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Understanding Therapeutic Change Process Research Through Multilevel Modeling and Text Mining.

Wouter A C Smink1,2, Jean-Paul Fox2, Erik Tjong Kim Sang3

  • 1Psychology, Health & Technology, University of Twente, Enschede, Netherlands.

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|June 14, 2019
PubMed
Summary

Text mining and multi-level models (MLMs) can analyze online therapy texts to understand therapeutic change processes. This approach successfully linked text data to intervention outcomes in clients with mild depression.

Keywords:
multilevel models (MLMs)online interventionsprocess datatext miningtext variablestherapeutic change processes research (TCPR)

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Area of Science:

  • Psychology
  • Computational Linguistics
  • Data Science

Background:

  • Therapeutic Change Process Research (TCPR) studies how therapy works.
  • Online interventions present unique challenges for analyzing therapeutic communication.
  • Deriving meaningful insights from therapy texts is a key challenge in TCPR.

Purpose of the Study:

  • To explore the use of text mining and multi-level models (MLMs) for Therapeutic Change Process Research (TCPR).
  • To investigate the relationship between textual features of online interventions and client outcomes.
  • To address challenges in deriving and assessing complex change processes from therapeutic texts.

Main Methods:

  • Utilized text mining techniques to extract variables from client-counsellor emails in an online intervention.
  • Applied multi-level models (MLMs) to analyze these extracted text variables.
  • Re-analyzed data from a previous study on clients with mild depressive symptoms.

Main Results:

  • Successfully related intervention outcomes to variables derived from text data.
  • Demonstrated the feasibility of combining text mining and MLMs for TCPR.
  • Showed that text mining can help identify therapeutic change processes.

Conclusions:

  • Text mining and MLMs can be effectively integrated to advance Therapeutic Change Process Research (TCPR).
  • This combined approach offers a promising method for analyzing online therapeutic interactions.
  • Further interdisciplinary collaboration is needed to refine the operationalization of TCPR concepts using textual data.