1. Modeling Approaches for Health Coaching Interventions
Holly Jimison, PhD, FACMI
College of Computer & Information Science
College of Health Sciences
Director,
Consortium on Technology for Proactive Care
Northeastern University, Boston, MA, USA
NSF International Workshop on Dynamic Modeling of Health Behavior Change and Maintenance, Sept 8-9, 2015, London, UK

2. Modeling for Coaching Overview Points
Use theoretical frameworks that health coaches actually use (mix and match as needed)
Use a decision theoretic framework (probabilities and utilities for any action taken (alerts, messaging)
Integrate intervention into daily life
Devices: smart phones, calendars
Coordinate with other interventions (stress management, medications, exercise, etc.)
Unobtrusive

3. What does this mean for Skyler?
Integrate intervention into daily life
Coordinate with other interventions (stress management, medications, exercise, sleep, etc.)
Unobtrusive or minimally obtrusive sensors
Smart phone for messaging, sensing voice quality, location for context, rough level of activity, EMA assessments
Credit card, debit card reports of food purchases
Computer interactions (cognitive games, mouse, keyboard interactions) for cognitive state
Smart watch for EDA, HRV, SaO2, activity, messaging
Bed sensor for HRV (stress recovery, sleep efficiency)

4. Theoretical frameworks that health coaches actually use:
Backdrop:
Collaborative, Tailored, Timely
Develop a tailored shared action plan
Monitor & provide feedback / encouragement
Frameworks:
Motivational Interviewing throughout
Motivations, Barriers, Triggers
Stages of Change for initial content & level of detail in later stage messaging
Self efficacy for preparation/action/maintenance

5. Model Variables Monitored behaviors Baseline variables for all modules
Eating behaviors
Purchasing behaviors
Physical exercise
Socialization activities
Sleep efficiency
Monitored physiology
HRV, EDA, SaO2
Context Variables
Location
Activity
Inferred patient states
Baseline variables for all modules
Behavior goals
Motivations
Barriers
Triggers
Stage of change
Self efficacy
Literacy/numberacy level
Contact info & preferences

6. Model Variables Possible actions Inferred Variables Tailored messaging
Adherence to goals
Stage of change
Self efficacy
Patient states
Quality of diet
Stress level
Cognitive functioning
Physical functioning
Socialization level
Sleep quality
Possible actions
Tailored messaging
Reminders
Encouragement
Suggestions
Information
Alerts
Coach, Family, Clinician
Interventions
Lighting to highlight good food choices
Stress management
…. other

7. When to use which type of computational model
Sensor data models
Sampling, filtering, summarization
Data harmonization, representation, storage
Sensor fusion models (not a simple average)
Inference of patient state – statistical and process models
Tailored messaging – production rules; active methods
Alerting or assessment – decision theoretic overlay

8. Dynamic User Model to Support Health Coaching
Intake Assessment
Health Status
Health Goals
Motivations
Barriers
Stage of Change
Social Support
Preferred Name
Contact Preferences
Dynamic User Model
Current Goals
Current Motivations
Current Barriers
Current Triggers
Current Self Efficacy
Current Patient States
Monitored Data
Eating Behaviors
Food Purchases
Emotional Status
Sleep Quality
Cognitive Status
Socialization
EMA Self Report
As needed
Tailored
Action
Plan
Data
Summary
Tailored
Message
Generator
Message Database
Greetings
Feedback Messages
Recommendations
Closings
General Interest News
Family
Interface
Patient
Interface
Coach
Interface

9. Use decision theory framework
Probabilities
Patient state
Patient activity
Utilities for any action taken
Messaging
Assessments
Alerts to coach, family, clinician

10. Modeling for Alerts
Decision Theory Framework
Probabilities
Utilities

11. Example: Medication Adherence
Modeling for Alerts
Decision Theory Framework
Probabilities
Utilities 11

12. Example: Medication Alerts
Model Variables
Importance of Drug
Likelihood of remembering
Cost of alert (nagging)
Generate Alerts
Patient Reminders
Display to coach
Display to family
Display to clinician
U=Utility, A=Alerting Action, C=Context, q=patient state

13. Summary:
Use theoretical frameworks that health coaches actually use (mix and match as needed)
Use computational models that fit the need
Use a decision theoretic framework (probabilities and utilities for any action taken
Integrate intervention into daily life
Holistic multifaceted approaches
Think long-term sustainability

14. Questions / Suggestions
Holly Jimison, PhD, FACMI