Precision Public Health: Enhancing Connections to Develop Just-in-Time Adaptive Intervention Strategies
- Conditions
- OverweightOverweight and ObesityObesity
- Interventions
- Behavioral: Nudge
- Registration Number
- NCT03836391
- Lead Sponsor
- University of North Carolina, Chapel Hill
- Brief Summary
The purpose of this pilot study is to examine the effects of different types of just-in-time intervention messages on daily meeting dietary, activity, and weighing goals in a sample of young adults participating in a mobile-based weight loss program.
- Detailed Description
Public health interventions typically rely on a set schedule of intervention delivery. Advances in technology and computer tailoring allow us to go from a "one size fits all" approach to one that uses digital health data to deliver "just-in-time adaptive interventions," or JITAIs, that can vary the timing, dose, and content of intervention messages to individuals. This pilot study is a micro-randomized trial that evaluates the effects of various intervention message options delivered in JIT moments on meeting dietary, activity, and weighing goals among young adults in a mobile-based weight loss program.
The Nudge study is a 12-week mobile health weight loss program delivered via a native smartphone application. Individuals are asked to track their red foods (high-calorie, high-fat foods) in the app daily and meet their personalized red foods goal, wear a Fitbit daily and meet their daily active minutes goal, and weigh daily on their WiFi-enabled scale. Up to 4 times each day, participants are randomized to receive or not receive intervention messages in order to examine the effects of these intervention message types on meeting daily weighing goals, red food goals, and activity goals. This is a within-subjects design in which each participant serves as their own control, and data is analyzed at the person-day level.
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 53
- Age 18-35
- BMI of 25-40 kg/m²
- Not adhering to the US physical activity guidelines of at least 150 moderate-to-vigorous intensity activity minutes/week
- English-speaking and writing
- No pre-existing medical condition(s) that preclude adherence to an unsupervised exercise program, diabetes treated with insulin, history of heart attack or stroke, current treatment for cancer, or inability to walk for exercise
- Has an iPhone with iOS 11 (or willing to download it) with internet access and text messaging plan
- Has home wireless access compatible with Fitbit Aria 2 scale (802.11b/g/n)
- Current participation in another physical activity or weight control program
- Currently pregnant, pregnant in last 6 months, or planning pregnancy in next 3 months
- Report a heart condition, chest pain during periods of activity or rest, loss of consciousness, joint or bone problems, or prescription medicine usage for blood pressure or heart condition on the Physical Activity Readiness Questionnaire (PAR-Q)
- Health or psychological diagnoses that preclude participation in a prescribed dietary and exercise program, including diagnosis of schizophrenia or bipolar disorder, hospitalization for a psychiatric diagnosis in the past year, diagnosis of alcohol or substance abuse
- Occupation requires primarily night shift work
- Owns and uses a physical activity tracker
- Moving out of area in next 4 months
- Out of town for a week or more during study period
- Not willing to attend two study visits
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- SINGLE_GROUP
- Arm && Interventions
Group Intervention Description Nudge Intervention Nudge Each of 7 intervention message options has specific decision rules (including weighed/not weighed and progress toward daily dietary and activity goals) that make a participant eligible to receive a specific intervention type at a specific time (decision points). At each decision point (early morning, morning, midday, and evening), the system evaluates which intervention options a participant is eligible to receive, and randomly chooses one intervention option from that list. Then the participant is randomly assigned to either receive or not receive that intervention message (with a 50-50 probability).
- Primary Outcome Measures
Name Time Method Percent of person-days with same-day weighing from Baseline to Week 12 Percent who weighed after the message randomization time until the end of the day (at the participant-day level) across the 12-week study
Percent of person-days with next-day weighing from Baseline to Week 12 Percent who weighed the day after the message randomization (at the participant-day level) across the 12-week study
Percent of person-days met active minutes goal on same day from Baseline to Week 12 Percent who met active minutes goal after the message randomization time until the end of the day (at the participant-day level) across the 12-week study
Percent of person-days met active minutes goal on next day from Baseline to Week 12 Percent who met active minutes goal the day after the message randomization (at the participant-day level) across the 12-week study
Percent of person-days met red foods goal on same day from Baseline to Week 12 Percent who met red foods goal after the message randomization time until the end of the day (at the participant-day level) across the 12-week study
Percent of person-days met red foods goal on next day from Baseline to Week 12 Percent who met red foods goal the day after the message randomization (at the participant-day level) across the 12-week study
- Secondary Outcome Measures
Name Time Method Number of active minutes from Baseline to Week 12 Total number of active minutes on the day of message randomization (at the participant-day level) across the 12-week study
Proximal effect of message on total red foods today from Baseline to Week 12 Total number of red foods on the day of message randomization (at the participant-day level) across the 12-week study
Mean weight change from Baseline to Week 12 Mean weight change across participants
Trial Locations
- Locations (1)
Department of Health Behavior, University of North Carolina, Chapel Hill
🇺🇸Chapel Hill, North Carolina, United States