Accepted for/Published in: JMIR Formative Research
Date Submitted: Aug 18, 2023
Date Accepted: Mar 21, 2024
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
A pilot study of the role of social capital in a Parkinson’s disease risk cohort
ABSTRACT
Background:
There is evidence that social interaction has an inverse association with the development of neurodegenerative diseases. PREDICT-PD is an online UK cohort study that stratifies participants for risk of future Parkinson’s 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.
Methods:
A web application was built to enable social interaction via 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. Both visualisation and analysis were conducted using Python. Descriptive analysis of the networks (i.e., number of users, posts, and posting frequency) was carried out using the Pandas library and Networkx. Relevant demographic data and Parkinson’s risk scores (expressed as an odds 1:x) were analysed using descriptive statistics. As the PD risk score is the inverse of the risk of developing PD, users with lower risk PD score have higher risk of developing PD. Regression analysis was conducted to estimate the relationships between risk scores (after log transformation) and network measures.
Results:
219 participants took part in a 4-month pilot forum embedded in the study website. 201 people connected in a large group, where most pairs of users could reach one another either directly or indirectly through other users. 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 with PREDICT-PD previously collected data was feasible, showing potential for future analyses correlating online network characteristics with risk of PD over time, as well as testing digital social engagement as an intervention to modify the risk of developing neurodegenerative diseases.
Conclusions:
These results show the potential of an online forum to investigate the role of social capital as a catalyst for moderating the risk of PD. Clinical Trial: n/a
Citation
