Pérez-Aldana Carlos A, Lewinski Allison A, Johnson Constance M, Vorderstrasse Allison A, Myneni Sahiti
School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States.
Durham Veterans Affairs Medical Center, Durham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham, NC, United States.
JMIR Diabetes. 2021 Jan 25;6(1):e21611. doi: 10.2196/21611.
Diabetes remains a major health problem in the United States, affecting an estimated 10.5% of the population. Diabetes self-management interventions improve diabetes knowledge, self-management behaviors, and clinical outcomes. Widespread internet connectivity facilitates the use of eHealth interventions, which positively impacts knowledge, social support, and clinical and behavioral outcomes. In particular, diabetes interventions based on virtual environments have the potential to improve diabetes self-efficacy and support, while being highly feasible and usable. However, little is known about the patterns of social interactions and support taking place within type 2 diabetes-specific virtual communities.
The objective of this study was to examine social support exchanges from a type 2 diabetes self-management education and support intervention that was delivered via a virtual environment.
Data comprised virtual environment-mediated synchronous interactions among participants and between participants and providers from an intervention for type 2 diabetes self-management education and support. Network data derived from such social interactions were used to create networks to analyze patterns of social support exchange with the lens of social network analysis. Additionally, network correlations were used to explore associations between social support networks.
The findings revealed structural differences between support networks, as well as key network characteristics of supportive interactions facilitated by the intervention. Emotional and appraisal support networks are the larger, most centralized, and most active networks, suggesting that virtual communities can be good sources for these types of support. In addition, appraisal and instrumental support networks are more connected, suggesting that members of virtual communities are more likely to engage in larger group interactions where these types of support can be exchanged. Lastly, network correlations suggest that participants who exchange emotional support are likely to exchange appraisal or instrumental support, and participants who exchange appraisal support are likely to exchange instrumental support.
Social interaction patterns from disease-specific virtual environments can be studied using a social network analysis approach to better understand the exchange of social support. Network data can provide valuable insights into the design of novel and effective eHealth interventions given the unique opportunity virtual environments have facilitating realistic environments that are effective and sustainable, where social interactions can be leveraged to achieve diverse health goals.
糖尿病在美国仍然是一个主要的健康问题，估计影响着10.5%的人口。糖尿病自我管理干预措施可提高糖尿病知识、自我管理行为和临床结果。广泛的互联网连接促进了电子健康干预措施的使用，这对知识、社会支持以及临床和行为结果产生了积极影响。特别是，基于虚拟环境的糖尿病干预措施有潜力提高糖尿病自我效能感并提供支持，同时具有高度的可行性和易用性。然而，对于2型糖尿病特定虚拟社区内发生的社会互动和支持模式知之甚少。
本研究的目的是检查通过虚拟环境提供的2型糖尿病自我管理教育和支持干预中的社会支持交流情况。
数据包括参与者之间以及参与者与提供者之间通过虚拟环境介导的同步互动，这些互动来自一项2型糖尿病自我管理教育和支持干预。从这种社会互动中得出的网络数据被用于创建网络，以便从社会网络分析的角度分析社会支持交流模式。此外，网络相关性被用于探索社会支持网络之间的关联。
研究结果揭示了支持网络之间的结构差异，以及该干预措施促进的支持性互动的关键网络特征。情感和评估支持网络是更大、最集中且最活跃的网络，这表明虚拟社区可以成为这些类型支持的良好来源。此外，评估和工具性支持网络的连接性更强，这表明虚拟社区的成员更有可能参与能够交流这些类型支持的更大规模的群体互动。最后，网络相关性表明，交换情感支持的参与者可能会交换评估或工具性支持，而交换评估支持的参与者可能会交换工具性支持。
可以使用社会网络分析方法研究特定疾病虚拟环境中的社会互动模式，以更好地理解社会支持的交流。鉴于虚拟环境具有促进有效且可持续的现实环境的独特机会，在这种环境中可以利用社会互动来实现各种健康目标，网络数据可以为设计新颖有效的电子健康干预措施提供有价值的见解。
