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• Systems science in Public Health: building capacity, navigating language... with MeSH?
  Laura Sheble
  Published on: 18 March 2016

• Published on: 18 March 2016

  Systems science in Public Health: building capacity, navigating language... with MeSH?

  • Laura Sheble, Postdoctoral Associate
  • Other Contributors:
    • Kristen Hassmiller Lich, Leah Frerichs, Gaurav Dave, Giselle Corbie-Smith: University of North Carolina at Chapel Hill, USA

  We agree with Carey et al.(1) that systems science methods are an important addition to the methodological and conceptual toolbox used to approach complex public health problems and risk factors.(2) In order to realize the full potential of these methods, it is necessary to review and critique the state of the science regarding systems science applications in the public health research context, both calling out successes...

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  We agree with Carey et al.(1) that systems science methods are an important addition to the methodological and conceptual toolbox used to approach complex public health problems and risk factors.(2) In order to realize the full potential of these methods, it is necessary to review and critique the state of the science regarding systems science applications in the public health research context, both calling out successes and learning from failures or shortcomings. However, for such efforts to have the greatest impact, they must be done carefully and represent the body of work studied. This is difficult when language used to describe relevant methods is inconsistent, as is true of many approaches being re-imagined or emerging, including systems science.

  A recent interpretive systematic review of systems thinking and systems science by Carey et al.(1) focused on a subset of public health literature (i.e. obesity, tobacco, alcohol, and social determinants of health). Through inductive qualitative analysis, the authors described and analyzed papers and highlighted the need to expand the capability of public health researchers to engage with the full range of systems science methodologies. We welcome the contribution of Carey et al. and believe the findings, in combination with other reviews and critiques of systems science methods in public health, will enable public health researchers to better integrate systems science methods with existing methodological tools and connect them to pressing public health challenges. Unfortunately, limitations of the study itself highlight critical gaps and capacity-building needs to advance the use of systems science in public health.

  A key limitation of Carey et al.'s review is a mismatch between the broad conceptual definition of systems thinking and science articulated and the much narrower operational definition used to conduct the review. The authors note that their methods were not positioned to conduct an exhaustive review, but claim their identified articles are likely representative of systems science publications in the field. Unfortunately, we believe the mismatch between what they describe broadly as their focus of the review and their operationalization of "systems science" provides a potentially limited representation that has important implications for continued development and integration of systems science methods in public health.

  Carey et al.'s operational definition, as indicated by the search query presented, underspecifies systems science methods. System dynamics, agent-based modeling (ABM), and network analysis are often identified as three prevalent systems science methods in public health research.(3) The search terms used to identify publications included the first of these methods, system dynamics, but not ABM or network analysis. This likely overestimates the proportion of systems science studies that apply system dynamics and underestimates the proportion of studies that use other methods. While several instances of these unnamed methods were identified, likely through the broader terms included in the search (e.g. 'systems science'), a more robust search is likely to have captured many more studies using these methods. This oversight is especially troubling given that ABM and network analysis studies qualified for inclusion in the study, but high profile (e.g. a manuscript by Christakis and Fowler assessing the social contagion of obesity through social networks (4)) and relevant studies (e.g. a manuscript by Orr using ABM to study racial disparities in obesity (5)) were not identified and included in the review.

  Complicating matters further, a more inclusive review might explicitly name a variety of other systems science methods, including soft systems methodology, critical systems heuristics, community based operations research, and discrete event simulation. (6,7,8) In our experience searching this literature, calls for understanding problems as shaped by systems often include the broader systems terms used in Carey et al.'s search, but applications of specific and relevant systems science methods are less likely to do so as their focus is more on describing the application and implications of the research.

  The reliance by Carey et al. on more general search terms (e.g. 'systems science', 'systems thinking', 'complex systems') without also including specific methodological names ('agent-based modeling', 'network analysis', 'community-based operations research') may have led to the high proportion (more than half) of more general introductory, expository, commentary-type publications included in the review. Therefore, the proportion of papers that engage in the rhetoric of systems science is likely over-stated and we believe there is a greater proportion of applications of systems methods than suggested by the review.

  Nonetheless, the large number of position papers is an important observation and we agree that public health has yet to take full advantage of systems science. Future studies are needed to examine the role of rhetoric in the public health research system and, for example, how these types of articles contribute to whether, to what extent, and in what contexts ideas such as systems thinking diffuse in public health. It is likely that discussion of methods new to a research field raises awareness, and possibly serves other functions (9). For example, discussion might influence selection, reformulation, and adaptation of methods from other fields.

  We commend the effort of Carey et al. to examine the state of systems science research in public health and agree with the authors that the review highlights important questions and future research directions. However, we caution that the findings in the recent systematic review likely present an unrepresentative view of the methods that comprise a systems science approach, important constituent approaches, and the relative prevalence of various approaches in the field. We encourage interested readers to search more extensively to find research and discussions of systems science methods. This is a difficult task, in part because of the diversity and evolution of terms and phrases authors use when writing about systems science. This situation could be remedied to an extent if terms indicating frequently used or emerging systems science methods were added to MeSH, as has been done for other methods such as clinical trials, meta-analysis, and community based participatory research. We also encourage practitioners of systems science methods to identify as such. This does not always happen, as emerging methods often need to be placed as more similar to commonly accepted scientific approaches, which are more likely to be deemed publishable. These changes may mitigate concerns that future reviews misrepresent the state of the science, and improve the ability of readers to access studies on the broad range of systems science applications in public health as language around systems science matures and new methods are developed.

  References:

  1. Carey G, Malbon E, Carey N, et al. Systems science and systems thinking for public health: a systematic review of the field. BMJ Open, 2015;5:e009002.

  2. Lich KH, Ginexi EM, Osgood ND, et al. A call to address complexity in prevention science research. Prev Sci, 2013;14:279-89.

  3. Luke DA, Stamatakis KA. Systems science methods in public health: Dynamics, networks, and agents. Annu Rev Public Health, 2012;33:357-76.

  4. Christakis N, Fowler J. The spread of obesity in a large social network over 32 years. N Engl J Med 2007;357(4):370-9.

  5. Orr MG, et al. Reducing racial disparities in obesity: simulating the effects of improved education and social network influence on diet behavior. Ann Epidemiol, 2014;24(8):563-9.

  6. Williams B, Imam I. Systems concepts in evaluation: An expert anthology. EdgePress, 2007

  7. Frerichs LF, Lich KH, Dave G, Corbie-Smith G. Integrating systems science and community-based participatory research to achieve health equity. Am J Public Health, 2016;106: 215-222.

  8. Speybroeck N, van Malderen C, Harper S, et al. Simulation models for socioeconomic inequalities in health: a systematic review. Int J Environ Res Public Health, 2013; 10(11):5750-80.

  9. Hyland, K. Disciplinary discourses: Social interactions in academic writing. Univ of Michigan Press, 2004

  Conflict of Interest:

  None declared

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  Conflict of Interest:
  None declared.

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