The Relationship between Working Night Shifts and Depression among Nurses: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: For many years, occupational physicians have debated whether there is a link between working the night shift and depression and other co-occurring mental health issues, with an emphasis on work-related, biological, individual, and environmental factors. We performed this systematic review and meta-analysis to estimate the overall association between sleep deprivation and depression among nurses working night shifts. Methods: A systematic search was carried out across the electronic databases PubMed, Scopus, and Web of Science from inception to 30 September 2022, for studies that reported a relationship between estimated night shift work and depression in nurses. The outcomes were measured using the odds ratio (OR) and matching 95% confidence interval (CI). The I2 statistic was used to assess heterogeneity. The Grading of Recommendations Assessment, Development and Evaluation technique was used to evaluate the quality of the evidence, and the Newcastle–Ottawa Scale was utilized to assess the methodological quality of each of the included studies. We determined the overall relationship between working nights and the onset of depression. Results: A total of 20 studies were included in the systematic review. Furthermore, 8 studies were included in the meta-analysis due to their common use of the OR as an effect measure. The 8 studies gave an overall estimate indicating a statistically significant association between night shift work and depression among nurses (OR = 1.49 95% CI: 1.26, 1.76). The prediction interval for the overall estimate was (0.995, 2.231). This implies that the true OR in a future study would most likely fall within this range, with a 95% certainty. Conclusions: The outcome of this systematic review and meta-analysis showed a significant association between night shift work, the circadian and sleep disruption it causes, and the risk of depression in nurses. This demonstrates that nurses who work night shifts are at risk of developing depression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".