Mobile HealthNCT04440553
A Mobile App to Increase Physical Activity in Students
A study testing Uniform random message delivery and Reinforcement learning message delivery in people with Mobile Health and Physical Activity, run by University of California, Berkeley at 1 site in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 65 yearsHealthy volunteers can take part
- Conditions the study is for
- Mobile Health, Physical Activity, Exercise
- What is being tested?
- Uniform random message delivery and Reinforcement learning message delivery
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 103 participants
- Where
- 1 siteUnited States
- Study dates
- 12 Sep 2019to 20 Dec 2019
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 65 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Inclusion Criteria: We will include currently enrolled undergraduate and graduate students ages 18 to 65.
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Exclusion Criteria: Students that do not have a smartphone, are not able to exercise due to disability, or have plans to leave the country during the 6 week study will be excluded.
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Trial locations and contacts
1 site in 1 country.
About this study
Official title: An mHealth App Using Adaptive Learning to Increase Physical Activity in University Students
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.
Read the detailed description
The investigators developed a smartphone application, the DIAMANTE app, that uses machine learning to generate adaptive text messages, learning from daily participant data to personalize the frequency and type of motivation of messages. In the current study, the investigators will compare this application in undergraduate and graduate students at the University of Berkeley, to text-messaging chosen randomly. This study will provide insight into the effectiveness of this smartphone application for increasing physical activity in university students. Further, it will provide preliminary knowledge on the working mechanisms and variables that moderate the effectiveness of the intervention.
This study is characterized by a factorial design with a total of 3 factors representing Motivational Messages (M), Feedback Messages (F) and the Time Frame (T) when the message was sent, of 4, 5 and 4 levels each, respectively. One level of M and F corresponded to a control treatment, i.e., no message sent. Each participant received one different combination of M, F and T every day.
Both the adaptive and uniform random group will receive the same types of messages: feedback (4 active categories plus no message) and motivation (3 active categories plus no message). However, the message categories, timing and frequency will be optimized by a reinforcement learning algorithm in the adaptive group, and will be delivered with equal probabilities in the uniform random group (following a uniform random distribution).
For the reinforcement learner group, the algorithm training data consists of the historical data of all participants (contextual variables), which include which messages were sent previously and within which time periods, and select clinical/demographic data (such as age, day of the week and depression scores) to improve prediction abilities. Subsequently, the message is chosen based on the predicted effectiveness of messages, combined with a sampling method. As such, it frequently picks out from the most rewarding messages and occasionally explores the messages with uncertainty in their reward.
The aims of this study are:
- to assess if participants in the reinforcement learning policy show a greater increase in daily steps after six week follow-up, than participants receiving messages with a uniform random distribution
- to assess if sociodemographic, baseline physical activity behavior/attitudes and psychological factors influence the effect of the adaptive intervention.
- to assess which messages are most beneficial in increasing physical activity.
- Conditions
- Mobile Health, Physical Activity, Exercise, Mood, Machine Learning
- Being tested
- Uniform random message delivery, Reinforcement learning message delivery
- Medical subject headings
- Motor Activity
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Uniform random message deliveryBehavioural
The uniform random intervention group receives feedback and motivational messages chosen from the messaging banks with equal probabilities.
Reinforcement learning message deliveryBehavioural
The adaptive intervention group receives messages chosen from the messaging banks by a reinforcement learning algorithm.
| Study group | Role | What they receive |
|---|---|---|
| Uniform random | Active comparator | In this arm the types of messages were sent out randomly, i.e. with a uniform random distribution. Receives: 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. Receives: Behavioral: Reinforcement learning message delivery |
What is being measured
The primary outcome is the main question the study is designed to answer.
Steps (measured by phone pedometer)
Change in daily step counts (today's steps count minus yesterday's steps count)
Measured: 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
Measured: Change from baseline to 6 week follow-up
Secondary outcomes (3)
Depression scores
Patient Health Questionnaire 9 item (PHQ-9). The PHQ-9 has scores from 0 to 27. Higher scores mean a worse outcome.
Measured: Change from baseline to 6 week follow-up
Anxiety scores
General Anxiety Disorder 7 item (GAD-7). The GAD-7 has scores from 0 to 21. Higher scores mean a worse outcome.
Measured: Change from baseline to 6 week follow-up
Behavioral Activation
Behavioral Activation for Depression Scale - Short Form (BADS-SF). The BADS-SF has scores from 0-54. Higher scores mean better outcomes.
Measured: Change from baseline to 6 week follow-up
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Jun 2020
- Study start12 Sep 2019
- Primary completion10 Dec 2019
- Study completion20 Dec 2019
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Mobile HealthStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- 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.
- Masking
- Single blind
- Who is masked
- Participant
- Enrolment
- 103 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of California, Berkeley
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Adrian Aguilera, PhD, Principal investigator, University of California, Berkeley
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04440553
- Sponsor's protocol ID
- 2019-04-12118
- Status last verified
- Jun 2020
- First submitted
- 17 Jun 2020
- Last updated
- 24 Jun 2020
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Individual participant data that underlies the results reported in the articles will be made available to researchers on request after deidentification.
Publications
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.
PubMed 33871015
Study at a glance
From the registry record, last updated by the sponsor on 24 Jun 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- An mHealth App Using Adaptive Learning to Increase Physical Activity in University Students
- ClinicalTrials.gov ID
- NCT04440553
- Acronym / sponsor ID
- 2019-04-12118
- Conditions
- Mobile Health, Physical Activity, Exercise, Mood, Machine Learning
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 103 participants (actual)
- Lead sponsor
- University of California, BerkeleyUniversity, hospital or other
- Study start
- 12 Sep 2019 (actual)
- Primary completion
- 10 Dec 2019 (actual)
- Study completion
- 20 Dec 2019 (actual)
- First posted
- 19 Jun 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
The investigators developed a smartphone application, the DIAMANTE app, that uses machine learning to generate adaptive text messages, learning from daily participant data to personalize the frequency and type of motivation of messages. In the current study, the investigators will compare this application in undergraduate and graduate students at the University of Berkeley, to text-messaging chosen randomly. This study will provide insight into the effectiveness of this smartphone application for increasing physical activity in university students. Further, it will provide preliminary knowledge on the working mechanisms and variables that moderate the effectiveness of the intervention.
This study is characterized by a factorial design with a total of 3 factors representing Motivational Messages (M), Feedback Messages (F) and the Time Frame (T) when the message was sent, of 4, 5 and 4 levels each, respectively. One level of M and F corresponded to a control treatment, i.e., no message sent. Each participant received one different combination of M, F and T every day.
Both the adaptive and uniform random group will receive the same types of messages: feedback (4 active categories plus no message) and motivation (3 active categories plus no message). However, the message categories, timing and frequency will be optimized by a reinforcement learning algorithm in the adaptive group, and will be delivered with equal probabilities in the uniform random group (following a uniform random distribution).
For the reinforcement learner group, the algorithm training data consists of the historical data of all participants (contextual variables), which include which messages were sent previously and within which time periods, and select clinical/demographic data (such as age, day of the week and depression scores) to improve prediction abilities. Subsequently, the message is chosen based on the predicted effectiveness of messages, combined with a sampling method. As such, it frequently picks out from the most rewarding messages and occasionally explores the messages with uncertainty in their reward.
The aims of this study are:
- to assess if participants in the reinforcement learning policy show a greater increase in daily steps after six week follow-up, than participants receiving messages with a uniform random distribution
- to assess if sociodemographic, baseline physical activity behavior/attitudes and psychological factors influence the effect of the adaptive intervention.
- to assess which messages are most beneficial in increasing physical activity.
Study design
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (participant)
- Number of arms
- 2
- Model description
- 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.
| Arm | Type | Receives |
|---|---|---|
| Uniform random | Active comparator | Behavioral: Uniform random message deliveryIn this arm the types of messages were sent out randomly, i.e. with a uniform random distribution. |
| Reinforcement learning | Experimental | Behavioral: Reinforcement learning message deliveryIn 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. |
Who may qualify
- Ages
- 18 to 65 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Uniform random message deliveryThe uniform random intervention group receives feedback and motivational messages chosen from the messaging banks with equal probabilities. | Behavioural | Uniform random |
| Reinforcement learning message deliveryThe adaptive intervention group receives messages chosen from the messaging banks by a reinforcement learning algorithm. | Behavioural | Reinforcement learning |
Primary outcome
Steps (measured by phone pedometer)
Time frame: 24 hours (measured for a period of 6 weeks)
Change in daily step counts (today's steps count minus yesterday's steps count)
Steps (measured by phone pedometer)
Time frame: Change from baseline to 6 week follow-up
Mean change in daily step counts during the course of the study
3 secondary outcomes
Depression scores
Time frame: Change from baseline to 6 week follow-up
Anxiety scores
Time frame: Change from baseline to 6 week follow-up
Behavioral Activation
Time frame: Change from baseline to 6 week follow-up
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Jun 2020.
- Derived from this study: PubMed 33871015Figueroa 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.
- Individual participant dataSharing planned: Yes. Individual participant data that underlies the results reported in the articles will be made available to researchers on request after deidentification.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Adrian Aguilera, PhD principal investigator
University of California, Berkeley
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Uniform random message delivery and Reinforcement learning message delivery in people with Mobile Health and Physical Activity, run by University of California, Berkeley at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 24 Jun 2020. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Steps (measured by phone pedometer) (time frame: 24 hours (measured for a period of 6 weeks)). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04440553, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Jun 2020.