Hameed Unaise A, Al-Jarrah Muhammed D, Manzar Md Dilshad, Nair Chithira, Albougami Abdulrhman, Alrasheadi Bader A, Noohu Majumi M, Salahuddin Mohammed
Department of Physiotherapy, Fatima College of Health Sciences, Abu-Dhabi, United Arab Emirates. E-mail.
Saudi Med J. 2020 Jul;41(7):746-752. doi: 10.15537/smj.2020.7.25146.
To analyze the fit of different competing factor models (a one-factor model, 3 2-factor models, and 2 4-factor models) of the Leeds sleep evaluation questionnaire (LSEQ) in the data from a Jordanian student population.
A cross-sectional study was conducted on university students, with 2 sleep-related tools - the LSEQ and the sleep hygiene index (SHI). The students (n=166) at Jordan University of Science and Technology, Irbid, Jordan participated in this study from January-April, 2019. A total of 12 LSEQ models (6 models with all 10-items, and 6 models with one item deleted) were evaluated by using confirmatory factor analysis. The summary statistics of correlation coefficients, descriptive measures of item analysis, the model fit, and Cronbach's alpha were determined.
The findings show that a 4-factor correlated solution was a plausible model for the LSEQ with 9-items, compared to a one-factor, 2-factor, and other 4-factor variant models. The deletion of one item from the original LSEQ improved the data fit significantly in the studied population. Moreover, correlation analysis between the LSEQ and SHI confirmed the divergent validity of the LSEQ.
The results support the validity of a 4-factor structure of the LSEQ with 9-items with adequate internal consistency and divergent validity.
分析利兹睡眠评估问卷（LSEQ）的不同竞争因子模型（一个单因子模型、3个双因子模型和2个四因子模型）在约旦学生群体数据中的拟合情况。
对大学生进行了一项横断面研究，使用了2种与睡眠相关的工具——LSEQ和睡眠卫生指数（SHI）。约旦伊尔比德的约旦科技大学的学生（n = 166）于2019年1月至4月参与了本研究。使用验证性因子分析对总共12个LSEQ模型（6个包含所有10个条目的模型和6个删除了一个条目的模型）进行了评估。确定了相关系数的汇总统计量、条目分析的描述性指标、模型拟合度和克朗巴哈α系数。
研究结果表明，与单因子、双因子和其他四因子变体模型相比，一个包含9个条目的四因子相关模型是LSEQ的一个合理模型。从原始LSEQ中删除一个条目可显著改善所研究群体的数据拟合度。此外，LSEQ与SHI之间的相关性分析证实了LSEQ的区分效度。
结果支持了一个包含9个条目的LSEQ四因子结构的有效性，该结构具有足够的内部一致性和区分效度。
