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Goodson Chapter 7 Resnicow & Page, 2008 Krieger, 1994 PowerPoint Presentation
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Goodson Chapter 7 Resnicow & Page, 2008 Krieger, 1994

Goodson Chapter 7 Resnicow & Page, 2008 Krieger, 1994

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Goodson Chapter 7 Resnicow & Page, 2008 Krieger, 1994

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  1. Goodson Chapter 7 • Resnicow& Page, 2008 • Krieger, 1994

  2. Pattern 3: Deliberate Privileging of Linearity: The Whole or the Sum of the Parts? Goodson, P. (2010). Theory in Health Promotion Research and Practice. Mississauga, Ontario: Jones and Bartlett Publishers.

  3. Limitations of Linear Theories • Focus on the individual • Focus on cognitive factors • “the whole is equal to the sum of its parts” “this orderly, linear framework remains the mainstream foundation of the human and social sciences to this day.” (Cooper & Geyer, 2008)

  4. Complexity Theories • Offer a non-linear way to explain unpredictability, complexity, and dynamic aspects of behavior • “Complex Adaptive Systems (CASs) consist of a set of interacting elements that are able to change and adapt in multiple ways (Zimmerman, Lindberg, & Plsek, 1998).”

  5. Complexity Theories • Whole is more than the sum of its parts • CASs comprise other CASs • Agents within CASs evolve • Sustainability depends on diversity • Decentralized, or “distributed” control • Size of output does not necessarily correspond to size of input • Dependence on original conditions (“Butterfly Effect”) • CASs drawn to attractors • Unpredictable behavior • Order to the chaos

  6. What are Attractors?

  7. Examples • School district • Puzzle • Others? Challenges in practice: Allowing a system to self-organize? Recognizing how behavior itself influences the system?

  8. Goodson Chapter 7 • Empirical evidence • Statistical implications • Cautions

  9. Embracing Chaos and Complexity: A Quantum Change for Public Health Resnicow, K. and Page, S.E. (2008). American Journal of Public Health, Vol 98, No. 8, pp. 1382-1389.

  10. Resnicow & Page, 2008 • Propose that the linear paradigm is flawed • Key Principles: • Quantum behavior change • Chaotic process, sensitive to initial conditions • Occurs within CASs

  11. Quantum Change • Wave/particle • Dramatic experience OR • Sudden insight (Miller) • Can occur with little input

  12. Initial Conditions • Butterfly Effect • Infinite permutations • Fractal patterns • Identification of fractals suggests intervention points

  13. Change as a CAS • “particle components of a motivational quantum” = different starting points • Multiple pathways • “lever points” or “tipping points”

  14. Implications for Public Health • Identification of leverage points • Consideration of timing and initial conditions • View behavior as probabilistic • Encourage “wing flapping”?

  15. Resnicow & Page, 2008 • Empirical evidence • Statistical implications

  16. Unify Linear and Complex?

  17. Resnicow & Page, 2008 • Practical implications • Repeated exposures • Understand individual “receptivity” (sounds familiar) • Lower upper limit on variance explained

  18. Resnicow & Page, 2008 • Potential areas of research • Qualitative methods • Quantitative methods • Physiological mechanism studies • Agent-based and computational modeling

  19. Epidemiology and the web of causation: Has anyone seen the spider? Krieger, N. (1994). Soc. Sci. Med. Vol. 39, No. 7, pp. 887-903

  20. Epidemiologic Theory • Web of Causation and multivariate analyses • “paucity of critical reflection” • Insufficient preparation of new epidemiologists

  21. MacMahon, Pugh, Ibsen (1960) as a challenge to “chain of causation” Web of Causation

  22. Web of Causation • Increased understanding of interaction and confounding • Rothman

  23. Problems with Web • Omitted discussion of origins • Lacks discussion of theory for the model • Focus on proximal factors • Does not distinguish between individuals and populations • “biomedical individualism”

  24. Modern Contributions • “environment” ill-defined (Vanderbroucke) • Resurgence of single agent theory • McKeown’s etiologic groups • Social determinants • Conclusion: Epi still lacking an ecosocial theory

  25. Ecosocial Framework • How to use epidemiological data • Greater precision in etiology • Better definitions of “lifestyle” • Challenge to current definition of “environment” • Challenge to rigid distinctions of individual and group level analyses