Turn Your Online Engagement in Chronic Disease Management from Zero to Hero: A Multi-Dimensional Continuous-Time Evaluation

Tongxin Zhou, L. Yan, Yingfei Wang, Yong Tan
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引用次数: 1

Abstract

Individuals’ engagement in online healthcare communities (OHCs) has attracted a large body of research. However, prior research has mainly studied a single behavioral dimension of online engagement. Given that individuals’ online engagement is a complex process, overlooking certain aspects of engagement may lead to underestimating the effectiveness of OHCs. In addition, due to the progressive nature of chronic disease, chronic disease management needs to be evaluated continuously. These concerns motivate us to develop a framework that accounts for both engagement dimensions and engagement timing for studying chronic disease management in OHCs. Considering that the engagement level of disease management cannot be directly observed, in this study, we propose a multi-dimensional Continuous-Time Hidden Markov Model (CTHMM) that captures individuals’ engagement level as a latent state. We root our research in the context of weight management. Our main findings include: 1) The timing of engagement can affect an individual’s engagement level; for instance, individuals with higher participation frequency are more likely to shift to different engagement levels. 2) Participating in support-exchange activities can shift individuals’ focus from weigh-ins to journals, which are two distinct behavioral dimensions of self-monitoring. Thus, an incomplete characterization of engagement dimensions can underestimate individuals’ activeness in OHCs, which will further lead to underrating the role of OHCs in chronic disease control. 3) Different forms of social support can have statistically different effects on engagement, and these effects are mediated by individuals’ own engagement levels. Individuals need to “smartly” adopt social support tools to improve their health management.
将您在慢性病管理中的在线参与从零变为英雄:多维度连续时间评估
个人参与在线医疗保健社区(ohc)已经吸引了大量的研究。然而,先前的研究主要是研究在线参与的单一行为维度。鉴于个人的在线参与是一个复杂的过程,忽视参与的某些方面可能会导致低估ohc的有效性。此外,由于慢性疾病的进行性,需要对慢性疾病的管理进行持续评估。这些问题促使我们开发一个框架,用于研究OHCs慢性疾病管理的参与维度和参与时间。考虑到疾病管理的投入水平无法直接观察,在本研究中,我们提出了一个多维连续时间隐马尔可夫模型(CTHMM),该模型将个体的投入水平作为一种潜在状态捕获。我们的研究植根于体重管理的背景下。我们的主要发现包括:1)投入的时间会影响个体的投入水平;例如,参与频率较高的个人更有可能转变为不同的参与水平。2)参与支持交换活动可以将个体的注意力从称重转移到期刊,这是自我监控的两个不同的行为维度。因此,不完整的敬业度表征会低估个体在职业健康中心中的活跃度,进而导致职业健康中心在慢性疾病控制中的作用被低估。3)不同形式的社会支持对敬业度的影响具有统计学上的差异,而这些影响是由个体自身的敬业度水平介导的。个人需要“聪明地”采用社会支持工具来改善他们的健康管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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