[Predictive power on therapy engagement in personality disorders: SWAP- 200 versus SCID-II].

Area of Science:

• Psychiatry
• Clinical Psychology
• Psychotherapy Research

Background:

• Accurate patient assessment is crucial for predicting engagement in long-term psychotherapy.
• Personality disorders present unique challenges in treatment adherence and outcome prediction.
• Comparing diagnostic instruments aids in selecting optimal assessment tools for clinical practice.

Purpose of the Study:

• To compare the predictive validity of the Shedler-Westen-Assessment Procedure-200 (SWAP-200) and the Structured Clinical Interview for DSM-IV (SCID) for psychotherapy engagement.
• To identify specific diagnostic features that predict treatment dropout in patients with personality disorders.
• To evaluate the clinical utility of SWAP-200 and SCID in a 4-year follow-up study.

Main Methods:

• A cohort of 297 patients diagnosed with personality disorders was assessed using SWAP-200 and SCID.
• Multinomial logistic regression analysis was employed to compare prediction rates.
• Cross-validation techniques were used to ensure the robustness of the findings.
• A 4-year follow-up period was utilized to track patient engagement in psychoanalytic psychotherapy.

Main Results:

• Small differences were observed in the prediction rates between the SWAP-200 and SCID in cross-validated data.
• Both instruments demonstrated clinically significant prediction rates for identifying treatment rejecters.
• SWAP-200 identified dysphoric traits as semi-stable predictors of rejection.
• SCID identified Negativistic, Depressive, and Schizotypal personality disorder traits as stable predictors of rejection.

Conclusions:

• The SWAP-200 and SCID offer valuable, albeit slightly different, predictive insights into psychotherapy engagement for personality disorder patients.
• The SWAP-200's comprehensive assessment, including affect, defense, and object relations, provides unique predictive information.
• Clinicians can leverage findings from both instruments to better anticipate and manage treatment dropout risk.