Stroke is a leading cause of death and disability worldwide [8], underscoring the need for effective digital solutions for stroke patients, caregivers, and healthcare professionals. Given that, this thesis aims to evaluate quality aspects of usability, accessibility, and readability of stroke-related mobile health (mHealth) applications, with the primary objective of identifying strengths and weaknesses to enhance user experience and app quality. This study assessed sixteen stroke-related apps through a comprehensive methodology, including accessibility testing with the Google Accessibility Scanner, Mobile Application Rating Scale (MARS) evaluation, heuristic evaluation, and readability assessment. Key findings indicate significant issues with touch target sizes and text contrast, which are crucial for users with impaired visionand motor skills. MARS evaluations revealed that “Constant Therapy” excelled in engagement and functionality due to its interactive features and personalized schedules. At the same time, “Stroke Recovery Predictor” and “Conversation Therapy Lite” scored lower due to limited functionality and unclear interfaces. The heuristic evaluation highlighted frequent violations of the visibility of system status and insufficient error messaging. Readability assessments showed a range of reading difficulty levels, with some apps lacking privacy policies that could be found either within the application or on the developer’s website. The study provides actionable recommendations for developers, such as improving touch target sizes, improving text contrast, increasing functional variety, optimizing navigation, and ensuring privacy policy transparency. Addressing these areas can significantly improve the usability and accessibility of stroke-related mHealth apps, ultimately supporting better health outcomes and quality of life for stroke survivors. Future research should involve more evaluators, use multiple assessment tools, and focus on specific types of stroke apps to refine the evaluation process and provide more targeted insights.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kau-100476 |
| Date | January 2024 |
| Creators | Svensson, Pontus |
| Publisher | Karlstads universitet, Institutionen för matematik och datavetenskap (from 2013) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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