The purpose of this study is to examine lay individuals’ gaps in understanding and misconceptions surrounding hypertension for more fundamental issues with reasoning about complexity. We coded for issues with complexity thinking in 100 posts from the online hypertension discussion forums, Ehealth.com and BPlog.com. Complementing the findings on novice and expert reasoning in the learning sciences literature, we identified four major issues with complexity thinking: Oversimplification of contributing factors, simple linear thinking, static reasoning, and discrete boundary thinking. We conclude with practical implications for these findings and suggestions for future research.
Get full access to this article
View all access options for this article.
References
1.
BlumenhagenD. (1980). Hyper-tension: A folk illness with a medical name. Culture,Medicine, and Psychiatry, 4, 197–227.
2.
BlumenhagenD. (1982). The meaning of hypertension. In ChrismanN.J.MaretskiT.W. (Eds.), Clinically applied anthropology. Dordrecht, Holland: D. Reidel.
3.
ChiM.T.FeltovichP.J.GlaserR. (1981). Categorization and representation of physics problems by experts and novices. Cognitive science, 5, 121–152.
4.
CilliersP. (1998). Complexity and postmodernism: Understanding complex systems. Routledge: London.
5.
diSessaA. (1993). Towards an epistemology of physics. Cognition and Instruction, 10, 105–225.
6.
DriverR.GuesneE.TiberghienA. (1985). Children’s ideas in science. Milton Keynes, England: Open University Press.
7.
FeltovichP.J.CoulsonR.L.SpiroR.J. (2001). Learners’ (mis)understanding of important and difficult concepts. In ForbusK. D.FeltovichP.J. (Eds.), Smart machines in education: The coming revolution in educational technology (pp. 349–375). Menlo Park, CA: AAAI/MIT Press.
8.
FeltovichP.J.SpiroR.J.CoulsonR.L. (1989). The nature of conceptual understanding in biomedicine: The deep structure of complex ideas and the development of misconceptions. In EvansD.PatelV. (Eds.), Cognitive science in medicine: Biomedical modeling. Cambridge, MA: MIT (Bradford) Press.
9.
FeltovichP.J.SpiroR.J.CoulsonR.L. (1993). Learning, teaching, and testing for complex conceptual understanding. In FrederiksenN.MislevyR.BejarI. (Eds.), Test theory for a new generation of tests. Hillsdale, NJ: Lawrence Erlbaum Associates.
10.
GaliliI.HazanA. (2000). Learners’ knowledge in optics: Interpretation, structure and analysis. International Journal of Science Education, 22, 57–88.
11.
GarroL. C. (1988). Explaining high blood pressure: Variation in knowledge about illness. American Ethnologist, 15, 98–119.
12.
Godoy-IzquierdoD.López-ChicheriI.López-TorrecillasF.VélezM.GodoyJ.F. (2007). Contents of lay illness models dimensions for physical and mental diseases and implications for health professionals. Patient Education and Counseling, 67, 196–213.
13.
GreenoJ.G. (1983). Forms of understanding in mathematical problem solving. In ParisS.G.OlsonG.M.StevensonH.W. (Eds.), Learning and motivation in the classroom (83111). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.
14.
GuytonA.C.ColemanT.G.CowleyA.W.ManningR.D.NormanR.A.FergusonJ.D. (1974). Brief reviews: A systems analysis approach to understanding long-range arterial blood pressure control and hypertension. Circulation Research, 35, 159–176.
LeventhalH.BrelandJ. Y.MoraP. A.LeventhalE. A. (2010). Lay representations of illness and treatment: A framework for action. Handbook of Behavioral Medicine: Methods and Applications, 3, 137–155.
MeyerD.LeventhalH.GuttmanM. (1985). Commonsense models of illness: The example of hypertension. Health Psychology, 4, 115–135.
20.
PerkinsD.N.GrotzerT.A. (2000). Models and moves: Focusing on dimensions of causal complexity to achieve deeper scientific understanding. Paper presented at the Annual Meeting of the American Educational Research Association, New Orleans, LA.
21.
ResnickM.WilenskyU. (1998). Diving into complexity: Developing probabilistic decentralized thinking through role-playing activities. The Journal of the Learning Sciences, 7, 153–172.
22.
SpencerJ.PhillipsE.OgedegbeG. (2005). Knowledge, attitudes, beliefs, and blood pressure control in a community-based sample in Ghana. Ethnicity and Disease, 15, 748–752.
23.
ZhangJ.ScardamaliaM.ReeveR.MessinaR. (2009). Designs for collective cognitive responsibility in knowledge building communities. Journal of the Learning Sciences, 18, 7–44.
