Review of literature 2
Agenda for future research 4
Any other 5
This review focuses on mobile medical health apps, with emphasis placed on patients using the app.
The objective was to identify how best to achieve user satisfaction. The review analyses various
studies on how the apps are currently being used and presented to users to identify which aspects of
the apps contribute the most to user satisfaction. The results of the review illustrate that there is a
need for apps to be streamlined, that there is still much research that needs to be conducted on the
topic and that the ratings used by users currently do not help to adequately identify the usability.
User Interfaces and the internet have become part of our everyday lives that we use for communication, to do transactions and get recent issues on the world. There has been a corresponding increase to the number of people using the internet to get health related information (Neubeck et al. 2016).In addition to using the internet to seek medical information, people have adopted the use of health applications (apps) to manage (Cho 2016) the lifestyles (Cho 2016).Before a call actioned by the US Medical institute, health apps have mostly been used by health professionals to manage the clinical health of patients. Recently consumers have shown an interest in consumer health apps which has contributed a rapid adoption of health (Baldwin et al. 2017). In a recent report done in 2017, it is estimated that there are over 325000 health apps in major app stores and over 40 000 are mobile health (mhealth) apps have being used every day. However there is little research on how best to design the apps on how you can make them usable and easy to use (Schnall et al. 2016). The interface plays an important role as it mediates the interaction between users and information displayed which can then influence how a user feels about the app being used (Neubeck et al. 2016). These studies focus on different aspects that make a worthy interfaces of mhealth apps and issues with regards to mobile health apps.
The objective is to find how the dimensions and factors such as visual aesthetics of the app, informative architecture which is how the information is presented, the interaction which describes how users navigate influences and affects a user’s perception of the usability of mobile health applications and what aspects of the application lead to user satisfaction.
Review of literature
As stated above there has been a rapid increase in the adoption of health apps amongst people or consumers (Cho 2016). People are leaning towards using mhealth apps because of how portable these apps are and how easy information is accessible (Paglialonga, Lugo and Santoro 2018).Many people manage their own health by using a diverse range of smartphone apps (Cho 2016). A recent survey showed that among apps users or patients, 66 % patients favour using informative mhealth apps, followed by 52 % use it for apps to access healthcare services and 52 % use it for apps on maintaining a healthy lifestyle (Paglialonga, Lugo and Santoro 2018). In a study conducted by (Sousa and Almeida 2016) they identified five factors or dimensions that affect health apps which are visual(aesthetics of the app), informative architecture which is how the information is presented, the interaction which describes how users navigate around the healthcare systems, social presence and user experience. The findings of that paper suggested that the most influential factors in the information architecture and user experience followed by interaction. (Baldwin et al. 2017) also supports the findings of this study by claiming that patients do not consider the app useful if the information displayed is difficult to understand. In recent study patients or mhealth users abandoned using the apps after two weeks and it shows that it was because of frustration with the design on interface and how difficult it is to navigate (Baldwin et al. 2017). According to Nielson when users view app, they see the content of the interface according to the task proposed to them. So if the content is complex the app is considered difficult to use by the user. (Cho 2016) different elements that make up usability in health and mhelath apps, these elements are confirmation, perceived ease of use, perceived usefulness, satisfaction and intent to continue using app. A user perceives the app as useful when he/she is able to achieve a certain goal, example if the app efficiently manages a health condition user will find that app useful(Cho 2016), furthermore depending on how easy it is to use the app, the user develops some emotions which are most likely satisfaction or dissatisfaction. From the results of (Cho 2016) study it is established that satisfaction of is highly related ease of use, not only that it also determines how likely the user is most likely to continue using the app. There exists some similarity within the elements identified by (Cho 2016) and (Sousa and Almeida 2016) that affect the functionality of the mhealth apps. Fitbit and IPhone 6’s built in health apps are considered more easy to use and intuitive, consumers also requires little effort to use login which covers almost all elements identified in both studies. Another point to be noted with the Fitbit and IPhone 6 is that it requires little effort to use it, this helps achieve better usability and user experience therefore it is important to reduce extraneous task load (Partala and Saari 2015).
One study also identified that some mHealth apps tend to more downloaded because of peer reviews they and how well they were rated by their users but not on how usable they are. However this can be overcome by using accredited rating platforms which assess apps based on a number of features like engagement, functionality, aesthetics and information. Another serious issue with most health apps have been developed to address a specific medical condition meaning there are lots of apps out there. This leads to users being concerned with app overload and have difficulty in keeping up with the different apps for different diseases. (Paglialonga, Lugo and Santoro 2018).
A sample consisting of 343 Korean adults who were currently using health apps on smartphones participated in an online survey. A path analysis was conducted to test the proposed model composed of the main factors from PAM and TAM (Giardina T. D. 2017). Post-acceptance model (PAM); Technology acceptance model (TAM).
A four-phase iterative process involved ten multidisciplinary clinicians and academics (primary care physician, nurses and allied health professionals), two design consultants, one graphic designer, three software developers and fourteen proposed end-users (Neubeck, L. 2016). This 18-month process involved, (1) defining the target audience and needs, (2) pilot testing and modification, (3) software development including validation and testing the algorithm, (4) user acceptance testing and beta testing. From this process, researchers were able to better understand end-user needs and preferences, thereby improving and enriching the progressively thorough system designs and prototypes for a mobile responsive web application.
Our work was guided by the ISR framework which is comprised of 3 cycles: Relevance, Rigor and Design. In the Relevance cycle, we conducted 5 focus groups with 33 targeted end-users. In the Rigor cycle, we performed a review to identify technology-based interventions for meeting the health prevention needs of our target population (Almeida, A. M. 2016). In the Design Cycle, we employed usability evaluation methods to iteratively develop and refine mock-ups for a mHealth app.
• There are too many apps that deal with different aspects of your health making it difficult to manage all of them. In contrast, if one app was developed to accommodate a range of health matters, it would vastly increase the usability for patients as it would centralize everything.
• The general consensus on factors that determine the usability of medical apps as identified by research is that it’s easy to use, the UI is easy to learn, and all medical terms must be phrased in laymen’s terms to ensure understand ability (Cho 2016).
• Most apps are biased because a user would sometimes rate it or not rate it. If the app is popular, it will have many reviews & ratings. With this in mind , you cannot factor (Baldwin et al. 2017) that user ratings are an important method in this ordeal to determine whether the app is effective & efficient.
• The most prominent limitation that has been discovered is that there isn’t much research that has been previously done on the usability for portals for patients (Paglialonga, Lugo and Santoro 2018). Therefore, there isn’t much information to draw conclusive results from. The little research that has been done focuses on the patient’s usage ; not doctor usage which further limits the capability of determining the full usability of the app.
• In terms of mobile health web apps, limitations that have been identified by the literature sources are that privacy is a huge concern (Cho 2016) as it cannot be achieved adequately given the degree of confidentiality associated with medical records. Additionally, it is important that patients be able to retract information that has been entered incorrectly due to the need for accuracy as the app’s results are dependent on the accuracy of the information that is entered.
• A huge limitation in determining the usability of medical apps is that the ratings developed are often biased as they are based on the number of downloads, which determines popularity not the actual usability of the app (Cho 2016). Furthermore, the rating methods used i.e. 5 stars does not accurately portray the usability of the app.
Agenda for future research
In dealing with eHealth services the future research leans towards an overview of the state of the evidence for the use of eHealth and mHealth in improving physical activity and nutrition behaviours in general and special populations. Rapid innovation in eHealth technologies would challenge policymakers and implementers to find a balance between evidence-based integration of technologies and constructive experimentation that may lead to a game-changing breakthrough.
Baldwin, J. L., Singh, H., Sittig, D. F. and Giardina, T. D. 2017. Patient portals and health apps: Pitfalls, promises, and what one might learn from the other. Healthcare, 5 (3): 81-85.
Cho, J. 2016. The impact of post-adoption beliefs on the continued use of health apps. International Journal of Medical Informatics, 87: 75-83.
Neubeck, L., Coorey, G., Peiris, D., Mulley, J., Heeley, E., Hersch, F. and Redfern, J. 2016. Development of an integrated e-health tool for people with, or at high risk of, cardiovascular disease: The Consumer Navigation of Electronic Cardiovascular Tools (CONNECT) web application. International Journal of Medical Informatics, 96: 24-37.
Paglialonga, A., Lugo, A. and Santoro, E. 2018. An overview on the emerging area of identification, characterization, and assessment of health apps. Journal of Biomedical Informatics, 83: 97-102.
Partala, T. and Saari, T. 2015. Understanding the most influential user experiences in successful and unsuccessful technology adoptions. Computers in Human Behavior, 53: 381-395.
Schnall, R., Rojas, M., Bakken, S., Brown, W., Carballo-Dieguez, A., Carry, M., Gelaude, D., Mosley, J. P. and Travers, J. 2016. A user-centered model for designing consumer mobile health (mHealth) applications (apps). Journal of Biomedical Informatics, 60: 243-251.
Sousa, A. P. d. and Almeida, A. M. 2016. Habits and Behaviors of e-health Users: A Study on the Influence of the Interface in the Perception of Trust and Credibility. Procedia Computer Science, 100: 602-610.