边际障碍五因素量表--超级简表和筛选器的开发与验证。

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-06-06 DOI:10.1177/10731911241256439
Hilary L DeShong, Courtney K Mason, Ben Porter, Kren Kelley, Stephanie N Mullins-Sweatt, Donald R Lynam, Joshua D Miller, Thomas Widiger
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引用次数: 0

摘要

边缘型人格障碍五因素量表(FFBI)和FFBI简表(FFBI-SF)分别由120个和48个项目组成,用于评估边缘型人格障碍(BPD)的潜在适应不良人格特质。本研究的目的是开发一种超级简表(FFBI-SSF)和一种 FFBI 筛选器,以方便使用针对 BPD 的维度特质测量。通过项目反应理论分析,使用大量本科生样本(N = 1300)将 48 个项目的测量结果缩减为 22 个项目,然后使用 Mechanical Turk 样本(N = 602)进行了重新测试,结果表明具有很强的可复制性。我们再次使用 IRT 将测量项目从 22 个进一步缩减为 4 个,以提供一个简短的筛查工具。在五个样本(N = 919、204、580、281 和 488)中比较了 FFBI-SSF 和筛选器与 BPD 相关变量测量的相关性。总体而言,FFBI-SSF 与 FFBI-SF 在全量表和领域水平量表上表现出相似的关系,而 FFBI 筛选器在全量表水平上表现出相似的关系。这种超级简表和筛选器最适合用于大规模研究或作为临床筛查工具的一部分。
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Development and Validation of the Five-Factor Borderline Inventory-Super Short Form and Screener.

The Five-Factor Borderline Inventory (FFBI) and FFBI-Short Form (FFBI-SF) are 120-item and 48-item measures that assess the underlying maladaptive personality traits of borderline personality disorder (BPD). The purpose of this study was to develop a super short form (FFBI-SSF) and an FFBI-Screener to facilitate the use of dimensional trait measures for BPD. Using item response theory analyses, the 48-item measure was reduced to 22 items using a large undergraduate sample (N = 1300) and then retested using a Mechanical Turk sample (N = 602), demonstrating strong replicability. IRT was again used to further reduce the measure from 22 items to four items to provide a brief screening tool. Correlations of the FFBI-SSF and Screener with measures of BPD-related variables were compared across five samples (N = 919, 204, 580, 281, and 488). Overall, the FFBI-SSF showed similar relations to the FFBI-SF at the full scale and domain-level scales, while the FFBI-screener demonstrated similar relations at the full scale level. This super short form and screener may best be used in large-scale research studies or as part of a screening tool in clinical settings.

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4.30%
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