Society of Behavioral Medicine: Advancing Methods in Behavioral Informatics

Eric Hekler, PhDSBM Technology SIG Co-Chair

Asst. Prof., College of Health Solutions

Arizona State University

@ehekler

www.designinghealth.org

Take-Home Message

SBM members are creating highly innovative

methods for designing, evaluating, and

implementing mHealth/eHealth behavioral

interventions for real-world use.

Domains

• Optimizing behavioral interventions

• Just-in-time adaptive interventions

• Theory taxonomy ontology real-world use

• Fostering rapid, relevant and responsive research

Optimizing Interventions

Linda M. Collins

The Methodology Center

Penn State

methodology.psu.edu

Statistical Reinforcement Learning LabUniversity of Michigan

• Research:

– Adaptive Interventions

– Sequential Multiple Assignment Randomized Trial

(SMART)

Inbal (Billie) Nahum-ShaniSusan MurphyDanny Almirall

Adaptive Intervention

SMART

Example

Adaptive

Example

http://methodology.psu.edu/ra/smart/projects

www.cbits.northwestern.edu

(Am J Prev Med 2013;45(4):517–523)

David Mohr

Northwestern

Just-in-Time Adaptive Interventions

Statistical Reinforcement Learning LabUniversity of Michigan

• Research:

– Just In Time Adaptive Interventions (JITAI)

– Micro-Randomized trial designs and data analysis

methods for JITAI development

https://community.isr.umich.edu/public/jitai/Workshop.aspx

Inbal (Billie)

Nahum-Shani

Susan MurphyDanny Almirall Pedja Klasnja Ambuj Tewari

Just In Time Adaptive Intervention (JITAIs)

• Individualized treatments delivered when-ever and where-ever the individual needs help, via a wearable device (e.g., smartphone).

+

• Advancing: • Micro-randomization trial designs • Data analysis methods for constructing good decision rules.• Online training algorithms that will personalize decision rules.

https://community.isr.umich.edu/public/jitai/Workshop.aspx

Controller-Driven Just in Time Adaptive Interventions

Co-PIs: Eric Hekler & Daniel Rivera, ASU

Other Collaborators: Matthew Buman, Marc Adams, & Pedrag Klasnja

Daniel Rivera

www.designinghealth.org support from the National Science Foundation

Dynamical Model of Social Cognitive Theory

Martin, Riley, Rivera, Hekler, et al. 2014

Informative Experiment for a Controller

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Intervention 4

Intervention 3

Intervention 2

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Measurement

www.designinghealth.org support from the National Science Foundation

Theory Taxonomy Ontology Use

Developed: BCT Taxonomy v1

Underway – BCT Theory Consortium

Study 4: TriangulationTriangulation of consensus, evidence synthesis and BCT clustering methods

Study 3: BCT ClusteringBCT clustering: Identifying implicit theories (published interventions and

expert consensus)

Study 2: Expert ConsensusIdentifying and agreeing BCT-Theory links

Study 1: Evidence SynthesisExamining BCT-Theory links in published interventions

Designing and evaluating theory-based interventions-

Developing and testing a methodology for linking behaviour

change techniques to theory

The Team

Marie Johnston

Professor Emeritus

University of Aberdeen

Marijn de Bruin

Chair in Health Psychology

University of Aberdeen

Susan Michie

Professor of Health

Psychology

University College LondonAlex Rothman

Professor of Psychology

University of Minnesota

Mike Kelly

Director of Centre for

Public Health

NICE

/ University of Cambridge

Lauren Connell

Research Assistant

University College London

Rachel Carey

Research Associate

University College London

International Advisory Board

Behavioral Ontology v1

Larry An

U. MichiganSusan Michie

U. College London

http://chcr.umich.edu/ http://www.ucl.ac.uk/behaviour-change

Timothy Bickmore, Northeastern University

Screen young African American

women on 108 health risks. Create

individualized action plan.

Conduct longitudinal, stage-

based counseling to address

specific risks (22 on average).

Preconception CareHow do we build systems to intervene on dozens of health behaviors

simultaneously?

Rapid, Relevant, and Responsive Research

Riley WT, Glasgow RE, Etheredge L, Abernethy AP. Rapid, responsive, relevant (R3) research: a call for a rapid learning

health research enterprise. Clinical and translational medicine. 2013;2(1):1-6.

Rapid, Relevant, and Responsive Research

Bill Riley

Acting Director,

OBSSR, NIH

Challenging Assumptions

www.agilescience.org

Developing Methods: Agile Science

www.agilescience.org

Creating the Tools

www.agilescience.org

Sign Up to Be a Beta-Tester

www.agilescience.org

Take-Home Message

SBM members are creating highly innovative

methods for designing, evaluating, and

implementing mHealth/eHealth behavioral

interventions for real-world use.

Slides Available

www.designinghealth.org/presentations.html

@ehekler

ehekler@asu.edu