Evidence map›Paper›PMID 35793132›Full record

ArticleJMIR formative research2022

Chinese Version of the Mobile Health App Usability Questionnaire: Translation, Adaptation, and Validation Study.

Yi Shan, Meng Ji, Wenxiu Xie, Rongying Li, Xiaobo Qian, Xiaomin Zhang, Tianyong Hao

Registry-linked trialAbstract read
In one paragraph

Article in JMIR formative research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07058623 (A Randomized Controlled Trial of Nurse-Led Telehealth Versus In-Person Consultations in Detecting Complications and Improving Recovery After Total Knee Replacement), which is not on this map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

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.

NCT07058623 narecruitingnot on this mapstarted 2025, after this paper: background citation

A Randomized Controlled Trial of Nurse-Led Telehealth Versus In-Person Consultations in Detecting Complications and Improving Recovery After Total Knee Replacement

TypeinterventionalSponsorHospital Authority, Hong KongRan2025 to 2026Enrolled98ConditionsArthroplasty, Replacement, Knee, Osteoarthritis, KneeArmsNurse-Led Telehealth Consultation, Traditional In-Person Nursing Consultation
3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

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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

7 authors.

Yi ShanSchool of Foreign Studies, Nantong University, Nantong, China.ORCID https://orcid.org/0000-0003-3168-1585
Meng JiSchool of Languages and Cultures, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0002-7463-9208
Wenxiu XieDepartment of Computer Science, City University of Hong Kong, Hong Kong, China.ORCID https://orcid.org/0000-0002-8528-5193
Rongying LiSchool of Artificial Intelligence, South China Normal University, Guangzhou, China.ORCID https://orcid.org/0000-0002-0502-2124
Xiaobo QianSchool of Computer Science, South China Normal University, Guangzhou, China.ORCID https://orcid.org/0000-0001-5819-4379
Xiaomin ZhangDepartment of Linguistics, Macquarie University, Sydney, Australia.ORCID https://orcid.org/0000-0002-1146-9141
Tianyong HaoSchool of Computer Science, South China Normal University, Guangzhou, China.ORCID https://orcid.org/0000-0002-9792-3949

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe usability of mobile health (mHealth) apps needs to be effectively evaluated before they are officially approved to be used to deliver health interventions. To this end, the mHealth App Usability Questionnaire (MAUQ) has been designed and proved valid and reliable in assessing the usability of mHealth apps. However, this English questionnaire needs to be translated into other languages, adapted, and validated before being utilized to evaluate the usability of mHealth apps.

objectiveThis study aims to improve, further adapt, and validate the Chinese version of the MAUQ (C-MAUQ; interactive for patients) on Left-handed Doctor, one of the most popular "reaching out to patients" interactive mHealth apps with chatbot function in China, to test the reliability and cross-cultural adaptability of the questionnaire.

methodsThe MAUQ (interactive for patients) has been translated into Chinese and validated for its reliability on Good Doctor, one of the most influential "reaching out to patients" mHealth apps without chatbot function in China. After asking for the researchers' approval to use this Chinese version, we adjusted and further adapted the C-MAUQ by checking it against the original English version and improving its comprehensibility, readability, idiomaticity, and cross-cultural adaptability. Following a trial survey completed by 50 respondents on wenjuanxing, the most popular online questionnaire platform in China, the improved version of the C-MAUQ (I-C-MAUQ) was finally used to evaluate the usability of Left-handed Doctor through an online questionnaire survey (answered by 322 participants) on wenjuanxing, to test its internal consistency, reliability, and validity.

resultsThe I-C-MAUQ still retained the 21 items and 3 dimensions of the original MAUQ: 8 items for usability and satisfaction, 6 items for system information arrangement, and 7 items for efficiency. The translation problems in the C-MAUQ, including (1) redundancy, (2) incompleteness, (3) misuse of parts of speech, (4) choice of inappropriate words, (5) incomprehensibility, and (6) cultural difference-induced improper translation, were improved. As shown in the analysis of data obtained through the online survey, the I-C-MAUQ had a better internal consistency (ie, the correlation coefficient between the score of each item and the total score of the questionnaire determined within the range of 0.861-0.938; P<.01), reliability (Cronbach α=.988), and validity (Kaiser-Meyer-Olkin=0.973), compared with the C-MAUQ. It was effectively used to test the usability of Left-handed Doctor, eliciting over 80% of informants' positive attitudes toward this mHealth app.

conclusionsThe I-C-MAUQ is highly reliable and valid for Left-handed Doctor, and suitable for testing the usability of interactive mHealth apps used by patients in China. This finding further confirms the cross-cultural validity, reliability, and adaptability of the MAUQ. We identified certain factors influencing the perceived usability of mHealth apps, including users' age, gender, education, profession, and possibly previous experience with mHealth apps and the chatbot function of such apps. Most notably, we found a wider acceptance of this new technology among young Chinese female college students who were more engaged in the interaction with health care chatbots. The age-, gender-, and profession-induced preference for new digital health interventions in China aligns with the findings in other similar studies in America and Malaysia. This preference identifies areas for further research on the social, cultural, and gender adaptation of health technologies.

Indexed as

Chinese version of MAUQcross-cultural adaptabilityimproved translationmHealth appmobile phonereliabilitystabilityusabilityvalidity

Identifiers

PMID35793132
PMCPMC9301561

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Registered trials

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.