Psychotherapists' acceptance of telepsychotherapy during the COVID‐19 pandemic: A machine learning approach

Objective This study aimed to develop predictive models of three aspects of psychotherapists' acceptance of telepsychotherapy (TPT) during the COVID‐19 pandemic, attitudes towards TPT technology, concerns about using TPT technology and intention to use TPT technology in the future. Method Thera...

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Published inClinical psychology and psychotherapy Vol. 28; no. 6; pp. 1403 - 1415
Main Authors Békés, Vera, Aafjes‐van Doorn, Katie, Zilcha‐Mano, Sigal, Prout, Tracy, Hoffman, Leon
Format Journal Article
LanguageEnglish
Published England John Wiley and Sons, Limited 01.11.2021
John Wiley and Sons Inc
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Abstract Objective This study aimed to develop predictive models of three aspects of psychotherapists' acceptance of telepsychotherapy (TPT) during the COVID‐19 pandemic, attitudes towards TPT technology, concerns about using TPT technology and intention to use TPT technology in the future. Method Therapists (n = 795) responded to a survey about their TPT experiences during the pandemic, including quality of the therapeutic relationship, professional self‐doubt, vicarious trauma and TPT acceptance. Regression decision tree machine learning analyses were used to build prediction models for each of three aspects of TPT acceptance in a training subset of the data and subsequently tested in the remaining subset of the total sample. Results Attitudes towards TPT were most positive for therapists who reported a neutral or strong online working alliance with their patients, especially if they experienced little professional self‐doubt and were younger than 40 years old. Therapists who were most concerned about TPT were those who reported higher levels of professional self‐doubt, particularly if they also reported vicarious trauma experiences. Therapists who reported low working alliance with their patients were least likely to use TPT in the future. Performance metrics for the decision trees indicated that these three models held up well in an out‐of‐sample dataset. Conclusions Therapists' professional self‐doubt and the quality of their working alliance with their online patients appear to be the most pertinent factors associated with therapists' acceptance of TPT technology during COVID‐19 and should be addressed in future training and research.
AbstractList Objective This study aimed to develop predictive models of three aspects of psychotherapists' acceptance of telepsychotherapy (TPT) during the COVID‐19 pandemic, attitudes towards TPT technology, concerns about using TPT technology and intention to use TPT technology in the future. Method Therapists (n = 795) responded to a survey about their TPT experiences during the pandemic, including quality of the therapeutic relationship, professional self‐doubt, vicarious trauma and TPT acceptance. Regression decision tree machine learning analyses were used to build prediction models for each of three aspects of TPT acceptance in a training subset of the data and subsequently tested in the remaining subset of the total sample. Results Attitudes towards TPT were most positive for therapists who reported a neutral or strong online working alliance with their patients, especially if they experienced little professional self‐doubt and were younger than 40 years old. Therapists who were most concerned about TPT were those who reported higher levels of professional self‐doubt, particularly if they also reported vicarious trauma experiences. Therapists who reported low working alliance with their patients were least likely to use TPT in the future. Performance metrics for the decision trees indicated that these three models held up well in an out‐of‐sample dataset. Conclusions Therapists' professional self‐doubt and the quality of their working alliance with their online patients appear to be the most pertinent factors associated with therapists' acceptance of TPT technology during COVID‐19 and should be addressed in future training and research.
Abstract Objective This study aimed to develop predictive models of three aspects of psychotherapists' acceptance of telepsychotherapy (TPT) during the COVID‐19 pandemic, attitudes towards TPT technology, concerns about using TPT technology and intention to use TPT technology in the future. Method Therapists ( n  = 795) responded to a survey about their TPT experiences during the pandemic, including quality of the therapeutic relationship, professional self‐doubt, vicarious trauma and TPT acceptance. Regression decision tree machine learning analyses were used to build prediction models for each of three aspects of TPT acceptance in a training subset of the data and subsequently tested in the remaining subset of the total sample. Results Attitudes towards TPT were most positive for therapists who reported a neutral or strong online working alliance with their patients, especially if they experienced little professional self‐doubt and were younger than 40 years old. Therapists who were most concerned about TPT were those who reported higher levels of professional self‐doubt, particularly if they also reported vicarious trauma experiences. Therapists who reported low working alliance with their patients were least likely to use TPT in the future. Performance metrics for the decision trees indicated that these three models held up well in an out‐of‐sample dataset. Conclusions Therapists' professional self‐doubt and the quality of their working alliance with their online patients appear to be the most pertinent factors associated with therapists' acceptance of TPT technology during COVID‐19 and should be addressed in future training and research.
ObjectiveThis study aimed to develop predictive models of three aspects of psychotherapists' acceptance of telepsychotherapy (TPT) during the COVID‐19 pandemic, attitudes towards TPT technology, concerns about using TPT technology and intention to use TPT technology in the future.MethodTherapists (n = 795) responded to a survey about their TPT experiences during the pandemic, including quality of the therapeutic relationship, professional self‐doubt, vicarious trauma and TPT acceptance. Regression decision tree machine learning analyses were used to build prediction models for each of three aspects of TPT acceptance in a training subset of the data and subsequently tested in the remaining subset of the total sample.ResultsAttitudes towards TPT were most positive for therapists who reported a neutral or strong online working alliance with their patients, especially if they experienced little professional self‐doubt and were younger than 40 years old. Therapists who were most concerned about TPT were those who reported higher levels of professional self‐doubt, particularly if they also reported vicarious trauma experiences. Therapists who reported low working alliance with their patients were least likely to use TPT in the future. Performance metrics for the decision trees indicated that these three models held up well in an out‐of‐sample dataset.ConclusionsTherapists' professional self‐doubt and the quality of their working alliance with their online patients appear to be the most pertinent factors associated with therapists' acceptance of TPT technology during COVID‐19 and should be addressed in future training and research.
This study aimed to develop predictive models of three aspects of psychotherapists' acceptance of telepsychotherapy (TPT) during the COVID-19 pandemic, attitudes towards TPT technology, concerns about using TPT technology and intention to use TPT technology in the future.OBJECTIVEThis study aimed to develop predictive models of three aspects of psychotherapists' acceptance of telepsychotherapy (TPT) during the COVID-19 pandemic, attitudes towards TPT technology, concerns about using TPT technology and intention to use TPT technology in the future.Therapists (n = 795) responded to a survey about their TPT experiences during the pandemic, including quality of the therapeutic relationship, professional self-doubt, vicarious trauma and TPT acceptance. Regression decision tree machine learning analyses were used to build prediction models for each of three aspects of TPT acceptance in a training subset of the data and subsequently tested in the remaining subset of the total sample.METHODTherapists (n = 795) responded to a survey about their TPT experiences during the pandemic, including quality of the therapeutic relationship, professional self-doubt, vicarious trauma and TPT acceptance. Regression decision tree machine learning analyses were used to build prediction models for each of three aspects of TPT acceptance in a training subset of the data and subsequently tested in the remaining subset of the total sample.Attitudes towards TPT were most positive for therapists who reported a neutral or strong online working alliance with their patients, especially if they experienced little professional self-doubt and were younger than 40 years old. Therapists who were most concerned about TPT were those who reported higher levels of professional self-doubt, particularly if they also reported vicarious trauma experiences. Therapists who reported low working alliance with their patients were least likely to use TPT in the future. Performance metrics for the decision trees indicated that these three models held up well in an out-of-sample dataset.RESULTSAttitudes towards TPT were most positive for therapists who reported a neutral or strong online working alliance with their patients, especially if they experienced little professional self-doubt and were younger than 40 years old. Therapists who were most concerned about TPT were those who reported higher levels of professional self-doubt, particularly if they also reported vicarious trauma experiences. Therapists who reported low working alliance with their patients were least likely to use TPT in the future. Performance metrics for the decision trees indicated that these three models held up well in an out-of-sample dataset.Therapists' professional self-doubt and the quality of their working alliance with their online patients appear to be the most pertinent factors associated with therapists' acceptance of TPT technology during COVID-19 and should be addressed in future training and research.CONCLUSIONSTherapists' professional self-doubt and the quality of their working alliance with their online patients appear to be the most pertinent factors associated with therapists' acceptance of TPT technology during COVID-19 and should be addressed in future training and research.
This study aimed to develop predictive models of three aspects of psychotherapists' acceptance of telepsychotherapy (TPT) during the COVID-19 pandemic, attitudes towards TPT technology, concerns about using TPT technology and intention to use TPT technology in the future. Therapists (n = 795) responded to a survey about their TPT experiences during the pandemic, including quality of the therapeutic relationship, professional self-doubt, vicarious trauma and TPT acceptance. Regression decision tree machine learning analyses were used to build prediction models for each of three aspects of TPT acceptance in a training subset of the data and subsequently tested in the remaining subset of the total sample. Attitudes towards TPT were most positive for therapists who reported a neutral or strong online working alliance with their patients, especially if they experienced little professional self-doubt and were younger than 40 years old. Therapists who were most concerned about TPT were those who reported higher levels of professional self-doubt, particularly if they also reported vicarious trauma experiences. Therapists who reported low working alliance with their patients were least likely to use TPT in the future. Performance metrics for the decision trees indicated that these three models held up well in an out-of-sample dataset. Therapists' professional self-doubt and the quality of their working alliance with their online patients appear to be the most pertinent factors associated with therapists' acceptance of TPT technology during COVID-19 and should be addressed in future training and research.
Author Zilcha‐Mano, Sigal
Aafjes‐van Doorn, Katie
Prout, Tracy
Hoffman, Leon
Békés, Vera
AuthorAffiliation 1 Ferkauf Graduate School of Psychology Yeshiva University New York New York USA
2 Department of Psychology University of Haifa Haifa Israel
3 New York Psychoanalytic Institute New York New York USA
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Issue 6
Keywords COVID-19
therapists
machine learning
online therapy
UTAUT model
telepsychotherapy
Language English
License 2021 John Wiley & Sons, Ltd.
This article is being made freely available through PubMed Central as part of the COVID-19 public health emergency response. It can be used for unrestricted research re-use and analysis in any form or by any means with acknowledgement of the original source, for the duration of the public health emergency.
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Notes Funding information
Vera Békés and Katie Aafjes‐van Doorn shared first authorship.
China American Psychoanalytic Alliance
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e_1_2_10_5_1
e_1_2_10_56_1
e_1_2_10_7_1
e_1_2_10_36_1
e_1_2_10_12_1
e_1_2_10_35_1
e_1_2_10_9_1
e_1_2_10_59_1
e_1_2_10_10_1
Glantz S. A. (e_1_2_10_31_1) 2001
e_1_2_10_33_1
e_1_2_10_50_1
e_1_2_10_60_1
e_1_2_10_62_1
e_1_2_10_64_1
e_1_2_10_28_1
e_1_2_10_49_1
e_1_2_10_66_1
Vrigazova B. (e_1_2_10_71_1) 2021; 12
e_1_2_10_26_1
e_1_2_10_47_1
e_1_2_10_68_1
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Snippet Objective This study aimed to develop predictive models of three aspects of psychotherapists' acceptance of telepsychotherapy (TPT) during the COVID‐19...
This study aimed to develop predictive models of three aspects of psychotherapists' acceptance of telepsychotherapy (TPT) during the COVID-19 pandemic,...
Abstract Objective This study aimed to develop predictive models of three aspects of psychotherapists' acceptance of telepsychotherapy (TPT) during the...
ObjectiveThis study aimed to develop predictive models of three aspects of psychotherapists' acceptance of telepsychotherapy (TPT) during the COVID‐19...
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StartPage 1403
SubjectTerms Adult
COVID-19
Humans
Learning algorithms
Machine Learning
online therapy
Pandemics
Prediction models
Psychotherapists
Psychotherapy
SARS-CoV-2
Special Issue
Telemedicine
telepsychotherapy
Therapists
Training
Trauma
UTAUT model
Title Psychotherapists' acceptance of telepsychotherapy during the COVID‐19 pandemic: A machine learning approach
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fcpp.2682
https://www.ncbi.nlm.nih.gov/pubmed/34723404
https://www.proquest.com/docview/2618220593
https://www.proquest.com/docview/2591216970
https://pubmed.ncbi.nlm.nih.gov/PMC8652775
Volume 28
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