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Using the Minnesota Multiphasic Personality Inventory–2 Restructured Form to Predict Functioning After Treatment for Borderline Personality Disorder: A Machine Learning Approach.

Insight into predictors of functioning after treatment for borderline personality disorder (BPD) is limited, despite growing recognition that more focus on other aspects of recovery, especially psychosocial functioning, is warranted. The present study explored the utility of a widely used omnibus as...

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Publicado en:Psychological Assessment Vol. 37; no. 6/7; pp. 261 - 273
Autores principales: Wibbelink, Carlijn J. M., Sellbom, Martin, Grasman, Raoul P. P. P., Arntz, Arnoud, Sinnaeve, Roland, Kamphuis, Jan H.
Formato: Artículo
Publicado: American Psychological Association Jul2025
Materias:
Treatment of borderline personality disorder
Borderline personality disorder
Psychological tests
Psychosocial factors
Risk assessment
Random forest algorithms
Treatment effectiveness
Descriptive statistics
Dialectical behavior therapy
Schema therapy
Machine learning
Psychosocial functioning
Predictive validity
Evaluation
Acceso en línea:Ver este registro en EBSCOhost