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다국어 초록 (Multilingual Abstract)

The purpose of this study is to present retirement age predictive functions of athletes that can be utilized as data to reduce psychological shock of athletes from retirement and prepare for the future. To accomplish such purpose, athletes who retired as an undergraduate, unemployed or professional registered on the athlete registration system of the Korean Sport & Olympic Committee for three years were selected as the population. Stratified sampling was used for convenience sampling. Content validity of a retirement factor questionnaire was examined by consulting with experts. Opinions of 72 retirees were collected through an open questionnaire, and samples of 260 persons were used in the first and second parts after consulting with experts based on first sample data. The stepwise regression analysis method was applied to develop reliable and valid retirement predictive regression function. The degree of relevance was shown by multiple correlation coefficient between predicted age calculated by the predictive function and actual retirement age. Significance level was .05 for all tests. The 8 predictive function are presented according to the procedure above. (retirement age of female athlete)= 24.097+1.778*(physical limitation 11)-1.142*(job plan29), (retirement age of male athlete)= 23.498+1.334*(popularity 2)-1.126*(exercise attitude 20)+1.021*(competitiveness 7)-1.020* (job plan 29)+0.871*(economy 18)-1.905*(administration 22)-1.024*(administration 23)+.778*(interpersonal relationship 13), (retirement age of combat sports)=23.158+.688*(physical limitation 11)-1.790*(job plan 29)+0.960*(popularity 1)-0.656*(exercise attitude 16)+0.747*(job plan 33)+0.643*(economy 18)-0.461*(administration 23)+.606*(injury 46), (retirement age of non-combat sports)=20.741+ 1.637*(popularity 2)-1.270*(exercise attitude 20)+0.942*(competitiveness 7)+2.061*(family 5)-3.291*(administration 21)+1.082*(administration 25)+1.192(interpersonal relationship 8), (retirement age of individual sports)=27.414-1.295*(job plan 29)+1.463*(physical limitation 15)+0.972*(popularity 1)-0.639* (exercise 16), (retirement age of group sports)= 21.950+1.950*(popularity 2)-1.318*(exercise attitude 20)+4.635*(interpersonal relationship 6)-3.337*(addiction 41), (retirement age of undergraduate athlete)= 21.950+1.950*(popularity 2)-1.318*(exercise attitude 20)+4.635*(interpersonal relationship 6) -3.337*(addiction 41), (retirement age of unemployed and professional athlete)= 27.808-0.874* (exercise attitude 19)+1.287*(competitiveness 8)-1.402*(administration 21)+0.757*(popularity 2).

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참고문헌 (Reference)

1 채진석, "한국프로야구 Post시즌 전력분석 및 예측모형" 국민체육진흥공단 한국스포츠정책과학원 25 (25): 92-107, 2014

2 조은형, "한국프로농구 플레이오프 진출을 위한 순위결정 요인 탐색과 통계적 모형 비교" 한국체육학회 55 (55): 733-745, 2016

3 채진석, "한국 프로야구 관중 수 예측" 국민체육진흥공단 한국스포츠정책과학원 23 (23): 892-905, 2012

4 성봉주, "한국 성인 남녀별 체력나이 추정식 개발" 한국체육측정평가학회 19 (19): 59-82, 2017

5 채진석, "프로야구 포스트시즌 진출 예측을 위한 통계적 모형 비교" 한국체육측정평가학회 12 (12): 33-48, 2010

6 홍승후, "프로선수의 은퇴준비와 선수개인의 속성,운동 경력요인 그리고 은퇴요인과 상관관계" 한국사회체육학회 (39) : 943-951, 2010

7 최형준, "인공신경망(Artificial Neural Network)을 이용한 2005년도 영국 윔블던 테니스 대회의 경기결과 예측에 관한 연구" 한국체육학회 45 (45): 459-468, 2006

8 최희윤, "은퇴한 여자핸드볼 선수의 삶에 관한 내러티브" 한국체육학회 51 (51): 83-93, 2012

9 채진석, "운동선수출신의 은퇴요인 탐색과 측정도구의 타당화" 한국체육측정평가학회 20 (20): 67-82, 2018

10 서연희, "운동선수의 은퇴기대, 심리적 위기감, 은퇴준비수준 및 재사회화 간의 구조관계" 한국체육과학회 21 (21): 393-406, 2012