Table 1 Comprehensive review of key studies on healthcare website usability evaluation.
From: Machine learning approach for optimizing usability of healthcare websites
Study & authors | Year | Focus Area | Methodology | Key contributions | Findings & Impact |
|---|---|---|---|---|---|
Michaud et al.26 | 2003 | Implementation & evaluation of a health website for adolescents in Switzerland | Website development and assessment using two questionnaires | Evaluated the effectiveness of delivering health-related topics to adolescents | Demonstrated that structured website design and assessment can improve engagement and accessibility for young users |
Teo et al.9 | 2005 | Evaluation of a breast cancer website | Interactive web-based questionnaire for usability and content analysis | Provided an in-depth analysis of hospital website effectiveness | Identified key usability factors and best practices for hospital websites, emphasizing user experience |
Elizabeth Sillence et al.17 | 2007 | Trustworthiness of health websites, focusing on hypertension | Developed guidelines for assessing online medical advice reliability | Identified trust-building elements in web-based health information | Differentiated interpersonal and web-based trust, guiding the design of credible health websites |
Dohoon Kim et al.24 | 2007 | Key functional characteristics of health information websites | Technical analysis of design and functionality | Proposed improvements in health website design to enhance user satisfaction | Highlighted essential features for better navigation and engagement in medical websites |
Duan et al.39 | 2007 | Automated verification techniques for website maintenance | Algebraic reasoning & model checking to assess web navigation behavior | Proposed methods for maintaining evolving web applications | Enhanced website stability and functionality through automated verification |
Vangelis Alexiou et al.36 | 2008 | Development of a global medical web portal | Compilation of high-quality educational resources | Created a centralized platform for medical knowledge dissemination | Improved accessibility to clinical practice guidelines and educational content |
Maaike Van Den Haak et al.37 | 2010 | Usability evaluation of consumer health information websites | Observational and user-driven data collection | Addressed methodological constraints in usability studies | Emphasized the importance of user feedback in website evaluation and design |
Moreno et al.2 | 2010 | Quality evaluation of health-related websites | Qualitative, user-centric approach using fuzzy linguistic strategy | Developed a structured assessment methodology based on user perceptions | Enhanced website evaluation through linguistic quality judgments, ensuring better alignment with user needs |
Nicola Reavley et al.38 | 2011 | Quality assessment of mental health information websites | Content quality analysis | Examined the reliability and comprehensiveness of mental health information | Identified deficiencies in online mental health resources, guiding improvements |
Chadaga et al.40 | 2023 | COVID-19 Diagnosis | AI-based decision support system | Enhanced diagnostic accuracy using haematological markers | Improved healthcare outcomes through AI-driven diagnostics |
Nayak et al.41 | 2023 | Monkeypox Diagnosis | Deep learning models | Achieved over 91% accuracy in detecting monkeypox | Advanced diagnostics, supporting digital healthcare |
Susmita et al.42 | 2023 | Stroke Risk Prediction | Explainable AI (XAI) Model | Developed an XAI model with 96% accuracy for stroke prediction | Improved patient engagement and personalized care |
