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Different platforms for different patients' needs: Automatic content analysis of different online health information platforms

机译:不同患者需求的不同平台:不同在线健康信息平台的自动内容分析

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摘要

Prior online health research has mainly focused on the predictors or outcomes of online health information, leaving online health information itself understudied. Therefore, online health information has remained an umbrella term encompassing different platforms (expert- vs. peer-generated). A hybrid method that combines qualitative and computational methods is used to identify different topics discussed on these different platforms, and an initial model of patients' social support needs was developed and applied to data obtained from the hybrid method. Using topic modeling (N-posts = 52.990), topics on two expert- and two peer-generated platforms were identified. Differences between and within platforms were found. While peer-generated platforms mainly covered interaction on emotional support topics, expert-generated platforms covered informational topics. Within peer-generated platforms, patients used their experiences differently.
机译:先前的在线健康研究主要集中在在线健康信息的预测因素或结果上,将在线健康信息本身留下来。 因此,在线健康信息仍然是包含不同平台的伞长术语(专家与对等生成的)。 将定性和计算方法结合的混合方法用于识别在这些不同平台上讨论的不同主题,并且开发了患者社会支持需求的初始模型,并应用于从混合方法获得的数据。 使用主题建模(n-posts = 52.990),确定了两个专家和两个对等生成平台的主题。 找到平台之间的差异。 虽然同伴的平台主要涵盖了情绪支持主题的互动,但专家生成的平台涵盖了信息主题。 在同伴生成的平台内,患者以不同的方式使用他们的体验。

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