國小高年級學童身體意象與社會影響因素之相關研究

• Main Author: 葉芳吟
• Other Authors: 黃芳銘
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/07994694597181689943

碩士 === 國立嘉義大學 === 教育學系研究所 === 96 === This research aimed at understanding the present situation of the high-grade children’s body image. The different background variables and the social influence factors for high-grade children’s body image were discussed. This research used questionnaires to survey high-grade children’s studying in 2006 and in public elementary schools in Taiwan. There were 660 effective questionnaires. The conclusions after statistical analysis are as follows: 1.The present situation of the high-grade children’s body image: to view on ‘appearance evaluation’, the score on appearance attention named ‘appearance orientation’ and the overall score on ‘body areas satisfaction’ tended to the average. But in ‘body figure’, people expected to have a thinner figure, no matter boys or girls. 2.The differences on different background variables for body image are as follows: for high-grade children with different genders, there were apparent differences on ‘high concerns for the appearance orientation’, ‘low concerns for the appearance orientation’, ‘negative evaluations’, and ‘body areas satisfaction’. But there was no apparent difference on ‘positive evaluations’. High-grade children with different grades and different family background had no apparent differences on the above factors. 3.The effects of social influence factors are as follows: in the aspect of high concern for appearance orientation, there were effective predictions and positive effects among ‘family’, ‘peers’, and ‘media’. Moreover, peers had the most powerful influence. In the aspect of ‘positive evaluations’, only can ‘media’ be predictable and appear to be negative effects. In the aspect of ‘body areas satisfaction’, the same as ‘positive evaluations’, only can ‘media’ be predictable and appear to be negative effects. However, ‘family’, ‘peers’, ‘school’, or ‘media’ can not predict ‘negative evalutions’ effectively.