Post-Graduate Program in Medical Sciences, School of Medicine, Universidade Federal do Rio Grande do Sul (UFRGS), Brazil.
J Psychosom Res. 2010 Mar;68(3):223-33. doi: 10.1016/j.jpsychores.2009.09.013. Epub 2009 Dec 9.
This study evaluates the State-Trait Anxiety Inventory (STAI) structure using a Rasch psychometric approach, and a refined and shorter STAI version is proposed.
A cross-sectional study was performed with 900 inpatients scheduled for elective surgery. Age varied from 18 to 60 years (American Society of Anesthesiologists physical status I-III). Demographic information was collected using a structured questionnaire. The measuring instrument (the STAI) was applied to all patients in the afternoon before the surgery and prior to the patients receiving preoperative sedatives.
Rasch analysis of the state and trait anxiety scales was performed separately. This analysis demonstrated that the original format of state and trait scales fails to show invariance across the trait-state anxiety level, which results in the unstable performance of items. The refined scale was retested in two subsequent random samples of 300 subjects each, and the results were confirmed. The performance was adequate regardless of gender. In the analysis, some items of the state scale (items 3,4,9,10,12,15, and 20) were deleted due to poor fit statistics. The remaining 13 items showed unidimensionality, local independence, and adequate index of internal consistency. Also, the original trait scale displayed several weaknesses. First, the four-point Likert response scale proved to be inadequate, and threshold disorders were found in all 20 items. Also, the original trait scale showed insufficient item-trait interaction and several individual item misfits. Following the rescoring process, and retesting in a second random sample, items were excluded (namely Items 3, 4, 11, 13, 14, 15, 18, and 19). The refined version showed local independence, unidimensionality, and adequate fit statistics.
The results indicate that the application of the Rasch model led to the refinement of the classic STAI state and trait scales. In addition, they suggest that these shorter versions have a more suitable psychometric performance and are free of threshold disorders and differential item functioning problems.
本研究采用 Rasch 心理计量学方法评估状态-特质焦虑量表(STAI)的结构,并提出一种经过改进且更简短的 STAI 版本。
这是一项横断面研究,共纳入 900 名择期手术的住院患者。年龄为 18-60 岁(美国麻醉医师协会身体状况 I-III 级)。采用结构化问卷收集人口统计学信息。所有患者均于手术前下午、接受术前镇静前使用 STAI 进行测量。
分别对状态和特质焦虑量表进行 Rasch 分析。该分析表明,状态和特质量表的原始格式无法在特质-状态焦虑水平上表现出不变性,从而导致项目表现不稳定。随后在另外两个各 300 名受试者的随机样本中重新测试了改进后的量表,结果得到了验证。无论性别如何,量表表现均良好。在分析中,由于拟合统计数据较差,状态量表的一些项目(项目 3、4、9、10、12、15 和 20)被删除。剩余的 13 个项目表现出单维性、局部独立性和足够的内部一致性指数。此外,原始特质量表也存在一些弱点。首先,四点 Likert 反应量表被证明是不充分的,并且在所有 20 个项目中都发现了阈限障碍。此外,原始特质量表显示出不足的项目-特质相互作用和几个单独项目不匹配。经过重新评分过程并在第二个随机样本中重新测试后,排除了一些项目(即项目 3、4、11、13、14、15、18 和 19)。改进后的版本显示出局部独立性、单维性和适当的拟合统计数据。
结果表明,Rasch 模型的应用导致了经典 STAI 状态和特质量表的改进。此外,它们表明这些更简短的版本具有更合适的心理计量学性能,并且没有阈限障碍和差异项目功能问题。