Reducing sickness absence among public-sector healthcare employees: the difference-making roles of managerial and employee participation.

PURPOSE: Evaluations of organizational-level interventions to prevent work-related illness have identified enabling factors, but knowledge of necessary and sufficient conditions for intervention success is needed. The aim was to identify difference-making factors that distinguish intervention groups with and without a positive intervention effect on sickness absence. METHODS: An organizational-level intervention designed to decrease sickness absence by providing support from process facilitators was implemented at eight healthcare workplaces in Sweden between 2017 and 2018. We applied coincidence analysis (CNA) to analyze 34 factors and determine which factors were necessary and sufficient for a successful implementation of tailored interventional measures on an organizational level (dichotomous) and reduced sickness absence (trichotomous). RESULTS: Two factors perfectly explained both the presence and absence of a successful implementation: "a high sense of urgency" and "good anchoring and participation from the strategic management". The presence of either of these factors alone was sufficient for successful implementation, whereas the joint absence of both conditions was necessary and sufficient for the absence of successful implementation and an intervention effect. In addition, high employee participation was both necessary and sufficient for a high intervention effect. For organizations without high employee participation, successful implementation led to a medium-effect size. CONCLUSIONS: This study identified participation as a difference-maker in the implementation process. Participation from different stakeholders turned out to be important in different phases. When implementing organizational-level interventions, high participation from both strategic management and employees appears to be crucial in terms of the intervention's effect on sickness absence.

Methodological approach for measuring the effects of organisational-level interventions on employee withdrawal behaviour.

BACKGROUND: Theoretical frameworks have recommended organisational-level interventions to decrease employee withdrawal behaviours such as sickness absence and employee turnover. However, evaluation of such interventions has produced inconclusive results. The aim of this study was to investigate if mixed-effects models in combination with time series analysis, process evaluation, and reference group comparisons could be used for evaluating the effects of an organisational-level intervention on employee withdrawal behaviour. METHODS: Monthly data on employee withdrawal behaviours (sickness absence, employee turnover, employment rate, and unpaid leave) were collected for 58 consecutive months (before and after the intervention) for intervention and reference groups. In total, eight intervention groups with a total of 1600 employees participated in the intervention. Process evaluation data were collected by process facilitators from the intervention team. Overall intervention effects were assessed using mixed-effects models with an AR (1) covariance structure for the repeated measurements and time as fixed effect. Intervention effects for each intervention group were assessed using time series analysis. Finally, results were compared descriptively with data from process evaluation and reference groups to disentangle the organisational-level intervention effects from other simultaneous effects. RESULTS: All measures of employee withdrawal behaviour indicated statistically significant time trends and seasonal variability. Applying these methods to an organisational-level intervention resulted in an overall decrease in employee withdrawal behaviour. Meanwhile, the intervention effects varied greatly between intervention groups, highlighting the need to perform analyses at multiple levels to obtain a full understanding. Results also indicated that possible delayed intervention effects must be considered and that data from process evaluation and reference group comparisons were vital for disentangling the intervention effects from other simultaneous effects. CONCLUSIONS: When analysing the effects of an intervention, time trends, seasonal variability, and other changes in the work environment must be considered. The use of mixed-effects models in combination with time series analysis, process evaluation, and reference groups is a promising way to improve the evaluation of organisational-level interventions that can easily be adopted by others.

Low personal exposure to benzene and 1,3-butadiene in the Swedish petroleum refinery industry.

PURPOSE: Petroleum refinery workers are exposed to the carcinogens benzene and 1,3-butadiene. Declining exposures have been reported internationally but information on current exposure in the Swedish refinery industry is limited. The aim was to examine refinery workers' personal exposure to benzene and 1,3-butadiene and increase awareness of exposure conditions by collaboration with involved refineries. METHODS: Altogether 505 repeated personal exposure measurements were performed among workers at two refineries. Full-shift measurements were conducted in different exposure groups using Perkin Elmer diffusive samplers filled with Carbopack X. Mean levels were calculated using mixed-effects models. A large fraction of measurements below the limit of detection (LOD) required imputation of computer-generated data. RESULTS: Mean benzene exposure among process technicians was 15.3 µg/m3 (95% CI 10.4-22.5 µg/m3) and 13.7 µg/m3 (95% CI 8.3-22.7 µg/m3) for Refinery 1 and 2, respectively. Process technicians working outdoors had higher exposure than maintenance workers (20.7 versus 5.9 µg/m3, p < 0.01). Working in the harbour and tank park (Refinery 1), compared with the process area, was associated with higher exposure. The 1,3-butadiene exposure was low, 5.4 and 1.8 µg/m3, respectively. The total variation was generally attributed to within-worker variability. CONCLUSIONS: Low benzene and 1,3-butadiene levels were found among refinery workers. Mean benzene exposure was about 1% of the Swedish occupational limit (1500 µg/m3) and for 1,3-butadiene, exposure was even lower. A large fraction of values below the LOD can be managed by carefully modelled, computer-generated data.

Personal exposure to benzene and 1,3-butadiene during petroleum refinery turnarounds and work in the oil harbour.

PURPOSE: Petroleum refinery workers' exposure to the carcinogens benzene and 1,3-butadiene has decreased during normal operations. However, certain occupational groups or events at the refineries still involve a risk of higher exposures. The aim of this study was to examine the personal exposure to benzene and 1,3-butadiene at refinery turnarounds and during work in the oil harbour. METHODS: Personal exposure measurements of benzene and 1,3-butadiene were taken during work shifts, with a priori assumed higher benzene exposure, using PerkinElmer diffusive samplers filled with Carbopack X. Mean exposure levels were calculated, and repeated exposure measurements, when available, were assessed using mixed effect models. Group and individual compliance with the Swedish occupational exposure limit (OEL) was tested for the different exposure groups. RESULTS: Mean benzene exposure levels for refinery workers during the three measured turnarounds were 150, 610 and 960 µg/m3, and mean exposures for oil harbour workers and sewage tanker drivers were 310 and 360 µg/m3, respectively. Higher exposures were associated with handling benzene-rich products. Most occupational groups did not comply with the Swedish OEL for benzene nor did the individuals within the groups. The exposure to 1,3-butadiene was very low, between <1 and 3 % of the Swedish OEL. CONCLUSIONS: Work within the petroleum refinery industry, with potential exposure to open product streams containing higher fractions of benzene, pose a risk of personal benzene exposures exceeding the OEL. Refinery workers performing these work tasks frequently, such as contractors, sewage tanker drivers and oil harbour workers, need to be identified and protected.