Semantic Web Technologies in the Provision of Personalised Patient Education

  • Susan Quinn

Student thesis: Doctoral Thesis

Abstract

Health information is a valuable resource for citizens which can assist them to navigate healthcare services, and make medical and lifestyle decisions. Increased Internet availability has facilitated convenient access to a wide range of health information resources. However, whilst health knowledge has become increasingly available, many individuals face obstacles when attempting to engage with the information obtained. Research challenges exist in finding strategies to formulate health education that will enhance its usability and efficacy for all citizens. This thesis considers the human factors associated with utilising health information, and the technological challenges associated with delivering health information. This investigation was fulfilled through the completion of four research studies. The research initially concentrated on the use of online health information. The first study investigated the online health information seeking behaviours of health consumers, and determined whether these behaviours could be associated with an individual’s health literacy and eHealth literacy skills. The focus then shifted to consider the characteristics of generic patient education and it was proposed that a novel personalisation strategy could enhance the usability and attractiveness of the education. The second study focused on the development of a web-based architecture that created personalised education for diabetic patients. Semantic web technologies, including an ontology and a rule-based personalisation component, were incorporated into the architecture. Subsequently the third study concentrated on the ontological knowledge base and sought to strengthen the validity of this knowledge model. A novel methodology for collaborative evaluation of the ontology was described and evaluated. The final study examined user engagement with different formats of patient education. The study compared the engagement behaviours of individuals that were using either a generic education booklet or electronically generated personalised patient education. The thesis proposes that appreciating the characteristics and aptitudes of citizens can assist with developing effective digital health information services.
Date of AwardApr 2018
LanguageEnglish
Awarding Institution
SupervisorChristopher Nugent (Supervisor) & Raymond Bond (Supervisor)

Keywords

  • Semantic Web Technologies
  • Ontology
  • Online Health Information Seeking Behaviour
  • Engagement

Cite this

Semantic Web Technologies in the Provision of Personalised Patient Education
Quinn, S. (Author). Apr 2018

Student thesis: Doctoral Thesis