Assessment of motivations of masters athletes at the World Masters Games

Authors: Joe Walsh, Ian Timothy Heazlewood, Mark DeBeliso, Mike Climstein

Corresponding Author:
Joe Walsh
School of Psychological and Clinical Sciences
Faculty of Engineering, Health, Science and the Environment
Charles Darwin University
Darwin, NT, 0909
Australia
jo.walsh@cdu.edu.au
+618 8946 7215

Joe Walsh is affiliated with The School of Psychological and Clinical Sciences, Faculty of Engineering, Health, Science and the Environment, Charles Darwin University, Darwin, Northern Territory, Australia.
Ian Timothy Heazlewood is Associate Professor and Theme Leader Exercise and Sport Science in The School of Psychological and Clinical Sciences, Faculty of Engineering, Health, Science and the Environment, Charles Darwin University, Darwin, Northern Territory, Australia.

Mark DeBeliso is Professor, Department of Physical Education and Human Performance, Southern Utah University, Cedar City, USA

Dr. Mike Climstein (FASMF, FACSM, FAAESS, AEP) is with Clinical Exercise Physiology, Southern Cross University, School of Health and Human Sciences, Gold Coast, Queensland, Australia; Adjunct Associate Professor with The University of Sydney, Exercise, Health and Performance Faculty Research Group, Sydney, New South Wales, Australia, and Adjunct Associate Professor and Co-Director of the Water Based Research Unit, Bond University, Robina, Queensland, Australia.

Assessment of motivations of masters athletes at the World Masters Games

ABSTRACT
The Motivations of Marathoners Scales (MOMS) is a quantitative instrument for assessing motivation of marathon participants. A large sample of masters athletes completed the MOMS as part of a questionnaire at the World Masters Games (WMG), the world’s largest multisport event. The aim of this research project was to document statistical patterns within this sample for the psychological variables in the MOMS. As the MOMS had been used for 25 years, this large sample represented a good opportunity to document patterns in the application of the MOMS psychometric tool and recommendations for those interested in promoting masters sports, based upon the participant motivations to compete. Statistically significant patterns were identified in the motivations of the 3,928 participants (2,010 male, 1,918 female) who completed the 56 question MOMS survey. As well as gender-based differences in motivations, 37 of the 56 questions were identified as being more or less important motivators by the participants. The most motivation for the cohort as a whole was given by the item construct “to socialize with other participants”, though there were also significant differences between the two genders. The weight control questions indicated these masters athletes did not place a priority on this construct, thus focusing marketing initiatives on constructs such as weight control may be ineffective. For promotion of participation in masters sport and by inference physical activity at older ages, marketing initiatives would focus on such constructs as to compete with others, to improving sporting performance, socialization, health improvement, improving physical fitness, feeling a sense of achievement, pushing oneself beyond current limits and staying in physical condition, all of which were more highly rated by participants than weight control.

Keywords: motivations of marathoners scales, sport participation, masters athlete, veteran athlete

INTRODUCTION
The Motivations of Marathoners Scales (MOMS) (37) is a valid and reliable, quantitative instrument for assessing motivation of marathon participants. Participant motivation evaluates those factors that enhance or inhibit motivation to participate and are represented by factors such as health orientation, weight concern/weight loss and personal goal achievement (36, 37). The MOMS is a psychometric instrument based upon a series of 56 questions and scored on a seven-point Likert scale (35). The MOMS instrument was constructed around nine re-occurring themes that had been reported in the preceding literature by marathon runners as reasons for participating in marathons (37). These themes were general health orientation, weight concern, affiliation, recognition, personal goal achievement, competition, coping, self-esteem and life meaning. The themes can in turn be clustered into four areas, namely: physical health, social, achievement, and psychological (37). Using a pool of different questions for each theme, Masters and colleagues (37) statistically tested these constructs and selected the most appropriate. The MOMS scale has been adopted to investigate athletes competing in other sports (other than marathon), including at both multi-sport events (22, 23) and individual sports tournaments such as rugby (31). Data collected using the MOMS scale has also been used as a convenience sample for demonstrating applications of data mining techniques that can be used in exercise science and exercise psychology (30).

This manuscript focuses on application of the MOMS psychometric tool to masters athletes. As defined by Raeburn and Dascombe (42), masters athletes are those systematically training for and competing in organized sporting events designed specifically for older adults. The biggest masters sporting event (by participant number) is the World Masters Games (WMG). Governed by the International Masters Games Association, the WMG are a non-invitational, quadrennial, international, multi-sport event. In terms of competitor numbers, the WMG has developed into the world’s largest international sports tournament.

Although the WMG have been in existence since 1985, surprisingly there was limited scientific literature available on this specific cohort. An international team of researchers was thus formed to investigate the nexus between aging, physical activity, indices of health and the global obesity epidemic by investigating those competing in masters sport.

The benefits of participation in masters athletic competition had been previously investigated with Seals (47) and others reporting positive adaptations in musculoskeletal health (15, 19, 69), improved glycaemia (41, 43) and considerable health benefits associated with the long-term exercise participation (16, 20, 34, 44, 49). Although long-term participation in sport (and physical activity (39)) is advocated by health professionals, the advanced age of participants is also commonly associated with an increased incidence of chronic diseases such as coronary artery disease (5, 50), hypertension, hypercholesterolemia, and type 2 diabetes mellitus (69). Research on the masters athletes competing at the Sydney WMG has included research on body mass index (53, 54, 60, 62, 63), injury incidence (9, 29, 55, 64) and health (6, 7, 10-13, 56-58) of competitors.

The questions identified in the MOMS have been demonstrated (4, 18, 40, 45) as important motivational constructs and have been used by sport psychology researchers for 25 years. A number of studies have been conducted on the MOMS in the context of masters athletes (1-3, 21-24, 26-28, 48, 59). Researchers have investigated prediction of gender from the sports psychological data in the MOMS (25, 66, 67). Being able to predict gender or other attributes of participants from MOMS data has value of its own based solely on the additional information produced. Additionally, further research on relationships between gender classification prediction and this scale may lead to supplementary insights that might assist in other research using the MOMS instrument. Heazlewood and colleagues (32) re-evaluated the first and second order factor structure of the MOMS instrument with masters athletes, the factor structure identified in the original MOMS instrument was not reproduced with the WMG male and female cohorts.

A large sample of masters athletes completed the MOMS as part of a questionnaire at a large multisport event. The manuscript will include measures of central tendency and dispersion for Likert responses for all respondents and also with responses split by gender. The manuscript will also include comparison between genders for each of the 56 questions. The purpose of this research project was to document descriptive statistics and significant statistical patterns within this data for the psychological variables in the MOMS. As the MOMS had been used for many years, this large sample represented a good opportunity to document patterns in the application of the MOMS psychometric tool and recommendations for those interested in promoting masters sports, based on the participant motivations to compete. It was hypothesised that there would be significant differences between the two genders. These differences were assumed based on the success achieved in past research (25, 66, 67) predicting participant gender from MOMS data.

METHODOLOGY
Approval for this study was granted by a university research ethics committee in accordance with the ethical standards of the Helsinki Declaration of 1975 (revised in 2008). The 2009 Sydney World Masters Games Organising Committee approved the project, stipulating the survey must only be provided in an online format so there was minimal disruption to the participants during the WMG. An online survey was created using Limesurveytm, an open-source, web-based application to deliver the survey. Filters were used in the participant questionnaires to abbreviate response times. Following pilot testing by investigators, electronic invitations were sent to masters games athletes who provided a valid email address upon registration. The survey consisted of several sections. These sections featured questions related to the following areas: information for participants, a privacy statement, participant demographics, participant medical history (personal and family), past surgical procedures, prescribed medications, physiologic data and psychological participation factors.

The MOMS (37) was used to gauge the importance of a range of psychological factors in determining sports participation. The age ranges in the research used to develop the MOMS survey instrument (37) had significant overlap with age ranges of participants at the WMG (7, 12, 13, 52). The MOMS scale featured 56 questions clustered within nine scales, which in turn were clustered in four areas. To complete the MOMS participants rated each of the items according to the scale in terms of how important it was as a reason for their participation in sport. A score of 1 would indicate that the item is “not a reason” for participation, whereas a score of 7 indicates that the item is a “very important reason” for participation and scores in-between these extremes represented relative degrees of each reason. The following are sample questions which sought responses to word stems such as; “to control my weight”, “to compete with others”, “to earn respect of peers”, “to improve my sporting performance”, “to earn respect of people in general”, “to socialize with other participants”, “to improve my health”, “to compete with myself”, “to become less anxious”, “to improve my self-esteem”, “to have something in common with other people”, “to add a sense of meaning to my life”, “to prolong my life” and “to become less depressed.” The full list of 56 words stems used are included in the results section. Analysis of this psychometric data was completed using the programming language R, version 3.5.0 (2018-04-23) “Joy in Playing” on platform x86_64-apple-darwin13.4.0 (64-bit) running under OS X El Capitan 10.11.3.

Heazlewood et al. (28) had conducted analysis of mean and standard deviations for participant motivation factor scores by gender summarising trends by adopting the underlying factors in the MOMS as applied to the WMG. These were calculated to assess trends as well as cross tabulations of BMI categories with gender. Due to the evidence of superior predictive scores utilising the 56 questions in the MOMS, as opposed to collapsing into underlying factors (67), the analysis in this manuscript was conducted using the raw 56 item constructs in the survey tool, as opposed to condensing them into the underlying factors (as per the MOMS structure). As well as reporting descriptive statistics in the form of measures of central tendency and dispersion, statistical analysis was conducted to investigate the differences in scoring the 56 items between the two genders. Comparison was made between genders using Welch two sample t-tests for each of the 56 questions. The Welch t-test was considered preferable over Student’s t-test due to no dependence on equal variances between independent groups (38, 46). To consider a difference between the genders to be statistical significant, the required level of significance α, was set a priori at p=0.05.

RESULTS
The 2009 Sydney World Masters Games featured 28,089 competitors representing 95 countries and competing in 28 sports (52). In fact, the largest ever attendance at a WMG event was in Sydney, making this the largest international sports tournament (in terms of participant numbers) in the modern era. A total of 3,928 masters athletes (14.0% of competitors) completed all questions utilized in the analysis in this manuscript. Participation at the Sydney WMG was open to sports people of all abilities and most ages, the minimum age criterion ranged between 25 and 35 years depending upon the sport.
Table 1 illustrates the mean and standard deviation of scores for each of the 56 questions in the MOMS for the WMG masters athletes. The word stem for each MOMS question is included. The mean scores are reported in the last two columns for both male and female masters athletes.

Table 1: Measures of central tendency and dispersion for Likert responses for all respondents and also with responses split by gender. Data is summarised to 3 decimal places.

Item Constructs

Both Genders Combined

Male
Mean

Female
Mean

Mean

Standard Deviation

To control my weight

3.593

2.070

3.472

3.721

To compete with others

5.207

1.696

5.355

5.051

To earn respect of peers

3.073

1.862

3.237

2.901

To reduce my weight

3.013

1.980

2.959

3.070

To improve my sporting performance

5.203

1.716

5.185

5.223

To earn respect of people in general

2.866

1.780

2.975

2.752

To socialize with other participants

5.713

1.498

5.476

5.960

To improve my health

5.554

1.662

5.485

5.627

To compete with myself

4.789

2.000

4.987

4.583

To become less anxious

2.461

1.770

2.454

2.468

To improve my self-esteem

3.075

1.984

3.062

3.089

To have something in common with other people

3.737

1.992

3.630

3.848

To add a sense of meaning to my life

3.692

2.036

3.579

3.812

To prolong my life

4.345

2.101

4.394

4.295

To become less depressed

2.399

1.863

2.371

2.429

To meet people

4.727

1.879

4.456

5.011

To become more physically fit

5.669

1.542

5.548

5.795

To distract myself from daily worries

3.294

1.986

3.257

3.333

To make my family and friends proud of me

2.973

1.814

2.951

2.996

To make my life more purposeful

3.310

1.951

3.231

3.393

To look leaner

3.408

1.981

3.319

3.502

To try to perform better

5.076

1.723

5.144

5.005

To feel more confident about myself

3.677

2.008

3.580

3.780

To participate with my family or friends

4.858

2.008

4.563

5.168

To make myself feel whole

3.020

1.980

2.991

3.052

To reduce my chance of having a heart attack

3.527

2.053

3.649

3.400

To make myself more complete

3.349

1.981

3.358

3.340

To improve my mood

3.388

1.982

3.275

3.507

To improve my sense of self-worth

2.962

1.904

2.928

2.998

To share a group identity with other participants

4.267

1.965

4.113

4.428

It is a positive emotional experience

4.905

1.854

4.744

5.074

To feel proud of myself

4.498

1.964

4.328

4.676

To visit with friends

4.304

2.018

3.943

4.684

To feel a sense of achievement

5.142

1.610

5.000

5.291

To push myself beyond my current limit

5.214

1.707

5.148

5.282

To have time alone to sought things out

2.650

1.847

2.605

2.698

To say in physical condition

5.438

1.645

5.381

5.498

To concentrate on my thoughts

2.766

1.870

2.800

2.729

To solve problems

2.388

1.693

2.374

2.404

To see how high I can place in my sport

4.310

2.116

4.563

4.045

To feel a sense of belonging in nature

2.677

1.876

2.633

2.723

To stay physically attractive

3.880

2.019

3.862

3.899

To get a better performance than my friends

2.628

1.815

2.923

2.318

To prevent illness

4.151

2.034

4.168

4.133

People will look up to me

2.476

1.671

2.579

2.369

To see if I can beat a certain performance

4.183

2.112

4.451

3.901

To blow off steam

2.984

1.926

2.924

3.048

Brings me recognition

2.596

1.743

2.750

2.435

To have time alone with the world

2.329

1.756

2.372

2.285

To get away from it all

2.673

1.856

2.608

2.740

To make my body better than before

4.345

1.960

4.414

4.273

To beat someone I’ve never beaten before

3.104

2.041

3.342

2.855

To feel mentally in my control of my body

3.662

2.057

3.744

3.577

To get compliments from others

2.464

1.657

2.575

2.347

To feel at peace with the world

2.634

1.868

2.630

2.638

To feel like a winner

3.500

2.042

3.583

3.413

Table 2 reports a comparison made between genders for each of the 56 questions using a Welch two sample t-test, a t-test preferable over Student’s t-test due to no dependence on equal variances between independent groups (38, 46).

Item Constructs

Welch two sample t-test

Interpretation

t

p-value

To control my weight

3.780

0.000159

Female score significantly higher

To compete with others

-5.625

1.988e-08

Male score significantly higher

To earn respect of peers

-5.675

1.487e-08

Male score significantly higher

To reduce my weight

1.759

0.07874

NS

To improve my sporting performance

0.704

0.4814

NS

To earn respect of people in general

-3.938

8.378e-05

Male score significantly higher

To socialize with other participants

10.291

< 2.2e-16

Female score significantly higher

To improve my health

2.671

0.007589

Female score significantly higher

To compete with myself

-6.338

2.595e-10

Male score significantly higher

To become less anxious

0.247

0.8051

NS

To improve my self-esteem

0.425

0.6707

NS

To have something in common with other people

3.435

0.0005991

Female score significantly higher

To add a sense of meaning to my life

3.589

0.0003363

Female score significantly higher

To prolong my life

-1.482

0.1385

NS

To become less depressed

0.965

0.3348

NS

To meet people

9.359

< 2.2e-16

Female score significantly higher

To become more physically fit

5.026

5.237e-07

Female score significantly higher

To distract myself from daily worries

1.197

0.2316

NS

To make my family and friends proud of me

0.769

0.4418

NS

To make my life more purposeful

2.589

0.009667

Female score significantly higher

To look leaner

2.880

0.003995

Female score significantly higher

To try to perform better

-2.528

0.01151

Male score significantly higher

To feel more confident about myself

3.127

0.001782

Female score significantly higher

To participate with my family or friends

9.569

< 2.2e-16

Female score significantly higher

To make myself feel whole

0.965

0.3346

NS

To reduce my chance of having a heart attack

-3.809

0.0001418

Male score significantly higher

To make myself more complete

-0.273

0.7852

NS

To improve my mood

3.671

0.0002447

Female score significantly higher

To improve my sense of self-worth

1.152

0.2496

NS

To share a group identity with other participants

5.033

5.057e-07

Female score significantly higher

It is a positive emotional experience

5.599

2.299e-08

Female score significantly higher

To feel proud of myself

5.571

2.698e-08

Female score significantly higher

To visit with friends

11.685

< 2.2e-16

Female score significantly higher

To feel a sense of achievement

5.674

1.493e-08

Female score significantly higher

To push myself beyond my current limit

2.456

0.01408

Female score significantly higher

To have time alone to sought things out

1.569

0.1167

NS

To say in physical condition

2.237

0.02534

Female score significantly higher

To concentrate on my thoughts

-1.182

0.2373

NS

To solve problems

0.563

0.5737

NS

To see how high I can place in my sport

-7.711

1.578e-14

Male score significantly higher

To feel a sense of belonging in nature

1.498

0.1341

NS

To stay physically attractive

0.576

0.5643

NS

To get a better performance than my friends

-10.622

< 2.2e-16

Male score significantly higher

To prevent illness

-0.534

0.5932

NS

People will look up to me

-3.956

7.745e-05

Male score significantly higher

To see if I can beat a certain performance

-8.217

2.816e-16

Male score significantly higher

To blow off steam

2.017

0.04382

Female score significantly higher

Brings me recognition

-5.695

1.323e-08

Male score significantly higher

To have time alone with the world

-1.561

0.1186

NS

To get away from it all

2.216

0.02677

Female score significantly higher

To make my body better than before

-2.256

0.02411

Male score significantly higher

To beat someone I’ve never beaten before

-7.536

5.978e-14

Male score significantly higher

To feel mentally in my control of my body

-2.538

0.0112

Male score significantly higher

To get compliments from others

-4.328

1.544e-05

Male score significantly higher

To feel at peace with the world

0.131

0.8961

NS

To feel like a winner

-2.610

0.009089

Male score significantly higher

From Table 1 there were similarities in the results for the 56 questions, with the same group of questions getting higher scores for males and females (and overall). The questions getting the highest ranking as motivational reasons behind competition at the Sydney WMG were “to compete with others”, “to improve my sporting performance”, “to socialize with other participants”, “to improve my health”, “to become more physically fit”, “to feel a sense of achievement”, “to push myself beyond my current limit” and “to say in physical condition”. The reasons for motivation “to meet people”, “to participate with my family or friends” and “it is a positive emotional experience” scored higher with females (mean Likert score above 5.0) than for males (mean Likert score below 5.0). From Table 2, it can be seen that female Likert scores for these motivations for competition were significantly (p <0.001) higher than for their male counterparts.

For males the questions that elicited the lowest response scores, as least motivating reasons behind competition were in order of ascending score (least relevant reason first): “to become less depressed”, “to have time alone with the world”, “to solve problems”, “to become less anxious”, “to get compliments from others”, “people will look up to me”. For females those questions eliciting the lowest scores were (in ascending order by score): “to have time alone with the world”, “to get a better performance than my friends”, “to get compliments from others”, “people will look up to me”, “to solve problems”, “brings me recognition” and “to become less depressed”. The psychological questions that scored lower for males also scored lower for females and vice versa, however there were differences as per Table 2, such as the question “to get a better performance than my friends”, which was significantly (p<0.0001) different with males rating the question higher on the Likert scale than females.

From Table 2, many of the questions demonstrated significantly higher importance as motivating factors when compared between the two genders. The questions: “to reduce my weight”, “to improve my sporting performance”, “to become less anxious”, “to improve my self-esteem”, “to prolong my life”, “to become less depressed”, “to distract myself from daily worries”, “to make my family and friends proud of me”, “to make myself feel whole”, “to make myself more complete”, “to improve my sense of self-worth”, “to have time alone to sought things out”, “to concentrate on my thoughts”, “to solve problems”, “to feel a sense of belonging in nature”, “to stay physically attractive”, “to prevent illness”, “to have time alone with the world” and “to feel at peace with the world”, were all not significantly (p>0.05) different when compared between the two genders.

DISCUSSION
Nineteen questions were not significantly (p>0.05) different when compared between the two genders. These nineteen questions, represented less than half of the 56 questions in the psychometric survey tool. Given so many individual questions demonstrated significantly different scoring for the two genders it is relevant in the context of the predictive modelling approaches based on the MOMS (66, 67) using gradient boosting (17) and ridge regression (33). In these papers (66, 67) the underlying factors linking the 56 questions were not used in their analysis and instead the raw 56 questions were used. This gave a higher accuracy at predicting gender than had been achieved in preceding research (25) using a multiplayer perceptron neural network (14). The finding that so many of the questions gave statistically significant differences for the two genders, gives further support to the logic behind this particular approach at using more questions for analysis as opposed to the overarching factors combining multiple questions.

From Table 1, as would be expected from past research findings on the MOMS at the Sydney WMG (21), the most motivation for the cohort as a whole was given by the item construct “to socialize with other participants”. For female masters athletes, this was the highest ranked item construct, with a mean Likert score of 5.960 out of 7. For males this construct also scored highly but was in fact the third highest ranked construct with “to become more physically fit” and “to improve my health” scoring higher. Females also scored highly on these other two constructs with scores which were in fact statistically significantly higher for both constructs than for males (as per Table 2). These findings would suggest as per previous research (21) that as “to socialize with other participants” was the highest scoring item construct, marketing endeavours to promote masters sport participation should focus on the socialising aspect of sport. As males scored highest on the construct “to become more physically fit”, therefore this construct would be the method of choice to targeted marketing initiatives addressed at males only, with “to improve my health” following as the second and “to socialize with other participants” as the third choice.

Amongst the lowest scoring item constructs was the construct “to have time alone with the world”, which scored a mean of 2.329 (standard deviation 1.756, male mean 2.372, female mean 2.285). This is logical as many masters competitors were competing in team events such as soccer, rugby union, softball, volleyball or touch football (a variation of touch rugby (65) that is one of the most popular sports in Australia and New Zealand (61)). In such team sports there would presumably be less time to be alone when training or competing than in marathon running (the environment under which the MOMS scale was originally designed (37)). The item constructs “to become less anxious” and “to become less depressed” demonstrated low mean scores compared to the majority of other constructs, both for the two genders combined (mean scores 2.461 and 2.399 on the seven-point Likert scale) as well as for males (means 2.454 and 2.371) and females (means 2.468 and 2.429) considered individually. These lower mean scores may be due to there only being a proportion of the masters cohort that suffered from anxiety or depression for whom these two questions were relevant, which may have resulted in a lower mean score across the cohort as a whole. This is confirmed in the literature (6), where 6.3% of the Sydney WMG cohort indicated they suffered from depression. It should be noted that based upon normative comparisons the incidence of depression was reported as high for Sydney’s 2009 WMG participants (6), though other masters cohorts have shown significantly less incidence of anxiety and depression than comparative data on the national population (8). Therefore, whilst only a small proportion of the cohort might find relevance in these two item constructs (depression and anxiety), for those who suffered from these disorders there may be a much higher degree of relevance and in turn the incidence in the Sydney WMG sample was considered as high compared to norms (6). It is accepted that exercise prescription has demonstrated benefits for mental health conditions such as depression (51). Of note, there was no significant difference detected via the Welch two sample t-test between the scores for males or females on these two item constructs (depression and anxiety), thought females did score both questions higher (though statistically non-significantly different). Therefore, no significant gender-based difference was apparent within this analysis confined to Likert scale mean scores.

In the literature (21), mental health constructs such as depression and anxiety were also demonstrated to be considered as not being important determinants of participation for WMG masters athletes. The alternative methodology in Heazlewood et al. (21) additionally identified the mental health constructs self-esteem, daily worries, improving mood and having a more purposeful life as not important determinants. These constructs had mean scores below the mean of all mean scores (3.717, approximated to three decimal places) of all 56 constructs measured. These scores (combined mean score by gender) were self-esteem (3.075), daily worries (3.294), improving mood (3.388) and having a more purposeful life (3.310).Whilst still scoring lower than the mean of the mean values calculated for the 56 other questions, females scored higher than males on all four of these mental health construct questions, this difference was larger enough to be statistically significant for the constructs “to improve my mood” (p<0.01) and “to make my life more purposeful” (p<0.0005). Whilst females scored higher than males in these mental health constructs in terms of their relevance for motivation behind participation at the WMG, as per the suggestion in Heazlewood et al. (21), it would be advised against marketing initiatives to promote participation in masters sports based on these mental health constructs as they may not be successful if utilised to promote participation, due to a low importance placed upon them by the majority of participants.

Whatman (68), indicated that in Australia (where the majority of competitors at the Sydney WMG were from (6)), health/fitness were major reasons behind participation in sport (>55% of respondents), followed to a lesser extent by enjoyment (22% of respondents). In our findings the construct “to improve my health” was one of the highest scoring constructs, for both males and females (though females scored significantly higher, p<0.01), with mean Likert score of 5.554 (both genders combined). Similarly, fitness was also identified as a major reason behind participation in line with the results reported by Whatman (68). Males and females (females significantly higher, p < 0.000001) both rated the construct “to become more physically fit” as one of the highest on the Likert scale (mean score for both genders combined 5.669). The MOMS scale does not have a question that directly translates to enjoyment, but a similar proxy would be “it is a positive emotional experience”, a construct that scored relatively highly for males and also females (though significantly higher for females, p < 0.0000001). It should be noted as per Heazlewood et al., 2011 (that applied an alternative assessment methodology) fitness constructs were rated more highly than weight control type constructs (e.g. “to control my weight” Likert mean 3.593 vs. “to become more physically fit” mean 5.669, numbers that in context of standard deviations are statistically significantly different, by inspection).

As the mean Likert score for weight control was statistically significantly lower than other constructs, the recommendation would be that to promote participation at masters events, marketing strategies should focus on other constructs. This is important to consider as research has shown associated positive outcomes in terms of obesity (53, 54, 60, 62, 63), reduced injury incidence and classification (9, 55, 9, 64) and reduced incidence of health-related diseases and some disorders (6-7, 10-13, 56-58) at the WMG. It would be recommended that constructs such as “to compete with others”, “to improve my sporting performance”, “to socialize with other participants”, “to improve my health”, “to become more physically fit”, “to feel a sense of achievement”, “to push myself beyond my current limit” and “to say in physical condition” would all provided a more targeted strategy.

CONCLUSIONS
For promotion of participation in masters sport and by inference physical activity at older ages, marketing initiatives should focus on such constructs as “to compete with others”, “to improve my sporting performance”, “to socialize with other participants”, “to improve my health”, “to become more physically fit”, “to feel a sense of achievement”, “to push myself beyond my current limit” and “to stay in physical condition”. The most motivation for the cohort as a whole was given by the item construct “to socialize with other participants”, though there were significant differences between the two genders. The weight control questions indicated these athletes did not place priority on this construct, thus focusing marketing initiatives on other constructs, such as for example weight control may be ineffective.

APPLICATIONS IN SPORT
In order to promote sport participation at older ages, focus should be placed on marketing the socialization aspects of sport. Though other constructs were also considered important to older athletes (such as competition, health and fitness), weight control was not considered an important construct, therefore marketing initiatives should avoid focusing on weight control as such a focus is likely to be ineffective for sport promotion.

ACKNOWLEDGMENTS
Assistance was provided by the Sydney WMG Committee. We appreciate IT support from Evan Wills. We acknowledge the useful comments provided by the journal on review of the manuscript, with some beneficial additions included in the manuscript in response to reviewer suggestions. We would like to thank especially the Sydney WMG masters athletes who took the time to participate in this project.

REFERENCES
1. Adams K, DeBeliso M, Walsh J, Burke S, Heazlewood I T, Kettunen J, Climstein M (2011). Motivations to Participate in Sport at the Sydney 2009 World Masters Games. Med Sci in Sports & Exerc. 43(5), S655.

2. Adams, K. J., DeBeliso, M., Walsh, J., Burke, S., Heazlewood, I. T., Kettunen, J., & Climstein, M. (2011). Why do people participate in the world masters games? Journal of Science and Medicine in Sport, 14(7), S166.

3. Adams, K. J., Walsh, J., Burke, S., Heazlewood, I. T., Kettunen, J., DeBeliso, M., & Climstein, M. (2012). Motivations to participate in sport at the 2010 pan pacific masters games. Medicine & Science in Sports & Exercise, 44(5), S309.

4. Buning, R. J., & Walker, M. (2016). Differentiating mass participant sport event consumers: traditional versus non-traditional events. Sport Marketing Quarterly, 25(1), 47.

5. Chugh, S. S., & Weiss, J. B. (2015). Sudden cardiac death in the older athlete. Journal of the American College of Cardiology, 65(5), 493-502.

6. Climstein, M., Burke, S., Walsh, J., Adams, K., DeBeliso, M., Heazlewood, I., … & Brock, K. (2010). Sydney 2009 World Masters Games: Participants medical and health history survey. Journal of Science and Medicine in Sport, 13, e71.

7. Climstein, M., Walsh, J., Burke, S., Adams, K., DeBeliso, M., Kettunen, J., & Heazlewood, I. (2011). Physiological demographics of the Sydney World Masters Games competitors. Journal of Science and Medicine in Sport, 14, e80.

8. Climstein, M., Walsh, J., Best, J., Heazlewood, I. T., Burke, S., Kettunen, J., … & DeBeliso, M. (2011). Incidence of chronic disease and lipid profile in veteran rugby athletes. International Journal of Biological and Medical Sciences, 1(1), 41.

9. Climstein, M., Walsh, J., Heazlewood, I., DeBeliso, M., Adams, K., Sevene, T., & Kettunen, J. (2012). Rowing, Soccer and Swimming: Injury differences (location, type, consequence) in preparation for the World Masters Games. Journal of Science and Medicine in Sport, 15, S129.

10. Climstein, M., Walsh, J., DeBeliso, M., Heazlewood, T., Sevene, T., & Adams, K. (2018). Cardiovascular risk profiles of world masters games participants. The Journal of Sports Medicine and Physical Fitness, 58(4), 489-496.

11. DeBeliso, M., Climstein, M., Adams, K., Walsh, J., Burke, S., Heazlewood, I.T., & Kettunen, J. (2011). North American medical and health history survey of 2009 Sydney World Masters Games participants. Journal of Science and Medicine in Sport, 14, e79-e80.

12. DeBeliso, M., Walsh, J., Climstein, M., Heazlewood, I. T., Kettunen, J., Sevene, T., & Adams, K. (2014). World Masters Games: North American participant medical and health history survey. The Sport Journal, 19.

13. DeBeliso, M., Walsh, J., Heazlewood, I.T., Sevene, T., Adams, K. J., & Climstein, M. (2017). Cardiovascular risk profiles of World Masters Games participants. Medicine & Science in Sports & Exercise, 49(5S), 277.

14. Fausett, L., (1994). Fundamentals of neural networks: architectures, algorithms, and applications (No. 006.3). Prentice-Hall.

15. Feland, J. B., Hager, R., & Merrill, R. M. (2005). Sit to stand transfer: performance in rising power, transfer time and sway by age and sex in senior athletes. British Journal of Sports Medicine, 39(11), e39-e39.

16. Franklin, B. A., Fern, A., & Voytas, J. (2004). Training principles for elite senior athletes. Current Sports Medicine Reports, 3(3), 173-179.

17. Friedman, J. H. (2002). Stochastic gradient boosting. Computational Statistics & Data Analysis, 38(4), 367-378.

18. Havenar, J., & Lochbaum, M. (2007). Differences in participation motives of first-time marathon finishers and pre-race dropouts. Journal of Sport Behavior, 30(3), 270.13.

19. Hawkins, S. A., Wiswell, R. A., & Marcell, T. J. (2003). Exercise and the master athlete—a model of successful aging?. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 58(11), M1009-M1011.

20. Heazlewood, I. T. & Walsh, J. (2007). Training and exercise recommendations for the masters client-athlete. In Proc. 2007 National Fitness Conference. Eveleigh, Sydney, Australia.

21. Heazlewood, I. T., Walsh, J., Climstein, M., Burke, S., Kettunen, J., Adams, K. J., & DeBeliso, M. (2011). Sport psychological constructs related to participation in the 2009 World Masters Games. World Academy of Science, Engineering and Technology, 7, 2027-2032.

22. Heazlewood, I. T., Walsh, J., Climstein, M., Burke, S., Kettunen, J., Adams, K. J., & DeBeliso, M. (2012). Athlete motivations to participate in the 2010 Pan Pacific Masters Games. In ICSEMIS 2012 Pre-Olympic conference: sport inspiring a learning legacy (Vol. 4, pp. 19-24).

23. Heazlewood, I., Walsh, J., Climstein, M., DeBeliso, M., Adams, K., Kettunen, J., & Munro, K. (2012). The motivations of marathoners scales instrument for evaluating motivational factors in a variety of mainstream sports. Journal of Science and Medicine in Sport, 15, S137.

24. Heazlewood, I., Walsh, J., Climstein, M., Adams, K., Sevene, T., DeBeliso, M., & Kettunen, J. (2015). Gender differences in participant motivation in masters football at the 2010 Pan Pacific Masters Games. International Research in Science and Soccer II, 236.

25. Heazlewood, I., Walsh, J., Climstein, M., Kettunen, J., Adams, K., & DeBeliso, M. (2016). A comparison of classification accuracy for gender using neural networks multilayer perceptron (MLP), radial basis function (RBF) procedures compared to discriminant function analysis and logistic regression based on nine sports psychological constructs to measure motivations to participate in masters sports competing at the 2009 World Masters Games. In Proceedings of the 10th International Symposium on Computer Science in Sports (ISCSS) (pp. 93-101). Springer, Cham.

26. Heazlewood, I., Walsh, J., Climstein, M., Adams, K., & Sevene, T. DeBeliso, M., & Kettunen, J. (2016). Participant motivation: A comparison of male and female athletes competing at the 2009 World Masters Games. In J.M. Montague & L.M. Tan (Eds.), Applied Psychology – proceedings of the 2015 Asian congress, (pp. 291-297). World Scientific Publishers.

27. Heazlewood, I. T., Walsh, J., Climstein, M., Adams, K., Sevene, T., & DeBeliso, M. (2016, June). Participant Motivation Predicting Training Sessions and Training Type in Male and Female Athletes Competing at 2010 Pan Pacific Masters Games. In Singapore Conference of Applied Psychology (pp. 137-146). Springer, Singapore.

28. Heazlewood, I. T., Walsh, J., Climstein, M., Adams, K., Sevene, T., & DeBeliso, M. (2016, June). Differences in Participant Motivation Based on Category of Body Mass Index and Gender. In Singapore Conference of Applied Psychology (pp. 125-135). Springer, Singapore.

29. Heazlewood, I.T., Walsh, J., Climstein, M., Adams, K., Sevene, T., & DeBeliso, M. (2017). Injury location, type and incidence of male and female athletes competing at the World Masters Games. Journal of Science and Medicine in Sport, 20, e51-e52.

30. Heazlewood, I., & Walsh, J. (2017). Data Mining: Applications of Neural Network Analysis in Exercise and Sport Science. In International Conference on Computer Science Education Innovation & Technology (CSEIT). Proceedings (pp. 77-83). Global Science and Technology Forum.

31. Heazlewood, I., Walsh, J., & Climstein, M. (2018). Can participant motivation predict training frequency and training type in Male Masters Rugby players competing at the 2010 World Golden Oldies Rugby Festival? In Proc. Singapore Conference on Applied Psychology 2018 (pp. 41-42). East Asia Research.

32. Heazlewood, I. T., Walsh, J., & Climstein, M. (2018). Re-evaluation of the Factor Structure of Motivations of Marathoners Scales (MOMS). In Applied Psychology Readings (pp. 57-71). Springer, Singapore.

33. Hoerl, A. E., & Kennard, R. W. (1970). Ridge regression: Biased estimation for nonorthogonal problems. Technometrics, 12(1), 55-67.

34. Kuska, M. (2018). The Importance of Physical Activity in the Process of Successful Ageing-An Overview. Central European Journal of Sport Sciences and Medicine, 21(1), 55-65.

35. Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology. 22(140). New York: Columbia University Press.

36. Marcus, B. H., & Forsyth, L. H. (2009). Motivating people to be physically active (No. Ed. 2). Human Kinetics.

37. Masters, K. S., Ogles, B. M., & Jolton, J. A. (1993). The development of an instrument to measure motivation for marathon running: The Motivations of Marathoners Scales (MOMS). Research Quarterly for Exercise and Sport, 64(2), 134-143.

38. Moser, B. K., & Stevens, G. R. (1992). Homogeneity of variance in the two-sample means test. The American Statistician, 46(1), 19-21.

39. Olejnik, A., Kubińska, Z., Pańczuk, A., & Kubińska, J. (2017). Physical Activity as a Health Need. Central European Journal of Sport Sciences and Medicine, 19(3), 105-111.

40. Ogles, B. M., & Masters, K. S. (2003). A typology of marathon runners based on cluster analysis of motivations. Journal of Sport Behavior, 26(1), 69.

41. Pratley, R. E., Hagberg, J. M., Rogus, E. M., & Goldberg, A. P. (1995). Enhanced insulin sensitivity and lower waist-to-hip ratio in master athletes. American Journal of Physiology-Endocrinology and Metabolism, 268(3), E484-E490.

42. Reaburn, P., & Dascombe, B. (2008). Endurance performance in masters athletes. European Review of Aging and Physical Activity, 5(1), 31-42.

43. Rogers, M. A., King, D. S., Hagberg, J. M., Ehsani, A. A., & Holloszy, J. O. (1990). Effect of 10 days of physical inactivity on glucose tolerance in master athletes. Journal of Applied Physiology, 68(5), 1833-1837.

44. Rosenbloom, C., & Bahns, M. (2005). What can we learn about diet and physical activity from master athletes?. Nutrition Today, 40(6), 267-272.

45. Ruiz, F., & Zarauz Sancho, A. (2011). Validation of the Spanish version of the Motivations of Marathoners Scales (MOMS). Revista Latinoamericana de Psicología, 43(1), 139-156.

46. Ruxton, G. D. (2006). The unequal variance t-test is an underused alternative to Student’s t-test and the Mann–Whitney U test. Behavioral Ecology, 17(4), 688-690.

47. Seals, D. R., Hagberg, J. M., Allen, W. K., Hurley, B. F., Dalsky, G. P., Ehsani, A. A., & Holloszy, J. O. (1984). Glucose tolerance in young and older athletes and sedentary men. Journal of Applied Physiology, 56(6), 1521-1525.

48. Sevene, T., Adams, K., Climstein, M., Walsh, J., Heazlewood, I., DeBeliso, M., & Kettunen, J. (2012). Are masters athletes primarily motivated by intrinsic or extrinsic factors? Journal of Science and Medicine in Sport, 15, S357.

49. Shephard, R. J., Kavanagh, T., Mertens, D. J., Qureshi, S., & Clark, M. (1995). Personal health benefits of Masters athletics competition. British Journal of Sports Medicine, 29(1), 35-40.

50. Shapero, K., Deluca, J., Contursi, M., Wasfy, M., Weiner, R. B., Lewis, G. D., & Baggish, A. L. (2016). Cardiovascular risk and disease among masters endurance athletes: insights from the Boston MASTER (Masters Athletes Survey To Evaluate Risk) initiative. Sports Medicine – Open, 2(1), 29.

51. Stanton, R., & Reaburn, P. (2014). Exercise and the treatment of depression: a review of the exercise program variables. Journal of Science and Medicine in Sport, 17(2), 177-182.

52. Sydney 2009 World Masters Games Committee. (2010). Sydney 2009 World Masters Games Final Report. Sydney, Australia.

53. Walsh, J., Climstein, M., Heazlewood, I. T., Burke, S., Kettunen, J., Adams, K., & DeBeliso, M. (2011). The loess regression relationship between age and BMI for both Sydney World Masters Games athletes and the Australian national population. International Journal of Biological and Medical Sciences, 1(1), 33.

54. Walsh, J., Heazlewood, I. T., Climstein, M., Burke, S., Adams, K., DeBeliso, M., & Kettunen, J. (2011). Body mass index for Australian athletes participating in rugby union, soccer and touch football at the World Masters Games. Journal of the World Academy of Science, Engineering and Technology, 7(77), 1119-23.

55. Walsh, J., Climstein, M., Heazlewood, I.T., Adams, K., DeBeliso, M., Burke, S., & Kettunen, J. (2011). Rugby union, soccer, touch football: Injury classification (masters athletes). Journal of Science and Medicine in Sport, 14, e76.

56. Walsh, J., Climstein, M., Heazlewood, I.T., Adams, K., DeBeliso, M., Burke, S., & Kettunen, J. (2011). Masters athletes: Are they hurt more often? (rugby union, soccer and touch football). Journal of Science and Medicine in Sport, 14, e76-e77.

57. Walsh, J., Burke, S., Climstein, M., Kettunen, J., Heazlewood, I. T., DeBeliso, M., & Adams, K. (2012). Obesity prevalence for athletes participating in soccer at the World Masters Games. International SportMed Journal, 13(2), 76-84.

58. Walsh, J., Climstein, M., Heazlewood, I., DeBeliso, M., Kettunen, J., Sevene, T., & Adams, K. (2012). Reduced prevalence of smoking in masters football codes (rugby union, soccer and touch football). Journal of Science and Medicine in Sport, 15, S134.

59. Walsh, J., Heazlewood, I.T., Climstein, M., DeBeliso, M., Adams, K.J., Burke, S., Kettunen, J. (2012). The effect of body mass index on motivations for competition at the Sydney World Masters Games. In Proc. Pre-Olympic Conference: International Convention on Science, Education and Medicine in Sport. 19-24 July, SECC, Glasgow, UK. FC45.3.

60. Walsh, J., Heazlewood, I.T., Climstein, M., DeBeliso, M., Adams, K.J., Burke, S., Kettunen, J. (2012). The Obesity Prevalence in Masters Athletes, a Comparison of all World Masters Games Sports. In Proc. Pre-Olympic Conference: International Convention on Science, Education and Medicine in Sport. 19-24 July, SECC, Glasgow, UK. FC90.4.

61. Walsh, J., Heazlewood, I., & Climstein, M. (2012). Modelling touch football (touch rugby) as a Markov process. Intl J of Sports Sci and Eng, 6, 203-212.

62. Walsh, J., Climstein, M., Heazlewood, I. T., DeBeliso, M., Adams, K. J., Burke, S., & Kettunen, J. (2013). Body mass index of masters basketball players. Medicina Sportiva, 7, 1700-1705.

63. Walsh, J., Climstein, M., Heazlewood, I. T., Kettunen, J., Burke, S., DeBeliso, M., & Adams, K. J. (2013). Body mass index for athletes participating in swimming at the World Masters Games. The Journal of Sports Medicine and Physical Fitness, 53(2), 162-168.

64. Walsh, J., Climstein, M., Heazlewood, I. T., DeBeliso, M., Kettunen, J., Sevene, T. G., & Adams, K. J. (2013). Masters athletes: No evidence of increased incidence of injury in football code athletes. Advances in Physical Education, 3(1), 36-42.

65. Walsh, J., Heazlewood, I. T. & Climstein, M. (2015). Modelling Touch Football (Touch Rugby): Can Successful Execution Of Line Attack And Defence Be Probabilistically Modelled As Independent Events. International Journal of Health, Physical Education and Computer Science in Sports. 20(1), 45-51.

66. Walsh, J., Heazlewood, T., & Climstein, M. (2018). Application of gradient boosted trees to gender prediction based on motivations of masters athletes. Model Assisted Statistics and Applications. 13(3).

67. Walsh, J., Heazlewood, T., & Climstein, M. (2018). Regularized linear and gradient boosted ensemble methods to predict athletes’ gender based on a survey of masters athletes. Model Assisted Statistics and Applications. 13(3).

68. Whatman, S. L. (2007). Australian Bureau of Statistics-Participation in Sport and Physical Recreation. ACHPER Action, 10(2), 1-4.

69. Whiteson, J. H., Bartels, M. N., Kim, H., & Alba, A. S. (2006). Coronary artery disease in masters-level athletes. Archives of Physical Medicine and Rehabilitation, 87(3), 79-81.

Print Friendly, PDF & Email
2018-07-11T14:09:51+00:00July 24th, 2018|Research, Sports Health & Fitness|Comments Off on Assessment of motivations of masters athletes at the World Masters Games