Evidence map›Paper›PMID 40418819›Full record

ArticleJMIR human factors2025

Using Personalized Intervention Criteria in a Mobile Just-in-Time Adaptive Intervention for Increasing Physical Activity in University Students: Pilot Study.

Mai Ikegaya, Jerome Clifford Foo, Taiga Murata, Kenta Oshima, Jinhyuk Kim

Abstract read
In one paragraph

Article in JMIR human factors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

5 authors.

Mai IkegayaDepartment of Informatics, Graduate School of Integrated Science and Technology, Shizuoka University, 3-5-1 Johoku, Chuo-ku, Hamamatsu, Shizuoka, 432-8011, Japan, 81 53-478-1526.ORCID 0009-0007-9988-3737
Jerome Clifford FooDepartment of Psychiatry, College of Health Sciences, University of Alberta, Edmonton, AB, Canada.ORCID 0000-0003-1067-5725
Taiga MurataDepartment of Informatics, Graduate School of Integrated Science and Technology, Shizuoka University, 3-5-1 Johoku, Chuo-ku, Hamamatsu, Shizuoka, 432-8011, Japan, 81 53-478-1526.ORCID 0009-0003-5314-6927
Kenta OshimaDepartment of Informatics, Graduate School of Integrated Science and Technology, Shizuoka University, 3-5-1 Johoku, Chuo-ku, Hamamatsu, Shizuoka, 432-8011, Japan, 81 53-478-1526.ORCID 0009-0006-8742-6144
Jinhyuk KimDepartment of Informatics, Graduate School of Integrated Science and Technology, Shizuoka University, 3-5-1 Johoku, Chuo-ku, Hamamatsu, Shizuoka, 432-8011, Japan, 81 53-478-1526.ORCID 0000-0003-4218-1631

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: While the health benefits of physical activity are well-known, adherence to regular physical activity remains a major challenge. Just-in-time adaptive intervention (JITAI) has been proposed as one method to increase physical activity by delivering an intervention at a time when individuals are more likely to make behavioral changes. However, most studies that have implemented JITAI have used uniform intervention criteria (UIC) across participants rather than personalized intervention criteria (PIC) for the individual. Objective: The objective of this paper was to examine the effectiveness of using JITAI implemented with PIC to increase physical activity. Methods: Healthy university students wore a wrist activity monitor for 2 weeks. Participants were divided into 2 groups, which received JITAI to promote physical activity according to either PIC or UIC. In the first week, the mean distance moved and sedentary time per hour for each participant were calculated to derive PIC. UIC was obtained from a 2-week study with a different sample (n=47) conducted under the same conditions. In the second week, JITAI prompts were sent every hour if both of the following criteria were met: the distance moved was shorter, and sedentary time was longer than PIC or UIC. Differences in changes in physical activity as a result of implementing interventions according to PIC and UIC were analyzed using multilevel models. Results: We analyzed data from 28 healthy university students (18-23 y old, female n=12). Both PIC (P<.001) and UIC (P<.001) significantly increased physical activity in the first hour after JITAI was received. In that first hour, PIC increased physical activity more than UIC; more calories were burned (P=.02), more steps were taken (P=.007), and distance moved was increased (P=.003). However, over the course of the week, the use of JITAI did not significantly increase physical activity levels. Conclusions: Our results appear to suggest that PIC-based JITAI is more effective than UIC-based JITAI, consistent with the idea of a need for precision health approaches. Further research is needed to develop effective long-term intervention designs with sustainable effects.

Indexed as

ExerciseHealth PromotionStudentsAdolescentAdultFemaleHumansMalePilot ProjectsUniversitiesYoung Adultactivity monitoractivity monitoringactivity trackerbehavioral changechronic diseaseconsumer-wearable activity trackersdigital healtheffectivenessjust-in-time adaptive interventionlong-term interventionmHealthmobile healthmobile phonemultilevel modelphysical activitypreventionsmartphonetreatmentwearable

Identifiers

PMID40418819
PMCPMC12129369

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.