Relation between Stress and Cognitive Impairment: A Study of a Sample of Healthcare Workers
Bibliographic record
Abstract
Background: Healthcare workers (HCWs) are susceptible to stress due to the exhausting nature of their work. This study aimed to assess the degree of work-related stress and its impact on cognitive impairment among HCWs.Methods: This cross-sectional survey-based study included 100 HCWS at Aswan University Hospital, Egypt. Perceived Stress Scale (PSS-10), the Arabic version of the Hamilton Anxiety Rating Scale (HAM-A), the Arabic version of the Hamilton Depression Rating Scale (HDRS), Mini-Mental State Examination (MMSE) and The Montreal Cognitive Assessment (MoCA) were used to assess stress, anxiety, depression, and cognitive functions respectively. Serum cortisol level was also detected.Results: Stress was mild in 2%, moderate in 86 %, and severe in 12 %. Hamilton anxiety rating scale was normal in 19 (19%), mild in 42 (42%), moderate in 34 (34%), and severe in 5 (5%) participants. Hamilton depression rating scale was normal in 26 (26%), mild in 39 (39%), moderate in 34 (34%), and severe in 1 (1%) participants. Mild cognitive impairment was the most prevalent condition. The correlations between stress parameters (PSS-10, HDRS, HARS, and cortisol level) and the cognitive function scales( MMSE and MoCA) were statistically significant.Conclusions: This study demonstrated the prevalence of mild to moderate stress, anxiety, depression, and cognitive impairment among HCWs. In addition, a strong correlation existed between stress and cognitive impairment among HCWs which makes them more liable for early cognitive impairment.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".