Evidence map›Paper›PMID 30714942›Full record

ArticleJMIR mHealth and uHealth2019

Perceptions and Acceptance of mHealth in Patients With Cardiovascular Diseases: A Cross-Sectional Study.

Jie Jiang, Qin Zhu, Yimei Zheng, Yajing Zhu, Yuxi Li, Yong Huo

Open access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 2 pooled it
7.7field-weighted citation impact, top 3% 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

27 citing papers in PubMed, 2 syntheses or guidelines pooled it, 52 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Jie JiangDepartment of Cardiology, Peking University First Hospital, Beijing, China.ORCID 0000-0002-4077-0056
Qin ZhuHealth Systems, Philips Research China, Shanghai, China.ORCID 0000-0003-1765-4636
Yimei ZhengDepartment of Cardiology, Peking University First Hospital, Beijing, China.ORCID 0000-0002-2497-2758
Yajing ZhuHealth Systems, Philips Research China, Shanghai, China.ORCID 0000-0001-8035-2337
Yuxi LiDepartment of Cardiology, Peking University First Hospital, Beijing, China.ORCID 0000-0003-1556-598X
Yong HuoDepartment of Cardiology, Peking University First Hospital, Beijing, China.ORCID 0000-0002-5407-8773
Peking University · CNPhilips (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile health (mHealth)-a method of assisting long-term care in patients with chronic cardiovascular diseases (CVDs)-is gaining popularity in China, mainly owing to the large number of patients and limited clinical resources. Patients of different ages have varying needs for CVD management. However, evidence regarding how age influences Chinese CVD patients' use and perceptions of mHealth is limited.

objectiveThis study aimed to explore age-related differences among Chinese patients with CVD regarding their use and perceptions of mHealth and to determine the factors that influence this population's willingness to use mHealth technologies.

methodsWe conducted a cross-sectional study of patients with chronic CVDs in a tertiary hospital in Beijing using a new questionnaire designed by the investigators. Participants were sourced using nonproportional quota-sampling methods, being recruited consecutively in each sampling category (age 18-49, 50-64, 65-74, and ≥75 years, with at least 25 men and 25 women in each age group). The survey consisted of 5 parts, including sociodemographic profile and medical history; current disease management situation; self-evaluation of disease management; current usage of mobile and internet technology (IT); and willingness to use an mHealth solution to perform disease self-management. Responses were compared among the 4 age groups as well as between patients who were willing to use mHealth solutions and those who were not. Multivariate logistic regression model was used to identify predictors of willingness to use mHealth for self-management.

resultsOverall, 231 patients (124 men) completed the questionnaire; of these, 53 were aged 18-49 years, 66 were aged 50-64 years, 54 were aged 65-74 years, and 58 were aged ≥75 years. Patients in the older cohorts visited hospitals more often than did those in the younger cohorts (P<.001), and they also showed lower technology skills regarding the use of mobile or internet devices (P<.001) and searched for health-related information on the internet less often (P<.001). In addition, 68.0% (157/231) of the patients showed interest in using mHealth solution to manage their disease; of these, 40.8% (64/157) were aged 65 years. Patients who were more willing to use mHealth solution to manage their diseases were younger (P<.001), more educated (P<.001), still working (P=.001), possessed higher skill regarding mobile or internet device use (P<.001), and more frequently searched for health information on the internet (P<.001). Finally, multivariate logistic regression showed that IT skill was the single indicator (P=.003) of willingness to use mHealth, not age.

conclusionsAlthough age is associated with the use of mobile or internet devices, the sole indicator of mHealth use for self-management was participants' IT skills. Education regarding the use of mobile devices and development of easy-to-use software might improve the acceptance of mHealth solutions among older patient populations.

Indexed as

PerceptionAdolescentAdultAgedAged, 80 and overCardiovascular DiseasesChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedPatient Acceptance of Health CareSelf-ManagementSurveys and QuestionnairesTelemedicineagecardiovascular diseaseinternetmHealthmobile phonesecondary preventionself-management

Identifiers

PMID30714942
PMCPMC6483059
OpenAlexW2898560267

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.