1. Frith, Karen H.

Article Content

Smartphones are in the hands of most Americans - 77 percent own smartphones, up from 35 percent in 2011, with younger adults more likely than older adults to use the mobile device as their exclusive connection to the Internet (Pew Research Center, 2018). The mobile revolution brings opportunities for nurse scientists to create apps to educate students and health care consumers, while simultaneously evaluating the long-term effects of the interventions made possible through the app. However, the opportunity comes with a responsibility to design apps with the end-user as a primary concern.


Too often end-users are the last thought in the design of an app. Because apps can be developed by anyone with little knowledge of coding and user experience (UX) design principles, the app can be seriously flawed (Wright et al., 2018). For example, Georgsson and Staggers (2016) investigated the usability of a diabetes app and found nearly 120 problems, which they coded into 19 usability categories.


An overarching principle to be used for all technology development is UX design. The UX "focuses on having a deep understanding of users, what they need, what they value, their abilities, and also their limitations" (US Department of Health & Human Services [DHHS], 2014). Apps with excellent UX design have high usability and are pleasurable for individuals to use. The International Organization for Standardization defined usability 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" (International Organization for Standardization, 1998). Usability studies are used to test and refine technology prior to field testing to ensure high usability and end-user satisfaction.


A team of experts, led by nurse scientists, can create an app with excellent UX design. Experts include UX designers with knowledge of human factors, software designers, and statisticians with knowledge of big data. The development of the app must follow a process with the user at the center of each step. At each milestone in the design process, the nurse scientist measures progress toward high-usability benchmarks, because the consequences of moving forward without usability are costly in terms of time and money for the redesign of flaws.


The process of early engagement of end-users requires a well-planned usability study directed by the nurse scientist. Usability studies focus on the interaction between humans and the information technology by way of the app's interface and typically investigate learnability (the ease of learning to use the app), memorability (consistency of the interface), productivity (time on task to accomplish tasks without errors), and user satisfaction with the app (Frith, 2018).


The first step in creating an app with high UX is to engage end-users before the first line of code is written. Although early engagement may sound premature, it is the most effective and least expensive way to begin the app design. Most nurse scientists who have worked with app developers would agree that resistance to reworking code is "directly proportional to the number of lines of code that has been already written" (Frith, 2018).


Realistic drawings on paper of the app's user interface are easy to create; several versions can be presented to end-users for feedback. A low-fidelity prototype can simply be a neatly hand-drawn image of the proposed interface; high-fidelity prototypes are drawn with software to simulate the true appearance of the interface (Adli & Lestari, 2017). A small number of end-users, typically five to eight individuals with different levels of smartphone use, can provide feedback about the layout of icons on the screen, the app navigation, and the desired features (Adli & Lestari, 2017). The nurse scientist gives the end-users time to review the prototype and then provides scenarios of interaction with the prototype. End-users can be asked to think aloud while working through the scenario, which provides insight into ease of use and, potentially, the cognitive load (amount of thinking) needed to complete a task (DHHS, 2018). Omitting the scenario will yield less feedback because end-users will typically give favorable feedback about the look of the interface but will become more critical when too many clicks are required to find information or information is not readily accessible. Open-ended questions posed by the nurse scientist can lead to meaningful data. Questions might include the following: What was your opinion of the app? Is this an app you would use to[horizontal ellipsis]? What are your favorite features? What would you change? The feedback from low- or high-fidelity prototypes becomes the basis for the next step of app development (Adli & Lestari, 2017).


Full-scale usability testing becomes an iterative process that is built into the app development cycles. A research plan for usability testing includes identifying the scope, purpose, schedule of sessions, equipment, participants, scenarios, quantitative metrics with benchmarks, and qualitative measures (DHHS, 2018). Table 1 shows examples of methods to test the app on the elements of usability with a space for benchmarks, results, and redesign plans. This table can be used as part of the usability study design.

Table 1 - Click to enlarge in new windowTable 1 Usability Testing Planning and Evaluation

Quantitative and qualitative measures are used in usability testing, depending on purpose. For example, task time, error rates, and user satisfaction lend themselves to quantitative measurement. A tool for measuring user satisfaction is the 10-item System Usability Scale originally developed by Brooks (1986), with normed scoring to create a percentile rank. However, qualitative methods such as observations about participant eye movements can illustrate navigation problems, and video recordings can record facial expressions that indicate when participants are frustrated or bored. Focus groups or interviews may yield participant suggestions.


Failure to attend to usability can frustrate end-users or cause harm. The responsibility for ensuring outstanding UX with apps created to improve knowledge or change health behaviors rests with nurse scientists and their teams. Nurse scientists who plan to seek funding for research using apps must conduct usability studies prior to field testing if they wish to obtain federal funding or obtain Federal Drug Administration clearance. For more information, readers are encouraged to explore




Adli M. A., & Lestari D. P. (2017). Designing an arisan mobile application for novice users using user-centered design approach. In 2017 International Conference on Advanced Informatics, Concepts, Theory, and Applications (ICAICTA) (pp. 1-6). Geneva, Switzerland: IEEE. doi:10.1016/j.jbi.2016.02.002 [Context Link]


Brooks J. (1986). SUS-A quick and dirty usability scale. Reading, United Kingdom: Digital Equipment. Retrieved from[Context Link]


Frith K. H. (2018). Usability in health Information technology. In Alexander S., Frith K. H., & Hoy H. (Eds.), Applied clinical informatics for nurses (2nd ed.). Burlington, MA: Jones and Bartlett Learning. [Context Link]


Georgsson M., & Staggers N. (2016). An evaluation of patients' experienced usability of a diabetes mHealth system using a multi-method approach. Journal of Biomedical Informatics, 59, 115-129. doi:10.1016/j.jbi.2015.11.008 [Context Link]


International Organization for Standardization. (1998). ISO 9241-11. Ergonomic requirements for office work with visual display terminals (VDTs) - Part 11: guidance on usability. Author. [Context Link]


Pew Research Center. (2018). Demographics of mobile device ownership and adoption in the United States. Retrieved from[Context Link]


US Department of Health & Human Services. (2014). User experience basics. Retrieved[Context Link]


US Department of Health & Human Services. (2018). Running a usability test. Retrieved from[Context Link]


Wright A., Ash J. S., Aaron S., Ai A., Hickman T. T., Wiesen J. F., [horizontal ellipsis] Sittig D. F. (2018). Best practices for preventing malfunctions in rule-based clinical decision support alerts and reminders: Results of a Delphi study. International Journal of Medical Informatics, 118, 78-85. doi:10.1016/j.ijmedinf.2018.08.001 [Context Link]