Why do patients go off track? Examining potential influencing factors for being at risk of psychotherapy treatment failure.

Autor: Schilling VNLS; Department of Psychology, Clinical Psychology and Psychotherapy, University of Trier, 54286, Trier, Germany. viola.schilling@uni-trier.d., Zimmermann D; Department of Psychology, Clinical Psychology and Psychotherapy, University of Trier, 54286, Trier, Germany., Rubel JA; Justus-Liebig-University Giessen, Giessen, Germany., Boyle KS; Department of Psychology, Clinical Psychology and Psychotherapy, University of Trier, 54286, Trier, Germany., Lutz W; Department of Psychology, Clinical Psychology and Psychotherapy, University of Trier, 54286, Trier, Germany.
Jazyk: angličtina
Zdroj: Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation [Qual Life Res] 2021 Nov; Vol. 30 (11), pp. 3287-3298. Date of Electronic Publication: 2020 Oct 21.
DOI: 10.1007/s11136-020-02664-6
Abstrakt: 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.
(© 2020. The Author(s).)
Databáze: MEDLINE
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