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Perfectionism as Possible Predictor for Treatment Success: Preliminary Data From Metacognitive Training for
Nathalie Claus1,2, Jakob Scheunemann3, Sönke Arlt3
1Department of Psychology, LMU Munich, Division of Clinical Psychology and Psychological Treatment, Munich, Germany.
Objectives:
In the treatment of depression and suicidal ideation, perfectionism has emerged as a possible predictor of treatment outcome. Some data suggest that cognitive-behavioral therapy outcomes are poorer for more perfectionistic patients. However, findings so far neglect the multidimensionality of perfectionism, and research has yet to be extended to newer treatment approaches.
Methods:
The current study comprised secondary analysis of data from inpatients in treatment for depression. We administered measures of perfectionistic concerns and perfectionistic strivings as well as depression and suicidal ideation severity. Patients received 4 weeks of metacognitive training for depression and suicidal ideation (D-MCT/S) in a group setting, alongside a comprehensive inpatient treatment. Hierarchical data over time was submitted to multi-level analysis.
Results:
Perfectionistic concerns at baseline negatively predicted depressive symptoms but not suicidal ideation across time points. In exploratory analysis including perfectionistic strivings as an additional predictor, perfectionism dimensions no longer predicted depressive symptoms. A reduction of perfectionistic concerns during treatment did not predict symptoms at follow-up. However, sensitivity analyses revealed significant differences in results based on the choice of symptom control variables.
Conclusions:
These results suggest that initial perfectionistic concerns may not prevent patients with depression and suicidal ideation from benefitting from metacognitive treatment. However, the contrast to previous findings may also be explained by differing results when separating the effects of perfectionistic concerns and perfectionistic strivings, as well as the choice of symptom control measure, or limited statistical power. Limitations and avenues for future research are discussed.
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