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

an article by Remco Sanders, Annemiek J. Linn, Theo B. Araujo, Rens Vliegenthart and  Julia C.M. van Weert (University of Amsterdam, the Netherlands) and Mies C. van Eenbergen (Netherlands Comprehensive Cancer Organisation, Utrecht, the Netherlands) published in International Journal of Human-Computer Studies Volume 137 (May 2020)

Highlights

• Peer-generated platforms mostly contain content on affective support needs whereas expert-generated platforms mostly contain content on cognitive support needs.
• Coupling topic modelling and a-priori defined theoretical models in a hybrid method proof to be useful in analysing online health information data.
• In line with the optimal matching model, patients should be referred to, or seek out, specific platforms depending on their needs.

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 modelling (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.

Labels;
information_seeking_behaviour, online_health_information, information_needs, cancer, automatic_content_analysis, model_of_patients’_social_support_needs,

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