Evidence map›Paper›PMID 40140824›Full record

ArticleBMC public health2025

How do electronic personal health information technologies enhance obesity prevention behaviors? Examining the roles of obesity risk perception and body weight.

Jizhou Francis Ye, Yuxiang Sam Song, Yuyuan Lai, Song Harris Ao, Xinshu Zhao

Abstract read
In one paragraph

Article in BMC public 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

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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

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

5 authors.

Jizhou Francis YeDepartment of Communication, University of Oklahoma, Norman, USA.
Yuxiang Sam SongInstitute of Collaborative Innovation, University of Macau, Taipa, Macao.
Yuyuan LaiInstitute of Collaborative Innovation, University of Macau, Taipa, Macao.
Song Harris AoSchool of Journalism and Communication, Sun Yat-Sen University, 132 Outer Ring Road East, Guangzhou, China. aosong3@mail.sysu.edu.cn.
Xinshu ZhaoInstitute of Collaborative Innovation, University of Macau, Taipa, Macao.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe global epidemic of overweight and obesity appears alongside numerous diseases. As electronic personal health information (ePHI) technology becomes more prevalent, understanding its relationship with health behaviors and how this relationship may differ across physical groups becomes increasingly relevant.

methodsUsing secondary data from the National Cancer Institute's Health Information National Trends Survey (HINTS) 2020, this study examined the relationships between ePHI technology use, obesity preventive behaviors (e.g., physical activity, alcohol consumption, and diet control), and risk perception of obesity, considering body weight as a potential moderator.

resultsThe patterns between ePHI technology use and obesity preventive behaviors differed across behavior types and body weight groups. Higher ePHI technology use was associated with increased physical activity (b = 5.98, b

conclusionThe findings suggest more limited relationships between ePHI technology and health behaviors than previously anticipated. Physical activity and dietary regulation showed modest associations with ePHI technology use, while alcohol consumption showed no significant relationship. Overweight and obese individuals did not show a higher risk perception of obesity or greater engagement in preventive behaviors compared to those of healthy weight. These findings highlight the importance of developing a more nuanced understanding of ePHI technology's role in health-related contexts.

Indexed as

Body WeightElectronic Health RecordsHealth BehaviorObesityAdolescentAdultExerciseFemaleHumansMaleMiddle AgedUnited StatesYoung AdultElectronic personal health information technologyObesityPreventive behaviorRisk perception

Identifiers

PMID40140824
PMCPMC11948975

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.