Evidence map›Paper›PMID 39454195›Full record

ArticleJMIR human factors2024

Factors Related to mHealth App Use Among Japanese Workers: Cross-Sectional Survey.

Itsuko Ozaki, Mariko Nishijima, Eiji Shibata, Yuri Zako, Chifa Chiang

Abstract read
In one paragraph

Article in JMIR human factors, 2024. 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

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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

5 authors.

Itsuko OzakiGraduate School of Nursing, Nagoya City University, Nagoya, Japan.ORCID 0000-0003-1071-5483
Mariko NishijimaGraduate School of Medicine, Ehime University, Toon, Japan.ORCID 0000-0001-6483-9890
Eiji ShibataYokkaichi Nursing and Medical Care University, Yokkaichi, Japan.ORCID 0000-0001-7674-766X
Yuri ZakoGraduate School of Nursing, Nagoya City University, Nagoya, Japan.ORCID 0009-0002-3984-1459
Chifa ChiangGraduate School of Nursing, Nagoya City University, Nagoya, Japan.ORCID 0000-0002-6161-1249

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth care providers can make health guidance more effective by using mobile health technologies such as health apps. Although health care providers need to know who uses health apps, existing studies have yielded inconsistent results.

objectiveThe aim of the study was (1) to clarify the prevalence and patterns of health app use to improve health behaviors for preventing lifestyle-related diseases among Japanese workers and (2) to identify the associations among demographic characteristics, health behavior, and internet use and health app use by gender.

methodsData were collected from a cross-sectional internet survey in 2023. In total, 2200 participants were included, with an even distribution of men and women in each age group aged 20 to 60 years. The participants were workers with smartphones and reported their gender, age, residence area, marital status, education, employment status, occupation, work pattern, diseases under treatment, health checkups, health guidance, health behaviors, internet use duration, and number of devices used. We asked about current and previous health app use for 1 month. A multivariate logistic regression analysis was conducted by gender.

resultsOf the participants, 472 (21.5%) and 189 (8.6%) were current and previous health app users, respectively. Most current and previous health app users used features that record and track their physical activity and other health behaviors. Health app users-both men and women-were more likely to have health checkups (odds ratio [OR] 1.53, 95% CI 1.12-2.11 and OR 1.51, 95% CI 1.10-2.07, respectively), receive health guidance (OR 2.01, 95% CI 1.47-2.74 and OR 1.86, 95% CI 1.32-2.62, respectively), engage in regular physical activity (OR 2.57, 95% CI 1.91-3.47 and OR 1.94, 95% CI 1.41-2.67, respectively), use the internet for 120-179 minutes per day (OR 1.76, 95% CI 1.13-2.75 and OR 1.70, 95% CI 1.12-2.57, respectively), and were less likely to be older (50-59 years: OR 0.54, 95% CI 0.33-0.88 and OR 0.40, 95% CI 0.25-0.6, respectively, and 60-69 years: OR 0.37, 95% CI 0.22-0.62 and OR 0.47, 95% CI 0.28-0.77, respectively). According to gender, male health app users were more likely to be married (OR 1.69, 95% CI 1.23-2.33) and less likely to work in the security, agriculture, forestry, fishing, manufacturing, or transportation industries (OR 0.62, 95% CI 0.41-0.95). Female health app users were more likely to have a university education or higher (OR 1.55, 95% CI 1.061-2.26), maintain an appropriate body weight (OR 1.52, 95% CI 1.10-2.11), and use 3 or more devices (OR 2.13, 95% CI 1.41-3.23).

conclusionsPhysical activity and health guidance are strong predictors of app use. Health care providers should assess the target populations' preferences for app use based on their characteristics, support their app use, and enhance the effectiveness of health guidance.

Indexed as

Mobile ApplicationsTelemedicineAdultCross-Sectional StudiesEast Asian PeopleFemaleHealth BehaviorHumansJapanMaleMiddle AgedSurveys and QuestionnairesYoung Adultapp userscross-sectional surveydisease managementhealth managementhealth promotionJapanJapanese workermHealthmobile healthmobile health appsphysical activityprevalence

Identifiers

PMID39454195
PMCPMC11549587

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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.