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Should I stay or must I go? Predictors of dropout in an internet-based psychotherapy programme for posttraumatic stress disorder in Arabic

Background: Dropout from psychotherapy has negative impacts on clients, therapists, and health-care agencies. Research has identified a variety of variables as predictors of dropout, which can be grouped in three domains: socio-demographic, psychological, and treatment-related variables. Objective:...

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Autores principales: Vöhringer, Max, Knaevelsrud, Christine, Wagner, Birgit, Slotta, Martin, Schmidt, Anne, Stammel, Nadine, Böttche, Maria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7006804/
https://www.ncbi.nlm.nih.gov/pubmed/32082510
http://dx.doi.org/10.1080/20008198.2019.1706297
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author Vöhringer, Max
Knaevelsrud, Christine
Wagner, Birgit
Slotta, Martin
Schmidt, Anne
Stammel, Nadine
Böttche, Maria
author_facet Vöhringer, Max
Knaevelsrud, Christine
Wagner, Birgit
Slotta, Martin
Schmidt, Anne
Stammel, Nadine
Böttche, Maria
author_sort Vöhringer, Max
collection PubMed
description Background: Dropout from psychotherapy has negative impacts on clients, therapists, and health-care agencies. Research has identified a variety of variables as predictors of dropout, which can be grouped in three domains: socio-demographic, psychological, and treatment-related variables. Objective: In order to further clarify the question of predictors of dropout, an exploratory research design was applied to a large sample, testing 25 different variables from the three domains as possible predictors. Method: The sample included 386 adults who started an internet-based cognitive-behavioural treatment approach for posttraumatic stress disorder (PTSD) in Arabic. As the participants had different countries of origin and of current residence, multilevel analyses were performed. For the selection of predictor variables, the Least Absolute Shrinkage and Selection Operator was used. Results: Dropout rates did not vary significantly between participants from different countries of origin or from different countries of residence. Likewise, dropout did not vary significantly between clusters of individuals with the same country of origin and the same country of residence, i.e. the same migration path. Three of the 25 variables were identified as significant predictors for dropout: marital status (divorced participants’ probability to drop out was higher compared to non-divorced, i.e. single, married, or widowed, clients), treatment credibility scores (higher dropout probability of participants with lower treatment credibility), and the participants’ year of registration for the treatment (earlier years of registration predicted lower dropout probability). The overall ability of the three-factor-model to discriminate between dropout and completion was poor (AUC = 0.652, with low sensitivity and acceptable specificity). Conclusions: The predictors belong to the treatment-related domain (credibility, year of registration) or are specific to the target group (marital status). However, the results show that predicting treatment dropout continues to be a very challenging endeavour and indicate that it is important to look at each intervention individually.
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spelling pubmed-70068042020-02-20 Should I stay or must I go? Predictors of dropout in an internet-based psychotherapy programme for posttraumatic stress disorder in Arabic Vöhringer, Max Knaevelsrud, Christine Wagner, Birgit Slotta, Martin Schmidt, Anne Stammel, Nadine Böttche, Maria Eur J Psychotraumatol Clinical Research Article Background: Dropout from psychotherapy has negative impacts on clients, therapists, and health-care agencies. Research has identified a variety of variables as predictors of dropout, which can be grouped in three domains: socio-demographic, psychological, and treatment-related variables. Objective: In order to further clarify the question of predictors of dropout, an exploratory research design was applied to a large sample, testing 25 different variables from the three domains as possible predictors. Method: The sample included 386 adults who started an internet-based cognitive-behavioural treatment approach for posttraumatic stress disorder (PTSD) in Arabic. As the participants had different countries of origin and of current residence, multilevel analyses were performed. For the selection of predictor variables, the Least Absolute Shrinkage and Selection Operator was used. Results: Dropout rates did not vary significantly between participants from different countries of origin or from different countries of residence. Likewise, dropout did not vary significantly between clusters of individuals with the same country of origin and the same country of residence, i.e. the same migration path. Three of the 25 variables were identified as significant predictors for dropout: marital status (divorced participants’ probability to drop out was higher compared to non-divorced, i.e. single, married, or widowed, clients), treatment credibility scores (higher dropout probability of participants with lower treatment credibility), and the participants’ year of registration for the treatment (earlier years of registration predicted lower dropout probability). The overall ability of the three-factor-model to discriminate between dropout and completion was poor (AUC = 0.652, with low sensitivity and acceptable specificity). Conclusions: The predictors belong to the treatment-related domain (credibility, year of registration) or are specific to the target group (marital status). However, the results show that predicting treatment dropout continues to be a very challenging endeavour and indicate that it is important to look at each intervention individually. Taylor & Francis 2020-01-23 /pmc/articles/PMC7006804/ /pubmed/32082510 http://dx.doi.org/10.1080/20008198.2019.1706297 Text en © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Clinical Research Article
Vöhringer, Max
Knaevelsrud, Christine
Wagner, Birgit
Slotta, Martin
Schmidt, Anne
Stammel, Nadine
Böttche, Maria
Should I stay or must I go? Predictors of dropout in an internet-based psychotherapy programme for posttraumatic stress disorder in Arabic
title Should I stay or must I go? Predictors of dropout in an internet-based psychotherapy programme for posttraumatic stress disorder in Arabic
title_full Should I stay or must I go? Predictors of dropout in an internet-based psychotherapy programme for posttraumatic stress disorder in Arabic
title_fullStr Should I stay or must I go? Predictors of dropout in an internet-based psychotherapy programme for posttraumatic stress disorder in Arabic
title_full_unstemmed Should I stay or must I go? Predictors of dropout in an internet-based psychotherapy programme for posttraumatic stress disorder in Arabic
title_short Should I stay or must I go? Predictors of dropout in an internet-based psychotherapy programme for posttraumatic stress disorder in Arabic
title_sort should i stay or must i go? predictors of dropout in an internet-based psychotherapy programme for posttraumatic stress disorder in arabic
topic Clinical Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7006804/
https://www.ncbi.nlm.nih.gov/pubmed/32082510
http://dx.doi.org/10.1080/20008198.2019.1706297
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