Evidence map›Paper›PMID 35357323›Full record

Trial reportJMIR mHealth and uHealth2022

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.

Raoul Nuijten, Pieter Van Gorp, Alireza Khanshan, Pascale Le Blanc, Pauline van den Berg, Astrid Kemperman, Monique Simons

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in JMIR mHealth and uHealth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05264155 (Evaluating the Impact of Adaptive Personalized Goal Setting on Engagement Levels of Government Staff With a Gamified mHealth Tool), which is not on this map. Cited by 15 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05264155 nacompletednot on this map

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

TypeinterventionalSponsorEindhoven University of TechnologyRan2019 to 2019Enrolled176ConditionsLifestyle, Lifestyle, Healthy, Lifestyle, Sedentary, Lifestyle Risk ReductionArmsGameBus (mHealth app)
3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Evaluation of temporomandibular disorder self-management apps in Australia: a systematic review to inform clinical use.International journal for quality in health care : journal of the International Society for Quality in Health Care · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Raoul NuijtenDepartment of Industrial Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.ORCID 0000-0003-0125-7708
Pieter Van GorpDepartment of Industrial Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.ORCID 0000-0001-5197-3986
Alireza KhanshanDepartment of Industrial Design, Eindhoven University of Technology, Eindhoven, Netherlands.ORCID 0000-0002-9112-4695
Pascale Le BlancDepartment of Industrial Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.ORCID 0000-0003-4693-9980
Pauline van den BergDepartment of the Built Environment, Eindhoven University of Technology, Eindhoven, Netherlands.ORCID 0000-0003-1712-5873
Astrid KempermanDepartment of the Built Environment, Eindhoven University of Technology, Eindhoven, Netherlands.ORCID 0000-0002-1312-4913
Monique SimonsDepartment of Social Sciences, Wageningen University and Research, Wageningen, Netherlands.ORCID 0000-0002-6475-4616

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough 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.

objectiveIn this study, we aim to evaluate the impact of personalized goal setting in the context of gamified mHealth interventions. We 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.

methodsThe study was designed as a 2-arm randomized intervention trial. Participants were recruited among staff members of 7 governmental organizations. 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.

resultsThe results indicated that engagement with the program inevitably dropped over time. However, engagement was higher for participants who had set themselves a goal in the intake survey. The impact of personalization was especially observed for frequency parameters because the personalization of sports session frequency did foster higher engagement levels, especially when participants set a goal to improve their capabilities. In addition, the personalization of suggested ride duration had a positive effect on self-perceived biking performance.

conclusionsPersonalization seems particularly promising for promoting the frequency of physical activity (eg, promoting the number of suggested sports sessions per week), as opposed to the intensity of the physical activity (eg, distance or duration). Replications and variations of our study setup are critical for consolidating and explaining (or refuting) these effects.

trial registrationClinicalTrials.gov NCT05264155; https://clinicaltrials.gov/ct2/show/NCT05264155.

Indexed as

Health PromotionTelemedicineExerciseGoalsGovernmentHumansadaptive goal settinggamificationhealth promotionmHealthoffice workerspersonalizationphysical activity

Identifiers

PMID35357323
PMCPMC9015741

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.