机构地区:[1]Victoria University Institute of Technology (VUIT), St. Albans Campus, McKechine Street, St. Albans P. O. Box 14428, Melbourne, Victoria 8001, Australia [2]Financial Mathematics Programme, Xi’an Jiaotong-Liverpool University, Suzhou, China
出 处:《Journal of Biosciences and Medicines》2015年第12期32-39,共8页生物科学与医学(英文)
摘 要:Background: Stigma of mental illness is often related to attitude studies in social science research, cross-cultural psychology and education in social behaviour. Majority of these studies used opinion on mental illness to examine attitudes. Method: A cross-sectional survey was presented to 208 registered nurses in Australia. Principal component analyses (with oblique rotation) were used to identify underlying dimensionality in the correlations of items for negative stereotyping attitudes. Subscale score variations were analysed across nurse type and ethnicity to examine the discriminant validity of the subscales. Results: Principal component analysis (PCA) revealed one dimension accounting for 50.5% of the variations within items for negative stereotyping. Developed as scale, labelled as “Dislike Attributed to Mental Illness (DISL)”, reliability analysis indicated high internal consistency with alpha coefficient of .93. Chinese general nurses scored highest on the DISL scale than the other three groups: Chinese psychiatric nurses, Anglo general and Anglo psychiatric nurses. Conclusion: Psychometric evaluation of the Dislike Attributed to Mental Illness (DISL) indicates that it is a reliable scale for measuring negative stereotyping attitudes towards mental illness. The main statistical significance was due to nurse ethnicity.Background: Stigma of mental illness is often related to attitude studies in social science research, cross-cultural psychology and education in social behaviour. Majority of these studies used opinion on mental illness to examine attitudes. Method: A cross-sectional survey was presented to 208 registered nurses in Australia. Principal component analyses (with oblique rotation) were used to identify underlying dimensionality in the correlations of items for negative stereotyping attitudes. Subscale score variations were analysed across nurse type and ethnicity to examine the discriminant validity of the subscales. Results: Principal component analysis (PCA) revealed one dimension accounting for 50.5% of the variations within items for negative stereotyping. Developed as scale, labelled as “Dislike Attributed to Mental Illness (DISL)”, reliability analysis indicated high internal consistency with alpha coefficient of .93. Chinese general nurses scored highest on the DISL scale than the other three groups: Chinese psychiatric nurses, Anglo general and Anglo psychiatric nurses. Conclusion: Psychometric evaluation of the Dislike Attributed to Mental Illness (DISL) indicates that it is a reliable scale for measuring negative stereotyping attitudes towards mental illness. The main statistical significance was due to nurse ethnicity.
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