Quantifying the qualitative: exploring epistemic network analysis as a method to study work system interactions Article Swipe
Dustin T. Weiler
,
A. J. Lingg
,
Brendan Eagan
,
David Williamson Shaffer
,
Nicole E. Werner
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1080/00140139.2022.2051609
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1080/00140139.2022.2051609
Studying interactions faces methodological challenges and existing methods, such as configural diagramming, have limitations. This work demonstrates Epistemic Network Analysis (ENA) as an analytical method to construct configural diagrams. We demonstrated ENA as an analytical tool by applying this method to study dementia caregiver work systems. We conducted 20 semi-structured interviews with caregivers to collect caregiving experiences. Guided by the Patient Work System model, we conducted a directed content analysis to identify work system components and used ENA to study interactions between components. By using ENA to create configural diagrams, we identified five frequently occurring interactions, compared work system configurations of caregivers providing care at home and away from home. Although we were underpowered to determine statistically significant differences, we identified visual and qualitative differences. Our results demonstrate the capability of ENA as an analytical method for studying work system interactions through configural diagramming. Practitioner summary: A new methodology, Epistemic Network Analysis (ENA), was presented to better support the study of work system interactions through configural diagramming. ENA was applied to qualitative data to demonstrate the capabilities of this method to construct configural diagrams of the work system. This study successfully demonstrated that ENA can visually represent and describe work system configurations.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1080/00140139.2022.2051609
- OA Status
- green
- Cited By
- 11
- References
- 63
- Related Works
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4221072101Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1080/00140139.2022.2051609Digital Object Identifier
- Title
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Quantifying the qualitative: exploring epistemic network analysis as a method to study work system interactionsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-03-08Full publication date if available
- Authors
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Dustin T. Weiler, A. J. Lingg, Brendan Eagan, David Williamson Shaffer, Nicole E. WernerList of authors in order
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https://doi.org/10.1080/00140139.2022.2051609Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://www.ncbi.nlm.nih.gov/pmc/articles/9489604Direct OA link when available
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Construct (python library), Work (physics), Qualitative research, Computer science, Qualitative analysis, Psychology, Data science, Engineering, Sociology, Programming language, Social science, Mechanical engineeringTop concepts (fields/topics) attached by OpenAlex
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11Total citation count in OpenAlex
- Citations by year (recent)
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2025: 4, 2024: 2, 2023: 5Per-year citation counts (last 5 years)
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63Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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