Variations in Facebook Posting Patterns Across Validated Patient Health Conditions: A Prospective Cohort Study.
Variations in Facebook Posting Patterns Across Validated Patient Health Conditions: A Prospective Cohort Study.
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Facebook的变化在经过验证的患者健康状况中发布模式：一项前瞻性队列研究。
DOI：
10.2196/jmir.6486
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发表时间：
2017-01-06
影响因子：
7.4
通讯作者：
Merchant RM
中科院分区：
文献类型：
--
作者：
Smith RJ;Crutchley P;Schwartz HA;Ungar L;Shofer F;Padrez KA;Merchant RM
社交媒体正在成为一个研究健康的有洞察力的平台。为了制定涉及社交媒体的有针对性的健康干预措施，我们试图确定在Facebook上发布帖子的频率的患者人口统计和疾病预测因素。其目的是探索在医疗保健环境中一群社交媒体用户中与社交媒体使用频率相关的语言话题，评估不同疾病诊断的个人在社交媒体发帖数量上的差异，并确定患者是否能够准确预测自己的社交媒体参与度。2014年3月至10月，在单一的学术、城市、三级医疗急诊室寻求治疗的患者被问及是否愿意分享他们Facebook账户和电子医疗记录(EMR)的数据。对于每个参与者，提取了Facebook帖子的总内容。使用潜在Dirichlet分配自然语言处理技术，将Facebook语言主题与Facebook使用频率相关联。然后，将注册前6个月的Facebook帖子的平均数量与样本中经过验证的健康结果进行比较。共有695名患者同意提供对他们的EMR和社交媒体数据的访问。在帖子占比最高的参与者中，显著相关的语言话题包含健康术语，如“咳嗽”、“头痛”和“失眠”。在调整人口统计学因素后，有抑郁史的个体的职位(平均值38，95%可信区间28-50)显著高于无抑郁史的个体(平均值22，95%可信区间19-26，P=.001)。除抑郁外，样本中常见的健康结果(高血压、糖尿病、哮喘)在有或没有每种疾病的个体之间没有显著差异。我们样本中的高频帖子更有可能发布关于健康的帖子，并被诊断为抑郁症。抑郁症和社交媒体使用之间的因果关系需要进一步评估。我们的发现表明，抑郁症患者可能是社交媒体上健康相关干预的合适目标。
Social media is emerging as an insightful platform for studying health. To develop targeted health interventions involving social media, we sought to identify the patient demographic and disease predictors of frequency of posting on Facebook. The aims were to explore the language topics correlated with frequency of social media use across a cohort of social media users within a health care setting, evaluate the differences in the quantity of social media postings across individuals with different disease diagnoses, and determine if patients could accurately predict their own levels of social media engagement. Patients seeking care at a single, academic, urban, tertiary care emergency department from March to October 2014 were queried on their willingness to share data from their Facebook accounts and electronic medical records (EMRs). For each participant, the total content of Facebook posts was extracted. Using the latent Dirichlet allocation natural language processing technique, Facebook language topics were correlated with frequency of Facebook use. The mean number of Facebook posts over 6 months prior to enrollment was then compared across validated health outcomes in the sample. A total of 695 patients consented to provide access to their EMR and social media data. Significantly correlated language topics among participants with the highest quartile of posts contained health terms, such as “cough,” “headaches,” and “insomnia.” When adjusted for demographics, individuals with a history of depression had significantly higher posts (mean 38, 95% CI 28-50) than individuals without a history of depression (mean 22, 95% CI 19-26, P=.001). Except for depression, across prevalent health outcomes in the sample (hypertension, diabetes, asthma), there were no significant posting differences between individuals with or without each condition. High-frequency posters in our sample were more likely to post about health and to have a diagnosis of depression. The direction of causality between depression and social media use requires further evaluation. Our findings suggest that patients with depression may be appropriate targets for health-related interventions on social media.