1. Model-based Social-Cognitive mHealth
Peter Pirolli
NSF International Workshop on Dynamic Modeling of Health Behavior Change and Maintenance, Sept 8-9, 2015, London, UK

2. Health Behavior Change via Smartphone

3. AI-based coach & team leader
Fittle+ (Nudg 2.0)
Daily habits
Small teams
AI-based coach & team leader

4. Behavior-Change Programs
Expert
Conceptual Architecture
Authoring Tool
Behavior-Change Programs

5. Conceptual Architecture
Expert
Conceptual Architecture
Authoring Tool
Behavior-Change Programs
Coaching Engine
Rich Content
Actions
& Decision Rules
Goals
User Model
User
EMIs
Team
Team
Model
Planning & Optimization
Team
Posts
Update Models
Activity &
Assessment
Learning
Interaction
Analyzer

6. Computational Neurocognitive Theory (ACT-R)
Redefine a “macro” theory of behavior change...
Self-Efficacy
Intention
Behavior
Social Cognitive Theory
...into a finer-grained computational simulation
Manual
Imaginal
Visual
Aural
Production
Declarative
Goal
Vocal
manual
imaginal
goal
vocal
retrieval
aural
visual
visual location
Behavior
ACT-R

7. Belief in capacity to execute behaviors Interventions
Self-efficacy
Belief in capacity to execute behaviors
Interventions
Guided Enactive Mastery
Selective Self-monitoring
Vicarious Experience
…..

8. An ACT-R Model of Self-Efficacy: The Basic Idea
Goal
to do a set of activities A that I believe have some difficulty δg
Call upon memory:
What have I done that is similar to A?
Blend memories to determine self- efficacy:
Based on my memories of the difficulty δE of my successful past experiences, I believe my ability is θE
Positive experiences (or thinking of them) increases the strength of those memories (increase Self- efficacy)
Memory
Goal

9. Fit of ACT-R-Based Model to 28-day Dstress mHealth
Data
Model
Konrad, A., Bellotti, V., Crenshaw, N., Tucker, S., Nelson, L., Du, H., Whittaker, S. (2015). Finding the Adaptive Sweet Spot: Balancing Compliance and Achievement in Automated Stress Reduction. Paper presented at the SIGCHI Conference on Human Factors in Computing Systems (CHI 2015), Seoul, Korea.

10. Assignment: What our Subject Matter Expert Wanted
Assumed Goals
Balanced regular meals, reduced snacking, processed foods, snacking, seets
Approach:
Healthy habits to replace poor ones
Slow eating, healthy breakfast, 5 servings veggies…
Environmental changes
Kitchen makeover….
Initial testing (tailoring rules dependent on these)
At least 8 blood/gene tests
Battery of at least 12 different integrative behavior-change instruments (activity, diet, psycho-social states, health-behavior, stress, sleep, body composition, environmental inventory….)
2-4 week self-monitoring phase
What are you doing? Food & feelings….
Not only for data—a healthy self-awareness habit
Must be simple!!!!!

11. Geeky Need #1: Scalable Expert Knowledge Capture
Authoring Tool
Behavior-Change Programs
S.M.A.R.T
mHealth

12. Geeky Need #1: Scalable Expert Knowledge Capture
Authoring Tool
Crowdsourcing?
Back-off to experts?
How do we start with 50% coverage and grow to 99%?
Behavior-Change Programs
Tune and Expand
Existing Program
User
EMI
Gaps

13. Geeky Idea #2: System 2 EMAs & EMIs
Mastering your inner elephant
Symbolic
System 2
(Explicit)
Manual
Imaginal
Visual
Aural
Production
Declarative
Goal
Vocal
manual
imaginal
goal
vocal
retrieval
aural
visual
visual location
ACT-R
System 1
(Implicit)
Subsymbolic Dynamics
Memory Blending

14. Geeky Idea #2: System 2 EMAs & EMIs
Mastering your inner elephant
Implicit taste vs health associations (System 1) modulate
Choice
Inhibitory control
Self-efficacy
Deliberate cognitive training can alter those associations and control systems
System 2
(Explicit)
System 1
(Implicit)

15. Implicit Attitudes Test (IAT)
Healthy
and
Tasty
Unhealthy
and
Not tasty
Block 3,4,5; 20 trials each; Healthy+Tasty vs. Unhealthy+Not tasty
Highlighted gray denotes selection
Next trial is automatic upon selection
Red X mark under stimuli if incorrect response, must press other option to fix error and move to next trial
Items in middle include both words and stimuli
LEFT
RIGHT

16. Implicit Attitudes Test (IAT)
Healthy
and
Tasty
Unhealthy
and
Not tasty
Feasible on smartphone
Thousands take it online of their own volition
Game-like and can be made more so
Can be used in cognitive training(?)
Block 3,4,5; 20 trials each; Healthy+Tasty vs. Unhealthy+Not tasty
Highlighted gray denotes selection
Next trial is automatic upon selection
Red X mark under stimuli if incorrect response, must press other option to fix error and move to next trial
Items in middle include both words and stimuli
LEFT
RIGHT

17. Geeky Need # 3: Simpler (but not automated!) Monitoring & Reflection
Quantified Self
Sensing
How are you spending your day?
Contexts, food & feelings, behaviors
Experience sampling
User tagging of automated logs
Smart about prompting:
Receptive, accurate, reflective
Lifelogs

18. CMU LifeLogger
Joy Zhang

19. THANK YOU.

20. Geeky Need #4: Deliberate (Virtual) Practice
Must be feasible on smartphone
System 2
Reflection on “virtual diary”
Practice for upcoming situations (family banquet, holiday travel) …
System 1
Cognitive training
Implicit attitudes
Regulatory responses

21. Underlying Computations for Self-efficacy

22. Impulse-like Nature of the ACT-R Model of Self-Efficacy