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dc.contributor.advisorHartvigsen, Gunnar
dc.contributor.authorChomutare, Taridzo Fred
dc.date.accessioned2014-08-20T10:49:32Z
dc.date.available2014-08-20T10:49:32Z
dc.date.issued2014-05-14
dc.description.abstractType 2 diabetes is one of the greatest challenges that continues to grow because of the ageing population, increasing morbid obesity and sedentary lifestyles. Social media such as Facebook and YouTube have transformed the way people interact in general and on the Internet, but the role of social media in healthcare is still not well-understood. Current understanding of the association between user interaction patterns and health outcomes or behaviour change is still limited. In this dissertation I present a framework, based on social network analysis, to explore the nature of patient interactions in online communities. Results show that people with diabetes join online communities typically immediately following diagnosis, with over 80% of the patients having being diagnosed in under 2 years. The networks are very centralized with continually shrinking density and diameter as the the networks grow, and these results directly contrast with current evidence about non-healthcare social networks. Further, using machine learning techniques, I show that we can predict health outcomes such as weight loss performance based on how the patients interact online. The results have practical relevance for understanding the nature of patients interactions, as well as for designing personalized diabetes interventions based on emergent social technologies.en
dc.description.doctoraltypeph.d.en
dc.description.popularabstractType 2-diabetes er en av de største utfordringer på grunn av aldrende befolkning, økende overvekt og stillesittende livsstil. Sosiale medier som Facebook og YouTube har endret måten mennesker samhandler, men hvilken rolle sosiale medier i helsevesenet er fortsatt ikke godt forstått, spesielt sammenhengen mellom brukermedvirkning atferd og helse utfall eller atferdsendring. I denne avhandlingen presenterer jeg et rammeverk, basert på sosial nettverksanalyse, for å utforske naturen av pasient interaksjoner i online lokalsamfunn. Resultatene viser at personer med diabetes delta nettsamfunn vanligvis umiddelbart etter diagnose, med over 80% av de pasientene som har blitt diagnostisert på under to år. Nettverkene er svært sentralisert med stadig krympende tetthet og diameter som de nettverkene vokser. Videre, ved hjelp av maskinlæringsteknikker, viser jeg at vi kan forutsi helse ytelse som vekttap basert på hvordan pasientene samhandler på nettet.en
dc.description.sponsorshipThis work was supported in part by the Research Programme for Telemedicine (HST), Helse Nord RHF, grant number HST1022-11en
dc.descriptionThe papers of this thesis are not available in Munin: <br/>1. Chomutare T, Fernandez-Luque L, Årsand E, Hartvigsen G.: 'Features of mobile diabetes applications: Review of the literature and analysis of current applications against evidence-based guidelines', Journal of Medical Internet Research (2011), vol. 13(3);e65. Available at <a href=http://dx.doi.org/10.2196/jmir.1874>http://dx.doi.org/10.2196/jmir.1874</a> <br/>2. Chomutare T, Årsand E, Fernandez-Luque L, Lauritzen J, Hartvigsen G.: 'Inferring community structure in healthcare forums: An empirical study', Methods of Information in Medicine (2013, vol. 52(2). Available at <a href=http://dx.doi.org/10.3414/ME12-02-0003>http://dx.doi.org/10.3414/ME12-02-0003</a> <br/>3. Chomutare T, Årsand E, Hartvigsen G.: 'Characterizing Development Patterns of Healthcare Social Networks', Network Modeling Analysis in Health Informatics and Bioinformatics (2013), vol. 2(3):147-157. Available at <a href=http://dx.doi.org/10.1007/s13721-013-0033-y>http://dx.doi.org/10.1007/s13721-013-0033-y</a> <br/>4. Chomutare T, Årsand E, Hartvigsen G.: 'Temporal community structure patterns in diabetes social networks', International Conference ASONAM (2012), pp.745-75. Available at <a href=http://dx.doi.org/10.1109/ASONAM.2012.137>http://dx.doi.org/10.1109/ASONAM.2012.137</a> <br/>5. Chomutare T, Tatara N, Årsand E, Hartvigsen G.: 'Designing a diabetes mobile application with social network support', Studies in Health Technology and Informatics (2013), vol. 188:58-64. <br/>6. Chomutare T, Xu A, Iyengar MS.: 'Social Network Analysis to Delineate Interaction Behaviour that Predicts Weight Loss Performance' (manuscript) <br/>7. Chomutare T.: 'Collaborative Filtering with Community Structure Properties in Healthcare Social Networks' (manuscript)en
dc.identifier.isbn978-82-8236-133-0
dc.identifier.urihttps://hdl.handle.net/10037/6544
dc.identifier.urnURN:NBN:no-uit_munin_6142
dc.language.isoengen
dc.publisherUiT Norges arktiske universiteten
dc.publisherUiT The Arctic University of Norwayen
dc.rights.accessRightsopenAccess
dc.rights.holderCopyright 2014 The Author(s)
dc.subject.courseIDDOKTOR-004en
dc.subjectVDP::Mathematics and natural science: 400::Information and communication science: 420en
dc.titleComplex Network Structure Patterns in Open Internet Communities for People with Diabetesen
dc.typeDoctoral thesisen
dc.typeDoktorgradsavhandlingen


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