Using early change to predict outcome in cognitive behaviour therapy: exploring timeframe, calculation method, and differences of disorder-specific versus general measures.

Early change can predict outcome of psychological treatment, especially in cognitive behavior therapy. However, the optimal operationalization of "early change" for maximizing its predictive ability, and differences in predictive ability of disorder-specific versus general mental health me...

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Autores principales: Peter Schibbye, Ata Ghaderi, Brjánn Ljótsson, Erik Hedman, Nils Lindefors, Christian Rück, Viktor Kaldo
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Publicado: Public Library of Science (PLoS) 2014
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Acceso en línea:https://doaj.org/article/f4dc98583e69494a90613be5431e76fb
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spelling oai:doaj.org-article:f4dc98583e69494a90613be5431e76fb2021-11-11T08:21:56ZUsing early change to predict outcome in cognitive behaviour therapy: exploring timeframe, calculation method, and differences of disorder-specific versus general measures.1932-620310.1371/journal.pone.0100614https://doaj.org/article/f4dc98583e69494a90613be5431e76fb2014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24959666/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Early change can predict outcome of psychological treatment, especially in cognitive behavior therapy. However, the optimal operationalization of "early change" for maximizing its predictive ability, and differences in predictive ability of disorder-specific versus general mental health measures has yet to be clarified. This study aimed to investigate how well early change predicted outcome depending on the week it was measured, the calculation method (regression slope or simple subtraction), the type of measures used, and the target disorder. During 10-15 weeks of internet-based cognitive behavior therapy for depression, social anxiety disorder, or panic disorder, weekly ratings were collected through both disorder-specific measures and general measures (Outcome Questionnaire-45 (OQ-45) and Clinical Outcomes in Routine Evaluation-10 (CORE-10)). With outcome defined as the disorder-specific measure, change at week four was the optimal predictor. Slope and subtraction methods performed equally well. The OQ-45 explained 18% of outcome for depression, 14% for social anxiety disorder, and 0% for panic disorder. Corresponding values for CORE-10 were 23%, 29%, and 25%. Specific measures explained 41%, 43%, and 34% respectively: this exceeded the ability of general measures also when they predicted themselves. We conclude that a simple calculation method with a disorder-specific measure at week four seems to provide a good choice for predicting outcome in time-limited cognitive behavior therapy.Peter SchibbyeAta GhaderiBrjánn LjótssonErik HedmanNils LindeforsChristian RückViktor KaldoPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 6, p e100614 (2014)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Peter Schibbye
Ata Ghaderi
Brjánn Ljótsson
Erik Hedman
Nils Lindefors
Christian Rück
Viktor Kaldo
Using early change to predict outcome in cognitive behaviour therapy: exploring timeframe, calculation method, and differences of disorder-specific versus general measures.
description Early change can predict outcome of psychological treatment, especially in cognitive behavior therapy. However, the optimal operationalization of "early change" for maximizing its predictive ability, and differences in predictive ability of disorder-specific versus general mental health measures has yet to be clarified. This study aimed to investigate how well early change predicted outcome depending on the week it was measured, the calculation method (regression slope or simple subtraction), the type of measures used, and the target disorder. During 10-15 weeks of internet-based cognitive behavior therapy for depression, social anxiety disorder, or panic disorder, weekly ratings were collected through both disorder-specific measures and general measures (Outcome Questionnaire-45 (OQ-45) and Clinical Outcomes in Routine Evaluation-10 (CORE-10)). With outcome defined as the disorder-specific measure, change at week four was the optimal predictor. Slope and subtraction methods performed equally well. The OQ-45 explained 18% of outcome for depression, 14% for social anxiety disorder, and 0% for panic disorder. Corresponding values for CORE-10 were 23%, 29%, and 25%. Specific measures explained 41%, 43%, and 34% respectively: this exceeded the ability of general measures also when they predicted themselves. We conclude that a simple calculation method with a disorder-specific measure at week four seems to provide a good choice for predicting outcome in time-limited cognitive behavior therapy.
format article
author Peter Schibbye
Ata Ghaderi
Brjánn Ljótsson
Erik Hedman
Nils Lindefors
Christian Rück
Viktor Kaldo
author_facet Peter Schibbye
Ata Ghaderi
Brjánn Ljótsson
Erik Hedman
Nils Lindefors
Christian Rück
Viktor Kaldo
author_sort Peter Schibbye
title Using early change to predict outcome in cognitive behaviour therapy: exploring timeframe, calculation method, and differences of disorder-specific versus general measures.
title_short Using early change to predict outcome in cognitive behaviour therapy: exploring timeframe, calculation method, and differences of disorder-specific versus general measures.
title_full Using early change to predict outcome in cognitive behaviour therapy: exploring timeframe, calculation method, and differences of disorder-specific versus general measures.
title_fullStr Using early change to predict outcome in cognitive behaviour therapy: exploring timeframe, calculation method, and differences of disorder-specific versus general measures.
title_full_unstemmed Using early change to predict outcome in cognitive behaviour therapy: exploring timeframe, calculation method, and differences of disorder-specific versus general measures.
title_sort using early change to predict outcome in cognitive behaviour therapy: exploring timeframe, calculation method, and differences of disorder-specific versus general measures.
publisher Public Library of Science (PLoS)
publishDate 2014
url https://doaj.org/article/f4dc98583e69494a90613be5431e76fb
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