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

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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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-022-01764-2.

Related collections

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Is Open Access

Mobile App Rating Scale: A New Tool for Assessing the Quality of Health Mobile Apps

Stoyan Stoyanov, Leanne Hides, David J Kavanagh … (2015)

Background The use of mobile apps for health and well being promotion has grown exponentially in recent years. Yet, there is currently no app-quality assessment tool beyond “star”-ratings. Objective The objective of this study was to develop a reliable, multidimensional measure for trialling, classifying, and rating the quality of mobile health apps. Methods A literature search was conducted to identify articles containing explicit Web or app quality rating criteria published between January 2000 and January 2013. Existing criteria for the assessment of app quality were categorized by an expert panel to develop the new Mobile App Rating Scale (MARS) subscales, items, descriptors, and anchors. There were sixty well being apps that were randomly selected using an iTunes search for MARS rating. There were ten that were used to pilot the rating procedure, and the remaining 50 provided data on interrater reliability. Results There were 372 explicit criteria for assessing Web or app quality that were extracted from 25 published papers, conference proceedings, and Internet resources. There were five broad categories of criteria that were identified including four objective quality scales: engagement, functionality, aesthetics, and information quality; and one subjective quality scale; which were refined into the 23-item MARS. The MARS demonstrated excellent internal consistency (alpha = .90) and interrater reliability intraclass correlation coefficient (ICC = .79). Conclusions The MARS is a simple, objective, and reliable tool for classifying and assessing the quality of mobile health apps. It can also be used to provide a checklist for the design and development of new high quality health apps.

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Author and article information

Contributors

Kambiz Bahaadinbeigy: Kbahaadini@kmu.ac.ir , kambizb321@gmail.com

Journal

Journal ID (nlm-ta): BMC Med Inform Decis Mak

Journal ID (iso-abbrev): BMC Med Inform Decis Mak

Title: BMC Medical Informatics and Decision Making

Publisher: BioMed Central (London )

ISSN (Electronic): 1472-6947

Publication date (Electronic): 27 January 2022

Publication date PMC-release: 27 January 2022

Publication date Collection: 2022

Volume: 22

Electronic Location Identifier: 22

Affiliations

[1 ]GRID grid.412105.3, ISNI 0000 0001 2092 9755, Medical Informatics Research Center, Institute for Futures Studies in Health, , Kerman University of Medical Sciences, ; Kerman, Iran

[2 ]GRID grid.411583.a, ISNI 0000 0001 2198 6209, Department of Medical Informatics, Faculty of Medicine, , Mashhad University of Medical Sciences, ; Mashhad, Iran

[3 ]GRID grid.1003.2, ISNI 0000 0000 9320 7537, Centre for Health Services Research, , The University of Queensland, ; Brisbane, Australia

[4 ]GRID grid.1002.3, ISNI 0000 0004 1936 7857, School of Psychological Sciences, , Monash University, ; Melbourne, Australia

[5 ]GRID grid.412105.3, ISNI 0000 0001 2092 9755, Department of Health Information Sciences, Faculty of Management and Medical Information Sciences, , Kerman University of Medical Sciences, ; Kerman, Iran

[6 ]GRID grid.412105.3, ISNI 0000 0001 2092 9755, Gastroenterology and Hepatology Research Center, Institute of Basic and Clinical Physiology Sciences, , Kerman University of Medical Sciences, ; Kerman, Iran

Article

Publisher ID: 1764

DOI: 10.1186/s12911-022-01764-2

PMC ID: 8793175

PubMed ID: 35081953

SO-VID: 5201cc11-4cbc-4911-af28-2612e10d8470

License:

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