Profiles of Primary School Children's Sports Participation and Their Motor Competencies

Abstract

Background/Objectives: Children participate in various organized and informal physical activities (PAs) in their leisure time, presenting diverse objectives and environments for motor and social development. However, current research often focuses on specific, mostly organized activities, overlooking the complexity of participation across different settings. This study aimed to (1) identify groups of children with similar characteristics based on their participation in five organized and informal sports activities and (2) examine how the groups differ regarding gender, age, BMI, motor competencies (MCs), and attendance in institutionalized care at school. Methods: The study included n = 1717 1st and 2nd graders (M = 7.60 years, SD = 0.59, 50.7% girls) and n = 1319 3rd and 4th graders (M = 9.46 years, SD = 0.57, 49.4% girls) from the "EMOKK" study, funded by the Swiss National Science Foundation. Data were collected via parent questionnaires on leisure sports participation, and MCs were assessed using MOBAK-1-2 and 3-4 tests. Latent profile analyses (LPAs) and univariate ANOVAs were used to identify group differences. Results: A three-profile LPA model best fits the data, revealing differences in participation across individual and team sports, optional school sports, free play on the school playground, and informal activities during leisure time. Children involved more in team sports (profiles: allrounder and very active sportsperson) participate more in informal play and present better MCs than children participating mainly in individual sports (profile: individual sportsperson). Girls were predominantly in the individual sports profile, while boys were more evenly spread across all groups. These findings highlight the importance of designing targeted interventions that promote participation in both organized and informal sports, particularly for children with lower levels of PA. Conclusions: Children show different patterns of engagement in different interrelated organized and informal leisure PA contexts. These specific patterns and the children's MCs should be taken into account for the targeted promotion of PAs during leisure time.

Full text

Citation: Kress, J.; Bretz, K.; Herrmann,
C.; Schuler, P.; Ferrari, I. Profiles of
Primary School Children’s Sports
Participation and Their Motor
Competencies. Children 2024,11, 1370.
https://doi.org/10.3390/
children11111370
Academic Editor: Jaak Jürimäe
Received: 15 October 2024
Revised: 1 November 2024
Accepted: 6 November 2024
Published: 12 November 2024
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Article
Profiles of Primary School Children’s Sports Participation and
Their Motor Competencies
Johanna Kress 1, Kathrin Bretz 1, Christian Herrmann 1, Patricia Schuler 2and Ilaria Ferrari 2, *
1Research Group Exercise and Sport, Zurich University of Teacher Education, 8090 Zurich, Switzerland;
johanna.kress@phzh.ch (J.K.); kathrin.bretz@phzh.ch (K.B.); christian.herrmann@phzh.ch (C.H.)
2Centre for Teaching Professions and Continuing Professional Development, Zurich University of Teacher
Education, 8090 Zurich, Switzerland; patricia.schuler@phzh.ch
*Correspondence: ilaria.ferrari@phzh.ch; Tel.: +41-(0)-43-305-54-84
Abstract: Background/Objectives: Children participate in various organized and informal physical
activities (PAs) in their leisure time, presenting diverse objectives and environments for motor and
social development. However, current research often focuses on specific, mostly organized activities,
overlooking the complexity of participation across different settings. This study aimed to (1) identify
groups of children with similar characteristics based on their participation in five organized and
informal sports activities and (2) examine how the groups differ regarding gender, age, BMI, motor
competencies (MCs), and attendance in institutionalized care at school. Methods: The study included
n= 1717 1st and 2nd graders (M = 7.60 years, SD = 0.59, 50.7% girls) and n= 1319 3rd and 4th graders
(M = 9.46 years, SD = 0.57, 49.4% girls) from the “EMOKK” study, funded by the Swiss National
Science Foundation. Data were collected via parent questionnaires on leisure sports participation, and
MCs were assessed using MOBAK-1-2 and 3-4 tests. Latent profile analyses (LPAs) and univariate
ANOVAs were used to identify group differences. Results: A three-profile LPA model best fits the
data, revealing differences in participation across individual and team sports, optional school sports,
free play on the school playground, and informal activities during leisure time. Children involved
more in team sports (profiles: allrounder and very active sportsperson) participate more in informal play
and present better MCs than children participating mainly in individual sports (profile: individual
sportsperson). Girls were predominantly in the individual sports profile, while boys were more evenly
spread across all groups. These findings highlight the importance of designing targeted interventions
that promote participation in both organized and informal sports, particularly for children with lower
levels of PA. Conclusions: Children show different patterns of engagement in different interrelated
organized and informal leisure PA contexts. These specific patterns and the children’s MCs should be
taken into account for the targeted promotion of PAs during leisure time.
Keywords: physical activity; organized sports; informal sports; latent profile analysis; all-day schools;
primary school
1. Introduction
In childhood, physical activity (PA), movement, and play are essential for exploring
the environment. Through movement, children interact with their environment and other
children and learn to estimate their competencies [
1
]. Both motor competencies and
interdisciplinary competencies (e.g., social skills) are developed in social contexts (e.g.,
sports club), in interactions with peers (e.g., playing during free time), and in Physical
Education (PE) [
2
–
4
]. PA is relevant from a health-related perspective across the entire
lifespan [
5
] and the World Health Organization (WHO) recommends at least one hour of
moderate-to-vigorous PA per day for children and adolescents. However, national and
international studies show that these PA recommendations are often not met [6–8].
However, PA, play, and sports are among the most frequent and popular leisure time
activities from the perspective of children and young people. In European countries, around
Children 2024,11, 1370. https://doi.org/10.3390/children11111370 https://www.mdpi.com/journal/children

Children 2024,11, 1370 2 of 18
two-thirds of children participate in sports club activities, making these activities the most
widespread form of youth organization engagement among children and adolescents [
9
–
11
].
It is acknowledged that children are particularly active in sports with friends, which further
emphasizes the importance of the social setting in sports [12].
In general, PA is influenced by a variety of factors. In the early childhood period, the
family context is undoubtedly a significant determinant, given that the family is typically
the initial and primary setting for children’s PA [
13
]. Contextual and socio-cultural factors
such as resource availability, cultural values, and family and community support influence
the design, implementation, and outcomes of youth sports participation [
14
,
15
]. Age,
gender, ethnicity, self-concept, and Body Mass Index (BMI) were identified as the most
common factors influencing overall participation in PA during childhood [
16
]. The studies
in the review of Hu and colleagues [
16
] indicated that girls were less active than boys and
boys were spending more time in informal, recreational PAs. Additionally, younger children
were found to be more active than older children, whereby a decrease in PA with increasing
age could be observed. While BMI is frequently indicated as an influencing factor, its
relationship with sports participation remains unclear [
16
,
17
]. Cairney and Veldhuizen [
17
]
observed a weak bidirectional relationship, indicating that lower BMI predicts future sports
participation, and conversely, participation in sports leads to lower BMIs.
The assessment of PA can be carried out in different ways. In contexts such as public
health, PA is often measured quantitatively by wearables, e.g., with accelerometers [
18
].
However, this method only provides information on the quantity of movement, neglecting
context-specific PA patterns and the children’s intentions to move. Other studies assess
PA through a questionnaire investigating not only the amount but also the quality of PA,
movement, and play, paying particular attention to the content and the context-specific
objectives of the activities. Considering the approach of PA as the participation in the culture
of sport and movement [
19
], the contexts in which children engage are relevant [
20
]. This
approach focuses on the fact that movement and sports provide children with differentiated
experiences and learning opportunities for the development not only of sports-related
competencies but also of social and cognitive competencies [
21
,
22
]. Indeed, the pedagogical
effect and the educational potential of learning opportunities in sports depend on their
motives and goals [11,14].
It is therefore pertinent to enquire as to the context and manner in which the chil-
dren move. Neuber and Golenia [
11
] developed a model that categorizes PA learning
environments into specific settings. This model, which is established in German-speaking
countries, identifies eight central sports-related learning contexts—family, daycare center,
school, all-day school, sports club, child and youth welfare, informal sports, and commer-
cial sports—for children and adolescents. The learning contexts were distinguished on a
continuum between formal (e.g., schools), non-formal (e.g., sports clubs), and informal
settings (e.g., informal sports and family) and between formal and informal educational
processes. For example, engagement in sports clubs is understood as a formal educational
process in a non-formal setting, whereas extracurricular PA activities in all-day schools
are seen as an informal educational process in a formal setting. The classifications of the
PA contexts in the following study are based on this concept linked to different settings.
Additionally, the analyzed contexts were distinguished between organized sports, which
refer to club sports or organized extracurricular school sports courses, and informal sports.
The latter category encompasses “non-organized” movement and play situations, including
free play on school grounds, during institutionalized care at school, or during leisure time
whether alone (e.g., cycling) or with friends (e.g., playing football) outside of school or club
settings. Understanding the balance between organized and informal sports participation
is essential for developing holistic public health interventions that address both structured
PE and free play in childhood [
15
,
23
]. While organized sports have been widely studied,
fewer studies have explored how informal play contributes to overall PA levels and motor
development in children, creating a gap that this study aims to fill.

Children 2024,11, 1370 3 of 18
Organized sports activities in sports clubs are often a central focus in discussions
about PA and movement during leisure time. Indeed sports clubs, as mentioned before,
are one of the most important non-formal settings to engage in sports for children [
9
,
10
].
Several studies show that boys enroll more often in sports clubs than girls, with around
60–70% of boys participating in sports clubs, while the participation rate of girls is around
50–60% depending on the country [
10
,
12
,
24
]. Girls predominantly participate in aesthetic
and individual sports (e.g., gymnastics, dancing, water sports, and track and field) whereas
the majority of boys engage in team sports such as football and floorball or racket sports
and combat sports [
10
,
25
]. Differences in sports club participation were not found for
body weight; however, the participation declines during the elementary school years and
becomes more pronounced during middle school years [26,27].
The school setting comprises several meaningful non-formal and informal contexts
for daily PA in children characterized by an informal learning environment [
11
,
28
,
29
].
In Switzerland, schools offer organized extracurricular school sports activities (in this
article, it is called optional school sports) that promote sports in the school environment
in a non-formal setting, so that accessibility for all children is given. These organized
sports opportunities complement the PE classes and serve as a bridge to the sports clubs,
enhancing the participants’ enjoyment of specific sports and potentially encouraging their
transition into club sports [10].
Informal sports and PAs with friends, family, or alone make an important contribution
to children’s overall PA and are the second most important setting for engaging in sports,
after sports clubs [
10
]. The school playground offers an important informal setting for PA,
as children use it for free play and movement during lunch breaks, but also after school and
on the weekends, with other children or family members. Indeed the school environment
is particularly found to be closely associated with children’s PA levels [
29
]. It provides a
familiar and accessible space for children to also engage in active outdoor play with other
children [
30
]. In addition, it was found that the presence of active children enhances overall
PA levels in playgrounds. However, girls’ PA tends to decrease when boys are present [
30
].
The all-day school setting comprises non-formal and informal contexts such as orga-
nized extracurricular school sports as well as informal free play on the school playground
during recess or in institutionalized care time at school. As institutionalized care at school
is becoming increasingly important in Switzerland [
31
], all-day schools assume the respon-
sibility for the development of suitable and varied PA and sports programs for children
and young people [
32
]. The program comprises after-school extracurricular sports courses,
supervised PA during lunchtime (open gym), and free PA during recess and before and
after school [32].
Motor competencies (MCs) are a prerequisite to actively participate in all the described
contexts and thus in the culture of sports and movement [
33
]. They are necessary to
develop sport-specific skills, which are needed for sustained engagement in sports and for
fostering an active lifestyle throughout the lifespan [
34
]. The motor competencies (MCs)
describe the ability to perform a range of motor tasks, including coordinating gross and
fine movements that are essential for daily sports activities [
35
–
37
]. Numerous studies
have identified the determinants and influencing factors of MCs. MCs have been shown
to be determinants of PA with higher levels of MCs positively correlating with higher
levels of PA and better health attributes [
38
]. MCs are developed through childhood and
adolescence and are dependent and influenced by different biological (e.g., sex and BMI),
and environmental factors (e.g., participation in learning situations or opportunities to
play) and their interplay [
34
,
39
]. Children participating in sports clubs show better MCs in
object control than children not participating [
33
]. In this article, MCs will be used as an
umbrella term encompassing the construct of basic motor competencies as a subset of MCs.
Overall, it can be concluded that leisure sports activities occur within a range of
learning environments and settings, with varying goals and characteristics. However, a
comprehensive overview of participation in different contexts in PA has yet to be estab-
lished. This study aims to analyze and present the contexts in which children in Switzerland

Children 2024,11, 1370 4 of 18
engage in leisure time PA, elucidating the interrelationships between these contexts. A key
aspect of this explorative and innovative approach is the analysis of participation profiles,
which allows us to identify and highlight the specific characteristics of different groups.
This study aimed (1) to identify groups of children with similar characteristics based
on their participation in five organized and informal sports activities and (2) to examine
how the groups differ regarding gender, age, BMI, MCs, and attendance in institutionalized
care time at school.
2. Materials and Methods
The data for this cross-sectional analysis were derived from a study that investigated
the “Development of basic motor competencies in children (EMOKK)” (2021–2025) founded
by the Swiss National Science Foundation (SNSF; grant number 200840). The MCs of 1st-
to 4th-grade primary school children were assessed through the basic motor competency
assessment test MOBAK [
40
], and information, e.g., about the children’s PA, was collected
in a proxy parent questionnaire [41].
Additionally, a subsample from a sub-study of EMOKK called “Sports at schools with
all-day facilities (SINTA)” (2022–2024) has been included. Data for additional informa-
tion were collected from two schools in the German-speaking part of Switzerland with a
movement-oriented all-day structure (these schools were partly from the EMOKK study
and the SINTA sub-study). As part of the SINTA project, the professionals at these schools
participated in an in-school training course on PAs and sports in childcare. They were
trained in the importance of movement in everyday life and received didactic input on
movement in the sports hall. The 3rd- and 4th-grade primary school children were asked
about the extracurricular PA programs at the all-day school using a questionnaire; these
questions extend beyond the EMOKK study. [42].
The study was conducted in accordance with the principles of voluntary participation,
and the children’s legal guardians were duly informed of the study’s objectives and proce-
dures prior to its commencement. The legal guardians provided informed consent, and the
children gave their assent to participate. The study fully conforms to the Declaration of
Helsinki. The legal and school-relevant ethical requirements were approved by the Ethics
Commission of the University of Zurich (No. 21.2.5) as well as by the school principals of
the primary schools concerned.
2.1. Sample Description
The study involved primary school children from the 1st, 2nd, 3rd, and 4th grades
from the German-, Italian- and French-speaking regions of Switzerland. Data were gathered
in the spring of 2024. To facilitate the analysis and account for differences in leisure time
sports participation between younger and older children, the tested children were divided
into two groups. This division is also given by the two different age-related tests used
for the assessment of the MCs [
43
]. The total sample was divided into two groups: one
comprising 1st and 2nd graders (sample 1, n= 1717) and the other consisting of 3rd and 4th
graders (sample 2, n= 1319). Sample 2 comprises a subsample that includes 243 children
from movement-oriented all-day schools (SINTA schools), which provided additional
data on structured sports opportunities and PAs outside of regular school hours. The
characteristics of the samples are described in Table 1.
Table 1. Sample description divided by sample 1 (1st and 2nd grades), sample 2 (3rd and 4th grades),
and subsample 2 (movement-oriented all-day schools with 3rd and 4th graders).
Sample 1
1st and 2nd Grade
Sample 2
3rd and 4th Grade
Subsample 2 1
3rd and 4th Grade
n1717 1319 243
Age
Range (years) 6.4–8.8 8.4–10.8 8.4–10.8

Children 2024,11, 1370 5 of 18
Table 1. Cont.
Sample 1
1st and 2nd Grade
Sample 2
3rd and 4th Grade
Subsample 2 1
3rd and 4th Grade
M (years) 7.6 9.5 9.7
SD 0.6 0.6 0.6
Gender
Girls 871 (50.7%) 652 (49.4%) 111 (45.7%)
Boys 846 (49.3%) 667 (50.6%) 132 (54.3%)
Diverse 0 (0%) 0 (0%) 0 (0%)
1
3rd- and 4th-grade children from the two schools with all-day care structures part of the SINTA project. Children
from this subsample are also included in the analysis of sample 2.
For the inclusion criteria, children were included in the study if data from at least
one sports activity during leisure time were recorded.
2.2. Instruments and Procedure
2.2.1. Procedure for Data Collection
Information on children’s sports activities during their leisure time such as playing
outside or participating in organized sports and general information about the child was
gathered from parents through a paper questionnaire. This survey was distributed to
parents as a component of the EMOKK study [
41
]. The MCs of the children were tested
during school hours by a test team of the EMOKK study.
In the subsample of the two movement-oriented all-day schools, students were invited
to participate in a survey administered online or in paper format. Before completing the
questionnaire, which took about 20 min, students received a brief introduction from either
the teacher or a research team member of the SINTA project [42].
2.2.2. Indicator Variables
Individual and team sports frequency: These variables represent the frequency of
participation in individual or team sports in a sports club, and therefore within the context
of organized sports [
44
]. The parents could answer the question if the child was a member
of a sports club (no or yes) and if so, tick or write down the type of sport as well as the
frequency per week the child was practicing this sport (0–7 times per week). A total of
two different sports could be specified. During data processing, the reported sports were
categorized into individual (e.g., track and field or swimming) and team (e.g., football
or basketball) sports according to the social patterns involved in practicing the sport and
based on previous classifications [
33
,
45
]. The values for the frequency of participation
in team and individual sports were then summed up to produce overall values (range
0–7 days per week).
Optional school sports: Participation in optional school sports, characterized as
extracurricular, organized sports offered by the school, was reported by the parents in the
proxy questionnaire with the question: “How often does your child participate in voluntary
sports activities at school?” (range: 0–7 days per week).
School playground: The school playground serves as a formal setting where children
can engage in free play and movement (informal sports activities). In the questionnaire, it
was asked, how many days per week does the child play in the school playground during
free time (outside of compulsory school hours)? (range: 0–7 days per week).
Informal sports outside of the school and outside the sports clubs labeled as days of
sport: In addition to organized sports, non-organized sports in informal settings, referred
to as “informal sports” in this article, play an important role in promoting PA [
23
]. In the
questionnaire, the parents were asked: “On how many days per week is your child active
in sports (e.g., cycling, football) for at least half an hour in his/her free time (outside school
and sports club)?” (range: 0–7 days per week).

Children 2024,11, 1370 6 of 18
The identified profiles in all samples were further analyzed using the variables gender,
age, and BMI of the children to identify differences in the distribution within the profiles.
The gender (girl or boy dichotomy, as the diverse category was not used) and the age
in months were determined via parents’ or legal guardians’ proxy reporting. The Body
Mass Index (BMI) was assessed by measuring the height and weight of the participants
using a standardized protocol during the on-site visits of the EMOKK study in the school
classes [41].
A further considered variable is the attendance in institutionalized care at schools
labeled as school care attendance; this indicates how many times a week (0 to 5) the child
attends the all-day school offering during lunchtime and in the afternoon after school
classes. In Switzerland, many educational establishments provide extended educational
facilities, also called all-day schools for children before, between, and after compulsory
school lessons. These services are provided on a fee-paying basis, with parents able to
decide which days their children will attend and for how long.
The children’s basic motor competencies, referred to in this article as the general term
MCs, were assessed through the MOBAK test instruments [
46
]. This test instrument is
age-specific and demonstrates curricular validity, aligning with the minimal curricular
requirements for PE in Switzerland and many European countries [
43
,
47
,
48
]. The MCs
were assessed by a research team using the MOBAK 1-2 and 3-4 test instruments during PE
lessons at school [
43
]. The MOBAK test measures basic motor qualifications in two compe-
tence domains, “Self-movement” (SM, representing locomotion) and “Object movement”
(OM, indicating object control), with each domain tested using four different test items.
Children have two attempts for each item, and each attempt is rated on a dichotomous scale
according to specific criteria (0 = failed and 1 = successful). The points are summed up per
item with a maximum of 2 points possible for the final item score. The item points can be
added for each competence domain (SM and OM), with a maximum of 8 points achievable.
The total MC score (MC sum) is calculated by summing the scores of the SM and OM
domains, with a range from 0 to 16 points [
43
]. The psychometric quality of the MOBAK
tests has been confirmed in several studies using confirmatory factor analysis [40,46].
In addition to the variables already described, in subsample 2, children attending
the all-day school care at least once a week indicated in a questionnaire how often they
participated in the open gym (PA during the lunchtime supervised by the childcare team)
offer (never = 0, sometimes = 1, frequently = 2, always = 3 [
42
]). This variable was answered
only by the children of the two schools that were part of the SINTA project. The open gym
can be described as an informal learning context in a formal setting [32]. The open gym is
a voluntary offer for children who attend the all-day school structures, which take place
at lunchtime or in the afternoon after school. It is supervised by childcare professionals
and is voluntary. For this offer, the childcare professionals were trained within the in-house
training of the SINTA project. The children have the flexibility to decide each day whether
they want to attend the open gym or participate in other leisure time activities such as free
play, library, etc.
2.3. Data Analysis
This study used a person-centered approach, employing latent profile analysis (LPA)
with MPlus version 8 [
49
]. LPA is a statistical method used to identify different subgroups
within a population that share some similar observable characteristics [
50
]. LPA was
selected due to its ability to model heterogeneity within the population and identify latent
subgroups based on unobserved patterns of participation in PA. The aim was to identify
homogeneous groups of school children with different profiles of sports behaviors based
on their frequency of (1) individual and (2) team sports, (3) frequency of participation in
optional school sports, (4) movement and play in the school playground, and (5) informal
PA during leisure time (variables ranged from 0 to 7 days per week). We applied LPA using
five classification variables related to PA in leisure time for the younger primary children
in the 1st and 2nd grades, as well as for older children in the 3rd and 4th grades. All the

Children 2024,11, 1370 7 of 18
steps of data analysis were carried out analogously for the two age samples. The missing
data were handled using full information maximum likelihood (FIML).
The LPA model testing process started with the estimation of a one-profile model,
progressively adding more profiles until the optimal number of latent profiles was deter-
mined. This process aimed at achieving the best solution both statistically and in terms
of theoretical interpretability. The determination of the optimal number of profiles was
based on the recommendations of Geiser [
51
] and of Weller and colleagues [
50
] following
the criteria of the following:
•
Model fit: The Bayesian information criterion (BIC), the Akaike information criterion
(AIC), and the sample-size-adjusted Bayesian information criterion (SABIC) were re-
ported as indicators of model fit. Lower values indicate a better fit of the model
[51,52]
.
In the fit statistics, the Vuong–Lo–Mendell–Rubin adjusted likelihood ratio test (LMR
LR), the Lo–Mendell–Rubin adjusted LRT test (ALMR LR), and the bootstrapped
likelihood ratio test (BLRT) provide indications if one model is statistically better than
another through a p-value [
50
]. Also, the average latent profile posterior probability
that indicates the average probability of an individual being assigned to a specific
group is desirable to be high and closer to 1.0. Among some researchers, the cutoff
value of 0.80 is accepted, whereas a value greater than 0.90 is considered as ideal.
Probabilities between 0.80 and 0.90 are acceptable if other criteria are satisfied and
the model is theoretically justified [
50
]. The entropy was considered for the accuracy
determination of group classification. This value was considered acceptable above
0.80 and ideal close to 1 [50].
•
Profile size: The sample size per profile was evaluated and models with profiles of
<5% were inspected, as they may be spurious [53].
•
Interpretability: According to the research questions, the number of profiles should be
theoretically meaningful and interpretable [50,51].
•
Parsimony: Models with fewer profiles should be preferred to avoid local likelihood
maxima and overfitting and to ensure that the profiles can be explained in a satisfactory
and meaningful way [51].
It is necessary to point out that the optimal number of profiles was chosen considering
both the statistical model fits in conjunction with the theoretical interpretation.
After determining the optimal LPA profile, we compared them to determine differences
in gender, age, BMI, attendance in school care, and basic motor competencies in the
two competence domains “Self-movement” and “Object movement”. For subsample 2, the
covariate of the participation in the open gym was additionally analyzed. We calculated
one-way ANOVAs with the covariate variables for group comparisons and descriptive
statistics using SPSS 28 [54].
3. Results
3.1. Latent Profiles of Sports Participation
The LPA identified three distinct profiles of sports participation across both age groups:
individual sportsperson,allrounder, and very active team sportsperson. These profiles reveal
significant gender differences and associations with motor competencies.
The model fit outcomes of the LPA are shown in Table 2for grades 1 and 2 and in
Table 3for grades 3 and 4. The aim of the LPA was to identify groups of children sharing
similar observable characteristics. In both cases, the AIC, BIC, and ABIC decrease consis-
tently as the number of profiles increases. The log-likelihood was always replicated except
for profile 5 for the 3rd and 4th grades. The three-profile solution was chosen as the best fit
for the data as the p-values of LMR LR, ALMR LR, and BLRT are significant and therefore
represent a statistically better model. The average probability of class membership in both
samples was over 0.90 (ranging from 0.885 to 0.985), which is more than acceptable. In both
profiles, the entropy is >0.80 indicating good accuracy. The profiles contain more than 5%
except for one profile in sample 1 which has 4%; nevertheless, it is acceptable, as the other
statistical values are well fitting, and the model can be theoretically explained. Compared

Children 2024,11, 1370 8 of 18
to the three-profile solution, the four- and five-group solution of sample 1 presents no
significant p-values in LMR, LR, and ALMR LR, and one profile contains 2% of people.
In sample 2, the main reason for not choosing a solution of four or five profiles was the
small sample proportion of some profiles (1% and 2% of people) and the theoretical in-
terpretation. Furthermore, the optimal log-likelihood could not be replicated with the
five-profile solution.
Table 2. Model fit indices for latent profile analysis for 1st and 2nd grades, sample 1.
AIC BIC ABIC Entropy LMR LR ALMR LR BLRT
1 Profile 26,532.65 26,587.14 26,555.37 - - - -
2 Profiles 25,979.90 26,067.07 26,016.24 0.80 p< 0.001 p< 0.001 p< 0.001
3 Profiles 25,389.64 25,509.50 25,439.61 0.81 p< 0.001 p< 0.001 p< 0.001
4 Profiles 24,327.60 24,480.15 24,391.20 0.85 p= 0.101 p= 0.105 p< 0.001
5 Profiles 23,238.55 23,423.8 23,315.78 0.86 p= 0.113 p= 0.117 p< 0.001
Note: AIC = Akaike information criterion; BIC = Bayesian information criterion; ABIC = sample-size-adjusted
BIC; LMR LR = Vuong–Lo–Mendell–Rubin likelihood ratio test; ALMR LR = Lo–Mendell–Rubin adjusted LRT
test; BLRT = bootstrap likelihood ratio test.
Table 3. Model fit indices for latent profile analysis for 3rd and 4th grades, sample 2.
AIC BIC ABIC Entropy LMR LR ALMR LR BLRT
1 Profile 22,129.47 22,181.32 22,149.55 - - - -
2 Profiles 21,637.94 21,720.89 21,670.07 0.71 p= 0.069 p= 0.072 p< 0.001
3 Profiles 21,285.10 21,399.16 21,329.28 0.83 p= 0.029 p= 0.031 p< 0.001
4 Profiles 21,005.59 21,150.75 21,061.81 0.85 p< 0.001 p< 0.001 p< 0.001
5 Profiles 20,626.06 20,802.34 20,694.34 0.86 p= 0.785 p= 0.788 p< 0.001
Note: AIC = Akaike information criterion; BIC = Bayesian information criterion; ABIC = Sample-size adjusted
BIC; LMR LR = Vuong–Lo–Mendell–Rubin likelihood ratio test; ALMR LR = Lo–Mendell–Rubin adjusted LRT
test; BLRT = bootstrap likelihood ratio test.
The analysis identified three different profiles in both samples 1 and 2. The results of
the LPAs are described based on sample 2 for grades 3 and 4. The resulting three profiles of
sample 2 closely resemble those identified in sample 1. Specific characteristics of sample
1 will be discussed in a subsequent section.
The mean values and standard deviations of the study variables for each group are
shown in Table 4for sample 1 and Table 5for sample 2. To facilitate the interpretation,
the mean values of the three-profile model (lines in colours yellow, green and blue) and
for the total sample (gray line) are graphically represented in Figures 1and 2showing the
five variables included in the LPA on the x-axis. On the y-axis, the number of days per
week (0–7 for all variables) is marked.
Table 4. Descriptive values of the study’s variables by profile of sample 1 primary school classes 1
and 2.
Profile 1 Profile 2 Profile 3
M
CI 95%
M
CI 95%
M
CI 95% Fpη2
frequency
individual sports *
1.61
[1.55; 1.68]
0.45
[0.39; 0.50]
0.47
[0.24; 0.71] (2, 1340) = 325.48 <0.001 0.327
frequency
team sports *
0.02
[0.01; 0.02]
1.32
[1.28; 1.36]
3.67
[3.47; 3.88] (2, 1340) = 4628.432 <0.001 0.874
optional school
sport *
0.86
[0.8; 0.92]
1.00
[0.91; 1.08]
1.83
[1.38; 2.28] (2, 1686) = 27.958 <0.001 0.032
school playground * 1.78
[1.67; 1.89]
2.01
[1.84; 2.17]
2.52
[2.06; 2.98] (2, 1695) = 7.046 <0.001 0.008

Children 2024,11, 1370 9 of 18
Table 4. Cont.
Profile 1 Profile 2 Profile 3
M
CI 95%
M
CI 95%
M
CI 95% Fpη2
days of sport * 2.52
[2.4; 2.64]
3.61
[3.42; 3.80]
3.61
[3.09; 4.14] (2, 1558) = 53.848 <0.001 0.065
age
(in months)
90.78
[90.36; 91.2]
91.69
[91.1; 92.29]
93.27
[91.71; 94.83] (2, 1714) = 6.442 0.002 0.007
BMI 15.94
[15.81; 16.07]
16.09
[15.89; 16.29]
16.21
[15.77; 16.65] (2, 1617) = 1.139 0.321 0.001
school care 0.93
[0.84; 1.02]
0.93
[0.8; 1.06]
0.96
[0.56; 1.36] (2, 1672) = 0.01 0.990 0.000
MC (MOBAKs) 10.08
[9.88; 10.29]
10.83
[10.56; 11.1]
12.06
[11.39; 12.73] (2, 1495) = 18.907 <0.001 0.025
OM 4.95
[4.84; 5.07]
5.74
[5.59; 5.89]
6.56
[6.23; 6.88] (2, 1556) = 51.727 <0.001 0.062
SM 5.12
[4.99; 5.25]
5.09
[4.92; 5.27]
5.49
[5.02; 5.95] (2, 1548) = 1.103 0.332 0.001
χ2p
gender (girls) 82.7% 16.2% 1.1% 2 = 284.48 <0.001
gender (boys) 43.7% 48.6% 7.7%
* days per week (0–7).
Table 5. Descriptive values of the study’s variables by profile of sample 2 primary school classes 3
and 4.
Profile 1 Profile 2 Profile 3
M
CI 95%
M
CI 95%
M
CI 95% Fpη2
frequency
individual sports *
1.61
[1.52; 1.7]
0.44
[0.35; 0.52]
0.11
[0.02; 0.2] (2, 1080) = 154.686 <0.001 0.223
frequency
team sports *
0.22
[0.19; 0.25]
2.28
[2.22; 2.33]
4.54
[4.27; 4.81] (2, 1080) = 3494.375 <0.001 0.866
optional school sport * 0.92
[0.84; 0.99]
1.52
[1.35; 1.69]
1.69
[1.2; 2.18] (2, 1305) = 34.3 <0.001 0.050
school playground * 1.67
[1.55; 1.79]
2.32
[2.08; 2.56]
2.27
[1.7; 2.83] (2, 1298) = 15.022 <0.001 0.023
days of sport * 2.62
[2.48; 2.75]
3.43
[3.19; 3.67]
3.51
[2.98; 4.03] (2, 1184) = 20.824 <0.001 0.034
age (in months) 113.16
[112.73; 113.6]
114.3
[113.57; 115.03]
113.68
[111.9; 115.47] (2, 1316) = 3.358 0.035 0.005
BMI 17.45
[17.23; 17.66]
17.04
[16.71; 17.37]
17.54
[16.85; 18.22] (2, 1228) = 1.962 0.141 0.003
school care 0.62
[0.54; 0.71]
0.80
[0.63; 0.97]
0.36
[0.12; 0.6] (2, 1282) = 3.534 0.029 0.005
frequency open gym a0.33
[0.2; 0.46]
0.48
[0.24; 0.72]
0.40
[−0.71; 1.51] (2, 240) = 0.667 0.514 0.006
MC (MOBAKs) 8.19
[7.96; 8.42]
9.62
[9.25; 9.98]
10.09
[9.26; 10.93] (2, 1105) = 25.601 <0.001 0.044

Children 2024,11, 1370 10 of 18
Table 5. Cont.
Profile 1 Profile 2 Profile 3
M
CI 95%
M
CI 95%
M
CI 95% Fpη2
OM 3.85
[3.72; 3.99]
5.07
[4.86; 5.27]
5.58
[5.13; 6.03] (2, 1172) = 56.627 <0.001 0.088
SM 4.31
[4.17; 4.45]
4.58
[4.36; 4.79]
4.47
[4.02; 4.93] (2, 1153) = 1.915 0.148 0.003
χ2p
gender (girls) 91.0% 8.4% 0.6% 2 = 242.153 <0.001
gender (boys) 52.5% 38.7% 8.8%
* days per week (0–7); adata from subsample 2.
Children 2024, 11, x FOR PEER REVIEW 10 of 21
Figure 1. Latent profile results: mean scores of physical activity seings (range: 0–7 days a week) for
children of the 1st and 2nd primary school class.
Figure 2. Latent profile results: mean scores of physical activity seings (range: 0–7 days a week) for
children of the 3rd and 4th primary school class.
Figure 1. Latent profile results: mean scores of physical activity settings (range: 0–7 days a week) for
children of the 1st and 2nd primary school class.
Profile 1 (yellow), labeled as individual sportsperson, includes 71% of the majority
of sample 2 and is characterized by moderate participation in individual sports about
1.61 times per week and almost no engagement in team sports (M = 0.22 days a week).
Participation in optional school sports is moderate but lower than in the other two profiles
(M = 0.92). Children in this group show medium-level data in school playgrounds outside
school hours (M = 1.67 days a week) and informal PA outside school and club sports (days
of sport = 2.62) compared to the other profiles. Comparing the values of the children in
this profile with the overall means of the sample, it turns out that these children participate
more in individual sports and far less in team sports and engage slightly less than the
average in informal sports (namely school sports and days played) and the optional sports
at school.

Children 2024,11, 1370 11 of 18
Children 2024, 11, x FOR PEER REVIEW 10 of 21
Figure 1. Latent profile results: mean scores of physical activity seings (range: 0–7 days a week) for
children of the 1st and 2nd primary school class.
Figure 2. Latent profile results: mean scores of physical activity seings (range: 0–7 days a week) for
children of the 3rd and 4th primary school class.
Figure 2. Latent profile results: mean scores of physical activity settings (range: 0–7 days a week) for
children of the 3rd and 4th primary school class.
Profile 2, (green) labeled allrounder, represents 24% of sample 2. Children in this
profile present low participation in individual sports (M = 0.44 days per week), moderate
participation in team sports in a club (M = 2.28 days per week), and frequent participation
in optional school sports (M = 1.52 days per week). Additionally, they have high levels of
informal sports at school (school playground = 2.32 days a week) and even higher levels
in settings outside the school (days of sport = 3.43). Comparing the mean values of this
profile with the overall mean values (gray line), in the sports contexts, it is noticeable
that these children are more active than the average in informal PA contexts during the
week and participate more often in team sports in clubs. On the other hand, they practice
considerably fewer individual sports than the total average.
In profile 3, (blue) labeled as a very active team sportsperson, 5% of sample 2 is included.
Characteristic of this profile is that they have minimal participation in individual sports
(
M = 0.11 days
per week) but a remarkably high level of participation in team sports in the
club 4.54 times a week. Children in this profile also often participate in optional school
sports (M = 1.69 days per week) and informal sports such as free play after school hours
at the school playground (M = 2.27) and outside of school and the sports club (
M = 3.51
).
Values in the informal sports activities, namely the school playground and the days of
sports of this profile are comparable with the values of profile 1 for these variables and
are reasonably higher than the participation of the overall sample. Also, the average
participation frequency of children in team sports in this profile is much higher (3.5 days
a week) than the overall average values. In contrast, children represented by this profile
show almost no participation in individual sports whereas the mean overall value is about
1.2 times a week. Overall, it can be seen that the variables that determine the profiles differ
significantly between the profiles (see F-value of the one-way ANOVA in Tables 4and 5in
the first half).
When comparing the LPAs of sample 2 of 3rd and 4th grades and sample 1 of 1st-
and 2nd-grade children, it can be seen that the calculated three profiles are similar, and
the sample proportion per profile is quite comparable (Tables 2and 3and Figures 1and 2).

Children 2024,11, 1370 12 of 18
Nevertheless, the LPAs of the two samples reveal discrepancies, particularly concerning
the context of organized sports in a club (as illustrated by a comparison of Figures 1and 2).
Children in the 3rd and 4th grades specialize more in terms of the type of sport, which
is particularly evident in the greater differentiation between team and individual sports
participation between the different profiles. Children at this age participate at a higher
frequency, especially in team sports, than younger children in grades 1 and 2. However, it is
remarkable that in both samples, children participating mainly in team-oriented organized
sports in the club are also more active in informal PA and sports (school playground and
days of sport) than children mainly participating in individual organized club sports.
3.2. Characteristics and Differences by Gender, Age, and MCs Between the Profiles
The second half of Tables 4and 5present the descriptive statistics for the variables
gender, age, BMI, school care, and the MCs (indicated with MOBAKs) for each profile in
the two samples. To compare the three profiles with each other, F-values for age, BMI,
school care, and the MCs are indicated, and for gender, chi-squared values are provided.
In both samples, significant differences between the three profiles were found for gender
(
1 = male
; 2 = female), age, and the MCs, especially regarding the competence domain OM.
The majority of girls are in profile 1 (sample 1 = 83%; sample 2 = 91%), while younger boys
are mostly represented by profiles 1 and 2 and older boys are more represented in profile
1. Regarding age, children in profile 1 are significantly younger than in profile 2 in both
samples. Concerning MCs, the competencies of children in profiles 2 and 3 (allrounders
and very active team sportspersons) are significantly higher than those of children in profile
1 (individual sportspersons) in both analyzed samples. These differences are mainly due to
different competence levels in the competence domain of OM.
With respect to children’s BMI, the three profiles in both samples did not significantly
differ from each other. However, differences emerged concerning children’s participation
in all-day school care. In sample 2, children categorized under profile 2 (allrounder) show
a higher frequency of school care attendance compared to those in the other two profiles.
This pattern was not found among children in grades 1 and 2 (sample 1). For the analyzed
subsample 2 of children attending the two movement-oriented all-day care structures, the
children in different profiles did not differ regarding the frequency of participation in the
open gym.
4. Discussion
The aim of this explorative study was to identify groups of children with similar
characteristics based on their participation in five organized and informal sports activities
(first research question). The results indicate that children significantly differ in their
leisure time sports participation in different contexts. For the two samples of primary
school children in years 1 and 2, and years 3 and 4, three different profiles of participation
were distinguished. For both age groups, the children showed similar patterns within
the profiles, although there were some differences in the levels of participation. The main
differentiating factor for the profiles is participation in organized club sports, categorized
into team and individual sports. Some children participate mainly in team sports and less
in individual sports, or vice versa. These discrepancies became more pronounced as the
children became older.
The first and most common profile was called individual sportsperson; children in this
group mainly attend individual sports in the context of organized sports. The second
profile indicates allrounders, characterized by participation in team sports and low-level
participation in individual sports. It represents almost one-third of 1st and 2nd graders and
a quarter of 3rd and 4th graders. The third profile represents only 4–5% of the total samples
and the children represented by this profile are labeled as very active team sportspersons.
These children show considerably more frequent participation in organized team sports
but almost no participation in individual sports.

Children 2024,11, 1370 13 of 18
On the other hand, the levels of participation in extracurricular sports activities and
informal sports during leisure time differ significantly between profile 1 and profiles 2 and
3. In particular, children in profile 1 (individual sportsperson) showed significantly less
participation in informal sports on the school playground and outside of the school context
compared to the other two profiles and to the overall means. Profiles 2 (allrounders) and
3 (very active team sportsperson) were quite active and had values above the mean values
of the total sample.
Given that children who engage in individual sports are less active in informal sports
(profile 1) and children participating in team sports are more active in informal sports
(profiles 2 and 3), it could be assumed that participation in team sports has a leverage effect
on informal sports. It stands to reason that informal sports also have a selective component,
especially considering the social context in which they are embedded. Children are likely
to participate in these PAs only if they demonstrate a certain level of skill or competence,
as participation is often contingent upon their perceived ability to “perform” in the social
setting [
55
]. This selective nature is reflected in our analyses, which show differences in
participation when comparing the profiles by their MC levels. As shown in previous studies,
an association has been found between levels of MCs and sports participation [
36
,
45
,
56
].
While children who mainly participated in team sports were better in “Object movement”,
children who mainly participated in individual sports had higher levels of MCs in “Self-
movement”. As optional sports courses and free play on the playground are often carried
out with balls, it could be that children who play ball sports in the sports club participate
more often in informal play and sports.
It is known that participation in team sports positively influences MC in both “Object
movement” and “Self-movement”; it could be that the children participate more in informal
sports due to their better MCs [
57
]. It seems that practicing team sports plays an important
role in informal sports settings. Encouraging team-based PA may have particular potential
to improve children’s MCs and promote higher overall activity levels.
Moreover, children participating in organized sports show higher social relationship
skills than children who do not [
45
]. These social relationship skills are needed to play and
participate in sports with other children. Bretz, Strotmeyer, and colleagues [
36
] showed
that especially children in team sports show higher levels of perceived motor competencies.
As perceived motor competencies are linked to sports participation [
58
], the link between
team sports participation and participation in informal sports could also be explained via
the self-concept.
In addition, family factors have been identified as influencing PAs and MCs. Parental
support for their child’s physical activity is positively associated with the child’s MCs and
PAs [
59
,
60
]. Furthermore, children whose parents are physically active show higher PA
levels than children with less active parents [61].
In consideration of the second research question—to examine how the profiles differ
regarding gender, age, BMI, MCs, and attendance in institutionalized care time at school—it
was notable that there were considerable discrepancies between the profiles concerning
gender, the MCs, and age. Conversely, in the case of BMI and participation in institutional-
ized care, there were fewer or no noteworthy differences between the profiles. The weight
status (BMI) was found to not be related to the PA behavior and the identified profiles of the
children. This finding is in line with the current study situation, in which the significance
of BMI for sports participation remains unclear [
16
]. Gender-specific differences in the
distribution of the profiles could be due to socialization effects, which also show themselves
in different levels of MCs [
56
]. These gender differences may stem from cultural norms and
societal expectations that associate team sports with boys and individual sports with girls.
Targeted programs that challenge these norms could promote more balanced participation
across all genders. Age effects are shown to be more important within younger children
(1st and 2nd graders) and less in older children (3rd and 4th graders). Older children
within both samples seem to participate more in team sports (profiles 2 and 3) than younger
children who tend to participate in individual sports and are less active (profile 1).

Children 2024,11, 1370 14 of 18
In the school setting, there are several contexts for PAs that are used by the children.
The organized extracurricular optional sports offered by the schools are attended more
by children playing team sports (profiles 2 and 3) than by those playing individual sports
(profile 1). It should be examined in more depth which topics and sports these courses
mainly cover, in order to analyze whether the differences are related to the content of
the courses and the children’s interests, or whether the children who are shown with the
individual profile (profile 1) are generally less active and do not participate. However, this
assumption would be in contrast to previous findings, which show that optional school
sports courses also reach less active children than the club spots and slightly more girls than
in other organized sports [
10
]. Also, the school playground seems to make an important
contribution to the informal sports participation of the children. As other studies point out,
public and school playgrounds are important contexts required to enable informal PA and
play for children in a safe and accessible social and physical environment [
30
]. However,
even in this context, children represented by the individual sportspersons (profile 1) are
less active than those represented by the two team sports profiles. One reason could be
that girls are mainly represented by this profile, and based on the findings of Reimers and
colleagues [
30
], girls’ PAs seem to be suppressed when boys are present in the playground
area. The reasons for these discrepancies should be further investigated to better promote
and enable sports activities for all children in this context.
Based on the results of this study, the all-day schools can provide a formal setting
for informal PA which does not stand in competition with the participation in traditional
sports clubs after school, as it was argued about in these contexts [
62
,
63
], but it seems to
be complementary. In particular, it turned out that older children (3rd and 4th graders)
represented by the profile allrounder (profile 2) are also more likely to attend all-day school,
although the small group of children participating extremely often in team sports (profile
3) attend less the institutionalized care time at school, which would be consistent with
the inconclusive results of the actual studies [
64
]. However, in the subsample of the
two movement-oriented all-day schools, children attending the open gym did not show
significant differences between the allocation to the profiles. This indicates that all children,
independent of their PA behaviors participate in this context. Therefore, the school setting,
especially during institutionalized care time at school, could provide a specific context for
participation in PA, for example, by promoting low-threshold PA in movement-oriented
activities in the informal context, such as by setting up the offer of an open gym. This
finding could be used to promote additional non-formal activities in the school setting.
According to Telford and colleagues [
65
], this approach is seen as a means of sustaining
PA as children age, making it more enjoyable and accessible. Some studies found that
as children grow older, particularly girls, PA levels decline. In line with our findings,
researchers suggest promoting informal, non-competitive, and lifestyle-oriented activities
that appeal specifically to older girls [65].
Further research on participation in different sports contexts is needed. In this study, it
is noteworthy that a considerable proportion of children (about 60% of 1st and 2nd graders
and 71% of 3rd and 4th graders) is represented by the individual sportsperson (profile 1). The
analyses did not identify any profile characterized by generally low participation in all PA
contexts. This indicates that most analyzed children participate at least to a certain extent
in either organized sports or informal contexts. As the first profile shows lower values in
optional school sports and informal sports than the overall mean, it could be assumed that
children with lower PA patterns are represented by this profile. Further studies should
analyze to which extent different profiles and contexts are related to the overall PA level
of children.
Another topic that should be considered in future research about informal sports is the
content and the goals of the activities that take place in informal sports. For a better under-
standing, it would be meaningful to analyze the reasons why children participating mostly
in team sports are also more active in informal sports. From a developmental perspective,
it would be valuable to examine the ongoing development of sports participation and MCs,

Children 2024,11, 1370 15 of 18
as well as their interplay, within a longitudinal research design. Future research should
explore longitudinal changes in these activity profiles to assess the long-term impact of
early sports participation on physical, social–emotional, and cognitive development.
Strengths and Limitations
The current state of studies indicates that when it comes to health promotion through
leisure time PA, most research focuses on formal, organized programs, while far less
attention is given to the effectiveness of informal programs [
15
]. Nevertheless, some studies
indicate the relevance of informal sports in promoting both participation and broader health
and social objectives [
23
,
66
,
67
]. This study is distinguished by an innovative, exploratory
child-centered approach with LPAs that is dedicated to both the context of organized sports
and the non-organized, informal sports in the context of sports in leisure time. The study is
based on a substantial database, which enabled the elaboration of movement profiles of
children that could be distinguished and described in terms of several characteristics.
In acknowledging the limitations of this study, it is important to consider the situation-
specific characteristics of the children’s living environments. As highlighted by Hu and
colleagues [
16
], participation in PA is influenced by cultural contexts and the availability of
local opportunities. However, this study’s findings may be constrained by these contextual
variables, as the socio-cultural and environmental factors shaping sports participation are
locally specific and present different availability and contents (e.g., in the optional school
sports or the organized sports in the clubs). Also, the interests and motives of children
participating in different contexts are not analyzed in depth. Additionally, the structure of
the Swiss school system, where children attend school both in the morning and afternoon,
plays a key role in shaping opportunities for PA participation. These aspects should be
considered when generalizing the results as these may limit the broader applicability
of the findings. Nevertheless, while the study draws from a large sample that includes
children from different linguistic regions of Switzerland, this diversity also introduces
variability that supports the generalizability of the results. Moreover, it is also important
to consider that the children’s participation in different sports contexts was reported via a
proxy questionnaire completed by their parents for reasons of practicality.
5. Conclusions
This study showed that in the context of leisure time sports and PA, both informal
and organized sports are important to consider as both of them contribute significantly to
the PA of children. Variations between the identified participation profiles are influenced
by multiple factors including gender, age, the type of sport, and especially the MCs.
Understanding these differences is crucial for designing comprehensive and effective
PA interventions. Accordingly, MCs should also be given special consideration when
promoting sports activities in an informal context, as they may have limited or leveraging
effects. The findings suggest that different strategies may be needed to promote PA among
the found groups. It is recommended to offer different contexts focusing on different
contents, in which children have the possibility to move according to their needs and
abilities. The school setting may be an important environment that could reach many
children, such as the ones who are less active and present lower MCs. The school setting
could offer differentiated activities that also consider non-competitive, low-threshold
opportunities for PAs and social encounters to provide children with a wide range of
extracurricular learning opportunities in the long term and across all age groups.
Author Contributions: Conceptualization, J.K., K.B., C.H. and I.F.; data curation, J.K., K.B. and C.H.;
formal analysis, J.K. and K.B.; funding acquisition, C.H., P.S. and I.F.; investigation, J.K. and K.B.;
methodology, J.K., K.B., C.H. and I.F.; project administration, C.H., P.S. and I.F.; supervision, C.H. and
I.F.; writing—original draft, J.K., K.B., C.H. and I.F.; writing—review and editing, J.K. and P.S. All
authors have read and agreed to the published version of the manuscript.

Children 2024,11, 1370 16 of 18
Funding: This research was funded by the Swiss National Science Foundation (SNSF, grant number
200840). The APC was funded by the University of Teacher Education Zurich (PHZH).
Institutional Review Board Statement: The study was conducted according to the guidelines of
the Declaration of Helsinki and approved by the Ethics Commission of the University of Zurich
(No. 21.2.5, date of approval: 19 December 2022).
Informed Consent Statement: The children and their parents were informed about the general
purpose of the school project and the study, the voluntary nature of the participation, and the
anonymous handling of the data. Furthermore, parents provided informed consent, and children
assented to participate.
Data Availability Statement: The data will be published in SWISSUbase.ch after the end of the
EMOKK project and will be available open access after an embargo period.
Acknowledgments: We would like to express our sincere appreciation to Simone Storni, Nicolas
Voisard, Patrizia Bernasconi, and Fabian Büchel for their efforts in data collection across the various
language regions and cantons. We would also like to thank the children, parents and teachers who
participated in this study.
Conflicts of Interest: The authors declare no conflicts of interest. The funders had no role in the
design of the study; in the collection, analyses, or interpretation of the data; in the writing of the
manuscript, or in the decision to publish the results.
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