Three Versions of the Perceived Stress Scale: Psychometric Evaluation in a Nationally Representative Sample of Chinese Adults during the COVID-19 Pandemic.
Zhuang SheDan LiWei ZhangNingning ZhouJuzhe XiKang JuPublished in: International journal of environmental research and public health (2021)
(1) Background: The COVID-19 outbreak has created pressure in people's daily lives, further threatening public health. Thus, it is important to assess people's perception of stress during COVID-19 for both research and practical purposes. The Perceived Stress Scale (PSS) is one of the most widely used instruments to measure perceived stress; however, previous validation studies focused on specific populations, possibly limiting the generalization of results. (2) Methods: This study tested the psychometric properties of three versions of the Chinese Perceived Stress Scale (CPSS-14, CPSS-10, and CPSS-4) in the Chinese general population during the COVID-19 pandemic. A commercial online survey was employed to construct a nationally representative sample of 1133 adults in Mainland China (548 males and 585 females) during a one-week period. (3) Results: The two-factor (positivity and negativity) solution for the three versions of the CPSS showed a good fit with the data. The CPSS-14 and CPSS-10 had very good reliability and the CPSS-4 showed acceptable reliability, supporting the concurrent validity of the CPSS. (4) Conclusions: All three versions of the CPSS appear to be appropriate for use in research with samples of adults in the Chinese general population under the COVID-19 crisis. The CPSS-10 and CPSS-14 both have strong psychometric properties, but the CPSS-10 would have more utility because it is shorter than the CPSS-14. However, the CPSS-4 is an acceptable alternative when administration time is limited.
Keyphrases
- public health
- psychometric properties
- physical activity
- social support
- depressive symptoms
- mental health
- stress induced
- sars cov
- randomized controlled trial
- clinical trial
- radiation therapy
- coronavirus disease
- big data
- electronic health record
- locally advanced
- rectal cancer
- artificial intelligence
- patient reported outcomes
- data analysis