Evidence map›Paper›PMID 37938885›Full record

ArticleJMIR formative research2023

The Efficacy of an mHealth App in Facilitating Weight Loss Among Japanese Fitness Center Members: Regression Analysis Study.

Akifumi Eguchi, Yumi Kawamura, Takayuki Kawashima, Cyrus Ghaznavi, Keiko Ishimura, Shun Kohsaka, Satoru Matsuo, Shinichiro Mizuno, Yuki Sasaki, Arata Takahashi and 4 more

Open access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.6field-weighted citation impact, top 10% of its field
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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Trial
  2. 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 at 5 institutions in 2 countries.

Akifumi Eguchi *Center for Preventive Medical Sciences, Chiba University, Chiba, Japan.ORCID https://orcid.org/0000-0001-5858-8132
Yumi Kawamura *Department of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan.ORCID https://orcid.org/0000-0001-8386-4645
Takayuki Kawashima *Department of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan.ORCID https://orcid.org/0000-0003-2245-126X
Cyrus GhaznaviDepartment of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan.ORCID https://orcid.org/0000-0002-5942-1948
Keiko IshimuraLink & Communication Inc, Tokyo, Japan.ORCID https://orcid.org/0000-0001-6794-5867
Shun KohsakaDepartment of Cardiology, School of Medicine, Keio University, Tokyo, Japan.ORCID https://orcid.org/0000-0003-3779-2972
Satoru MatsuoCommunication Design Division, RENAISSANCE INC, Tokyo, Japan.ORCID https://orcid.org/0009-0007-6548-6346
Shinichiro MizunoLink & Communication Inc, Tokyo, Japan.ORCID https://orcid.org/0009-0004-8485-9791
Yuki SasakiLink & Communication Inc, Tokyo, Japan.ORCID https://orcid.org/0000-0001-9119-643X
Arata TakahashiDepartment of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan.ORCID https://orcid.org/0000-0002-1056-1480
Yuta TanoueDepartment of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan.ORCID https://orcid.org/0000-0002-0005-0468
Daisuke YoneokaCenter for Surveillance, Immunization, and Epidemiologic Research, National Institute of Infectious Diseases, Tokyo, Japan.ORCID https://orcid.org/0000-0002-3525-5092
Hiroaki MiyataDepartment of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan.ORCID https://orcid.org/0009-0008-9620-6922
Shuhei NomuraDepartment of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan.ORCID https://orcid.org/0000-0002-2963-7297
Keio University · JPChiba University · JPNational Institute of Infectious Diseases · JPTokyo Institute of Technology · JPUniversity of California, San Francisco · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSelf-tracking smartphone apps have emerged as promising tools to encourage healthy behaviors. In this longitudinal study, we used gym use data from members of a major fitness club that operates gyms throughout Japan from January 2014 to December 2019.

objectiveOur objective was to assess the extent to which a health and fitness self-tracking mobile app introduced to gym members on January 1, 2018, contributed to their weight loss. The app allows users to input information regarding diet, sleep, weight, and gym exercise so that they can receive personalized feedback from an artificial intelligence chatbot to improve their health behaviors.

methodsWe used linear regression to quantify the association between app use and weight loss. The primary outcome of the study was the weight loss achieved by each gym user, which was calculated as the difference between their initial and final weights in kilograms, as recorded in the app. Individuals who did not attend the gym or failed to use the mobile app at least twice during the study period were excluded from the analysis. The model accounted for age, gender, distance between the gym and the member's residence, average weekly number of times a member used the gym, user's gym membership length in weeks, average weekly number of times a member input information into the app, and the number of weeks that the app was used at least once.

resultsData from 26,589 participants were analyzed. Statistically significant associations were detected between weight loss and 2 metrics related to app use: the average weekly frequency of use and the total number of weeks in which the app was used at least once. One input per week was found to be associated with a loss of 62.1 (95% CI 53.8-70.5) g, and 1 week of app use was associated with 21.7 (95% CI 20.5-22.9) g of weight loss from the day of the first input to that of the final input to the app. Furthermore, the average number of times that a member used the gym weekly was also shown to be statistically significantly associated with weight loss: 1 use per week was associated with 255.5 (95% CI 228.5-282.6) g of weight loss.

conclusionsThis empirical study demonstrated a significant association between weight loss among gym members and not only the frequency of weekly gym use but also the use of a health and fitness self-tracking app. However, further work is needed to examine the mechanisms through which mobile apps affect health behaviors and to identify the specific app features that are most effective in promoting weight loss.

Indexed as

digital healthgym attendanceJapanreal-world datasmartphone applicationweight loss

Identifiers

PMID37938885
PMCPMC10666009
OpenAlexW4388514031

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.