Evidence map›Paper›PMID 40673359›Full record

Trial reportJournal of occupational health2025

Effectiveness of recommendations in promoting the use of mobile health applications in health guidance: a randomized controlled trial.

Takeshi Onoue, Kazuki Nishida, Yoshio Nakata, Fumi Hayashi, Miki Marutani, Naoki Sakane, Jiro Moriguchi, Shigeki Muto, Kiminori Kato, Izuru Masuda and 4 more

Abstract readRandomized Controlled TrialMulticenter Study
In one paragraph

Trial report in Journal of occupational health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

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. Article
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

14 authors.

Takeshi OnoueDepartment of Endocrinology and Diabetes, Nagoya University Graduate School of Medicine, Nagoya, Japan.ORCID 0000-0002-8589-9937
Kazuki NishidaDepartment of Advanced Medicine, Nagoya University Hospital, Nagoya, Japan.ORCID 0000-0003-0367-8557
Yoshio NakataInstitute of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan.ORCID 0000-0002-0888-4440
Fumi HayashiGraduate School of Nutrition Sciences, Kagawa Nutrition University, Saitama, Japan.ORCID 0000-0002-3422-0138
Miki MarutaniDepartment of Health Promotion, National Institute of Public Health, Saitama, Japan.ORCID 0000-0002-4786-3167
Naoki SakaneDivision of Preventive Medicine, Clinical Research Institute for Endocrine and Metabolic Disease, National Hospital Organization, Kyoto Medical Center, Kyoto, Japan.ORCID 0000-0002-2625-571X
Jiro MoriguchiOccupational Health Research Center, Kyoto Industrial Health Association, Kyoto, Japan.
Shigeki MutoDepartment of Health Care, Seirei Center for Health Promotion and Preventive Medicine, Hamamatsu, Japan.
Kiminori KatoDepartment of Prevention of Noncommunicable Diseases and Promotion of Health Checkup, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan.
Izuru MasudaNingen Dock Center, Mitsubishi Kyoto Hospital, Kyoto, Japan.
Tomonori OkamuraDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan.ORCID 0000-0003-0488-0351
Keiichi MatsuzakiDepartment of Public Health, Kitasato University School of Medicine, Kanagawa, Japan.ORCID 0000-0002-2113-1574
Takashi KawamuraDepartment of Preventive Services, Kyoto University School of Public Health, Kyoto, Japan.ORCID 0000-0002-4539-1338
Kazuyo TsushitaGraduate School of Nutrition Sciences, Kagawa Nutrition University, Saitama, Japan.ORCID 0000-0002-5755-9345

Funding

Japan Agency for Medical Research and Development (AMED)
6 · The paper itself

Abstract

objectivesUse of commercially available mobile health (mHealth) applications in supporting lifestyle improvements has become popular in recent years. However, the effectiveness of advice promoting the use of such applications based on individual behavioral goals in a health guidance setting remains unclear. This study explored how guiding participants of the Specific Health Guidance (SHG) program, a Japanese public health initiative to prevent cardiovascular disease, to use commercially available mHealth applications impacted their application usage, lifestyle habits, and cardiovascular risk factors.

methodsIn this multicenter, randomized, open-label, parallel-group comparison study, 156 individuals with a history of SHG participation and who were engaged in the Motivational Health Guidance program (a type of SHG) in 2021 were assigned to intervention (n = 76) or control (n = 80) groups. Whereas both groups received standard guidance, the intervention group also received recommendations for mHealth applications based on their individual behavioral goals. The participants' application usage, behavioral changes, and body weight were assessed after 3 months, with health checkup data evaluated after 1 year.

resultsThe proportion of mHealth application users after 3 months was significantly higher in the intervention group (68.4%) than in the control group (40.0%). The intervention group also reported a significantly greater weekly frequency of mHealth application usage. Moreover, the intervention group reported a significantly decreased change in triglyceride levels after 1 year compared with the control group.

conclusionsRecommending commercially available mHealth applications in a health guidance setting significantly increased the number of mHealth application users and their frequency of use.

Indexed as

Cardiovascular DiseasesHealth PromotionMobile ApplicationsTelemedicineAdultAgedFemaleHealth BehaviorHumansJapanLife StyleMaleMiddle AgedMotivationhealth guidancemetabolic syndromemobile health applicationobesitysmartphone application

Identifiers

PMID40673359
PMCPMC12321321

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.