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Anxiety, Demoralization, and the Gender Difference in Job Satisfaction

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Abstract

The tendency for women in Canada and the United States to report being more satisfied than men with their jobs is considered paradoxical because women, on average, receive fewer job-related resources than men. Theory and research suggest that the magnitude of the gender difference that underlies that paradox may increase as levels of negative affect increase. Using data from people living and working in Toronto, Canada, this study evaluates hypotheses about the joint association of gender and two forms of negative affect, anxiety and demoralization, with job satisfaction. Data collected in telephone interviews are analyzed using ordinal probit regression. As job satisfaction decreases with increasing negative affect, the size of the gender difference in job satisfaction increases. When job characteristics indicative of job quality are controlled, the interaction between gender and demoralization is reduced to a non-significant level, but the interaction between gender and anxiety changes little, and remains significant. The results are interpreted as indicating that as negative affect increases, women are more likely to reference standards that counterbalance decreases in their satisfaction (e.g., standards linked to “communion” with co-workers), and men are more likely to reference standards that further decrease their satisfaction (e.g., standards linked to relative advantage). The persistence of the interaction between gender and anxiety after job characteristics are controlled suggests that anxiety-provoking experiences outside of the workplace may contribute to the gender difference in job satisfaction. The associations among quality of work, demoralization, and job satisfaction are stronger among men than women, explaining the interaction of gender with demoralization.

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Acknowledgments

Data collection was funded by a grant from the Social Sciences and Humanities Research Council of Canada. I wish to thank the editor, Dr. Frieze, and the two anonymous reviewers for extensive feedback and suggestions that substantially improved the paper. Thanks also to Lesley Kenny and Sherri Klassen for editorial assistance.

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Appendix A: Evaluating the Hypothesis that a Two-Factor Model Specifying Correlated Latent Factors for Global Anxiety and Global Demoralization will Fit Better Than a Single Factor Model

Appendix A: Evaluating the Hypothesis that a Two-Factor Model Specifying Correlated Latent Factors for Global Anxiety and Global Demoralization will Fit Better Than a Single Factor Model

Studies have found anxiety and depressive moods to constitute the negative poles of distinct dimensions of global affect (Tellegen, Watson, & Clark, 1999). The ability to empirically differentiate between these two dimensions depends on the measures of each. In order to determine if the two dimensions can be differentiated in the current data a confirmatory factor analyses (CFA) is conducted. The correlations analyzed in this analysis are presented in Table 4, along with correlations with measures of job-related affect. Kendall’s Tau-b coefficients (Kendall & Gibbons, 1990) are presented since response scales are ordinal and skewed. Empirical distinguishability of work-related affect from global affect has been demonstrated in a previous report using these data (Magee and St-Arnaud 2012).

The fit of two CFA models are compared in Table 5. One model specifies a single latent factor for global negative affect, indicated by responses to all five of the global affect items. The other model specifies two latent factors with separate indicators of global demoralization (two-indicators) and global stress/anxiety (three indicators). Both analyses specify that loadings of indicators on latent factors are gender invariant. However, the correlation between the two latent factors in the two-factor model is free to vary by gender. Estimates are obtained from the asymptotic distribution-free (ADF) estimator in Stata 12 (StataCorp 2011). That estimator does not require that joint normality or the assumption of symmetry in item distributions.

By all fit criteria, the two-factor model fits the data well, and the single factor model does not fit the data at all. In addition, score-tests from the two-factor model indicate that there would be no gain from estimating models with different loadings for men and women (i.e., all tests are non-significant). Studies that have more extensively assessed anxiety, though, suggest that men and women may experience different symptoms of anxiety (de Visser, et al. 2010).

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Magee, W. Anxiety, Demoralization, and the Gender Difference in Job Satisfaction. Sex Roles 69, 308–322 (2013). https://doi.org/10.1007/s11199-013-0297-9

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