文章基本信息

标题：Development and Standardization of the Gratitude Scale
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作者：Mohammad Anas, Akbar Husain Shah Mohd. Khan, Asiya Aijaz
期刊名称：Journal of Educational, Health and Community Psychology
印刷版ISSN：2088-3129
出版年度：2016
卷号：5
期号：3
页码：1-14
语种：English
出版社：Universitas Ahmad Dahlan
摘要：Abstract The Gratitude Scale (GS) developed by the authors was administered to 456 adults to determine the psychometric characteristics i.e. reliability and validity. Cronbach’s Alpha of the scale was found 0.91. Content validity of the scale was verified by some experts, academicians, and professionals. For testing multicollinearity and singularity ‘Determinant’ of the R-matrix was estimated and it was greater than 0.00001. The items having factor loading greater than or equal to 0.40 were selected. Total 26 items with five dimensions emerged through Exploratory Factor Analysis explaining 58.14% of the variance, which provided the evidence of factorial/construct validity of the scale. The scale can be used for research and human resource development programs in school/university and organizations. Keywords : Gratitude, content validity, Factor analysis, Multicollinearity, R-matrix
其他摘要：Abstract The Gratitude Scale (GS) developed by the authors was administered to 456 adults to determine the psychometric characteristics i.e. reliability and validity. Cronbach’s Alpha of the scale was found 0.91. Content validity of the scale was verified by some experts, academicians, and professionals. For testing multicollinearity and singularity ‘Determinant’ of the R-matrix was estimated and it was greater than 0.00001. The items having factor loading greater than or equal to 0.40 were selected. Total 26 items with five dimensions emerged through Exploratory Factor Analysis explaining 58.14% of the variance, which provided the evidence of factorial/construct validity of the scale. The scale can be used for research and human resource development programs in school/university and organizations. Keywords : Gratitude, content validity, Factor analysis, Multicollinearity, R-matrix