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.
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.
What it found
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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.
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
Who cites it
15 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- 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 · 2025Pooled it
- Design Features Associated With Engagement in Mobile Health Physical Activity Interventions Among Youth: Systematic Review of Qualitative and Quantitative Studies.JMIR mHealth and uHealth · 2023Pooled it
- Potential associations between behavior change techniques and engagement with mobile health apps: a systematic review.Frontiers in psychology · 2023Pooled it
- Everyday Digital Support to Promote Health and Literacy Among Older Adults: 14-Week Randomized Digital Pilot Trial by Engagement Level.JMIR formative research · 2025Trial
- Gamification Elements in Physical Activity Interventions: Scoping Review and Taxonomy Based on the Octalysis Framework.JMIR serious games · 2026Review
- Sleep-inducing algorithms: can artificial intelligence help shiftworkers and those working nonstandard hours sleep better?Sleep advances : a journal of the Sleep Research Society · 2026Article
- Relationship between sedentary time and cognitive decline in hypertensive patients-mediating role of the weight-adjusted waist circumference index.Scientific reports · 2025Article
- Moving Beyond One-Size-Fits-All: Charting a Path to Personalized Nonpharmacological and Noninvasive Chronic Pain Management.Journal of pain research · 2025Article
- Personal Goals, User Engagement, and Meal Adherence within a Personalised AI-Based Mobile Application for Nutrition and Physical Activity.Life (Basel, Switzerland) · 2024Article
- Attraction and achievement as 2 attributes of gamification in healthcare: an evolutionary concept analysisJournal of educational evaluation for health professions · 2024Review
- Advantages and disadvantages of mobile applications for workplace health promotion: A scoping review.PloS one · 2024Article
- Impact of a comprehensive cardiac rehabilitation programme versus coronary revascularisation in patients with stable angina pectoris: study protocol for the PRO-FIT randomised controlled trial.BMC cardiovascular disorders · 2023Article
- Personal Goals, Barriers to Self-Management and Desired mHealth Application Features to Improve Self-Care in Multi-Ethnic Asian Patients with Type 2 Diabetes: A Qualitative Study.International journal of environmental research and public health · 2022Article
- Assessing the Influence of Physical Activity Upon the Experience Sampling Response Rate on Wrist-Worn Devices.International journal of environmental research and public health · 2021Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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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.