Sleep Deprivation and Academic Performance of Nursing Students in a Tertiary Institution in Cross River State, Nigeria
Bibliographic record
Abstract
This study investigated sleep deprivation and academic performance on nursing students of University of Calabar. A self-structured instrument was administered to a sample of 109 students. Data was analyzed using SPSS version 20.0. Most, 55(50.5. %) of the respondents start depriving themselves of sleep immediately after resumption. On school days, most 53 (48.6%) respondents sleep for 1–3 hours on average; while 40(36.7%) respondents sleep for 4–6 hours on average. During weekends most, 69(63.3%) respondents sleep for 4-6 hours on average, however, during examinations, majority 73(67. %), sleep for 1–3 hours on average. 64(58.6%) take different substances to keep awake. More male 69(63.3%) respondents start depriving themselves of sleep immediately after resumption, as against 50(46%) female respondents. Male students have an average sleep of 5.02 hours during schools days; 5.07 hours during weekends, and 2.39 hours during examinations, while female students have an average sleep of 5.25 hours during schools days, 5.43 hours during weekends, and 4.77 hours during examinations. Male students have a lower mean (SD) hours of sleep of (4.16±.35) compared to female students mean (SD) hours of (5.15±.49). The result further showed a statistically significant relationship between sleep deprivation and academic performance, also, a statistically significant influence of sleep deprivation on academic performance of male and female nursing students. Recommendations: nursing students should be properly counseled on the importance of adequate sleep to their academic performance. They should only deprive themselves of sleep during school days and less during examination.
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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 | 0.001 | 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".