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Leveraging Technology to Change Behavior: Measurement is a Necessary but Not Sufficient Condition William Riley, Ph.D. Chief, Science of Research and Technology.

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Presentation on theme: "Leveraging Technology to Change Behavior: Measurement is a Necessary but Not Sufficient Condition William Riley, Ph.D. Chief, Science of Research and Technology."— Presentation transcript:

1 Leveraging Technology to Change Behavior: Measurement is a Necessary but Not Sufficient Condition William Riley, Ph.D. Chief, Science of Research and Technology Branch Division of Cancer Control and Population Science National Cancer Institute

2 "Nearly all the grandest discoveries of science have been but the rewards of accurate measurement." Lord Kelvin, 1872

3 Previous State of Behavioral Measurement

4 Technological Advances in Behavioral Measurement Item Response Theory (IRT) and Computer Adaptive Testing (CAT) Ecological Momentary Assessment (EMA) Passive Sensor Technologies

5 Leverage Better Measurement for Modeling Behavior Barrientos, Rivera, and Collins (2010). A dynamical model for describing behavioral interventions for weight loss and body composition change. Mathematical and Computer Modeling of Dynamical Systems.

6 Leveraging Better Measurement for Behavioral Interventions Measurement alone does not improve health Behavior change is the core of nearly every tech-delivered health intervention To improve health, we must leverage technology not only to measure behavior, but to change behavior

7 Rely on Health Professionals to Close the Loop Inputs UserIntegration & Analytics Health Professional

8 Weaknesses of the Health Professional Closing the Loop Drinking through a firehose Data = Liability Set alert parameters Optimize healthcare interface Univ. of Maryland Human Computer Interface Lab

9 Weaknesses of the Health Professional Closing the Loop Assumes healthcare professional will intervene appropriately Cabana, et al. JAMA 1999;282:1458-1465

10 Prompting Inputs UserIntegration & Analytics Provides a cue to action for the desired behavior Assumes “forgetting” is the cause of inaction Often fails to pair with or build naturalistic prompts

11 Feedback to the Patient Inputs UserIntegration & Analytics Bolsters self-regulatory processes Assumes lack of info is the cause of inaction (or over-action) Must be digestible and actionable to change behavior

12 Self- Efficacy Behavior Observational Learning Mini-goals O O O

13 Michie et al., 2013. The Behavior Change Technique Taxonomy (v1) of 93 Hierarchically Clustered Techniques: Building an International Consensus for the Reporting of Behavior Change Interventions. Annals Behavioral Medicine,

14 Reminders of a Few “Laws” of Behavior Change Habituation Respondent (Pavlovian) Conditioning Operant Conditioning Observational Learning Skills Training

15 Expanding Our Output Modalities On demand video trainings Rich media presentations Proactive social support Monetary incentives via mBanking, etc. Adaptive – To behavioral context – To prior intervention responses Theoretically and Empirically Grounded – especially in behavior change

16 NCI Science of Research and Technology Branch Priorities Theory development, testing and application; Measure development and testing, particularly of antecedents to, changes in, and consequences of health behavior; Technology development and application; Methodological innovation, particularly in analytic approaches; Data harmonization and research synthesis; and Team science and cross-disciplinary approaches.

17 Thank You Contact William Riley National Cancer Institute wiriley@mail.nih.gov


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