Skip to main content

The most used questionnaires for evaluating satisfaction, usability, acceptance, and quality outcomes of mobile health

Abstract

Background

Various questionnaires are used for evaluating satisfaction, usability, acceptance, and quality outcomes of mobile health (mHealth) services. Using the best one to meet the needs of an mHealth study is a challenge for researchers. Therefore, this study aimed to review and determine the frequently used questionnaires for evaluating the mentioned outcomes of mHealth services.

Methods

The PubMed database was searched for conducting this review in April 2021. Papers that used a referenced questionnaire to evaluate the satisfaction, usability, acceptance, or quality outcomes of mHealth were included. The first author’s name, year of publication, evaluation outcome, and evaluation questionnaire were extracted from relevant papers. Data were analyzed using descriptive statistics.

Results

In total, 247 papers were included in the study. Questionnaires were used for usability (40%), quality (34.5%), acceptance (8.5%), and satisfaction (4%) outcomes, respectively. System usability scale (36.5%), mobile application rating scale (35.5%), post study system usability questionnaire (6%), user mobile application rating scale (5%), technology acceptance model (4.5%), computer system usability questionnaire (2.5%), net promoter score (2%), health information technology usability evaluation scale (2%), the usefulness, satisfaction, and ease of use (1.5%), client satisfaction questionnaire (1.5%), unified theory of acceptance and use of technology (1.5%), questionnaire for user interaction satisfaction (1%), user experience questionnaire (1%), and after-scenario questionnaire (1%) were the most used questionnaires, respectively.

Conclusion

Despite the existence of special questionnaires for evaluating several outcomes of mHealth, general questionnaires with fewer items and higher reliability have been used more frequently. Researchers should pay more attention to questionnaires with a goal-based design.

Peer Review reports

Background

In recent years, mobile phones have found a special role in people's daily lives because of their portability and availability. Mobile phones are also used in the healthcare field for different purposes [1]. The use of mobile and wireless communication technologies to improve disease management, medication adherence, medical decision-making, medical education, and research is named mobile health (mHealth) [2, 3]. mHealth includes the use of simple capabilities of a mobile device such as voice call and short messaging service (SMS) as well as more complex applications designed for medical, fitness, and public health purposes [4].

mHealth could help patients to monitor and control their health when they do not have access to healthcare providers [1]. Along with the potential benefits of mHealth, some factors such as perceived ease of use, perceived usefulness, content quality and accuracy, and consumer attitude can influence the use of this technology [5]. Therefore, evaluating mHealth services in terms of different aspects such as usability, user satisfaction and acceptance, and quality is important.

Usability is defined as “the extent to which a product can be used by specified users to achieve specified goals with effectiveness, efficiency, and satisfaction in a specified context of use” by ISO 9241-11 [6]. A review study showed that about 88% of the studies that evaluated the usability of mobile applications used the above-mentioned definition [7]. There are two general methods for usability evaluation, including user evaluation and expert inspection [8]. User satisfaction is defined as “the net feeling of pleasure or displeasure that results from aggregating all the benefits that a person hopes to receive from interaction with the information system” [9]. The Cambridge Dictionary defines acceptance as a “general agreement that something is satisfactory or right” [10]. In the technology acceptance lifecycle, acceptance is measured in both the initial and sustained use stages of mHealth services [11]. As Stoyanov et al. indicated in their study, the quality of mHealth applications is evaluated in different categories, including engagement, functionality, aesthetics, information quality, and subjective quality [12].

There are various methods for evaluating mHealth services, such as questionnaires, interviews, and observation [11, 13, 14]. Researchers use a variety of general and specified questionnaires for evaluating different aspects of mHealth services. Studies usually use previously designed questionnaires [15, 16] and sometimes design a new one with compliance to their needs [12, 17]. The validity and reliability of the used questionnaires are important in any scientific project.

Due to the existence of a large number of questionnaires, selecting and using the appropriate one to meet the needs of an mHealth study is a challenge for researchers. To the best of our knowledge, no study has reviewed and listed the most appropriate questionnaires for evaluating different outcomes of mHealth services including satisfaction, usability, acceptance, and quality. Therefore, this study aimed to review and introduce the frequently used questionnaires for evaluating the mentioned outcomes. The results of this study will help other investigations to select the appropriate goal-based questionnaire.

Methods

Database and date

PubMed database was searched for conducting this review study. The search was performed on 18 April 2021 without date restriction.

Search strategy

We used three categories of keywords for setting the search strategy (Table 1). The keywords in each category were combined and searched by OR Boolean operator. Then the results of these searches were combined by AND Boolean operator for retrieving relevant papers. The search was conducted in the Title/Abstract search field and was filtered with English language.

Table 1 Keywords used for the search strategy

Inclusion criteria

The following studies were included in the study:

  • Original observational and interventional research papers in which a referenced questionnaire or a questionnaire that has been used at least two times in the studies was used to evaluate the satisfaction, usability, acceptance, and quality outcomes of mhealth.

  • App review studies that used the Mobile Application Rating Scale (MARS) for the evaluation of mhealth applications.

Exclusion criteria

The following studies were excluded from the study:

  • Review, protocol, conference, and report papers

  • Papers without full text

  • Papers that did not use mhealth services

  • Papers that did not evaluate satisfaction, usability, acceptance, and quality outcomes

  • Papers that did not use a referenced questionnaire

  • Papers that did not include details about the questionnaires used

Paper selection

In the first stage, all the retrieved papers were reviewed based on title and abstract by two authors (S.H, F.Kh). Next, the same individuals assessed the full text of the selected papers. In the cases of disagreements, the opinion of the other author (K.B) was asked. Finally, a list of included papers was provided.

Data extraction

The first author’s name, year of publication, evaluation outcome, and evaluation questionnaire were extracted from the included papers.

Data analysis

Data were analyzed using descriptive statistics including frequency and frequency percentage.

Results

Searching the PubMed database resulted in 1028 papers. The title and abstract of all these papers were screened. A total of 683 papers were excluded. After that, the full text of the 345 remaining papers was reviewed. Finally, 247 papers were included for extracting data (Fig. 1).

Fig. 1
figure 1

The process of finding and including the papers

The extracted data from the included papers are presented in Additional file 1: Appendix 1. The main results were as follows:

Year of publication

The included papers have been published since 2014. The number of papers has increased since that time (Fig. 2). More than half of the papers (67%) were published in the last three years (2019, 2020, and 2021).

Fig. 2
figure 2

The number of papers based on the year of publication

Evaluation outcome

The evaluation outcomes in this study referred to usability, satisfaction, acceptance, and quality of mHealth services. Usability is the most evaluated outcome that was assessed by a questionnaire in the studies (n = 99, 40%). After that, quality (n = 85, 34.5%), acceptance (n = 21, 8.5%), and satisfaction (n = 10, 4%) were the most evaluated outcomes, respectively. The remaining papers evaluated more than one outcome, including usability and satisfaction (n = 10, 4%), usability and quality (n = 9, 3.5%), usability and acceptance (n = 9, 3.5%), satisfaction and quality (n = 3, 1%), and satisfaction and acceptance (n = 3, 1%).

Evaluation questionnaire

The most used questionnaires (more than two times) for evaluating mHealth services are shown in Table 2. The other questionnaires have been used in 17 papers (7%). Forty-three (17.5%) papers used more than one questionnaire.

Table 2 The most frequently used questionnaires for evaluating mHealth services

Discussion

This study was performed to review the most frequently used questionnaires for evaluating satisfaction, usability, acceptance, and quality outcomes of mHealth services. Usability is the most evaluated outcome in the mHealth studies. SUS, PSSUQ, and CSUQ were the top three most used questionnaires for evaluating the usability of mHealth services, respectively. The two most used questionnaires for evaluating the quality of mHealth applications were MARS and uMARS. In addition, TAM and UTAUT were the most used questionnaires for measuring the user acceptance of mHealth services. The three most used questionnaires for evaluating user satisfaction were NPS, CSQ, and GEQ.

Usability evaluation questionnaires

The present study showed that SUS questionnaire had been used much more than similar questionnaires such as PSSUQ and CSUQ in evaluating the usability of mHealth services. SUS is a general questionnaire that is used for evaluating the usability of electronic systems such as mobile devices. Compared with other questionnaires such as CSUQ, SUS is a quicker tool for judging the perceived usability of systems because it has fewer items with less scale pointing. This questionnaire also includes a question regarding the satisfaction of the user with the digital solution. The satisfaction evaluation questionnaires focus on tools that evaluate only this outcome, but it is also contained in the usability outcome [18, 19]. Because of these features and its reproducibility, reliability, and validity, researchers and evaluators of mHealth services have frequently used the SUS questionnaire. Another study that reviewed the most used questionnaires for evaluating telemedicine services also showed that SUS is the most used general questionnaire after the Telehealth Usability Questionnaire (TUQ), which is a specific questionnaire for evaluating the usability of telemedicine systems [35].

Although MAUQ was specifically designed for evaluating the usability of mHealth applications and considered both interactive and standalone mHealth applications [17], it was rarely used in the studies that were included in our review. This lack of use might be due to the fact that MAUQ was introduced 2 years ago, and researchers are less familiar with this questionnaire. It is recommended that researchers and evaluators of mHealth services use such questionnaires that were specifically designed for evaluating these services.

Quality evaluation questionnaires

MARS and its user version (uMARS) were the most used questionnaires for assessing the quality of mHealth applications. To use MARS for evaluating mHealth applications, users should be professional in mHealth. Because of this limitation, uMARS was designed to be administered by end-users without special expertise. The importance of the quality and reliability of information and content provided in mHealth applications and the impact that this content has on people's health led to the design of MARS [12]. MARS prompted researchers to look at another consequence of mHealth, which significantly impacts the practical and safe use of mHealth applications. This issue has led to the use of these questionnaires in many studies.

Acceptance evaluation questionnaires

This study revealed that TAM and UTAUT were the most used questionnaires for measuring mHealth acceptance. These questionnaires were derived from two models with the same name. Generally, TAM and UTAUT are the most used acceptance models in health informatics because of their simplicity [36]. Both models focus on the usefulness and easy use of technology. Since UTAUT derives from eight models such as TAM, it evaluates two additional factors, including social environment and organizational infrastructure, that may impact the adoption of the new technology [36]. However, since TAM and UTAUT have not been developed in healthcare settings, different emotional, organizational, and cultural factors that may influence technology acceptance in healthcare settings are not covered by these two questionnaires [23, 30]. Therefore, researchers in health informatics would better design the acceptance questionnaire based on the objective systems.

Satisfaction evaluation questionnaires

The present research revealed that NPS is the most widely used tool for measuring the satisfaction of m-Health users. NPS is a very small tool for evaluating client satisfaction. This tool only has one question [25]. The fact that this scale has only one item has probably contributed to its wide use. It should be taken into account that a single question cannot identify the various factors that affect user satisfaction with a service. After NPS, CSQ and GEQ were the most used questionnaires in reviewed articles. CSQ has two characteristics that may affect its usage. The first one is that it considers the quality of different aspects, such as procedure, environment, staff, service, and outcome. The second characteristic is that with this comprehensiveness, this questionnaire has only eight items [29]. Studies that used mobile-based games to provide mHealth services used GEQ [37, 38] because it is a specific, comprehensive, and practical questionnaire that measures game user satisfaction [34]. Melin et al. presented a questionnaire for assessing the satisfaction of mHealth applications users [39]. However, none of the papers included in our study used this questionnaire because this is a new tool, and researchers are less familiar with it. It is recommended that researchers in mHealth, use this specific questionnaire in their future studies.

Evaluation outcomes

Most of the included papers evaluated the usability of mHealth services using a questionnaire. Usability is a critical issue that affects willingness to use a system. Therefore, it is essential to evaluate this outcome in different phases of system development. The questionnaire is the most used method for evaluating the usability outcome of a mobile application because of its simpleness in terms of accomplishment and data analysis [17]. A review study also showed that the usability of mHealth applications is mostly assessed using a questionnaire [40]. Another study revealed that questionnaires were mostly used for evaluating the user satisfaction outcome of telemedicine [35]. The differences between the results of our research and those of this study may be due to the fact that mHealth services are mostly presented with an application; therefore, evaluating the user interface of the application is very important and should be considered for effective use [40].

Limitations

To the best of our knowledge, this is the first study that reviewed the most used questionnaires for evaluating the satisfaction, usability, acceptance, and quality outcomes of mHealth services. Nevertheless, this study has some limitations. We only searched the PubMed database to retrieve relevant papers. Also, we restricted our search to the Title/Abstract field. Moreover, we excluded review papers and only included the app review studies that use MARS. These limitations may have led to the missing of some papers from our study.

Conclusion

This study showed that usability and quality were the most frequently considered outcomes in the mHealth field. Since user acceptance and satisfaction with mHealth services lead to more engagement in using these applications, they should be more considered. Although there is a questionnaire that is specifically designed for measuring several mHealth outcomes, general questionnaires such as SUS, PSSUQ, TAM, CSUQ, Health-ITUES, the USE, CSQ, UTAUT, QUIS, UEQ, and ASQ are mostly used for evaluating mHealth services. Moreover, the results showed that researchers prefer to use questionnaires with high reliability and fewer items. Therefore, when selecting the best-fitted questionnaires for evaluating different outcomes of mHealth services, it is better to pay more attention to the reliability and the number of questions and items.

Availability of data and materials

Not applicable.

Abbreviations

mhealth:

Mobile health

ISO:

International Organization for Standardization

MARS:

Mobile application rating scale

SUS:

System usability scale

PSSUQ:

Post study system usability questionnaire

uMARS:

User mobile application rating scale

TAM:

Technology acceptance model

CSUQ:

Computer system usability questionnaire

NPS:

Net promoter score

Health-ITUES:

Health information technology usability evaluation scale

USE:

Usefulness, satisfaction, and ease of use

CSQ:

Client satisfaction questionnaire

UTAUT:

Unified theory of acceptance and use of technology

QUIS:

Questionnaire for user interaction satisfaction

UEQ:

User experience questionnaire

ASQ:

After-scenario questionnaire

MAUQ:

MHealth app usability questionnaire

GEQ:

Game experience questionnaire

TUQ:

Telehealth usability questionnaire

SUTAQ:

Service user technology acceptability questionnaire

References

  1. Kao CK, Liebovitz DM. Consumer mobile health apps: current state, barriers, and future directions. PM & R J Inj Funct Rehabil. 2017;9(5s):S106–15.

    Google Scholar 

  2. Park Y-T. Emerging new era of mobile health technologies. Healthc Inform Res. 2016;22(4):253–4.

    Article  Google Scholar 

  3. Singh K, Landman AB. Mobile health. In: Sheikh A, Bates DW, Wright A, Cresswell K, editors. Key advances in clinical informatics: Transforming health care through health information technology. London: Academic Press; 2018. p. 183–96.

    Google Scholar 

  4. World Health Organization. mHealth: New horizons for health through mobile technologies. 2011. Available from: https://www.who.int/goe/publications/goe_mhealth_web.pdf.

  5. Mangkunegara C, Azzahro F, Handayani P. Analysis of factors affecting user's intention in using mobile health application: a case study of halodoc. 2018. p. 87–92

  6. ISO9241-11. Ergonomics of human–system interaction—Part 11: usability: definitions and concepts 2018. Available from: https://www.iso.org/obp/ui/#iso:std:iso:9241:-11:ed-2:v1:en.

  7. Weichbroth P. Usability of mobile applications: a systematic literature study. IEEE Access. 2020;8:55563–77.

    Article  Google Scholar 

  8. Swaid S. Usability of mobile apps: an integrated approach. AHFE; July 17-212017.

  9. Seddon PB. A respecification and extension of the DeLone and McLean model of IS success. Inf Syst Res. 1997;8(3):240–53.

    Article  Google Scholar 

  10. Cambridge Dictionary-Cambridge University Press. Acceptance 2020 [Available from: https://dictionary.cambridge.org/dictionary/english/acceptance.

  11. Nadal C, Sas C, Doherty G. Technology acceptance in mobile health: scoping review of definitions, models, and measurement. J Med Internet Res. 2020;22(7):e17256.

    Article  Google Scholar 

  12. Stoyanov SR, Hides L, Kavanagh DJ, Zelenko O, Tjondronegoro D, Mani M. Mobile app rating scale: a new tool for assessing the quality of health mobile apps. JMIR mHealth uHealth. 2015;3(1):e27.

    Article  Google Scholar 

  13. Jake-Schoffman DE, Silfee VJ, Waring ME, Boudreaux ED, Sadasivam RS, Mullen SP, et al. Methods for evaluating the content, usability, and efficacy of commercial mobile health apps. JMIR mHealth uHealth. 2017;5(12):e190-e.

    Article  Google Scholar 

  14. Maramba I, Chatterjee A, Newman C. Methods of usability testing in the development of eHealth applications: a scoping review. Int J Med Inform. 2019;126:95–104.

    Article  Google Scholar 

  15. Alanzi T, Istepanian R, Philip N. Design and usability evaluation of social mobile diabetes management system in the gulf region. JMIR Res Protoc. 2016;5(3):e93.

    Article  Google Scholar 

  16. Bakogiannis C, Tsarouchas A, Mouselimis D, Lazaridis C, Theofillogianakos EK, Billis A, et al. A patient-oriented app (ThessHF) to improve self-care quality in heart failure: from evidence-based design to pilot study. JMIR mHealth uHealth. 2021;9(4):e24271.

    Article  Google Scholar 

  17. 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  Google Scholar 

  18. Lewis JR. The system usability scale: past, present, and future. Int J Hum Comput Interact. 2018;34(7):577–90.

    Article  Google Scholar 

  19. Brooke J. Sus: a “quick and dirty’usability. J Usability Eval Ind. 1996;189:189–94.

    Google Scholar 

  20. Terhorst Y, Philippi P, Sander LB, Schultchen D, Paganini S, Bardus M, et al. Validation of the mobile application rating scale (MARS). PLoS ONE. 2020;15(11):e0241480.

    CAS  Article  Google Scholar 

  21. Lewis JR, editor. Psychometric evaluation of the post-study system usability questionnaire: the PSSUQ. In: Proceedings of the human factors society annual meeting. Los Angeles: Sage Publications; 1992.

  22. Stoyanov SR, Hides L, Kavanagh DJ, Wilson H. Development and validation of the user version of the mobile application rating scale (uMARS). JMIR mHealth uHealth. 2016;4(2):e72.

    Article  Google Scholar 

  23. Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. J MIS Q. 1989;13:319–40.

    Article  Google Scholar 

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

    Article  Google Scholar 

  25. Reichheld FF. The one number you need to grow. Harv Bus Rev. 2003;81(12):46–54.

    PubMed  Google Scholar 

  26. Yen P-Y, Wantland D, Bakken S. Development of a customizable health it usability evaluation scale. In: AMIA annual symposium proceedings/AMIA symposium, vol. 2010. 2010. p. 917–21.

  27. Lund A. Measuring usability with the use questionnaire. Usability and user experience newsletter of the STC usability SIG. Usability Interface. 2001;8:3–6.

    Google Scholar 

  28. Gao M, Kortum P, Oswald F, editors. Psychometric evaluation of the use (usefulness, satisfaction, and ease of use) questionnaire for reliability and validity. In: Proceedings of the human factors and ergonomics society annual meeting. Los Angeles: SAGE Publications; 2018

  29. Larsen DL, Attkisson CC, Hargreaves WA, Nguyen TD. Assessment of client/patient satisfaction: development of a general scale. Eval Program Plan. 1979;2(3):197–207.

    CAS  Article  Google Scholar 

  30. Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: toward a unified view. MIS Q. 2003;27:425–78.

    Article  Google Scholar 

  31. Chin JP, Diehl VA, Norman KL, editors. Development of an instrument measuring user satisfaction of the human-computer interface. In: Proceedings of the SIGCHI conference on human factors in computing systems; 1988.

  32. Laugwitz B, Held T, Schrepp M, editors. Construction and evaluation of a user experience questionnaire. HCI and usability for education and work. Berlin: Springer; 2008.

    Google Scholar 

  33. Lewis J. Psychometric evaluation of an after-scenario questionnaire for computer usability studies: the ASQ. SIGCHI Bull. 1991;23:78–81.

    Article  Google Scholar 

  34. Poels K, de Kort YAW, IJsselsteijn WA. D3.3: Game Experience Questionnaire. Eindhoven: Technische Universiteit Eindhoven; 2007.

    Google Scholar 

  35. Hajesmaeel-Gohari S, Bahaadinbeigy K. The most used questionnaires for evaluating telemedicine services. BMC Med Inform Decis Mak. 2021;21(1):36.

    Article  Google Scholar 

  36. Ammenwerth E. Technology acceptance models in health informatics: TAM and UTAUT. Stud Health Technol Inform. 2019;263:64–71.

    PubMed  Google Scholar 

  37. De Cock N, Van Lippevelde W, Vangeel J, Notebaert M, Beullens K, Eggermont S, et al. Feasibility and impact study of a reward-based mobile application to improve adolescents’ snacking habits. Public Health Nutr. 2018;21(12):2329–44.

    Article  Google Scholar 

  38. Lawitschka A, Buehrer S, Bauer D, Peters K, Silbernagl M, Zubarovskaya N, et al. A web-based mobile app (INTERACCT App) for adolescents undergoing cancer and hematopoietic stem cell transplantation aftercare to improve the quality of medical information for clinicians: observational study. JMIR mHealth uHealth. 2020;8(6):e18781.

    Article  Google Scholar 

  39. Melin J, Bonn SE, Pendrill L, Lagerros YT. A questionnaire for assessing user satisfaction with mobile health apps: development using rasch measurement theory. JMIR mHealth uHealth. 2020;8(5):e15909.

    Article  Google Scholar 

  40. Ansaar MZ, Hussain J, Bang J, Lee S, Shin KY, Woo KY, editors. The mHealth applications usability evaluation review. In: 2020 International conference on information networking (ICOIN). IEEE; 2020.

Download references

Acknowledgements

We would like to express our gratitude to the Institute for Future Studies in Health of Kerman University of Medical Sciences for providing the research environment.

Funding

This study was funded by Kerman University of Medical Sciences with the research ID 400000266.

Author information

Authors and Affiliations

Authors

Contributions

SH, FF, and KB contributed to designing the study. The selection and evaluation of the papers and data extraction were done by SH and FKh. SH, HS, and KB participated in drafting the manuscript. All authors read and approved the final version of the manuscript.

Corresponding author

Correspondence to Kambiz Bahaadinbeigy.

Ethics declarations

Ethics approval and consent to participate

This research was approved by the Ethics Committee of Kerman University of Medical Sciences with the Ethical ID IR.KMU.REC.1400.197.

Consent to publish

Not applicable.

Competing interests

The authors declare that there are no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1

. The extracted data from the included papers.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Hajesmaeel-Gohari, S., Khordastan, F., Fatehi, F. et al. The most used questionnaires for evaluating satisfaction, usability, acceptance, and quality outcomes of mobile health. BMC Med Inform Decis Mak 22, 22 (2022). https://doi.org/10.1186/s12911-022-01764-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12911-022-01764-2

Keywords

  • Mobile health
  • Questionnaire
  • Evaluation