LifestyleBSAK19NCT05264155
Evaluation of the Impact of Adaptive Goal Setting on Engagement Levels of Government Staff With a Gamified mHealth Tool
A study testing GameBus (mHealth app) in people with Lifestyle and Lifestyle, Healthy, run by Eindhoven University of Technology at 1 site in Belgium.
Trial summary
Background: Although the health benefits of physical activity are well established, it remains challenging for people to adopt a more active lifestyle. Mobile health (mHealth) interventions can be effective tools to promote physical activity and reduce sedentary behavior. Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Lifestyle, Lifestyle, Healthy, Lifestyle, Sedentary
- What is being tested?
- GameBus (mHealth app)
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- Yes, some participants may receive a placebo
- How many people
- 176 participants
- Where
- 1 siteBelgium
- Study dates
- 14 Oct 2019to 16 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 Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Who may be able to join
- Employee of Noorderkempen governmental organization
Who cannot join
- None
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Evaluating the Impact of Adaptive Personalized Goal Setting on Engagement Levels of Government Staff With a Gamified mHealth Tool: Study Protocol for a 2-Month Randomized Controlled Trial
Background: Although the health benefits of physical activity are well established, it remains challenging for people to adopt a more active lifestyle. Mobile health (mHealth) interventions can be effective tools to promote physical activity and reduce sedentary behavior. Promising results have been obtained by using gamification techniques as behavior change strategies, especially when they were tailored toward an individual's preferences and goals; yet, it remains unclear how goals could be personalized to effectively promote health behaviors.
Objective: In this study, the investigators aim to evaluate the impact of personalized goal setting in the context of gamified mHealth interventions. The investigators hypothesize that interventions suggesting health goals that are tailored based on end users' (self-reported) current and desired capabilities will be more engaging than interventions with generic goals.
Read more
Methods: The study was designed as a 2-arm randomized intervention trial. Participants were recruited among staff members of Noorderkempen governmental organization. They participated in an 8-week digital health promotion campaign that was especially designed to promote walks, bike rides, and sports sessions. Using an mHealth app, participants could track their performance on two social leaderboards: a leaderboard displaying the individual scores of participants and a leaderboard displaying the average scores per organizational department. The mHealth app also provided a news feed that showed when other participants had scored points. Points could be collected by performing any of the 6 assigned tasks (eg, walk for at least 2000 m). The level of complexity of 3 of these 6 tasks was updated every 2 weeks by changing either the suggested task intensity or the suggested frequency of the task. The 2 intervention arms-with participants randomly assigned-consisted of a personalized treatment that tailored the complexity parameters based on participants' self-reported capabilities and goals and a control treatment where the complexity parameters were set generically based on national guidelines. Measures were collected from the mHealth app as well as from intake and posttest surveys and analyzed using hierarchical linear models.
Note: Eindhoven University of Technology is not an official GCP sponsor. Hence, this study is not a medical clinical trial.
- Being tested
- GameBus (mHealth app)
- Keywords
- Promoting Healthier Lifestyles, mHealth
- Medical subject headings
- Sedentary Behavior, Risk Reduction Behavior
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
GameBus (mHealth app)Behavioural
Using the mHealth app GameBus, participants could track their performance on 2 social leaderboards: a leaderboard displaying the individual scores of participants and a leaderboard displaying the average scores per department. To score points on these leaderboards, a participant was given a set of 6 tasks that, upon completion, were rewarded with points. In this study, 3/6 tasks were either updated generically (for the control group) or personalized (for the treatment group). By means of the mobile app, users could manually register that they had performed a task. Alternatively, users could use an activity tracker to automatically track their efforts. The activity trackers that were supported included Google Fit, Strava, and a GPS-based activity tracker. Finally, GameBus provided a set of features for social support: a newsfeed showed when other participants had scored points, and participants could like and comment on each other's healthy achievements as well as chat with each other.
| Study group | Role | What they receive |
|---|---|---|
| Control: one-size-fits-all | Placebo comparator | The study was designed as a 2-arm randomized intervention trial. The experimental setup was centered around setting the complexity parameters (ie, the X values) of the 3 dynamic tasks. In particular, the parameters to determine were as follows: (1) the minimum distance of a longer walk, (2) the minimum distance of a longer bike ride, and (3) the maximum number of rewarded sports sessions (and consequently the number of rewarded points per sports session).
For the control group, the parameter values of the dynamic tasks were based on national guidelines. Receives: Behavioral: GameBus (mHealth app) |
| Treatment: personalized | Active comparator | The study was designed as a 2-arm randomized intervention trial. The experimental setup was centered around setting the complexity parameters (ie, the X values) of the 3 dynamic tasks. In particular, the parameters to determine were as follows: (1) the minimum distance of a longer walk, (2) the minimum distance of a longer bike ride, and (3) the maximum number of rewarded sports sessions (and consequently the number of rewarded points per sports session).
For the treatment group, these parameters were tailored to the users' self-reported capabilities and health goals. Receives: Behavioral: GameBus (mHealth app) |
What is being measured
The primary outcome is the main question the study is designed to answer.
Passive user engagement
Number of days participants visited in the app.
Measured: one week.
Active user engagement
Number of health-related activities participants visited in the app.
Measured: one week.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 Mar 2022
- Study start14 Oct 2019
- Primary completion16 Dec 2019
- Study completion16 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 LifestyleStudies 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
- Masking
- None (open label)
- Enrolment
- 176 participants (actual)
Sponsor and investigators
- Lead sponsor
- Eindhoven University of Technology
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Pieter Van Gorp, Dr., Principal investigator, Eindhoven University of Technology
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05264155
- Sponsor's protocol ID
- BSAK19
- Acronym
- BSAK19
- Status last verified
- Mar 2022
- First submitted
- 22 Feb 2022
- Last updated
- 22 Mar 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Nuijten R, Van Gorp P, Khanshan A, Le Blanc P, van den Berg P, Kemperman A, Simons M. Evaluating the Impact of Adaptive Personalized Goal Setting on Engagement Levels of Government Staff With a Gamified mHealth Tool: Results From a 2-Month Randomized Controlled Trial. JMIR Mhealth Uhealth. 2022 Mar 31;10(3):e28801. doi: 10.2196/28801.
PubMed 35357323
Study at a glance
From the registry record, last updated by the sponsor on 22 Mar 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluating the Impact of Adaptive Personalized Goal Setting on Engagement Levels of Government Staff With a Gamified mHealth Tool: Study Protocol for a 2-Month Randomized Controlled Trial
- ClinicalTrials.gov ID
- NCT05264155
- Acronym / sponsor ID
- BSAK19 / BSAK19
- Keywords
- Promoting Healthier Lifestyles, mHealth
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 176 participants (actual)
- Lead sponsor
- Eindhoven University of TechnologyUniversity, hospital or other
- Study start
- 14 Oct 2019 (actual)
- Primary completion
- 16 Dec 2019 (actual)
- Study completion
- 16 Dec 2019 (actual)
- First posted
- 3 Mar 2022 (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: Although the health benefits of physical activity are well established, it remains challenging for people to adopt a more active lifestyle. Mobile health (mHealth) interventions can be effective tools to promote physical activity and reduce sedentary behavior. Promising results have been obtained by using gamification techniques as behavior change strategies, especially when they were tailored toward an individual's preferences and goals; yet, it remains unclear how goals could be personalized to effectively promote health behaviors.
Objective: In this study, the investigators aim to evaluate the impact of personalized goal setting in the context of gamified mHealth interventions. The investigators hypothesize that interventions suggesting health goals that are tailored based on end users' (self-reported) current and desired capabilities will be more engaging than interventions with generic goals.
Methods: The study was designed as a 2-arm randomized intervention trial. Participants were recruited among staff members of Noorderkempen governmental organization. They participated in an 8-week digital health promotion campaign that was especially designed to promote walks, bike rides, and sports sessions. Using an mHealth app, participants could track their performance on two social leaderboards: a leaderboard displaying the individual scores of participants and a leaderboard displaying the average scores per organizational department. The mHealth app also provided a news feed that showed when other participants had scored points. Points could be collected by performing any of the 6 assigned tasks (eg, walk for at least 2000 m). The level of complexity of 3 of these 6 tasks was updated every 2 weeks by changing either the suggested task intensity or the suggested frequency of the task. The 2 intervention arms-with participants randomly assigned-consisted of a personalized treatment that tailored the complexity parameters based on participants' self-reported capabilities and goals and a control treatment where the complexity parameters were set generically based on national guidelines. Measures were collected from the mHealth app as well as from intake and posttest surveys and analyzed using hierarchical linear models.
Note: Eindhoven University of Technology is not an official GCP sponsor. Hence, this study is not a medical clinical trial.
Study design
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Control: one-size-fits-all | Placebo comparator | Behavioral: GameBus (mHealth app)The study was designed as a 2-arm randomized intervention trial. The experimental setup was centered around setting the complexity parameters (ie, the X values) of the 3 dynamic tasks. In particular, the parameters to determine were as follows: (1) the minimum distance of a longer walk, (2) the minimum distance of a longer bike ride, and (3) the maximum number of rewarded sports sessions (and consequently the number of rewarded points per sports session). For the control group, the parameter values of the dynamic tasks were based on national guidelines. |
| Treatment: personalized | Active comparator | Behavioral: GameBus (mHealth app)The study was designed as a 2-arm randomized intervention trial. The experimental setup was centered around setting the complexity parameters (ie, the X values) of the 3 dynamic tasks. In particular, the parameters to determine were as follows: (1) the minimum distance of a longer walk, (2) the minimum distance of a longer bike ride, and (3) the maximum number of rewarded sports sessions (and consequently the number of rewarded points per sports session). For the treatment group, these parameters were tailored to the users' self-reported capabilities and health goals. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (1 listed)
- Employee of Noorderkempen governmental organization
Key exclusion criteria (1 listed)
- None
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 |
|---|---|---|
| GameBus (mHealth app)Using the mHealth app GameBus, participants could track their performance on 2 social leaderboards: a leaderboard displaying the individual scores of participants and a leaderboard displaying the average scores per department. To score points on these leaderboards, a participant was given a set of 6 tasks that, upon completion, were rewarded with points. In this study, 3/6 tasks were either updated generically (for the control group) or personalized (for the treatment group). By means of the mobile app, users could manually register that they had performed a task. Alternatively, users could use an activity tracker to automatically track their efforts. The activity trackers that were supported included Google Fit, Strava, and a GPS-based activity tracker. Finally, GameBus provided a set of features for social support: a newsfeed showed when other participants had scored points, and participants could like and comment on each other's healthy achievements as well as chat with each other. | Behavioural | Control: one-size-fits-all, Treatment: personalized |
Primary outcome
Passive user engagement
Time frame: one week.
Number of days participants visited in the app.
Active user engagement
Time frame: one week.
Number of health-related activities participants visited in the app.
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 22 Mar 2022.
- Derived from this study: PubMed 35357323Nuijten R, Van Gorp P, Khanshan A, Le Blanc P, van den Berg P, Kemperman A, Simons M. Evaluating the Impact of Adaptive Personalized Goal Setting on Engagement Levels of Government Staff With a Gamified mHealth Tool: Results From a 2-Month Randomized Controlled Trial. JMIR Mhealth Uhealth. 2022 Mar 31;10(3):e28801. doi: 10.2196/28801.
- Individual participant dataSharing planned: No
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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.
Pieter Van Gorp, Dr. principal investigator
Eindhoven University of Technology
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing GameBus (mHealth app) in people with Lifestyle and Lifestyle, Healthy, run by Eindhoven University of Technology at 1 site in Belgium.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. 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 22 Mar 2022. 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 Belgium. 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. Some participants in this study may receive a placebo. 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?
Passive user engagement (time frame: one week.). 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 NCT05264155, 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 22 Mar 2022.