Effects of the Labour Inspectorate Authority’s regulatory tools on psychosocial and biomechanical work factors in Norwegian home care services: a cluster randomised controlled trial

Abstract

ObjectivesThis study aimed to determine the effects of the Labour Inspectorate Authority’s (LIA’s) regulatory tools on psychosocial and biomechanical work factors in the Norwegian municipal home care services.MethodsA cluster-randomised controlled trial conducted in the home care services with employee questionnaire data on work factors at baseline, and 6 and 12 months after the interventions. In total, 96 eligible municipalities were randomly assigned to either the control group or one of two interventions: (1) labour inspection visits, based on the LIA’s standard inspections; and (2) guidance-through-workshops, where the participating services highlighted issues and trained labour inspectors provided guidance based on existing labour laws and regulations.ResultsNo favourable intervention effect was observed for the inspection intervention. No effects were observed for most of the variables in the guidance intervention, although an effect was observed for the following psychosocial factors: decision control, control over work intensity and empowering leadership. However, after adjusting for multiple testing, none of the observed effects were statistically significant.ConclusionLabour inspections did not affect psychosocial and biomechanical work factors in the home care services. A favourable effect of the guidance intervention on psychosocial work factors was observed. However, this was not evident after adjusting for multiple testing. Further research is needed to elaborate on how labour inspections and other regulatory tools can impact psychosocial and biomechanical work factors.Trial registration numberNCT03855163.

Effects of the Labor Inspection Authority’s regulatory tools on physician-certified sick leave and employee health in Norwegian home-care services – a cluster randomized controlled trial

“…The results suggest a need to further develop the content of regulatory tools to better address risk factors to occupational health in practice, for example through clearer and more defined regulations. The findings are in accordance with a previously noted lack of effect of regulatory tools on psychosocial and mechanical work factors ( 25 ), further suggesting a need for future studies on how regulatory tools can influence the work environment and prevent ill-health and subsequent sickness absence. Future research should also aim to further elucidate the effects of regulatory tools, for example using other methods and in different sectors.…”

“…Given this lack of effect on work factors, one would expect limited potential of the two interventions to influence employee health and rates of sickness absence. Work factors other than those covered in Finnanger Garshol et al ( 25 ) could potentially influence sickness absence and employee health, and the interventions could have influenced how employers followed-up employee sickness absences. As such, unobserved factors could potentially explain some of the patterns seen regarding changes in physician certified sick leaves with a decrease in musculoskeletal-related sick leave and an increase in psychology-related sick leave.…”

“…The lower response rate and subsequent attrition could have introduced biases in the data, and those who stopped responding were generally younger, with less education and a lower mean employment percentage, and were more often in the “other healthcare staff” category. However, the differences were small, and the between-group distribution remained similar to that at baseline throughout the study period ( 25 ). Similar differences were observed among those who did not consent to the use of registry data.…”

“…Overall, 104 of the 132 randomly assigned municipalities were recruited before the planned implementation of the interventions. Originally three intervention groups were planned ( 24 ), but – due to fewer recruited municipalities than expected – those in the last intervention group (online risk assessment) were randomly reallocated to the remaining two interventions and the control group [see Finnanger Garshol et al ( 25 ) for further details]. In total, 96 municipalities participated in the study, and these had 3985 employees in their home-care services.…”

“…There were no drop-out in the registry data, while the overall drop-out rate among those who responded at baseline was 65.2% over the course of the study. Those who stopped responding were younger, had less education, had a lower percentage of full-time equivalent employment, and were more often listed as “other care staff” ( 25 ). Figure 1, adapted from the project protocol ( 24 ), provides an overview of the study recruitment and the flow of participants including endpoint for registry data.…”