Presentation Title

Gender and Quality of Life

Faculty Mentor

Megan Granquist

Start Date

23-11-2019 10:00 AM

End Date

23-11-2019 10:45 AM

Location

41

Session

poster 3

Type of Presentation

Poster

Subject Area

behavioral_social_sciences

Abstract

Introduction: There is growing evidence to support sex differences in health related quality of life (Lam, St Thomas, Valier, McLeod, & Bay, 2017). There are several health benefits of physical activity that reduce the risk of major diseases and research indicates that physical activity promotes psychological health and over all wellbeing (Gill, Chang, Murphy, Speed, Hammond, Rodriguez, & Shang, 2011). Further, Lam et al. (2017) suggest that because of athletes’ increased physical activity, their sex may influence quality of life (Lam et al., 2017).

Objective: This research will determine if there is a difference in quality of life between male and female athletes.

Setting: NCAA Division III institution

Variables:

Independent Variable: Gender (males and females)

Dependent Variable: Quality of Life measured by the Quality of Life Survey (Gill et al., 2011)

Results:

Participants

Participants were athletes (n = 49; 26 males, 23 females) and their age ranged from 18 to 24 (mean=19.98; SD=1.57). The majority of the participants identified as White or Caucasian (44.9%), followed by Hispanic or Latino (24.5%), parents that are from two different groups (16.3%), Black or African American (6.1%), American Indian or Native American (2%), and Asian or Asian American (0%); three participants did not list their ethnicity.

Descriptive Statistics

The Quality of Life Survey total ranged from 91 to 151 (mean = 122.96; SD = 15.01); males’ mean score was 124.74 (SD = 14.23) and females’ mean score was 120.96 (SD = 15.93).

Inferential Statistics

Independent Samples t-Test. The results demonstrate no statistical difference in Quality of Life between male and female athletes [t(47) = .876, p = .385].

Conclusions:

A major limitation of this study was the small sample size. Additionally, data may be bias as participants self-reported their quality of life. Future research should include a larger sample size.

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Nov 23rd, 10:00 AM Nov 23rd, 10:45 AM

Gender and Quality of Life

41

Introduction: There is growing evidence to support sex differences in health related quality of life (Lam, St Thomas, Valier, McLeod, & Bay, 2017). There are several health benefits of physical activity that reduce the risk of major diseases and research indicates that physical activity promotes psychological health and over all wellbeing (Gill, Chang, Murphy, Speed, Hammond, Rodriguez, & Shang, 2011). Further, Lam et al. (2017) suggest that because of athletes’ increased physical activity, their sex may influence quality of life (Lam et al., 2017).

Objective: This research will determine if there is a difference in quality of life between male and female athletes.

Setting: NCAA Division III institution

Variables:

Independent Variable: Gender (males and females)

Dependent Variable: Quality of Life measured by the Quality of Life Survey (Gill et al., 2011)

Results:

Participants

Participants were athletes (n = 49; 26 males, 23 females) and their age ranged from 18 to 24 (mean=19.98; SD=1.57). The majority of the participants identified as White or Caucasian (44.9%), followed by Hispanic or Latino (24.5%), parents that are from two different groups (16.3%), Black or African American (6.1%), American Indian or Native American (2%), and Asian or Asian American (0%); three participants did not list their ethnicity.

Descriptive Statistics

The Quality of Life Survey total ranged from 91 to 151 (mean = 122.96; SD = 15.01); males’ mean score was 124.74 (SD = 14.23) and females’ mean score was 120.96 (SD = 15.93).

Inferential Statistics

Independent Samples t-Test. The results demonstrate no statistical difference in Quality of Life between male and female athletes [t(47) = .876, p = .385].

Conclusions:

A major limitation of this study was the small sample size. Additionally, data may be bias as participants self-reported their quality of life. Future research should include a larger sample size.