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Why do patients go off track? Examining potential influencing factors for being at risk of psychotherapy treatment failure
BACKGROUND: Routine outcome monitoring can support clinicians to detect patients who deteriorate [not-on-track (NOT)] early in psychotherapy. Implemented Clinical Support Tools can direct clinicians’ attention towards potential obstacles to a positive treatment outcome and provide suggestions for su...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8528765/ https://www.ncbi.nlm.nih.gov/pubmed/33089473 http://dx.doi.org/10.1007/s11136-020-02664-6 |
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author | Schilling, Viola N. L. S. Zimmermann, Dirk Rubel, Julian A. Boyle, Kaitlyn S. Lutz, Wolfgang |
author_facet | Schilling, Viola N. L. S. Zimmermann, Dirk Rubel, Julian A. Boyle, Kaitlyn S. Lutz, Wolfgang |
author_sort | Schilling, Viola N. L. S. |
collection | PubMed |
description | BACKGROUND: Routine outcome monitoring can support clinicians to detect patients who deteriorate [not-on-track (NOT)] early in psychotherapy. Implemented Clinical Support Tools can direct clinicians’ attention towards potential obstacles to a positive treatment outcome and provide suggestions for suitable interventions. However, few studies have compared NOT patients to patients showing expected progress [on-track (OT)] regarding such obstacles. This study aimed to identify domains that have predictive value for NOT trajectories and to compare OT and NOT patients regarding these domains and the items of the underlying scales. METHODS: During treatment, 413 outpatients filled in the Hopkins-Symptom-Checklist-11 (depressive and anxious symptom distress) before every therapy session as a routine outcome measure. Further, the Assessment for Signal Clients, Affective Style Questionnaire, and Outcome Questionnaire-30 were applied every fifth session. These questionnaires measure the following domains, which were investigated as potential obstacles to treatment success: risk/suicidality, therapeutic alliance, motivation, social support and life events, as well as emotion regulation. Two groups (OT and NOT patients) were formed by defining a cut-off (failure boundary) as the 90% confidence interval (upper bound) of the respective patients’ expected recovery curves. In order to differentiate group membership based on the respective problem areas, multilevel logistic regression analyses were performed. Further, OT and NOT patients were compared with regard to the domains’ and items’ cut-offs by performing Pearson chi-square tests and independent samples t-tests. RESULTS: The life events and motivation scale as well as the risk/suicidality scale proved to be significant predictors of being not-on-track. NOT patients also crossed the cut-off significantly more often on the domains risk/suicidality, social support, and life events. For both OT and NOT patients, the emotion regulation domain’s cut-off was most commonly exceeded. CONCLUSION: Life events, motivation, and risk/suicidality seem to be directly linked to treatment failure and should be further investigated for the use in clinical support tools. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11136-020-02664-6) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-8528765 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-85287652021-11-04 Why do patients go off track? Examining potential influencing factors for being at risk of psychotherapy treatment failure Schilling, Viola N. L. S. Zimmermann, Dirk Rubel, Julian A. Boyle, Kaitlyn S. Lutz, Wolfgang Qual Life Res Special Section: Feedback Tools BACKGROUND: Routine outcome monitoring can support clinicians to detect patients who deteriorate [not-on-track (NOT)] early in psychotherapy. Implemented Clinical Support Tools can direct clinicians’ attention towards potential obstacles to a positive treatment outcome and provide suggestions for suitable interventions. However, few studies have compared NOT patients to patients showing expected progress [on-track (OT)] regarding such obstacles. This study aimed to identify domains that have predictive value for NOT trajectories and to compare OT and NOT patients regarding these domains and the items of the underlying scales. METHODS: During treatment, 413 outpatients filled in the Hopkins-Symptom-Checklist-11 (depressive and anxious symptom distress) before every therapy session as a routine outcome measure. Further, the Assessment for Signal Clients, Affective Style Questionnaire, and Outcome Questionnaire-30 were applied every fifth session. These questionnaires measure the following domains, which were investigated as potential obstacles to treatment success: risk/suicidality, therapeutic alliance, motivation, social support and life events, as well as emotion regulation. Two groups (OT and NOT patients) were formed by defining a cut-off (failure boundary) as the 90% confidence interval (upper bound) of the respective patients’ expected recovery curves. In order to differentiate group membership based on the respective problem areas, multilevel logistic regression analyses were performed. Further, OT and NOT patients were compared with regard to the domains’ and items’ cut-offs by performing Pearson chi-square tests and independent samples t-tests. RESULTS: The life events and motivation scale as well as the risk/suicidality scale proved to be significant predictors of being not-on-track. NOT patients also crossed the cut-off significantly more often on the domains risk/suicidality, social support, and life events. For both OT and NOT patients, the emotion regulation domain’s cut-off was most commonly exceeded. CONCLUSION: Life events, motivation, and risk/suicidality seem to be directly linked to treatment failure and should be further investigated for the use in clinical support tools. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11136-020-02664-6) contains supplementary material, which is available to authorized users. Springer International Publishing 2020-10-21 2021 /pmc/articles/PMC8528765/ /pubmed/33089473 http://dx.doi.org/10.1007/s11136-020-02664-6 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Special Section: Feedback Tools Schilling, Viola N. L. S. Zimmermann, Dirk Rubel, Julian A. Boyle, Kaitlyn S. Lutz, Wolfgang Why do patients go off track? Examining potential influencing factors for being at risk of psychotherapy treatment failure |
title | Why do patients go off track? Examining potential influencing factors for being at risk of psychotherapy treatment failure |
title_full | Why do patients go off track? Examining potential influencing factors for being at risk of psychotherapy treatment failure |
title_fullStr | Why do patients go off track? Examining potential influencing factors for being at risk of psychotherapy treatment failure |
title_full_unstemmed | Why do patients go off track? Examining potential influencing factors for being at risk of psychotherapy treatment failure |
title_short | Why do patients go off track? Examining potential influencing factors for being at risk of psychotherapy treatment failure |
title_sort | why do patients go off track? examining potential influencing factors for being at risk of psychotherapy treatment failure |
topic | Special Section: Feedback Tools |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8528765/ https://www.ncbi.nlm.nih.gov/pubmed/33089473 http://dx.doi.org/10.1007/s11136-020-02664-6 |
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