| Literature DB >> 25296091 |
Kamila Wojdylo1, Nicola Baumann2, Lis Fischbach2, Stefan Engeser2.
Abstract
OBJECTIVE: According to the theory of work craving, a workaholic has a craving for self-worth compensatory incentives and an expectation of relief from negative affect experienced through neurotic perfectionism and an obsessive-compulsive style of working. Research has shown that workaholism and work engagement should be considered as two distinct work styles with different health consequences. However, the mechanisms underlying the adoption of these work styles have been neglected. The present study proposes that work craving and work engagement are differentially associated with self-regulatory competencies and health. In particular, we expected that the working styles mediate the relationships between emotional self-regulation and health.Entities:
Mesh:
Year: 2014 PMID: 25296091 PMCID: PMC4189784 DOI: 10.1371/journal.pone.0106379
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Descriptives and Bivariate Correlations (Pearson) Between Study Variables (N = 469).
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| Scale | Range | (2) | (3) | (4) | (5) | (6) | (7) | Gender a | |
| (1) Action Orientation (AOF) | 5.96 | 3.46 | 0 – 12 | 0 – 12 | .52*** | .24*** | −.53*** | .50*** | .08 | .05 | .22*** |
| (2) Action Orientation (AOD) | 7.54 | 3.66 | 0 – 12 | 0 – 12 | .34*** | −.31*** | .41*** | .03 | .03 | .09 | |
| (3) Work Engagement (UWES) | 5.64 | 0.84 | 1 – 7 | 2.2 – 7.0 | .02 | .32*** | .08 | .02 | −.12 | ||
| (4) Work Craving (WCS) | 2.78 | 1.09 | 1 – 7 | 1.0 – 6.4 | −.48*** | .10 | −.12 | −.08 | |||
| (5) General Health (GHQ) | 3.12 | 0.45 | 1 – 4 | 1.0 – 3.9 | −.06 | .08 | .07 | ||||
| (6) Working Hours b | 7.68 | 2.36 | 0 – 24 | 1.0 – 15 | .00 | .15** | |||||
| (7) Age c | 44.94 | 10.57 | 21 – 64 | .19*** |
Note. afemale = 1; male = 2. b N = 436. c N = 459.
* p <.05 ** p <.01 *** p <.001.
Figure 1Regression coefficients of two path models tested through structural equation modeling.
Indirect path coefficients are in parentheses. The residual variance components (error variances) indicate the amount of unexplained variance. For each observed variable, R2 = (1 - error variance). * p <.05 *** p <.001.