A. Mäkikangas

Multilevel Latent Profile Analysis With Covariates: Identifying Job Characteristics Profiles in Hierarchical Data as an Example

Latent profile analysis (LPA) is a person-centered method commonly used in organizational research to identify homogeneous subpopulations of employees within a heterogeneous population. However, in the case of nested data structures, such as employees nested in work departments, multilevel techniques are needed. Multilevel LPA (MLPA) enables adequate modeling of subpopulations in hierarchical data sets. MLPA enables investigation of variability in the proportions of Level 1 profiles across Level 2 units, and of Level 2 latent classes based on the proportions of Level 1 latent profiles and Level 1 ratings, and the extent to which covariates drawn from the different hierarchical levels of the data affect the probability of a membership of a particular profile. We demonstrate the use of MLPA by investigating job characteristics profiles based on the job-demand-control-support (JDCS) model using data from 1,958 university employees clustered in 78 work departments. The implications of the results for organizational research are discussed, together with several issues related to the potential of MLPA for wider application.

Testing the direct and moderator effects of the stressor–detachment model over one year: A latent change perspective

ABSTRACT To test the direct and moderator effects of the stressor–detachment model from a long-term perspective, we investigated whether workload and detachment are related to changes in exhaustion and sleep difficulties over one year. We also examined whether detachment attenuates the relationship between high workload and these outcomes both cross-sectionally and over time. Questionnaire data with 1722 respondents at Time 1 and 1182 respondents at Time 2 were collected. We used a latent change score approach to analyse the data in order to identify intra-individual change among the studied constructs. Our results showed that high workload and low detachment at baseline were related to an increase in exhaustion over one year. Additionally, an increase in workload and a decrease in detachment were related to a simultaneous increase in exhaustion over time. Low detachment, but not high workload, was related to an increase in sleep difficulties over time, and a decrease in detachment across one year was related to a simultaneous increase in sleep difficulties. A high level of detachment only attenuated the relationship between workload and exhaustion at baseline. Our results underline the significance of poor psychological detachment as a risk factor for the development of strain outcomes over time.

Work–family interface in atypical working arrangements

In this chapter, we review previous quantitative studies, which have focused on family-related outcomes of atypical work arrangements, including non-standard working hours and temporary work. Altogether, it seems that non-standard working hours have more often received research attention than temporary work, as far as family-related outcomes are concerned. Specifically, the results of our review reveal that non-standard working hours do not inevitably result in negative family-related outcomes, for example, work–family conflict, marital instability, children’s socio-emotional or cognitive problems. However, there are certain risk factors, such as night shifts, small children at home, which might increase the likelihood for negative family-related outcomes. Thus far, published studies on the effects of temporary work arrangements on family-related outcomes are rare. Moreover, these earlier findings are inconclusive, with only some evidence for the detrimental effects of temporary work on family-related effects, for example, work–family conflict, work–family enrichment. On the basis of our findings, we also suggest an integrative model for future research and present some of the implications for policy makers and organizations.