The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Consequences of work-family conflict on employee well-being over time
Abstract
The effects of work-family conflict on the well-being of a diverse sample of 342 non-professional employees from the greater Los Angeles area were examined. Data were collected at two points in time, and a rigorous research design was employed. The effects of self-report bias were considered by controlling for social desirability bias, and by collecting two sources of data (i.e. self-reports and co-workers reports). The results revealed that work-family conflict predicted employee well-being over and above social desirability bias. In addition, analyses were consistent when both self-reports and co-workers reports were utilized. Finally, work-family conflict was a longitudinal predictor of employee's positive well-being. Both cross-sectional and longitudinal analyses were consistent across self-reports and co-worker reports.
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Cites
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Wang, B., Liu, Y., Qian, J., & Parker, S. K. (2021) · Applied Psychology · doi:10.1111/apps.12290 · Cited by 1,722
SPECTOR, P. E., ALLEN, T. D., POELMANS, S. A. Y., LAPIERRE, L. M., COOPER, C. L., MICHAEL, O., SANCHEZ, J. I., ABARCA, N., ALEXANDROVA, M., BEHAM, B., et al. (2007) · Personnel Psychology · doi:10.1111/j.1744-6570.2007.00092.x · Cited by 478
It's not just the amount that counts: Balanced need-satisfaction also affects well-being
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Metadata
- Authors
- Grant-Vallone, E. J., & Donaldson, S. I.
- Venue
- Work & Stress
- Publisher
- Informa UK Limited
- Published
- 2001-07
- Volume
- 15
- Issue
- 3
- Pages
- 214-226
- ISSN
- 0267-8373 (ISSN-L)
- 1464-5335
- OpenAlex
- W2156688916
- Cited by
- 331
- References
- 40
- FWCI
- 10.88
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
