Understanding Therapeutic Change Process Research Through Multilevel Modeling and Text Mining

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Abstract

Online interventions hold great potential for Therapeutic Change Process Research (TCPR), a field that aims to relate in-therapeutic change processes to the outcomes of interventions. Online a client is treated essentially through the language their counsellor uses, therefore the verbal interaction contains many important ingredients that bring about change. TCPR faces two challenges: how to derive meaningful change processes from texts, and secondly, how to assess these complex, varied, and multi-layered processes? We advocate the use text mining and multi-level models (MLMs): the former offers tools and methods to discovers patterns in texts; the latter can analyse these change processes as outcomes that vary at multiple levels. We (re-)used the data from Lamers et al. (2015) because it includes outcomes and the complete online intervention for clients with mild depressive symptoms. We used text mining to obtain basic text-variables from e-mails, that we analyzed through MLMs. We found that we could relate outcomes of interventions to variables containing text-information. We conclude that we can indeed bridge text mining and MLMs for TCPR as it was possible to relate text-information (obtained through text mining) to multi-leveled TCPR outcomes (using a MLM). Text mining can be helpful to obtain change processes, which is also the main challenge for TCPR. We showed how MLMs and text mining can be combined, but our proposition leaves open how to obtain the most relevant textual operationalization of TCPR concepts. That requires interdisciplinary collaboration and discussion. The future does look bright: based on our proof-of-concept study we conclude that MLMs and text mining can indeed advance TCPR.
Original languageEnglish
Article number1186
Pages (from-to)10
JournalFrontiers in psychology
Volume10
DOIs
Publication statusPublished - 29 May 2019

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Data Mining
Research
Therapeutics
Postal Service
Language
Outcome Assessment (Health Care)
Depression

Keywords

  • Therapeutic change processes research (TCPR)
  • Multilevel models (MLMs)
  • Text mining
  • Process data
  • Online interventions
  • Text variables

Cite this

@article{c04a222897d04a9ea92a69f0e1c6cd76,
title = "Understanding Therapeutic Change Process Research Through Multilevel Modeling and Text Mining",
abstract = "Online interventions hold great potential for Therapeutic Change Process Research (TCPR), a field that aims to relate in-therapeutic change processes to the outcomes of interventions. Online a client is treated essentially through the language their counsellor uses, therefore the verbal interaction contains many important ingredients that bring about change. TCPR faces two challenges: how to derive meaningful change processes from texts, and secondly, how to assess these complex, varied, and multi-layered processes? We advocate the use text mining and multi-level models (MLMs): the former offers tools and methods to discovers patterns in texts; the latter can analyse these change processes as outcomes that vary at multiple levels. We (re-)used the data from Lamers et al. (2015) because it includes outcomes and the complete online intervention for clients with mild depressive symptoms. We used text mining to obtain basic text-variables from e-mails, that we analyzed through MLMs. We found that we could relate outcomes of interventions to variables containing text-information. We conclude that we can indeed bridge text mining and MLMs for TCPR as it was possible to relate text-information (obtained through text mining) to multi-leveled TCPR outcomes (using a MLM). Text mining can be helpful to obtain change processes, which is also the main challenge for TCPR. We showed how MLMs and text mining can be combined, but our proposition leaves open how to obtain the most relevant textual operationalization of TCPR concepts. That requires interdisciplinary collaboration and discussion. The future does look bright: based on our proof-of-concept study we conclude that MLMs and text mining can indeed advance TCPR.",
keywords = "Therapeutic change processes research (TCPR), Multilevel models (MLMs), Text mining, Process data, Online interventions, Text variables",
author = "Smink, {Wouter A.C.} and Jean-Paul Fox and {Tjong Kim Sang}, Erik and Sools, {Anneke M.} and Westerhof, {Gerben J.} and Veldkamp, {Bernard P.}",
year = "2019",
month = "5",
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language = "English",
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journal = "Frontiers in psychology",
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Understanding Therapeutic Change Process Research Through Multilevel Modeling and Text Mining. / Smink, Wouter A.C.; Fox, Jean-Paul; Tjong Kim Sang, Erik; Sools, Anneke M.; Westerhof, Gerben J.; Veldkamp, Bernard P.

In: Frontiers in psychology, Vol. 10, 1186, 29.05.2019, p. 10.

Research output: Contribution to journalArticleAcademicpeer-review

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T1 - Understanding Therapeutic Change Process Research Through Multilevel Modeling and Text Mining

AU - Smink, Wouter A.C.

AU - Fox, Jean-Paul

AU - Tjong Kim Sang, Erik

AU - Sools, Anneke M.

AU - Westerhof, Gerben J.

AU - Veldkamp, Bernard P.

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AB - Online interventions hold great potential for Therapeutic Change Process Research (TCPR), a field that aims to relate in-therapeutic change processes to the outcomes of interventions. Online a client is treated essentially through the language their counsellor uses, therefore the verbal interaction contains many important ingredients that bring about change. TCPR faces two challenges: how to derive meaningful change processes from texts, and secondly, how to assess these complex, varied, and multi-layered processes? We advocate the use text mining and multi-level models (MLMs): the former offers tools and methods to discovers patterns in texts; the latter can analyse these change processes as outcomes that vary at multiple levels. We (re-)used the data from Lamers et al. (2015) because it includes outcomes and the complete online intervention for clients with mild depressive symptoms. We used text mining to obtain basic text-variables from e-mails, that we analyzed through MLMs. We found that we could relate outcomes of interventions to variables containing text-information. We conclude that we can indeed bridge text mining and MLMs for TCPR as it was possible to relate text-information (obtained through text mining) to multi-leveled TCPR outcomes (using a MLM). Text mining can be helpful to obtain change processes, which is also the main challenge for TCPR. We showed how MLMs and text mining can be combined, but our proposition leaves open how to obtain the most relevant textual operationalization of TCPR concepts. That requires interdisciplinary collaboration and discussion. The future does look bright: based on our proof-of-concept study we conclude that MLMs and text mining can indeed advance TCPR.

KW - Therapeutic change processes research (TCPR)

KW - Multilevel models (MLMs)

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KW - Process data

KW - Online interventions

KW - Text variables

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DO - 10.3389/fpsyg.2019.01186

M3 - Article

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JO - Frontiers in psychology

JF - Frontiers in psychology

SN - 1664-1078

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