Sex differences in schizophrenia, a review of the literature
Bibliographic record
Abstract
OBJECTIVE: To comprehensively and critically review the literature on gender differences in schizophrenia. METHOD: An initial search of MEDLINE abstracts (1966-1999) was conducted using the terms sex or gender and schizophrenia, followed by systematic search of all relevant articles. RESULTS: Males have consistently an earlier onset, poorer premorbid functioning and different premorbid behavioral predictors. Males show more negative symptoms and cognitive deficits, with greater structural brain and neurophysiological abnormalities. Females display more affective symptoms, auditory hallucinations and persecutory delusions with more rapid and greater responsivity to antipsychotics in the premenopausal period but increased side effects. Course of illness is more favorable in females in the short- and middle-term, with less smoking and substance abuse. Families of males are more critical, and expressed emotion has a greater negative impact on males. There are no clear sex differences in family history, obstetric complications, minor physical anomalies and neurological soft signs. CONCLUSION: This review supports the presence of significant differences between schizophrenic males and females arising from the interplay of sex hormones, neurodevelopmental and psychosocial sex differences.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".