A Mobile App to Increase Physical Activity in Students

NCT04440553 | Completed

• 1 other identifier: 2019-04-12118
• Study Type: interventional
• Target: 103
• Locations: 1 country
• Sites: 1

Brief 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

Outcome Measures

Primary Outcomes (2)

• Steps (measured by phone pedometer)

  Change in daily step counts (today's steps count minus yesterday's steps count)

  24 hours (measured for a period of 6 weeks)

• Steps (measured by phone pedometer)

  Mean change in daily step counts during the course of the study

  Change from baseline to 6 week follow-up

Secondary Outcomes (3)

• Depression scores

  Change from baseline to 6 week follow-up

• Anxiety scores

  Change from baseline to 6 week follow-up

• Behavioral Activation

  Change from baseline to 6 week follow-up

Study Arms (2)

Uniform random

ACTIVE COMPARATOR

In this arm the types of messages were sent out randomly, i.e. with a uniform random distribution.

Behavioral: Uniform random message delivery

Reinforcement learning

EXPERIMENTAL

In this arm the types of messages were chosen by a reinforcement learning algorithm. The decision about which message to send was based on several contextual variables, including data for the pedometer app, and consecutive days since messages from different categories were sent.

Behavioral: Reinforcement learning message delivery

Interventions

Uniform random message delivery BEHAVIORAL

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

Uniform random

Reinforcement learning message delivery BEHAVIORAL

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

Reinforcement learning

Eligibility Criteria

• Age: 18 Years - 65 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

Sponsors & Collaborators

• University of California, Berkeley: lead

Study Sites (1)

Caroline Figueroa

Berkeley, California, 94709, United States

Location

Related Publications (1)

• Figueroa CA, Deliu N, Chakraborty B, Modiri A, Xu J, Aggarwal J, Jay Williams J, Lyles C, Aguilera A. Daily Motivational Text Messages to Promote Physical Activity in University Students: Results From a Microrandomized Trial. Ann Behav Med. 2022 Feb 11;56(2):212-218. doi: 10.1093/abm/kaab028.

  PMID: 33871015 DERIVED

MeSH Terms

Conditions

Motor Activity

Condition Hierarchy (Ancestors)

Behavior

Study Officials

• Adrian Aguilera, PhD

  University of California, Berkeley

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: PARTICIPANT
• Masking Details: Participants were unaware of their group membership. Investigators were not blinded to group membership.
• Purpose: PREVENTION
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Model Details: Participants were randomized to a uniform random group, or a reinforcement learning group. Within these groups, participants received the same types of text-messages, but the delivery schedule differed.

Study Record Dates

• First Submitted: June 17, 2020
• First Posted: June 19, 2020
• Study Start: September 12, 2019
• Primary Completion: December 10, 2019
• Study Completion: December 20, 2019
• Last Updated: June 24, 2020

Record last verified: 2020-06

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ANALYTIC CODE
• Time Frame: After publication of the data, no end date
• Access Criteria: Anyone with a methodologically sound proposal.

Locations

US (1)