The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Professional Flourishing: The Job Demands–Resources Model and Emergency Nursing
Abstract
Can we craft the perfect job for the next generation of emergency nurses? Ideally, emergency nursing work is engaging, motivating, and meaningful while leading to the nurse’s personal flourishing, wellbeing, optimal health, and performance excellence. Attaining this occupational ideal requires overcoming many contemporary challenges and barriers that emergency nurses face every day. The Job Demands–Resources, or JD–R, model (Figure) is an interdisciplinary theory developed to predict organizational outcomes such as employee well-being, burnout, and work performance. The theory has been tested around the globe for a variety of occupations. In this model, 2 processes occur concurrently, creating a tug-of-war between positive and negative organizational outcomes. On the one hand, job demands, which lead to strain, are the mental and physical requirements that drain employees, increase the risk of health problems, and contribute to worsened work outcomes. On the other hand, job resources are the factors that nurture motivation, leading to improved health and engagement and better work activity. The theory assumes that every occupation or specialty has unique job demands and requires unique resources, which means that the factors leading to an ideal
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“Although the JD-R model is mainly used in quantitative approaches, it has also been utilised for qualitative applications in attempts to explore healthcare workers’ stress more deeply [33, 36, 37].”
From Paramedics’ perceptions of job demands and resources in Finnish emergency medical services: a qualitative study (2022) · cites this paper as [33]
In the citing paper
“The use of Job Demands and Resource model was based on strong validation from within the occupational health literature [32, 33].”
From Paramedics’ perceptions of job demands and resources in Finnish emergency medical services: a qualitative study (2022) · cites this paper as [33]
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Cites
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Shared Governance and Work Engagement in Emergency Nurses
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Cited by
Ericsson, C. R., Lindström, V., Rudman, A., & Nordquist, H. (2022) · BMC Health Services Research · doi:10.1186/s12913-022-08856-9 · Cited by 40
“Although the JD-R model is mainly used in quantitative approaches, it has also been utilised for qualitative applications in attempts to explore healthcare workers’ stress more deeply [33, 36, 37].”
Method
Metadata
- Authors
- Castner, J.
- Corresponding author
- Castner, Jessica
- ORCID
- Castner, Jessica
- Venue
- Journal of Emergency Nursing
- Publisher
- Elsevier BV
- Published
- 2019-11
- Volume
- 45
- Issue
- 6
- Pages
- 607-610
- ISSN
- 0099-1767 (ISSN-L)
- OpenAlex
- W2986256279
- Cited by
- 18
- References
- 29
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 4 · 2023: 4 · 2022: 3 · 2021: 1 · 2020: 1
- FWCI
- 1.75
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- Locations
- Journal of Emergency Nursing (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Job Satisfaction and Organizational Behavior
- Health Sciences › Nursing › Research and Theory › Nursing education and management
- Health Sciences › Nursing › Leadership and Management › Healthcare Education and Workforce Issues
- Keywords
- job demands-resources model, emergency nursing, nurse well-being, burnout, employee performance, work engagement
- MeSH terms
- Burnout, Professional, Humans, Job Satisfaction, Surveys and Questionnaires, Workload, Emergency Nursing
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Data sources
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.
