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Bond, Carol S.; Ahmed, Osman H. (2016)
Publisher: BCS, The Chartered Institute for IT
Journal: Journal of Innovation in Health Informatics
Languages: English
Types: Article
Subjects: R858-859.7, Computer applications to medicine. Medical informatics, Participatory Healthcare, Information, eHealth, Diabetes, Self-Management, Internet
Background Peer-to-peer health care is increasing, especially amongst people living with a long-term condition. How information is shared is, however, sometimes of concern to health care professionals. Objective This study explored what information is being shared on health-related discussion boards and identified the approaches people used to signpost their peers to information. Methods This study was conducted using a qualitative content analysis methodology to explore information shared on discussion boards for people living with diabetes. Whilst there is debate about the best ethical lens to view research carried out on data posted on online discussion boards, the researchers chose to adopt the stance of treating this type of information as “personal health text”, a specific type of research data in its own right. Results Qualitative content analysis and basic descriptive statistics were used to analyse the selected posts. Two major themes were identified: ‘Information Sharing from Experience’ and ‘Signposting Other Sources of Information’. Conclusions People were actively engaging in information sharing in online discussion forums, mainly through direct signposting. The quality of the information shared was important, with reasons for recommendations being given. Much of the information sharing was based on experience, which also brought in information from external sources such as health care professionals and other acknowledged experts in the field. With the rise in peer-to-peer support networks, the nature of health knowledge and expertise needs to be redefined. People online are combining external information with their own personal experiences and sharing that for others to take and develop as they wish.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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