Working, but not for a living: a longitudinal study on the psychological consequences of economic vulnerability among German employees

Abstract

Despite the rise of in-work poverty across Europe, the psychological consequences of individual economic vulnerability are still rather unknown. Drawing on both objective and subjective conceptualizations of economic vulnerability, we investigate the effects of individual low labour income and perceived financial strain on mental well-being. We argue that economic vulnerability restricts workers' agency and propose sense of control as a mediator in the relationship between economic vulnerability and mental well-being-irrespective of the household's financial situation. Multilevel analyses across 19 years based on a sample of N = 7,107 employed adults from the German Socioeconomic Panel (SOEP) demonstrated that a) persons reporting low income and higher financial strain showed lower health and life satisfaction, and b) intra-individual changes in income and financial strain were associated with corresponding changes in mental health and life satisfaction, respectively. These relationships were mediated by sense of control, both on the between-and the within-person level. The findings emphasize the importance of individual income and financial strain for mental well-being, and underline sense of control as an important psychological mechanism explaining individual consequences of economic vulnerability.

Dualized Labor Market and Polarized Health: A Longitudinal Perspective on the Association between Precarious Employment and Mental and Physical Health in Germany

“…These findings are in line with previous studies that found robust differences in health between precarious and nonprecarious employees (Benach et al 2014) and only a weak causal interplay between precarious employment and health within employees (Dawson et al 2015; Green and Heywood 2011; Klug et al 2020; Pförtner and Schmidt-Catran 2017). For example, the study by Pförtner and Schmidt-Catran (2017) shows with data from the GSOEP from 1995 to 2013 that variations in self-rated health are largely explained by differences between working poor employees and non-working poor employees and not by changes in an employed individual’s working poverty status.…”

“…Longitudinal studies, although less common in the literature given their requirements and complexities, are better suited for producing knowledge about cumulative risk over time than cross-sectional observational studies (Ferrie et al 2002; Scott-Marshall and Tompa 2011). Still, most of the extant knowledge about longitudinal associations between precarious employment and subsequent health status is based on differences between precarious and nonprecarious workers rather than intraindividual changes in precarious employment status and health (Dawson et al 2015; Green and Heywood 2011; Klug et al 2020; Pförtner and Schmidt-Catran 2017).…”

“…Occupational health research has identified various health risks associated with precarious employment. Cross-sectional studies have found that multiple dimensions of precarious employment, such as job insecurity (Llosa-Fernández et al 2018;Witte, Pienaar, and Cuyper 2016), nonstandard working time arrangements (Quinlan, Mayhew, and Bohle 2001;Virtanen et al 2005), and working poverty (Klug, Selenko, and Gerlitz 2020;Pförtner and Schmidt-Catran 2017;Topete et al 2018;Zagorsky 1999), have cumulative associations with physical and mental health over time (Vives et al 2010(Vives et al , 2013. Trend studies have shown that differences in health status between various forms of precarious employment have increased over time, such as has been shown in Germany from 1995 to 2015 (Pförtner, Pfaff, and Hower 2019) and in Europe between 2006 and 2014 (Reibling et al 2017).…”

Archival Data Sets Should not be a Secondary (or Even Last) Choice in Micro-Organizational Research

“…(e.g., Debus et al, 2012; Kessler & Gutworth, online first-2022; Naranjo et al, 2021; Okulicz-Kozaryn, 2011; Probst & Jiang, 2017; Shultz, Wang, Crimmins, et al, 2010)• What does the data suggest about the magnitude of an effect, base rate, role of time (within-person time or historical time), or level of analysis at which an effect emerges? (e.g., Klug et al, 2020; Shoss & Kueny, 2022)• How does public policy or other events influence an effect? (e.g., Probst et al, 2020; Sieweke & Santoni, 2020)…”

“…• What does the data suggest about the magnitude of an effect, base rate, role of time (within-person time or historical time), or level of analysis at which an effect emerges? (e.g., Klug et al, 2020; Shoss & Kueny, 2022)…”