The relationship of participant motivation factors with level of education, health indices and lifestyle decisions for rugby players competing at the Golden Oldies World Rugby Festival

Research output: Contribution to conferenceAbstractResearchpeer-review

Abstract

Introduction:Participant motivation based on Motivations of Marathoners Scale (MOMS) (Masters, OglesB & Jolton, 1993; Marcus & Forsyth, 2009) evaluates factors, which enhance or impede motivation to participate in competitive sport. Factors as to health orientation, weight concern,personal goal achievement, competition, recognition, affiliation, psychological coping, life meaning and self-esteem. Previous research indicated a hierarchy of importance of these in Rugby players, however scores on these factors did not predict training frequency and type((Heazlewood et al., 2018). However, at the Masters Pan Pacific multi sport competition total weekly training session in males were predicted by goal achievement and affiliation, whereas in females the predictor set was goal achievement, affiliation, health orientation and psychological coping for Masters Pan Pacific multi sport competition athletes (Heazlewood etal., 2016). The research aim was to extend upon the previous research designs to evaluate relationships between the MOMS nine factor participant motivation concepts with level of education, health indices and lifestyle decisions for Rugby players competing at the 2010 Golden Oldies World Rugby Festival.

Methods: Participants were males competing at the 2010 Golden Oldies World Rugby Festival, Sydney,Australia (n=216, mean age=51.27, s.d.=8.04 years; age range 35 – 72 years) and completed an online survey prior to competition using the Limesurveytm interactive survey system where they completed Motivations of Marathoners Scale (MOMS), which measured nine participant motivation factors related to health orientation, weight concern, personal goal achievement,competition, recognition, affiliation, psychological coping, life meaning and self-esteem. Level of education was classified as diploma-trade-technical, high school completion, undergraduate university and post graduate university. Health indices/markers were BMI, waist circumference, systolic and diastolic BP, HDLs, LDLs, triglycerides, fasting plasma glucose(FPG) and HbA1C. Lifestyle decisions were drinker/non-drinker and frequency and current/exsmoking, non-smoking and frequency. Correlation and ANOVA analyses were applied to evaluate the many possible relationships. 

Results: No significant differences were observed between level of education and the nine participant motivation factors. The correlations of health indices with the participant motivation displayed no relationship with BMI; waist circumference positive with psychological coping, health orientation and weight control (r=.140 – 154, p<.05); no relationship for systolic and diastolic BP; positive for HDLs (r=.242,p=0.042), and LDLs (r=.278, p=028), with psychological coping; positive for triglycerides with psychological coping (r=.275 and p=.035), health orientation (r= .276, p=.034), competition(r= .314, p=.018) and goal achievement (r= .362, p=.005); FPG significantly negatively correlated with self-esteem (r=-.435 and p=.016), life meaning (r=-.374 and p=.029), health orientation (r=-.345 and p=.045), affiliation (r=-.458 and p=.006) and competition (r=-.353 and p=.040) and no relationship for HbA1C. Results for lifestyle decisions were all correlations were non-significant for drinks/wk with nine factors. Comparing drinkers to non-drinkers MOMS scores was unrealistic as most players were drinkers. All correlations were non significant for cigarettes/wk with nine factors. However, ANOVA displayed higher scores for psychological coping for non-smokers compared to current smokers (score 4.21>2.95, p=0.48)and almost significant for health orientation as non-smokers had higher scores than current smokers (5.03>3.62, p=0.54). 

Discussion: Level of education is usually regarded as a positive indicator of increased physical activity and positive perceptions toward exercise, however not with this cohort. Some interesting findings concerning health indices as waist circumference, HDLs, LDLs, triglycerides and FPG, and indicators of metabolic syndrome and health risk, were positively associated with psychological coping, weight control, health orientation, competition and goal achievement suggesting links to participant motivation perceptions. However, such correlations were low to moderate. Significant FPG negative correlations are a result of lower FPG value (a better the test result) to higher positive scores for five of the nine factors and a more positive profile in participant motivation. Lifestyle decisions in terms of drinking and smoking indicates frequency of drinking is non-predictive of participant motivation and a similar trend displayed by frequency of cigarettes/wk. In terms of the different categories for smoking/non- smoking,non-smoking players indicated psychological coping was an important participant motivation factors as compared to smoking players. Therefore, player health indices have a higher relationship to participant motivation factors and may reflect participant motivation is partially driven by a health belief model for physical activity in this cohort.
Original languageEnglish
Pages25-26
Number of pages2
Publication statusPublished - 20 Jun 2019
EventSingapore Conference on Applied Psychology 2019 - Grand Copthorne Waterfront, Singapore
Duration: 20 Jun 201921 Jun 2019
https://scap.ear.com.sg/

Conference

ConferenceSingapore Conference on Applied Psychology 2019
Abbreviated titleSCAP 2019
CountrySingapore
Period20/06/1921/06/19
Internet address

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Holidays
Football
Health Status
Life Style
Motivation
Education
Health
Psychology
Fasting
Waist Circumference
Smoking
Sports
Weights and Measures
Glucose
Self Concept
Drinking
Research
Tobacco Products
Athletes

Cite this

@conference{2dffa78e4ea348e98c1e44cf4e6df2e8,
title = "The relationship of participant motivation factors with level of education, health indices and lifestyle decisions for rugby players competing at the Golden Oldies World Rugby Festival",
abstract = "Introduction:Participant motivation based on Motivations of Marathoners Scale (MOMS) (Masters, OglesB & Jolton, 1993; Marcus & Forsyth, 2009) evaluates factors, which enhance or impede motivation to participate in competitive sport. Factors as to health orientation, weight concern,personal goal achievement, competition, recognition, affiliation, psychological coping, life meaning and self-esteem. Previous research indicated a hierarchy of importance of these in Rugby players, however scores on these factors did not predict training frequency and type((Heazlewood et al., 2018). However, at the Masters Pan Pacific multi sport competition total weekly training session in males were predicted by goal achievement and affiliation, whereas in females the predictor set was goal achievement, affiliation, health orientation and psychological coping for Masters Pan Pacific multi sport competition athletes (Heazlewood etal., 2016). The research aim was to extend upon the previous research designs to evaluate relationships between the MOMS nine factor participant motivation concepts with level of education, health indices and lifestyle decisions for Rugby players competing at the 2010 Golden Oldies World Rugby Festival.Methods: Participants were males competing at the 2010 Golden Oldies World Rugby Festival, Sydney,Australia (n=216, mean age=51.27, s.d.=8.04 years; age range 35 – 72 years) and completed an online survey prior to competition using the Limesurveytm interactive survey system where they completed Motivations of Marathoners Scale (MOMS), which measured nine participant motivation factors related to health orientation, weight concern, personal goal achievement,competition, recognition, affiliation, psychological coping, life meaning and self-esteem. Level of education was classified as diploma-trade-technical, high school completion, undergraduate university and post graduate university. Health indices/markers were BMI, waist circumference, systolic and diastolic BP, HDLs, LDLs, triglycerides, fasting plasma glucose(FPG) and HbA1C. Lifestyle decisions were drinker/non-drinker and frequency and current/exsmoking, non-smoking and frequency. Correlation and ANOVA analyses were applied to evaluate the many possible relationships. Results: No significant differences were observed between level of education and the nine participant motivation factors. The correlations of health indices with the participant motivation displayed no relationship with BMI; waist circumference positive with psychological coping, health orientation and weight control (r=.140 – 154, p<.05); no relationship for systolic and diastolic BP; positive for HDLs (r=.242,p=0.042), and LDLs (r=.278, p=028), with psychological coping; positive for triglycerides with psychological coping (r=.275 and p=.035), health orientation (r= .276, p=.034), competition(r= .314, p=.018) and goal achievement (r= .362, p=.005); FPG significantly negatively correlated with self-esteem (r=-.435 and p=.016), life meaning (r=-.374 and p=.029), health orientation (r=-.345 and p=.045), affiliation (r=-.458 and p=.006) and competition (r=-.353 and p=.040) and no relationship for HbA1C. Results for lifestyle decisions were all correlations were non-significant for drinks/wk with nine factors. Comparing drinkers to non-drinkers MOMS scores was unrealistic as most players were drinkers. All correlations were non significant for cigarettes/wk with nine factors. However, ANOVA displayed higher scores for psychological coping for non-smokers compared to current smokers (score 4.21>2.95, p=0.48)and almost significant for health orientation as non-smokers had higher scores than current smokers (5.03>3.62, p=0.54). Discussion: Level of education is usually regarded as a positive indicator of increased physical activity and positive perceptions toward exercise, however not with this cohort. Some interesting findings concerning health indices as waist circumference, HDLs, LDLs, triglycerides and FPG, and indicators of metabolic syndrome and health risk, were positively associated with psychological coping, weight control, health orientation, competition and goal achievement suggesting links to participant motivation perceptions. However, such correlations were low to moderate. Significant FPG negative correlations are a result of lower FPG value (a better the test result) to higher positive scores for five of the nine factors and a more positive profile in participant motivation. Lifestyle decisions in terms of drinking and smoking indicates frequency of drinking is non-predictive of participant motivation and a similar trend displayed by frequency of cigarettes/wk. In terms of the different categories for smoking/non- smoking,non-smoking players indicated psychological coping was an important participant motivation factors as compared to smoking players. Therefore, player health indices have a higher relationship to participant motivation factors and may reflect participant motivation is partially driven by a health belief model for physical activity in this cohort.",
author = "Tim Heazlewood",
year = "2019",
month = "6",
day = "20",
language = "English",
pages = "25--26",
note = "Singapore Conference on Applied Psychology 2019, SCAP 2019 ; Conference date: 20-06-2019 Through 21-06-2019",
url = "https://scap.ear.com.sg/",

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The relationship of participant motivation factors with level of education, health indices and lifestyle decisions for rugby players competing at the Golden Oldies World Rugby Festival. / Heazlewood, Tim.

2019. 25-26 Abstract from Singapore Conference on Applied Psychology 2019, Singapore.

Research output: Contribution to conferenceAbstractResearchpeer-review

TY - CONF

T1 - The relationship of participant motivation factors with level of education, health indices and lifestyle decisions for rugby players competing at the Golden Oldies World Rugby Festival

AU - Heazlewood, Tim

PY - 2019/6/20

Y1 - 2019/6/20

N2 - Introduction:Participant motivation based on Motivations of Marathoners Scale (MOMS) (Masters, OglesB & Jolton, 1993; Marcus & Forsyth, 2009) evaluates factors, which enhance or impede motivation to participate in competitive sport. Factors as to health orientation, weight concern,personal goal achievement, competition, recognition, affiliation, psychological coping, life meaning and self-esteem. Previous research indicated a hierarchy of importance of these in Rugby players, however scores on these factors did not predict training frequency and type((Heazlewood et al., 2018). However, at the Masters Pan Pacific multi sport competition total weekly training session in males were predicted by goal achievement and affiliation, whereas in females the predictor set was goal achievement, affiliation, health orientation and psychological coping for Masters Pan Pacific multi sport competition athletes (Heazlewood etal., 2016). The research aim was to extend upon the previous research designs to evaluate relationships between the MOMS nine factor participant motivation concepts with level of education, health indices and lifestyle decisions for Rugby players competing at the 2010 Golden Oldies World Rugby Festival.Methods: Participants were males competing at the 2010 Golden Oldies World Rugby Festival, Sydney,Australia (n=216, mean age=51.27, s.d.=8.04 years; age range 35 – 72 years) and completed an online survey prior to competition using the Limesurveytm interactive survey system where they completed Motivations of Marathoners Scale (MOMS), which measured nine participant motivation factors related to health orientation, weight concern, personal goal achievement,competition, recognition, affiliation, psychological coping, life meaning and self-esteem. Level of education was classified as diploma-trade-technical, high school completion, undergraduate university and post graduate university. Health indices/markers were BMI, waist circumference, systolic and diastolic BP, HDLs, LDLs, triglycerides, fasting plasma glucose(FPG) and HbA1C. Lifestyle decisions were drinker/non-drinker and frequency and current/exsmoking, non-smoking and frequency. Correlation and ANOVA analyses were applied to evaluate the many possible relationships. Results: No significant differences were observed between level of education and the nine participant motivation factors. The correlations of health indices with the participant motivation displayed no relationship with BMI; waist circumference positive with psychological coping, health orientation and weight control (r=.140 – 154, p<.05); no relationship for systolic and diastolic BP; positive for HDLs (r=.242,p=0.042), and LDLs (r=.278, p=028), with psychological coping; positive for triglycerides with psychological coping (r=.275 and p=.035), health orientation (r= .276, p=.034), competition(r= .314, p=.018) and goal achievement (r= .362, p=.005); FPG significantly negatively correlated with self-esteem (r=-.435 and p=.016), life meaning (r=-.374 and p=.029), health orientation (r=-.345 and p=.045), affiliation (r=-.458 and p=.006) and competition (r=-.353 and p=.040) and no relationship for HbA1C. Results for lifestyle decisions were all correlations were non-significant for drinks/wk with nine factors. Comparing drinkers to non-drinkers MOMS scores was unrealistic as most players were drinkers. All correlations were non significant for cigarettes/wk with nine factors. However, ANOVA displayed higher scores for psychological coping for non-smokers compared to current smokers (score 4.21>2.95, p=0.48)and almost significant for health orientation as non-smokers had higher scores than current smokers (5.03>3.62, p=0.54). Discussion: Level of education is usually regarded as a positive indicator of increased physical activity and positive perceptions toward exercise, however not with this cohort. Some interesting findings concerning health indices as waist circumference, HDLs, LDLs, triglycerides and FPG, and indicators of metabolic syndrome and health risk, were positively associated with psychological coping, weight control, health orientation, competition and goal achievement suggesting links to participant motivation perceptions. However, such correlations were low to moderate. Significant FPG negative correlations are a result of lower FPG value (a better the test result) to higher positive scores for five of the nine factors and a more positive profile in participant motivation. Lifestyle decisions in terms of drinking and smoking indicates frequency of drinking is non-predictive of participant motivation and a similar trend displayed by frequency of cigarettes/wk. In terms of the different categories for smoking/non- smoking,non-smoking players indicated psychological coping was an important participant motivation factors as compared to smoking players. Therefore, player health indices have a higher relationship to participant motivation factors and may reflect participant motivation is partially driven by a health belief model for physical activity in this cohort.

AB - Introduction:Participant motivation based on Motivations of Marathoners Scale (MOMS) (Masters, OglesB & Jolton, 1993; Marcus & Forsyth, 2009) evaluates factors, which enhance or impede motivation to participate in competitive sport. Factors as to health orientation, weight concern,personal goal achievement, competition, recognition, affiliation, psychological coping, life meaning and self-esteem. Previous research indicated a hierarchy of importance of these in Rugby players, however scores on these factors did not predict training frequency and type((Heazlewood et al., 2018). However, at the Masters Pan Pacific multi sport competition total weekly training session in males were predicted by goal achievement and affiliation, whereas in females the predictor set was goal achievement, affiliation, health orientation and psychological coping for Masters Pan Pacific multi sport competition athletes (Heazlewood etal., 2016). The research aim was to extend upon the previous research designs to evaluate relationships between the MOMS nine factor participant motivation concepts with level of education, health indices and lifestyle decisions for Rugby players competing at the 2010 Golden Oldies World Rugby Festival.Methods: Participants were males competing at the 2010 Golden Oldies World Rugby Festival, Sydney,Australia (n=216, mean age=51.27, s.d.=8.04 years; age range 35 – 72 years) and completed an online survey prior to competition using the Limesurveytm interactive survey system where they completed Motivations of Marathoners Scale (MOMS), which measured nine participant motivation factors related to health orientation, weight concern, personal goal achievement,competition, recognition, affiliation, psychological coping, life meaning and self-esteem. Level of education was classified as diploma-trade-technical, high school completion, undergraduate university and post graduate university. Health indices/markers were BMI, waist circumference, systolic and diastolic BP, HDLs, LDLs, triglycerides, fasting plasma glucose(FPG) and HbA1C. Lifestyle decisions were drinker/non-drinker and frequency and current/exsmoking, non-smoking and frequency. Correlation and ANOVA analyses were applied to evaluate the many possible relationships. Results: No significant differences were observed between level of education and the nine participant motivation factors. The correlations of health indices with the participant motivation displayed no relationship with BMI; waist circumference positive with psychological coping, health orientation and weight control (r=.140 – 154, p<.05); no relationship for systolic and diastolic BP; positive for HDLs (r=.242,p=0.042), and LDLs (r=.278, p=028), with psychological coping; positive for triglycerides with psychological coping (r=.275 and p=.035), health orientation (r= .276, p=.034), competition(r= .314, p=.018) and goal achievement (r= .362, p=.005); FPG significantly negatively correlated with self-esteem (r=-.435 and p=.016), life meaning (r=-.374 and p=.029), health orientation (r=-.345 and p=.045), affiliation (r=-.458 and p=.006) and competition (r=-.353 and p=.040) and no relationship for HbA1C. Results for lifestyle decisions were all correlations were non-significant for drinks/wk with nine factors. Comparing drinkers to non-drinkers MOMS scores was unrealistic as most players were drinkers. All correlations were non significant for cigarettes/wk with nine factors. However, ANOVA displayed higher scores for psychological coping for non-smokers compared to current smokers (score 4.21>2.95, p=0.48)and almost significant for health orientation as non-smokers had higher scores than current smokers (5.03>3.62, p=0.54). Discussion: Level of education is usually regarded as a positive indicator of increased physical activity and positive perceptions toward exercise, however not with this cohort. Some interesting findings concerning health indices as waist circumference, HDLs, LDLs, triglycerides and FPG, and indicators of metabolic syndrome and health risk, were positively associated with psychological coping, weight control, health orientation, competition and goal achievement suggesting links to participant motivation perceptions. However, such correlations were low to moderate. Significant FPG negative correlations are a result of lower FPG value (a better the test result) to higher positive scores for five of the nine factors and a more positive profile in participant motivation. Lifestyle decisions in terms of drinking and smoking indicates frequency of drinking is non-predictive of participant motivation and a similar trend displayed by frequency of cigarettes/wk. In terms of the different categories for smoking/non- smoking,non-smoking players indicated psychological coping was an important participant motivation factors as compared to smoking players. Therefore, player health indices have a higher relationship to participant motivation factors and may reflect participant motivation is partially driven by a health belief model for physical activity in this cohort.

M3 - Abstract

SP - 25

EP - 26

ER -