Sex Differences in Verbal Memory Predict Functioning Through Negative Symptoms in Early Psychosis
Bibliographic record
Abstract
Verbal memory (VM) is one of the most affected cognitive domains in first-episode psychosis (FEP) and is a robust predictor of functioning. Given that healthy females demonstrate superior VM relative to males and that female patients show less-severe illness courses than male patients, this study examined whether normative sex differences in VM extend to FEP and influence functioning. Four hundred and thirty-five patients (299 males, 136 females) with affective or nonaffective psychosis were recruited from a catchment-based specialized FEP intervention service and 138 nonclinical controls (96 males, 42 females) were recruited from the same community. One of the two neurocognitive batteries comprising six cognitive domains (VM, visual memory, working memory, attention, executive function, processing speed) were administered at baseline. In patients, positive and negative symptoms were evaluated at baseline and functioning was assessed at 1-year follow-up. Patients were more impaired than controls on all cognitive domains, but only VM showed sex differences (both patient and control males performed worse than females), and these results were consistent across batteries. In patients, better baseline VM in females was related to better functioning after 1 year, mediated through fewer baseline negative symptoms. Supplemental analyses revealed these results were not driven by affective psychosis nor by age and parental education. Thus, normative sex differences in VM are preserved in FEP and mediate functioning at 1-year follow-up via negative symptoms. This study highlights the importance of investigating sex effects for understanding VM deficits in early psychosis and suggests that sex may be a disease-modifying variable with important treatment implications.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".