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Usability questionnaire for standalone or interactive mobile health applications: a systematic review

BMC Digital Health volume 3, Article number: 11 (2025) Cite this article

Abstract

Background

Mobile health apps (mHealth apps) play important roles in various aspects of disease management, health monitoring, behavioural change, education, and medication adherence. The usability and satisfaction of the app indicate whether the app is favoured and used for its optimal potential. Surveys are among the most commonly used methods and are simple to conduct, and data analysis is easily quantifiable. We aimed to synthesize the evidence from questionnaires available to assess the usability and satisfaction of mHealth apps, both standalone and interactive apps, and to evaluate the validation status of the questionnaire.

Methods

An extensive search of the literature published from 2000 to June 2023 was conducted via PubMed, Scopus and Google Scholar. The keywords, MeSH terms, truncation and text words used for the search included “mobile health” or “health” or “mobile app*” or “mhealth” and “patient satisfaction” or “user” or “usability” or “feasibility” and “survey” or “questionnaire”. Eligibility was independently assessed by two investigators on the basis of the inclusion and exclusion criteria. Human studies published in English that reported the usability and/or satisfaction of patients or users with mHealth apps with published questionnaires were included. Studies that did not include questions or assessed the usability and/or satisfaction of healthcare providers or experts were excluded. Studies such as questionnaire development and validation, translation studies, qualitative studies, reviews, editorials, brief reports, comments, conference proceedings, letters and wrong outcomes were excluded. The first author, year and country of publication; sample size; demographics of the study population; name and type of mobile health application; assessment tool; validation status; and number of questions, domains and scores were collected from each study. The quality assessment was independently performed by two reviewers via the Joanna Briggs Institute (JBI) critical appraisal checklist for cross-sectional studies.

Results

Electronic database searches identified 5703 potentially relevant studies, and 40 studies with a total of 1552 respondents were included. The majority of the studies assessed the usability of standalone apps (62.5%). Half of the studies (50.0%) utilized researcher-developed questionnaires, whereas only 25% of the researcher-developed questionnaires were validated. Nine studies used the System Usability Survey (SUS). The majority of the studies (70.0%) used questionnaires that were not validated. When the JBI critical appraisal checklist was used to assess quality, 14 (35.0%) studies were assessed to be poor quality.

Conclusion

Researchers have developed questionnaires, and the SUS is the most commonly used method to assess the usability and satisfaction of mobile health applications. Although most questionnaires have not been validated, ensuring the optimal use of mHealth apps via adapted and customized questionnaires is crucial.

Peer Review reports

Background

In today’s digital era, the use of mobile phones has evolved quickly from being a gadget for communication to being a significant part of daily activities, offering a wide range of accessibilities, especially through the use of mobile applications. Among its various definitions, mobile health (mHealth) can be used to describe the integration of mobile device applications and next-generation technologies in the healthcare sector [1]. MHealth apps have been shown to play important roles in various aspects of disease management, health monitoring, behavioural change, education, and medication adherence [2]. While its uses can range from basic mobile device functions such as voice calls and short message services, it is also capable of more complex functions designed for medical, physical health, and public health purposes [2].

MHealth apps are often designed on the basis of two classifications: type of users and type of mobile apps [3]. The type of user for the app is divided into patients and healthcare providers, and it is determined by their purpose for using the app. When users are patients, they may use the app to maintain, improve, or manage their health, whereas when users are healthcare providers, they may be delivering healthcare services through the app [3]. The next domain, which is the type of mobile app, refers to the nature of the app, whether it is interactive or standalone. Interactive mHealth apps have functions for users to send and receive information from their healthcare providers or communicate with other people, whereas standalone mHealth apps only store, collect and save health information entered by users and do not send data to healthcare providers [3].

Although mHealth apps have many benefits, acceptance among users is still related to ease of use, perceived usefulness, accuracy and quality of content, and consumer attitudes [2]. Studies have shown that well-designed mHealth apps have the ability to empower patients, improve medication adherence, and decrease healthcare costs [4,5,6]. However, a previous study revealed a decrease in usage among mHealth users for several reasons, such as unseen costs, tedious data entry loads and disinterest [7]. An apparent factor to question when such issues surface would be the usability and satisfaction of the app design, as this indicates whether the app is favoured and used to its optimal potential. Therefore, in efforts to enhance mHealth services, there is an increasing demand for research to assess the usability and satisfaction of mHealth apps. This further leads to the need to systematically review the methods used to evaluate these factors.

Surveys are among the methods most commonly used to evaluate usability, as they are simple to conduct and data analysis is easily quantifiable [3]. Validated usability surveys that are readily available and widely used are fundamentally designed for computerized systems and may not cover aspects that are exclusive to mobile apps [3]. On the other hand, while investigator-derived surveys can be tailored specifically for mobile apps, they are often not validated or have insufficient data for reliable psychometric analysis. For example, a review on the usability of a disease-specific management app revealed that the available apps were incomprehensible and unable to cater to specific target populations [8]. The ideal step forward in ensuring optimal use of the app would be a validated usability and satisfaction questionnaire that is designed specifically for mHealth apps and considers the four aspects of its design. This study aimed to synthesize the current evidence on the types of usability and satisfaction questionnaires available, their use for standalone and interactive mHealth apps, and the validation of the questionnaire.

Methods

This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [9] and was registered with the National Medical Research Register of Malaysia (NMRR ID-22–02846-I21). This study was exempt from ethical approval, as the data were extracted from previously published studies.

Search strategy

An extensive search of the literature was conducted via electronic databases, namely, PubMed, Scopus, and Google Scholar. The keywords used for the search included (“mobile health (MeSH Terms)”) or (“health (MeSH Terms)”) or (“mobile app* (MeSH Terms)”) and (“patient satisfaction (MeSH Terms)”) or (“user (MeSH Terms)”) or (“usability (MeSH Terms)”) or (“feasibility (MeSH Terms)”) and (“survey (MeSH Terms)”). Further title and abstract keyword searches included “mhealth” or “mobile application” and “questionnaire” and “satisfaction” or “usability”. In addition, the references of each retrieved study were screened for relevant titles.

Inclusion and exclusion criteria

Only studies published in the English language and conducted with human subjects between 2000 and June 2023 were included in the literature review. Studies reporting the usability and/or satisfaction of patients or users with mHealth apps with published questionnaires were included.

Studies that did not include questions to assess usability and/or satisfaction were excluded. Studies that assessed the usability and/or satisfaction of health care providers or experts were excluded. Studies such as questionnaire development and validation, translation studies, qualitative studies, reviews, editorials, brief reports, comments, conference proceedings, letters and wrong outcomes were excluded.

These criteria were established to filter out non-relevant studies and ensure that the review focused on types of usability and/or satisfaction questionnaires available to assess interactive or standalone mHealth apps.

Study selection and data collection

Initially, potential eligible studies were selected by screening the title and abstract relevance by two investigators (LPC and RR) independently. After the removal of duplications, the full texts were retrieved. Eligibility was independently assessed by two investigators (LPC and LYL) on the basis of the inclusion and exclusion criteria. Decisions to include or exclude the study were compared between the two investigators. When disagreements arose, the other investigators were consulted if the primary reviewers could not reach a consensus.

A data collection sheet was used to extract the data. The following information was collected from each study: first author, year and country of publication, sample size, demographics of the study population, name and type of mobile health application, assessment tool and validation status, number of questions, domains and scoring. The findings were synthesized narratively as heterogeneity in the study methodologies, which included population, assessment tools and mobile health applications.

Quality assessment

The quality of the eligible studies was independently assessed by two reviewers (RR and LPC) via the Joanna Briggs Institute (JBI) critical appraisal checklist for cross-sectional studies [10]. JBI provided permissions to use and publish the JBI critical appraisal checklist for cross sectional studies. The tool consists of eight questions and one overall appraisal to assess the quality of the study methods and determine the possibility of bias in terms of study design, conduct, and analysis. The answers for every question were yes (Y), no (N), unclear (UC), or not applicable (NA).

Results

The study screening and selection process are shown in Fig. 1. Electronic database searches identified 5703 potentially relevant studies, of which 1964 studies were removed because of duplication. The titles and abstracts were screened, and 3200 studies were found to be irrelevant. The remaining 539 studies underwent full-text review, and 40 studies [11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50] met the inclusion criteria.

Fig. 1
figure 1

Flow chart for study screening and selection according to PRISMA guidelines

Full size image

The study screening and selection process are shown in Fig. 1.

The studies included originated from the United States of America (n = 13), Asia (n = 12), Europe (n = 7), Australia (n = 4), Canada (n = 2) and Brazil (n = 2). A total of 1552 patients or users, the majority of whom were females (38 studies, 63.2%), were assessed for the usability and satisfaction of mHealth apps through cross-sectional studies. Eight studies were conducted among adolescents [18, 19, 27, 42, 45, 47, 48, 50]. Moreover, three studies assessed the usability and satisfaction of females only, as the mHealth apps were designed for pregnancy [13, 15] and breast cancer [16]. A total of 633 Likert scale questions, 10 open-ended questions and 23 interview questions were identified. The studies are summarized in Table 1. The majority of the mHealth apps (62.5%) were standalone applications.

Table 1 Summary of study characteristics, mHealth apps, assessment tools and validation status
Full size table

Usability and satisfaction assessment tools and scoring

Assessment tools

The usability assessment tools are shown in Table 2. Half of the studies (50%) utilized researcher-developed questionnaires, and only 25% of the researcher-developed questionnaires were validated.

Table 2 Types of questionnaires for interactive and standalone mHealth apps
Full size table

The most commonly used existing questionnaire was the System Usability Scale (SUS) [53], with 9 studies [15, 16, 19, 27, 32, 33, 35, 37, 41] using this questionnaire to assess the usability of mHealth apps. Additionally, four studies [14, 23, 29, 34] used a researcher-developed questionnaire that was developed on the basis of the SUS [53]. Few studies [39, 48] have adapted questions from the Post-Study System Usability Questionnaire (PSSUQ) [54] and a study [24] from the Technology Acceptance Model (TAM) [56]. Several researchers have developed questionnaires [25, 29, 34, 42] on the basis of the TAM [56]. Other questionnaires [13, 30, 32, 47] utilized for usability assessment include the mHealth App Usability Questionnaire (MAUQ) [3] and the Usefulness, Satisfaction and Ease of Use (USE) questionnaire [55].

Fifteen studies [11,12,13,14,15,16,17,18,19,20,21,22,23,24,25] used interactive mHealth apps, eight studies assessed usability via a researcher-developed questionnaire, and three studies used the SUS [53] (Table 2). Nevertheless, only eight studies that utilized interactive apps had questions related to the connection between patients or users and healthcare providers [11,12,13, 17, 21,22,23] or the same community [18]. Although the other seven studies used interactive apps, the usability questionnaire focused on usefulness, ease of use, interface and satisfaction.

Only 30% of the studies validated the questionnaire. The validation status of the questionnaire is summarized in Fig. 2.

Fig. 2
figure 2

Validation status of the questionnaire for interactive and standalone mHealth apps

Full size image

Scoring

Among the questionnaires, only the SUS [53], Smartphone Usability Questionnaire (SURE) [59] and Health Information Technology Usability Survey (Health-ITUES) [58] elaborated on the scoring. In the SUS [53], odd questions are positive, whereas even questions are negative. A new number was formed by subtracting one from the response for odd questions and five for even questions. The total number of new numbers was added and multiplied by 2.5 to convert to a total ranging from 0 to 100. Good usability was considered when the score was above 68 [27]. On the other hand, the total score for SURE was 124 points. If the total score was 80 or above, the respondents agreed with the usability of the scale [36]. Moreover, the total score for Health-ITUES ranges from 20 to 100, with a higher score indicating better usability [28].

Quality assessment

When the JBI critical appraisal checklist was used to assess quality, 14 (35%) studies were assessed as poor quality (Table 3). However, all studies were included. Only studies conducted by Jaffar et al. [13], Chen et al. [28], and Everett et al. [41] received yes for every question for the quality assessment. A total of 95% of the studies used nonprobability sampling methods, with the majority using convenient sampling methods. The studies by Ji et al. [35] and Zhou et al. [39] reported random sampling. The majority of the studies did not validate the questionnaire.

Table 3 Quality assessment via the Joanna Briggs Institute (JBI) critical appraisal checklist [10]
Full size table

Discussion

This review highlighted multiple questionnaires that were utilized to assess the usability of mHealth apps. It is vital to assess the usability of an mHealth app to ensure that it meets users’ preferences and expectations as well as the optimal use of the app. SUS [53], which was originally developed to assess the usability of the system, was the most commonly used questionnaire for both interactive and standalone mHealth apps. In addition, the SUS was translated into multiple languages, such as Malay [27], German [19] and Chinese [14]. Moreover, the SUS is an easy and quick tool for assessing usability with scoring. This enabled the SUS to be the most preferred option because it could be used across a wider variety of subjects.

Other questionnaires, such as the PSSUQ [54] and TAM [56], were originally designed to assess the usability of computer systems and to measure the acceptance and use of technology, respectively. The SURE questionnaire reported by Marques et al. [36] was not designed for the assessment of mHealth but rather for the usability assessment of smartphones. However, there was no statement on the validation, adaptation, or adoption of the questionnaire, and a comparison with the original article could not be made, as the latter was not in English [59]. This review highlights the point that these questionnaires were not specific to mHealth apps. However, these questionnaires have been adopted and adapted in many studies and have often not been validated. A common reason for this could be that the validation process is often very time-consuming and can pose a challenge for those inexperienced in questionnaire development and validation. As a consequence, certain usability aspects of mHealth apps may not be reliably measured. Furthermore, these questionnaires may not gauge the benefit of mHealth apps for end users, as they are unable to provide unique information related to mHealth apps.

A few researchers have developed questionnaires consisting of Likert scale questions and open-ended questions [19, 22, 40, 50] or mixed methods with interview questions [12, 18, 32, 48]. The interviews and open-ended questions were intended to evaluate the recommendations to improve the apps and the satisfaction of the respondents with the app as well as the medical care service.

On the other hand, Health-ITUES was designed to assess the perceptions of nurses toward a web-based communication system [58]. To cater to a different target population, a previous study modified and validated the Health-ITUES to assess the usability of mHealth apps among HIV patients [62]. Additionally, Chen et al. modified and validated the Health-ITUES to assess the perceptions of chronic heart disease patients towards self-management and risk factors [28].

Interactive mHealth apps are possibly more favourable, as they involve communication between patients or users and either healthcare providers or the community that has the same disease. This function improved access to healthcare and served as a sharing platform for the users [63]. Considering that only 53% of the studies involving interactive mHealth apps assessed the communication between the users and healthcare providers or the community, a more in-depth questionnaire would be more beneficial in assessing these vital functions of interactive apps.

In 2019, Zhou et al. developed a 21-item mHealth App Usability Questionnaire (MAUQ) with three domains, namely, ease of use and satisfaction (8 items), system information arrangement (6 items) and usefulness (7 items), for interactive mobile applications for health from the patient’s perspective. In addition, an 18-item questionnaire for standalone mHealth for patients was developed with questions on ease of use (5 items), interface and satisfaction (7 items) and usefulness (6 items) [3]. Jaffar et al. utilized the translated and validated Malay version of the MAUQ as an interactive app [13]. The MAUQ is more specific for assessing the usability of end users towards mHealth apps, as it consists of health-related questions such as those concerning access to health, interactions with healthcare providers and improvements in self-management.

While the MAUQ questionnaires were more specific for assessing the usability of end users for mHealth apps, the majority of the studies utilized researcher-developed questionnaires. This is possibly because each mHealth app has its own unique features and functions such that only app-specific questionnaires can be used to assess the usability and satisfaction of its end users comprehensively. However, the main issue was that these questionnaires, although they were designed most specifically for the app, were almost always not validated. Tsang et al. concluded that to ensure that a questionnaire is psychometrically adequate, it is necessary that it undergoes a validation process [64].

This review synthesized evidence from questionnaires used to assess the usability and satisfaction of end users with mHealth apps, which included vigorous searches via multiple databases. Every phase involved two reviewers, hence reducing bias. Nevertheless, the findings of this review should be interpreted in light of its limitations. Although extensive search strategies were employed to identify relevant articles, some studies may have been missed because of the terminology used. In addition, non-English language articles were excluded, which may have reduced the representativeness of our findings. This review involved a usability assessment of multiple mHealth apps for various health and disease types. In addition, the wide variety of questionnaires used with limited scoring caused the reporting of the results to be inconsistent across the studies. Several studies were of poor quality but were included because the intention was to review the current evidence from questionnaires.

The overall implication of these results highlights the existence of a significant gap in the available tools for assessing the usability and satisfaction of mHealth apps. The lack of validated, intentionally designed questionnaires specific to mHealth apps compromises the reliability of research outcomes, whereas the adaptation of existing tools may fail to fully achieve an optimal user experience. Researchers and practitioners in the field should direct their aim towards developing, validating and implementing more targeted questionnaires that are intended to assess not only usability but also user satisfaction and the impact of interactive features, which are key to the successful use of these technologies in healthcare settings. Addressing these issues would be an effective pathway towards sustaining mHealth apps, thus ensuring better healthcare services and improved patient outcomes.

Conclusion

Various questionnaires have been used to assess the usability and satisfaction of mobile health applications, with the majority being researcher-developed questionnaires followed by the System Usability Scale (SUS) for both interactive and standalone mobile health applications. The majority of the questionnaires were not validated prior to use. In addition, most existing questionnaires that are readily available were not designed to assess the usability of mHealth apps specifically; however, they were adapted or modified to customize to the mHealth app without validation. More than half of the studies involving interactive apps comprehensively assess features exclusive to interactive apps. It is vital to assess the benefit of this function, as it allows healthcare providers to extend the reach to patients. Researchers have developed questionnaires, although the optimal design flexibility is still a drawback if it is not validated. The usability and satisfaction of mHealth apps are important measures for ensuring their continuous use. Ideally, all questionnaires should be customized and validated for a specific mHealth app prior to assessment of its usability and satisfaction.

Data availability

All data generated or analysed during this study are included in this published article.

Abbreviations

App:

Application

AEFI:

Adverse event following immunization

CEO:

Chief executive officer

COVID-19:

Coronavirus Disease

Health-ITUES:

Health Information Technology Usability Survey

HIV:

Human immunodeficiency virus

JBI:

Joanna Briggs Institute

KEPT:

Kegel exercise pregnancy training

MAUQ:

MHealth App Usability Questionnaire

mHealth:

Mobile health

PRISMA:

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

PSSUQ:

Post-Study System Usability Questionnaire

QUIS:

Questionnaire for User Interaction Satisfaction

RPS:

Reactions to Program Scale

SKAMA:

‘Skala Kebolehgunaan Aplikasi Mudah Alih’

SURE:

Smartphone Usability Questionnaire

SUS:

System Usability Scale

TAM:

Technology Acceptance Model

USE:

Usefulness, Satisfaction and Ease of Use

References

  1. Ali EE, Chew L, Yap KY. Evolution and current status of mhealth research: a systematic review. BMJ Innovations. 2016;2:33–40.

    Article  Google Scholar 

  2. Hajesmaeel-Gohari S, Khordastan F, Fatehi F, Samzadeh H, Bahaadinbeigy K. The most used questionnaires for evaluating satisfaction, usability, acceptance, and quality outcomes of mobile health. BMC Med Inform Decis Mak. 2022;22(1):22.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Zhou L, Bao J, Setiawan IMA, Saptono A, Parmanto B. The mHealth app usability questionnaire (MAUQ): Development and validation study. JMIR MHealth UHealth. 2019;7(4):e11500.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Zhou L, Bao J, Watzlaf V, Parmanto B. Barriers to and facilitators of the use of mobile health apps from a security perspective: Mixed-methods study. JMIR MHealth UHealth. 2019;7(4):e11223.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Seto E, Leonard KJ, Cafazzo JA, Barnsley J, Masino C, Ross HJ. Perceptions and experiences of heart failure patients and clinicians on the use of mobile phone-based telemonitoring. J Med Internet Res. 2012;14(1):e25.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Parmanto B, Pramana G, Yu DX, Fairman AD, Dicianno BE, McCue MP. iMHere: A Novel mHealth System for Supporting Self-Care in Management of Complex and Chronic Conditions. JMIR Mhealth Uhealth. 2013;1(2):e10.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Krebs P, Duncan DT. Health App Use Among US Mobile Phone Owners: A National Survey. JMIR Mhealth Uhealth. 2015;3(4):e101.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Bhattarai P, Newton-John TRO, Phillips JL. Quality and Usability of Arthritic Pain Self-Management Apps for Older Adults: A Systematic Review. Pain Med. 2018;19(3):471–84.

    Article  PubMed  Google Scholar 

  9. Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev. 2015;4(1):1.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Moola S, Munn Z, Tufanaru C, Aromataris E, Sears K, Sfetcu R, et al. Chapter 7: Systematic reviews of etiology and risk. In Aromataris E, Munn Z (Editors) JBI Manual for Evidence Synthesis. JBI, 2020. Available online: https://synthesismanual.jbi.global. Accessed on 1 Sept 2023.

  11. Chiang YT, Chang CW, Yu HY, Tsay PK, Lo FS, Chen CW, et al. Developing the “Healthcare CEO App” for patients with type 1 diabetes transitioning from adolescence to young adulthood: A mixed-methods study. Nurs Open. 2023;10(3):1755–66.

    Article  PubMed  Google Scholar 

  12. Bosse JD, Hoffman K, Wiest K, Todd Korthuis P, Petluri R, Pertl K, et al. Patient evaluation of a smartphone application for telehealth care of opioid use disorder. Addict Sci Clin Pract. 2022;17(1):50.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Jaffar A, Muhammad NA, Mohd Sidik S, Admodisastro N, Abdul Manaf R, Foo CN, et al. Feasibility and Usability of Kegel Exercise Pregnancy Training App (KEPT App) among Pregnant Women with Urinary Incontinence. Int J Environ Res Public Health. 2022;19(6):3574.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Jiang S, Lv M, Wu T, Chen W, Zhang J. A smartphone application for remote adjustment of warfarin dose: Development and usability study. Appl Nurs Res. 2022;63:151521.

    Article  PubMed  Google Scholar 

  15. Lee Y, Choi S, Jung H. Self-Care Mobile Application for South Korean Pregnant Women at Work: Development and Usability Study. Risk Manag Healthc Policy. 2022;15:997–1009.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Rezaee R, Asadi S, Yazdani A, Rezvani A, Kazeroon AM. Development, usability and quality evaluation of the resilient mobile application for women with breast cancer. Health Sci Rep. 2022;5(4):e708.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Kooij L, Vos PJE, Dijkstra A, van Harten WH. Effectiveness of a mobile health and self-management app for high-risk patients with chronic obstructive pulmonary disease in daily clinical practice: mixed methods evaluation study. JMIR Mhealth Uhealth. 2021;9(2):e21977.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Francis J, Cross D, Schultz A, Armstrong D, Nguyen R, Branch-Smith C. Developing a smartphone application to support social connectedness and wellbeing in young people with cystic fibrosis. J Cyst Fibros. 2020;19(2):277–83.

    Article  PubMed  Google Scholar 

  19. Rudolf I, Pieper K, Nolte H, Junge S, Dopfer C, Sauer-Heilborn A, et al. Assessment of a mobile app by adolescents and young adults with cystic fibrosis: pilot evaluation. JMIR Mhealth Uhealth. 2019;7(11):e12442.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Støme LN, Pripp AH, Kværner JS, Kvaerner KJ. Acceptability, usability and utility of a personalised application in promoting behavioural change in patients with osteoarthritis: a feasibility study in Norway. BMJ Open. 2019;9(1):e021608.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Bauer AM, Iles-Shih M, Ghomi RH, Rue T, Grover T, Kincler N, et al. Acceptability of mHealth augmentation of Collaborative Care: A mixed methods pilot study. Gen Hosp Psychiatry. 2018;51:22–9.

    Article  PubMed  Google Scholar 

  22. Casida JM, Aikens JE, Craddock H, Aldrich MW, Pagani FD. Development and feasibility of self-management application in left-ventricular assist devices. ASAIO J. 2018;64(2):159–67.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Liu JF, Lee JM, Strock E, Phillips R, Mari K, Killiam B, et al. Technology applications: use of digital health technology to enable drug development. JCO Clin Cancer Inform. 2018;2:1–12.

    Article  PubMed  Google Scholar 

  24. Chen YS, Wong JE, Ayob AF, Othman NE, Poh BK. Can Malaysian young adults report dietary intake using a food diary mobile application? a pilot study on acceptability and compliance. Nutrients. 2017;9(1):62.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Al Ayubi SU, Parmanto B, Branch R, Ding D. A Persuasive and Social mHealth application for physical activity: a usability and feasibility study. JMIR Mhealth Uhealth. 2014;2(2):e25.

    Article  PubMed  PubMed Central  Google Scholar 

  26. AlAli E, Al-Dossary R, Al-Rayes S, Al-Ansary N, Alshawan D, Almulla S, et al. Evaluation of the patient experience with the Mawid App during the COVID-19 Pandemic in Al Hassa, Saudi Arabia. Healthcare (Basel). 2022;10(6):1008.

    Article  PubMed  Google Scholar 

  27. Akmal Muhamat N, Hasan R, Saddki N, Mohd Arshad MR, Ahmad M. Development and usability testing of mobile application on diet and oral health. PLoS ONE. 2021;16(9):e0257035.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Chen CS, Kim J, Garg N, Guntupalli H, Jagsi R, Griggs JJ, et al. Chemotherapy-induced peripheral neuropathy detection via a Smartphone app: cross-sectional pilot study. JMIR Mhealth Uhealth. 2021;9(7):e27502.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Chulasai P, Chinwong D, Chinwong S, Hall JJ, Vientong P. Feasibility of a smoking cessation smartphone App (Quit with US) for young adult smokers: a single arm, pre-post study. Int J Environ Res Public Health. 2021;18(17):9376.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Chumkasian W, Fernandez R, Win KT, Petsoglou C, Lord H. Adaptation of the MAUQ and usability evaluation of a mobile phone-based system to promote eye donation. Int J Med Inform. 2021;151:104462.

    Article  PubMed  Google Scholar 

  31. Hsia B, Mowrey W, Keskin T, Wu S, Aita R, Kwak L, et al. Developing and pilot testing ASTHMAXcel, a mobile app for adults with asthma. J Asthma. 2021;58(6):834–47.

    Article  PubMed  Google Scholar 

  32. Tonga E, Williamson E, Srikesavan C, Özen T, Sarıtaş F, Lamb SE. A hand exercise mobile app for people with rheumatoid arthritis in Turkey: design, development and usability study. Rheumatol Int. 2021;41(6):1151–60.

    Article  PubMed  Google Scholar 

  33. Valente PSMC, Carneiro CLB, de Aguiar RGP, de Souza Júnior FEA, Maciel AA, Marçal E, et al. Development and usability evaluation of an application for patients with glaucoma. Int Ophthalmol. 2021;41(10):3419–25.

    Article  PubMed  Google Scholar 

  34. Adu MD, Malabu UH, Malau-Aduli AEO, Drovandi A, Malau-Aduli BS. Efficacy and acceptability of my care hub mobile app to support self-management in Australians with Type 1 or type 2 diabetes. Int J Environ Res Public Health. 2020;17(7):2573.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Ji Y, Plourde H, Bouzo V, Kilgour RD, Cohen TR. Validity and usability of a smartphone image-based dietary assessment app compared to 3-day food diaries in assessing dietary intake among Canadian adults: randomized controlled trial. JMIR Mhealth Uhealth. 2020;8(9):e16953.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Marques ADB, Moreira TMM, Jorge TV, Rabelo SMS, Carvalho REFL, Felipe GF. Usability of a mobile application on diabetic foot self-care. Rev Bras Enferm. 2020;73(4):e20180862.

    Article  PubMed  Google Scholar 

  37. Sung M, Park S, Jung S, Lee E, Lee J, Park YR. Developing a mobile app for monitoring medical record changes using blockchain: development and usability study. J Med Internet Res. 2020;22(8):e19657.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Battineni G, Di Canio M, Chintalapudi N, Amenta F, Nittari G. Development of physical training smartphone application to maintain fitness levels in seafarers. Int Marit Health. 2019;70(3):180–6.

    Article  PubMed  Google Scholar 

  39. Zhou L, DeAlmeida D, Parmanto B. Applying a user-centered approach to building a mobile personal health record app: development and usability study. JMIR Mhealth Uhealth. 2019;7(7):e13194.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Ambrosini GL, Hurworth M, Giglia R, Trapp G, Strauss P. Feasibility of a commercial smartphone application for dietary assessment in epidemiological research and comparison with 24-h dietary recalls. Nutr J. 2018;17(1):5.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Everett E, Kane B, Yoo A, Dobs A, Mathioudakis N. A novel approach for fully automated, personalized health coaching for adults with prediabetes: pilot clinical trial. J Med Internet Res. 2018;20(2):e72.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Wu YP, Linder LA, Kanokvimankul P, Fowler B, Parsons BG, Macpherson CF, et al. Use of a smartphone application for prompting oral medication adherence among adolescents and young adults with cancer. Oncol Nurs Forum. 2018;45(1):69–76.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Boisseau CL, Schwartzman CM, Lawton J, Mancebo MC. App-guided exposure and response prevention for obsessive compulsive disorder: an open pilot trial. Cogn Behav Ther. 2017;46(6):447–58.

    Article  PubMed  Google Scholar 

  44. Boushey CJ, Spoden M, Delp EJ, Zhu F, Bosch M, Ahmad Z, et al. Reported energy intake accuracy compared to doubly labeled water and usability of the mobile food record among community dwelling adults. Nutrients. 2017;9(3):312.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Lee JE, Song S, Ahn JS, Kim Y, Lee JE. Use of a mobile application for self-monitoring dietary intake: feasibility test and an intervention study. Nutrients. 2017;9(7):748.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Prada P, Zamberg I, Bouillault G, Jimenez N, Zimmermann J, Hasler R, et al. EMOTEO: A Smartphone application for monitoring and reducing aversive tension in borderline personality disorder patients, a pilot study. Perspect Psychiatr Care. 2017;53(4):289–98.

    Article  PubMed  Google Scholar 

  47. Stoll R, Pina A, Gary K, Amresh A. Usability of a smartphone application to support the prevention and early intervention of anxiety in youth. Cogn Behav Pract. 2017;24(4):393–404.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Shellmer DA, Dew MA, Mazariegos G, DeVito DA. Development and field testing of Teen Pocket PATH(®), a mobile health application to improve medication adherence in adolescent solid organ recipients. Pediatr Transplant. 2016;20(1):130–40.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Wilson K, Atkinson KM, Westeinde J, Bell C, Marty K, Fergusson D, et al. An evaluation of the feasibility and usability of a proof of concept mobile app for adverse event reporting post influenza vaccination. Hum Vaccin Immunother. 2016;12(7):1738–48.

    PubMed  PubMed Central  Google Scholar 

  50. Kenny R, Dooley B, Fitzgerald A. Feasibility of “CopeSmart”: A Telemental Health App for Adolescents. JMIR Ment Health. 2015;2(3):e22.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Cai RA, Beste D, Chaplin H, Varakliotis S, Suffield L, Josephs F, et al. Developing and Evaluating JIApp: acceptability and usability of a smartphone app system to improve self-management in young people with juvenile idiopathic arthritis. JMIR Mhealth Uhealth. 2017;5(8):e121.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Wood J, Jenkins S, Putrino D, Mulrennan S, Morey S, Cecins N, et al. A smartphone application for reporting symptoms in adults with cystic fibrosis improves the detection of exacerbations: Results of a randomised controlled trial. J Cyst Fibros. 2020;19(2):271–6.

    Article  CAS  PubMed  Google Scholar 

  53. Brooke J. SUS: A quick and dirty usability scale. In: Jordan PW, Thomas B, Weerdmeester BA, and McClelland IL, editors. Usability evaluation in industry. London: Taylor & Francis; 1996. p. 189–194

  54. Lewis J. IBM computer usability satisfaction questionnaires: Psychometric evaluation and instructions for use. Int J Hum Comput Interact. 1995;7(1):57–78.

    Article  Google Scholar 

  55. Lund AM. Measuring usability with the USE questionnaire. Usability Interface. 2001;8(2):3–6.

    Google Scholar 

  56. Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989;13(3):319–39.

    Article  Google Scholar 

  57. Chin JP, Diehl VA, Norman KL. Development of an instrument measuring user satisfaction of the human-computer interface. International conference on human factors in computing systems proceedings. 1988;213–18.

  58. Yen PY, Sousa KH, Bakken S. Examining construct and predictive validity of the Health-IT Usability Evaluation Scale: confirmatory factor analysis and structural equation modeling results. J Am Med Inform Assoc. 2014;21(e2):e241–8.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Wangenheim CG, Borgatto AF, Nunes JV, Lacerda TC, Oliveira RJ, Krone C, et al. Sure: uma proposta de questionário e escala para avaliar a usabilidade de aplicações para smartphones pós-teste de usabilidade. 6ta. Conferencia Latinoamericana de Diseño de Interacción. 2014;19–22. Available online: https://repositorio.uca.edu.ar/handle/123456789/7958. Accessed on 24 Dec 2024.

  60. Parasuraman A, Colby CL. An updated and streamlined technology readiness index TRI 2.0. J Serv Res. 2014;18(1):59–74.

    Article  Google Scholar 

  61. Rapee RM, Wignall A, Sheffield J, Kowalenko N, Davis A, McLoone J, Spence SH. Adolescents’ reactions to universal and indicated prevention programs for depression: Perceived stigma and consumer satisfaction. Prev Sci. 2006;7(2):167–77.

    Article  PubMed  Google Scholar 

  62. Schnall R, Cho H, Liu J. Health Information Technology Usability Evaluation Scale (Health-ITUES) for usability assessment of mobile health technology: validation study. JMIR Mhealth Uhealth. 2018;6(1):e4.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Arigo D, Jake-Schoffman DE, Wolin K, Beckjord E, Hekler EB, Pagoto SL. The history and future of digital health in the field of behavioral medicine. J Behav Med. 2019;42(1):67–83.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Tsang S, Royse CF, Terkawi AS. Guidelines for developing, translating, and validating a questionnaire in perioperative and pain medicine. Saudi J Anaesth. 2017;11(Suppl 1):S80–9.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We would like to thank Director General of Health, Ministry of Health Malaysia for the approval to publish this article.

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Authors and Affiliations

  1. Pharmacy Department, Hospital Pulau Pinang, George Town, Penang, 10990, Malaysia

    Phei Ching Lim

  2. Universiti Sains Malaysia, Minden, Penang, 11800, Malaysia

    Phei Ching Lim & Hadzliana Zainal

  3. Clinical Research Centre, Hospital Pulau Pinang, George Town, Penang, 10990, Malaysia

    Yen Li Lim

  4. Institute for Clinical Research, National Institutes of Health, Ministry of Health, Shah Alam, Selangor, 40170, Malaysia

    Yen Li Lim

  5. Pharmacy Department, Hospital Seberang Jaya, Perai, Penang, 13700, Malaysia

    Retha Rajah

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Contributions

P.C.L., Y.L.L., R.R. and H.Z. contributed to the study conception, design, material preparation and analysis. All authors contributed equally to this work including data collection, writing and review of manuscript. All authors read and approved the final manuscript.

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Correspondence to Yen Li Lim or Hadzliana Zainal.

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This research is registered in the National Medical Research Register, Malaysia (No. NMRR-22–02846-I21) and approved by the Medical Research Ethics Committee, Malaysia. There was no consent form involved in the literature search, and no patient identifiers were used.

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Lim, P.C., Lim, Y.L., Rajah, R. et al. Usability questionnaire for standalone or interactive mobile health applications: a systematic review. BMC Digit Health 3, 11 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s44247-025-00150-y

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Keywords

BMC Digital Health

ISSN: 2731-684X

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