1. Just-In-Time, Adaptive Intervention framework for lifelong healthy dietary habits
Donna Spruijt-Metz, MFA PhD
Research Professor, Psychology
Director, USC mHealth Collaboratory
University of Southern California
@metzlab @
NSF International Workshop on Dynamic Modeling of Health Behavior Change and Maintenance,
Sept 8-9, 2015, London, UK

2. What, when, where and how
Skyler lives within a system of embedded systems (family, workplace, community, etc.)
Given how little we know of the dynamics of these systems in real time, choose 1 (family)
Use current behavioral evidence
Using food as reward or self medication
Stress & stressful interactions
Modeling
Availability
& Theories of choice
Self-regulation/self-control strength model (Muraven & Baumesiter Psyc Bull 2000)
Some form of family Systems Theory (McHale, Amato, Booth 2014)
To inform development of a learning sensor system to collect data describe eating behaviors in time and context
Wearable & deployable sensors that have pull as well as push capabilities.
NSF SCH , Spruijt-Metz, Stancovic, Lach & De LaHaye

3. What, when, where and how
Using data accrued, develop dynamic models of selected and discovered behaviors to understand behavior (interactions, loops) in system in real time
Conceptually seeded with current behavioral theories & behavioral evidence
‘Cycle out’ constructs when they no longer appear to contribute to the model,
Cycle in new ones as they are ‘discovered’ in an iterative fashion
This is a transdisciplinary effort
Use these models to inform choices on what, when and where to intervene on these models
Base “how” on theory and iterative user-centered design.
NSF SCH , Spruijt-Metz, Stancovic, Lach & De LaHaye

4. Self-Regulation of Eating in real-time & in context
A1 Stress
C1 Stress
C1 Self Regulation
C1: EE-4
A1 angry tone
C1 speed of Eating
Social Facilitation
C2: EE-3
Duration C1: EE-4
A1 mimic C1
A1 speed of eating
A1: EE-4
A1 self-regulation + -
C2 mimic C1
FED System Dynamic Model
Feedback loops (i.e. behaviors or events or states that spiral to effect themselves or other behaviors, events or states), ‘intervention’ effects (i.e. effects of events, states, or environments upon behaviors that wax and wane in unexpected forms and timeframes), using current theory to ‘seed’ new models, and the emergence of ‘new’ variables will be considered – This diagram can help inform choices of sensing modalities (what do you need to know?)
Legend
Family Members
C1 = Child 1
C2 = Child 2
A1 = Adult 1
A2 = Adult 2
Eating Event Categories
Hunger No Hunger
Meal EE EE-2
Snack EE EE-4
NSF SCH , Spruijt-Metz, Stancovic, Lach & De LaHaye

5. Current knowledge on behavior & theory breaks here: Multilevel & Multisystem
Time
System
Within-Individual
Family
Momentary
Self-Control strength
Modeling eating sweets
Within a day
Self-Control depletion
Stressful interactions
Over a week
Self-Control replenishing
Availability of sweets
Months
Ability to self-regulate mood
System of dinner table stressors
Spruijt-Metz, Hekler,
Saranummi, Intille, Korhonen,
Nilsen, Rivera, Spring, Michie,
Asch, Sanna, Salcedo, Kukafka,
Pavel, Trans Beh Med 2015
Years
Develop healthy eating habits
Parent Child-feeding practices

6. Not just when in need: Learning algorithms
Meaningful moments
Receptivity1
Availability2
Opportune moments3
In need and/or vulnerable
Receptive and/or available
Motivated and/or able
1 Nahum-Shani, Hekler, Spruijt-Metz, Health Psyc in press
2 Sharmin, Ali, Rahman, Bari, Hossain, Kumar, UbiComp ’14
3 Poppinga, Heuten, Boll, Pervasive Computing 2014

7. Baseline data: What and how long? Combining sensing & Self-report
Momentary level
Eating episodes (with whom, quality of interactions, where, when, speed, duration, stress, external cues/temptation – if possible, what)
Antecedents (physical activity, proximity to others, satiety, hunger, mood, access)
Outcomes (stress relief, self-control depletion)
Dynamic models to determine
Meaningful moments
How momentary behavior, emotion, cognition and environment interact
And how they interact with past behavior, emotion, cognition

8. Baseline data: What and how long? Combining sensing & Self-report
Periodically
Impulsivity
Chronic stressors
Pantry inventory & shopping habits
Whatever else choices of theory/behavior dictate
These get fed into the multilevel models.

9. Framework: prompting, pulling and pushing information, decision rules
Prompts via phone, via deployable and wearable sensors, via network members – at meaningful moments
Models will inform choices of data to acquire, sensors, platforms, types of messages, when/where to intervene, decision rules
Models will need to be run in an ongoing fashion (decision rule needed here too) in order to continue adaptation ‘on the fly’ – the intervention targets and messaging will evolve as person changes.
One can’t model everything all the time. Choices will need to be made to achieve some kind of parsimony