Neurocognition, functional competence and self-reported functional impairment in psychometrically defined schizotypy
Bibliographic record
Abstract
INTRODUCTION: Schizotypy is phenologically and genetically related to schizophrenia-spectrum illness. Previous studies find cognitive function to be mildly impaired, but specific impairments and their relationship to functioning are not well understood. In this study, we sought to examine how cognitive load affects performance in schizotypy and to examine whether impairments might manifest in functional capacity and quality of life. METHODS: Undergraduate students were screened for abnormally high levels of schizotypy (N = 72) and compared to those without psychopathology (N = 80) on a standard battery of neuropsychological tests, cognitive tests with varying cognitive load, functional capacity measures and quality of life. RESULTS: The high schizotypy group did not differ from controls on traditional measures of neuropsychological functioning, but an interaction of group by cognitive load was observed, where those with schizotypy manifested a greater decline in performance as information processing load was parametrically increased. Differences in functioning were observed and cognitive impairment was associated with impaired functioning. CONCLUSIONS: Cognitive and functional impairment can be observed in those with high schizotypal traits who are non-treatment seeking. The sensitivity of cognitive tests to impairment in this population might be a function of their ability to parametrically increase cognitive load.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".