Revisiting Gender Differences in Somatic Symptoms of Depression: Much Ado about Nothing?
Bibliographic record
Abstract
BACKGROUND: Women have a higher prevalence of Major Depressive Disorder (MDD) and report more severe depressive symptoms than men. Several studies have suggested that gender differences in depression may occur because women report higher levels of somatic symptoms than men. Those studies, however, have not controlled or matched for non-somatic symptoms. The objective of this study was to examine if women report relatively more somatic symptoms than men matched on cognitive/affective symptoms. METHODS: Male and female patients receiving treatment for MDD in outpatient psychiatric clinics in New Jersey and Pennsylvania, USA were matched on Beck Depression Inventory-II (BDI-II) cognitive/affective symptom scores. Male and female BDI-II somatic symptom scores were compared using independent samples 2-tailed t-tests. RESULTS: Of 472 male and 1,026 female patients, there were 470 male patients (mean age = 40.1 years, SD = 15.1) and 470 female patients (mean age = 43.1 years, SD = 17.2) successfully matched on BDI-II cognitive/affective symptom scores. Somatic symptoms accounted for 35% of total BDI-II scores for male patients versus 38% for matched female patients. Female patients had somatic symptom scores on average 1.3 points higher than males (p<.001), equivalent to 4% of the total BDI-II scores of female patients. Only 5% of male patients and 7% of female patients scored 2 or higher on all BDI-II somatic symptom items. CONCLUSIONS: Gender differences in somatic scores were very small. Thus, differences in the experience and reporting of somatic symptoms would not likely explain gender differences in depression rates and symptom severity.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".