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System dynamics modeling for cancer prevention and control: A systematic review
Erin S Kenzie1,2,3, Mellodie Seater3, Wayne Wakeland2
1OHSU-PSU School of Public Health, Oregon Health & Science University, Portland, Oregon, United States of America.
Plos One
|December 1, 2023
Summary
System dynamics modeling aids cancer control by illustrating complex interactions. However, studies often lack rigor and transparency in model development and testing, indicating a need for improved best practices.
Area of Science:
- Public Health
- Computational Biology
- Health Systems Research
Background:
- Cancer prevention and control involve complex, multilevel factors.
- System dynamics modeling (SDM) offers tools for understanding and managing this complexity.
- The scope, characteristics, and quality of SDM applications in cancer research are not well-documented.
Approach:
- A systematic literature search was conducted across major databases (PubMed, Scopus, APA PsycInfo) and journals.
- Included studies using SDM for cancer-related topics underwent dual review and quality assessment.
- Study characteristics and model details were abstracted and synthesized.
Key Points:
- 32 studies met the inclusion criteria, utilizing both diagramming and simulation approaches.
- Topics included chemotherapy, tobacco/e-cigarette use reduction, and environmental cancer risk.
- Models covered all cancer control continuum areas, with treatment, prevention, and detection being most frequent.
- Overall study quality was low, especially for simulation-based studies, with significant room for improvement in participant involvement, model development transparency, and validation.
Conclusions:
- System dynamics modeling is a valuable tool for visualizing cancer control complexities and identifying interventions.
- Current applications are limited by insufficient rigor and transparency in model development and validation.
- Enhanced infrastructure and best practices are needed to advance SDM in multidisciplinary cancer research.
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