Drawing the borderline: Predicting treatment outcomes in patients with borderline personality disorder. (October 2020)
- Record Type:
- Journal Article
- Title:
- Drawing the borderline: Predicting treatment outcomes in patients with borderline personality disorder. (October 2020)
- Main Title:
- Drawing the borderline: Predicting treatment outcomes in patients with borderline personality disorder
- Authors:
- Herzog, Philipp
Feldmann, Matthias
Voderholzer, Ulrich
Gärtner, Thomas
Armbrust, Michael
Rauh, Elisabeth
Doerr, Robert
Rief, Winfried
Brakemeier, Eva-Lotta - Abstract:
- Abstract: Background: A routinely collected big data set was analyzed to determine the effectiveness of naturalistic inpatient treatment and to identify predictors of treatment outcome and discontinuation. Methods: The sample included 878 patients with borderline personality disorder who received non-manualized dialectic behavioral therapy in a psychosomatic clinic. Effect sizes (Hedge's g) were calculated to determine effectiveness. A bootstrap-enhanced regularized regression with 91 potential predictors was used to identify stable predictors of residualized symptom- and functional change and treatment discontinuation. Results were validated in a holdout sample and repeated cross validation. Results: Effect sizes were small to medium (g = 0.28-0.51). Positive symptom-related outcome was predicted by low affect regulation skills and no previous outpatient psychotherapy. Lower age, absence of work disability, high emotional and physical role limitations and low bodily pain were associated with greater improvement in functional outcome. Higher education and comorbid recurrent depressive disorder were the main predictors of treatment completion. The predictive quality of the models varied, with the best being found for symptom-related outcome (R 2 = 18%). Conclusion: While the exploratory process of variable selection replicates previous findings, the validation results suggest that tailoring treatment to the individual patient might not be based solely on sociodemographic,Abstract: Background: A routinely collected big data set was analyzed to determine the effectiveness of naturalistic inpatient treatment and to identify predictors of treatment outcome and discontinuation. Methods: The sample included 878 patients with borderline personality disorder who received non-manualized dialectic behavioral therapy in a psychosomatic clinic. Effect sizes (Hedge's g) were calculated to determine effectiveness. A bootstrap-enhanced regularized regression with 91 potential predictors was used to identify stable predictors of residualized symptom- and functional change and treatment discontinuation. Results were validated in a holdout sample and repeated cross validation. Results: Effect sizes were small to medium (g = 0.28-0.51). Positive symptom-related outcome was predicted by low affect regulation skills and no previous outpatient psychotherapy. Lower age, absence of work disability, high emotional and physical role limitations and low bodily pain were associated with greater improvement in functional outcome. Higher education and comorbid recurrent depressive disorder were the main predictors of treatment completion. The predictive quality of the models varied, with the best being found for symptom-related outcome (R 2 = 18%). Conclusion: While the exploratory process of variable selection replicates previous findings, the validation results suggest that tailoring treatment to the individual patient might not be based solely on sociodemographic, clinical and psychological baseline data. Highlights: The naturalistic effectiveness of a DBT program for severely impaired BPD inpatients is small to moderate. Higher education and comorbid recurrent depressive disorder appear to be the main predictors of treatment completion. Lower age, absence of work disability, high perceived emotional and physical role limitations and low reported bodily pain may positively predict functioning-related change in addition to baseline functioning. The applied variable selection procedure replicates previous research findings on predictors, but its validation does not appear to be stable. The identification of stable predictors of treatment outcomes in BPD remains difficult. Tailoring DBT to individual BPD patients should therefore not only be based on demographic and clinical baseline data. … (more)
- Is Part Of:
- Behaviour research and therapy. Volume 133(2020)
- Journal:
- Behaviour research and therapy
- Issue:
- Volume 133(2020)
- Issue Display:
- Volume 133, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 133
- Issue:
- 2020
- Issue Sort Value:
- 2020-0133-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-10
- Subjects:
- Borderline personality disorder -- Effectiveness -- Predictors -- Treatment outcome -- Dropout -- Premature treatment discontinuation
Cognitive therapy -- Periodicals
Psychotherapy -- Periodicals
616.891 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00057967 ↗
http://www.elsevier.com/wps/find/journaldescription.cws_home/265/description#description ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.brat.2020.103692 ↗
- Languages:
- English
- ISSNs:
- 0005-7967
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1876.810000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 13930.xml