{"title":"Analyzing the Factor Structure and Sleep Quality of Pittsburgh Sleep Quality Index in Indian Information Technology Sector","authors":"Arindam Chatterjee, Rimu Chaudhuri, Arijit Dutta","doi":"10.1101/2024.07.25.24308199","DOIUrl":null,"url":null,"abstract":"The Pittsburgh Sleep Quality Index (PSQI) has gained widespread acceptance as a useful tool to measure sleep quality. In order to formulate the diagnosis process, it is essential that we understand the factor structure inherent in the PSQI data. In this work, we seek to estimate such a structure with a focus on the Indian Information Technology (IT) workers. We have used Confirmatory Factor Analysis (CFA) and the Exploratory Factor Analysis (EFA) for this purpose. We have also used the Multi layer perceptron based method to see how we can classify the sleep quality of the sampled population. We have discovered that, contrary to the general perception, most Indian IT employees have sleep quality belonging to good and very good classes.","PeriodicalId":501454,"journal":{"name":"medRxiv - Health Informatics","volume":"125 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Health Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.07.25.24308199","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The Pittsburgh Sleep Quality Index (PSQI) has gained widespread acceptance as a useful tool to measure sleep quality. In order to formulate the diagnosis process, it is essential that we understand the factor structure inherent in the PSQI data. In this work, we seek to estimate such a structure with a focus on the Indian Information Technology (IT) workers. We have used Confirmatory Factor Analysis (CFA) and the Exploratory Factor Analysis (EFA) for this purpose. We have also used the Multi layer perceptron based method to see how we can classify the sleep quality of the sampled population. We have discovered that, contrary to the general perception, most Indian IT employees have sleep quality belonging to good and very good classes.
匹兹堡睡眠质量指数(PSQI)作为测量睡眠质量的有效工具已被广泛接受。为了制定诊断程序,我们必须了解 PSQI 数据的内在因素结构。在这项工作中,我们试图以印度信息技术(IT)工作者为重点,对这种结构进行估计。为此,我们使用了确认性因子分析(CFA)和探索性因子分析(EFA)。我们还使用了基于多层感知器的方法来了解如何对抽样人群的睡眠质量进行分类。我们发现,与一般看法相反,大多数印度 IT 员工的睡眠质量属于良好和非常好的级别。