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How do online communities of people with long-term conditions function and evolve? Network analysis of the structure and dynamics of the Asthma UK and British Lung Foundation (BLF) online communities.

Research output: Contribution to journalArticlepeer-review

Sagar Prakash Joglekar, Nishanth Ramakrishna Sastry, Anna De Simoni, Pietro Panzarasa

Original languageEnglish
JournalJMIR Medical Informatics
Early online date11 Jul 2018
DOIs
Accepted/In press12 May 2018
E-pub ahead of print11 Jul 2018

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King's Authors

Abstract

Background:
Self-management support can improve health and reduce health care utilization by people with long-term conditions (LTCs). Online communities for people with LTCs have the potential to influence health, usage of health-care resources, and facilitate illness self-management. However, little is known about how such communities function and evolve over time, and how they support self-management of LTCs in practice.
Objective:
To gain a better understanding of the mechanisms underlying online self-management support systems through analysis of the structure and dynamics of the networks connecting users who write posts over time.
Methods:
Longitudinal network analysis of anonymised data from two UK patients’ online communities: the Asthma UK and the British Lung Foundation (BLF) communities, respectively in 2006-2016 and 2012-2016.
Results:
Number of users and activity grew over time, reaching 3,345 users and 32,780 posts in the Asthma UK community, and 19,837 users and 875,151 posts in the BLF community. People who wrote posts in the Asthma UK forum tended to write at an interval of 1-20 days and six months, whilst those in the BLF community at an interval of two days. In both communities, most pairs of users could reach one another either directly or indirectly through other users. Those who wrote a disproportionally large number of posts (the super-users) represented 1% of the overall population of both Asthma UK and BLF communities, and accounted for 32% and 49% of the posts, respectively. Sensitivity analysis showed that the removal of super-users would cause the communities to collapse. Thus, interactions were held together by very few super-users, who posted frequently and regularly, 65% of them at least every 1.7 days in the BLF community and 70% every 3.1 days in the Asthma UK community. Their posting activity indirectly facilitated tie formation between other users. Super-users were a constantly available resource, with an average of 80 and 20 super-users active at any one time in the BLF and Asthma UK communities, respectively. Over time, the more active users became, the more likely they were to reply to other users’ posts rather than to write new ones, shifting from a help-seeking to a help-giving role. This might suggest that super-users were more likely to provide than to seek advice.
Conclusions:
In this study we uncover key structural properties related to the way users interact and sustain online health communities. Super-users’ engagement plays a fundamental sustaining role and deserves research attention. Further studies are needed to explore network determinants of effectiveness of online engagement with respect to health-related outcomes. In resource-constrained healthcare systems, scaling up online communities may offer a potentially accessible, wide-reaching and cost-effective intervention facilitating greater levels of self-management.

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