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The Steak is More
than Sizzle: Behavior
Change Models in
eHealth Applications
Chair: Robin C. Anthony Kouyaté, PhD,
WellDoc Inc, Baltimore, MD
Discussant: Edwin B. Fisher, PhD, Health
Behavior and Health Education, School of
Public Health, University of North Carolina,
Chapel Hill, Chapel Hill, NC
E-Health
• “use of information communication
technology for health” (WHO, 2005)
• Rapidly evolving range of eHealth
technologies and functionality:
• Internet
• PDAs
• Mobile technologies (e.g. phones, iPads)
• Sensory devices
• SMS, apps, social media, EHRs, etc…
Health Behavior Interventions
Design
• Evidence-base
• Models and theories
• Behaviors and determinants to be influenced
• Intervention mapping
• Behavior Change Techniques (BCT) – “Active ingredients”
• Messaging strategy including concept identification, framing, and
tailoring dimensions
Implementation
• Strategy
• Integration into specific settings
• Considerations/constraints for implementation model or business
model
• Mechanisms for intervention delivery
Evaluation
• Appropriate methods for measuring efficacy and effectiveness
Unique considerations for
eHealth interventions
Design
• Ability to fit into daily life patterns
• User centered design and the role of user experience and user interface
in the art of delivery
• Rapidly emerging tools
• Rapid iteration
Implementation
• Best tool for the job: mapping features and functionality to intervention
objectives
• How enhances or complements existing modes of delivery
• Influence on level and type of interactivity
• Enhanced possibilities for dynamic, adaptive delivery of interventions
Evaluation
• Faster loop
• Data collection to inform design - type, modality, frequency and timing
• Appropriate methods for measuring efficacy and effectiveness (e.g.
MOST, SMART , RCT)
Introduction to Presentations
Conversing with a computer to improve self-management of
diabetes: How does it work?
Brian Oldenburg, Monash University, Melbourne, VIC, Australia
It’s Your Game: Keep It Real
Ross Shegog, PhD, University of Texas School of Public Health and
Jeffery McLaughlin, Radiant Creative Group
Defining an integrated clinical/behavioral framework to
translate research into evidence-based mHealth interventions
that support chronic illness management
Calvin C. Wilhide, PhD, Malinda Peeples, RN, MS, CDE, Robin C.
Anthony Kouyaté, PhD
Thoughts
• Advantages of eHealth vs. traditional approaches
• Comparative advantage of various technologies
for addressing behavioral determinants and
intervention objectives
• Potential modifications of behavioral models as a
result of eHealth technology
• Considerations for real world implementation

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The Steak is More than Sizzle (symposium overview)

  • 1. The Steak is More than Sizzle: Behavior Change Models in eHealth Applications Chair: Robin C. Anthony Kouyaté, PhD, WellDoc Inc, Baltimore, MD Discussant: Edwin B. Fisher, PhD, Health Behavior and Health Education, School of Public Health, University of North Carolina, Chapel Hill, Chapel Hill, NC
  • 2. E-Health • “use of information communication technology for health” (WHO, 2005) • Rapidly evolving range of eHealth technologies and functionality: • Internet • PDAs • Mobile technologies (e.g. phones, iPads) • Sensory devices • SMS, apps, social media, EHRs, etc…
  • 3. Health Behavior Interventions Design • Evidence-base • Models and theories • Behaviors and determinants to be influenced • Intervention mapping • Behavior Change Techniques (BCT) – “Active ingredients” • Messaging strategy including concept identification, framing, and tailoring dimensions Implementation • Strategy • Integration into specific settings • Considerations/constraints for implementation model or business model • Mechanisms for intervention delivery Evaluation • Appropriate methods for measuring efficacy and effectiveness
  • 4. Unique considerations for eHealth interventions Design • Ability to fit into daily life patterns • User centered design and the role of user experience and user interface in the art of delivery • Rapidly emerging tools • Rapid iteration Implementation • Best tool for the job: mapping features and functionality to intervention objectives • How enhances or complements existing modes of delivery • Influence on level and type of interactivity • Enhanced possibilities for dynamic, adaptive delivery of interventions Evaluation • Faster loop • Data collection to inform design - type, modality, frequency and timing • Appropriate methods for measuring efficacy and effectiveness (e.g. MOST, SMART , RCT)
  • 5. Introduction to Presentations Conversing with a computer to improve self-management of diabetes: How does it work? Brian Oldenburg, Monash University, Melbourne, VIC, Australia It’s Your Game: Keep It Real Ross Shegog, PhD, University of Texas School of Public Health and Jeffery McLaughlin, Radiant Creative Group Defining an integrated clinical/behavioral framework to translate research into evidence-based mHealth interventions that support chronic illness management Calvin C. Wilhide, PhD, Malinda Peeples, RN, MS, CDE, Robin C. Anthony Kouyaté, PhD
  • 6. Thoughts • Advantages of eHealth vs. traditional approaches • Comparative advantage of various technologies for addressing behavioral determinants and intervention objectives • Potential modifications of behavioral models as a result of eHealth technology • Considerations for real world implementation