Methods of usability testing in the development of eHealth applications: A scoping review

BACKGROUND The number of eHealth applications has exponentially increased in recent years, with over 325,000 health apps now available on all major app stores. This is in addition to other eHealth applications available on other platforms such as PC software, web sites and even gaming consoles. As with other digital applications, usability is one of the key factors in the successful implementation of eHealth apps. Reviews of the literature on empirical methods of usability testing in eHealth were last published in 2015. In the context of an exponentially increasing rate of App development year on year, an updated review is warranted. OBJECTIVE To identify, explore, and summarize the current methods used in the usability testing of eHealth applications. METHODS A scoping review was conducted on literature available from April 2014 up to October 2017. Four databases were searched. Literature was considered for inclusion if it was (1) focused on an eHealth application (which includes websites, PC software, smartphone and tablet applications), (2) provided information about usability of the application, (3) provided empirical results of the usability testing, (4) a full or short paper (not an abstract) published in English after March 2014. We then extracted data pertaining to the usability evaluation processes described in the selected studies. RESULTS 133 articles met the inclusion criteria. The methods used for usability testing, in decreasing order of frequency were: questionnaires (n = 105), task completion (n = 57), 'Think-Aloud' (n = 45), interviews (n = 37), heuristic testing (n = 18) and focus groups (n = 13). Majority of the studies used one (n = 45) or two (n = 46) methods of testing. The rest used a combination of three (n = 30) or four (n = 12) methods of testing usability. None of the studies used automated mechanisms to test usability. The System Usability Scale (SUS) was the most frequently used questionnaire (n = 44). The ten most frequent health conditions or diseases where eHealth apps were being evaluated for usability were the following: mental health (n = 12), cancer (n = 10), nutrition (n = 10), child health (n = 9), diabetes (n = 9), telemedicine (n = 8), cardiovascular disease (n = 6), HIV (n = 4), health information systems (n = 4) and smoking (n = 4). Further iterations of the app were reported in a minority of the studies (n = 41). The use of the 'Think-Aloud' (Pearson Chi-squared test: χ2 = 11.15, p < 0.05) and heuristic walkthrough (Pearson Chi-squared test: χ2 = 4.48, p < 0.05) were significantly associated with at least one further iteration of the app being developed. CONCLUSION Although there has been an exponential increase in the number of eHealth apps, the number of studies that have been published that report the results of usability testing on these apps has not increased at an equivalent rate. The number of digital health applications that publish their usability evaluation results remains only a small fraction. Questionnaires are the most prevalent method of evaluating usability in eHealth applications, which provide an overall measure of usability but do not pinpoint the problems that need to be addressed. Qualitative methods may be more useful in this regard. The use of multiple evaluation methods has increased. Automated methods such as eye tracking have not gained traction in evaluating health apps. Further research is needed into which methods are best suited for the different types of eHealth applications, according to their target users and the health conditions being addressed.

[1]  Laurie A Huryk Factors influencing nurses' attitudes towards healthcare information technology. , 2010, Journal of nursing management.

[2]  Harry Bouwman,et al.  Context of Use: The Final Frontier in the Practice of User-Centered Design? , 2016, Interact. Comput..

[3]  Ray B. Jones,et al.  Searching for a sustainable process of service user and health professional online discussions to facilitate the implementation of e-health , 2016, Health Informatics J..

[4]  Laurie A. Huryk Rn Factors influencing nurses’ attitudes towards healthcare information technology , 2010 .

[5]  Susy Braun,et al.  Design and Development of a Telerehabilitation Platform for Patients With Phantom Limb Pain: A User-Centered Approach , 2017, JMIR rehabilitation and assistive technologies.

[6]  Aldo von Wangenheim,et al.  Quality Evaluation of Poison Control Information Systems: A Case Study of the DATATOX System , 2016, 2016 IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS).

[7]  Arsénio Reis,et al.  Using Intelligent Personal Assistants to Strengthen the Elderlies' Social Bonds - A Preliminary Evaluation of Amazon Alexa, Google Assistant, Microsoft Cortana, and Apple Siri , 2017, HCI.

[8]  Harry Hochheiser,et al.  A prototype mobile application for triaging dental emergencies. , 2016, Journal of the American Dental Association.

[9]  Jacek Gwizdka,et al.  Using Wireless EEG Signals to Assess Memory Workload in the $n$-Back Task , 2016, IEEE Transactions on Human-Machine Systems.

[10]  Pearl Brereton,et al.  Systematic literature reviews in software engineering - A tertiary study , 2010, Inf. Softw. Technol..

[11]  Gunnar Hartvigsen,et al.  Assessing the Potential Use of Eye-Tracking Triangulation for Evaluating the Usability of an Online Diabetes Exercise System , 2015, MedInfo.

[12]  Nicol Nijland,et al.  Why Business Modeling is Crucial in the Development of eHealth Technologies , 2011, Journal of medical Internet research.

[13]  Peter Pirolli,et al.  Acceptability of a team-based mobile health (mHealth) application for lifestyle self-management in individuals with chronic illnesses , 2016, EMBC.

[14]  W. Buxton Human-Computer Interaction , 1988, Springer Berlin Heidelberg.

[15]  Aldo von Wangenheim,et al.  Software Quality Evaluation of the Laboratory Information System Used in the Santa Catarina State Integrated Telemedicine and Telehealth System , 2016, 2016 IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS).

[16]  Jasmine Travers,et al.  A user-centered model for designing consumer mobile health (mHealth) applications (apps) , 2016, J. Biomed. Informatics.

[17]  Alexandre Savaris,et al.  GISTelemed: An online-based GIS approach to epidemiological analysis in telemedicine systems , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[18]  Mei R Fu,et al.  mHealth self-care interventions: managing symptoms following breast cancer treatment. , 2016, mHealth.

[19]  Theresa Devine,et al.  Designing Health Literate Mobile Apps , 2014 .

[20]  Brianna S Fjeldsoe,et al.  Iterative development of Stand Up Australia: a multi-component intervention to reduce workplace sitting , 2014, International Journal of Behavioral Nutrition and Physical Activity.

[21]  Jorgen P. Bansler,et al.  Aligning Concerns in Telecare: Three Concepts to Guide the Design of Patient-Centred E-Health , 2018, Computer Supported Cooperative Work (CSCW).

[22]  Andres Ledesma,et al.  Health figures: an open source JavaScript library for health data visualization , 2016, BMC Medical Informatics and Decision Making.

[23]  P. Sandercock,et al.  Framework for design and evaluation of complex interventions to improve health , 2000, BMJ : British Medical Journal.

[24]  William Brown,et al.  Assessment of the Health IT Usability Evaluation Model (Health-ITUEM) for evaluating mobile health (mHealth) technology , 2013, J. Biomed. Informatics.

[25]  Hongming Zhu,et al.  Extending Mobile App Analytics for Usability Test Logging , 2017, INTERACT.

[26]  Warner V. Slack,et al.  Reflections on electronic medical records: When doctors will use them and when they will not , 2010, Int. J. Medical Informatics.

[27]  Monique W. M. Jaspers,et al.  Pre-Post Evaluation of Physicians' Satisfaction with a Redesigned Electronic Medical Record System , 2008, MIE.

[28]  Maria Ebling,et al.  Can Cognitive Assistants Disappear? , 2016, IEEE Pervasive Comput..

[29]  Patricia McInerney,et al.  The Joanna Briggs Institute reviewers' manual 2015: methodology for JBI scoping reviews , 2015 .

[30]  Alejandro Rodríguez-Molinero,et al.  A Human-Centered Design Methodology to Enhance the Usability, Human Factors, and User Experience of Connected Health Systems: A Three-Phase Methodology , 2017, JMIR human factors.

[31]  Trisha Greenhalgh,et al.  Beyond Adoption: A New Framework for Theorizing and Evaluating Nonadoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies , 2017, Journal of medical Internet research.

[32]  Jennifer Dixon,et al.  The NHS long term plan , 2019, British Medical Journal.

[33]  Ali Idri,et al.  Empirical Studies on Usability of mHealth Apps: A Systematic Literature Review , 2015, Journal of Medical Systems.

[34]  Harry Bouwman,et al.  Addressing the Context of Use in Mobile Computing: a Survey on the State of the Practice , 2015, Interact. Comput..

[35]  Alejandro Rodríguez-Molinero,et al.  Human-Centered Design Study: Enhancing the Usability of a Mobile Phone App in an Integrated Falls Risk Detection System for Use by Older Adult Users , 2017, JMIR mHealth and uHealth.