Cognitive and Emotional Variables Predicting Treatment Outcome of Cognitive Behavior Therapies for Patients with Medically Unexplained Symptoms: A Meta-Analysis

Lena Sarter, Philipps-University Marburg
Jens Heider, University of Koblenz-Landau
Lukas Kirchner, Philipps-University Marburg
Sandra Schenkel, Johannes Gutenburg-University Mainz
Michael Witthöft, Johannes Gutenberg-University Mainz
Winfried Rief, Philipps-University Marburg
Maria Kleinstäuber, University of Otago


Objective: Cognitive behavior therapy (CBT) is the best-evaluated psychological approach to treat patients with medically unexplained symptoms (MUS). We still need a better understanding of what characterizes patients with MUS who benefit more or less from CBT. This systematic review aimed to identify patients' cognitive-emotional characteristics predicting the outcome of CBT for MUS. Methods: A systematic literature search (PubMed, PsycINFO, Web of Science) revealed 37 eligible studies, 23 of these provided data for meta-analyses. Mean correlation coefficients between predictor variables and the outcomes (symptom intensity, physical or social-emotional functioning) were calculated using a random-effects model. Differences between syndromes of MUS were investigated with moderator analyses. Results: Meta-analyses showed that patients with a comorbid mood disorder (r = 0.32, p < .01) or anxiety disorder (r = 0.18, p < .01), symptom catastrophizing and worries (r = 0.34, p < .01), tendencies of somatosensory amplification (r = 0.46, p = .04), and low symptom acceptance or self-efficacy (r = 0.25, p < .01) have a less favorable CBT outcome. Moderator analyses revealed that these associations between predictors and treatment outcome are pronounced in patients with chronic fatigue syndrome and irritable bowel syndrome. Conclusions: Our results show that pre-treatment differences in patients' cognitive-emotional characteristics predict patients' outcome in CBT. Patient-tailored CBT could be a promising approach to address MUS patients' widely varying needs more effectively.