Acute fatigue predicts sickness absence in the workplace: A 1-year retrospective cohort study in paediatric nurses.

AIMS: To examine the relationship between fatigue and sickness absence in nurses from a paediatric hospital over 12 months of follow-up. A secondary aim was to identify other work and personal factors that predict sickness absence. BACKGROUND: Sickness absence is often related to worker-fatigue, yet few studies have explored this relationship in nurses despite documented high fatigue levels. DESIGN: The study used retrospective cohort design. METHODS: Baseline data on 40 nurses from an intervention study were linked to absence data using the hospital's attendance records (2012-2013). A total of 6,057 work shifts were studied of which 5.2% were absence episodes. Fatigue was measured by the Occupational Fatigue Exhaustion Recovery scale. The questionnaire included instruments assessing sleep disturbances, workload and personal characteristics. Generalized linear mixed models were used to test the associations between fatigue, work, personal factors and sickness absence, while accounting for non-independency of repeated measures. RESULTS: With 1SD increase in acute fatigue scores, nurses were 1.29 times more likely to be absent from work. Factors such as intershift recovery, perceived workload, obstructive sleep apnoea and marital status also predicted sickness absence, that is, with 1SD increase in workload scores, nurses were 1.23 times more likely to be absent from work. Nurses with obstructive sleep apnoea had two times higher odds of sickness absence. CONCLUSION: Sickness absence is related to acute fatigue in paediatric nurses and to workload. Nursing leaders can monitor these factors to reduce sickness absence and screen for sleep apnoea and assist nurses in receiving the appropriate treatments.

Nurses' Short-Term Sickness Absences Before and After the Implementation of a Brief Napping Opportunity During Night Shifts.

BACKGROUND: Nurses who work at night have used naps to alleviate their sleepiness and fatigue. Research has shown night shifts, sleepiness, and fatigue predict nurses' missed workdays. Thus, nighttime napping may have a beneficial consequence of reducing nurses' sickness absences. The purpose of this brief report was to describe the difference in rates of short-term sickness absence before and after implementation of a 30-min nap opportunity in one U.S. hospital for 12-hr shift nurses. METHODS: The study was a retrospective pre-post evaluation design. Eight units provided nap opportunities for the nurses. Full-time nurses were classified into night and rotating shifts based on their 2 years of scheduling patterns. Absence data were extracted from the hospital's timekeeping system and annual absence rates were computed. A single linear mixed model with rank transformed data was conducted for each group. Median estimates, minimum and maximum, and p-values were reported. FINDINGS: The median absence rates for night shift nurses were 4.3% and 4.0% for the pre-napping and post-napping implementation periods, respectively; however, this difference was not statistically significant (p = .241). The median absence rates for rotating shift nurses were 2.0% and 3.9% for the pre-napping and post-napping implementation periods, respectively; and the difference increase was statistically significant (p < .001). CONCLUSION/APPLICATION TO PRACTICE: A nap policy which provides nurses with the opportunity to take nighttime naps did not benefit their sickness absence rates. Future research needs to examine the actual napping process on sickness absences, as well as explore other sickness management avenues.

Bio-mathematical fatigue models predict sickness absence in hospital nurses: An 18 months retrospective cohort study.

This study examined the associations between bio-mathematical fatigue-risk scores and sickness absence (SA) in hospital nurses over 18 months. Work schedules and SA data were extracted from the hospital's attendance system. Fatigue-risk scores were generated for work days using the Fatigue Audit InterDyne (FAID) and Fatigue Risk Index (FRI). Over the study period, 5.4% of the shifts were absence shifts. FAID-fatigue ranged from 7 to 154; scores for a standard 9-5 work schedule can range from 7 to 40. Nurses with high FAID-scores were more likely to be absent from work when compared to standard FAID-scores (41-79, OR = 1.38, 95%CI = 1.21-1.58; 80-99, OR = 1.63, 95%CI = 1.37-1.94 and ≥ 100, OR = 1.73, 95%CI = 1.40-2.13). FRI-fatigue ranged from 0.9 to 76.8. When FRI-scores were >60, nurses were at 1.58 times (95%CI = 1.05-2.37) at increased odds for SA compared to scores in the 0.9-20 category. Nurse leaders can use these decision-support models to adjust high-risk schedules or the number of staff needed to cover anticipated absences from work.