Predicting physical exercise changes in Chinese rural adolescents: the application of the health action process approach model.

Predicting physical exercise changes in Chinese rural adolescents: the application of the health action process approach model.

Xu, Huanyu;Su, Chang;Ji, Yuanyi;Yin, Fei;Yang, Yang;Yang, Shujuan;Xu, Ying;Zhou, Huan;Zhou, Junmin;Ma, Xiao;Liu, Qiaolan;
psychology, health & medicine 2019 pp. 1-13
255
xu2019predictingpsychology

Abstract

The purposes of the current study were to explore the applicability of the Health Action Process Approach (HAPA) model for interpreting changes in physical exercise behavior and to examine the key determinants of changes in physical exercise. The participants were 639 rural middle school students in Sichuan province, China, who did not perform physical exercise. Three surveys and two interventions were completed in the same participants within 1.5 years. The HAPA model elements and physical exercise were estimated by a self-reported questionnaire. The results showed that 158 students (24.7%) formed a habit of physical exercise. The structural equation model for the pre-intention stage and behavior stage showed acceptable goodness of fit. Outcome expectancies (=0.136, 0.014) and action self-efficacy (=0.314, 0.001) directly predicted intention of physical exercise, the latter directly predicted physical exerciseplanning (=0.537, <0.001), andplanning subsequently predicted physical exercise (=0.324, <0.001). Maintenance self-efficacy indirectly predicted physical exercise through planning (95%CI: 0.014, 0.053). The findings suggested that the HAPA model was a very useful tool for predicting changes in physical exercise behavior, as this model explains the process of changing physical exercise habits and reveals the weak link in such behavioral changes among Chinese rural adolescents.

Citation

ID: 95805
Ref Key: xu2019predictingpsychology
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
95805
Unique Identifier:
10.1080/13548506.2019.1709653
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet