Suppr超能文献

运用 Rasch 分析开发并验证 6 项修订版加州大学洛杉矶分校孤独量表(RULS-6)。

Development and validation of a 6-item Revised UCLA Loneliness Scale (RULS-6) using Rasch analysis.

机构信息

Department of Psychiatry, Faculty of Medicine, Chiang Mai University, Thailand.

Jittavej Nakhon Sawan Ratchanakarin Hospital, Nakhon Sawan, Thailand.

出版信息

Br J Health Psychol. 2020 May;25(2):233-256. doi: 10.1111/bjhp.12404. Epub 2020 Jan 30.

Abstract

OBJECTIVE

The UCLA Loneliness Scale, containing 20 items, is one of the commonly used loneliness scales. Some shorter versions have been developed using factor analysis. The study aimed to shorten the UCLA Loneliness Scale using Rasch and factor analysis methods and test the psychometric properties of the new scale.

METHODS

The full sample of the study included 719 respondents, divided into three subsamples (205, 324, and 190 for samples 1-3, respectively). The original, 20-item Revised UCLA Loneliness Scale (R-ULS) was shortened using 205 students (sample 1); the shortened scale was then validated for construct and concurrent validity with 324 students (sample 2) and 190 clinical participants (sample 3). Confirmatory factor analysis and Rasch analysis were used for construct validity. Convergent, discriminant, and concurrent validity were assessed by exploring the correlation with other psychological measurements.

RESULTS

In sample 1, the R-ULS was shortened to a 6-item scale (RULS-6) that fits the Rasch model. The RULS-6 met the criteria of unidimensionality and local independence without differential item functioning due to age and sex, and good targeting the clinical sample. Person Separation Index (PSI) reflected that reliability from the Rasch perspective was acceptable. However, collapsing categories 2 (sometime) and 3 (rarely) may be required in a clinical sample. When tested in samples 2 and 3, the RULS-6 fits the Rasch measurement model. Convergent and discriminant validity were demonstrated with interpersonal problems and attachment scales. As expected, a positive correlation was found between RULS-6 and anxiety, depression subscale, interpersonal difficulties, and somatization subscales denoting concurrent validity. Cronbach's alpha of the RULS-6 was good (.83).

CONCLUSION

Using Rasch analysis, the proposed RULS-6 constituted a 70% reduction of the number of original items, yet preserved the psychometric properties in independent samples of students and psychiatric outpatients. Statement of contribution What is already known on this subject? The UCLA Loneliness Scale is a common instrument used to gauge loneliness levels. The 20-item revised scale (R-ULS) has acceptable psychometric properties but its construct varies. Due to the length of the questionnaire, administration of R-ULS is not always practical. Short versions vary in items and were developed with classic test theory (e.g., factor analysis). Rasch analysis - providing more accuracy based on measurement theory - could be used instead. What does this study add? Using a Rasch analysis approach, a 6-item scale of loneliness (RULS-6) was created. The RULS-6 was tested in student and clinical samples, meeting Rasch measurement model criteria. The RULS-6 showed promising psychometrics to be used in both non-clinical and clinical samples.

摘要

目的

UCLA 孤独量表包含 20 个项目,是常用的孤独量表之一。一些更短的版本已经通过因子分析开发出来。本研究旨在使用 Rasch 和因子分析方法缩短 UCLA 孤独量表,并测试新量表的心理测量特性。

方法

研究的全样本包括 719 名受访者,分为三个子样本(样本 1 为 205 名,样本 2 为 324 名,样本 3 为 190 名)。使用 205 名学生(样本 1)缩短原始的 20 项修订 UCLA 孤独量表(R-ULS);然后使用 324 名学生(样本 2)和 190 名临床参与者(样本 3)验证构建效度和同时效度。采用验证性因子分析和 Rasch 分析进行结构效度验证。通过探索与其他心理测量的相关性来评估收敛、区分和同时效度。

结果

在样本 1 中,R-ULS 缩短为 6 项量表(RULS-6),符合 Rasch 模型。RULS-6 满足单维性和局部独立性的标准,不受年龄和性别的差异项目功能影响,并且很好地针对临床样本。个体分离指数(PSI)反映了从 Rasch 角度来看可靠性是可以接受的。然而,在临床样本中可能需要将类别 2(有时)和 3(很少)合并。在样本 2 和 3 中进行测试时,RULS-6 符合 Rasch 测量模型。与人际问题和依恋量表一起证明了收敛和区分效度。正如预期的那样,RULS-6 与焦虑、抑郁亚量表、人际困难和躯体化亚量表呈正相关,表明具有同时效度。RULS-6 的 Cronbach's alpha 为 0.83,信度良好。

结论

使用 Rasch 分析,建议的 RULS-6 将原始项目数量减少了 70%,但在学生和精神病门诊患者的独立样本中保留了心理测量特性。

关于这个主题已经知道些什么?

UCLA 孤独量表是一种常用的衡量孤独水平的工具。经过修订的 20 项量表(R-ULS)具有可接受的心理测量特性,但它的结构有所不同。由于问卷的长度,R-ULS 的管理并不总是实际可行的。不同的简短版本在项目上有所不同,并且是使用经典测试理论(例如,因子分析)开发的。基于测量理论的 Rasch 分析可以替代经典测试理论。

这项研究有什么新发现?

使用 Rasch 分析方法,创建了一个 6 项孤独量表(RULS-6)。RULS-6 在学生和临床样本中进行了测试,符合 Rasch 测量模型标准。RULS-6 在非临床和临床样本中都具有有前途的心理测量特性。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验