MedTrace Logo

A Mobile App to Increase Physical Activity in Students

NCT04440553 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 103

Last updated 2020-06-24

No results posted yet for this study

Summary

Background: Insufficient physical activity is one of the leading risk factors of death worldwide. Behavioral treatments delivered via smartphone apps, hold great promise for helping people engage in healthy behaviors including becoming more physically active. However, similar to 'face-to-face' treatments, effects typically do not seem to be sustained over longer periods of time.

Methods: the investigators developed a smartphone application that uses different types of motivational and feedback text-messaging to motivate individuals to increase physical activity. Here, participants are randomized to either receive messages by a uniform random distribution (n=50), or chosen by a reinforcement learning algorithm (n=50), which learns from daily participant data to personalize the frequency and type of motivation of messages.

Objectives: In the current study, the investigators examine this application in undergraduate and graduate students at the University of California, Berkeley. The investigators compare whether participants in the uniform random or adaptive group have higher increases in steps during the study. The investigators also examine the effect of the different types of messages on step counts. Further the investigators assess the influence of patient characteristics, such as socio-demographic, psychological questionnaire scores and baseline physical activity on the effect of the adaptive arm and effectiveness of the messages. Finally, the investigators assess participant qualitative feedback on the text-messaging program, through feedback provided via questionnaires, text-message and phone interviews.

Conditions

  • Mobile Health
  • Physical Activity
  • Exercise
  • Mood
  • Machine Learning

Interventions

BEHAVIORAL

Uniform random message delivery

The uniform random intervention group receives feedback and motivational messages chosen from the messaging banks with equal probabilities.

BEHAVIORAL

Reinforcement learning message delivery

The adaptive intervention group receives messages chosen from the messaging banks by a reinforcement learning algorithm.

Sponsors & Collaborators

Principal Investigators

  • Adrian Aguilera, PhD · University of California, Berkeley

Study Design

Allocation
RANDOMIZED
Purpose
PREVENTION
Masking
SINGLE
Model
PARALLEL

Eligibility

Min Age
18 Years
Max Age
65 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2019-09-12
Primary Completion
2019-12-10
Completion
2019-12-20

Countries

  • United States

Study Locations

More Related Trials

Entities

Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04440553 on ClinicalTrials.gov