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Abstract and Figures

Learning to ride a bicycle is an important milestone in children’s life, so it is important to allow them to explore cycling as soon as possible. The use of a bicycle with training wheels (BTW) for learning to cycling independently is an old approach practiced worldwide. Most recently, a new approach using the balance bike (BB) has increased, and several entities believe that this could be most efficient. Drawing on the work of Bronfenbrenner (1995) and Newel (1986), this study aimed to analyse the effect of BB’s use on the learning process of cycling independently. Data were collected in Portugal from an online structured survey between November 2019 and June 2020. A total of 2005 responses were obtained for adults and children (parental response). Results revealed that when the balance bike’s approach was used, learning age (LA) occurred earlier (M=4.16 ± 1.34 years) than with the bicycle with training wheels’ approach (M=5.97 ± 2.16 years) ( p <0,001); or than when there was only the single use of the traditional bicycle (TB) (M=7.27 ± 3.74 years) ( p <0,001). Children who used the BB as the first bike had a significant lower LA than children who didn´t use it ( p <0.001). To maximize its effects, the BB should be used in the beginning of the learning process.
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Learning to Cycle: from Training Wheels to Balance Bikes
Learning to ride a bicycle is an important milestone in children’s life, so it is important to allow
them to explore cycling as soon as possible. The use of a bicycle with training wheels (BTW) for
learning to cycling independently is an old approach practiced worldwide. Most recently, a new
approach using the balance bike (BB) has increased, and several entities believe that this could
be most efficient. Drawing on the work of Bronfenbrenner (1995) and Newel (1986), this study
aimed to analyse the effect of BB’s use on the learning process of cycling independently. Data
were collected in Portugal from an online structured survey between November 2019 and June
2020. A total of 2005 responses were obtained for adults and children (parental response).
Results revealed that when the balance bike’s approach was used, learning age (LA) occurred
earlier (M=4.16 ± 1.34 years) than with the bicycle with training wheels’ approach (M=5.97 ±
2.16 years) (p<0,001); or than when there was only the single use of the traditional bicycle (TB)
(M=7.27 ± 3.74 years) (p<0,001). Children who used the BB as the first bike had a significant
lower LA than children who didn´t use it (p<0.001). To maximize its effects, the BB should be
used in the beginning of the learning process.
Balance bike; bicycle with training wheels; learning to ride a bicycle; cycling; Portugal.
1. Introduction
Humans have different natural modes of locomotion, such as walking and running. With the
cultural evolution of our species, the bicycle was invented as a transport vehicle, being more
efficient, economic and less tiresome than our natural modes of locomotion (Herlihy, 2004).
Nowadays these invention won a very important role in human life, it is used everywhere for
transportation, exercise, sports competition or simply for recreation (Astrom et al., 2005;
Oosterhuis, 2016). Cycling also proved to be an activity that improves health. It has a positive
relationship with cardiorespiratory fitness in youths, cardiovascular fitness in adults, and a
strong inverse relationship with all-cause mortality, cancer mortality and morbidity in middle-
aged and elderly people (Oja et al., 2011). In children, cycling also has several health benefits,
like better cardiorespiratory fitness, less body fat and less incidence of metabolic syndrome
(Ramírez-Vélez et al., 2017). There are also social benefits, such as the development of relational
and emotional skills, promoting fun play moments where children can interact with other
people, and make new friendships (Handy and Lee, 2020; Karabaic, 2016; Orsini and O’Brien,
2006). In addition, cycling allows for a greater exploration of the environment mobility, enabling
children to become more independent and active (Smith et al., 2017). Cycle trains are a good
example of this, children travel to school by bicycle and stop at their colleagues' houses
increasing the train until school (Smith et al., 2020). Most recently the active transport in
children, including cycling, has also revealed an positive association with academic achievement
and cognition (Phansikar et al., 2019), contributing further for their physical, mental and social
wellbeing (Ikeda et al., 2020; Stark et al., 2019).For all these reasons, learning to ride a bicycle is
an important milestone in children’s life (Linus et al., 2015), so it is important to allow children
to explore cycling as soon as possible.
The present study draws on the theoretical juxtaposition of the Bioecological Theory of
Bronfenbrenner (1995) and Newell’s model of constraints (1986) applied to the learning
pathways of bicycles sequences that children go through until they are able to cycle
independently and without training wheels.
According to Bronfenbrenner, the child’s development occurs within interactions and
relationships between the child and his/her environment (Bronfenbrenner, 1995, 1979). The
different layers of environment affect the child’s development, including motor development
and the learning of new skills, such as learning how to cycle. The initial model proposed by
Bronfenbrenner (Bronfenbrenner, 1979) considered the following layers : micro-, meso-, exo-,
and macrosystem (Bronfenbrenner, 1979). At a later stage (Bronfenbrenner, 1995), time was
included into the model and the chronosystem dimension was added. The different
microsystems consist in a set of environments where the child can engage in face-to-face
interactions with other people, for example family, friends or community institutions like the
school are examples of microsystems. If the microsystems the child interacts with value cycling,
and if the child has access to a bicycle since an early age, it is more likely that he or she will learn
to ride a bicycle earlier than if cycling and having a bicycle are not valued or prioritized. Parents
encouragement is a key factor not only to cycle learning (Temple et al., 2016) but also for
increase cycle practice (Emond and Handy, 2012). The mesosystem comprises the interactions
between the different microsystems, for example the relationship between the child’s family
and the school. If the school launches a “bike to school” campaign and the family has a good
relationship and an active participation in the school, it is more likely that they will join that
campaign (Emond and Handy, 2012). The exosystem includes contexts where the child is not
directly involved but that can have an indirect effect on him/her, such as the availability of
community programs for cycling in the child’s neighbourhood or the media promotion of active
transport and cycling. The existence of a community program to promote cycling in family can
enhance bicycle’s use and learning from an early age (Alad Limited, 2002; Chandler et al., 2015).
The macrosystem consists in societal, cultural and global influence, which can include the
cultural value given to cycling, the papers attributed to genders or simply the laws and
governmental policies. If the government promotes safe conditions for cycling, for example
through bike paths’ construction or protective laws for cyclists, an increase in cycling is expected
(Florindo et al., 2018). Finally, the chronosystem adds the dimension of time, for example the
era in which the child lives also influences the value given to cycling, the age at which the child’s
parents will give him/her a bike, and the type of bike the child will be given (if any).
In our perspective, when looking at the milestone of learning to ride a bike, Bronfenbrenner’s
theory shares a common ground with Newell’s model of constraints (1986), namely in terms of
what Bronfenbrenner & Morris (1998) describe as four fundamental properties (person, context,
time and process), which dynamically interact with each other in order for developmental
acquisitions to occur. Process is the central intermediate element of the model as it represents
particular forms of interaction that occur over time between the person and the environment.
These reciprocal interactions, designated of proximal processes, progressively become more
complex and are considered the key agents of human development (Bronfenbrenner & Morris,
1998). However, the degree of influence these proximal processes have on development vary
according the interrelationship given by the evolving person’s characteristics, the immediate
and more distal environmental contexts, and the time periods of these interactions
(Bronfenbrenner & Morris, 2006). Similarly, in a more microscopic scale, according to Newell
movement arises from the dynamic interaction between individual, task and environmental
constraints (Bronfenbrenner, 1995, 1979; Newell, 1986). Individual constraints consist in the
features of the system itself like age or motor competence. Probably children with a better
motor competence and a greater motor repertoire will learn to ride a bicycle more easily
(Rodrigues et al., 2019). Task constraints consist in modified features related to the task itself
like the instrument used, time or frequency. For example, several institutions believe that the
balance bike can be more efficient for learning than the bicycle with training wheels (PCF, 2020a,
2020b). Finally, environmental constraints are features related to the physical environment like
the weather or to the sociocultural factors like the family context. In this sense, the dynamic
proximal processes between the child and the environment advocated by Bronfenbrenner’s
theory, are also present in Newell’s model. According to this model, these proximal interactions
between the different constraints are fundamental and if any constraint changes, the resultant
movement changes. Sometimes constraints change mildly (e.g., when the individual constraint
of the height of the child changes it might be necessary to adjust the height of the bike), but
sometimes constraints change more abruptly (e.g., changing a task constraint such as taking the
training wheels out will interact with the child’s ability to keep balance).
To learn how to ride a bicycle the combination of constrains and possible pathways are endless.
For example, the child can learn alone, with parents, friends; can practice in the street, cycle
path or dirt; use a balance bike, bicycle with training wheels or simply the traditional bike.
The learning process is always individual and complex. Each system, each human being, is unique
and is influenced by the sociocultural environment and by different constraints
(Bronfenbrenner, 1995, 1979; Newell, 1986). The variability of possible pathways to learn how
to cycle, is probably one of the reasons why the better or the most efficient methodology and
type of bike used for learning is still not consensual.
The use of the bicycle with lateral training wheels (BTW) is a worldwide practice, however not
everyone agrees with this approach (Becker and Jenny, 2017; Shim and Norman, 2015).
Recently, the use of the balance bike is increasing. A balance bike (BB) consists in a bicycle
without the training wheels or pedals, so children should use their feet against the ground to
propel themselves. Several institutions including the Portuguese Cycling Federation (PCF) and
the Biciculture House in Portugal believe that using a BB instead of the traditional BTW improves
the learning process. For this reason, some initiatives of the PCF, such as the “Cycling for
Everyone and the Cycling Goes to Schoolprovide balance bikes for children who do not know
how to ride (PCF, 2020a, 2020b).
While the traditional and old approach with BTW allows children to explore the pedalling being
balanced by the training wheels, the new approach with BB works the other way around,
allowing children to first explore the balance in the bicycle, and then introducing the pedalling
(Figure 1). Despite the empirical experience of bicycle instructors that prefer to use BB and the
positioning of recognized entities like PCF, the scientific literature that supports balance bike’s
use is very scarce. In this sense, the present article aimed to study the influence of balance bike’s
use on the process of learning to ride a bicycle independently adopting a bioecological approach
to such a relevant acquisition in terms of children’s motor development. More specifically, we
aimed to: i) verify if the BB’s use is related with a possible decrease in the learning age of
independently cycling (LA) over decades; ii) identify the most common learning pathways of
bicycles sequence (learning paths); iii) verify if the learning paths are related with the LA; iv)
analyse and compare the LA between children who used and did not used BB.
Figure 1 Old and new approaches for learning to cycle independently: A using training wheels; B
using the balance bike.
2. Methodology
2.1. Survey
Data were collected using an online survey. During the pilot phase, an initial version of the survey
was developed by a group 4 of experts in child development and was tested online on 485
participants. A sub-sample of 30 participants was additionally inquired about the
comprehension of the survey. After that, some adjustments were made. For example, one group
related to the dates of acquisition of different motor milestones was deleted and some
questions were reformulated to improve clarity according to the respondent’s suggestions. At a
second stage, the survey was discussed with a group of 5 international experts who provided
further suggestions (e.g., adding questions regarding mother tongue and different seasons of
the year). Finally, the survey was translated for different languages and is now available in 10
languages (Portuguese from Portugal and Brazil, English, German, Croatian, Finish, French,
Dutch, Italian, Japanese and Spanish). For the current article, only the Portuguese data were
analysed. The final Portuguese version was launched online on November 22, 2019 and data for
the current study were collected between that date and June 8, 2020. The survey was publicized
in the national conference on Child Development and disseminated through social media
(Facebook, Instagram, WhatsApp), and by email. In addition, partnerships with the PCF and kids
and parent’s magazines were established for dissemination on their websites and paper
The survey takes approximately 5 to 15 minutes to complete (depending on the number of
children), it is anonymous and comprises 3 sections:
1. “About you” - Questions about the participant’s own experience and biographical data (e.g.,
place of residence, age, gender, physical activity habits, if they know to ride a bike, if not why
not, if yes - when did they learn, what types of bikes were used and in what sequence, where
did they learn, who taught them, how often do they ride a bike, what do they use it for).
2. “About your older child” (to be completed only if the participant has children) - These
questions are the same as the questions in the first group but regarding the participant’s older
3. “About your younger child” (to be completed only if the participant has more than 1 child) -
These questions are the same as the questions in the first group but regarding the participant’s
younger child.
This survey was approved by the Ethics Committee of the ******* (approval number: 22/2019).
2.2. Sample
The survey was completed with information regarding 2386 participants. For the present study
only participants who could ride a bicycle independently were considered (n=2005). Participants
age ranged from 2.39 to 60.18 years (M=27.97 ± 14.7 years). In order to analyse differences in
learning to ride a bike across generations, the birth decades of the participants were considered.
Regarding geographical location, we collected data from participants in all 20 Portuguese
districts and the 2 autonomous regions, Madeira and Azores. Descriptive data of the sample is
presented in Table 1.
Table 1 Descriptive data regarding age and sex of the participants by decade and total
Decimal Age (yrs)
Gender (n)
M ± SD
Don’t want
to say
55.05 ± 2.70
44.53 ± 2.75
35.65 ± 2.92
23.79 ± 2.88
15.92 ± 3.20
7.34 ± 1.81
27.97 ± 14.7
2.3. Statistical Analysis
Data extracted of LimeSurvey was organized and codified by a Matlab routine specifically
developed for this purpose. The data were later processed in the software Statistical Package
for the Social Sciences (SPSS, version 25).
Analyses of frequency and Chi-Square tests were used to investigate the differences in the
percentage of BB’s use between consecutive decades. ANOVAs one-way were performed to
assess differences in the learning age across decades and between different learning paths (i.e.,
considering the order of use of the BB). In cases of non-homogeneity, the Welch correction was
applied. To investigate significant differences between groups, the Bonferroni or the Games
Howell post hocs were used, depending on the existence or not of homogeneity of variances
(Field, 2013). The level of significance was set at .05.
2.4. Sample Calculation
Sample calculation was performed a posteriori with the software G*Power (version For
this calculation it was performed and considered the effect size of the main variable, age
learned, from the data of test’s version which revealed an effect size of 0.1. The calculation was
conducted to ANOVA one-way and considered the question with the lowest sample, 1341, and
the higher number of groups, 8, with a significance level of 0.05. This sample calculation
estimated an observed power of 0.76.
3.1. Learning age over decades
Learning age changed significantly over the decades (F(7, 786) = 41.79, p <0.001, ηp2 = 0.07).
Considering consecutive decades, only a non significant increase between 1960-69 and 1970-79
(Figure 2) was found. After that the LA always decreased, being the difference significant
between 1970-79 and 1980-89 (p=0.01), and between 2000-09 and 2010-2019 (p<0.001).
Figure 2 Evolution of learning age according to decades, mean and 95% confidence interval.
1960-69 1970-79 1980-89 1990-99 2000-09 2010-19
Learning Age (years)
3.2. Use of BB’s over decades
Results regarding the types of bicycles used to learn, indicate that the percentage of people
using the BB has increased over time from 9.6% (for people born in the 1960’s) to 49.2% (for
people born between 2010 and 2019). The percentage of people using the BB increased rapidly
in this millennium, since when analysing consecutive decades, we found significant differences
between the decades of 1990-99 and 2000-09 (χ2(1) = 6.32, p=0.012); and between 2000-09 and
2010-2019 (χ2(1) = 55.02, p<0.001) (see Figure 3).
Figure 3 Balance bike’s percentage of use according decades.
3.3. Learning Paths
The type of bikes and order in which those bikes were used during the learning process defines
the different learning paths that were used. We considered the possible use of 4 types of bikes
during the learning process: the balance bike (BB), a bike with 2 training wheels (BTW), a bike
with just 1 training wheel (B1TW) and the traditional bike with no training wheels (TB). The
learning paths emerge from any combination between the order of use of these bikes that ends
with the TB. In the present article the learning paths are represented by a sequence of 4
numbers, the position of the number represents the type of bike used and its value represents
the order. More specifically, the first digit represents the BB, the second represents the BTW,
the third represents B1TW and the fourth represents the TB. So, if the child presented a learning
path of 1002 it means that the BB was used in first place, the BTW or B1TW were not used, and
the TB was used in second place. If one digit is repeated (e.g., 1102), it means that the child used
those bikes simultaneously.
9.6 12.7 11.7
1960-69 1970-79 1980-89 1990-99 2000-09 2010-19
Percentage of use (%)
Of all the possible combinations, we found 29 different learning paths in our sample, but only
the learning paths that were used by at least 30 participants were considered for analysis (Figure
Figure 4 Learning age according learnings paths, mean and 95% confidence interval.
Note: Each digit in the learning paths corresponds to order of use of one specific type of bicycle, first digit - balance
bike; second digit - bicycle with 2 training wheels; third digit - bicycle with 1 training wheel, fourth digit - traditional
bicycle. Error bars represent 95% Confidence Intervals.
Results indicated that the LA is significantly different depending on the learning paths used (F(7,
194) = 26.83, p <0.001, ηp2 = 0.08). Descriptive statistics of the learning age according to the
different learning path and results of the post hoc analyses are presented in Table 2.
Table 2 Descriptive statistics of learning age according learning paths
M ± SD
95% CI
Games Howell
Significant Differences
4.16 ± 1.34
All*** except 1203
4.63 ± 1.44
All*** except 1002
5.64 ± 1.99
0001***, 0123***, 1002***,
5.90 ± 1.69
0001***, 1002***, 1203***
5.97 ± 2.16
0001***, 1002***, 1203***
6.03 ± 1.73
0001***, 1002***, 1203***,
6.78 ± 2.98
0001***, 1002***, 1203***
7.27 ± 3.74
Notes: first digit in learning path - balance bike; second digit - bicycle with 2 training wheels; third digit - bicycle with
1 training wheel, fourth digit - traditional bicycle; ***p<0.001; **p<0.01; *p<0.05.
4.16 4.63
5.64 5.90 5.97 6.03
6.78 7.27
1002 1203 1234 3124 0102 0123 0101 0001
Learning Age (years)
Learning Paths
The learning path with the lowest learning age (M=4.16 ± 1.34 years) was the one where the BB
was used first and then TB (1002). Considering these values, and using the mean minus the SD
as a reference, we believe that by 2 and a half years of age, children seem to be ready to start
using the balance bike. People who used the BB first and then TB had a significant lower learning
age (p<0.001) than people who used any of the others other learning paths except using the BB
first, 2 training wheels second and then TB (1203). The traditional learning approach, which
starts by using the 2 training wheels and then TB (0102) had a mean LA of 5.97 ± 2.16 years. The
learning path with the highest learning age was the single use of the TB (0001), with a mean age
of 7.27 ± 3.74 years, a value significantly higher than all the other learning paths (p<0.001).
3.4. Order of use of the Balance Bike
Considering not the learning path, but the order of use of the balance bike in the learning
process, there were significant differences in learning age depending on the moment the BB was
used (F(1, 4) = 9,88, p ≤ 0.001, ηp2 = 0.02). The lowest learning age occurs when the BB is used
first (M=5.13 ± 2.89 years), while the highest learning age occurs when the BB is not used
(M=6.32 ± 2.13 years). The group who used the BB first learned at a significant earlier age than
the groups that never used it (p<0.001) or that used it in 4th place (p<0.001). Analysing
differences between pairs (Figure 5), the non-use and 1st use were significantly different
(p<0.001), and also the 1st and 4th use (p=0.022).
Figure 5 Learning age according to the order of use of balance bike, mean and 95% confidence
Note: Significant differences with ***p<0.001; **p<0.01; *p<0.05
5.68 5.93 6.30
Not used 1st used 2nd used 3rd used 4th used
Learning Age (years)
Balance Bike's Orde Use
4. Discussion
4.1. Relation between BB’s percentage of use and the learning age over time
Although the BB’s boom in Portugal was recent, our results indicated that at least since the
1960s some people mentioned to have used it in the process of learning to cycle independently.
Looking from an historical perspective, the BB is very similar to the first bicycle model. The
bicycle was created in 1817 by Karl Drais and it consisted in a wooden prototype just with two
wheels, without chain, brakes or pedals. So, riders should propel the bike by pushing the floor
with their feet (Andrews, 2017; Herlihy, 2004). Maybe this bicycle model persisted in some way
over time. It is also possible that even after the general commercialization of the training wheels,
some people still chose to remove the pedalboard and let children play with the bicycle instead
of using the training wheels. We could identify the biggest boom in the use of the BB between
2000-09 and 2010-2019. Decathlon, one of biggest sport articles retailers in Portugal started to
sell BBs in 2012-2013, and some of the biggest supermarkets also started to commercialize it
around the same time. In this decade the media also started to include images of balance bikes
in commercials. The bigger dissemination of the BB also lead entities like PCF to include it in their
cycling programs (PCF, 2020a, 2020b). Some municipalities have even started to make BBs
available in preschools to promote earlier cycling (Mirante, 2019). All of these interactions
between the macrosystem (cultural views in biking and healthy lifestyles), exosystem (cycling
programs in the municipality and BB incorporated in media), mesosystem and microsystem
(opportunity to explore the BB in school and with friends), added to the fact that the BB became
more accessible to consumer, contributed to the significant increase of the BB’s use.
Children born during the last decade (i.e., 2010-2019) had the lowest learning age compared to
the other groups. However, the results of this decade should be considered with caution. Due
to the historical proximity of this period, some of the participants born in the last years of this
decade still haven´t learned how to ride a bicycle. Thus, early learners might be slightly over-
represented in the last decade. Nevertheless, the tendency for a significant decrease in learning
age across decades was clear. Considering that the BB’s use increased significantly in the last
two decades, it is possible that the decrease in learning age is associated with the increase in
the use of BB.
4.2. Learning Paths
We found a great variability of learning paths in our study, which underlines the fact that the
same motor developmental state can be achieved over different pathways (i.e., equifinality, see
Waddington, 1957).
The most frequent learning path was the traditional approach (n=630), using first the bicycle
with 2 training wheels and then the traditional bike (learning path 0102). This data reinforces
the idea that training wheels are a practice ingrained in the culture of learning to ride a bicycle.
The second most frequent learning path is the one with the higher learning age, the single use
of TB (n=404, learning path 0001). Although it does not seem to be a path that facilitates
learning, this high frequency might result from a lack of availability of other type of bike. If the
child has no opportunity to explore the BB or the training wheels, he/she probably will learn by
just using the TB. The first use of 2 training wheels followed by 1 training wheel and then the TB
(learning path 0123), follows as the third most frequent path (n=364), highlighting once more
the training wheels culture. After this, using first the BB and then the TB is the next most
frequent learning path (n=54, learning path 1002). The BB’s use has a significantly increased
(p<0,001) in the last decade (Figure 2), so it is expected that the frequency of the learning paths
involving the BB and, namely this new approach for learning, will increase in future.
The child’s learning path occurs in specific socioecological contexts, from proximal to distal
(Bronfenbrenner, 1995) and is shaped at every moment by the interaction between the existent
constraints (Newell, 1996). The parents support during cycling learning, is related to the
microsystem layer; the community culture and cycling programs, to the mesosystem layer; the
media promotion of training wheels or balance bike, to the exosystem layer; a culture that
values and promotes cycling, to the macrosystem layer. All these environments have the
potential to shape the child’s learning path. In addition, the child’s individual constrains will also
influence the learning process. For example, a poor body composition (BC) is associated with a
lower balance ability (Deforche et al., 2009; Kakebeeke et al., 2017; McGraw et al., 2000; Pau et
al., 2012). Considering that balance is fundamental for cycling, and particularly challenging in
the initial stages of learning, children with a poor BC will probably have more difficulty in learning
how to cycle independently. The lack of balance can also interact with other individual
constraints, such as the child’s motivation to learn. If a child constantly struggles to keep balance
and falls frequently during the first stages of learning, he/she will be more likely to develop a
fear of falling and to start avoiding cycling to prevent injuries. Conversely, if the child has a good
motor competence, it’s expected that he/she feels experiences more success during learning,
feels more motivated and learns to ride a bicycle earlier (Robinson et al., 2015; Stodden et al.,
2008). Finally, the task constraints also play an important role in the learning process. The fact
that different learning path, using different types of bikes significantly influenced learning age
learning age in our study, highlights the importance of the task constraints in the dynamic
process of learning how to ride a bike.
The most successful path for learning (i.e., the path with the lowest learning age, around 4 years
of age) seems to be to use the BB first and then the TB (0102). On the other hand, using the 2
training wheels first and then TB (0102) seems to postpone learning to a later age (around 6
years of age in our study). In a direct comparison between these two approaches (Figure 1), it
seems that the newest approach, with the balance bike indeed promotes a significant faster
learning than the older, with training wheels. In average, in the present study, kids who
transitioned directly from the BB to the TB learned to ride 1.81 years earlier than kids who
transitioned from the TW to the TB.
By analysing the learning paths sorted increasingly by learning age (Figure 4), it is possible to
verify that in the first three paths, with the lowest learning ages, the BB was used the first. In
the fourth path, the BB was used third, and in the last four paths, with the highest learning ages,
it was not used. This confirms the association between the use of the BB in the learning process
and a lower learning age. Some authors consider that balance is the most difficult challenge in
the process of learning how to cycle (Becker and Jenny, 2017; Shim and Norman, 2015). The
balance bike improves balance from an early stage, not focusing on the pedalling coordination
and maybe this is the key for its success.
The BB allows children to explore several movement patterns while using it, they can walk, run,
propel the bike with both feet or just one, and can also explore the flight phase when they
experience balance for increasing amounts of time without any contact of the feet with the
ground. While doing this, children are exploring and learning to control their centre of gravity
and the bicycle's centre of gravity, as they learn to keep balance on the bicycle.
With the BTW children develop first the ability to pedal and balance is not a challenge because
it is guaranteed by the training wheels. So, when children transition from the BTW to the TB
removing the training wheels, they have to learn how to balance and there is a greater instability
associated with the pedalling. This approach seems to pose a greater challenge than mastering
balance first and feet coordination afterwards. t should be noted that all the paths fulfil the
purpose, all allow children to learn to ride a bicycle, but some of them are faster than others.
The learning path with the highest learning age consisted in the single use of TB, with a mean of
7.27 ± 3.74 years. In this approach, the initial challenges are great since there are no training
wheels to guarantee the balance and the pedals are already there to be used. The child should
simultaneously learn how to balance, pedal, break and turn. This seems to be a too much
complex task, leading to a longer duration of the learning process.
4.3. Order of use of Balance Bike
The importance of using the BB in the beginning of the learning process is clear if we look at the
learning age according the order of use of the balance bike (Figure 5), learning path. Using the
BB first afforded a significant lower LA that not using it (p<0,001). The task constraint of using
the BB influences the learning process (Newell, 1986), but that influence should occur earlier in
the learning process, since as BB ceases to be prioritized, its effect decreases. Possibly this
happens not because of the BB itself, but because of the introduction of another types of bikes
that require different types of adaptations from the child and cause more noise in the learning
process. When the BB wasn´t the first bike used generally it means that children started to
explore the pedalling before testing their balance and exploring balance at a later stage does
not seems to be the best option since it costs time. When BB is used in the last place the effect
is almost lost and the learning age significant differs from when its used in the first place
4.4. Strengths and weaknesses
Learning how to ride a bike is an important milestone in children’s life (Linus et al., 2015) and it
can also be seen as a public health question due to its benefits. The major strength of this study
was to address the existent gap in the literature concerning the influence of using the BB on this
learning process. Although our results clearly support the general feeling that exists among bike
instructors that the BB accelerates learning, due to the characteristics of this study (i.e., online
survey), we could not analyse the learning process in a more individual basis. The results show
that learning how to cycle independently is a process quite sensitive to the task constrains,
specifically to the type of bicycle used, but the influence of specific individual constraints, such
as body composition (Deforche et al., 2009; Kakebeeke et al., 2017; McGraw et al., 2000; Pau et
al., 2012) or motor competence (Rodrigues et al., 2019) on this task should be addressed in
studies with a different design (e.g., smaller sample of children followed longitudinally during
the learning process) . This type of studies would also allow us to better understand the process
of mastering to control the balance bike and to explore its flight phase during the initial learning
stages. Finally, the comparison between the learning process among different cultures can be
explored in the future.
5. Conclusion
To our knowledge this is the first large scale study to investigate the influence of using a BB in
the process of learning to ride a bicycle independently. Our results indicate that using a BB,
particularly during the first stages of the learning process, leads to a significant decrease in the
learning age for this motor milestone. The use of the BB has been increasing along decades
accompanied by a decrease in the average age for learning, which in Portugal has been more
marked since the beginning of the millennium. There are different benefits of learning how to
cycle earlier. For example, children who begun to cycle at an early age are more likely to have a
healthy weight in the next schools years (Pabayo et al., 2010), they can have fun moments
cycling outdoors with peers or family, they develop motor component and mature their social
and emotional skills (Karabaic, 2016; Orsini and O’Brien, 2006). Although a great number of
learning paths will always continue to exist, it seems that the sooner children master balance,
the earlier they will be able to control the TB. The difference in the learning age for cycling
independently varies in 2 to 3 years depending on the learning path and the type of bikes used.
This temporal gap could have an impact in children’s life, so it’s important to promote the best
approach for learning how to cycle as soon as possible, which seems to be the one that uses the
BB first. Based on the data, it is suggested to start learning to cycle at about 2 and half years of
age by using the balance bike.
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... The age span of participants in these studies ranged from four to 18 years. In typically developing children, the intervention age could probably be even lower, since some studies indicate that many three-year-old children can learn how to ride a bike (Mercê et al. 2021). ...
... Training bicycle: training wheels, balance bike, roller and tandem bicycle It is possible to use different types of bicycles in the process of learning to ride a bike, the most typical are the training wheels and the balance bike (Cain, Ulrich, and Perkins 2012). In Europe, especially in southern countries, the use of the balance bike is relatively recent, e.g. in Portugal, there was a significant increase after 2000, and using training wheels remains the most common learning method (Mercê et al. 2021). Despite its popularity, using training wheels for learning is not considered to be a good method in almost all the analysed studies. ...
... In fact, when no progressive learning strategies are used, the age to learn how to cycle independently increases. A recent study by Mercê et al. (2021) indicates that children who exclusively use the conventional bicycle learn to cycle significantly later than children who used other learning paths (e.g. using the balance bike or training wheels). When children learn how to cycle by simply using the conventional bicycle, with pedals and no support, they must learn how to manage the breaks, the handlebar, the pedals and acquire balance all at once, which seems to be too complex, resulting in a later learning age. ...
Background: The bicycle is a popular means of transportation, exercise, recreation and also socializing for children worldwide, allowing them several physical and psychological benefits. Several methodologies and types of bicycles have been used for learning how to cycle, however, the best approach is still unclear. Purpose: The purpose of this study was to review and summarize the existent studies of programmes that aim to teach children how to ride a bicycle independently, in order to identify which possibilities lead to a more efficient intervention. Methods: A comprehensive search was performed in seven electronic databases (TRID, CENTRAL, Web of Science, SCOPUS, EBSCO, ProQuest Dissertations and Theses and Google Scholar), including grey literature and the citations of relevant articles, from their inception to April 2020. Studies were included according to the eligibility criteria: children and youths aged 18 or less, with and without disabilities; intervention programmes that aimed to teach how to ride a bicycle with a pre- and post-intervention assessment regarding the ability to ride. The Downs and Black checklist was used for quality assessment. Results: Nine intervention studies, including a randomized controlled trial, were included. The mean quality score was 11.8 ± 3.6 points. Just one of the included studies was targeted at children without disabilities. Different facilitating constraints and barriers were identified, which resulted in a list of tips for future intervention programmes to teach children how to ride a bicycle. The facilitating constrains were using a progressive learning strategy; using an individualized approach; making bicycle adjustments; having motivated children and having family support throughout the learning process. The barriers were: the fear of falling; lack of parents’ support; and lower leg strength. Learning to cycle was also associated with a decrease in sedentary time, increase in physical activity, improvement in leg strength, and a positive influence on body composition, indicating that it can be a solution to disrupt the cycle of consistent weight gain over time in children with disabilities. Conclusions: There is a gap concerning intervention studies to teach children without disabilities how to cycle. The best strategy is probably a progressive learning strategy by using simpler training bicycles that enable the child to explore balance from the beginning, and simpler exercises first. Teaching programmes should adopt an individualized intervention, feedback and motivation, considering each child’s specific characteristics.
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Active school travel contributes to children’s physical, mental and social wellbeing. The prevalence of children’s active school travel, however, has been declining in many developed countries. Gaining insights into school culture and environments in relation to school travel behaviour is crucial to inform interventions. Using a multiphase mixed methods approach, this study aimed to provide a comprehensive understanding of how school policies and practices supported or inhibited school travel behaviour in Auckland, New Zealand. Data were drawn from Neighbourhoods for Active Kids, a cross-sectional study of 1085 children aged 8–13 years between February 2015 and December 2016. School representatives were interviewed regarding their policies and practices related to school travel behaviour and traffic around school, and the data were analysed thematically. An overarching theme, sub-themes and categories were contextualised for quantitative modelling using objectively measured school variables (school socioeconomic status, active school travel programme, built environments around school). Mixed effects multinomial logistic regression models were employed to determine associations between school travel mode and objectively measured child (sociodemographic characteristics, traffic safety perceptions) and school variables. Safety was the core concept of school travel policies, procedures and programmes. Significant differences in child variables, school socioeconomic status, and cycle lanes and traffic lights around school were found between children who actively travelled or used public transport to school and those driven to school. Overall, this study demonstrated the important role of school policy and procedures and the potential application of an intersectoral approach for interventions to support changes in school travel behaviour.
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Introduction Active school travel (AST) is important for child and environmental health. In New Zealand, AST has declined over recent decades and is relatively low compared to many other countries. A plethora of evidence related to children's AST exists, yet a holistic and context-specific understanding of factors related to the behaviour remains elusive. The aim of this study is to triangulate data from children, their parents, school representatives, and objectively-assessed environmental features to generate a model that enables a comprehensive understanding of associates of AST in New Zealand children, how these variables interrelate with each other, and where change can occur. Methods Data were drawn from recent investigations conducted with children, parents/caregivers, and school representatives, and studies examining objectively-assessed built environment characteristics in relation to AST. Findings were summarised, aggregated, and triangulated, with a focus on themes where consistent findings were observed across data sources or respondents (i.e., children, parents, school representatives, geographic information systems (GIS)-derived variables). Links between variables were investigated and integrated into the final model. Results Distance from home to school and ensuring child safety were prevailing factors associated with children's AST. School policies, practices, partnerships and culture play an integral role in supporting children's AST, and in some cases can mitigate environmental barriers. An active community culture, positive neighbourhood social relations, and links between the school and community are important elements to support AST. Conclusion This research demonstrates the complexity of AST and reinforces that interventions for increasing active travel modes need to be multi-faceted and not isolated projects. Cross-sector approaches that are sustained over time are needed to facilitate meaningful change in AST. Strategic resourcing and national targets for AST rates may be effective ways to harness commitment across sectors and ensure actions to address the needs presented are operationalised.
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Active commuting to school (ACS) is an important source of physical activity among children. Recent research has focused on ACS and its benefits on cognition and academic achievement (AA), factors important for success in school. This review aims to synthesize literature on the relationship between ACS and cognition or AA among children and adolescents. Peer-reviewed articles in PubMed, Web of Science, PsycINFO and Cochrane Library assessing ACS with cognition and/or AA among children, until February 2019, were selected. Twelve studies across nine countries (age range 4-18.5 years) were included. One study used accelerometers, whereas all others used self-report measures of ACS. A wide range of objective assessments of cognitive functioning and AA domains were used. Five among eight studies, and four among six found a positive relationship between ACS and cognitive or AA measure, respectively. Four studies found dose-response relationships, and some studies found sex differences. The quantitative analysis found that ACS was not significantly associated with mathematics score (odds ratio = 1.18; CI = 0.40, 3.48). Findings are discussed in terms of methodological issues, potential confounders, and the strength of the evidence. Future studies should conduct longitudinal studies and use objective measures of ACS to understand this relationship further.
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Abstract Objectives: Growing evidence of the importance of motor competence for developing a healthy lifestyle has been established in the last decade. Nonetheless, no single instrument or observation tool have been able to fully measure this construct, particularly because most were built for the diagnosis of children in risk for motor impairment; are limited to a few years of the developmental span; lack objectivity in the assessment protocols; or do not include the locomotor, stability, and manipulative components. This led to the difficulty of comparing researches, and longitudinally follow children into adulthood. Recently, a novel proposal to assess motor competence was presented - the Motor Competence Assessment (MCA) - and this study aims to present the MCA normative data from 3-to-23 years. Design and Methods: Two thousand and eighty-seven participants (1102 boys) between 3 and 23 years of age were evaluated in the MCA (standing long jump, 10m shuttle run, throwing velocity, kicking velocity, lateral jumps, shifting platforms). Results for each test were introduced in the LMS Chartmaker 2.3. The best model for test and sex was used, resulting in normative curves and percentile values. Results: Final norms showed a good fit to the instrument developmental expectations, allowing to differentiate and classify performances along the age interval. Conclusions: The MCA age- and sex- normative values allow to assess motor competence from childhood to early adulthood. Future directions will include obtaining a total MCA score and the normative scores for the MCA components (stability, locomotion, object control), and to expand the norms to adulthood and old age.
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Cities that support cycling for transportation reap many public health benefits. However, the prevalence of this mode of transportation is low in Latin American countries and the association with facilities such as bike paths and train/subway stations have not been clarified. We conducted a cross-sectional analysis of the relationship between bike paths, train/subway stations and cycling for transportation in adults from the city of Sao Paulo. We used data from the Sao Paulo Health Survey (n = 3145). Cycling for transportation was evaluated by a questionnaire and bike paths and train/subway stations were geocoded using the geographic coordinates of the adults’ residential addresses in 1500-m buffers. We used multilevel logistic regression, taking account of clustering by census tract and households. The prevalence of cycling for transportation was low (5.1%), and was more prevalent in males, singles, those active in leisure time, and in people with bicycle ownership in their family. Cycling for transportation was associated with bike paths up to a distance of 500 m from residences (OR (Odds Ratio) = 2.54, 95% CI (Confidence interval) 1.16–5.54) and with the presence of train/subway stations for distances >500 m from residences (OR = 2.07, 95% CI 1.10–3.86). These results are important to support policies to improve cycling for transportation in megacities such as Sao Paulo.
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Background Evidence is mounting to suggest a causal relationship between the built environment and people’s physical activity behaviours, particularly active transport. The evidence base has been hindered to date by restricted consideration of cost and economic factors associated with built environment interventions, investigation of socioeconomic or ethnic differences in intervention effects, and an inability to isolate the effect of the built environment from other intervention types. The aims of this systematic review were to identify which environmental interventions increase physical activity in residents at the local level, and to build on the evidence base by considering intervention cost, and the differential effects of interventions by ethnicity and socioeconomic status. Methods A systematic database search was conducted in June 2015. Articles were eligible if they reported a quantitative empirical study (natural experiment or a prospective, retrospective, experimental, or longitudinal research) investigating the relationship between objectively measured built environment feature(s) and physical activity and/or travel behaviours in children or adults. Quality assessment was conducted and data on intervention cost and whether the effect of the built environment differed by ethnicity or socioeconomic status were extracted. Results Twenty-eight studies were included in the review. Findings showed a positive effect of walkability components, provision of quality parks and playgrounds, and installation of or improvements in active transport infrastructure on active transport, physical activity, and visits or use of settings. There was some indication that infrastructure improvements may predominantly benefit socioeconomically advantaged groups. Studies were commonly limited by selection bias and insufficient controlling for confounders. Heterogeneity in study design and reporting limited comparability across studies or any clear conclusions to be made regarding intervention cost. Conclusions Improving neighbourhood walkability, quality of parks and playgrounds, and providing adequate active transport infrastructure is likely to generate positive impacts on activity in children and adults. The possibility that the benefits of infrastructure improvements may be inequitably distributed requires further investigation. Opportunities to improve the quality of evidence exist, including strategies to improve response rates and representativeness, use of valid and reliable measurement tools, cost-benefit analyses, and adequate controlling for confounders. Electronic supplementary material The online version of this article (10.1186/s12966-017-0613-9) contains supplementary material, which is available to authorized users.
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Objective: Being overweight makes physical movement more difficult. Our aim was to investigate the association between body composition and motor performance in preschool children. Methods: A total of 476 predominantly normal-weight preschool children (age 3.9 ± 0.7 years; m/f: 251/225; BMI 16.0 ± 1.4 kg/m2) participated in the Swiss Preschoolers' Health Study (SPLASHY). Body composition assessments included skinfold thickness, waist circumference (WC), and BMI. The Zurich Neuromotor Assessment (ZNA) was used to assess gross and fine motor tasks. Results: After adjustment for age, sex, socioeconomic status, sociocultural characteristics, and physical activity (assessed with accelerometers), skinfold thickness and WC were both inversely correlated with jumping sideward (gross motor task β-coefficient -1.92, p = 0.027; and -3.34, p = 0.014, respectively), while BMI was positively correlated with running performance (gross motor task β-coefficient 9.12, p = 0.001). No significant associations were found between body composition measures and fine motor tasks. Conclusion: The inverse associations between skinfold thickness or WC and jumping sideward indicates that children with high fat mass may be less proficient in certain gross motor tasks. The positive association between BMI and running suggests that BMI might be an indicator of fat-free (i.e., muscle) mass in predominately normal-weight preschool children.
Enjoyment of alternatives to driving can make up for what are often longer travel times in the mode choice calculus. In particular, studies show that liking of bicycling is a significant predictor of bicycling, but few studies have systematically explored what it is about bicycling that people like. We address this question in an exploratory analysis of positive statements about bicycling drawn from 54 in-depth interviews with residents of Davis, California about their experiences with bicycling over their lifetimes. Eight themes emerged from our analysis of these statements: activities, bonding, sensations, feelings, pride, convenience, nice places, and memories. The incidence of themes differs across stages of life and gender. Participants often talked about the freedom and excitement of bicycling when they were children, for example, but tended to focus on convenience and health benefits when talking about bicycling as adults. These results reinforce findings from previous studies while adding new dimensions. This study provides a starting point for further research as well as guidance for the development of policies and programs to encourage more bicycling.
In line with global trends of declining physical activity and growing obesity, children's school travel nowadays is often characterized by being driven to school instead of walking and cycling. In order to counter these trends one needs to understand children's travel behavior and mobility needs. In that regard, one underexplored task is if and how transport modes relate to children's well-being. This study aims to evaluate the connections between children's subjective psychological well-being, mode use and attitudes. A sample of children from three primary and two secondary schools in the City of Vienna reported their mood and alertness on and after school trips along with travel mode use, preferences, and attitudes. The results showed that children's psychological well-being was related to the travel modes they used and their preferences and attitudes towards those modes. The association between mode use and PWB was positive for active travel but weak. Age differences were also apparent-younger children preferred active travel modes for school and leisure trips, while older children had more positive attitudes and stronger preferences for car use-foreshadowing potential travel behavior changes as children approach young adulthood and become more independent.
Objective: To analyse the association between cycling to/from school and body composition, physical fitness, and metabolic syndrome among a sample of Colombian children and adolescents. Study design: During the 2014–2015 school years, we examined a cross-sectional component of the FUPRECOL study. Participants included 2,877 youths (54.5% girls) from Bogota (Colombia). A self-reported questionnaire was used to measure frequency and mode of commuting to school. Four components of physical fitness were measured: (1) anthropometric parameter (height, weight, body mass index, and waist circumference); (2) musculoskeletal parameters (handgrip and standing long jump test); (3) motor parameter (speed-agility test; 4 × 10 m shuttle run); and (4) cardiorespiratory parameter (20mSRT: 20 m shuttle run test). The prevalence of metabolic syndrome was determined by the definitions provided by the International Diabetes Federation. Results: Twenty-three percent of the sample reported commuting by cycle. Active commuting boys showed lower likelihood (OR) of having unhealthy 4 x 10 m levels (OR = 0.72; 95% CI 0.53 to 0.98, p = 0.038) compared to the reference group (passive commuters). Active commuting girls showed a lower likelihood of having unhealthy 20mSRT levels (OR = 0.81; 95% CI 0.56 to 0.99, p = 0.047) and metabolic syndrome (OR = 0.61; 95%CI 0.35 to 0.99, p = 0.048) compared to passive commuters. Conclusion: Our results provide some evidence that regular cycling to school may to be associated to greater physical fitness and lower metabolic syndrome than passive transport, especially in girls.