Department of Psychology, University of New Brunswick.
Department of Psychology, St. Francis Xavier University.
Personal Disord. 2023 Sep;14(5):579-583. doi: 10.1037/per0000627. Epub 2023 May 18.
Treatment dropout is high among outpatients with borderline personality disorder (BPD) and is associated with myriad negative therapeutic and psychosocial outcomes. Identifying predictors of treatment dropout can inform treatment provision for this population. The present study investigated whether symptom profiles of static and dynamic factors could predict treatment dropout. Treatment-seeking outpatients with BPD ( = 102) completed pre-treatment measures of BPD symptom severity, emotion dysregulation, impulsivity, motivation, self-harm, and attachment style to determine their collective impact on dropout prior to 6 months of treatment. Discriminant function analysis was used to classify group membership (treatment dropout vs. nondropout) but did not produce a statistically significant function. Groups were distinguished by baseline levels of emotion dysregulation with higher dysregulation predicting premature treatment dropout. Clinicians working with outpatients with BPD might benefit from optimizing emotion regulation and distress tolerance strategies earlier in treatment to reduce premature dropout. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
治疗脱落率在边缘型人格障碍(BPD)门诊患者中较高,与众多负面治疗和心理社会结果相关。识别治疗脱落的预测因素可以为该人群的治疗提供信息。本研究调查了静态和动态因素的症状特征是否可以预测治疗脱落。寻求治疗的 BPD 门诊患者(n=102)在治疗前完成了 BPD 症状严重程度、情绪调节、冲动、动机、自残和依恋风格的测量,以确定它们在 6 个月治疗前对脱落的综合影响。判别函数分析用于对组别的归属(治疗脱落与非脱落)进行分类,但没有产生统计学上显著的函数。通过情绪调节的基线水平来区分组别的归属,情绪调节越高,预示着治疗过早脱落。与 BPD 门诊患者合作的临床医生可能会受益于在治疗早期优化情绪调节和压力耐受策略,以减少过早脱落。(PsycInfo 数据库记录(c)2023 APA,保留所有权利)。