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School of Indigenous, Medical and Health Sciences, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, New South Wales, Australia
School of Computing and Information Technology, Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, New South Wales, Australia
Corresponding author at: School of Indigenous, Medical and Health Sciences, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, New South Wales, Australia.
School of Indigenous, Medical and Health Sciences, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, New South Wales, AustraliaIllawarra Health and Medical Research Institute, Wollongong, New South Wales, Australia
People living with multiple sclerosis tend to be involved in app development.
•
Videos/photos, gamification and embedded sensors were incorporated in the apps.
•
Behavior change theories were applied in the apps for fatigue management and physical activity.
•
Limited applied elements of dialogue and social support implied a lack of device-mediated interaction and engagement in the apps.
Abstract
Background
Multiple Sclerosis (MS) is a chronic neurodegenerative disorder. People living with MS (plwMS) require long-term, multidisciplinary care in both clinical and community settings. MS-specific mHealth interventions have advanced in the form of clinical treatments, rehabilitation, disease monitoring and self-management of disease. However, mHealth interventions for plwMS appear to have limited proof of clinical efficacy. As native mobile apps target specific mobile operating systems, they tend to have better interactive designs leveraging platform-specific guidelines. Thus, to improve such efficacy, it is pivotal to explore the design characteristics of native mobile apps used for plwMS.
Objectives
This study aimed to explore the design characteristics of native mobile apps used for adults living with MS in academic settings.
Methods
A scoping review of studies was conducted. A literature search was performed through PubMed, CINAHL, MEDLINE and Cochrane Library. Per native mobile apps, characteristics, persuasive technology elements and evaluations were summarized.
Results
A total of 14 native mobile apps were identified and 43% of the identified apps were used for data collection (n=6). Approximately 70% of the included apps involved users (plwMS) whilst developing (n=10). A total of three apps utilized embedded sensors. Videos or photos were used for physical activity interventions (n=2) and gamification principles were applied for cognitive and/or motor rehabilitation interventions (n=3). Behavior change theories were integrated into the design of the apps for fatigue management and physical activity. Regarding persuasive technology, the design principles of primary support were applied across all identified apps. The elements of dialogue support and social support were the least applied. The methods for evaluating the identified apps were varied.
Conclusion
The findings suggest that the identified apps were in the early stages of development and had a user-centered design. By applying the persuasive systems design model, interaction design qualities and features of the identified mobile apps in academic settings were systematically evaluated at a deeper level. Identifying the digital functionality and interface design of mobile apps for plwMS will help researchers to better understand interactive design and how to incorporate these concepts in mHealth interventions for improvement of clinical efficacy.
). Symptoms (e.g., fatigue, cognitive impairment and pain) are major contributors to health related quality of life amongst people living with MS (plwMS) (
). For example, the use of disease-modifying treatments aims at reducing the risk of relapses and halting disability progression, along with symptomatic treatments and rehabilitation in community settings (
), mHealth offers an obvious opportunity for increasing the reach of disease management and healthcare delivery. With the advances in digital technology, these devices integrate sensors that can obtain signal related to different aspects of medical purposes in different environments. mHealth has the potential for bridging time and distance barriers to health and healthcare delivery that is traditionally delivered face-to-face (
Patient-centered applications: use of information technology to promote disease management and wellness. A white paper by the AMIA knowledge in motion working group.
MS specific mHealth interventions have advanced in the form of clinical treatments, rehabilitation, disease monitoring and self-management of disease. A 2018 analysis in the North America revealed that 2,556 (46.2%) of 5,408 participants with MS reported using mobile apps (
). However, mHealth interventions for plwMS appear to have limited proof of clinical efficacy. In a controlled environment (e.g., testing a mobile app), good adherence and usability were established in plwMS (
Adherence and satisfaction of smartphone- and smartwatch-based remote active testing and passive monitoring in people with multiple sclerosis: nonrandomized interventional feasibility study.
Interaction design of mobile apps plays a critical role in clinical efficacy. Adherence to digital interventions suggests relying heavily on interactive design of digital tools (
). Commercial apps tend to be developed by specialized companies in digital technology. Mobile device-mediate engagement is a key focus of commercial apps (
). However, there are limitation and potential risk to use commercial apps in clinical settings. The evidence reveals that commercial apps tend to have no basis in evidence and lack documentation regarding data privacy and confidentiality (
). The definitions and examples for design principles of the PSD model are shown in Table 1. By applying this model, the interaction design qualities and features of mobile apps can be systematically evaluated, further exploring their possible influence on device-mediated communication at the interface level.
Table 1Definitions and examples of design principles proposed in persuasive systems design model*.
Persuasive systems design
Definition
Example
Primary task support: Carrying out of user's primary task
Reduction
System should reduce effort that users expend with regard to performing their target behavior
A mHealth intervention for fatigue management includes a diary for recording energy levels in the morning and afternoon to divide the task of fatigue management into simple steps
Tunnelling
System should guide users in the attitude change process by providing means for action that brings them closer to the target behavior
A mHealth intervention for the prevention of cigarette smoking that delivers the content in sequential lessons that can only be accessed when the previous lesson is completed
Tailoring
System should provide tailored information for its user groups
A mHealth intervention for offering different information content for different user groups, e.g., information for beginners
Personalized
System should offer personalized content and services for its users
A mHealth intervention for providing information content based on individual's needs.
Self-monitoring
System should provide means for users to track their performance or status
A mHealth intervention for improving physical activity to provide a diary to track and view daily step count
Simulation
System should provide means for observing the link between the cause and effect with regard to users’ behavior
A mHealth intervention for weight loss includes before-and-after pictures of people
Rehearsal
System should provide means for rehearsing a target behavior
A mHealth intervention for psychotherapy starts each session with the same important exercise
Dialogue support: Providing feedback and implementing app-human dialogue support in a manner that helps users keep moving towards their goal or target behavior
Praise
System should use praise via words, images, symbols, or sounds as a way to provide user feedback information based on his/her behavior
A mHealth intervention for healthy eating compliments users by sending automated text- messages for reaching individual goals
Rewards
System should provide virtual rewards for users in order to give credit for performing the target behavior
A mHealth intervention for improving physical activity gives users a virtual trophy if they follow their program
Reminders
System should remind users of their target behavior during use of the system
A mHealth intervention for weight management sends notifications to its users as daily reminders
Suggestion
System should suggest that users carry out behaviors during the system use process
A mHealth intervention for healthier eating habits suggests that users eats fruit instead of candy at snack time.
Similarity
System should imitate its users in some specific way
A mHealth intervention for increasing intake of vegetables provides food advice based on food preference
Liking
System should have a look and feel that appeals to its users
A mHealth intervention for encouraging intake of fruit using pictures of fruit
Social role
System should adopt a social role
A mHealth intervention to support motor rehabilitation incorporates a virtual specialist to guide users through the exercise
System credibility support: more credible and thus more persuasive
Trustworthiness
System should provide information that is truthful, fair and unbiased
A mHealth intervention for healthy eating provides information related to benefit of eating fruit and vegetables rather than simply providing biased advertising or marketing information on superfoods
Expertise
System should provide information showing knowledge, experience, and competence
A mHealth intervention for monitoring symptoms in people with multiple sclerosis is developed by neurologists and healthcare professionals
Surface credibility
System should have competent look and feel
A mHealth intervention for motor rehabilitation contains a limited and well-justified number of sessions
Real-world feel
System should provide information of the organization and/or actual people behind its content and services
A mHealth intervention for medical data collection in people with multiple sclerosis provides possibilities to contact healthcare professionals through sending feedback or asking questions
Authority
System should refer to people in the role of authority
A mHealth intervention quotes an authority, such as a statement by government health office
Third-party endorsements
System should provide endorsements from respected sources
A mHealth intervention for healthy eating shows a certificate logo from the national professional organization of dietetics practice
Verifiability
System should provide means to verify the accuracy of site content via outside sources
A mHealth intervention for psychotherapy is supported by offering links to evidence of the exercises
Social support: motivates users by leveraging social influence
Social learning
System should provide means to observe other users who are performing their target behavior and to see the outcomes of their behaviors
An mHealth intervention for weight management provides the option to share the self-monitoring journal of physical activity on the discussion board
Social comparison
System should provide means for comparing performance with the performance of other users
A mHealth intervention for improving physical activity, users can share and compare information related to their daily step count via instant messaging application
Normative influence
System should provide means for gathering together users who have the same goal and make them feel norms
An mHealth intervention for improving intake of vegetables provides feedback on intake by comparing it to the top three users who achieved the goals
Social facilitation
System should provide means for discerning other users who are performing the behavior
An mHealth intervention for improving physical activity can recommend how many users are tracking their step count at the same time as them
Cooperation
System should provide means for co-operation
An mHealth intervention for motor rehabilitation forms user groups to achieve a group goal each week
Competition
System should provide means for competing with other users
A mHealth intervention for medication tracking includes a leader board in which users who enter intake of medications at the right times in a month period receive the highest place
Recognition
System should provide public recognition for users who perform their target behavior
A mHealth intervention for monitoring symptoms in multiple sclerosis shares personal stories of users who have succeeded in their goal behavior are published on the application
* Adapted from Oinas-Kukkonen, H. and M. Harjumaa, Persuasive systems design: Key issues, process model, and system features. Communications of the association for Information Systems, 2009. 24(1): p. 28Identifying relevant studies.
). However, the literature does not distinguish between web-based and native mobile apps. There are a number of strategies to develop an app using mobile devices, such as native mobile apps and web-based mobile apps (e.g., mobile web apps, web-based hybrid mobile apps and progressive web apps) (
). As mobile operating systems are dominated by iOS and Android, native mobile apps appear to target these two platforms. Native mobile apps are downloaded directly to the user's device and stored locally from app stores. Platform-specific programming languages, tools and guidelines are used to develop native mobile apps. For example, to develop a native mobile app for iOS operating system, developers are required to follow the Development Guidelines, Design Guidelines and Brand and Marketing Guidelines (
). Therefore, the present study focused on native mobile apps developed for iOS and/or Android operating systems. The aim of the study was to explore the current state of literature surrounding native mobile apps developed for adults living with MS in academic settings.
2. Methods
A scoping review is conducted to determine the scope of the research or to map the available literature on a phenomenon (
). To better understand the scope and coverage of evidence on the design characteristics of native mobile apps for plwMS in academic settings, a scoping review was conducted based on the framework proposed by Arksey and O'Malley (
). The review followed five steps, including identifying the research question, identifying relevant studies stage, study selection, charting the data and collating, summarizing and reporting the results (
). Identifying relevant studies, study selection and charting the data were conducted independently by two authors (ZH and VG.), with any disagreements resolved via consensus. Where consensus could not be reached, a third author was consulted (KTW).
2.1 Identifying the research question
Based on the framework, a scoping review employs both broad and more focused questions to provide a direction for the initial identification and eventual selection of relevant studies (
). The broad directive in this review was to explore the features of mobile apps developed for plwMS (aged 18 years) in academic settings.
The specific research questions that guided this review were as follows:
•
What are the key characteristics of mobile apps developed for adults living with MS in academic settings?
•
Are there any differences in characteristics between the purposes of mobile apps aimed at MS in terms of technology and interaction?
•
How are the mobile apps evaluated?
A literature search was performed through the databases PubMed, MEDLINE (EBSCO), Cumulative Index to Nursing and Allied Health Literature (EBSCO) and Cochrane Library. Both MEDLINE and PubMed were searched to ensure that recent studies were involved (
). The search covered the period from 1st April 2012 to 31st March 2022. The articles within the past 10 years were included in the present review, as mHealth described in articles before 10 years ago suggests to be less comparable with technologies described in newer articles (
). The search strategy was based on two concepts, which were combined with ‘AND’: mobile apps and MS. Where possible Medical Subject Headings in addition to free-text search terms were used in the search (
). An example of the search strategy of PubMed is available in Table 2. Articles were initially processed using Endnote 20 (2022, Endnote 20.3 for macOS) including removal of duplicates and screening, before being transferred into Microsoft Excel (2022, Microsoft Excel version 16.62 for macOS) for full-text review.
Table 2PubMed search strategy.
Concept category (combined with AND)
Search terms
Mobile Applications
“Mobile Applications" [MeSH Terms] OR "smartphone" [MeSH Terms] OR "telemedicine" [MeSH Terms] OR "mobile*" [Title/Abstract] OR "app" [Title/Abstract] OR "smartphone*" [Title/Abstract] OR "mhealth" [Title/Abstract] OR "telemedicine" [Title/Abstract])
Multiple sclerosis
"Multiple Sclerosis" [MeSH Terms] OR "myelitis, transverse" [MeSH Terms] OR "Optic Neuritis" [MeSH Terms] OR "clinically isolated syndrome" [Title/Abstract] OR "disseminated sclerosis" [Title/Abstract] OR "Multiple Sclerosis" [Title/Abstract] OR "Optic Neuritis" [Title/Abstract] OR "transverse myelitis" [Title/Abstract]
The design of apps can be determined in terms of technology and interaction.
•
Adults ( 18 years) diagnosed with any form of MS.
•
Intended for use by plwMS, not health care professionals.
•
Included evaluation(s) (e.g., user-based, expert-based, or using predictive model).
•
The study was published in a peer-reviewed academic journal or report from a scientific conference.
•
Full texts and apps published in English.
2.2 Study selection
Articles were screened based on the title and abstract. Any articles with titles or abstracts that did not fit the eligibility criteria were excluded. In the case that an abstract was not available or did not provide sufficient information to draw a conclusion regarding eligibility, the full-text articles were retrieved for further review. Following screening, full-text articles were reviewed against the eligibility criteria. When multiple articles describe the same mobile app, only the latest relevant full article which described the design of the app was included. The reference lists of all systematic reviews that were identified in the original search were checked to identify additional articles that met the inclusion criteria.
2.3 Charting the data
The following information was extracted from each included article by using Microsoft Excel (2022, Microsoft Excel version 16.62 for macOS): citation, country, name of the mobile app, purpose of the app, operating system(s), method of development, persuasive technology elements and evaluation (including sample characteristics, duration, used mobile device, setting, method and measured outcomes). The applied elements of persuasive technology within the apps were coded according to the PSD framework of Oinas-Kukkonen and Harjumaa (
. Applying this tool, the abstract and title, introduction and aims, method and data, sampling, data analysis, ethics and bias, results, transferability, and implications and usefulness were evaluated by allocating a score between 1 and 4 described in
). First, a descriptive summary was used to create a numerical overview of the characteristics of mobile apps developed for plwMS in academic settings. Differences in characteristics between apps were explored in terms of technology (e.g., using sensors), interaction (e.g., behavior change theory/techniques, design principles of the PSD model (
Second, thematic analysis was applied to obtain more insight into the various components’ specific designs based on the purposes of mobile apps. When patterns were observed linking technology and interaction, these components were then identified as key components. Thematic analysis was used to create the data-charting form.
3. Results
The search yielded an initial 15,816 articles after the removal of duplicates. A total of 15,710 articles were excluded by screening titles and abstracts, and 82 articles were assessed for eligibility. A total 14 articles were identified for the review. The process of study selection is shown in Fig. 1.
Evaluating the utility of smartphone-based sensor assessments in persons with multiple sclerosis in the real-world using an App (elevateMS): observational, prospective pilot digital health study.
Design, development, and testing of an app for dual-task assessment and training regarding cognitive-motor interference (CMI-APP) in people with multiple sclerosis: multicenter pilot study.
Design, development, and testing of an app for dual-task assessment and training regarding cognitive-motor interference (CMI-APP) in people with multiple sclerosis: multicenter pilot study.
Evaluating the utility of smartphone-based sensor assessments in persons with multiple sclerosis in the real-world using an App (elevateMS): observational, prospective pilot digital health study.
Design, development, and testing of an app for dual-task assessment and training regarding cognitive-motor interference (CMI-APP) in people with multiple sclerosis: multicenter pilot study.
). One included app was designed for fall risk assessment and not only followed a user-centered design but also considered the common MS symptoms including fatigue, vision and cognitive impairment whilst developing (
Evaluating the utility of smartphone-based sensor assessments in persons with multiple sclerosis in the real-world using an App (elevateMS): observational, prospective pilot digital health study.
Design, development, and testing of an app for dual-task assessment and training regarding cognitive-motor interference (CMI-APP) in people with multiple sclerosis: multicenter pilot study.
Evaluating the utility of smartphone-based sensor assessments in persons with multiple sclerosis in the real-world using an App (elevateMS): observational, prospective pilot digital health study.
Design, development, and testing of an app for dual-task assessment and training regarding cognitive-motor interference (CMI-APP) in people with multiple sclerosis: multicenter pilot study.
Evaluating the utility of smartphone-based sensor assessments in persons with multiple sclerosis in the real-world using an App (elevateMS): observational, prospective pilot digital health study.
Design, development, and testing of an app for dual-task assessment and training regarding cognitive-motor interference (CMI-APP) in people with multiple sclerosis: multicenter pilot study.
In the primary support, the design principles of reduction, tunnelling and tailoring were utilized across all apps, shown in Table 4. Approximately 70% of the apps applied the design principles of personalization and self-monitoring (n=10). For example, the fatigue management apps track sleep and energy level based on users’ needs (
Design, development, and testing of an app for dual-task assessment and training regarding cognitive-motor interference (CMI-APP) in people with multiple sclerosis: multicenter pilot study.
). For dialogue support, 93% of the apps applied the design principle of liking (n=13). A total of nine out of 14 apps integrated the design principle of suggestion (64%), and six for reminders (43%). As for credibility, the design principles of trustworthiness, expertise and surface credibility were applied across all apps. The design principles of social support were rarely used in the identified apps.
Table 4Design principles of persuasive system design by purposes of the mobile apps.
There were five of 14 studies applied a cross-sectional study design (36%) for evaluation, presented in Table 5. A total of six studies reported the durations of evaluations were greater than eight weeks (
Evaluating the utility of smartphone-based sensor assessments in persons with multiple sclerosis in the real-world using an App (elevateMS): observational, prospective pilot digital health study.
Design, development, and testing of an app for dual-task assessment and training regarding cognitive-motor interference (CMI-APP) in people with multiple sclerosis: multicenter pilot study.
). A total of nine of the identified apps were evaluated by using smartphones (64%). Tablets were used to evaluate the interventions of cognitive rehabilitation (
Design, development, and testing of an app for dual-task assessment and training regarding cognitive-motor interference (CMI-APP) in people with multiple sclerosis: multicenter pilot study.
Evaluating the utility of smartphone-based sensor assessments in persons with multiple sclerosis in the real-world using an App (elevateMS): observational, prospective pilot digital health study.
). There were eight out of 14 apps evaluated in natural settings (57%). In the controlled settings, a qualitative study tended to be applied to evaluate the apps (n=4) (
). Approximate 30% of the apps were evaluated by using MS related measurements such as disease stage, disease duration, Expanded Disability Status Scale and self-reported MS severity (n=4) (
Evaluating the utility of smartphone-based sensor assessments in persons with multiple sclerosis in the real-world using an App (elevateMS): observational, prospective pilot digital health study.
Design, development, and testing of an app for dual-task assessment and training regarding cognitive-motor interference (CMI-APP) in people with multiple sclerosis: multicenter pilot study.
Design, development, and testing of an app for dual-task assessment and training regarding cognitive-motor interference (CMI-APP) in people with multiple sclerosis: multicenter pilot study.
Evaluating the utility of smartphone-based sensor assessments in persons with multiple sclerosis in the real-world using an App (elevateMS): observational, prospective pilot digital health study.
3 groups: Self-referred participants who reported an MS diagnosis, clinic-referred participants with neurologist-confirmed MS, and participants without MS (controls)
495 had MS (n=359 self-referred, n=136 clinic-referred), and 134 controls.
Self-referred (45.20 ± 11.64), clinic-referred (48.93±11.20) and control (39.34 ± 11.41)
12 weeks
Smartphone
Natural
MS related measurements
Retention analysis Associations between self-reported MS severity and sensor-based active functional tests measurements, and the impact of local weather conditions on disease burden
MS patients 46.2 ± 10.1 Healthy controls 45.7 ± 10.7
Cross-sectional
Tablet
Controlled
Qualitative study MS related measurements
Test-retest reliability Associations to EDSS, disease stage, disease duration and patient-reported outcomes Associations to technician-administered neurological and neuropsychological testing
Design, development, and testing of an app for dual-task assessment and training regarding cognitive-motor interference (CMI-APP) in people with multiple sclerosis: multicenter pilot study.
This scoping review identified and explored the current native mobile apps in academic settings designed for plwMS. The majority of the included studies involved users (plwMS) whilst developing. The findings revealed that the digital functionality and interface design of the identified mobile apps were determined by the purpose of the apps. The finding demonstrated that there was an overall underutilization of dialogue support and social support within the identified mobile apps. The methods used for evaluating the mobile apps for plwMS were varied in academic settings.
The present exploratory results reveal that the design characteristics of the native mobile apps developed for plwMS were selected based on the purposes of the apps. The identified apps utilized smartphone embedded sensors which ensure precision in the collection of data (
Evaluating the utility of smartphone-based sensor assessments in persons with multiple sclerosis in the real-world using an App (elevateMS): observational, prospective pilot digital health study.
). Due to the symptoms of MS such as fatigue, pain and cognitive decline, using built-in sensors of devices allows real-time reporting of symptoms and minimizes the user burden. This can be a key tool in monitoring and mitigating symptoms of MS. The apps designed for fatigue management also had defining characteristics. Fatigue management apps for plwMS typically consisted of educational content as well as sleep and/or energy tracking tools (
). Thus, the goals of the identified apps appear to support self-management of fatigue. Furthermore, the identified apps designed for physical activity interventions utilize photo and video demonstrations (
). The apps for cognitive and motor rehabilitation were most likely to be gamified. Gamification is seen as the use of game design elements in non-game contexts to increase motivation to continue use (
From game design elements to gamefulness: defining "gamification".
in: Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments, Tampere, FinlandAssociation for Computing Machinery,
2011: 9-15
). They are either designed for plwMS to improve working memory or to assess their cognitive function and how these affected other aspects of their lives (
Design, development, and testing of an app for dual-task assessment and training regarding cognitive-motor interference (CMI-APP) in people with multiple sclerosis: multicenter pilot study.
). Cognitive rehabilitation is a key as cognitive impairment affects approximately 65% of plwMS and can have an impact on all areas of a person's life (
). Moreover, using sensors in this type of intervention can be an advancement in the realm of digital health interventions as they can automatically and continuously record high-density data from users (
Regarding the design features of persuasive technology, the findings suggest that the selected design principles tend to be determined by the purpose of the identified mobile apps. The goals of using mHealth in health and healthcare delivery appear to automate and advance current evidence-based practice leveraging the fast development and maturation of digital tools (
). The increasing popularity of smartphones offers new opportunities to implement innovative, scalable tools to improve the reach and effectiveness of health and healthcare delivery (
). Thus, primary task support is the most utilized across the apps to act as a supportive tool. Another important element of primary task support is rehearsal (
). However, the literature suggests that the utilization of rehearsal appears to be reported as lower than reality as authors may see rehearsal as an obvious element of the intervention and fail to report on it (
). Dialogue support was employed less across all the apps. The present finding reported that liking was the most employed design principle in dialogue support. This indicated that the apps overall were well laid out, but a lack of device-mediated interaction and engagement. Furthermore, over 55% of the included apps did not utilize reminders. Studies have shown the importance of reminders as effective tools in encouraging behavior change in health interventions (
Using the internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy.
). This may be due to the nature of apps, with many being data collection tools. Dialogue support elements such as praise and rewards are seldom used, which may be a weakness as recent literature surrounding the gamification of apps show praise and rewards are expected to have positive effects on the outcomes of health interventions (
Revealing the theoretical basis of gamification: a systematic review and analysis of theory in research on gamification, serious games and game-based learning.
). As for credibility, almost all the apps employed the features of trustworthiness, expertise, and surface credibility. This reinforces the nature of mobile apps in academic settings. Social support was the least utilized category of the PSD model. Social support plays an important role in behavior change, which has been explored in available literature (
). This may be due to the nature of the apps to provide support for interventions of self-management. As mobile health apps are to support consumer's self-management behavior and to assist patient engagement, providing relevant design features from the PSD will mimic or assist the communication of patient provider communication (
While the primary task support and the credibility support were the most frequently noted features of mobile app for plwMS in this study, more features from dialogue support and social support could be included by applying the design principles of the PSD model. However, the functionalities do not by any means cover all of the design principle of the PSD model (
). For example, a recent qualitative study on app requirements suggests that an app for promoting the physical activity guidelines for plwMS should be user-friendly and track personal goals, as well as incorporate motivational, functional, and personalization strategies in its design (
). By applying the design principles related to rewards of dialogue support, an app can include features that encourage human-app interaction to help users keep moving towards their goals, leveraging gamification principles. One of examples is to create a challenge for tracking physical activity on a personal basis, where users are awarded a virtual trophy if they successfully complete the challenge. This feature provides a more engaging and enjoyable way for users to gain experience in tracking physical activity. In addition to individual challenges, the app can also offer an option to establish team challenges with a shared goal. This feature applies the design principle of cooperation in social support, with the aim to work together to achieve a shared goal. Furthermore, design principles of the PSD model are applied to the interface design of digital tools with the aim of guiding the planned persuasive effects of the tools (
). Therefore, the nature, purpose, procedures, potential risks, and benefits of the study can be clearly communicated to participants, who are able to provide explicit and informed consent before any data is collected and analyzed.
The finding of the present study suggests that most identified apps designed for use by plwMS applied a user-centered design principle. This is especially important as the previous evidence suggests digital health tools not meeting the needs of users (
). The goal of applying a user-centered design approach is to create solutions specific to the intended users and ensure the tool is easy to use, easy to understand and acceptable (
). The target users and relevant stakeholders are involved in the different stages of product development. However, there is a gap in translating the specific needs for digital health tools in plwMS into technology features (
). Therefore, a supportive environment within apps may be required to guide users to gain positive experience.
The present results suggest that the methods used to evaluate the mobile apps in academic settings are varied. Evaluation and design of a mobile app tend to be closely integrated (
). For example, usability testing may be integrated in the varied stages of product development to establish how well an app functions and serves its intended purpose for a target population. The outcomes of evaluation tend to be integrated into the digital health tool via iterations. In the present study, approximately half of the identified apps focused on evaluating usability and one third of such studies used the System Usability Scale (
). In addition, MS-related outcomes were evaluated to establish preliminary evidence on clinical efficacy of the identified app. This is likely due to the early stages of development and nature of the academic setting, which is for research purposes.
However, there are several limitations for the present study. The most significant limitation of this scoping review was that the inclusion criteria necessitated that each included studies clearly described the details on the interface design of mobile apps. This decision was made to align with the scope of this review. Further, as there was no standard reporting system for digital technology tools, when assessing for the apps, we relied on the description and screenshots of the app to make the decision on digital functionality, applied behavior change theory/technique, and persuasive technology. Although an extensive scope search was conducted in scientific databases, some relevant literature in other domains might have been excluded. The results of this scoping review are only inclusive of studies written in English; therefore, findings may not be generalizable internationally. In addition, industry-developed apps were excluded in this analysis. These apps tend to undertake the path of designing and developing software as a medical device (
). Software as a medical device is a type of software that is capable of performing medical functions without requiring any specific medical device hardware (
). Software as a medical device must meet the standards of device regulatory agencies on design control, cybersecurity and data privacy, risk analysis, and clinical evaluation (
). Therefore, developing apps for use as medical devices requires maintaining a balance between clinical, technical, and regulatory processes to achieve the required level of rigor. Moreover, industry-developed apps tend to be owned by a company or individual. The design tends to be kept confidential and not publicly disclosed for gaining a competitive advantage in a specific market or industry. However, development for software as medical device appears to commence after establishing proof of concept of digital solutions in a research context (
). The outcome of proof of concept offers feedback for further improving the app in clinical effectiveness, technical capabilities and user experience (
). By embracing Industry 4.0 or digital technologies, government agencies have initiated and invested substantially in innovation and research commercialization. A growing number of universities have developed programs and resources to facilitate the flow of research from universities to industry (
). The outcome of the studies on apps in academic settings provides evidence to determine whether the digital solution has commercial viability for attracting funding and investors (
). It not only provides ongoing support for maintenance of these apps but also offer opportunities to further refine and improve the app for clinical effectiveness. Thus, conducting a scoping review on native mobile apps in academic setting may determine the scope on key characteristics of apps for plwMS.
5. Conclusion
This scoping review identified and explored the current mobile apps available for plwMS. The present findings suggest that the content and digital technologies of these apps were chosen differently based on the purposes of the apps. By applying design principles of the PSD model, the interaction design qualities and features of the identified mobile apps in academic settings were systematically evaluated at a deeper level. Despite the limitations, the majority of included studies were in the early stages of development and had a user-centered design, highlighting an upcoming realm of digital health technology. Further studies are needed in this field to expand on mobile digital tools available for plwMS.
Research involving human and animal participants
The present study was a review. Ethics approval is not required for reviews.
Role of funding source
The funder had no role in the design of the study; in the development, analyses or interpretation of data; in the writing of the manuscript or in the decision to publish the results.
Funding
VG was supported by Multiple Sclerosis Australia Postdoctoral Fellowship (Grant number 20-223).
CRediT authorship contribution statement
Zahli Howard: Formal analysis, Investigation, Data curation, Writing – original draft. Khin Than Win: Methodology, Writing – review & editing. Vivienne Guan: Conceptualization, Methodology, Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review & editing, Supervision.
Declaration of Competing Interest
The authors declare no conflict of interest.
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