# Sensor-based Just-in Time Adaptive Interventions (JITAIs) Targeting Eating Behavior

> **NIH NIH R01** · UNIVERSITY OF ALABAMA IN TUSCALOOSA · 2021 · $61,011

## Abstract

PROJECT SUMMARY/ABSTRACT
Long-term weight control is difficult to achieve and requires permanent changes in eating behavior. Emerging
wearable sensor technology enables accurate and objective measurement of ingestive behavior, and real-time
analysis of the sensor data paves the way for development of individually tailored and immediately delivered
intervention (just-in-time adaptive Intervention; JITAI) to change eating behavior. Grounded in empirically and
theoretically supported behavior change strategies for weight control, the proposed project relies on the
synergy of wearable sensor technology, machine learning, behavioral science, personalized medicine, and
nutrition to deliver and test such JITAIs. We previously developed a wearable sensor, the Automatic Ingestion
Monitor (AIM), that automatically and accurately detects eating and characterizes meal microstructure (e.g.,
eating duration, rate of ingestion). These data can also be used to accurately estimate energy intake. The
goals of this project are to: 1) use the AIM to study two common behavioral patterns observed among
individuals with overweight/obesity, namely, excessive total daily energy intake (EI) and fast eating rate; 2)
define the optimal personalized triggering metrics for two JITAIs targeting these behaviors; and 3) evaluate
JITAIs’ effects on daily energy intake and targeted behaviors. In fulfillment of these goals, we will first conduct
a study to characterize the target eating behaviors, then simulate and define triggering metrics for personalized
JITAIs to change targeted eating behaviors and decrease EI. The JITAIs are rooted in self-regulation theory
(SRT): setting a behavioral goal and monitoring progress toward that goal, with feedback to reinforce success.
To enable the SRT-informed JITAIs, we will first use the AIM to collect data about ingestive behaviors
quantified by objective, sensor-measured metrics from 90 adults with overweight/obesity who will wear the
device for one week in free living conditions. Second, using the collected dataset, we will: a) analyze individual
curves of cumulative daily EI and rate of eating within eating episodes to define triggering parameters for
personalized JITAI delivery, and b) numerically simulate JITAI delivery and effects. We will then conduct a
second study to evaluate the immediate effect of JITAIs on EI and ingestive behavior in free living participants.
We will conduct a within-subjects trial with 128 adults wearing the AIM for 7 weeks. To personalize JITAIs, the
AIM will learn individual eating patterns over a 1-week run-in period. Each JITAI will be delivered for two weeks
(weeks 2-3 and 5-6) in a randomized crossover design with the resulting daily EI and ingestive behavior
compared to baseline and the acceptability of the JITAIs assessed via questionnaire. On washout weeks 4 and
7, participants will continue to wear the AIM (no JITAIs) to assess persistence of intervention effects. The
proposed project is the first st...

## Key facts

- **NIH application ID:** 10425512
- **Project number:** 3R01DK122473-03S1
- **Recipient organization:** UNIVERSITY OF ALABAMA IN TUSCALOOSA
- **Principal Investigator:** EDWARD S SAZONOV
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $61,011
- **Award type:** 3
- **Project period:** 2019-09-01 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10425512

## Citation

> US National Institutes of Health, RePORTER application 10425512, Sensor-based Just-in Time Adaptive Interventions (JITAIs) Targeting Eating Behavior (3R01DK122473-03S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10425512. Licensed CC0.

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