Consolidation, Stages of Change, and Loyalty among Users of Public Sports and Health Services Aged 12–16

Abstract

There are two main lines of inquiry in the literature on adherence and/or loyalty to the practice of physical activity and to health services: one focuses on the impact of perceived quality of sports and health services and satisfaction with these services on user loyalty, while the other concludes that users with more self-determined motivation at more advanced stages of physical activity display higher levels of physical activity and greater intentions to continue this activity. The objective of this study is to ascertain the impact of different dimensions of sports service quality on satisfaction and loyalty among users aged 12 to 16 years old and to identify any differences between adolescent users at more and less consolidated stages of physical activity. A total of 1717 minors with a mean age of 13.83 ± 1.32 years who practise organised physical activity at public sports centres in Nuevo León (Mexico), 51.5% of whom were boys, participated in the study. The model of structural equations linking quality, satisfaction, and loyalty displayed adequate indices. The results showed that the staff, specific activity, and user satisfaction are predictors of loyalty. Significant differences were only found between minors at consolidated and non-consolidated stages of physical activity in the relationship between service personnel and loyalty. In conclusion, human resources and their deployment are predictive of loyalty towards sports and health services among adolescents.

Full text

International Journal of
Environmental Research
and Public Health
Article
Consolidation, Stages of Change, and Loyalty among Users of
Public Sports and Health Services Aged 12–16
Antonio Fernández-Martínez 1, * , Luis Alberto Dueñas-Dorado 2, María Rosario Teva-Villén1
and Alberto Nuviala 1, *


Citation: Fernández-Martínez, A.;
Dueñas-Dorado, L.A.; Teva-Villén,
M.R.; Nuviala, A. Consolidation,
Stages of Change, and Loyalty among
Users of Public Sports and Health
Services Aged 12–16. Int. J. Environ.
Res. Public Health 2021,18, 10113.
https://doi.org/10.3390/
ijerph181910113
Academic Editor: Paul B. Tchounwou
Received: 23 August 2021
Accepted: 23 September 2021
Published: 26 September 2021
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
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iations.
Copyright: © 2021 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/).
1Department of Sports and Computer Science, Pablo de Olavide University, Crta. de Utrera, Km1,
41013 Seville, Spain; rteva@upo.es
2Faculty of Sports Organisation, Universidad Autónoma de Nuevo Leon (Mexico), Cd. Universitaria, s/n,
San Nicolás de los Garza 66455, N.L., Mexico; luis.duenasdrd@uanl.edu.mx
*Correspondence: afermar1@upo.es (A.F.-M.); anuvnuv@upo.es (A.N.); Tel.: +34-954-977-602 (A.F.-M.)
Abstract:
There are two main lines of inquiry in the literature on adherence and/or loyalty to the
practice of physical activity and to health services: one focuses on the impact of perceived quality
of sports and health services and satisfaction with these services on user loyalty, while the other
concludes that users with more self-determined motivation at more advanced stages of physical
activity display higher levels of physical activity and greater intentions to continue this activity. The
objective of this study is to ascertain the impact of different dimensions of sports service quality on
satisfaction and loyalty among users aged 12 to 16 years old and to identify any differences between
adolescent users at more and less consolidated stages of physical activity. A total of 1717 minors with
a mean age of 13.83
±
1.32 years who practise organised physical activity at public sports centres in
Nuevo León (Mexico), 51.5% of whom were boys, participated in the study. The model of structural
equations linking quality, satisfaction, and loyalty displayed adequate indices. The results showed
that the staff, specific activity, and user satisfaction are predictors of loyalty. Significant differences
were only found between minors at consolidated and non-consolidated stages of physical activity in
the relationship between service personnel and loyalty. In conclusion, human resources and their
deployment are predictive of loyalty towards sports and health services among adolescents.
Keywords: perceived quality; satisfaction; loyalty; stages of change; adolescents
1. Introduction
Understanding users of sports and health services is a useful strategy for maintaining
and increasing levels of physical activity among the population [
1
,
2
]. The literature has
shown that advanced stages of physical activity are linked to high levels of this activity [
3
]
and greater willingness to do exercise [
4
]. Meanwhile, other studies associate high levels
of physical activity with satisfaction with the service received and greater loyalty to the
organisation [
5
]. However, no research has been carried out so far into the impact of stages
of change on the relationship between quality, satisfaction, and loyalty to sports services
in adults or in children and adolescents, despite the importance of habits established
during childhood for future behaviour in adult life [
6
]. Physical activity in children has
been proven to determine their current health, future health, and lifestyle throughout
adolescence and adulthood [
7
]. Therefore, this study aims to explore the dimensions of
quality that influence satisfaction and loyalty among adolescent users of sports services
and to ascertain the impact of stages of behaviour change on the relationships between
these concepts.
Sedentary behaviour and a lack of physical activity have risen [
8
] to become one of
the main causes of mortality around the world [
9
]. Inactivity and sedentary behaviour are
currently a cause for concern for the public health authorities [
10
,
11
] due to their significant
influence on mortality and cardiometabolic morbidity, as well as on the appearance of
Int. J. Environ. Res. Public Health 2021,18, 10113. https://doi.org/10.3390/ijerph181910113 https://www.mdpi.com/journal/ijerph

Int. J. Environ. Res. Public Health 2021,18, 10113 2 of 15
certain cancers [
12
]. High levels of sedentarism have been observed among children and
adolescents, 80% of whom are inactive and fail to meet recommendations for physical
activity [
13
,
14
]. These sedentary behaviours among children and adolescents are associated
with early metabolic and cardiovascular risk [
15
,
16
]. Behaviour in childhood has been
shown to directly influence behaviour in adulthood [
17
]. As a result, physical activity and
sedentarism among children determine their current health and are a clear predictor of
their health and lifestyle during adolescence and adulthood [7].
Recent studies have demonstrated the relationship between quality, satisfaction, and
loyalty to the sports organisation among adult users of sports services [
2
,
18
] and even
among adolescent users [
19
] as a strategy for encouraging adherence to and maintenance
of physical activity levels. According to Oliver [
20
], loyalty is understood as a strong
commitment to purchase goods or services on an ongoing basis into the future, despite the
possibility of competitors’ efforts and/or situational influences bringing about a change
in behaviour. The concept of loyalty is related to service continuity [
21
]. In other words,
consumers who repeatedly return to the same service are loyal [
22
], but building loyalty
and encouraging repeat visits in the sports and health services market also entails the
acquisition of healthy habits [
23
]. Most of the studies that have analysed the relationship
between these concepts have used unidimensional models with adults [
18
,
24
,
25
]. Only
Pérez-Órdas et al. [
19
] used a model in adolescents to analyse relationships between the
different dimensions of quality and loyalty. Unfortunately, their study did not consider
the relationships between dimensions of quality and satisfaction or potential indirect
relationships with loyalty via satisfaction. A lack of information prevents programme
managers from developing reliable strategies with an objective impact on sports and
health services. This shortcoming may be due to the failure to explore secondary concepts,
as the primary objective of most studies is to determine the role of service quality in
its relationships with other variables [
23
] rather than to ascertain the importance of the
model’s dimensions. The order of the structural model in Figure 1should start from the
left with Perceived Quality (independent variable) and end with Satisfaction and Loyalty
(dependent variable). Also, the structural model should include different dimensions of
the quality of sports services in Figure 1.
Int. J. Environ. Res. Public Health 2021, 18, x FOR PEER REVIEW 2 of 15
currently a cause for concern for the public health authorities [10,11] due to their signifi-
cant influence on mortality and cardiometabolic morbidity, as well as on the appearance
of certain cancers [12]. High levels of sedentarism have been observed among children
and adolescents, 80% of whom are inactive and fail to meet recommendations for physical
activity [13,14]. These sedentary behaviours among children and adolescents are associ-
ated with early metabolic and cardiovascular risk [15,16]. Behaviour in childhood has
been shown to directly influence behaviour in adulthood [17]. As a result, physical activity
and sedentarism among children determine their current health and are a clear predictor
of their health and lifestyle during adolescence and adulthood [7].
Recent studies have demonstrated the relationship between quality, satisfaction, and
loyalty to the sports organisation among adult users of sports services [2,18] and even
among adolescent users [19] as a strategy for encouraging adherence to and maintenance
of physical activity levels. According to Oliver [20], loyalty is understood as a strong com-
mitment to purchase goods or services on an ongoing basis into the future, despite the
possibility of competitors’ efforts and/or situational influences bringing about a change in
behaviour. The concept of loyalty is related to service continuity [21]. In other words, con-
sumers who repeatedly return to the same service are loyal [22], but building loyalty and
encouraging repeat visits in the sports and health services market also entails the acquisi-
tion of healthy habits [23]. Most of the studies that have analysed the relationship between
these concepts have used unidimensional models with adults [18,24,25]. Only Pérez-Ór-
das et al. [19] used a model in adolescents to analyse relationships between the different
dimensions of quality and loyalty. Unfortunately, their study did not consider the rela-
tionships between dimensions of quality and satisfaction or potential indirect relation-
ships with loyalty via satisfaction. A lack of information prevents programme managers
from developing reliable strategies with an objective impact on sports and health services.
This shortcoming may be due to the failure to explore secondary concepts, as the primary
objective of most studies is to determine the role of service quality in its relationships with
other variables [23] rather than to ascertain the importance of the model’s dimensions.
The order of the structural model in Figure 1 should start from the left with Perceived
Quality (independent variable) and end with Satisfaction and Loyalty (dependent varia-
ble). Also, the structural model should include different dimensions of the quality of
sports services in Figure 1.
Figure 1. Structural model predicting loyalty to sports and health services among users aged 12–
16.
Satisfaction
Loyalty
Sports activity
Communication
Service
personnel
Sports
instructor
Sports areas
Equipment
PERCEIVED QUALITY
Figure 1.
Structural model predicting loyalty to sports and health services among users aged 12–16.

Int. J. Environ. Res. Public Health 2021,18, 10113 3 of 15
In order to understand adherence to and maintenance of sports practice, it is also
necessary to identify the influence of motivation [
26
]. Mechanisms for adherence to
different physical exercise programmes are highly diverse [
27
] and an analysis of these
mechanisms is key to understanding people’s commitment to sport [
28
]. The influence
of motivational processes on the practice of and adherence to physical or sports activities
has been amply studied [
3
] from two main independent theoretical perspectives: the
transtheoretical model (TTM) of behaviour change [
29
] and self-determination theory
(SDT) [
30
,
31
]. TTM comprises stages and processes of change. The stages explain when
and the processes explain how changes in individuals’ attitudes, intentions, and behaviour
come about [
32
]. The model posits the idea that physical exercise is a dynamic behaviour
and that people go through five stages of behaviour change in their attempts to exchange
their sedentary behaviours for a more physically active lifestyle [
3
]. The stages included
in the model are: pre-contemplation (the subject does not engage in physical activity
and has no intention of doing so), contemplation (the subject is inactive but intends to
change), preparation (the subject is active but does not fulfil the recommendations for
healthy practice), action (the subject is active and fulfils the recommendations for healthy
practice but has not yet completed six full months of regular practice) and maintenance
(the subject has engaged in healthy physical activity for more than six months). The action
and maintenance stages of behaviour change are the most active [3,33].
SDT [
34
] is the most commonly used motivational theory in the study of physical
exercise. It is used to explain the phenomenon of adherence to sports practice [
35
]. In
SDT, motivation is situated on a continuum where three levels may be identified [
36
,
37
]:
intrinsic motivation (the most self-determined: engaging in an activity out of personal
pleasure), extrinsic motivation (engaging in an activity for external reward or recognition),
and amotivation (the least self-determined). Three basic psychological needs (BPNs)
are established: autonomy (engaging in activities on one’s own initiative), competence
(interacting efficiently with one’s surroundings to feel competent) and relatedness to others
(feeling part of a group) [
31
,
34
]. In SDT, BPNs are psychological mediators that influence
the three main types of motivation [
30
,
31
]. Studies have shown that high levels of self-
determined motivation act as a predictor of physical activity [
38
,
39
]. Other research has
revealed that highly motivated individuals dedicate more time to sport and engage in
sports practice more frequently [
40
]. Scientific evidence has also demonstrated the positive
association between self-determined motivation and levels of physical activity during
leisure time among adolescents [41].
Some studies have established a relationship between the stages of change and moti-
vation, or between SDT and TTM. Their findings show that people at the action and main-
tenance stages of change appear to experience more self-determined motivation [
3
,
42
–
44
].
It has even been observed that people at more advanced stages display greater willingness
to engage in exercise [
4
]. Two main lines of inquiry may be identified in the literature.
One points to the influence of quality and satisfaction on user loyalty (understood as a
greater frequency of sports practice) and the presence of higher levels of physical activity
among users who are loyal to sports organisations. The other concludes that users with
more self-determined motivation at more advanced stages of physical activity display high
levels of physical activity and express a stronger intention to continue with it. Therefore, it
is relevant to explore how different dimensions of the quality of sports services influence
satisfaction and loyalty among users aged 12 to 16 and to identify any differences between
minors at the maintenance stage and at the action stage. If such differences are found to be
present, different strategies for encouraging adherence to sports and health practice would
be required to reflect the needs of minors at each stage (Figure 1).

Int. J. Environ. Res. Public Health 2021,18, 10113 4 of 15
2. Materials and Methods
2.1. Subjects
The study population was made up of 1717 minors with a mean age of 13.83
±
1.32
who engage in organised physical activity at public sports centres in the metropolitan area
of Monterrey, Nuevo León (Mexico). Boys slightly outnumbered girls in the sample (51.5%).
The average session duration was 104.97
±
55.48 min, and 14.9% of users completed fewer
than three sessions of physical activity per week. 42.3% claimed to engage in physical
activity four or more times per week. 16.6% of the users were at less consolidated stages of
physical activity (precontemplation; contemplation; preparation).
2.2. Instruments
To identify the stage of change occupied by users of municipal public sports services,
Marcus & Forsyth’s questionnaire was used [
32
]. The questionnaire was adapted and
validated for the Mexican context by Zamarripa, Ruiz-Juan, & Ruiz-Risueño [
3
]. It consists
of a brief definition of the concepts of physical activity and regular physical activity, as
well as four statements requiring a dichotomous response (yes/no): (1) I am currently
physically active; (2) I intend to become more physically active in the next 6 months, (3) I
currently engage in regular physical activity; and (4) I have been regularly physically active
for the past 6 months. Prior research has confirmed the questionnaire’s reliability and
criterion validity [3,32].
The quality of the services and user satisfaction with them were assessed using the
24 items of the EPOD2: Sports Organisations Perception Scale, version 2 [
25
]. The items are
grouped into seven dimensions: sports instructors, service personnel, equipment, sports
facilities, communication, activity, and satisfaction. The instrument is a Likert scale ranging
from 1 (strongly disagree) to 5 (strongly agree). Loyalty was measured via four items on a
scale of future intentions among sports service users that ranged from 1 to 7 [
45
] (Table 1).
2.3. Procedure and Research Design
Before data collection began, a letter was sent to the directors of the municipal sports
centres participating in the study to request permission to proceed (San Nicolás de los
Garza, Monterrey, Escobedo, and Guadalupe). The participants’ legal guardians were then
asked to consent to their participation in the study. Participation was anonymous and
voluntary and the participants were able to ask questions about any items they did not
fully understand. All participants were informed of the security measures taken to protect
their anonymity and image and ensure the confidentiality of all data, and were told that
there were no right or wrong answers. They were asked to respond sincerely and honestly.
Participants took approximately 10 min to fill out the questionnaires. The question-
naires were administered at the reception of the municipal sports centres, where a person
was appointed to supervise their completion and answer any questions that arose. This
study complies with international ethical guidelines as recommended by the American
Psychological Association. Ethical approval was obtained from the Universidad Autónoma
de Nuevo León (Mexico), review committee 16CI19039021. The study was also approved
by the Vice-Rectorate for Research and Technology Transfer at the Universidad Pablo de
Olavide in Seville.

Int. J. Environ. Res. Public Health 2021,18, 10113 5 of 15
Table 1. Descriptive statistics, internal consistency, convergent and discriminant validity. Bivariate correlations.
Dimensions and Items Mean SD Skewness Kurtosis Factor
Loading Correlation
1 2 3 4 5 6 7 8
1. Sports instructors;
α
= 0.84; AVE = 0.68; CR = 0.89
- 0.409 ** 0.388 ** 0.650 ** 0.365 ** 0.585 ** 0.473 ** 0.527 **
I am happy with the treatment I have received so
far from the teacher/coach. 3.86 1.11 −0.814 0.060 0.818
I believe that the teacher/coach has been paying
appropriate attention to the users’ problems since
day one.
3.80 1.04 −0.614 −0.228 0.846
I believe that the teacher/coach adapts the
classes/training to the customers’ interests/needs.
3.84 1.02 −0.627 −0.147 0.819
I believe that the teacher/coach is encouraging the
group sufficiently. 3.96 1.04 −0.776 −0.074 0.815
2. Sports facilities; α= 0.85; AVE = 0.77; CR = 0.91 - - 0.604 ** 0.452 ** 0.440 ** 0.515 ** 0.464 ** 0.423 **
The changing rooms are sufficiently clean. 3.39 1.18 −0.278 −0.699 0.884
The changing rooms are spacious enough. 3.45 1.11 −0.211 −0.701 0.881
The facilities are clean enough. 3.44 1.14 −0.283 −0.652 0.869
3. Equipment; α= 0.83; AVE = 0.75; CR = 0.90 - - - 0.491 ** 0.439 ** 0.527 ** 0.417 ** 0.411 **
There is sufficient equipment for training. 3.50 1.13 −0.333 −0.650 0.863
The equipment is in good condition for use. 3.57 1.08 −0.333 −0.523 0.905
The equipment is modern. 3.43 1.15 −0.293 −0.672 0.837
4. Activity; α= 0.82; AVE = 0.58; CR = 0.87 - - - - 0.499 ** 0.659 ** 0.563 ** 0.619 **
The activity is enjoyable. 3.82 1.05 −0.610 −0.162 0.782
The tasks carried out in the training sessions are
diverse enough. 3.88 0.98 −0.617 −0.133 0.819
Activities end at the appointed time. 3.85 1.10 −0.725 −0.219 0.723
I get the expected results with this activity. 3.87 1.03 −0.769 0.145 0.783
It was easy for me to join the activity I am
participating in. 3.85 1.09 −0.745 −0.109 0.717
5. Communication;
α
= 0.81; AVE = 0.73; CR = 0.89
- - - - - 0.542 ** 0.555 ** 0.510 **
The facilities have several means of receiving
suggestions (suggestion box, bulletin board). 3.26 1.21 −0.164 −0.849 0.823
The information on the activities offered at the
centre is appropriate. 3.59 1.06 −0.304 −0.488 0.869
The range of activities is constantly being updated.
3.55 1.09 −0.291 −0.590 0.871

Int. J. Environ. Res. Public Health 2021,18, 10113 6 of 15
Table 1. Cont.
Dimensions and Items Mean SD Skewness Kurtosis Factor
Loading Correlation
6. Service personnel;
α
= 0.80; AVE = 0.83; CR = 0.91
- - - - - - 0.619 ** 0.624 **
The staff are friendly. 3.80 1.06 −0.647 −0.094 0.916
The staff at the facility have a good relationship
with each other. 3.87 1.02 −0.602 −0.260 0.916
7. Satisfaction; α= 0.89; AVE = 0.75; CR = 0.92 - - - - - - - 0.614 **
Joining this club was a good decision. 3.98 1.01 −0.786 0.096 0.871
I am glad I joined this club. 4.05 0.95 −0.731 −0.080 0.894
It was a good decision to engage in sports
activities in this club. 4.04 0.95 −0.754 0.017 0.887
I am pleased to be enrolled in this club. 4.06 0.98 −0.853 0.113 0.824
8. Loyalty; α= 0.88; AVE = 0.70; CR = 0.92 - - - - - - - -
I will share the positive aspects of this sports club
with other people. 5.50 1.41 −1.004 0.778 0.855
I will recommend this sports centre to anyone
seeking my advice. 5.54 1.34 −0.850 0.190 0.892
I will encourage my friends and family to
participate in sports activities at this centre. 5.59 1.39 −0.897 0.158 0.860
I would consider this club as my first choice for
any sports service I might need. 5.50 1.45 −0.938 0.404 0.844
In the next few years, I will take part in more
sports activities in this club. 5.26 1.65 −0.882 0.050 0.734
SD: Standard Deviation; AVE: Average Variance Extracted; CR: Composite Reliability; ** p< 0.001.

Int. J. Environ. Res. Public Health 2021,18, 10113 7 of 15
2.4. Statistical Analysis
First, a series of exploratory tests of the items were carried out, such as the calculation
of frequencies, means, standard deviations (SD), skewness, kurtosis and factor loading.
In order to verify the reliability and validity of the instruments used in this research,
correlations between the study constructs, average variance extracted (AVE), composite
reliability (CR), and Cronbach’s alpha were calculated. Analysis of variance (ANOVA)
and contingency tables were used to compare means and proportions between groups of
the latent variables studied, studying the size of the effect. Calculations were performed
using a spreadsheet in Excel and the Statistical Package for the Social Sciences (SPSS, IBM,
Armonk, NY, USA), version 22.0. The model linking perceived quality (sports instructors,
service personnel, equipment, sports facilities, communication, activity), satisfaction, and
loyalty was then tested using the programme Analysis of Moment Structure (AMOS, IBM,
Armonk, NY, USA), version 22.0. A confirmatory factor analysis of the model was carried
out, followed by a multi-group analysis. Byrne’s guidelines [
46
] were followed: firstly, the
model fit for each sample was checked separately (total population, model 0; users at less
consolidated stages, model 0a; users at consolidated stages, model 0b). The variation of
the model between the groups was then checked; this involved specifying a model with
equal parameters for all groups and comparing this model with a less restrictive model
with parameters free to take any value. This procedure allowed the invariance of the factor
structure of the model to be checked. The aim of the analysis was to determine whether
the model linking quality and its dimensions to satisfaction and loyalty was the same for
both groups of users: users at less consolidated stages and users at consolidated stages
of physical activity. The maximum likelihood method was used [
47
]. The adjustment of
each model was assessed by examining various indices. The Root Mean Square Error of
Approximation (RMSEA), the Comparative Fit Index (CFI), the Expected Cross-Validation
Index (ECVI), and the Akaike Information Criterion (AIC) were used. The
χ2
value (CMIN)
and the
χ2
value/degrees of freedom (CMIN/DF) were also used. RMSEA values < 0.07
indicate an acceptable fit [
48
] and RMSEA values
≤
0.06 indicate a good fit [
49
]. CFI
values
≥
0.95 are considered to be acceptable [
49
]. Small AIC and ECVI values suggest
a good model fit [
50
]. With respect to the
χ2
value/degrees of freedom ratio, a perfect
model would yield a value of 1.00, and ratios below 2.00 would be considered to be
indicators of a very good model fit, while values below 5.00 would be considered to be
acceptable [
49
,
51
,
52
]. Invariance in measurement between groups was assessed using
the
∆χ2
test and the recommendations of Chen [
53
] and Cheung & Rensvold [
54
] were
followed, which state that the cut-off values
∆
CFI
≤
0.01 and
∆
RMSEA
≤
0.015 indicate
the absence of differences between models. Finally, the standardised regression coefficients
were calculated for the relationships in the model by groups of users.
3. Results
83.4% of the minors in the study were at advanced stages of consolidation of physical
activity. The majority of the participants were at the maintenance stage. Gender differ-
ences were observed between the different stages. A higher proportion of girls were at
consolidated stages. No significant differences were observed by age. An analysis of the
dimensions of quality revealed significant differences between the consolidated group and
the less consolidated group for all dimensions. The consolidated group rated all dimen-
sions of service quality higher than users at less consolidated stages; the same phenomenon
was observed for satisfaction and loyalty (Table 2).

Int. J. Environ. Res. Public Health 2021,18, 10113 8 of 15
Table 2. Stages of change, gender, age, perceived quality, satisfaction, and loyalty. Percentages, means, and standard deviations. Contingency table and ANOVA.
Socio-Demographic
Variables and
Dimensions
Stages of Change Groups
1 2 3 4 5 Total Less Consolidated
Stages Later Stages Comparison Size Effect
Total 1.6% 8.7% 6.3% 14.1% 69.3% 16.6% 83.4%
0.009
Male 1.8% 10.3% 6.8% 15.3% 65.9% 18.9% 81.1% 0.063
Female 1.3% 7.0% 5.9% 12.9% 73.0% 14.2% 85.8%
Age 13.85 ±1.29 14.04 ±1.24 13.66 ±1.26 13.79 ±1.32 13.82 ±1.33 13.83 ±1.32 13.88 ±1.26 13.82 ±1.33 0.498
INS 3.52 ±1.17 3.65 ±0.79 3.68 ±0.95 3.69 ±0.81 3.95 ±0.86 3.86 ±0.87 3.65 ±0.89 3.90 ±0.86 0.000 0.012
SP 3.64 ±1.17 3.63 ±0.75 3.49 ±0.91 3.68 ±0.84 3.92 ±0.83 3.83 ±0.84 3.58 ±0.86 3.88 ±0.83 0.000 0.017
SF 3.23 ±1.19 3.33 ±0.91 3.04 ±1.09 3.36 ±0.94 3.50 ±1.01 3.43 ±1.01 3.21 ±1.02 3.47 ±1.00 0.000 0.009
EQP 3.25 ±1.21 3.43 ±0.86 3.11 ±1.11 3.46 ±0.92 3.56 ±0.97 3.50 ±0.97 3.20 ±1.00 3.54 ±0.96 0.000 0.006
ACT 3.47 ±1.10 3.62 ±0.74 3.69 ±0.85 3.74 ±0.74 3.93 ±0.79 3.86 ±0.80 3.63 ±0.82 3.90 ±0.79 0.000 0.015
COMM 3.23 ±1.12 3.38 ±0.84 3.12 ±1.03 3.30 ±0.93 3.54 ± −95 3.46 ±0.96 3.27 ±0.95 3.50 ±0.95 0.000 0.008
SATS 3.67 ±1.22 3.70 ±0.94 3.71 ±1.01 3.79 ±0.89 3.99 ±0.90 3.91 ±0.92 3.70 ±0.99 3.95 ±0.90 0.000 0.010
LOY 4.80 ±1.61 5.13 ±1.18 5.10 ±1.28 5.28 ±1.13 5.61 ±1.18 5.48 ±1.21 5.09 ±1.26 5.56 ±0.1.18 0.000 0.021
INS: Sports instructor; SP: Service personnel; SF: Sports facilities; EQP: Equipment; ACT: Activity; COMM: Communication; SATS: Satisfaction; LOY: Loyalty; 1: Precontemplation; 2: Contemplation;
3: Preparation; 4: Action; 5: Maintenance.

Int. J. Environ. Res. Public Health 2021,18, 10113 9 of 15
Once the presence of differences in quality assessments, satisfaction, and loyalty to
the sports organisations providing services to the minors had been confirmed, it was time
to identify any differences in the relationships between the different dimensions and the
factors comprising the model that links quality, satisfaction, and loyalty. Firstly, the model
was tested. Table 3shows that the analysed model displays adequate adjustment indices
for the total study population (model 0), for users at less consolidated stages (model 0a),
and for users at consolidated stages (model 0b).
Table 3.
Adjustment statistics for the models. Comparison between models using model 1 as correct in the two groups of
users aged 12–16.
Goodness-of-Fit Indices and Model Comparisons for Tested Models
Model CMIN DF CMIN/DF CFI RMSEA ECVI AIC
0 896.370 349 2.568 0.965 0.041 1.165 1068.370
0a 633.172 349 1.814 0.922 0.059 3.426 805.172
0b 647.129 349 1.854 0.973 0.037 1.296 819.129
1 2231.567 698 3.197 0.948 0.036 1.502 2575.567
2 2270.842 719 3.158 0.948 0.035 1.500 2572.842
3 2282.322 732 3.118 0.948 0.035 1.492 2558.322
4 2333.449 753 3.099 0.947 0.035 1.497 2567.449
5 2344.171 755 3.105 0.947 0.035 1.501 2574.171
Comparisons of Conditions Using Measurement Invariance Procedures
Model correct Model Dif. DF Dif. CMIN pDif. CFI Dif.
RMSEA
Assuming model 1 to be correct
2 21 39.275 0.009 0.000 −0.001
3 34 50.756 0.032 0.000 −0.001
4 55 101.882 0.000 −0.001 −0.001
5 57 112.604 0.000 −0.001 −0.001
Assuming model 2 to be correct
3 13 11.481 0.571 0.000 0.000
4 34 62.607 0.002 −0.001 0.000
5 36 73.330 0.000 −0.001 0.000
Assuming model 3 to be correct 4 21 51.126 0.000 −0.001 0.000
5 23 61.849 0.000 −0.001 0.000
Assuming model 4 to be correct 5 2 10.722 0.005 0.000 0.000
Note. Model 0, total number of minors; model 0a, minors at less consolidated stages; model 0b, minors at advanced stages; model 1, no
parameters constrained to be equal across groups; model 2, factor loadings constrained to be equal; model 3, observed structural weights
and factor loadings constrained to be equal; model 4, observed structural covariances, structural weights, and factor loadings constrained
to be equal; model 5, observed structural residuals, structural covariances, structural weights, and factor loadings constrained to be equal.
Dif. CMIN, difference between models; Dif. DF, difference between models; p= significance level between models; Dif. CFI, difference
between models; Dif. RMSEA, difference between models.
In order to compare the model for the two groups of minors classified by stage of
change (Table 2), factor invariance tests were performed. When the difference in
χ2
between
the unrestricted models (model 1) and the other models was considered for the two groups
of minors, significant differences became apparent. There were also differences when
models 2, 3, 4, and 5 were compared with one another. Meanwhile, the CFI and RMSEA
values for all the models were very similar, with a difference between them of less than 0.01
and 0.015 respectively, indicating the factor invariance of the model for studying differences
by minors’ stages of change (Table 3).
The results have shown that sports instructors, service personnel, and the specific
activity are predictors of satisfaction for the total study population. Satisfaction and the
activity factor have a direct effect on loyalty, while sports instructors, service personnel,
and activity are indirect predictors of loyalty. These results are repeated in the population
at a consolidated stage of physical activity. It is important to note that communication
is a predictor of loyalty among consolidated users but not among the total population.

Int. J. Environ. Res. Public Health 2021,18, 10113 10 of 15
However, service personnel and activity are predictors of satisfaction among the group
of less consolidated users. Only service personnel have a direct effect on loyalty among
minors at less advanced stages of consolidation of physical and sports practice (Table 4).
Table 4.
Comparison between standardised and unstandardised regression coefficients and significance levels of the two
groups of users aged 12–16.
Total Users Less Consolidated Group More Advanced Group
Direct Effects Indirect Effects Direct Effects Indirect Effects Direct Effects Indirect Effects
Relations between
Dimensions Beta Beta Beta Beta Beta Beta
SATS
←INS 0.110 * – 0.177 – 0.099 * –
SATS
←SS 0.447 ** – 0.431 ** – 0.446 ** –
SATS
←
COMM
0.015 – 0.078 – 0.003 –
SATS
←ACT 0.306 ** – 0.299 * – 0.307 ** –
SATS
←EQP 0.024 – 0.024 – 0.017 –
SATS
←SF 0.016 – 0.043 – 0.018 –
LOY ←
SATS
0.426 ** – 0.254 – 0.444 ** –
LOY ←INS 0.057 0.047 * 0.091 – 0.051 0.044 *
LOY ←SP 0.110 0.191 ** 0.393 * – 0.058 0.198 **
LOY ←
COMM
0.090 – 0.019 – 0.106 * –
LOY ←ACT 0.221 * 0.130 * 0.181 – 0.227 ** 0.137 **
LOY ←EQP −0.045 – 0.055 – −0.048 –
LOY ←SF 0.040 – −0.056 – 0.052 –
INS: Sports instructor; SP: Service personnel; SF: Sports facilities; EQP: Equipment; ACT: Activity; COMM: Communication; SATS:
Satisfaction; LOY: Loyalty; * p< 0.05; ** p< 0.001.
4. Discussion
Sedentary habits and a lack of physical activity have risen among the general pop-
ulation, becoming a significant concern due to the risks of mortality and morbidity that
they entail. Sedentary behaviours are replicated by children and adolescents, resulting in
a decline in their current health and a direct impact on their future health and lifestyle.
Therefore, it is important to maintain and increase levels of physical activity among chil-
dren and young people as high levels of physical and sports practice are associated with
consolidated stages of physical activity and greater willingness to exercise. Sports and
health services must seek strategies to encourage the practice of physical activity and sport
among their users, especially among children. The aim of this study was to ascertain which
dimensions of the quality of sports and health services influence satisfaction and loyalty
among users aged 12–16 and how these dimensions affect the relationships between these
concepts and the stages of behaviour change.
To confirm the validity and reliability of the study, the items were first analysed quan-
titatively. The mean score of the study items and factors was examined. The results showed
values around the middle of the scale and a standard deviation close to 1, demonstrating the
normality of the results according to Carretero-Dios & Pérez [
55
]. Reliability was confirmed
using Cronbach’s
α
, obtaining adequate values. Convergent validity was determined via
correlations between the study factors using Pearson’s coefficient. The correlations were
positive and significantly related, demonstrating this type of validity. Another test used to
ascertain the instrument’s validity were the CR and AVE values. The acceptable values
were >0.6 for CR and >0.5 for AVE [
56
,
57
]; the results exceeded the values suggested in the
literature, so they were confirmed to be valid.
The validity of the model linking quality and its dimensions to satisfaction and loyalty
was then tested via a confirmatory factor analysis. The parameters were estimated using
the maximum likelihood method, following Thompson’s recommendation [
47
]. To evaluate
the adequacy of the model, a group of indices were assessed jointly (CMIN, DF, CMIN/DF,
CFI, RMSEA, AIC, and ECVI). Byrne’s [
46
] suggestions were followed, so the model was
studied for the total population (model 0) and for the two groups of users: minors at

Int. J. Environ. Res. Public Health 2021,18, 10113 11 of 15
less consolidated stages (model 0a) and minors at advanced stages (model 0b). The fit
indices were adequate for all models. The variance of the model between the groups was
then checked; this involved specifying a model with equal parameters for all groups and
comparing this model with a less restrictive model with parameters free to take any value.
This procedure allowed the invariance of the factor structure of the model to be checked.
When the difference in
χ2
between the unrestricted models (model 1) and the other models
was considered for the two groups of minors, significant differences emerged. There
were also differences when models 2, 3, 4, and 5 were compared with one another. Since
CMIN/DF is sensitive to sample size, the criterion established by Cheung & Rensvold [
58
]
with regard to the
∆
CFI and the
∆
RMSEA was also used. According to them, invariance
is admitted when
∆
CFI
≤
0.01 and
∆
RMSEA
≤
0.015. The CFI and RMSEA values for
all the models were very similar, with a difference between them of less than 0.01 and
0.015 respectively, indicating the factor invariance of the model for studying differences by
minors’ stages of change.
The descriptive analysis of the results shows that most minors using sports and health
services are at the maintenance stage, which appears logical as this population regularly
engages in physical activity. Moreover, according to Daley & Duda [
58
], who view the
TTM in quantitative terms, there is a relationship between the amount of physical activity
practised and the more advanced stages. In order to be included in the maintenance
stage, users had to have been active throughout the past six months. This points to the
considerable levels of physical activity practised by the majority of users of these types of
services. Another aspect of note are the significant differences in the percentage of users
at more advanced stages of consolidation of physical activity, with a higher proportion of
girls found at these stages. The researchers had already observed this difference among
university students, attributing it to greater self-determined motivation among women.
Future research could explore how motivation affects quality, satisfaction, and loyalty to
sports and health services.
The multi-group analysis showed that satisfaction is predicted by sports instructors,
service and administrative personnel, and the specific activity in the total population
and in the group of minors at more consolidated stages of physical activity. Despite the
absence of differences between the groups of minors, only the activity dimension and the
service and administrative personnel dimensions were predictors of satisfaction among
the minors at less consolidated stages. This difference may owe to motivational issues,
as
Nuviala et al. [26]
demonstrated in a study grouping users of these services by their
motivations for practising physical activity. Higher levels of self-determined motivation are
found among groups at more consolidated stages of physical activity, as Dueñas-Dorado
et al. and Zamarripa et al. [
3
,
5
] observe. Equally, it is important to note the similarity
between the results of this study and the findings of Haro-González et al. [
59
] in elderly
women using sports services. The sports facilities dimension was found not to predict
loyalty; nor did being a woman who attends sports centres not exclusively catering to
women. This finding was explained by the different socioeconomic profile of the two
groups of women. Therefore, motivation and the socioeconomic profile of sports and
health service users could be two important variables to consider when implementing
strategies to improve quality and build loyalty.
A direct relationship between satisfaction and loyalty was also observed among the
total population and the minors at consolidated stages of physical activity, demonstrating
the significant role of satisfaction in building loyalty [
18
,
60
,
61
], one of the most important
factors influencing users’ future intentions and behaviours. It is important for these services
to achieve high levels of satisfaction [
19
] as building loyalty in the sports and health services
market leads to the development of more healthy lifestyles [23].
With regard to the relationships between the dimensions of quality and their effect on
loyalty to sports and health services, the activity dimension emerged as the only predictor
of loyalty for the total population. Nuviala et al. [
62
] showed that the programme of
activities was a key component in school-age children’s participation, as there is a direct

Int. J. Environ. Res. Public Health 2021,18, 10113 12 of 15
relationship between activity quality and level of practice. Quality in programmes of
sports activities is understood as a range of services that reflects minors’ interests and
needs as closely as possible, encouraging greater loyalty among them [
63
]. Therefore, it
is important to determine adolescents’ motivations for engaging in sports activities [
64
].
Sports instructors, service and administrative personnel, and the specific activity have an
indirect relationship with loyalty via satisfaction in the total population. These results can
be observed in the group of minors at consolidated stages of practice.
Interestingly, communication is a direct predictor of loyalty in the group of minors
at more consolidated stages. Fernández-Martínez et al. [
65
] demonstrated the presence of
this direct relationship in sports and health services among Spanish minors of both sexes.
Despite the effect of communication on loyalty, this topic has not been studied in depth
and few studies have sought to examine it. The importance of word-of-mouth [
45
,
61
] as a
vehicle for influencing peers to engage in the specific behaviour of physical activity [
66
,
67
]
has also been overlooked.
Another of the most relevant findings is that the only element to display significant
differences between the groups is the direct influence of service and administrative per-
sonnel on loyalty towards sports and health services among minors at less consolidated
stages, whereas this influence is indirect among the total population and the group at
more consolidated stages. This is a hugely important finding given the role played by this
group of employees. Haro-González et al. [
59
] and Macintosh & Doherty [
68
] highlighted
the importance of these personnel for user satisfaction. It is possible that the influence
of service and administrative personnel originates in the organisational culture, which
influences customer perceptions [
68
] and user satisfaction [
69
]. For this reason, sports and
health services should work on organisational culture with their staff as a key variable,
especially service and administrative personnel who add value to the range of activities on
offer [63].
Due to the importance of consolidating physical activity among young people (as it
results in improved current and future health and consolidates the habit of sports practice
and healthy activities), it is important to continue researching this topic and introducing
new elements or modifying existing ones. It would be interesting to conduct a more detailed
analysis of the sociodemographic profile of service users and assess the impact of this
variable on loyalty. Moreover, high levels of self-determined motivation are associated with
high levels of adherence to sports practice, but whether or not intrinsic motivation directly
modifies the relationship between quality, satisfaction, and loyalty remains unknown.
Human resources (sports instructors and service personnel) have become one of the
key components of loyalty towards sports and health services. It would be helpful to anal-
yse the profile of these professionals in order to find out more about them. Communication
from the organisation, be it directly via its human resources or indirectly via different
types of messages and channels, is another relevant dimension to consider. Assessing
the influence of communication on loyalty to the service and adherence to the practice of
physical activity would be another fruitful line of research.
The activities themselves, another key component of adherence, should be analysed
in more detail. It would also be interesting to find out whether or not the use of different
methods by sports instructors affects adherence to physical activity. This relationship may
differ depending on the type of activity practised, so an in-depth study of the topic would
be required.
5. Conclusions
The latent variables satisfaction and physical activities carried out at sports and health
services aimed at adolescents are direct precursors of adherence and loyalty to the practice
of physical activity in this age group. Human resources (sports instructors and service
personnel) and physical activity are indirect precursors of loyalty via satisfaction. It is also
important to note that service personnel play an important role in building loyalty among
boys and girls at less consolidated stages.

Int. J. Environ. Res. Public Health 2021,18, 10113 13 of 15
Author Contributions:
Conceptualisation, L.A.D.-D. and A.N.; methodology, A.N. and A.F.-M.;
software, L.A.D.-D. and M.R.T.-V.; validation, A.N. and A.F.-M.; formal analysis, A.N.; investigation,
L.A.D.-D.; writing—original draft preparation, A.F.-M.; L.A.D.-D. and A.N.; writing—review and
editing, A.F.-M. and A.N.; visualisation, M.R.T.-V.; supervision, A.F.-M. and A.N. All authors have
read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement:
The study was conducted according to the guidelines of
the Declaration of Helsinki and approved by the Universidad Autónoma de Nuevo León (Mexico),
review committee 16CI19039021. The study was also approved by the Vice-Rectorate for Research
and Technology Transfer at the Universidad Pablo de Olavide in Seville.
Informed Consent Statement:
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement:
The data presented in this study are available on request from the
corresponding authors.
Conflicts of Interest: The authors declare no conflict of interest.
Abbreviations
TTM: Transtheoretical Model; DST: Self-determination Theory; BNP: Basic Psychological Needs;
EPOD2: Sports Organisations Perception Scale, version 2; AVE: Average Variance Extracted; CR:
Composite Reliability; SPSS: Statistical Package for the Social Sciences; AMOS: Analysis of Moment
Structure; RMSEA: Root Mean Square Error of Approximation; CFI: Comparative Fix Index; ECVI:
Expected Cross Validation Index; AIC: Akaike Information Criterion; CMIN: chi-squared; DF: De-
grees of Freedom; ∆: Increase.
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