Impact of depression on cognitive function among women in a psychiatric hospital: Analysis via the Beck Scale Short Version and the Moroccan Version of the Montreal Cognitive Assessment (MoCA) test
Bibliographic record
Abstract
AIM: This study assessed the impact of depression on cognitive function in newly diagnosed women presenting to psychiatric emergency services through the cold track. METHODS: A cross-sectional study was conducted at Ar-Razi Psychiatric Hospital in Salé, Morocco, involving 86 women aged 18-58 years, newly diagnosed with depression. Depression severity was measured using the 13-item Beck Depression Inventory Short Version, and cognitive functions were assessed with the Moroccan version of the Montreal Cognitive Assessment (MoCA) test. Data analysis used SPSS v.26, employing correlation tests and one-way analysis of variance (ANOVA) to explore relationships and group differences. A confidence level of 95% and a significance threshold of 0.05 were applied. RESULTS: Among the participants, severe depression was prevalent, particularly among women aged 38-48 years. Depression scores were significantly higher in women with only primary education, while widowed women exhibited the highest overall scores. Students and unemployed participants were the most severely affected. A negative correlation was observed between depression symptoms and cognitive function, with higher depression levels associated with lower cognitive scores. Feelings of sadness and concentration deficits were negatively correlated, as were feelings of discouragement and executive functions. Positive correlations emerged between feelings of guilt and verbal fluency. CONCLUSION: This study underscores the relationship between depression and cognitive impairment in women, emphasizing the need for comprehensive evaluations of cognitive deficits in depressed patients. Tailored interventions should be prioritized to improve their quality of life.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".