| Reference : Quality of Work and Quality of Employment Profiles and their longitudinal impact on w... |
| Scientific congresses, symposiums and conference proceedings : Unpublished conference | |||
| Social & behavioral sciences, psychology : Social, industrial & organizational psychology | |||
| http://hdl.handle.net/10993/52175 | |||
| Quality of Work and Quality of Employment Profiles and their longitudinal impact on well-being | |
| English | |
Sischka, Philipp  [University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Behavioural and Cognitive Sciences (DBCS) >] | |
| Fernandez de Henestrosa, Martha [University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Behavioural and Cognitive Sciences (DBCS) >] | |
| Steffgen, Georges [University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Behavioural and Cognitive Sciences (DBCS) >] | |
| 6-Jul-2022 | |
| Yes | |
| No | |
| International | |
| 17th European Congress of Psychology | |
| 05-07-2022 to 08-07-2022 | |
| Cankarjev dom | |
| Ljubljana | |
| Slovenia | |
| [en] Quality of Work ; Quality of Employment ; Well-Being ; Latent Class Analysis ; Latent Transition Analysis ; Job quality | |
| [en] Many studies on job quality operationalize job quality as a composite indicator (Munoz de Bustillo et al., 2011) and investigate its link with different well-being outcomes or investigate the incremental effects of specific job characteristics on well-being. However, these variable-centered approaches on job quality ignore the fact that certain job characteristic configurations cluster in specific employee groups (Van Aeren et al., 2014). Thus, the current longitudinal study employs a person-centered approach (i.e., latent profile and transition analysis (LPA/LTA), e.g., Spurk et al., 2020) to identify groups of employees that show different job characteristic profiles (over time).
Data were collected via CATI or CAWI within a stratified random sample from Luxembourg’s working population (nWave 1 = 1,689; nWave 2 = 848). The survey contains eleven quality of work and six quality of employment dimensions that were used as indicators for the latent profile analysis. Moreover, the survey contains different mental health and work-related attitudinal outcomes. Fit indices and substantive interpretability/utility were jointly considered to determine the number of profiles. To explore the relationships between the latent categorical variable and the other variables, we followed the three-step procedure (e.g., Asparouhov & Muthén, 2014) LPA revealed five profiles, i.e., poor working conditions (1), medium working conditions, high work intensity (2), high working conditions, medium work intensity (3), high working conditions, high work intensity and physical demands (4), medium working conditions, low work intensity (5). Cross-sectionally, these profiles were meaningfully linked with mental and attitudinal outcomes. LTA suggests the stability of these profiles within one year, with varying impact depending on mental health and work-related attitudinal outcome. Scholars and policy makers need to be aware of job characteristic configurations. To promote employee’s well-being organizations and policy makers need to redesign the ecological contexts of working conditions depending on its profiles. | |
| Quality of Work | |
| Researchers | |
| http://hdl.handle.net/10993/52175 | |
| https://www.ecp2022.eu/index.php/programme/programme |
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