Kevin Patrick, MD, MS Center for Wireless and Population Health Systems, University of California, San Diego, La Jolla, California NSF International Workshop.

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Presentation transcript:

Kevin Patrick, MD, MS Center for Wireless and Population Health Systems, University of California, San Diego, La Jolla, California NSF International Workshop on Dynamic Modeling of Health Behavior Change and Maintenance, Sept 8-9, 2015, London, UK MH2010 | K. Patrick

1. Sensors are available to capture continuous data on: Assumptions: 1. Sensors are available to capture continuous data on: Physical Activity Sedentary periods Location Heart rate   2. The platform for intervention will be based around a mobile phone, one or more wearable sensors and computational elements on the sensors, phone and in the cloud. NSF International Workshop on Dynamic Modeling of Health Behavior Change and Maintenance, Sept 8-9, 2015, London, UK

Assumptions (cont): 3. Prior to the onset of the intervention we can gather baseline information on:   Strategies for weight management Location of residence, workplace, usual transportation practices Preferences for type(s) of physical activity (walking, cycling, gym, outdoors, etc.) GIS and other location information on a rich set of environmental influences on food intake such as locations of healthy food, junk food, convenience stores, locations where food identified by Skyler as problematic may be found (e.g., bars where too much drinking and snack consumption occurs).

Major influences on health

Assumptions (cont): 4. We will have a run-in period of use of the system in which background norms for Skyler can be ascertained. At least a week, longer if possible, in particular if things are changing at a longer term scale like new job, move of residence, etc.  

Describe the JITAI that you would like to develop.   Monitor physical activity as a proxy for calorie consumption. Improve the modeling of this monitoring location data and sending periodic SMS or other EMA strategies to label and strengthen knowledge about times when less than optimal food intake occurs The intervention would then be based upon a combination of energy expenditure data and location data, the latter serving as a proxy for places where healthy or unhealthy eating behaviors might occur – including at home & work. Periodic prompts to improve labeling of selected events would be provided to strengthen, over time, the expert aspects of the intervention.

What framework would you need to enable decisions on what, when, how and where, to provide that momentary intervention?   It would be a combination of time-based messages (based upon a priori specified “at risk” times for either good or bad SWMs) and prompted assessments (pulls) or messages (pushes) based upon other key elements. Could also factor in the types of messages that are liked or not liked.

What theory would you employ, and how?   Behavior change techniques would be used, as would control theory. Measure, feedback, measure again, feedback, etc., based upon results, preferences, etc.

Where do you think that theory might break down in the context of momentary interventions that can be adapted to individual needs on the fly (Just-In-Time, Adaptive Interventions, or JITAIs; Ecological momentary interventions)?   It might break down during times of unusual stress or other external issues that are not under the control of Skyler.

For how long a period of time would you need to collect those data before willfully perturbing that data by initiating an intervention?   It depends… A few days for some of the training data. But this might depend upon how robust the classification method is as well as on how many different data sources are being used for the intervention elements.

ConTxt Sketch the framework… PURPOSE To develop and test the efficacy of a SMS intervention for weight loss among overweight and moderately obese (BMI 27-39.9) men and women ages 21–60.  The ConTxt study builds upon our work with pilot SMS weight loss study mDIET. The ConTxt study aims to extend the expert logic of the SMS messages including ecological components and evaluate it in an RCT. NIH/NCI R01 CA138730; Patrick, PI Copyright, Regents of the University of California, 2014

RCT Study Design Sketch the framework… n = 103 n = 103 RCT ENROLLMENT: Began: October 2011 Completed: March, 2014 Community Recruitment: Email listservs, flyers, community events, print and/or radio advertisements 309 Subjects, 21-60 years old male & female, Weight: 27 < BMI < 39.9 English & Spanish speaking Text Messages Users (or willing to learn) n = 103 SMS Only SMS Only + Counseling n = 103 Comparison Copyright, Regents of the University of California, 2014

SMS Logic & Flow Sketch the framework… Weekly Mastery Assessment (Friday) Sunday Weekly SWM Messages Willingness Send SMS: “Are you willing to set goals for [WBI] this week? (y/n)” Send SMS: “On a scale of 1 (never) to 5 (always), how often did you [insert WBI] in the past week?”   Barrier SMS Messages (M, T, W, TH, SA) Mastery = Weekly Average (after 3 weeks) >/= to 4 NO YES Answer 1, 2, or 3 Answer 4 or 5 Knowledge Text Messages Skills/ Tips Text Messages Send Multiple Choice Barrier Question Barrier 1 Barrier 2 Barrier 3 Barrier 4 SWM Maintenance Messages (M, T, W, TH, SA) Copyright, Regents of the University of California, 2014

“Liked” and “Unliked” Message Logic Sketch the framework… “Liked” and “Unliked” Message Logic Copyright, Regents of the University of California, 2014