Evidence map›Paper›PMID 42616576›Full record

ArticleJMIR human factors2026

Exploring Response Patterns to Motivational Messages Supporting Physical Activity: Latent Class Analysis.

Chihiro Moriishi, Takeyuki Oba, Keisuke Takano, Kentaro Katahira, Kenta Kimura

Abstract read
In one paragraph

Article in JMIR human factors, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

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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

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

5 authors.

Chihiro Moriishi *Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, Ibaraki, Japan.ORCID 0000-0002-3594-906X
Takeyuki Oba *Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, Ibaraki, Japan.ORCID 0000-0002-9075-2622
Keisuke TakanoHuman Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, Ibaraki, Japan.ORCID 0000-0003-0406-8654
Kentaro KatahiraHuman Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, Ibaraki, Japan.ORCID 0000-0002-2018-3938
Kenta KimuraHuman Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, Ibaraki, Japan.ORCID 0000-0003-2385-2081

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn mobile health care, text messages play an important role in improving physical activity. Recent studies have developed message banks based on theories, including the behavior change technique (BCT) taxonomy. However, little evidence is available for individual differences (ie, who responds to which BCTs presented in messages), which is crucial for optimizing message delivery.

objectiveWe investigated how individuals perceive messages supporting physical activity and what clusters of individuals are identified by their responses.

methodsJapanese-speaking adults (n=2859; mean age 54.5, SD 17.5 years; 1486 women) were presented with messages conveying different BCTs and rated how motivational each message was. The motivation ratings were subjected to latent class analysis to identify clusters of individuals per motivation rating.

resultsA total of 7 clusters were identified. Two clusters gave consistently high ratings across BCT types; one showed a general receptivity to all messages, while the other showed a clearer preference for information-based BCTs. Two clusters showed moderate ratings, both preferring information about consequences but differing in their additional preferences for goal setting vs rewards. Two clusters gave overall low ratings and typically included less active individuals in the preaction stages, both showing a preference for information-based BCTs. The remaining cluster showed the greatest variability in BCT preferences, with the strongest preference for salience of consequences.

conclusionsThese results highlight individual differences in perceived motivations across BCTs, informing what BCTs should be prioritized in delivery. The practical implications for message tailoring are also discussed.

Indexed as

ExerciseMotivationText MessagingAdultAgedFemaleHumansLatent Class AnalysisMaleMiddle Agedbehavior change techniqueclustering algorithmdigital healthphysical activitytext message

Identifiers

PMID42616576
PMCPMC13539174

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.