Do Sex/Gender and Menopause Influence the Psychopathology and Comorbidity Observed in Delusional Disorders?
Bibliographic record
Abstract
Background: While sex differences and gonadal hormone levels are taken seriously in the understanding and treatment of schizophrenia, their influence in the psychopathology of delusional disorders (DD) remains unknown. Methods: Our strategy was to conduct a narrative review of the effects of (a) sex/gender difference and (b) menopause on delusional content, affective and anxiety-related comorbidity, substance use disorders, cognition, aggressivity, and suicide risk in DD. Results: Because the literature is scarce, our results are tentative. We found that erotomania was more prevalent in women than in men, and especially in women with premenopausal onset. In contrast, jealous and somatic delusions were more commonly seen in DD women with postmenopausal onset. With respect to depressive comorbidity, women with premenopausal onset appear more vulnerable to depression than those with later onset. Age at menopause is reported to correlate positively with intensity of suicidal ideation. Anxiety symptoms may be related to estrogen levels. Men present with higher rates of substance use disorders, particularly alcohol use. Conclusions: Many male/female differences in DD may be attributable to sociocultural factors but menopause, and, therefore, levels of female hormones, influence symptom expression in women and mediate the expression of psychiatric comorbidities. Further research in this area promises to lead to improved individualized treatment.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".