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Understanding Exercise Maintenance in Older Cardiac Patients: A Causal Analysis Approach

This study investigates exercise maintenance among older cardiac patients using self-experimentation and causal diaries. Conducted from September 2006 to September 2009 under the National Heart and Blood Institute, it explores the causes and constraints influencing exercise patterns post-rehabilitation. Participants documented their experiences in a 14-day diary, identifying barriers like weather and personal circumstances, while employing statistical methods such as logistic regression and Bayesian networks for analysis. The goal is to tailor solutions for individual exercise challenges, enhancing sustainability in physical activity.

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Understanding Exercise Maintenance in Older Cardiac Patients: A Causal Analysis Approach

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  1. Self Experiments Analysis of Patients’ Causal Diaries

  2. System Change for Exercise Maintenance in Older Cardiac Patients National Heart and Blood Institute 09/1/2006- 09/1/2009 PI: Shirley Moore RN, PhDCo-PI: Farrokh Alemi, PhD

  3. Exercise Causes & Constraints “… I realized how many great reasons I had to skip my workout today. First: rain… Second: low quality sleep after a night spent with my 17-pound cat getting tangled in the blinds. How could anyone exercise after a night like that?” Paige Waehner

  4. Exercise Causes & Constraints “What makes me exercise is that I have to take a shower and the only place I can take a fun shower, with lost of water, is at the gym. My shower at home does not have much water pressure. I have no choice but to go to the gym.” 68 years old woman

  5. Exercise Causes & Constraints “When I bike, I do not exercise. I commute to work. ” 42 year old man

  6. Exercise Causes & Constraints • People have different reasons • One solution does not fit all • People have wrong perceptions • I fail because of my environment • I succeed because of myself

  7. Exercise Causes & Constraints • People have different reasons • One solution does not fit all • People have wrong perceptions • I fail because of my environment • I succeed because of myself We cannot succeed, if we do not know why we have failed

  8. Post-cardiac Exercise Patterns

  9. Health Sustain exercise post rehab Objectives

  10. Health Sustain exercise post rehab Understand causes of & constraints for exercise Objectives

  11. Health Sustain exercise post rehab Understand causes of & constraints for exercise Conduct self experiments: Maintain diary, analyze data, repeat the process. Gain insight. Objectives

  12. Self Experiments • List possible causes/constraints • Trace occurrences • Analyze data • Small data sets of 10-14 data points

  13. Example

  14. Bike to work Shower at gym Sleep early Rain Diary

  15. 14-day Diary

  16. 14-day Diary Too little data for most statistical methods of analysis

  17. Obvious Lessons • No variation in outcomes: • No exercise in the entire 2 weeks • Exercise every day • No variation in causes: • Always present cause • Always absent cause

  18. Causal Analysis • Sequence • Cause precedes exercise • Association • When the cause is present, exercise should be likely • Counter-factual • If the cause is absent, and no other causes are present, exercise should be unlikely

  19. Methods of Analysis • Logistic regression • Bayesian networks • Causal analysis

  20. Method 1: Logistic Regression

  21. Method 2: Bayesian Network • Markov blanket • Use of conditional probabilities • Serial conditional independence • Common cause • Common effect

  22. Method 3: Causal Analysis Conditional 1-Counterfactual

  23. 14-day Diary with No Constraints

  24. Method 3: Causal Analysis

  25. Method 3: Causal Analysis

  26. Method 3: Causal Analysis

  27. Method 3: Causal Analysis

  28. Study Phase I • Which of the methods is most accurate? • Which method is easier to understand? • Which method is easier to use?

  29. Questions & Comments

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