Value of social network analysis for developing and evaluating complex healthcare interventions: a scoping review
Open accessAbstract
Objectives: Most complex healthcare interventions target a network of healthcare professionals. Social network analysis (SNA) is a powerful technique to study how social relationships within a network are established and evolve. We identified in which phases of complex healthcare intervention research SNA is used and the value of SNA for developing and evaluating complex healthcare interventions. Methods: A scoping review was conducted using the Arksey and O’Malley methodological framework. We included complex healthcare intervention studies using SNA to identify the study characteristics, level of complexity of the healthcare interventions, reported strengths and limitations, and reported implications of SNA. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews 2018 was used to guide the reporting. Results: Among 2466 identified studies, 40 studies were selected for analysis. At first, the results showed that SNA seems underused in evaluating complex intervention research. Second, SNA was not used in the development phase of the included studies. Third, the reported implications in the evaluation and implementation phase reflect the value of SNA in addressing the implementation and population complexity. Fourth, pathway complexity and contextual complexity of the included interventions were unclear or unable to access. Fifth, the use of a mixed methods approach was reported as a strength, as the combination and integration of a quantitative and qualitative method clearly establishes the results. Conclusion: SNA is a widely applicable method that can be used in different phases of complex intervention research. SNA can be of value to disentangle and address the level of complexity of complex healthcare interventions. Furthermore, the routine use of SNA within a mixed method approach could yield actionable insights that would be useful in the transactional context of complex interventions.
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ML and AI techniques, such as social network analysis and agent-based modeling, can model the complex interactions between individuals and their social environments to identify key leverage points for interventions that promote health and well-being across communities.
“ML and AI techniques, such as social network analysis and agent-based modeling, can model the complex interactions between individuals and their social environments to identify key leverage points for interventions that promote health and well-being across communities [40, 47].”
From Integrating machine learning and artificial intelligence in life-course epidemiology: pathways to innovative public health solutions (2024) · cites this paper as [47]
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- Authors
- Smit, L. C., Dikken, J., Schuurmans, M. J., de Wit, N. J., & Bleijenberg, N.
- Affiliations
- University of Applied Sciences Utrecht (NL)
- The Hague University of Applied Sciences (NL)
- University Medical Center Utrecht (NL)
- Department of General Practice, Division Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- Corresponding author
- Smit, Linda C
- Venue
- BMJ Open
- Publisher
- BMJ
- Published
- 2020-11
- Volume
- 10
- Issue
- 11
- Pages
- e039681
- ISSN
- 2044-6055 (ISSN-L)
- PMC
- PMC7674094
- OpenAlex
- W3102020374
- Cited by
- 42
- References
- 70
- Citations by year
- 2026: 5 · 2025: 10 · 2024: 13 · 2023: 8 · 2022: 2 · 2021: 4
- FWCI
- 0.67
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMJ Open (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- HighWire Press Open Archive (submittedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
- Social Sciences › Decision Sciences › Management Science and Operations Research › Evaluation and Performance Assessment
- Social Sciences › Decision Sciences › Information Systems and Management › Interdisciplinary Research and Collaboration
- Keywords
- social network analysis, intervention development, intervention evaluation, implementation complexity, contextual complexity, mixed methods
- MeSH terms
- Social Network Analysis, Delivery of Health Care, Health Facilities, Health Personnel, Health Services, Humans
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