The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.
A meta-analytic examination of hardiness.
Abstract
Hardiness, which is a multidimensional personality trait that is hypothesized to protect people from the effects of stress, has attracted considerable research attention during the last 30 years. The current study provides a meta-analytic review of hardiness. Specifically, we examined the relation-ships between the hardiness facets, the relationship between hardiness and other personality variables, as well as the relationships between hardiness and several hypothesized criteria, including stressors, strains, social support, coping, and performance. Our analyses generally suggest that hardiness is: (a) positively related to other personality traits that are expected to protect people from stress, (b) negatively related to personality traits that are expected to exacerbate the effects of stress, (c) negatively related to stressors, strains, and regressive coping, and (d) positively related to social support, active coping, and performance. Regression analyses suggest that hardiness is significantly related to important criteria after the effects of other person-ality traits (e.g., the Five Factor Model traits) are controlled.
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Psychological interventions to foster resilience in healthcare professionals
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A Meta-Analytic Review of Social Identification and Health in Organizational Contexts
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Resilience Factors Among Police Investigators: Hardiness-commitment a Unique Contributor
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Metadata
- Authors
- Eschleman, K. J., Bowling, N. A., & Alarcon, G. M.
- Venue
- International Journal of Stress Management
- Published
- 2010-11
- Volume
- 17
- Issue
- 4
- Pages
- 277-307
- ISSN
- 1072-5245 (ISSN-L)
- 1573-3424
- OpenAlex
- W2067687575
- Cited by
- 300
- References
- 59
- FWCI
- 9.83
- 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.