PDF(Pubmed)
Abstract：
BACKGROUND: There is evidence that social interaction has an inverse association with the development of neurodegenerative diseases. PREDICT-Parkinson Disease (PREDICT-PD) is an online UK cohort study that stratifies participants for risk of future Parkinson disease (PD).
OBJECTIVE: This study aims to explore the methodological approach and feasibility of assessing the digital social characteristics of people at risk of developing PD and their social capital within the PREDICT-PD platform, making hypotheses about the relationship between web-based social engagement and potential predictive risk indicators of PD.
METHODS: A web-based application was built to enable social interaction through the PREDICT-PD portal. Feedback from existing members of the cohort was sought and informed the design of the pilot. Dedicated staff used weekly engagement activities, consisting of PD-related research, facts, and queries, to stimulate discussion. Data were collected by the hosting platform. We examined the pattern of connections generated over time through the cumulative number of posts and replies and ego networks using social network analysis. We used network metrics to describe the bonding, bridging, and linking of social capital among participants on the platform. Relevant demographic data and Parkinson risk scores (expressed as an odd 1:x) were analyzed using descriptive statistics. Regression analysis was conducted to estimate the relationship between risk scores (after log transformation) and network measures.
RESULTS: Overall, 219 participants took part in a 4-month pilot forum embedded in the study website. In it, 200 people (n=80, 40% male and n=113, 57% female) connected in a large group, where most pairs of users could reach one another either directly or indirectly through other users. A total of 59% (20/34) of discussions were spontaneously started by participants. Participation was asynchronous, with some individuals acting as \"brokers\" between groups of discussions. As more participants joined the forum and connected to one another through online posts, distinct groups of connected users started to emerge. This pilot showed that a forum application within the cohort web platform was feasible and acceptable and fostered digital social interaction. Matching participants\' web-based social engagement with previously collected data at individual level in the PREDICT-PD study was feasible, showing potential for future analyses correlating online network characteristics with the risk of PD over time, as well as testing digital social engagement as an intervention to modify the risk of developing neurodegenerative diseases.
CONCLUSIONS: The results from the pilot suggest that an online forum can serve as an intervention to enhance social connectedness and investigate whether patterns of online engagement can impact the risk of developing PD through long-term follow-up. This highlights the potential of leveraging online platforms to study the role of social capital in moderating PD risk and underscores the feasibility of such approaches in future research or interventions.
OBJECTIVE: This study aims to explore the methodological approach and feasibility of assessing the digital social characteristics of people at risk of developing PD and their social capital within the PREDICT-PD platform, making hypotheses about the relationship between web-based social engagement and potential predictive risk indicators of PD.
METHODS: A web-based application was built to enable social interaction through the PREDICT-PD portal. Feedback from existing members of the cohort was sought and informed the design of the pilot. Dedicated staff used weekly engagement activities, consisting of PD-related research, facts, and queries, to stimulate discussion. Data were collected by the hosting platform. We examined the pattern of connections generated over time through the cumulative number of posts and replies and ego networks using social network analysis. We used network metrics to describe the bonding, bridging, and linking of social capital among participants on the platform. Relevant demographic data and Parkinson risk scores (expressed as an odd 1:x) were analyzed using descriptive statistics. Regression analysis was conducted to estimate the relationship between risk scores (after log transformation) and network measures.
RESULTS: Overall, 219 participants took part in a 4-month pilot forum embedded in the study website. In it, 200 people (n=80, 40% male and n=113, 57% female) connected in a large group, where most pairs of users could reach one another either directly or indirectly through other users. A total of 59% (20/34) of discussions were spontaneously started by participants. Participation was asynchronous, with some individuals acting as \"brokers\" between groups of discussions. As more participants joined the forum and connected to one another through online posts, distinct groups of connected users started to emerge. This pilot showed that a forum application within the cohort web platform was feasible and acceptable and fostered digital social interaction. Matching participants\' web-based social engagement with previously collected data at individual level in the PREDICT-PD study was feasible, showing potential for future analyses correlating online network characteristics with the risk of PD over time, as well as testing digital social engagement as an intervention to modify the risk of developing neurodegenerative diseases.
CONCLUSIONS: The results from the pilot suggest that an online forum can serve as an intervention to enhance social connectedness and investigate whether patterns of online engagement can impact the risk of developing PD through long-term follow-up. This highlights the potential of leveraging online platforms to study the role of social capital in moderating PD risk and underscores the feasibility of such approaches in future research or interventions.
摘要：
背景：有证据表明，社会互动与神经退行性疾病的发展呈负相关。PREDICT-帕金森病（PREDICT-PD）是一项在线英国队列研究，对参与者的未来帕金森病（PD）风险进行分层。
目的：本研究旨在探索在PREDICT-PD平台中评估有发展PD风险的人的数字社会特征及其社会资本的方法和可行性，对基于网络的社交参与与PD的潜在预测风险指标之间的关系进行假设。
方法：构建了一个基于Web的应用程序，以通过PREDICT-PD门户进行社交互动。从该队列的现有成员那里寻求反馈，并告知飞行员的设计。敬业的员工使用每周的参与活动，由PD相关研究组成，事实,和查询，激发讨论。数据由托管平台收集。我们使用社交网络分析，通过帖子和回复的累积数量以及自我网络来检查随着时间的推移产生的联系模式。我们使用网络度量来描述这种联系，桥接，以及平台上参与者之间的社会资本联系。使用描述性统计学分析相关的人口统计学数据和帕金森风险评分(表示为奇数1:x)。进行回归分析以估计风险评分（经过对数转换）与网络度量之间的关系。
结果：总体而言，219名参与者参加了嵌入研究网站的为期4个月的试点论坛。在它，200人（n=80，40％的男性和n=113，57％的女性）连接在一个大的群体，大多数用户可以通过其他用户直接或间接地联系到对方。共有59％（20/34）的讨论是由参与者自发开始的。参与是异步的，一些人充当讨论小组之间的“经纪人”。随着越来越多的参与者加入论坛并通过在线帖子相互联系，不同的连接用户群开始出现。该试点表明，队列网络平台中的论坛应用程序是可行且可接受的，并促进了数字社交互动。在PREDICT-PD研究中，将参与者基于网络的社交参与与先前收集的个人数据进行匹配是可行的，显示出未来分析的潜力，将在线网络特征与随着时间的推移的PD风险相关联，以及测试数字社交参与作为一种干预措施，以改变患神经退行性疾病的风险。
结论：试点结果表明，在线论坛可以作为一种干预措施，以增强社交联系，并调查在线参与模式是否会通过长期随访影响发展为PD的风险。这凸显了利用在线平台研究社会资本在调节PD风险中的作用的潜力，并强调了此类方法在未来研究或干预中的可行性。
目的：本研究旨在探索在PREDICT-PD平台中评估有发展PD风险的人的数字社会特征及其社会资本的方法和可行性，对基于网络的社交参与与PD的潜在预测风险指标之间的关系进行假设。
方法：构建了一个基于Web的应用程序，以通过PREDICT-PD门户进行社交互动。从该队列的现有成员那里寻求反馈，并告知飞行员的设计。敬业的员工使用每周的参与活动，由PD相关研究组成，事实,和查询，激发讨论。数据由托管平台收集。我们使用社交网络分析，通过帖子和回复的累积数量以及自我网络来检查随着时间的推移产生的联系模式。我们使用网络度量来描述这种联系，桥接，以及平台上参与者之间的社会资本联系。使用描述性统计学分析相关的人口统计学数据和帕金森风险评分(表示为奇数1:x)。进行回归分析以估计风险评分（经过对数转换）与网络度量之间的关系。
结果：总体而言，219名参与者参加了嵌入研究网站的为期4个月的试点论坛。在它，200人（n=80，40％的男性和n=113，57％的女性）连接在一个大的群体，大多数用户可以通过其他用户直接或间接地联系到对方。共有59％（20/34）的讨论是由参与者自发开始的。参与是异步的，一些人充当讨论小组之间的“经纪人”。随着越来越多的参与者加入论坛并通过在线帖子相互联系，不同的连接用户群开始出现。该试点表明，队列网络平台中的论坛应用程序是可行且可接受的，并促进了数字社交互动。在PREDICT-PD研究中，将参与者基于网络的社交参与与先前收集的个人数据进行匹配是可行的，显示出未来分析的潜力，将在线网络特征与随着时间的推移的PD风险相关联，以及测试数字社交参与作为一种干预措施，以改变患神经退行性疾病的风险。
结论：试点结果表明，在线论坛可以作为一种干预措施，以增强社交联系，并调查在线参与模式是否会通过长期随访影响发展为PD的风险。这凸显了利用在线平台研究社会资本在调节PD风险中的作用的潜力，并强调了此类方法在未来研究或干预中的可行性。
