase of the North American Prodrome Longitudinal Study (NAPLS 2). The dates of analysis were August 2015 to August 2016. The setting was a consortium of 8 university-based, outpatient programs studying the psychosis prodrome in North America. Participants were 264 healthy controls (HCs) and 689 CHR individuals, aged 12 to 35 years. MAIN OUTCOMES AND MEASURES: Neurocognitive associations with transition to psychosis and effects of medication on neurocognition. Nineteen neuropsychological tests and 4 factors derived from factor analysis were used: executive and visuospatial abilities, verbal abilities, attention and working memory abilities, and declarative memory abilities. RESULTS: This study included 264 HCs (137 male and 127 female) and 689 CHR participants (398 male and 291 female). In the HCs, 145 (54.9%) were white and 119 (45.1%) were not, whereas 397 CHR participants (57.6%) were white and 291 (42.3%) were not. In the HCs, 45 (17%) were of Hispanic origin, whereas 127 CHR participants (18.4%) were of Hispanic origin. The CHR individuals were significantly impaired compared with HCs on attention and working memory abilities and declarative memory abilities. The CHR converters had large deficits in attention and working memory abilities and declarative memory abilities (Cohen d, approximately 0.80) compared with controls and performed significantly worse on these dimensions than nonconverters (Cohen d, 0.28 and 0.48, respectively). These results were not accounted for by general cognitive ability or medications. In Cox proportional hazards regression, time to conversion in those who transitioned to psychosis was significantly predicted by high verbal (premorbid) abilities (β = 0.40; hazard ratio [HR], 1.48; 95% CI, 1.08-2.04; P = .02), impaired declarative memory abilities (β = -0.87; HR, 0.42; 95% CI, 0.31-0.56; P < .001), age (β = -0.10; HR, 0.90; 95% CI, 0.84-0.97; P = .003), site, and a combined score of unusual thought content or delusional ideas and suspiciousness or persecutory ideas items (β = 0.44; HR, 1.56; 95% CI, 1.36-1.78; P < .001). CONCLUSIONS AND RELEVANCE: Neurocognitive impairment, especially in attention and working memory abilities and declarative memory abilities, is a robust characteristic of CHR participants, especially those who later develop psychosis. Interventions targeting the enhancement of neurocognitive functioning are warranted in this population.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".