Effects of Sleep Deprivation on the Cognitive Performance of Nurses Working in Shift
Bibliographic record
Abstract
INTRODUCTION: Sleep deprivation and altered circadian rhythm affects the cognitive performance of an individual. Quality of sleep is compromised in those who are frequently involved in extended working hours and shift work which is found to be more common among nurses. Cognitive impairment leads to fatigability, decline in attention and efficiency in their workplace which puts their health and patients' health at risk. AIM: To find out the prevalence of sleep deprivation and its impact on cognition among shift working nurses. MATERIALS AND METHODS: Sleep deprivation among 97 female and three male healthy nurses of age 20-50 years was assessed by Epworth sleepiness scale (ESS). Cognition was assessed by Montreal Cognitive Assessment (MoCA) questionnaire. Mobile applications were used to test their vigilance, reaction time, photographic memory and numerical cognition. The above said parameters were assessed during end of day shift and 3-4 days after start of night shift. RESULTS: Poor sleep quality was observed among 69% of shift working nurses according to ESS scores. The cognitive performance was analysed using Wilcoxon signed rank test. The MoCA score was found to be lesser among 66% of nurses during night (25.72) than day (26.81). During the night, 32% made more mathematical errors. It was also found that, 71%, 83% and 68% of the nurses scored lesser during night in the Stroop's colour test, vigilance test and memory tests respectively. Thus, impairment in cognitive performance was statistically significant (p<0.001) among shift working nurses. CONCLUSION: Cognitive performance was found to be impaired among shift working nurses, due to poor sleep quality and decreased alertness during wake state. Thus, shift work poses significant cognitive risks in work performance of nurses.
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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 | 0.000 | 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) | 0.001 | 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".