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

Remco Sanders*, Annemiek J. Linn, Theo B. Araujo, Rens Vliegenthart, Mies C. van Eenbergen, Julia C.M. van Weert

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

10 Citations (Scopus)

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.

Original languageEnglish
Article number102386
JournalInternational Journal of Human Computer Studies
Volume137
DOIs
Publication statusPublished - May 2020
Externally publishedYes

Keywords

  • Automatic content analysis
  • Cancer
  • Information needs
  • Information seeking behavior
  • Model of patients’ social support needs
  • Online health information

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