| Literature DB >> 28269969 |
Shaodian Zhang1, Noémie Elhadad1.
Abstract
Dropping-out, which refers to when an individual abandons an intervention, is common in Internet-based studies as well as in online health communities. Community facilitators and health researchers are interested in this phenomenon because it usually indicates dissatisfaction towards the community and/or its failure to deliver expected benefits. In this study, we propose a method to identify dropout members from a large public online breast cancer community. We then study quantitatively what longitudinal factors of participation are correlated with dropping-out. Our experimental results suggest that dropout members discuss diagnosis- and treatment-related topics more than other topics. Furthermore, in the time before withdrawing from the community, dropout members tend to initiate more discussions but do not receive adequate response from the other members. We also discuss implications of our results and challenges in dropout-member identification. This study contributes to further understanding community participation and opens up a number of future research questions.Entities:
Mesh:
Year: 2017 PMID: 28269969 PMCID: PMC5333218
Source DB: PubMed Journal: AMIA Annu Symp Proc ISSN: 1559-4076