A Study of Gender Differences in Cognitive Functions of Patients Suffering with Anxiety Disorders
Bibliographic record
Abstract
Background: Patients with anxiety disorders have been reported to have impairments in cognitive functioning; however, this area requires more consistent data. Furthermore, limited data are available concerning gender differences for the same. Hence, studying gender differences in cognitive functioning of patients suffering from anxiety disorders becomes paramount. The aim of this study is to measure the prevalence of cognitive impairment in patients suffering from anxiety disorders, to examine the gender differences in cognitive functioning, and to assess the association between the severity of anxiety and cognitive dysfunction across gender. Methodology: Following Institutional Ethics Committee approval, data were collected from 70 participants (aged 18–60 years) diagnosed with anxiety disorders. After obtaining informed consent, participants were assessed using a semi-structured pro forma, the Hamilton Anxiety Rating Scale, and the Montreal Cognitive Assessment. Results: Cognitive impairment was observed in 24.28% of the participants. The prevalence was higher in females (28.57%) than in males (20%), although this difference was not statistically significant ( P = 0.403). No significant association was found between anxiety severity and cognitive dysfunction overall ( P = 0.112), or when analyzed separately by gender (males: P = 0.644; females: P = 0.173). Conclusion: Although cognitive impairment was more prevalent among females with anxiety disorders, the relationship between anxiety severity andcognition was not statistically significant. Further research with larger samples is recommended.
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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 | 0.002 |
| 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".