Evidence map›Paper›PMID 36481001›Full record

ArticleJournal of safety research2022

Do employees' work schedules put them at-risk? The role of shift scheduling and holidays in predicting near miss and incident likelihood.

Matthew M Laske, Philip E Hinson, Yalcin Acikgoz, Timothy D Ludwig, Anne M Foreman, Shawn M Bergman

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of safety research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Matthew M LaskeUniversity of Kansas, United States.
Philip E HinsonAppalachian State University, United States.
Yalcin AcikgozAppalachian State University, United States. Electronic address: acikgozy@appstate.edu.
Timothy D LudwigAppalachian State University, United States.
Anne M ForemanNational Institute of Occupational Safety and Health, United States.
Shawn M BergmanAppalachian State University, United States.

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

introductionUsing crew scheduling and injury incident data from a Fortune 500 manufacturing company, this study analyzed the effect of consecutive shifts and shifts near holidays on near misses and incidents.

methodsLogistic regressions were conducted with consecutive workdays, days near holidays, and time of shift as predictors of incident and near miss outcomes.

resultsThe logistic regression analysis indicated that working consecutive day shifts increases the probability of an incident occurring, with the fourth consecutive shift resulting in the most risk. The consecutive shift pattern did not replicate to employees working the night shift. However, the first and second shifts when transferring to a night schedule appear to have a greater chance of incident. Shifts near holidays did not have a significantly higher risk than other shifts. PRACTICAL APPLICATION: The current research suggests that organizations can use similar analytic techniques to determine if shift scheduling might be related to increased risk and allocate resources to mitigate hazards during those peak probability shifts.

Indexed as

Personnel Staffing and SchedulingHumansConsecutive shiftsHoliday scheduleInjury predictionNear miss predictionShift-schedule

Identifiers

PMID36481001
PMCPMC10098862

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.