346
Views
3
CrossRef citations to date
0
Altmetric
North America

Validation of a Chinese version of the physical activity enjoyment scale: Factorial validity, measurement equivalence, and predictive validity

, &
Pages 367-380 | Received 07 Nov 2016, Accepted 29 Jun 2017, Published online: 20 Jul 2017
 

Abstract

The present study examined the psychometric properties, factorial validity, and measurement equivalence across gender and three education levels of a Chinese short version of physical activity enjoyment scale (S-PACESC). Participants (N = 4051) were fifth to 12th grade public school students recruited from eight different geographic areas of mainland Chinese. Confirmatory factor analysis supported the unidimensionality of S-PACESC with great model fit. In addition, the S-PACESC was equivalent between genders and across three education levels (i.e. elementary, middle, and high school) at both configural, full metric, and full scalar levels. The latent means comparison revealed that boys perceived significantly higher physical activity (PA) enjoyment and the PA enjoyment tends to decrease as adolescents continue to age. PA enjoyment measured by S-PACESC successfully predicted moderate to vigorous PA (MVPA) for both total and various sub-samples. The S-PACESC is a valid tool that can be used to measure PA enjoyment for Chinese students.

Additional information

Funding

This work was supported by National Social Science Foundation of China: [grant number 13CTY031].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 242.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.