The rapidly expanding self-compassion research is driven mainly by Neff's (2003a, 2003b, 2023) six-factor Self-Compassion Scale (SCS). Despite broad agreement on its six-first-order factor structure, there is much debate on SCS's global structure (one- vs. two-global factors). Neff et al. (2019) argue for an exploratory structural equation model (ESEM) with six specific and one global bifactor (6ESEM + 1GlbBF) rather than two global factors (6ESEM + 2GlbBF). However, ESEM's methodological limitations precluded testing the appropriate 6ESEM + 2GlbBF, relying instead on a model combining ESEM and traditional confirmatory factor analysis (6ESEM + 2CFA). Although intuitively reasonable, this alternative model results in internally inconsistent, illogical interpretations. Instead, we apply recent advances in Bayesian SEM frameworks and Bayes structural equation models fit indices to test a more appropriate bifactor model with two global factors. This model (as does 6CFA + 2GlbBF) fits the data well, and correlations between compassionate self-responding (CS) and reverse-scored uncompassionate self-responding (RUS) factors (∼.6) are much less than the 1.0 correlation implied by a single bipolar factor. We discuss the critical implications for theory, scoring, and clinical application for the SCS that previously were inappropriately based on this now-discredited 6ESEM + 2GlbCFA. In applied practice, we endorse using scores representing the six SCS factors, total SCS, and CS and RUS components rather than relying solely on one global factor. Our approach to these issues (dimensionality, factor structure, first-order and higher order models, positive vs. negatively oriented constructs, item-wording effects, and alternative estimation procedures) has wide applicability to clinical measurement (see our annotated bibliography of 20 instruments that might benefit from our approach). (PsycInfo Database Record (c) 2023 APA, all rights reserved).

中文翻译：

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自我慈悲量表的双因素结构：克服探索性结构方程模型 (ESEM) 局限性的贝叶斯方法。

快速扩展的自我慈悲研究主要是由 Neff (2003a, 2003b, 2023) 的六因素自我慈悲量表 (SCS) 推动的。尽管人们对其六一阶因子结构达成了广泛共识，但对 SCS 的全局结构（一与二全局因子）仍存在很多争议。内夫等人。（2019）主张探索性结构方程模型（ESEM）具有六个特定双因子和一个全局双因子（6ESEM + 1GlbBF），而不是两个全局因子（6ESEM + 2GlbBF）。然而，ESEM 的方法学限制无法测试适当的 6ESEM + 2GlbBF，而是依赖于 ESEM 和传统验证性因素分析相结合的模型 (6ESEM + 2CFA)。尽管直观上合理，但这种替代模型会导致内部不一致、不合逻辑的解释。相反，我们应用贝叶斯 SEM 框架和贝叶斯结构方程模型拟合指数的最新进展来测试具有两个全局因子的更合适的双因子模型。该模型（6CFA + 2GlbBF 也是如此）很好地拟合了数据，并且富有同情心的自我反应 (CS) 和反向评分的无同情心的自我反应 (RUS) 因素 (∼.6) 之间的相关性远小于由单一双极性因素。我们讨论了 SCS 的理论、评分和临床应用的关键含义，这些含义以前不恰当地基于现在已不可信的 6ESEM + 2GlbCFA。在应用实践中，我们赞同使用代表六个 SCS 因素、总 SCS 以及 CS 和 RUS 组成部分的分数，而不是仅仅依赖于一项全局因素。我们解决这些问题的方法（维度、因子结构、一阶和高阶模型、正向与负向结构、项目措辞效应和替代估计程序）具有广泛的适用性到临床测量（参见我们带注释的 20 种仪器的参考书目）这可能会受益于我们的方法）。（PsycInfo 数据库记录 (c) 2023 APA，保留所有权利）。