이 연구는 기술대학 학생들의 사회인구학적 변인과 체육활동 수준에 따른 웰빙의 차이를 알아보고, 주요 변인들의 상대적 공헌도를 규명하여 기술대학의 체육프로그램 개발과 생활지도를 위한 기초정보를 제공하는데 목적이 있었다. 연구대상자는 전국 37개 한국기술대학에 재학 중인 학생들이었으며, 사용된 검사도구는 Abbot와 Jones(2006)의 웰니스검사지(the Wellness Inventory)를 연구자가 우리문화에 맞도록 번안하여 신뢰도와 타당도 검정을 거친 한국판 웰빙검사지였다. 자료처리는 SPSS Version 14.0 통계 프로그램을 이용하여 연령대, 신체질량지수(BMI), 체육수업 시수, 체육수업 참여적극성, 방과후 체육 참여빈도, 방과후 체육 참여적극성, 웰빙의 평균과 표준편차를 산출하였다. 다변량분산분석(MANOVA) 결과 연령대가 높을수록 웰빙이 높은 것으로 나타났으며(p<.001), 정상수준의 BMI에서 웰빙을 높게 인식하였다(p<.001). 또한 체육수업과 방과후 체육 참여빈도와 참여적극성이 높을수록 웰빙수준이 높게 나타났다(p<.001). 동시입력방식 중다회귀분석(enter multiple regression analysis)을 통해 총웰빙에 영향을 미치는 주요 변인들의 공헌도를 알아본 결과, 체육수업 참여적극성, 방과후 체육 참여적극성, 방과후 체육 참여빈도, 가족월평균수입, 흡연량 순으로 나타나 신체활동 변인들이 웰빙에 중요한 결정 요인임을 시사하였다.
The purpose of this study was to examine the wellbeing to the levels of socio-demographic background and physical education activity in Polytechnic Colleges' students, and to identify the relative contribution rate of major variables in order to provide basic data for the development of physical education programs and guidance for them. The subjects were a total of 1,358 students at 37 Korea Polytechnic Colleges around the nation. The Korean version of the Wellness Inventory (Abbot & Jones, 2006) modified and complemented with the help of experts was used to carry out this study. The collected data were analyzed with SPSS Version 14.0 program to calculate the average value and the standard deviation, and the independent t-test was utilized to analyze the variation of well-being by sex. And then, MANOVA was used to examine the effects of age, body mass index, the number of physical education classes, the level of participation in physical education classes, the frequency of participation in after-school physical activity and the level of participation in after-school physical activity on wellness. When the significant F-value was shown, Scheffe's post hoc test was used to compare a specific group differences. Multiple regression analysis and enter method were used to find out the relative contribution of major variables affecting wellbeing. The results showed that the wellbeing of the male students was more positive than that of female students. Students in their thirties have a higher level of wellbeing than the other age groups. Also, students at normal level of BMI have the higher level recognition of well-being compared to the other groups. In physical activity, the recognition of wellbeing was higher as the frequency and the level of participation are higher. The contribution rate affecting total wellbeing in descending order was the level of participation in physical education classes, the level of participation in after-school physical activity, the frequency of participation in after-school physical activity, monthly family income, and the amount of smoking.