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Annals of Leisure Research
ISSN: 1174-5398 (Print) 2159-6816 (Online) Journal homepage: http://www.tandfonline.com/loi/ranz20
An examination of children’s motives for triathlon
participation as a function of age
Andrew J. Martin, Rachel Batty, Ashleigh Thompson, Robert Kuchár & Petr
Pančoška
To cite this article: Andrew J. Martin, Rachel Batty, Ashleigh Thompson, Robert Kuchár & Petr
Pančoška (2018): An examination of children’s motives for triathlon participation as a function of
age, Annals of Leisure Research, DOI: 10.1080/11745398.2018.1559068
To link to this article: https://doi.org/10.1080/11745398.2018.1559068
Published online: 18 Dec 2018.
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An examination of children’s motives for triathlon
participation as a function of age
Andrew J. Martin
a
, Rachel Batty
a
, Ashleigh Thompson
a
*, Robert Kuchár
b
and
Petr Pančoška
c
a
School of Sport, Exercise & Nutrition, Massey University, Palmerston North, New Zealand;
b
University of
Economics Prague, Prague, Czech Republic;
c
Department of Advanced Mathematics in Healthcare, University
of Pittsburgh Medical Centre, Pittsburgh, USA
ABSTRACT
This study examines children’s motives for participation in triathlon
as a function of age. Initiatives implemented by a Regional Sport
Organization in New Zealand have resulted in increased
participation in ‘I Tri’d the Tri’Series (ITTS) from 300 in 2004–3300
in 2015 (aged 2–12). Participants of the 2015 ITTS were surveyed.
Graph theory analysis was applied to the data. We found
compelling 2-D and 3-D representations of age- and gender-
dependent relationships, indicating a multi-linear relationship
between the starting age of the children in the ITTS and their
participation. The main participation factors were fun and
enjoyment involving friends, competition, challenge and fitness,
as well as tangible outcomes such as spot prizes, goodies and
medals. The key implication of this study is the importance of age
and gender motives, and involving peer, whole family and other
sports involvement in engaging children in future participation in
sport.
ARTICLE HISTORY
Received 25 September 2017
Accepted 11 December 2018
KEYWORDS
Children; participation;
motives; triathlon
Introduction
Organizational initiatives that encourage sport participation and physical activity are
important for children’s health and development (Casey, Payne, and Eime 2012), and
addressing societal issues of dropout (Crane and Temple 2015), inactivity and obesity
(Blair 2009). However, there is limited research on the multi-dimensional factors (Sterdt,
Liersch, and Walter 2014) that motivate children to be physically active, particularly for
those under the age of 12 (Pannekoek, Piek, and Hagger 2013).
The aim of this current study is to build on Martin, Eagleman, and Pancoska’s(2014)
findings of how a voluntary Regional Sport Organization (RSO) in New Zealand, the Man-
awatu Triathlon Club (MTC), had dealt with macro- and micro-environmental factors in the
development and evolution of increasing participation in the sport of triathlon over a 15-
year period. Organizers had managed a total participation increase from 300 adult partici-
pants in 1999 to close to 1200 in 2012–2013. An increase in child participants from 300 in
2004–3400 in 2012–2013 also took place. Archives of the results of the respective adult
© 2018 Australia and New Zealand Association of Leisure Studies
CONTACT Andrew J. Martin a.j.martin@massey.ac.nz
*Present address: Department of Management, Sport and Tourism, LaTrobe University, Bendigo, Australia.
ANNALS OF LEISURE RESEARCH
https://doi.org/10.1080/11745398.2018.1559068
and children’s series of triathlon events from 1998 to 2013 were analysed. Data collected
and retrieved for analysis in this previously published study included event date, location,
lengths of the duathlon/triathlon parts, number of participants, and their respective age
and gender sub-groupings. The longitudinal monitoring of participation data of the
MTC events identified a number of related macro- and micro-environmental factors,
social network impacts and initiatives.
Martin, Eagleman, and Pancoska’s(2014)findings indicated that development initiat-
ives relating to increased participation in regional triathlons in New Zealand were a
result of informal and formal organizational responses to internal and external pressures.
These pressures directly or indirectly assisted in increasing sport participation of both
adults and children. The responses outlined in Martin, Eagleman, and Pancoska’s(2014)
research focused on new events targeting different groups and periodic adaptive organ-
izational infrastructure review and change. Implications included the importance of
ongoing sport event product changes and enhancements, and the use of formal internal
and external review processes, such as the Organization Development Tool, for commu-
nity or Regional Sport Organization (RSO) to support increased physical activity and par-
ticipation (Martin, Eagleman, and Pancoska 2014).
The purpose of this current study is to examine the children’s motives for participation
in triathlon as a function of age, through the ‘I Tri’d the Tri’Series (ITTS), implemented by a
voluntary RSO. The event statistics database maintained by the MTC show that from the
initial development of the ITTS participation increased by 5.5 times, averaging 120 children
for the 3 race series in 2004, with race numbers averaging 660 children for the 5 race series
in 2015. Figure 1 indicates the trend in actual average participation per race in the ITTS
from 2004–2015.
Getz and Andersson’s(2008)findings reinforced Getz’s(1997) argument that event
organizers need to be aware of the programme’s life cycle and make contingency plans
to ensure its popularity and sustainability, with possible rejuvenation initiatives to
prevent participation decline. Since the ITTS was introduced in 2004, there has been sig-
nificant growth in participant numbers. However, with the event now in a period of matu-
ration, there is a need to understand the children’s’motives towards triathlon to ensure
participation continues to develop.
Challenges to sport participation
Declining and stagnant sport participation are issues affecting both developed and devel-
oping countries worldwide (Vail 2007). Crawford, Jackson, and Godbey’s(1991)‘Hierarch-
ical Model of Leisure Constraints’highlighted the following challenges of participation:
intrapersonal (e.g. lack of skill), interpersonal (e.g. lack of partners), and structural (e.g.
cost and availability). Clearly organizational initiatives that develop sport participation
are important to help promote an increase in community physical activity and encourage
healthier behaviours, particularly among children (Casey, Payne, and Eime 2012; Green
2005; Griffiths and Rainer 2009; Henderson 2009; Mummery and Brown 2008). However,
Mummery and Brown (2008) pointed out there is still a great deal to be learned about
community physical activity interventions that engage and result in a population’s behav-
iour change. To achieve mass sport participation at the grassroots level there needs to be a
greater understanding of how to manage sports as a means for promoting active lifestyles
2A. J. MARTIN ET AL.
for children (Green 2005). Green (2005) argued that despite the area of sport development
lacking a theoretical framework, the ‘pyramid’model provides a useful starting point, high-
lighting the importance of developing support mechanisms for a broad base of athlete
entrance to sport involvement (mass participation), leading to retention (competition),
and advancement (high performance).
Attraction and enjoyment have been well-established factors of involvement with
recreation and sport activities (Bailey 2005; Paxton, Estabrooks, and Dzewaltowski 2004).
Allender, Cowburn, and Foster’s(2006, 834) review of participation in sport and physical
activity among children and adults indicated that ‘participation is motivated by enjoy-
ment’. Funk and James (2001) discussion of their ‘Psychological Continuum Model’also
points out the importance of understanding participant’s motives.
Children’s motives to participate in sport
Children’s motives to participate in sport and physical activity are complex and multi-
dimensional, and determined by biological, psychological, sociocultural and environ-
mental factors (Sterdt, Liersch, and Walter 2014). A number of theories and models of
motives for sport participation have been suggested. The ‘Sport Commitment Model’pro-
poses that children’s participation is determined by sport enjoyment, social constraints,
and involvement opportunities (Scanlan et al. 1993a,1993b). Sallis, Prochaska, and
Taylor’s(2000) comprehensive review of correlates of physical activity for children (ages
3–12) and adolescents (ages 13–18) noted different motives for age and gender
findings. Self-determination theory related to physical activity highlights the dominant
role of intrinsic rather than extrinsic motivations (Frederick-Recascino 2002), and the
Figure 1. Trend in actual average participation per race in the ITTS from 2004–2015.
ANNALS OF LEISURE RESEARCH 3
link to the notion that competence facilitates internalization (Valllerand 2007), which
enhances commitment (Ryan and Deci 2000). Birchwood, Roberts, and Pollock (2008)
also contended that any variations in an individual’s participation in sport or another
type of physical activity depended on predispositions that were established during child-
hood. More recently though, Pannekoek, Piek, and Hagger (2013, 1097) argue that:
Motivation for physical activity in children below the age of 12 years is a largely underrepre-
sented issue in contemporary research. Although engagement in sufficient physical activity is
highly important for children’s current and later health, relatively little is known of the factors
that motivate children to be physically active.
However, Cope, Bailey, and Pearce’s(2013) review found that children’s participation in
sport is motivated by five primary factors; perception of competence; fun and enjoyment;
parents; learning new skills; and friends and peers. In particular, the socio-cultural context
in which children play influences their motives to participate. In contrast, Crane and
Temple’s(2015) review identified five factors associated with dropout: lack of enjoyment,
perceptions of competence, social pressures, competing priorities and physical factors
(maturation and injuries).
Hence, based on the hypothesis that age is a factor in determining participation in
triathlon, the primary research question is, what are children’s motives for participation
in triathlon as a function of age?
Method
Study context: an adapted triathlon setting
The region’s main city where the triathlon is based, Palmerston North, has an estimated
population of 83,500 (PNCC 2016). Compared to the demographics of the rest of New
Zealand, Palmerston North has a young population (especially high in the 15–29 year
old category due to the city’s tertiary education strengths and the presence of two
major New Zealand defence force bases in the region (PNCC 2016)), with approximately
8900 primary school age children (Ministry of Education 2012). This information defines
the demographic and socio-behavioural context of the sport event implementation.
The original longer version of a triathlon, such as the Ironman series, involves a 3.8 km
swim, 180 km cycle, and 42.2 km run. Since, 2000, an Olympic distance triathlon consists of
a 1.5 km swim, 40 km cycle, and 10 km run. In the current study of an RSO, other distances
have also been adapted. The ITTS, which began in 2004, adapted the Olympic triathlon
distances. Children aged between ten and twelve participate in 10% adapted distances:
150 m swim, 4 km bike, and 1 km run. Distances for younger primary school children
(aged 6–9) are at 5%: 75 m swim, 2 km bike, and 500 m run. Families with pre-school chil-
dren (aged 2–5) also participate, and distances are approximately 1% of Olympic distance
triathlons. These mini-events are characterized by a 15 m ‘swim’where children may touch
the pool bottom and use swimming aids; 400 m ‘bike’where children have training
wheels; and a 100 m run. Children of this age are often assisted in the bike and run sections
by parents/siblings following a roped grass course. The off-road location for this event is
required to enhance the safety of the event. The increased participation and event devel-
opment of the ITTS has been supported by periodic adaptive organization infrastructure
review and change (Martin, Eagleman, and Pancoska 2014). ITTS is organized as a series
4A. J. MARTIN ET AL.
of five events on consecutive Monday evenings during the summer months of February
and March.
Fifty volunteers, (including family members and 20 teenagers who had participated in
previous years) were involved in organizing the ITTS. Growing participation has also
attracted some twenty community business sponsors. For example, the naming rights
sponsor is a bike shop providing major giveaway prizes and along with five other main
sponsors provides funding for 700 t-shirts, which are given to race entrants on the first
week of the event. Weekly prizes, food and drink products, and other related event
costs are also covered by sponsors. The low-cost entry fee, of just US$3 ($5NZD) per
race, has remained unchanged throughout the period of study, which has enhanced
the affordability of the event. As well as a t-shirt, goodies, certificate and ‘spot’prizes,
the children also receive a sponsored medal if they complete at least four of the events
in the series. However, whilst the events are competitive for the participants themselves,
no times or places are recorded and no formal acknowledgement of the winners is made.
This current research focuses on examining children’s motives for participation in triath-
lon as a function of age. Flyvbjerg (2006) pointed out that single study findings (i.e. from
the Manawatu Triathlon Club’s‘I Tri’d the Tri’Series) can be generalizable. Whilst it is
acknowledged that the results of this current research are unique to the ITTS/MTC, it is
hoped that the findings reveal information that similar voluntary community organizations
should keep in mind when attempting to sustain or increase participation levels.
Data collection
For this current study there was two distinct sources of data, (1) event statistics retrieved
from the database maintained by the MTC; (2) results from questionnaire surveys sent to
parents of participants in the 2015 ITTS. The parents then asked the children both open
and closed questions, with one questionnaire response being returned per child. It is
acknowledged that data analysed in this study were obtained in a second-hand
manner, which has the potential to introduce biases into the data obtained. However, it
is hoped that the parents did not unduly impact or influence the children’s responses.
Moreover, analysing patterns in the data collected for every individual participant was
undertaken, compensating for entry biases (to change the pattern significantly, difference
in many individual entries should occur simultaneously, which is less likely to happen).
The questionnaire was the main tool used for data collection related to the primary
research question (see Appendix –Table A1)–The segments labelled S1–S8 highlight
different sections of the questionnaire (i.e. demographics, parent/child involvement in
triathlon, and the key factors perceived to encourage and motivate the children’spartici-
pation in triathlon and other sports). The questions were developed from discussion with
the co-authors experienced in research projects related to the different sections of
interest.
For the current study, the researchers retrieved participant numbers from the MTC
(2015) data archives of the ITTS for the time period 2004–2015. This process was
efficient due to the lead author’s involvement throughout the period as event organizer
and vice president. It is also acknowledged that all the researchers involved in the
study have been event volunteers. Whilst our involvement could also have increased
biases, it should be noted that we had no vested interest (financial or otherwise) in
ANNALS OF LEISURE RESEARCH 5
positively reporting the RSO. The lead author was not directly involved in the facilitation or
collection of the survey itself, and the responses were anonymous.
The questionnaire was sent to 576 email addresses with a 44% completion rate; 253
surveys were submitted during a two week period, using the Qualtrics online question-
naire system. However, 65 of these questionnaires contained a large fraction (>50%) of
unanswered questions. For this reason, only 188 completed surveys were used for the pur-
poses of the content analysis; representing a 33% usable response rate (188/576). Ethical
approval for this low-risk research was obtained from the Massey University Ethics Com-
mittee with the key ethical considerations related to the purpose, confidentiality and
anonymity explained to the participants. Permission for the research was provided by
MTC, who were also identified in Martin, Eagleman, and Pancoska’s(2014) previous study.
Data analysis
Content analysis of the open-ended question responses involved searching, using proces-
sing software, for all occurrences of characteristic words in their semantic contexts and
placing them into various ordered or partially ordered categories using word cloud rep-
resentations (Barth et al. 2013). The measure used for quantification of the impact of
the term in the analysis was then of the frequency or variety of the most salient themes
(Cohen, Manion, and Morrison 2007).
Standard statistical testing and processing of individual data was undertaken first using
JMP Pro 12 software (Carver 2014) and Maple 12 library routines (Shingareva and Lizar-
raga-Celaya 2009). A novel approach to relationship-based analysis, developed for clinical
analytics (Pancoska et al. 2014) was then applied to the questionnaire data to provide
compelling 2-D and 3-D representations of age and gender dependent personal relation-
ship patterns from this sport setting. The novelty of this approach is the characterization of
participants not just by their question responses (58 –see Table A1), but by a complete
network of relationships between these answers, as are provided simultaneously by an
individual respondent. Such complete utilization of the personal answer data covariates
would lead to intractable complexity in conventional statistical processing. Therefore
new mathematical foundations were developed from information and contemporary
graph theory (Pancoska 2014). This approach allows processing of these relationship pat-
terns using algorithms developed and proved for this task. The founding principles were as
follows:
1. To identify clearly separated subgroups of participant response patterns, such that the
result is unique in a maximal sampling diversity sense (Banks and Constantine 1998).
2. These identified sub-groups should be preserved when the number of participants
increases to infinity (convergence of clustering, in Nešetřil and Ossona de Mendez
2016).
3. To satisfy the maximal sampling diversity entropy by selecting a block design compli-
ant, maximally packed system of patterns (Hanani 1963; Rodl 1985).
In this data ‘pre-processing’, the relationship between all the answers was represented
by a personal 58-partite graph for each person (see Figure 2(a,b)). Vertices (circles) rep-
resent different answers (red circles) for each question or parameter intervals (e.g. age).
6A. J. MARTIN ET AL.
Lower values and ‘no’answers are on the periphery; higher values, ‘yes’answers are pro-
portionally closer to the centre of the graph. Edges (lines) are the relationships between
the respective answers, which allow for the context-based analysis of the data. The
relationship of the respective partitions to the questionnaire questions is shown as
Figure 2. (a) 58-partite octagonal graphs (RHS): Respondents’questionnaire response relationship
profiles demonstrating separation for the >9 year group. Graphs (LHS): Statistically significant differ-
ences between the histograms and distances between the individual answer networks for respondents
from the <6 group. (b) 58-partite octagonal graphs (RHS): Respondents’questionnaire response
relationship profiles demonstrating separation for the <6 year group. Graphs (LHS): Statistically signifi-
cant differences between the histograms and distances between the individual answer networks for
respondents from the >9 group.
ANNALS OF LEISURE RESEARCH 7
numbers, with corresponding questions listed in Table A1. Comparison of these graphs
using algorithms satisfying uniquely the founding principles (Pancoska 2014) revealed
groups of respondents with similar patterns (‘clusters’) from the total cohort (N = 188).
Based on the assumption that age is a factor for triathlon motives towards participation,
the cohort was separated into three age-defined sub-cohorts: <6, 6–9 and >9 year old (N =
45, 73 and 70, respectively) and examined (by exhaustive statistical algorithm search/pro-
cessing; Pancoska 2014)tofind features of each respondents’profile graph that were stat-
istically unique and distinct for the <6 and >9 groups, 20% (115/576) of the sample (see
Figure 3(a,b)), as opposed to the ‘intermediate’(6–9) age group, which was used as the
test set to validate the a priori hypothesis that (if age plays a functional role) their triath-
lon-motives will be ‘in between’the distinct younger and the older groups. We argue that
this validation, where we test the classification results on the ‘intermediate’sub-group,
eliminates the possibility that the event restriction on participation age (ITTS cut-offof
12 years old) can adversely skew the findings.
Figure 2 (LHS) demonstrates separation in the cohort’sresponsesforthedifferent age (<6
and >9) groups in terms of the distribution of graph-graph distances. This outcome is deter-
mined by comparing the personal response graph of each participant to the two optimal
reference patterns of Figure 2 (RHS) and computing the graph-graph edit distances (Gao
et al. 2010) between them. The optimality of this choice of reference patterns from the com-
plete set for age-dependent difference quantification was confirmed by systematic statistical
hypothesis testing. The distributions of the distances of participants from the <6 and >9 year
groups have the largest difference in means, shown in Figure 2 (LHS) as δμ. The highest stat-
istical significance of these differences in edit distance distribution means, is quantified by p-
value from the two-way t-test of difference of these means, which are p=10
−22
and p=
10
−15
, respectively (significantly lower than the ‘conventional’0.05 level) for the two refer-
ence patterns, represented by graphs in Figure 2 (LHS).
Findings
In the following discussion, Figures 4(a,b), 5(a,b) and Table 1 provide explanation and rep-
resentation of the key results from standard statistical processing of questionnaire surveys
sent to parents of participants in the 2015 ITTS. The findings from the 2015 survey
responses indicated 56% boy: 44% girl participation (see also Table 1 for parent age
and household income). Their ethnicity showed slightly higher European (85%; 7%
Māori; Pacific Islander 2%; Other 6%) participation compared to the regions’demographic
(79% European, 16.5% Māori, 4.5% Pacific Islander; Statistics New Zealand 2013 census).
Relationship between starting age and participation
Preliminary data (Figure 4(a)) shows the relationship between the starting age of children
and their participation in the ITTS. The majority of children have been participating in the
ITTS event for up to 7 years. This multi-linear trend between the age at which the children
started to participate in triathlon and the actual age of the children supports the hypoth-
esis that age might be an important factor in the children’s motives for participating in
triathlon as well as in staying active in regular events. This observation is reinforced in
the 3-D histograms shown in Figure 4(b). Here the lines connecting the most populated
8A. J. MARTIN ET AL.
Figure 3. (a) Graph of the separation in triathlon motivations for the different age (<6 and >9) groups.
(b) 3-D histogram of the distribution of participants’triathlon motivations across the two age depen-
dent groups (<6 and >9).
ANNALS OF LEISURE RESEARCH 9
pairs of ages and their corresponding participation, shown as red lines in Figure 4(a), are
identified by the arrows connecting the maxima in the 3-D histograms. This connection
indicates that the distribution of the number of children of given ages with the same
year at which they start participating in triathlon (TriAge) is linearly decreasing both
with increasing age and TriAge, as expected.
Factors for encouraging participation
Examples of feedback highlighted that ‘it’s a fun event that is encouraging to all levels of
triathlete’and overall, ‘This was one of the most memorable occasions I have spent at a
sports event –well done and see you next year.’The content analysis of the questionnaire
responses with the highest frequencies noted by word cloud representations indicated
that ITTS participants most enjoyed taking part due to the triathlon activity, prizes/
goodies, friends, fun, competition, and challenge. We present below typical examples of
responses containing these high-frequency terms:
Completing this triathlon, getting a certificate and the prize/ socks/ snacks from the ‘I Tri’d the
Tri’series.
Figure 4. (a) Relationship between the starting age of participants and their long term participation in
the ITTS shown by a multi-linear relationship (b) Relationship between the starting age of participants
and their long term participation in the ITTS shown by 3D histograms.
10 A. J. MARTIN ET AL.
Having fun with her friends.
Racing and feeling he has done well. He finishes middle of the field and is always happy with
that.
Five main factors also related to their participation motives: enjoyment and fun, friends,
competition, challenge and fitness.
Its only fun; doesn’t matter where you come
Participating with friends
Has really enjoyed seeing how much better she is getting, especially with doing the training
this year.
Achievement and satisfaction of knowing he can do it.
Improves fitness.
The responses also highlight that the children’s sport participation is perceived to be posi-
tively influenced by their family (siblings, parent as trainers, triathlon participants or sup-
porters) and peer (sport and/or school friends) involvement.
Believe in, and actively participate in, and role model sporting activity within our family.
Competing against her friends and doing lots of bike rides together as a family to prepare.
Having fun with friends and other kids.
Table 1. Study cohort demographics.
Response %
Child gender
Male 120 56%
Female 96 44%
Total 216 100%
Household income
Less than $20,000 2 1%
$20,001 to $40,000 9 4%
$40,001 to $60,000 14 7%
$60,001 to $80,000 47 22%
$80,001 to $100,000 51 24%
$100,001 to $120,000 36 17%
$120,001 to $140,000 20 9%
$140,001 or above 34 16%
Total 213 100%
Ethnicity
Maori 15 7%
Pacific Islander 5 2%
Pakeha/European 185 85%
Other (please state) 12 6%
Total 217 100%
Parent age
25 yrs to 30 yrs 9 4%
31 yrs to 35 yrs 23 11%
36 yrs to 40 yrs 58 27%
41 yrs to 45 yrs 99 45%
46 yrs to 50 yrs 21 10%
51 yrs or above 8 4%
Total 218 100%
ANNALS OF LEISURE RESEARCH 11
The role of age in patterns of factors influencing participant motives
Figure 3(a) shows the result of graph-based analysis of ITTS data, indicating highly signifi-
cant separation in triathlon motives for the different age (<6 and >9) groups. The open
circles show the positions of the triathlon-motive patterns, computed independently for
participants of ages 6–9 after the algorithm was optimized using the data for <6 and
>9 age groups. The representation of the intermediate age group (6–9) in this plane
confirms the a priori stated hypothesis, that their answer networks will be intermediate
between the <6 and >9 groups. The 3-D histogram (Figure 3(b)) also shows the distribution
of participants’with variable triathlon motives across the age-dependent groups. Figure 5
(a) shows conceptually the essence of the algorithm. We identify the peaks in the partici-
pant histograms, connect these peaks by the linear ‘ridge’and compute the equation of
the linear separator between the age groups. This equation passes through the ‘canyon’
between the ridges, so the sum of the distances measured orthogonally from the separa-
tor line to the ridges is minimal. Patterns typical for responses of the younger children <6
are located along the x-axis, indicating the dominant compliance of their triathlon motives
network with the typical <6 network, with only minor contributions of the answer patterns
typical for >9 children. The same is true for >9 children with their individual answer net-
works concentrated along the y-axis with minimal mixture with the <6 relationship in their
answers.
Figure 5. (a) Graphs & 3-D histograms of age-dependent separation in the triathlon motivations for the
different age (<6 and >9) groups highlighting gender differences. (b) 2-D example of a linear x and y
equation passing through the ‘canyon’between the ‘ridges’.
12 A. J. MARTIN ET AL.
Interestingly, there are also gender differences evident with boys aged <6 and >9 adher-
ing to their peer age group norm of triathlon participation motive patterns, whereas girls’
patterns tend to be more varied related to their age group norm (Figure 5(b)).
We can now identify the main differences in these patterns between the respective sub-
groups. Linked or connected sub-patterns of factors that were most characteristic for chil-
dren age <6 compared to >9 year-olds in the complete triathlon motive patterns were
parents aged 36–40 with an income over US$100,000 (the average NZ income of NZ
$50,000 is approximately US$33,000). With these younger participants, there were typically
no siblings taking part, no directinvolvement in the sport by parents, and there were no other
entry activities for a triathlon. Also, the cost was minimal to participate. Note, that the simul-
taneous presence of all these factors is the unique motive pattern for this age group, ident-
ified by our approach. The sub-patterns of factors that were evident in the complete patterns
of answers for children age >9 were different: They simultaneously contained parents aged
41–45 with an income of up to US$66,000. Other siblings and parents were involved in triath-
lon and the children were participating in other events, such as the Weet-Bix and inter-
schools triathlons, which increased the cost of equipment and participation.
Discussion
The relationship between ITTS children’s starting age of participation
The findings show a strong relationship between the early starting age of the children and
their ongoing participation in the ITTS, with many of the children having participated for
up to seven years. Kirk (2005) and Birchwood, Roberts, and Pollock’s(2008)findings also
highlighted the importance of this early childhood engagement and reinforcement of
physical and sport activity as vital determinants of participation. The influence of internal
and external event initiatives that impacted the ITTS were identified as important in devel-
oping significantly increased and sustained participation, as reported in the earlier MTC
study by Martin, Eagleman, and Pancoska (2014).
Factors for encouraging the ITTS children’s participation
We have shown here that the children’s sport participation is strongly influenced by
relationship patterns of factors, including simultaneously age, family (as parent partici-
pants, siblings, supporters or trainers) and peer (school and other sport friends) involve-
ment. These findings support the arguments presented by Kremarik (2000) and Craike,
Symonds, and Zimmermann (2011) for sport organizations to utilize family to help
engage children in regular physical activity. The importance of parent engagement and
their volunteer involvement in sport are also emphasized by Green, Smith, and Roberts
(2005). We argue that their involvement (‘attenders’) has positively influenced, as initiators
and catalysts, their children’s ITTS participation, the ‘intenders’(Martin, Eagleman, and
Pancoska 2014). The critical role of family, particularly parental involvement, as partici-
pants and volunteers, is also highlighted by Kirk (2005) and Henderson (2009) in encoura-
ging children’s participation in organized sports, particularly as Kirk’s(2005) review
suggested that traditional primary and secondary school physical education programmes
have largely been ineffective in promoting lifelong physical activities. Henderson (2009)
ANNALS OF LEISURE RESEARCH 13
argued that children who receive family support or have parental involvement in orga-
nized sports as participants or volunteer administrators are significantly more likely to par-
ticipate than other children.
The current findings indicate that the children’s main perceived factors for deciding to
participate are less impacted by individual factors, but rather by simultaneously networked
patterns of multiple components, including fun and enjoyment involving friends (Cope,
Bailey, and Pearce 2013; Scanlan et al. 1993a,1993b). However, also noted are the intrinsic
motivation factors of competition, challenge and fitness, as well as extrinsic tangible out-
comes such, as ‘spot’prizes, goodies and medals. There are no results or placings at the
ITTS, so the competition and challenge is an intrinsic motivation for participants. These
positive factors increase the attraction of the event (Funk and James 2001). The children’s
motives of enjoyment also parallel Allender, Cowburn, and Foster’s(2006)findings from a
review of qualitative studies relating to participation in sport and physical activity among
children and adults; ‘participation is motivated by enjoyment and the development and
maintenance of social support networks’(834).
The role of age in patterns of factors influencing participant motives
These current findings, indicating a dominant role of patterns of multi-components over the
individual factors, support Misener and Doherty’s(2009) argument for the use of a multi-
dimensional approach to developing non-profit sport organization event capacity. Our
approach, based upon analysis of characteristic patterns of demographic and motive
profiles for each participant, enables quantitative capturing of these multi-dimensional
factors. Application of the relationship-based analysis (Pancoska et al. 2014) to this current
study’s datahas indicated characteristic features in the age-typical components of event par-
ticipants’triathlon motives. Age, and particularly early childhood engagement, which is the
dominant factor in all the relationship networks we identified, is highlighted by both Sallis,
Prochaska, and Taylor’s(2000), Kirk’s(2005) and Birchwood, Roberts, and Pollock’s(2008)
findings influencing physical activity and explaining differences in sport participation.
Since the ITTS was introduced in 2004, there has been significant growth in participant
numbers. However, with the event now in a period of maturation, event organizers need
to be aware of the programme’s life cycle and make contingency plans to ensure its popu-
larity and sustainability, as suggested by Getz (1997) and reinforced by Getz and Anders-
son (2008). Wheeler and Green (2014) noted that the increasing age at which individuals
are entering into parenthood is potentially driving the intensification of middle-class
investment in children’s sport. These views support those of Green, Smith, and Roberts
(2005) who noted that,
middle-class parents are not only more likely to possess the material resources or economic
capital to enable their offspring to engage in sport, but they are also more likely to be in a
position to transfer their social and cultural capital by virtue of being already actively involved
themselves and inclined to pass on their ‘love of sport’. (36)
These current findings also highlight the relationship between the higher age and
incomes of parents, but the plateauing of participation numbers suggests this pre-dis-
posed favourably motivated market has largely been tapped. There is a need to
promote the ITTS through support (Emmett, Havitz, and McCarville 1996)tonon-
14 A. J. MARTIN ET AL.
participating or under-represented groups (e.g. Māori and Pacific Islanders), especially
younger aged parents and lower income families. Developing initiatives that encourage
diversification of participant demographics will help increase opportunities alongside
more welcoming environments aimed at enhancing family participation, as emphasized
by Misener and Mason (2006).
Conclusions
The findings, related to the primary research question examining children’s motives for
participation in triathlon as a function of age, indicated that there was a clear multi-
linear relationship between the starting age of the children in the ITTS and their partici-
pation. Overall, the main findings from this current study are:
(a) Age should not be considered as the single factor in sport participation motives
(b) Age is a highly connected and important networked factor in the multi-dimensional
personal motive patterns
(c) In the sport activity motive patterns of younger (<6) and older (>9) children, their age
appears in two completely different contexts (see Figures 3(a,b))
(d) There is continuous age-dependent transition from the younger (<6) into the older
(>9) children’s motive pattern
(e) Future promotion can be targeted differently to several specific sub-populations of
potential participants (and their families), identified by our findings.
Implications
The results of this study can be used to re-design programmes to enhance children’s sport
participation motives and commitment. It is hoped that these findings can be reviewed to
develop future actions, which can then be implemented by the regional community-based
triathlon event organizers to increase triathlon participation to the ITTS event. For
example, from a practical angle, our results indicate that one target group to promote
the ITTS to are higher income families with young children and siblings and parents
who are currently not involved. Future promotion can also target differently several
specific other sub-populations of potential participants identified from the findings.
Low-cost entry and central city location have enhanced the event’saffordability,
although equipment cost (bikes etc.) may provide a financial barrier to entry or for contin-
ued triathlon event involvement. Hence, through support, there is an opportunity to
promote the ITTS to non-participating (e.g. low-income families) or under-represented
groups (e.g. Māori and Pacific Islanders). There is also strong perceived event attraction
evident. This point is further enhanced by the children’s main perceived factors for decid-
ing to participate were not individual motive factors, but rather multi-component patterns
that incorporate fun, enjoyment involving friends, competition, challenge, and fitness, as
well as tangible outcomes such, as sport prizes, goodies and medals. However, an interest-
ing finding of this current study is the importance of differentiating age and gender
motives, involving a network of peers, the whole family and other sport involvement in
engaging children’s future participation in sport. This finding related to differentiating
gender motivations merits further research attention.
ANNALS OF LEISURE RESEARCH 15
In 2018, the number of children participating each week in the ITTS increased some
15% on the 2015 numbers, a growth from an average 660 to a record 756. Initiatives
that may have helped this increase are greater use of social media, such as Facebook,
to enhance peer and whole family, and school engagement. The local Regional Sport
Trust has also promoted participation and coaching programme initiatives, encouraging
school age children from low-income families to learn to swim and bike, particularly
amongst underrepresented schools. To enhance commitment, entry fees have been dis-
counted for pre-entry for the ITTS on-line (US$15, NZ$20), rather than a weekly fee, and
all participants receive a sponsored ‘free’t-shirt. Also to encourage involvement, junior
membership to the MTC now includes free entry to the ITTS, and free entry to subsequent
events throughout the year.
It is hoped that further research involving data relationship-based analysis, examining
the impact of social media initiatives, and the effectiveness of entry-level sport partici-
pation programmes will provide greater insights for developing whole community phys-
ical activity initiatives and help similar voluntary sport organizations to increase event
participation levels.
Disclosure statement
No potential conflict of interest was reported by the authors.
Funding
Petr Pancoska work on this project was funded by the Ministry of Education, Youth and Sports of
Czech Republic, grant ERC-CZ LL1201.
Notes on contributors
Andrew Martin, Ph.D., is a Professor in Sport Management and Physical Education at Massey Univer-
sity, New Zealand.
Rachel Batty, Ph.D., is a Lecturer in Sport Management at Massey University, New Zealand.
Ashleigh Thompson, Ph.D., is a Lecturer in Sport Management at La Trobe University, Australia.
Robert Kuchar is completing his Ph.D. at the Prague School of Economics, Czech Republic.
Petr Pancoska, Ph.D., is a Research Associate Professor at the University of Pittsburgh, USA and visit-
ing Professor at Charles University, Prague, Czech Republic.
ORCID
Andrew J. Martin http://orcid.org/0000-0002-4958-2609
Ashleigh Thompson http://orcid.org/0000-0001-9391-743X
Petr Pančoška http://orcid.org/0000-0002-6724-8559
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Appendix
Table A1. Questionnaire used in this study.
Partition Variable Questionnaire section
1 Parent age
2 Income
3 Child age
4 Tri age S1 –Demographic questions
5 Child gender
6 Child ethnicity
7 No. brothers
8 No. sisters
9 Tri brothers
10 Tri sisters
11 Tri years S2 –Participation in other Triathlon events
12 Tri’d Tri event
13 Weetbix event
14 InterSchool event
15 Parent involved
16 Parent trainer
17 Parent volunteer
18 Parent other S3 –Parent participation
19 Parent physically active
20 Extended family involved
21 Friends involved
22 Tri’d investment
23 Weetbix investment
24 InterSchool investment
25 Tri money S4 –Participation costs
26 Tri bike bought
27 Tri apparel expensive
28 Tri equip expensive
29 Training before Tri
30 Child selected Tri
31 Why child participate
32 Child enjoyment
33 Child competition S5 –Participation motivation
34 Child challenge
35 Child social
36 Child achievement
37 Child active
38 Child sport skill
39 Child sport participation
40 Outlook 2 yrs
41 Outlook 4 years
42 Outlook 6 years S6 –Motivations and intentions
43 Outlook 8 years
44 Outlook 10 years
45 In other tri
46 What equipment
47 How aware
48 Reason 1 to participate
49 Reason 2 to participate S7 –Enjoyment in participating
50 Reason 3 to participate
51 Reason 4 to participate
52 Most enjoyed
53 Least enjoyed
54 Favourite sport child
55 Sport sel. Reason1
56 No tri sports S8 –General sport participation and physical / activity
57 Sport training classes
58 Most competitive sport
ANNALS OF LEISURE RESEARCH 19
