Automated framework for comprehensive usability analysis of healthcare websites using web parsing
Abstract In the digital age, hospital websites are essential for providing healthcare information and services. This research introduces an automated tool, WUAHP, created in Python utilizing BeautifulSoup for HTML parsing. This facilitates the extraction of structural and content-based components es...
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-07271-4 |
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| author | Amandeep Kaur Jaswinder Singh Satinder Kaur |
| author_facet | Amandeep Kaur Jaswinder Singh Satinder Kaur |
| author_sort | Amandeep Kaur |
| collection | DOAJ |
| description | Abstract In the digital age, hospital websites are essential for providing healthcare information and services. This research introduces an automated tool, WUAHP, created in Python utilizing BeautifulSoup for HTML parsing. This facilitates the extraction of structural and content-based components essential for usability assessment. It assesses websites based on five principal criteria: Navigational efficiency, operational efficiency, accessibility, responsiveness & compatibility, and security—each subdivided into many sub-criteria. Each measure is evaluated on a scale from 0 (least desirable) to 1 (most ideal) utilizing normalized modules. The entropy weighting method is utilized to impartially allocate weights according to data variability. Usability scores are subsequently confirmed via user feedback and aligned with Nielsen’s heuristic usability standards. The tool was utilized on fifty healthcare websites. The results indicated significant variability, with HW9 attaining the greatest usability score of 97% and HW39 the lowest at 12%. The ultimate usability scores varied from 12 to 97%, underscoring disparities in design efficacy. WUAHP provides web developers and healthcare providers with an effective method to assess and enhance website usability. The technology establishes a basis for future applications in training machine learning models for automated, large-scale website assessment. |
| format | Article |
| id | doaj-art-e021fd2b768c43ce92bb7c049d6da901 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-e021fd2b768c43ce92bb7c049d6da9012025-08-20T04:01:35ZengNature PortfolioScientific Reports2045-23222025-07-0115112110.1038/s41598-025-07271-4Automated framework for comprehensive usability analysis of healthcare websites using web parsingAmandeep Kaur0Jaswinder Singh1Satinder Kaur2Department of Computer Science, Guru Nanak Dev UniversityDepartment of Computer Science, Guru Nanak Dev UniversityDepartment of Computer Engineering and Technology, Guru Nanak Dev UniversityAbstract In the digital age, hospital websites are essential for providing healthcare information and services. This research introduces an automated tool, WUAHP, created in Python utilizing BeautifulSoup for HTML parsing. This facilitates the extraction of structural and content-based components essential for usability assessment. It assesses websites based on five principal criteria: Navigational efficiency, operational efficiency, accessibility, responsiveness & compatibility, and security—each subdivided into many sub-criteria. Each measure is evaluated on a scale from 0 (least desirable) to 1 (most ideal) utilizing normalized modules. The entropy weighting method is utilized to impartially allocate weights according to data variability. Usability scores are subsequently confirmed via user feedback and aligned with Nielsen’s heuristic usability standards. The tool was utilized on fifty healthcare websites. The results indicated significant variability, with HW9 attaining the greatest usability score of 97% and HW39 the lowest at 12%. The ultimate usability scores varied from 12 to 97%, underscoring disparities in design efficacy. WUAHP provides web developers and healthcare providers with an effective method to assess and enhance website usability. The technology establishes a basis for future applications in training machine learning models for automated, large-scale website assessment.https://doi.org/10.1038/s41598-025-07271-4AestheticsWebsite evaluationUsabilityWeb engineeringBeautifulSoupHealthcare websites |
| spellingShingle | Amandeep Kaur Jaswinder Singh Satinder Kaur Automated framework for comprehensive usability analysis of healthcare websites using web parsing Scientific Reports Aesthetics Website evaluation Usability Web engineering BeautifulSoup Healthcare websites |
| title | Automated framework for comprehensive usability analysis of healthcare websites using web parsing |
| title_full | Automated framework for comprehensive usability analysis of healthcare websites using web parsing |
| title_fullStr | Automated framework for comprehensive usability analysis of healthcare websites using web parsing |
| title_full_unstemmed | Automated framework for comprehensive usability analysis of healthcare websites using web parsing |
| title_short | Automated framework for comprehensive usability analysis of healthcare websites using web parsing |
| title_sort | automated framework for comprehensive usability analysis of healthcare websites using web parsing |
| topic | Aesthetics Website evaluation Usability Web engineering BeautifulSoup Healthcare websites |
| url | https://doi.org/10.1038/s41598-025-07271-4 |
| work_keys_str_mv | AT amandeepkaur automatedframeworkforcomprehensiveusabilityanalysisofhealthcarewebsitesusingwebparsing AT jaswindersingh automatedframeworkforcomprehensiveusabilityanalysisofhealthcarewebsitesusingwebparsing AT satinderkaur automatedframeworkforcomprehensiveusabilityanalysisofhealthcarewebsitesusingwebparsing |