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1.
BMC Health Serv Res ; 18(1): 414, 2018 06 05.
Artigo em Inglês | MEDLINE | ID: mdl-29871675

RESUMO

BACKGROUND: Participatory health approaches are increasingly drawing attention among the scientific community, and could be used for health promotion programmes on diabetes through social media. The main aim of this project is to research how to best use social media to promote healthy lifestyles with and within the Norwegian population. METHODS: The design of the health promotion intervention (HPI) will be participatory, and will involve both a panel of healthcare experts and social media users following the Norwegian Diabetes Association. The panel of experts will agree on the contents by following the Delphi method, and social media users will participate in the definition of the HPI by expressing their opinions through an adhoc online questionnaire. The agreed contents between both parties to be used in the HPI will be posted on three social media channels (Facebook, Twitter and Instagram) along 24 months. The 3 months before starting the HPI, and the 3 months after the HPI will be used as control data. The effect of the HPI will be assessed by comparing formats, frequency, and reactions to the published HPI messages, as well as comparing potential changes in five support-intended communication behaviours expressed on social media, and variations in sentiment analysis before vs during and after the HPI. The HPI's effect on social media users' health-related lifestyles, online health behaviours, and satisfaction with the intervention will be assessed every 6 months through online questionnaires. A separate questionnaire will be used to assess the panel of experts' satisfaction and perceptions of the benefits for health professionals of a HPI as this one. DISCUSSION: The time constraints of today's medical practice combined with the piling demand of chronic conditions such as diabetes make any additional request of extra time used by health care professionals a challenge. Social media channels provide efficient, ubiquitous and user-friendly platforms that can encourage participation, engagement and action necessary from both those who receive and provide care to make health promotion interventions successful.


Assuntos
Diabetes Mellitus , Promoção da Saúde/métodos , Mídias Sociais/estatística & dados numéricos , Rede Social , Adulto , Diabetes Mellitus/prevenção & controle , Diabetes Mellitus/terapia , Comportamentos Relacionados com a Saúde , Inquéritos Epidemiológicos , Humanos , Comportamento de Busca de Informação , Estilo de Vida , Noruega , Saúde Pública
2.
Methods Inf Med ; 52(2): 160-7, 2013.
Artigo em Inglês | MEDLINE | ID: mdl-23392282

RESUMO

BACKGROUND: Detecting community structures in complex networks is a problem interesting to several domains. In healthcare, discovering communities may enhance the quality of web offerings for people with chronic diseases. Understanding the social dynamics and community attachments is key to predicting and influencing interaction and information flow to the right patients. OBJECTIVES: The goal of the study is to empirically assess the extent to which we can infer meaningful community structures from implicit networks of peer interaction in online healthcare forums. METHODS: We used datasets from five online diabetes forums to design networks based on peer-interactions. A quality function based on user interaction similarity was used to assess the quality of the discovered communities to complement existing homophily measures. RESULTS: Results show that we can infer meaningful communities by observing forum interactions. Closely similar users tended to co-appear in the top communities, suggesting the discovered communities are intuitive. The number of years since diagnosis was a significant factor for cohesiveness in some diabetes communities. CONCLUSION: Network analysis is a tool that can be useful in studying implicit networks that form in healthcare forums. Current analysis informs further work on predicting and influencing interaction, information flow and user interests that could be useful for personalizing medical social media.


Assuntos
Pesquisa Empírica , Internet , Apoio Social , Algoritmos , Diabetes Mellitus , Humanos , Grupo Associado , Estados Unidos
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