Evidence map›Paper›PMID 41680943›Full record

ArticleJournal of activity, sedentary and sleep behaviors2026

MOVE@NUS digital intervention cohort: protocol of a pilot study to promote healthy movement in university students.

Mingyue Chen, Madlene Movia, Xin Hui Chua, Sarah Yi Xuan Tan, Shenglin Zheng, Kaiyi Jin, Thitikorn Topothai, Natarajan Padmapriya, Falk Müller-Riemenschneider, Sarah Edney

Registry-linked trialAbstract read
In one paragraph

Article in Journal of activity, sedentary and sleep behaviors, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06597890 (Move@NUS), which is not on this map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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.

NCT06597890 nanot yet recruitingnot on this map

Move@NUS: Pilot Study of a Digital Intervention Cohort to Promote Healthy Sleep, Screen Viewing, and Physical Activity Habits for Improved Health and Wellbeing

TypeinterventionalSponsorNational University of SingaporeRan2024 to 2025Enrolled150ConditionsPhysical Inactivity, Sedentary Behavior, Sleep Insufficiency, Well-Being, PsychologicalArmseducational content (sleep hygiene), sleep hygiene strategies, reminders, review of behavioural goal, educational content (sleep guidelines)
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Mingyue ChenSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Madlene MoviaSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Xin Hui ChuaSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Sarah Yi Xuan TanSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Shenglin ZhengSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Kaiyi JinSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Thitikorn TopothaiSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Natarajan PadmapriyaSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Falk Müller-Riemenschneider *Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore. ephmf@nus.edu.sg.
Sarah Edney *Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.

Funding

Physical Activity and Nutrition Determinants in Asia (PANDA) Research Program A-0006101-00-00
6 · The paper itself

Abstract

introductionDue to academic pressures and irregular schedules, university students often face challenges in maintaining healthy movement behaviours (including sleep, physical activity, and screen time), which are interrelated and influence both physical and mental health. Smartwatch- and smartphone-based ecological momentary assessments (EMAs) and ecological momentary interventions (EMIs) offer real-time, context-aware strategies to promote movement behaviours. This pilot study aims to assess the feasibility and preliminary effectiveness of a hybrid approach that combines continuous digital monitoring of movement behaviours with sequentially embedded randomised controlled trials (RCTs) evaluating EMIs. METHODS/

designMOVE@NUS pilot study employed a five-month hybrid design that combines continuous passive monitoring (primarily via Apple Watches, supplemented by iPhones) with three embedded RCTs targeting sleep (RCT-1), physical activity (RCT-2), and screen time (RCT-3). For each RCT, participants are randomised on a 1:1:1 schedule (control, intervention 1, intervention 2). Eligible participants are first-year undergraduates at the National University of Singapore, aged 18-25 years, who own or regularly use an iPhone and an Apple Watch. EMIs, delivered via the study app, comprise standard health messages or personalised reminders based on HealthKit data or participants' self-reported behaviours and preferences. Self-reported measures include eight EMA bursts (three-day periods every two weeks) and online questionnaires at baseline, midway (2.5 months), and endpoint (5 months). All EMIs and EMAs are text-based and can be completed in under two minutes. Feasibility outcomes include recruitment, engagement, and user experience assessed through quantitative surveys and semi-structured interviews. Preliminary effectiveness will be explored separately for each RCT, comparing movement behaviours between intervention and control groups. DISCUSSION: Findings from this study will inform the development of scalable and longer-term digital intervention cohorts for promoting healthier lifestyles among university students. Furthermore, as university students soon transition to the workforce, insights gained will inform scalable digital health interventions for broader populations.

trial registrationClinicalTrials.gov ID NCT06597890 First Posted: 19 September 2024.

Indexed as

Ambulatory assessmentBehaviour changeDigital health technologyHealth trackingJust-in-time adaptive interventionMhealthMobile interventionMobile phoneReal-time monitoringWearable sensors

Identifiers

PMID41680943
PMCPMC13005513

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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.