Evidence map›Paper›PMID 38188859›Full record

ArticleDigital health

Validity and reliability of the Chinese version of digital health readiness questionnaire among hypertension patients in rural areas of China.

Linqi Xu, Tianzhuo Yu, Xin Leng, Tianyue Yu, Martijn Scherrenberg, Maarten Falter, Toshiki Kaihara, Sevda Ece Kizilkilic, Hanne Van Erum, Hanne Kindermans and 3 more

Open access · goldAbstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.5field-weighted citation impact, top 12% 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

5 citing papers in PubMed, 3 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

13 authors at 5 institutions in 3 countries.

Linqi XuSchool of Nursing, Jilin University, Changchun, China.
Tianzhuo YuSchool of Nursing, Jilin University, Changchun, China.
Xin LengSchool of Nursing, Jilin University, Changchun, China.
Tianyue YuSchool of Nursing, Jilin University, Changchun, China.
Martijn ScherrenbergHeart Centre Hasselt, Jessa Hospital, Hasselt, Belgium.
Maarten FalterHeart Centre Hasselt, Jessa Hospital, Hasselt, Belgium.
Toshiki KaiharaDivision of Cardiology, Department of Internal Medicine, St Marianna University School of Medicine, Kawasaki, Japan.
Sevda Ece KizilkilicHeart Centre Hasselt, Jessa Hospital, Hasselt, Belgium.
Hanne Van ErumFaculty of Medicine and Life Sciences, UHasselt, Diepenbeek, Belgium.
Hanne KindermansFaculty of Medicine and Life Sciences, UHasselt, Diepenbeek, Belgium.
Paul DendaleHeart Centre Hasselt, Jessa Hospital, Hasselt, Belgium.
Qian TongDepartment of Cardiovascular Medicine, The First Hospital of Jilin University, Changchun, Jilin Province, China.
Feng LiSchool of Nursing, Jilin University, Changchun, China.ORCID https://orcid.org/0000-0001-7423-8730
Jilin University · CNJessa Hospital · BEHasselt University · BESt. Marianna University School of Medicine · JPUniversity of Antwerp · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Digital health has the potential to support health care in rural areas by overcoming the problems of distance and poor infrastructure, however, rural areas have extremely low use of digital health because of the lack of interaction with technology. There is no existing tool to measure digital health literacy in rural China. This study aims to test and validate the digital health readiness questionnaire for assessing digital readiness among patients in rural China. Methods: Due to the different Internet environments in China compared to Belgium, a cultural adaptation is needed to optimize the use of Digital Health Readiness Questionnaire in China. Then, a prospective single-center survey study was conducted in rural China among patients with hypertension. Confirmatory factor analysis was computed to test the measurement models. Results: A total of 330 full questionnaires were selected and included in the analysis. The model-fit measures were used to assess the model's overall goodness of fit (Chi-square/degrees of freedom = 5.060, comparative fit index = 0.889, Tucker-Lewis index (TLI) = 0.869, root mean square error of approximation (RMSEA) = 0.111, standardized root mean square residual (SRMR) = 0.0880). TLI is a little bit lower than the borderline (more than 0.9) and RMSEA is higher than it (less than 0.08 means good model fit). We deleted two items 2 and 4 and the result shows a better goodness of fit (Chi-square/degrees of freedom = 4.897, comparative fit index = 0.914, TLI = 0.895, RMSEA = 0.109, SRMR = 0.0765). Conclusion: To increase applicability and generalizability in rural areas, it should be considered to use the calculation of only the parts Digital skills, Digital literacy and Digital health literacy which are equally applicable in a Belgian population as in a rural Chinese population.

Indexed as

Digital health literacydigital learnabilitydigital literacy‌digital skills‌Digital usabilityhypertension

Identifiers

PMID38188859
PMCPMC10768576
OpenAlexW4390582972

What OpenQuestion holds

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LicenceCC BY-NC
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.