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RESEARCH PRODUCT
The effects of using participatory working time scheduling software on working hour characteristics and wellbeing : a quasi-experimental study of irregular shift work
Sampsa PuttonenMika KivimäkiAnneli OjajärviTarja HakolaJarno TurunenMikko HärmäAnnina RopponenKati Karhulasubject
Shift workIMPACTComputer scienceNursesCAREER SATISFACTIONLogistic regressionwork time controlScheduling (computing)Work time controlShift work0302 clinical medicinenursingWork Schedule ToleranceHealth care030212 general & internal medicinehospital employeesGeneral NursingFinlandosallistuminenself-rostering030504 nursingShift Work ScheduleASSOCIATIONWorking timehealth carevuorotyöBALANCE8. Economic growthworking time autonomySelf-rosteringHEALTHHospital employees health care316 Nursing0305 other medical scienceEMPLOYEE CONTROLtyöhyvinvointiStaffingPersonnel Staffing and SchedulingNursing03 medical and health sciencesHumansOperations managementajanhallintaGeneral linear modelbusiness.industryWorking time autonomySLEEP DISTURBANCESRepeated measures designtyöaikashift workhoitohenkilöstöbusinessSoftwarehoitotyödescription
Background: Studies in the health care sector indicate that good work time control is associated with better perceived wellbeing but also with non-ergonomic work schedules, such as compressed work schedules. Participatory working time scheduling is a collaborative approach to scheduling shift work. Currently, there is a lack of information on whether working hour characteristics and employees' wellbeing in irregular shift work change after implementing participatory working time scheduling. Objective: To investigate the effects of using digital participatory working time scheduling software on working hour characteristics and well-being among Finnish hospital employees. Participants and methods: We compared changes in objective working hour characteristics and wellbeing between 2015 and 2017 among employees (n = 677, mainly nurses and practical nurses) when using participatory working time scheduling software (participatory scheduling, n = 283) and traditional shift scheduling (traditional scheduling, n = 394). The statistical analyses were conducted using the repeated measures general linear model and the generalized logit model for binomial and multinomial variables adjusted for age, sex, education, shift work experience, control over scheduling of shifts at baseline (where applicable) and hospital district. Results: The proportion of long work shifts (>= 12 h) increased to a greater extent (F = 4.642, p = 0.032) with the participatory scheduling than with the traditional scheduling. In comparison to traditional scheduling, the perceived control over scheduling of shifts increased (OR 3.24, 95% CI 1.73-6.06) and excessive sleepiness in connection with evening shifts decreased (OR 0.40, 95% CI 0.16-0.99) significantly with participatory scheduling. None of the other wellbeing variables showed statistically significant changes in the adjusted models. Conclusions: The proportion of long work shifts and perceived control over scheduling of shifts increased more among employees using participatory working time scheduling than among those using traditional scheduling. Otherwise, using participatory working time scheduling software had little effect on both objectively measured working hour characteristics and perceived wellbeing in comparison to traditional scheduling. The results merit confirmation in a larger sample with a longer follow-up. Tweetable abstract Participatory working time scheduling combines individual flexibility and staffing requirements in shift work. (C) 2020 Elsevier Ltd. All rights reserved. Peer reviewed
year | journal | country | edition | language |
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2020-12-01 |