Understanding social forces involved in diabetes outcomes: a systems science approach to quality-of-life research.
OBJECTIVE
The field of quality-of-life (QOL) research would benefit from learning about and integrating systems science approaches that model how social forces interact dynamically with health and affect the course of chronic illnesses. Our purpose is to describe the systems science mindset and to illustrate the utility of a system dynamics approach to promoting QOL research in chronic disease, using diabetes as an example.


METHODS
We build a series of causal loop diagrams incrementally, introducing new variables and their dynamic relationships at each stage.


RESULTS
These causal loop diagrams demonstrate how a common set of relationships among these variables can generate different disease and QOL trajectories for people with diabetes and also lead to a consideration of non-clinical (psychosocial and behavioral) factors that can have implications for program design and policy formulation.


CONCLUSIONS
The policy implications of the causal loop diagrams are discussed, and empirical next steps to validate the diagrams and quantify the relationships are described.
Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.
David W
DW
Lounsbury
Gary B
GB
Hirsch
Chawntel
C
Vega
Carolyn E
CE
Schwartz
D000223:Adaptation, Psychological; D003920:Diabetes Mellitus / Q000523:psychology* / Q000628:therapy; D007722:Health Knowledge, Attitudes, Practice; D006291:Health Policy; D006297:Health Services Accessibility; D054625:Healthcare Disparities; D006801:Humans; D007398:Interpersonal Relations; D008019:Life Style; D017063:Outcome Assessment, Health Care / Q000379:methods* / Q000592:standards; D011788:Quality of Life; D012307:Risk Factors; D013598:Systems Theory; D009626:Terminology as Topic