Inpatient psychotherapy for depression in a large routine clinical care sample: A Bayesian approach to examining clinical outcomes and predictors of change

Philipp Herzog; Matthias Feldmann; Tobias Kube; Gernot Langs; Thomas Gärtner; Elisabeth Rauh; Robert Doerr; Andreas Hillert; Ulrich Voderholzer; Winfried Rief; Dominik Endres; Eva-Lotta Brakemeier

doi:10.1016/j.jad.2022.02.057

Inpatient psychotherapy for depression in a large routine clinical care sample: A Bayesian approach to examining clinical outcomes and predictors of change

J Affect Disord. 2022 May 15:305:133-143. doi: 10.1016/j.jad.2022.02.057. Epub 2022 Feb 25.

Authors

Affiliations

¹ Philipps-University of Marburg, Department of Clinical Psychology and Psychotherapy, Gutenbergstraße 18, D-35032 Marburg, Germany; University of Greifswald, Department of Clinical Psychology and Psychotherapy, Franz-Mehring-Straße 47, D-17489 Greifswald, Germany; University of Koblenz-Landau, Department of Clinical Psychology and Psychotherapy, Ostbahnstraße 10, D-76829 Landau, Germany. Electronic address: herzog@uni-landau.de.
² Philipps-University of Marburg, Department of Clinical Psychology and Psychotherapy, Gutenbergstraße 18, D-35032 Marburg, Germany.
³ Philipps-University of Marburg, Department of Clinical Psychology and Psychotherapy, Gutenbergstraße 18, D-35032 Marburg, Germany; University of Koblenz-Landau, Department of Clinical Psychology and Psychotherapy, Ostbahnstraße 10, D-76829 Landau, Germany.
⁴ Schön-Klinik Bad Bramstedt, Psychosomatic Clinic, Birkenweg 10, D-24576 Bad Bramstedt, Germany.
⁵ Schön-Klinik Bad Arolsen, Psychosomatic Clinic, Hofgarten 10, D-34454 Bad Arolsen, Germany.
⁶ Schön-Klinik Bad Staffelstein, Psychsomatic Clinic, Am Kurpark 11, D-96231 Bad Staffelstein, Germany.
⁷ Schön-Klinik Berchtesgadener Land, Psychosomatic Clinic, Malterhöh 1, D-83471 Schönau am Königssee, Germany.
⁸ Schön-Klinik Roseneck, Psychosomatic Clinic, Am Roseneck 6, D-83209 Prien am Chiemsee, Germany.
⁹ Schön-Klinik Roseneck, Psychosomatic Clinic, Am Roseneck 6, D-83209 Prien am Chiemsee, Germany; University Hospital of Munich, Department of Psychiatry and Psychotherapy, Nußbaumstraße 7, D-80336 München, Germany.
¹⁰ Philipps-University of Marburg, Department of Theoretical Neuroscience, Gutenbergstraße 18, D-35032 Marburg, Germany.
¹¹ Philipps-University of Marburg, Department of Clinical Psychology and Psychotherapy, Gutenbergstraße 18, D-35032 Marburg, Germany; University of Greifswald, Department of Clinical Psychology and Psychotherapy, Franz-Mehring-Straße 47, D-17489 Greifswald, Germany.

PMID: 35219740
DOI: 10.1016/j.jad.2022.02.057

Abstract

Background: A routinely collected dataset was analyzed (1) to determine the naturalistic effectiveness of inpatient psychotherapy for depression in routine psychotherapeutic care, and (2) to identify potential predictors of change.

Methods: In a sample of 22,681 inpatients with depression, pre-post and pre-follow-up effect sizes were computed for various outcome variables. To build a probabilistic model of predictors of change, an independent component analysis generated components from demographic and clinical data, and Bayesian EFA extracted factors from the available pre-test, post-test and follow-up questionnaires in a subsample (N = 6377). To select the best-fitted model, the BIC of different path models were compared. A Bayesian path analysis was performed to identify the most important factors to predict changes.

Results: Effect sizes were large for the primary outcome and moderate for various secondary outcomes. Almost all pretreatment factors exerted significant influences on different baseline factors. Several factors were found to be resistant to change during treatment: suicidality, agoraphobia, life dissatisfaction, physical disability and pain. The strongest cross-loadings were observed from suicidality on negative cognitions, from agoraphobia on anxiety, and from physical disability on perceived disability.

Limitations: No causal conclusions can be drawn directly from our results as we only used cross-lagged panel data without control group.

Conclusions: The results indicate large effects of inpatient psychotherapy for depression in routine clinical care. The direct influence of pretreatment factors decreased over the course of treatment. However, some factors appeared stable and difficult to treat, which might hinder treatment outcome. Findings of different predictors of change are discussed.

Keywords: Depression; Effectiveness; Prediction; Predictors of change; Routine clinical care.

MeSH terms

Anxiety Disorders
Bayes Theorem
Depression* / therapy
Humans
Inpatients*
Psychotherapy / methods
Treatment Outcome