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Predicting Prediabetes Through Facebook Postings: Protocol for a Mixed-Methods Study

机译:通过Facebook帖子预测糖尿病前期:混合方法研究的协议

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Background The field of infodemiology uses health care trends found in public networks, such as social media, to track and quantify the spread of disease. Type 2 diabetes is on the rise worldwide, and social media may be useful in identifying prediabetes through behavior exhibited through social media platforms such as Facebook and thus in designing and administering early interventions and containing further progression of the disease. Objective This pilot study is designed to investigate the social media behavior of individuals with prediabetes, before and after diagnosis. Pre- and postdiagnosis Facebook content (posts) of such individuals will be used to create a taxonomy of prediabetes indicators and to identify themes and factors associated with an actual diagnosis of prediabetes. Methods This is a single-center exploratory retrospective study that examines 20 adults with prediabetes. The investigators will code Facebook posts 3 months before through 3 months after prediabetes diagnosis. Data will be analyzed using both qualitative content analysis methodology as well as quantitative methodology to characterize participants and compare their posts pre- and postdiagnosis. Results The project was funded for 2015-2018, and enrollment will be completed by the end of 2018. Data coding is currently under way and the first results are expected to be submitted for publication in 2019. Results will include both quantitative and qualitative data about participants and the similarities and differences between coded social media posts. Conclusions This pilot study is the first step in creating a taxonomy of social media indicators for prediabetes. Such a taxonomy would provide a tool for researchers and health care professionals to use social media postings for identifying those at greater risk of having prediabetes.
机译:背景技术信息流行病学领域使用在公共网络(例如社交媒体)中发现的医疗保健趋势来跟踪和量化疾病的传播。 2型糖尿病在全球范围内呈上升趋势,社交媒体可用于通过社交媒体平台(如Facebook)表现出的行为来识别糖尿病,从而设计和管理早期干预措施并控制疾病的进一步发展。目的这项初步研究旨在调查糖尿病前个体在诊断前后的社交媒体行为。诊断前和诊断后此类人的Facebook内容(帖子)将用于创建糖尿病前指标的分类法,并确定与糖尿病前期实际诊断相关的主题和因素。方法这是一项单中心探索性回顾性研究,研究了20位患有糖尿病前期的成年人。研究人员将在糖尿病前诊断的3个月到3个月之前为Facebook帖子编码。将使用定性内容分析方法和定量方法对数据进行分析,以表征参与者并比较他们的诊断前后。结果该项目的资金来源为2015-2018年,注册将于2018年底完成。目前正在进行数据编码,并且预期将在2019年提交第一批结果。结果将包括有关以下方面的定量和定性数据:参与者以及编码后的社交媒体帖子之间的异同。结论这项初步研究是建立糖尿病前期社交媒体指标分类标准的第一步。这样的分类法将为研究人员和卫生保健专业人员提供工具,使他们可以使用社交媒体发布信息来识别罹患前驱糖尿病风险更大的人。

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