Non-standard work hours, accidents and injuries among seafarers. A systematic Review
Bibliographic record
Abstract
Studies have shown that non-standard work hours are associated with an increased risk of accidents and injuries in healthcare, transportation and manufacturing sectors. Nevertheless, findings in Maritime work environment related to seafarers remain limited and inconsistent. To date, no meta-analytic synthesis has been published on this topic. We conducted a systematic review to examine whether exposure to non-standard work hours/shift work such as night shifts, extended work hours, rotation shifts is associated with an increased risk of accidents and injuries among seafarers. The study was registered in PROSPERO 2024 CRD42024543444.Methods: The review included 941 relevant original empirical studies from peer-reviewed electronic databases such as Ovid MEDLINE, PsycINFO, EMBASE and the Web of Science core collection using a predefined search strategy following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines. Inclusion criteria yielded only three (03) studies in the final review, which did not specifically study the relationship between non-standard work hours and the occurrence of injuries and accidents in seafarers.Results: Studies were largely registry based, cross-sectional studies and reported accidents and injury rates as key outcomes. The studies were from multiple counties, including the UK, Norway, Sweden, Canada, Poland, Philippine, Croatia, Indonesia, Spain, South Africa, German, Hongkong, Russia, Poland, China, Italy and Denmark. In the Great Britain, 36% of the deaths at sea were caused by accidents (95% CI: 19.8-34.7, N=1405) between 1979/80 and 1982/3, with a fatal accident rate in seafaring of 51.6 per 100,000 seafarer-years. Higher accident frequency occurred during night shifts (00:00-04:00) than during normal day hours and were related to work schedules and sleep deprivation. Injury rate varied from 6.31 per 1,000 (95%CI: 4.98-7.85) seafarers-years (4-year period) in Italy, 43.7 per 100,000 seafarer-years in the UK, to 40 per 1,000,000 work hours in a multi country study (11- countries). Conclusion: This review shows a high rate of accidents and injury among seafarers documented in various studies across the globe and suggests that these incidents are more frequent during non-standard work hours. However, studies directly associating non-standard work shifts with the occurrence of accidents and injuries among seafarers are scarce, warranting further research in this area.
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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 | 0.008 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".