Cognitive Accessibility in User Experience Assessment of Mobile Health: A Review

Cognitive Accessibility in User Experience Assessment of Mobile Health: A Review Laura MONTOYAa,1, Octavio RIVERA-ROMERO a, and Enrique DORRONZORO-ZUBIETEa a Departament of Electronic Technology, Universidad de Sevilla, Spain ORCiD ID: Laura Montoya https://orcid.org/0009-0004-8953-2448, Octavio RiveraRomero https://orcid.org/0000-0001-7212-9805, Enrique Dorronzoro-Zubiete https://orcid.org/0000-0001-8478-9851 Abstract. With an increasingly aging population, cognitive impairment (CI) prevalence is a major concern in healthcare. The international standard for health technologies specifies requirements to design cognitively accessible products aimed to support people with CI regardless of age. While User Experience (UX) design frameworks like the Honeycomb define accessibility as a dimension to be considered, little is known about how cognitive accessibility (CA) is being regarded in the UX assessment of mobile health (mHealth). We conducted a secondary analysis from a broader review on UX assessment of interactive mHealth technologies focusing on CA consideration in those targeted to people with, or at risk of CI. Nine papers were analyzed. Most common adaptations of the UX assessment procedure were to involve caregivers, conducting interviews in person and in naturalistic settings and time considerations. Only one study utilized an adapted validated version of mHealth technology questionnaire. Considerations of CA included means of motivation, simple design considerations and means of representation and understanding. While some guidelines of CA are being regarded, results of the assessments show a gap between what is important for patients and what was considered in the evaluation instruments. Developing mHealth specific UX questionnaires could help in understanding the needs of people with CI and guide the design of accessible technologies. Keywords. User Experience, Mobile Health, Cognitive impairments, Accessibility 1. Introduction Cognitive impairment (CI) is a major concern driven by the anticipated rise in prevalence of disease and disability associated with the global trend of population aging [1]. Mobile health technologies (mHealth) are increasingly generating interest for their ability to monitor, assists, and support self-management of individuals with CI or those at risk of declining cognitively over time. Memory loss, attention deficits as well as fatigue may, however, hinder the interaction and adherence to these technologies. Indeed, research revealed that cognitively older adults show different phone usage patterns such as use of fewer apps and longer times to complete tasks [2]. Assessing the 1 Corresponding Author: Laura Montoya, Department of Electronic Technology, ETSII, Universidad de Sevilla, Seville, Spain; E-mail: [email protected]. Intelligent Health Systems – From Technology to Data and Knowledge E. Andrikopoulou et al. (Eds.) © 2025 The Authors. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). doi:10.3233/SHTI250516 969 experience of people with CI in the interaction with mHealth solutions is therefore crucial to guide the design of accessible and user-friendly mHealth technologies. The International Organization for Standardization (ISO) posits cognitive accessibility (CA) as a requirement for the design of all interactive and assistive technologies [3]. CA refers to the ability of systems to be used by individuals with diverse cognitive needs and capabilities to achieve specific goals in various contexts [3]. Ensuring simplicity and understandability, offering strong support, fostering autonomy and ensuring safety is even more essential for mHealth designed for people with or at risk of cognitive decline. User experience (UX) assessment is key for understanding whether these requirements are being successfully implemented. While UX design frameworks such as the Honeycomb by Morville [4] posit accessibility as a key element to be considered in the design of mHealth solutions, little is known about how cognitive function is being regarded in UX in mHealth assessments. This paper aims to explore whether and how CA is being considered in UX assessments of interactive mHealth technologies targeted to people with, or at risk of CI. 2. Method A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines [5]. This was a secondary analysis, part of a broader review we previously conducted on UX evaluations of interactive mHealth technologies. PubMed, APA PsycInfo, IEEE Xplore, ACM Digital Library databases were searched using using keywords around three categories: Mobile Health, UX and Evaluation. We included papers in English language with available access to full text that explicitly conducted UX evaluations of interactive mHealth technologies targeted to adults with CI or at risk of suffering cognitive decline either because of a neurological condition or aging. Conditions not causing directly CI such as affective or sleep disorders were excluded. Articles were excluded if target users were health care professionals or formal caregivers and those whose UX evaluation was made by experts, stakeholders, or health professionals. For each included study, we collected data on target population, type and purpose of the assessed mHealth solution, UX evaluation methods and tools, adaptations of the UX evaluation methods to cognitive skills of the target population, and cognitive accessibility aspects considered in the UX evaluation and reported in the results. We used the ISO-21801-1:2020 [3] to identify the aspects of CA: “Flexibility of Use” (FU), “Means of Expressions” (ME), “Means of Motivation” (MM), “Means of Representation and Understandings” (MRU), “Organization, Planning and Time Management” (OPTM), “Support needed for Completion of Tasks/Assistance with Errors” (SCTAE), “Simple, Understandable and Logical Design” (SULD), Focus, Attention and Feedback’’ (FAF), “Spatial Orientation and Understanding of Values and Sizes’’ (SOUVS). 3. Results Nine papers were identified to meet the inclusion criteria and selected for analysis [614]. Eight works addressed older or elderly adults (range of ages from 60-90) [6-9, 11L. Montoya et al. / Cognitive Accessibility in User Experience Assessment of Mobile Health970 14] and one for adults (from around 36 to 60) with a risk of CI [10]. The mHealth technologies comprised apps (6/9) [6,8,10,12-14] and integrated systems (e.g., wearables and app) (3/9) [7,9,11] and they targeted sedentarism [12], general care [8], frailty [14], adherence to treatment [6,10], dementia [9], cognitive decline detection [13] and fall prevention [7,11]. Three different methods were used to evaluate UX in these studies, surveys using questionnaires (7/9) [6-8,10,11,13,14], interviews (4/9) [7, 8,11,12] and focus groups (1/9) [9]. The most used questionnaire was the UEQ (3/9) [6,8,10], followed by purpose-built questionnaire (2/9) [6,14], and the SUS (2/9) [7, 11]. Only one paper used a validated adapted version of a questionnaire for their population, namely, the SUS-S [13]. Attempts to adapt the UX assessment of people at risk of being cognitively impaired are summarized in Table 1. The most used adaptations were flexibility in the time to use the device and involving family members or caregivers (5/9). Table 2 shows the aspects considered in the selected studies. The most considered aspect was “Means of Motivation” (9/9) followed by SULD considered in 5 studies. Table 1. Adaptations of the UX assessment methods used in the included studies. Ref. Adaptation of UX assessment method [6] Time management; Involvement of families [7] Time management [8] Guided app interaction with a researcher; Caregivers invited for social support [9] Assess cognitive reserve and technical proficiency; Assistance of caregivers [10] Promotion of autonomy; Real-life setting [11] Time management [12] Length and format; Flexibility; Time management [13] Time management; Adapted questionnaire for elders [14] Assess digital skills; Allow caregivers to be present; Comparison with paper format Table 2. Cognitive accessibility aspects considered in the selected studies. Aspects considered in the evaluation are represented by points while those that raised in the reported results are represented by crosses. Ref. FU ME MM MRU OPTM SCTAE SULD FAF SOUVS [6] Evaluation ● ● Results X X [7] Evaluation ● Results X X X [8] Evaluation ● ● ● Results X X X X X [9] Evaluation ● ● ● Results X X [10] Evaluation ● ● ● Results X [11] Evaluation ● Results X [12] Evaluation ● ● Results X X X [13] Evaluation ● ● ● Results X X X X X [14] Evaluation ● ● ● ● Results X L. Montoya et al. / Cognitive Accessibility in User Experience Assessment of Mobile Health 971 4. Discussion and Conclusions This paper aimed to explore how CA is being regarded in the assessments of the experience with mHealth technologies of people with, or at risk of CI. Nine papers were reviewed to look for factors of CA considered in the process and assessment of user experience. Most of the papers targeted people at risk of cognitive decline and only two papers were specific for people with CI. For the assessment procedures, the adaptations observed mainly entailed involving caregivers for patient’s support, choosing naturalistic environments, time considerations and providing alternative conventional methods. Common considerations of CA included means of motivation, simple design considerations and means of representation and understanding. A finding worth mentioning was the lack of use of health specific questionnaires, despite all studies involved patients at risk of cognitive decline. Only Young et al., 2024 utilized an adapted questionnaire for elders [13]. While some dimensions related to CA were considered, aspects that proved to be important to users were not. For instance, need of assistance and enhanced feedback after errors were common complains. These findings could be explained by post error slowing related to aging [15]. Furthermore, interestingly, for more complex mHealth systems involving more than one device, users tended to delegate part of the system to caregivers, aligning with insights on cognitively impaired people preference for using less apps [2]. Understanding cognitive abilities of users is thus crucial for achieving accessible designs. While all studies implemented at least one measure to enhance the accessibility of the UX assessment, only a study for patients with dementia [9] assessed the cognitive status of users. UX assessments revealed, however, issues related to lack of confidence with user’s own skills [13] or forgetfulness [6] as barriers for adhering to the use of mHealth in patients at risk of CI. Given the utility of these papers was to enhance adherence to treatment, it might have been beneficial to understand and consider the cognitive status of patients. Moreover, longitudinal assessment might be key to adapt to changing cognitive demands of users and guarantee the accessibility of technology over time. 5. Conclusions and Limitations This review of how CA is being regarded in UX assessments for people with or at risk of CI highlights the need for more considerations and attention to user’s state and needs. Understanding CI user experience could maximize the usefulness and usability of these technologies benefitting the acceptance and adherence of adults with CI. This study presents some limitations: Not all databases have been searched, so there may be relevant articles that have not been studied. Some authors may have considered some aspects of CA without explicitly reporting it in the paper. Acknowledgements Grant PID2021-125528OB-I00 funded by MICIU/AEI/10.13039/501100011033 and by “ERDF A way of making Europe” L. 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