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Using Student-Athlete Experience To Predict Mental Well-being

Chet Hesson

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Abstract

The purpose of this correlational research study was to examine which student-athlete experiences at Bowling Green State University (BGSU best predicted student-athlete mental well-being. Data were collected by BGSU Athletics through the analysis of the BGSU 2017 Student-Athlete End of the Year Survey (SAEYS), which was a formal assessment of student-athlete experience and perceived mental well-being. All student-athletes at BGSU on the athletic rosters in April 2017 (380 student-athletes were invited to complete the SAEYS, and 264 student-athletes completed the survey, generating a response rate of 69.4%. Four research questions guided the study. A Factor Analysis was conducted to examine how many reliable and interpretable components there were among student-athlete experience variables. Generally, all factors in the SAEYS were determined to be reliable and interpretable components. Diversity and Inclusion had the highest mean score of all subscales. Time Demands had the strongest correlation with Mental Well-being. Forward multiple regression was utilized to examine which student-athlete experiences best predicted mental well-being. Time Demands, SAS, and Coaching accounted for 21% of the variance found in Mental Well-being, with Time Demands accounting for the largest amount. Additionally, forward multiple regression was conducted to investigate whether student-athlete experience predictive models of mental well-being differed by gender (male/female, ethnicity (minority/non-minority, sport (revenue/non-revenue generating, and citizenship (domestic/international. The study indicated that there were differences between variables. This study also indicated that mental well-being differs by gender, ethnicity, and sport. This study did not see a significant difference in mental well-being of citizenship. Males, minorities, and non-revenue sport participants all indicated a greater mental well-being than their respective counterparts, females, non-minorities, and revenue sport participants. This study focused on highlighting the growing need for athletic departments to focus their efforts not just on the tactical skills associated with their sport, but rather on the student-athletes holistic development, and the impact programming, or lack thereof, can have on the mental well-being of each student-athlete. Each research question showcased connections not previously uncovered, that indicated significant differences among variables studied. This study has hopefully extended research on student-athlete mental health and well-being.

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The purpose of this correlational research study was to examine which student-athlete experiences at Bowling Green State University (BGSU best predicted student-athlete mental well-being. Data were collected by BGSU Athletics through the analysis of the BGSU 2017 Student-Athlete End of the Year Survey (SAEYS), which was a formal assessment of student-athlete experience and perceived mental well-being. All student-athletes at BGSU on the athletic rosters in April 2017 (380 student-athletes were invited to complete the SAEYS, and 264 student-athletes completed the survey, generating a response rate of 69.4%. Four research questions guided the study. A Factor Analysis was conducted to examine how many reliable and interpretable components there were among student-athlete experience variables. Generally, all factors in the SAEYS were determined to be reliable and interpretable components. Diversity and Inclusion had the highest mean score of all subscales. Time Demands had the strongest correlation with Mental Well-being. Forward multiple regression was utilized to examine which student-athlete experiences best predicted mental well-being. Time Demands, SAS, and Coaching accounted for 21% of the variance found in Mental Well-being, with Time Demands accounting for the largest amount. Additionally, forward multiple regression was conducted to investigate whether student-athlete experience predictive models of mental well-being differed by gender (male/female, ethnicity (minority/non-minority, sport (revenue/non-revenue generating, and citizenship (domestic/international. The study indicated that there were differences between variables. This study also indicated that mental well-being differs by gender, ethnicity, and sport. This study did not see a significant difference in mental well-being of citizenship. Males, minorities, and non-revenue sport participants all indicated a greater mental well-being than their respective counterparts, females, non-minorities, and revenue sport participants. This study focused on highlighting the growing need for athletic departments to focus their efforts not just on the tactical skills associated with their sport, but rather on the student-athletes holistic development, and the impact programming, or lack thereof, can have on the mental well-being of each student-athlete. Each research question showcased connections not previously uncovered, that indicated significant differences among variables studied. This study has hopefully extended research on student-athlete mental health and well-being.

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Available abstract

The purpose of this correlational research study was to examine which student-athlete experiences at Bowling Green State University (BGSU best predicted student-athlete mental well-being. Data were collected by BGSU Athletics through the analysis of the BGSU 2017 Student-Athlete End of the Year Survey (SAEYS), which was a formal assessment of student-athlete experience and perceived mental well-being. All student-athletes at BGSU on the athletic rosters in April 2017 (380 student-athletes were invited to complete the SAEYS, and 264 student-athletes completed the survey, generating a response rate of 69.4%. Four research questions guided the study. A Factor Analysis was conducted to examine how many reliable and interpretable components there were among student-athlete experience variables. Generally, all factors in the SAEYS were determined to be reliable and interpretable components. Diversity and Inclusion had the highest mean score of all subscales. Time Demands had the strongest correlation with Mental Well-being. Forward multiple regression was utilized to examine which student-athlete experiences best predicted mental well-being. Time Demands, SAS, and Coaching accounted for 21% of the variance found in Mental Well-being, with Time Demands accounting for the largest amount. Additionally, forward multiple regression was conducted to investigate whether student-athlete experience predictive models of mental well-being differed by gender (male/female, ethnicity (minority/non-minority, sport (revenue/non-revenue generating, and citizenship (domestic/international. The study indicated that there were differences between variables. This study also indicated that mental well-being differs by gender, ethnicity, and sport. This study did not see a significant difference in mental well-being of citizenship. Males, minorities, and non-revenue sport participants all indicated a greater mental well-being than their respective counterparts, females, non-minorities, and revenue sport participants. This study focused on highlighting the growing need for athletic departments to focus their efforts not just on the tactical skills associated with their sport, but rather on the student-athletes holistic development, and the impact programming, or lack thereof, can have on the mental well-being of each student-athlete. Each research question showcased connections not previously uncovered, that indicated significant differences among variables studied. This study has hopefully extended research on student-athlete mental health and well-being.

Key concepts: Psychology, Applied psychology, Computer science

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