Data mining techniques in psychotherapy: applications for studying therapeutic alliance

Detalhes bibliográficos
Autor(a) principal: Mosavi, Nasimsadat
Data de Publicação: 2023
Outros Autores: Ribeiro, Eugénia, Sampaio, Adriana, Santos, Manuel
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/1822/90409
Resumo: Data has been uploaded to the public repository; Kaggle. @misc{nasim sadat mosavi_2023, title={therapeutic alliance_ clients and therapists}, url={https://www.kaggle.com/dsv/6168984}, DOI={10.34740/KAGGLE/ DSV/6168984}, publisher={Kaggle}, author={Nasim Sadat Mosavi}, year={2023}}.
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spelling Data mining techniques in psychotherapy: applications for studying therapeutic allianceCiências Sociais::PsicologiaEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaData has been uploaded to the public repository; Kaggle. @misc{nasim sadat mosavi_2023, title={therapeutic alliance_ clients and therapists}, url={https://www.kaggle.com/dsv/6168984}, DOI={10.34740/KAGGLE/ DSV/6168984}, publisher={Kaggle}, author={Nasim Sadat Mosavi}, year={2023}}.Therapeutic Alliance (TA) has been consistently reported as a robust predictor of therapy outcomes and is one of the most investigated therapy relational factors. Research on therapists' and clients’ contributions to the alliance development and the alliance-outcome relationship had shown mixed results. The relation of the therapist’s and client’s biological markers with the alliance is an important and under-investigated topic. Taking advantage of data mining techniques, this exploratory study aimed to investigate the role of different therapist and client factors, including heart rate (HR) and electrodermal activity (EDA), in relation to TA. Twenty-two dyads with 6 therapists and 22 clients participated in the study. The Working Alliance Inventory (WAI) was used to evaluate the client’s and therapist's perception of the alliance at the end of each session and through the therapy processes. The Cross-Industry Standard Process for Data Mining (CRISP-DM) was used to explore patterns that may contribute to TA. Machine Learning (ML) models have been employed to provide insights into the predictors and correlates of TA. Our results showed that Linear Regression (LR) was the best technique for predicting the therapist’s TA, with client “Diagnostic” and therapy “Termination” being identified as significant predictors of the therapist’s TA. In addition, for clients’ TA, the Random Forest (RF) was shown to have the best performance. The therapist’s TA and therapy “Outcome” were observed as the most influential predictors for the client’s TA. In addition, while the Heart Rate (therapist) was negatively associated with the therapist’s TA, EDA in the client was a physiological indicator related to the client’s TA. Overall, these findings can assist in identifying key factors that therapists should focus on to enhance the quality of therapeutic alliance. Results are discussed in terms of their consistency with empirical literature, innovative and interdisciplinary research on the therapeutic alliance field, and, in particulaThe work of Eugénia Ribeiro and Adriana Sampaio has been supported by FCT – Fundação para a Ciência e Tecnologia AND Bial Foundation and was conducted at the Psychology Research Centre (CIPsi/UM) School of Psychology, University of Minho, supported by the Foundation for Science and Technology (FCT) through the Portuguese State Budget (UIDB/01662/2020). Furthermore, Nasim Sadat Mosavi and Manuel Filipe Santos have been supported by FCT—Fundação para Ciência e Tecnologia within the R&D Units ( Algoritmi Centre University of Minho, Portugal) Project Scope: UIDB/00319/2020.Nature ResearchUniversidade do MinhoMosavi, NasimsadatRibeiro, EugéniaSampaio, AdrianaSantos, Manuel20232023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/90409engMosavi, N.S., Ribeiro, E., Sampaio, A. et al. Data mining techniques in psychotherapy: applications for studying therapeutic alliance. Sci Rep 13, 16409 (2023). https://doi.org/10.1038/s41598-023-43366-62045-232210.1038/s41598-023-43366-63777552437775524https://www.nature.com/articles/s41598-023-43366-6info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-05-11T07:02:20Zoai:repositorium.sdum.uminho.pt:1822/90409Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-11T07:02:20Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Data mining techniques in psychotherapy: applications for studying therapeutic alliance
title Data mining techniques in psychotherapy: applications for studying therapeutic alliance
spellingShingle Data mining techniques in psychotherapy: applications for studying therapeutic alliance
Mosavi, Nasimsadat
Ciências Sociais::Psicologia
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
title_short Data mining techniques in psychotherapy: applications for studying therapeutic alliance
title_full Data mining techniques in psychotherapy: applications for studying therapeutic alliance
title_fullStr Data mining techniques in psychotherapy: applications for studying therapeutic alliance
title_full_unstemmed Data mining techniques in psychotherapy: applications for studying therapeutic alliance
title_sort Data mining techniques in psychotherapy: applications for studying therapeutic alliance
author Mosavi, Nasimsadat
author_facet Mosavi, Nasimsadat
Ribeiro, Eugénia
Sampaio, Adriana
Santos, Manuel
author_role author
author2 Ribeiro, Eugénia
Sampaio, Adriana
Santos, Manuel
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Mosavi, Nasimsadat
Ribeiro, Eugénia
Sampaio, Adriana
Santos, Manuel
dc.subject.por.fl_str_mv Ciências Sociais::Psicologia
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
topic Ciências Sociais::Psicologia
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
description Data has been uploaded to the public repository; Kaggle. @misc{nasim sadat mosavi_2023, title={therapeutic alliance_ clients and therapists}, url={https://www.kaggle.com/dsv/6168984}, DOI={10.34740/KAGGLE/ DSV/6168984}, publisher={Kaggle}, author={Nasim Sadat Mosavi}, year={2023}}.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/1822/90409
url https://hdl.handle.net/1822/90409
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Mosavi, N.S., Ribeiro, E., Sampaio, A. et al. Data mining techniques in psychotherapy: applications for studying therapeutic alliance. Sci Rep 13, 16409 (2023). https://doi.org/10.1038/s41598-023-43366-6
2045-2322
10.1038/s41598-023-43366-6
37775524
37775524
https://www.nature.com/articles/s41598-023-43366-6
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instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv mluisa.alvim@gmail.com
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