Understanding job satisfaction in the causal attitude network (CAN) model.

Job satisfaction researchers typically assume a tripartite model, suggesting evaluations of the job are explained by latent cognitive and affective factors. However, in the attitudes literature, connectionist theorists view attitudes as emergent structures resulting from the mutually reinforcing causal force of interacting cognitive evaluations. Recently, the causal attitudes network (CAN; Dalege et al., 2016) model was proposed as an integration of both these perspectives with network theory. Here, we describe the CAN model and its implications for understanding job satisfaction. We extend the existing literature by drawing from both attitude and network theory. Using multiple data sets and measures of job satisfaction, we test these ideas empirically. First, drawing on the functional approach to attitudes, we show the instrumental-symbolic distinction in attitude objects is evident in job satisfaction networks. Specifically, networks for more instrumental features (e.g., pay) show stable, high connectivity and form a single cluster, whereas networks regarding symbolic features (e.g., supervisor) increase in connectivity with exposure (i.e., job tenure) and form clusters based on valence and cognitive-affective distinction. We show these distinctions result in "small-world" networks for symbolic features wherein affective reactions are more central than cognitive reactions, consistent with the affective primacy hypothesis. We show the practical advantage of CAN by demonstrating in longitudinal data that items with high centrality are more likely to affect change throughout the attitude network, and that network models are better able to predict future voluntary turnover compared with structural equation models. Implications of this exciting new model for research and practice are discussed. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Cohort differences in the marriage-health relationship for midlife women.

The present study aimed to identify potential cohort differences in midlife women's self-reported functional limitations and chronic diseases. Additionally, we examined the relationship between marital status and health, comparing the health of divorced, widowed, and never married women with married women, and how this relationship differs by cohort. Using data from the Health and Retirement Study (HRS), we examined potential differences in the level of functional limitations and six chronic diseases in two age-matched cohorts of midlife women in the United States: Pre-Baby Boomers, born 1933-1942, N = 4574; and Early Baby Boomers, born 1947-1956, N = 2098. Linear and logistic regressions tested the marital status/health relationship, as well as cohort differences in this relationship, controlling for age, education, race, number of marriages, length of time in marital status, physical activity, and smoking status. We found that Early Baby Boom women had fewer functional limitations but higher risk of chronic disease diagnosis compared to Pre-Baby Boom women. In both cohorts, marriage was associated with lower disease risk and fewer functional limitations; however, never-married Early Baby Boom women had more functional limitations, as well as greater likelihood of lung disease than their Pre-Baby Boom counterparts (OR = 0.28). Results are discussed in terms of the stress model of marriage, and the association between historical context and cohort health (e.g., the influence of economic hardship vs. economic prosperity). Additionally, we discuss cohort differences in selection into marital status, particularly as they pertain to never-married women, and the relative impact of marital dissolution on physical health for the two cohorts of women.