Different platforms for different patients’ needs: Automatic content analysis of different online health information platforms

Open Access
Authors
Publication date 05-2020
Journal International Journal of Human-Computer Studies
Article number 102386
Volume | Issue number 137
Number of pages 10
Organisations
  • Faculty of Social and Behavioural Sciences (FMG) - Amsterdam School of Communication Research (ASCoR)
Abstract
Prior online health research has mainly focused on the predictors or outcomes of online health information, leaving online health information itself understudied. Therefore, online health information has remained an umbrella term encompassing different platforms (expert- vs. peer-generated). A hybrid method that combines qualitative and computational methods is used to identify different topics discussed on these different platforms, and an initial model of patients’ social support needs was developed and applied to data obtained from the hybrid method. Using topic modeling (Nposts = 52.990), topics on two expert- and two peer-generated platforms were identified. Differences between and within platforms were found. While peer-generated platforms mainly covered interaction on emotional support topics, expert-generated platforms covered informational topics. Within peer-generated platforms, patients used their experiences differently.
Document type Article
Language English
Published at https://doi.org/10.1016/j.ijhcs.2019.102386
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