scholarly journals Effect of social cognitive theory-based HIV education prevention program among high school students in Nanjing, China

2011 ◽  
Vol 26 (3) ◽  
pp. 419-431 ◽  
Author(s):  
X. Li ◽  
L. Zhang ◽  
R. Mao ◽  
Q. Zhao ◽  
B. Stanton
2018 ◽  
Vol 12 (4) ◽  
pp. 973-980 ◽  
Author(s):  
Chung Gun Lee ◽  
Seiyeong Park ◽  
Seung Hwan Lee ◽  
Hyunwoo Kim ◽  
Ji-Won Park

The most critical step in developing and implementing effective physical activity interventions is to understand the determinants and correlates of physical activity, and it is strongly suggested that such effort should be based on theories. The purpose of this study is to test the direct, indirect, and total effect of social cognitive theory constructs on physical activity among Korean male high-school students. Three-hundred and forty-one 10th-grade male students were recruited from a private single-sex high school located in Seoul, South Korea. Structural equation modeling was used to test the expected relationships among the latent variables. The proposed model accounted for 42% of the variance in physical activity. Self-efficacy had the strongest total effect on physical activity. Self-efficacy for being physically active was positively associated with physical activity ( p < .01). Self-efficacy also had positive indirect effects on physical activity through perceived benefits ( p < .05) and goal setting ( p < .01). The results of this study indicated that the social cognitive theory is a useful framework to understand physical activity among Korean male adolescents. Physical activity interventions targeting Korean male high-school students should focus on the major sources of efficacy.


2020 ◽  
Vol 30 (2) ◽  
Author(s):  
Garrett Miller ◽  
Manoj Sharma ◽  
David Brown ◽  
Mohammad Shahbazi

The purpose of this study was to use social cognitive theory to predict the frequency and intention for not smoking among middle school students. The study utilized a cross-sectional design (n=163) and administered a 38-item valid and reliable questionnaire. Frequency for smoking was predicted by environment not supportive to smoking (p < 0.0001) and emotional coping (p < 0.001) (Adjusted R2= 0.20). Intent to smoke was predicted by emotional coping (p < 0.0001); environment not supportive to smoking (p < 0.001), expectations for not smoking (p < 0.003), and self-control for not smoking (p <0.017) (Adjusted R2= 0.36).


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