The Use of Worktime Planning Tools in the Finnish Public Sector. A Quasi-experimental Study (PLANTOOLS) (PLANTOOLS)

The Use of Worktime Planning Tools in the Finnish Public Sector. A Quasi-experimental Study (PLANTOOLS)

The Use of Worktime Planning Tools in the Finnish Public Sector. A Quasi-experimental Study (PLANTOOLS)

CGI Finland Ltd, Helsinki, Finland, Finnish Work Environment Fund, NordForsk, Nordic Program on Health and Welfare, Oslo, Norway, European Union Horizon2020 Call:H2020-SC1-DTH-2018-2020

This study aims to investigate whether use of interactive worktime planning tools that support work-time control (possibilities to influence individual shift rosters, i.e., participatory rostering) and guide for health-supporting shift ergonomics will improve health and well-being among shift workers, especially among ageing employees. Effects of the worktime planning tools will be studied in a quasi-experimental design in the Finnish public sector. Health and well-being at baseline (2012-2015), will be compared to follow-up data in 2016-2019 based on questionnaire and pay-roll based objective working hour and sickness absence data among those who a) use an interactive self-rostering software with a shift ergonomics sub-tool, b) whose working hours are designed with a non-interactive shift planning software with the shift ergonomics sub-tool and c) whose working hours are designed with a non-interactive shift planning software without the shift ergonomics sub-tool.

Introduction Epidemiological studies suggest that shift work increases the risk of several major public health diseases, such as cardiovascular diseases. Shift work is also associated with work-life conflict and work stress. Appropriate shift scheduling is expected to modify the health risks of shift work but there is not sufficiently knowledge on whether it is possible to improve work time control and other health-supporting shift characteristics (shift ergonomics) using different types of shift scheduling tools, and whether the possible changes in working hours can lead to successful and cost-saving changes in health and well-being. There is especially lack of intervention studies on the means to improve the working hours of women and ageing workers. Material and methods Software In the Finnish public sector, basically three separate shift scheduling software versions are currently available (Titania, CGI© Finland, Finland). The first one (Titania1), is an interactive software supporting interactive shift rostering (individual worktime control for employees) and giving guidance for health-supporting shift ergonomics both to the shift planners use the employees using the software. The second software (Titania2) is used by the shift planners only, and it gives similar guidance for health-supporting shift ergonomics than software Titania1 but does not include an option for participatory rostering. The third software (Titania3) is otherwise similar shift planning software than Titania 2 (used by the shift planners only) but does not include neither the participatory rostering nor the health-supporting shift ergonomics tools. The investigators will use a sampling software that has been developed earlier, to retrieve all the daily objective working hour and absence data from the employers´ records. The reliability, validity, and accuracy of the used method to retrieve and analyze pay-roll data on working hours has been assessed earlier based partially on the same dataset as this study. The raw data will include data on each calendar day on shift starting and ending times, the use of shift wishes and reasons for absence. The raw data will be processed into individual level data by construction of variables within specific time frame (i.e., shift characteristics based on the length, time, recovery and social aspects of working hours per month or year). Study design Using a non-randomized quasi-experimental design, the use of a self-rostering software including also an option to evaluate shift ergonomics will be compared to the use of a shift scheduling software without self-rostering but an option for shift ergonomics evaluation and secondly, to shift scheduling software as usual (without self-rostering and shift ergonomics evaluation). Questionnaire and registry data from 2016-2019 after the intervention (T2) will be compared to baseline data from 2012 to 2015 before the intervention (T1) in the three groups. Participants The use of the three different versions of shift planning software will be studied in approximately 6 000 employees in shift planning units/departments that will be accounted as clusters in the analyses in six hospital districts of the ongoing Finnish Public Sector study. According to 3/2016 information, 2/6 hospital districts have made a managerial decision to start to use the Titania1 software during 2016 in all applicable wards, 2/6 hospital districts have decided to start to use the Titania2 software, and 2/6 organizations have decided to remain in Titania3 software. Participants are all hospital employees working in units that use the software (1-3) in the 6 hospital districts since 9/2015 for at least one year, and who have answered to a questionnaire sent to all the workers of the organizations in 2015 and 2017 or 2019. Based on earlier response rates of the cohort, the expected sample size is approximately 6000 employees, who are using at least one version of the software, and who will reply the questionnaire both in 2015 and 2017 and/or 2019. In order to minimize potential bias due to non-randomization and possible selection, the shift planning units (clusters) using Titania1, Titania2 and Titania3 will be matched for a) the amount of shift work (% of workers in each cluster having non-day shifts), b) age and c) baseline level of perceived work-time control (only for intervention 1: shift planning with shift ergonomics and self-rostering) or c) shift ergonomics (only for intervention 2: shift ergonomics). The pay-roll based daily working hour data will be retrieved from the shift scheduling program retrospectively from the beginning of 2012 and prospectively up to the end of 2019. Additional funding enables us to continue the follow-up from 2017 to 2019. In addition to comparing the overall effects of the use of Titania1 and Titania2 tools compared to Titania3, a subgroup analysis will be done based on the registry-based individual use of the Titania1 and Titania 2 software within the group the possible changes of the perceived worktime control and objective shift characteristics and individual differences (e.g. age, diurnal type, health). Thematic focus group interviews will be performed in the participating organizations to gather end-user, shift-planner and employers´ attitudes, change processes and experiences on using the Titania tools. This information will be used to further develop the Titania tools according to feedback. The guidelines of the Transparent Reporting of Evaluations with Non-randomized Designs (TREND) will be used in the reporting of the results.

Employees working in shift planning units (clusters) using an interactive shift planning software (Titania1) with sub-tools for individual shift planning (self-rostering) and an option for shift ergonomics evaluation to both the shift planner and the employees

Employees working in shift planning units (clusters) where shift planners use a non-interactive shift planning software (Titania2) providing guidance for health-supporting shift ergonomics.

Employees working in shift planning units (clusters) where a standard shift planning software (Titania3) without interactive shift rostering or guidance for health-supporting shift ergonomics is used by shift planners.

Employees working in shift planning units (clusters) using an interactive shift planning software (Titania1) with sub-tools for individual shift planning (self-rostering) and an option for shift ergonomics evaluation to both the shift planner and the employees

Employees working in shift planning units (clusters) where shift planners use a non-interactive shift planning software (Titania2) providing guidance for health-supporting shift ergonomics.

Length (1-365 days/year) of sickness absence and frequency of sickness absence spells (i.e. frequency of all sickness absence periods within 1-365 days/year) obtained from the pay-roll based objective working hour data including dates of absence due to sickness without information on the medical cause of the sickness absence.

Length of working hours, time of the day (when worked), shift intensity and social aspects of working hours (Härmä et al. 2015) obtained from the pay-roll based objective working hour data.

Questionnaire data on the work-family and family-work interaction with a 6-point scale (0 = no family, from 1 never to 5 very often), and general situation in life with a 6-point scale (from 1=easy to 6=extremely hard)

Questionnaire data on perceived subjective health with a 5-point scale from 1=good to 5=poor (OARS 1978, Idler et al. 1990)

Starting and ending times of a workday, taking breaks during workday, handling private matters during workday, scheduling of work shifts, scheduling of vacations and paid days off, and taking unpaid leave (Ala-Mursula et al. 2002)

Questionnaire data with following questions: How often you have had severe sleepiness during the past three months, and how often you have had insomnia (difficulties in initiating sleep, difficulties in maintaining sleep and frequent awakenings during sleep) during the past three months (ICSD-3 classification), both questions with regard to morning shifts, evening shifts, night shifts, and during days off from work and during at least two weeks´ vacation.

Questionnaire data on GHQ12 -measure. The four response choices 0 "Not at all", 1 "Same as usual", 2 "Rather more than usual" and 3 "Much more than usual" will be dichotomized as follows: 0=0, 1=0, 2=1, 3=1. GHQ-12 case ≥ 3 points. (Goldberg & Williams 1988)

Economic benefits measured as changes in sickness absence and use of replacement labour (based on pay-roll based working hour data), changes in disability pension experience rating (based on employer registers), changes in intentions to continue in current work (questionnaire data on intentions in continuing at current work if it were possible to switch workplace or occupation: continue at current work, switch workplace, switch occupation, give up working. Intentions in continuing working or retiring if it were possible to retire: continue working, retiring, don't know) and changes in perceived pecuniary and nonpecuniary benefits (questionnaire data on perceived pecuniary and nonpecuniary benefits on 5-point scale from 1= very much to 5 = very little). Costs include all the costs related to intervention such as purchase, maintenance, training and use of Titania (based on employer registers).

Thematic interviews in each participating organization to gather end-user, shift-planner and employers´ attitudes, change processes and experiences on using the Titania and sub-tools.

Inclusion criteria: All hospital workers in the hospital wards (clusters) of six hospital districts in Finland Working hours are planned with Titania software (1-3) starting from 9/2015 for at least one year Employees who have answered a questionnaire sent to all current employees of the organizations in 2015 Employees who will answer to similar questionnaire in 2017 and/or 2019. Exclusion Criteria: Physicians (due to on-call work not registered in the database) Employees who have less than 120 working days (approx.6 months without leaves) before and after the use of the software

Ala-Mursula L, Vahtera J, Kivimaki M, Kevin MV, Pentti J. Employee control over working times: associations with subjective health and sickness absences. J Epidemiol Community Health. 2002 Apr;56(4):272-8. doi: 10.1136/jech.56.4.272.

Des Jarlais DC, Lyles C, Crepaz N; TREND Group. Improving the reporting quality of nonrandomized evaluations of behavioral and public health interventions: the TREND statement. Am J Public Health. 2004 Mar;94(3):361-6. doi: 10.2105/ajph.94.3.361.

Goldberg D, Williams P. 1988. A user´s guide to the General Health Questionnaire. Berkshire: UK. NFER-Nelson.

Hansen AM, Nabe-Nielsen K, Albertsen K, Hogh A, Lund H, Hvid H, Garde AH. Self-rostering and psychosocial work factors - a mixed methods intervention study. Appl Ergon. 2015 Mar;47:203-10. doi: 10.1016/j.apergo.2014.10.006. Epub 2014 Oct 22.

Harma M, Ropponen A, Hakola T, Koskinen A, Vanttola P, Puttonen S, Sallinen M, Salo P, Oksanen T, Pentti J, Vahtera J, Kivimaki M. Developing register-based measures for assessment of working time patterns for epidemiologic studies. Scand J Work Environ Health. 2015 May 1;41(3):268-79. doi: 10.5271/sjweh.3492. Epub 2015 Mar 19.

Idler EL, Angel RJ. Self-rated health and mortality in the NHANES-I Epidemiologic Follow-up Study. Am J Public Health. 1990 Apr;80(4):446-52. doi: 10.2105/ajph.80.4.446.

OARS. 1978. Multidimensional functional assessment: The OARS methodology (2nd ed.). Durham, NC: Duke University.

Turunen J, Karhula K, Ropponen A, Koskinen A, Hakola T, Puttonen S, Hamalainen K, Pehkonen J, Harma M. The effects of using participatory working time scheduling software on sickness absence: A difference-in-differences study. Int J Nurs Stud. 2020 Dec;112:103716. doi: 10.1016/j.ijnurstu.2020.103716. Epub 2020 Jul 14.

Karhula K, Turunen J, Hakola T, Ojajarvi A, Puttonen S, Ropponen A, Kivimaki M, Harma M. The effects of using participatory working time scheduling software on working hour characteristics and wellbeing: A quasi-experimental study of irregular shift work. Int J Nurs Stud. 2020 Dec;112:103696. doi: 10.1016/j.ijnurstu.2020.103696. Epub 2020 Jun 24.

Shiri R, Karhula K, Turunen J, Koskinen A, Ropponen A, Ervasti J, Kivimaki M, Harma M. The Effect of Using Participatory Working Time Scheduling Software on Employee Well-Being and Workability: A Cohort Study Analysed as a Pseudo-Experiment. Healthcare (Basel). 2021 Oct 16;9(10):1385. doi: 10.3390/healthcare9101385.

Karhula K, Hakola T, Koskinen A, Lallukka T, Ojajarvi A, Puttonen S, Oksanen T, Rahkonen O, Ropponen A, Harma M. Ageing shift workers' sleep and working-hour characteristics after implementing ergonomic shift-scheduling rules. J Sleep Res. 2021 Aug;30(4):e13227. doi: 10.1111/jsr.13227. Epub 2020 Nov 9.

Turunen J, Karhula K, Ropponen A, Koskinen A, Shiri R, Sallinen M, Ervasti J, Pehkonen J, Harma M. The Time-Varying Effect of Participatory Shift Scheduling on Working Hour Characteristics and Sickness Absence: Evidence from a Quasi-Experiment in Hospitals. Int J Environ Res Public Health. 2022 Nov 8;19(22):14654. doi: 10.3390/ijerph192214654.