The stress in nursing students scale (SINS) : principal components analysis of longitudinal data from Hong Kong

Roger Watson; Ian J. Deary; David R. Thompson; Gloria Li

doi:10.1111/j.1365-2702.2009.03159.x

The stress in nursing students scale (SINS) : principal components analysis of longitudinal data from Hong Kong

Roger Watson, Ian J. Deary, David R. Thompson, Gloria Li

Research output: Contribution to journal › Article › peer-review

10 Citations (Scopus)

Abstract

The aim of this study is to investigate the psychometric structure of the Stress in Nursing Students Scale (SINS) using a cohort of nursing students in Hong Kong who were tested on two occasions and to compare the structure obtained with a previously derived structure in a separate and culturally contrasting sample.

Original language	English
Pages (from-to)	1170-1172
Number of pages	3
Journal	Journal of Clinical Nursing
Volume	19
Issue number	45511
DOIs	https://doi.org/10.1111/j.1365-2702.2009.03159.x
Publication status	Published - 2010

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10.1111/j.1365-2702.2009.03159.x

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title = "The stress in nursing students scale (SINS) : principal components analysis of longitudinal data from Hong Kong",

abstract = "The aim of this study is to investigate the psychometric structure of the Stress in Nursing Students Scale (SINS) using a cohort of nursing students in Hong Kong who were tested on two occasions and to compare the structure obtained with a previously derived structure in a separate and culturally contrasting sample.",

author = "Roger Watson and Deary, {Ian J.} and Thompson, {David R.} and Gloria Li",

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AB - The aim of this study is to investigate the psychometric structure of the Stress in Nursing Students Scale (SINS) using a cohort of nursing students in Hong Kong who were tested on two occasions and to compare the structure obtained with a previously derived structure in a separate and culturally contrasting sample.

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DO - 10.1111/j.1365-2702.2009.03159.x

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The stress in nursing students scale (SINS) : principal components analysis of longitudinal data from Hong Kong

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