The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Antecedents to Retention and Turnover among Child Welfare, Social Work, and Other Human Service Employees: What Can We Learn from Past Research? A Review and Metanalysis
Abstract
This study involves a metanalysis of 25 articles concerning the relationship between demographic variables, personal perceptions, and organizational conditions and either turnover or intention to leave. It finds that burnout, job dissatisfaction, availability of employment alternatives, low organizational and professional commitment, stress, and lack of social support are the strongest predictors of turnover or intention to leave. Since the major predictors of leaving are not personal or related to the balance between work and family but are organizational or job‐based, there might be a great deal that both managers and policy makers can do to prevent turnover.
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Citations
Cites
Generalized expectancies for internal versus external control of reinforcement.
Rotter, J. B. (1966) · Psychological Monographs: General and Applied · doi:10.1037/h0092976 · Cited by 21,937
Methods of Meta-Analysis: Correcting Error and Bias in Research Findings
Schmidt, F. L., & Hunter, J. E. (2015) · doi:10.4135/9781483398105 · Cited by 5,542
JOB SEARCH BEHAVIOR OF EMPLOYED MANAGERS
BRETZ, R. D., BOUDREAU, J. W., & JUDGE, T. A. (1994) · Personnel Psychology · doi:10.1111/j.1744-6570.1994.tb01725.x · Cited by 297
Occupational stress management programmes: a practical overview of published effect studies
van der Hek, H., & Plomp, H. N. (1997) · Occupational Medicine · doi:10.1093/occmed/47.3.133 · Cited by 169 · cited 1×
“Examples of work-site interventions that have been shown to decrease burnout and increase job satisfaction include stress management training, allowing for greater job autonomy, and providing additional instrumental and social support (Bellarosa and Chen 1997; van der Hek and Plomp 1997).”
Background
Cited by
McFadden, P., Campbell, A., & Taylor, B. (2015) · British Journal of Social Work · doi:10.1093/bjsw/bct210 · Cited by 499
Chinese teachers’ work stress and their turnover intention.
Liu, S., & Onwuegbuzie, A. J. (2012) · International Journal of Educational Research · doi:10.1016/j.ijer.2012.03.006 · Cited by 350
Systematic Review of Mindfulness Practice for Reducing Job Burnout
Luken, M., & Sammons, A. (2016) · American Journal of Occupational Therapy · doi:10.5014/ajot.2016.016956 · Cited by 250
Burnout and Physical Health among Social Workers: A Three-Year Longitudinal Study
Kim, H., Ji, J., & Kao, D. (2011) · Social Work · doi:10.1093/sw/56.3.258 · Cited by 229
The Role of Staff Turnover in the Implementation of Evidence-Based Practices in Mental Health Care
Woltmann, E. M., Whitley, R., McHugo, G. J., Brunette, M., Torrey, W. C., Coots, L., Lynde, D., & Drake, R. E. (2008) · Psychiatric Services · doi:10.1176/ps.2008.59.7.732 · Cited by 246
Metadata
- Authors
- Mor Barak, M. E., Nissly, J. A., & Levin, A.
- Venue
- Social Service Review
- Publisher
- University of Chicago Press
- Published
- 2001-12
- Volume
- 75
- Issue
- 4
- Pages
- 625-661
- ISSN
- 0037-7961 (ISSN-L)
- 1537-5404
- OpenAlex
- W1970427447
- Cited by
- 1,005
- References
- 4
- FWCI
- 18.03
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Antecedents to Retention and Turnover among Child Welfare, Social Work, and Other Human Service Employees: What Can We Learn from Past Research? A Review and Metanalysis. https://app.cochat.ai/papers/10.1086/323166
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- Mor Barak, M. E., Nissly, J. A., & Levin, A. (2001). Antecedents to Retention and Turnover among Child Welfare, Social Work, and Other Human Service Employees: What Can We Learn from Past Research? A Review and Metanalysis. Social Service Review. https://doi.org/10.1086/323166
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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.
