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Electronic Journal of Research in Educational Psychology, 19 (2), 416-436. ISSN:1696-2095. 2021. no. 54 416
Validation of the Amotivation Inventory in
Physical Education: physical activity and
physical self-concept
María Jesús Lirola1, Christopher M. Spray 2
1 Universidad Miguel Hernández
2 Loughborough University
Spain
United Kingdom
Correspondencia: María Jesús Lirola. Universidad Miguel Hernández de Elche. E-mail: mlirola@umh.es
© Universidad de Almería and Ilustre Colegio Oficial de la Psicología de Andalucía Oriental (Spain))
Validation of the Amotivation Inventory in Physical Education: exercise level and physical self-concept
Electronic Journal of Research in Educational Psychology, 19 (2), 416-436. ISSN:1696-2095. 2021. no. 54 417
Abstract
Introduction. According to Self-Determination Theory, it is known that motivation is an
essential factor for the adherence and enjoyment of exercise, generating long-lasting habits.
The importance of generating such habits from an early age is a determining factor in the fu-
ture health of people. The child and youth population invests a great amount of hours per
week in their training in Educational Centers. The objective of this investigation was to adapt
the Amotivation Inventory-Physical Education to the Spanish context, in addition to examin-
ing its psychometric properties.
Method. Two hundred thirty-two boys and girls from 6th grade of Primary Education partic-
ipated. Ages ranged from 10 to 12 years old (Mage = 10.99; SD = .47).
Results. The results of the confirmatory factor analysis showed adequate model fit. In addi-
tion, the factor structure was shown to be invariant by gender. High levels of internal con-
sistency were obtained and external validity was shown through a linear regression analysis
with physical activity behaviour and physical self-concept as independent variables to explain
amotivation in physical education lessons.
Discussion and Conclusion. In conclusion, the scale is shown to be a reliable, gender-
invariant and valid measure with both boys and girls in Primary Education.
Keywords: Motivationals factors; healthy habits; young population; body image
María Jesús Lirola & Christopher M. Spray
418 Electronic Journal of Research in Educational Psychology, 19(2), 416-436. ISSN:1696-2095. 2021. no. 54
Resumen
Introducción. Según la teoría de la autodeterminación, se conoce que la motivación es un
factor esencial para la adherencia y el disfrute del ejercicio, generando hábitos duraderos. La
importancia de generar tales hábitos desde una edad temprana es un factor determinante para
la salud futura. La población infantil y juvenil invierte una gran cantidad de horas semanales
en su formación en Centros Educativos. El objetivo de esta investigación fue adaptar el Inven-
tario de desmotivación en Educación Física al contexto español, además de examinar sus pro-
piedades psicométricas.
Método. Participaron 232 niños y niñas de 6º curso de Educación Primaria. Las edades osci-
laron entre los 10 y los 12 años (Medad = 10.99; DT = .47).
Resultados. Los resultados del análisis factorial confirmatorio mostraron índices de ajuste
adecuados. Además, se mostró su invarianza según el género. Se obtuvieron altos niveles de
consistencia interna y evidencias de validez externa a través de un análisis de regresión lineal
con las variables de nivel de ejercicio físico y autoconcepto físico para explicar la desmotiva-
ción en las clases de Educación Física.
Discusión y Conclusion: En conclusión, la escala se muestra como una medida fiable, inva-
riable por género y válida para niños y niñas en la Educación Primaria.
Palabras clave: Factores motivacionales; hábitos saludables; población joven; imagen cor-
poral
Validation of the Amotivation Inventory in Physical Education: exercise level and physical self-concept
Electronic Journal of Research in Educational Psychology, 19 (2), 416-436. ISSN:1696-2095. 2021. no. 54 419
Introduction
Based on reports from the World Health Organization (WHO, 2019) concerning the
current health status of the population, it can be found that there is a progressive deterioration
in general health levels over the last few decades, which predicts a decline in terms of quality
of life and its length in years. There are many benefits and studies that contrast and recom-
mend the performance of any type of physical activity as a daily habit for the improvement of
current health and as a means to enjoy better future health, either at physical, psychological or
social levels (Duque-Fernández, Ornelas-Contreras, & Benavides-Pando, 2020; Ramos &
Coduras, 2020). Despite all the benefits and recommendations made by recognized institu-
tions (i.e., WHO, 2019), the most recent scientific evidence shows that levels of exercise
practice decline when children promote from primary to secondary schools, showing insuffi-
cient levels for experiencing the benefits derived from its practice (Scherrer & Preckel, 2019;
Wu, Tao, Zhang, Zhang, & Tao, 2015). In this sense, the promotion of healthy habits (i.e., the
promotion of physical activity) in this population group has become a priority.
Extensive research reflects the importance of building healthy habits from an early
age, since activities performed during this stage of life seem to be more enduring over time
even manifesting themselves as part of a person's daily life for the rest of their life (Hoyt,
Chase-Lansdale, McDade, & Adam, 2012; Paes, & Bianchini, 2015). This segment of the
population spends a large volume of hours in schools, thus experts in the field recommend
that these centers be promoters of a holistic and integrated education, where correct health
habits, such as regular exercise, are encouraged (Frantz, 2015; St Leger, & Young, 2009). For
this reason, educational centres would be a key part within the process of promoting healthy
habits in children and young people, thus helping to achieve the recommendations described
above. Following the timetable established in the schools of Education, we can find different
subjects or disciplines among which Physical Education stands out; these classes would play a
key role in the work and promotion towards adherence to exercise as a healthy habit (Gallotta
et al., 2016). Specifically, Physical Education lessons can help develop healthy exercise be-
haviour not only at school, but also influence the decisions made by children outside school in
their spare time (OFSTED, 2013). On the one hand, there are strong reasons to explore phe-
nomena related to physical education lessons with the purpose of expanding knowledge relat-
ed to the promotion and adherence to childhood physical activity in different contexts. On the
María Jesús Lirola & Christopher M. Spray
420 Electronic Journal of Research in Educational Psychology, 19(2), 416-436. ISSN:1696-2095. 2021. no. 54
other hand, the end of the Primary Education stage seems to be a year of great interest as it is
a period of transition towards the compulsory Secondary Education stage, where changes take
place in terms of interpersonal and motivational factors related to the practice of physical ed-
ucation (Taylor, Spray & Pearson, 2014).
A macro-theory that has been extensively investigated in the context of Physical Edu-
cation lessons and that provides light to the analysis of student's behaviours and motivation
towards the practice of exercise, would be Self-Determination Theory (SDT; Deci & Ryan,
2012; Ryan & Deci, 2019). SDT delves into human motivation, and in particular within the
context of Physical Education lessons, it has been possible to study the motivational factors
that affect children in their relationship with physical activity (e.g., Ntoumanis, 2012). This
theory distinguishes various level of motivation according to their degree of self-
determination. Thus, for example, intrinsic motivation would represent the most self-
determined type of motivation; such motivation arises when the activity is performed by the
fact that it is attractive and interesting (Deci & Ryan, 2012). In decreasing order regarding the
self-determination degree, it can be found four different types of extrinsic motivation (i.e.,
integrated regulation, identified regulation, introjected regulation and external regulation).
Finally, amotivation remains, in which the person completely lacks any type of motivation to
participate in the activity and, therefore, would not maintain any type of involvement with it
(Ryan & Deci, 2019).
Relative to both intrinsic (i.e., performing an activity for the mere enjoyment of its
performance) and extrinsic motivation (i.e., performing an activity as a vehicle for achieving
an external goal or approval), amotivation is associated with the poorest degree of self-
determination and involves a total absence of desire and interest in performing such behaviour
(Deci and Ryan, 2002). In this line, it has been studied that people who present a lack of mo-
tivation towards a concrete activity, are not consistent in the realization of the mentioned ac-
tivity, due to the lack of connection that exists between their own realization and the conse-
quences derived from their participation (Pelletier, Fortier, Vallerand, & Briere, 2001). Be-
cause of the lack of connection with the benefits derived from their practice, these people will
invest little time and energy in its realization (Ntoumanis et al., 2004). In order to improve the
understanding of this factor (i.e., amotivation) and taking into account the particularity of the
educational system environment, Green-Demers et al. (2008) created and conceptually vali-
dated from a multidimensional perspective the construct of amotivation. Specifically, they
Validation of the Amotivation Inventory in Physical Education: exercise level and physical self-concept
Electronic Journal of Research in Educational Psychology, 19 (2), 416-436. ISSN:1696-2095. 2021. no. 54 421
developed four dimensions for amotivation, being: a) deficient ability beliefs, b) deficient
effort beliefs, c) insufficient academic values, and d) unappealing characteristics of school
tasks.
When students experience a belief in deficient ability, it may lead to amotivation when
they feel that their scholastic weakness are due to poor perception of competence and when
they experience reduced expectancy of self-efficacy in the completion of school tasks (Wig-
field & Eccles, 2000). Even if students are fully aware of those aspects, or tasks, that are ex-
pected of them and know how to perform them, they may feel that they do not possess the
skills or abilities needed to respond and cope with the requested task (Pelletier, Dion, Tuson,
& Green-Demers, 1999). In the case of amotivation, this can derive from the belief in ineffec-
tive or insufficient effort, from the absence of desire or ability to make the required effort in
scholastic tasks. Children may be reticent and hesitant to engage in behaviour if it requires an
investment of effort or if the requested activity or task subsequently shows no transference
into their daily lives. Unattractive homework may contribute to student amotivation (Legault,
Green-Demers, & Pelletier, 2006). For their part, Ainley, Hidi and Berndorff (2002) pointed
out how people need to feel a certain level of enjoyment or attraction in order for a behaviour
to be performed.
Notwithstanding the existence of previous studies within SDT framework contributing
to a deeper understanding of amotivation, most of them treated amotivation as a one-
dimensional construction. In this line, in the Spanish context, research has been conducted
that has taken into account the role of amotivation either towards exercise or in physical edu-
cation classes and its relationship with maladaptive psychological constructs, such as present-
ing lower resilience or manifesting anxious behaviours (Trigueros et al., 2019; Trigueros et
al., 2020). However, based on the complexity of the educational system and school subjects
and context, Shen, McCaughtry, and Martin (2008) reported that because of the particular
school context and the diversity of spaces where learning takes place, these could significant-
ly influence the type of motivation pupils could manifest. It is clear that the reasons why chil-
dren may lose motivation may have different origins, conceptualizing amotivation as a single,
general construct would not help to explain the scenario of low motivation levels in school
settings. Legault et al. (2006) already defined amotivation within the academic context as a
multifaceted variable that was attended to and dependent on multiple factors in order to be-
come manifest.
María Jesús Lirola & Christopher M. Spray
422 Electronic Journal of Research in Educational Psychology, 19(2), 416-436. ISSN:1696-2095. 2021. no. 54
In accordance with the defined multidimensional concept of amotivation in education,
Legault et al. (2006) generated the Academic Amotivation Inventory. The inventory was de-
signed to examine and analyze the reasons students had for not showing interest in learning or
performing their academic tasks. Using exploratory factor analysis and first- and second-order
confirmatory factor analysis, the authors offered evidence for structuring academic amotiva-
tion in four factors: ability beliefs, effort beliefs, task characteristics, and task value. In addi-
tion, this four-factor structure was tested through discriminant validity and construct validity
analysis with linked psychological and behavioural constructs (e.g., academic performance,
self-esteem, anxiety, basic psychological needs, and subjective vitality) (Legault et al., 2006;
Vlachopoulos, Katartzi, & Kontou, 2013). This tool was developed and evaluated in the class-
rooms themselves. Subsequently, Shen, Winger, Li, Sun, and Rukavina, (2010a) adapted this
scale to measure participation intentions in specific PE lessons.
Objectives and hypotheses
The aim of this study will be to validate to the Spanish context the scale that Shen et
al. (2010) adapted to evaluate amotivation in the Physical Education discipline, as well as to
show evidence of its external validity by relating the dimensions that compose amotivation
with the psychological variable of positive self-concept and the frequency of physical activity.
It has been shown that amotivation maintains a negative relationship with other positive psy-
chological aspects (Baker, 2004; Pelletier et al, 2001; Vallerand et al., 1993) and that the lack
of motivation leads to the inhibition of behaviour itself (Ryan & Deci, 2019). Thus, it is hy-
pothesized that these constructs with amotivation will show a negative relationship.
Method
Participants
A total of 232 boys and girls from 6th grade of Primary Education (130 boys and 102
girls) aged 10-12 years participated in the study (Mage = 10.99; SD = .47). They belonged to
six different primary schools in the province of Almería (Spain).
Instruments
Validation of the Amotivation Inventory in Physical Education: exercise level and physical self-concept
Electronic Journal of Research in Educational Psychology, 19 (2), 416-436. ISSN:1696-2095. 2021. no. 54 423
Amotivation. An adapted version of Shen et al. (2010) Amotivation Inventory-Physical
Education (AI-PE) was applied to measure the motives of students for not wanting to take
part in Physical Education (see Appendix). The AI-PE comprises 16 items distributed among
the four factors proposed for amotivation: Ability beliefs (e.g., "Because I'm not good at PE");
Effort beliefs (e.g., "Because I don't have the energy to participate in PE"); Task characteris-
tics (e.g., "Because I find that the activities being played is boring"); and Value assigned to
the task (e.g., "Because participating in PE is not valuable to me"). The answers were collect-
ed on a Likert-type scale from 1 to 7, the answers corresponding to their reasons for not want-
ing to participate in Physical Education (1 = strongly disagree; 7 = strongly agree). Previous
research has supported the reliability (i.e., α between .85 and .91 for each dimension) and fac-
tor structure of the AI-PE subscales using confirmatory factor analysis (CFA) obtaining the
following fit index: NNFI = .99; CFI=.99, SRMR =.02, RMSEA =.03 (Shen et al. 2010a).
Physical self-concept. In order to measure physical self-concept, we used the three
items from the abbreviated form of the Physical Self-Description Questionnaire (Marsh, Mar-
tin, & Jackson, 2010) and adapted to the Spanish context by Tomás, Marsh, González-Romá,
Valls, and Nagengast (2014). An example of an item was "Physically, I am happy with my-
self" and the items were answered on a 6-point Likert scale, ranging from 1 (false) to 6 (true).
Previous work has demonstrated the reliability (α between .84 and .91) and validity (i.e., both
convergent and discriminant validity) of the subscale (Marsh et al., 2010).
Level of physical activity. The Physical Activity Questionnaire for Older Children
(PAQ-C; Crocker et al., 1997) adapted to the Spanish context by Manchola-González, Bagur-
Calafat and Girabent-Farrés (2017) was used to assess the activity level of participants. The
PAQ-C consists of 9 questions that evaluate different aspects of the physical activity per-
formed by the adolescent using a 5-point Likert scale. Specifically, only the last question of
the questionnaire was used to assess the level of physical activity performed during the 7 days
of the week. It measured 5 overall levels, from none to vigorous physical activity. Internal
consistency (α = 0.83; Crocker et al., 1997) and validity (i.e., convergent and construct validi-
ty proved by Kowalski, Crocker & Faulkner, 1997) have been previously demonstrated in
similarly aged samples.
Procedure
María Jesús Lirola & Christopher M. Spray
424 Electronic Journal of Research in Educational Psychology, 19(2), 416-436. ISSN:1696-2095. 2021. no. 54
The procedure for the AI-PE adaptation to Spanish was carried out using the reverse
translation strategy (Muñiz, Elosua, & Hambleton, 2013). Two independent groups formed by
two translators with previous experience in the translation of psychometric tools carried out,
respectively, the translation of the AI-PE from English to Spanish and again from Spanish to
English. Each group was composed of a native English and a native Spanish translator. The
accuracy and adequacy of the translation was judged qualitatively by consensus between the
two translators based on the translations made by each one individually. In order to guarantee
the proper comprehension of the items, the questionnaire was initially administered to an in-
dependent sample of children (n=9). Then, six Spanish primary schools located in the same
province of Almeria were consulted to request cooperation in the study. For this purpose, an
initial meeting was held with the directors of the respective schools, followed by a second
informative meeting with the parents/legal guardians, and informed consent was requested
from the families of the participating students. In the presence of the first author of this study,
the survey was conducted, who, in addition to informing about the anonymous and optional
participation in the study, was at the disposal of the respondents to resolve possible doubts
that may have arisen throughout the process of collecting data. Approximately 15 minutes
were required to fill out the survey. This research was approved by the pertinent Bioethics
Committee.
Datal analysis
First, the factor structure of the AI-PE was analysed by a confirmatory factor analysis
(CFA). Observing the absence of multivariate normality (Mardia Coefficient= 412.61; Critical
Ratio= 130.93), the CFA was performed using the matrix of covariances between items using
the maximum likelihood method (ML) and a 2000-sample bootstrapping technique. From an
empirical sampling distribution, the bootstrapping technique allows the estimation of the dif-
ferent parameters and their 95% corrected bias confidence interval (Yuan & Hayashi, 2003)
along with the adjusted p-value obtained from the test correction χ2 (Bollen & Stine, 1992).
Previous works suggest the validity of the ML estimation method used in conjunction with the
bootstrapping technique applied to ordinal variables when the response scale used contains at
least five categories (Byrne, 2010; Finney & Di Stefano, 2006).
A combination of fit indices was used to judge the model tested: χ2/df, CFI (Compara-
tive Fit Index), IFI (Incremental Fit Index), RMSEA (Root Mean Square Error of Approxima-
tion) plus its 90% confidence interval (CI), and SRMS (Standardized Root Mean Square Re-
Validation of the Amotivation Inventory in Physical Education: exercise level and physical self-concept
Electronic Journal of Research in Educational Psychology, 19 (2), 416-436. ISSN:1696-2095. 2021. no. 54 425
sidual). Owing to the fact that the statistic χ2 is very sensitive to sample size (Jöreskog &
Sörbom, 1993) the index χ2/df was used, and values below 5 were considered acceptable
(Bentler, 1989). The following cut-off values were adopted: SRMR ≤ 0.08; CFI-IFI ≥ 0.90,
and RMSEA ≤ 0.08 (Marsh et al., 2004; Byrne, 2010; Hair et al., 2014).
To check the reliability of the instrument, an internal consistency analysis was per-
formed in which Cronbach's alpha index (
) was calculated. Internal consistency values
≥.70 were considered adequate (Fleiss, 2011; Hair et al., 2018). Subsequently, a multi-group
analysis was carried out according to gender considering successive restricted models. It was
estimated that the null hypothesis of invariance should be rejected in the presence of decreas-
es > .010 CFI (Cheung & Rensvold, 2002) or increases > .015 RMSEA (Chen, 2007) between
successive restricted models. Finally, a linear regression analysis was performed in which the
dependent variables considered (i.e., level of physical activity and physical self-concept) were
estimated from the mean score of the four factors that compose the AI-PE. The analyses were
performed using the IBM SPSS and AMOS v.22 statistical packages
Results
Confirmatory factor analysis
The CFA tested the structure of the four-factor, 16-item model (Figure 1), revealing
excellent fit indexes: χ2 (98, N= 232) = 242.99, p < .001; χ2/df= 2.48; CFI = .97; IFI = .97;
RMSEA = .080 (CI 90% = .067, .093); SRMR = .040. In this model, correlations between fac-
tors ranged from .27 to .60 and standardized regression weights ranged from .77 to .97, all of
which were statistically significant (p< .001).
María Jesús Lirola & Christopher M. Spray
426 Electronic Journal of Research in Educational Psychology, 19(2), 416-436. ISSN:1696-2095. 2021. no. 54
Figure 1. Confirmatory factor analysis of the four-factor model of the AI-PE.
Note: The ellipses represent the factors and the rectangles represent the items. The residual variances are shown
in small circles. All correlations and regression weights shown were statistically significant (p< .01)
Invariance analysis by gender
Table 1 shows the adjustment indexes obtained for the structural model tested. Only
significant differences (CFI increments > .01) were found between Models 3 and 4 for the
Validation of the Amotivation Inventory in Physical Education: exercise level and physical self-concept
Electronic Journal of Research in Educational Psychology, 19 (2), 416-436. ISSN:1696-2095. 2021. no. 54 427
correlated four-factor structure and there were no increments > .015 RMSEA between the
different models. Therefore, configural, metric, and scalar invariance were accepted.
Table 1. Multigroup Gender Invariance Analysis
Four-factor model of primary order
Model
χ2
gl
χ2/df
χ2
df
CFI
CFI
IFI
RMSEA
(IC 90%)
RMSEA
SRMR
Unrestricted
477.80
196
2.44
-
-
.94
-
.94
.079
(.070-.088)
-
.052
Invariant
measurement
weights
510.18
208
2.45
32.38***
12
.94
.00
.94
.079
(.071-.088)
.000
.053
Invariant
structural
weights
598.11
218
2.74
120.31***
22
.92
-.02
.92
.087
(.087-.102)
.008
.099
Invariant
measurement
residuals
714.01
234
3.05
236.21***
38
.90
-.02
.90
.094
(.289-.303)
.015
.096
***p< .001
Reliability analysis
Adequate levels of internal consistency were shown by the AI-PE factors as reflected
in Table 2. Correlations between the different factors of AI-PE, physical self-concept and
physical activity level are shown, with all correlations being significant except for the rela-
tionship between task characteristics and physical self-concept. Correlations ranged from -.30
to .60. The correlation analysis displayed values <.80 in its absolute term, underpinning the
absence of multicollinearity among the variables inspected (Hair et al., 2018). This analysis
also showed positive correlations between the four factors of amotivation. By contrast, there
were negative correlations between the 4 amotivation factors and both physical activity level
and physical self-concept.
María Jesús Lirola & Christopher M. Spray
428 Electronic Journal of Research in Educational Psychology, 19(2), 416-436. ISSN:1696-2095. 2021. no. 54
Table 2. Descriptive Statistics, Internal Consistency and Correlational Analysis between
Study Variables
Factors
Range
M
SD
1
2
3
4
5
6
1.
Ability beliefs
1-7
1.32
0.70
2.95
9.38
.96
-
.51***
.24***
.38***
-.35***
-.23***
2.
Effort beliefs
1-7
1.28
0.64
3.28
12.72
.96
-
.37***
.47***
-.29***
-.28***
3.
Characteristics of
the task
1-7
1.42
0.75
2.20
4.87
.94
-
.60***
-.08
-.16*
4.
Task value
1-7
1.21
0.57
3.46
12.66
.97
-
-.15*
-.30***
5.
Physical self-
concept
1-6
5.27
1.11
-2.11
4.52
.94
-
.31***
6.
Physical activity
1-5
3.53
0.81
-0.36
-0.23
.77
-
Note.= Skewness; = Kurtosis; = Cronbach´s alpha
*p< .05; **p< .01; *** p<.001
Evidence of criterion validity
Table 3 shows that of the four factors that compose amotivation, two of them
predicted in a statistically significant and negative way the physical self-concept (i.e., the
ability and effort beliefs) and two others did it also in the same sense for the physical activity
performance (i.e., the effort belief and the task value).
Table 3. Regression Analysis Predicting Physical Self-Concept and Physical Activity Level
Physical self-concept
Physical activity
Independent variables
t
R2
t
R2
Ability beliefs
-.43***
-3.76
.13
-.09
-1.10
.11
Effort beliefs
-.30*
-2.21
-.20*
-1.99
Characteristics of the task
.06
.58
.06
.72
Task value
.01
.04
-.32**
-2.74
*p< .05; **p< .01; ***p< .001.
Discussion and conclusion
The aim of this investigation was to analyse the psychometric properties of AI-PE
(Shen et al. 2010a) in the Spanish context. The results obtained in this study show that the AI-
Validation of the Amotivation Inventory in Physical Education: exercise level and physical self-concept
Electronic Journal of Research in Educational Psychology, 19 (2), 416-436. ISSN:1696-2095. 2021. no. 54 429
PE is a tool with adequate realiability and validity to evaluate amotivation in Physical Educa-
tion lessons in Spain in line with SDT (Deci & Ryan, 2000).
Confirmatory factor analysis supported the four-factor structure (i.e., ability beliefs,
effort beliefs, characteristics of the task, and task value) proposed by Shen et al. (2010a). The
resulting model was composed of four items per factor. In addition, internal consistency anal-
yses suggest that the Spanish version of the AI-PE is a reliable measure for evaluating this
construct. The multi-group analyses performed supported the existence of configurural, sca-
lar, and metric invariance, representing for some authors a minimum requirement that would
allow assuming that the instrument is invariant and, thus, comparing the means obtained in its
different latent factors (Milfont & Fischer, 2010; Strasheim, 2011).
The results of the regression analyses showed evidence of criterion validity of the AI-
PE by showing it to be in line with the theoretical postulates of SDT (Deci & Ryan, 2012).
From SDT, it is postulated that amotivation promotes negative results in terms of adherence
to physical activity behaviour. This postulate has received empirical support in different in-
vestigations; individuals who present amotivation cannot discern a connection from what they
do and the results derived from them (Pelletier, Fortier, Vallerand, & Briere, 2001). In this
sense, they will feel detached from their actions, without control over the situation and, thus,
the result will be the poor investment of interest, effort or energy to perform such behaviour.
In this sense, amotivation has been connected with both boredom and improper focus at
school (Vallerand et al., 1993), inadequate psycho-social adjustment, a high degree of per-
ceived stress in school (Baker, 2004) and early school dropout (Pelletier et al., 2001). On the
other hand, different investigations have discovered that manifest a positive physical self-
concept may lead to a better and higher level of exercise practice behaviour (Crocker, Sabis-
ton, Kowalski, McDonough & Kowalski, 2006). Following Fernandez-Lasarte, Goñi, Camino
and Zubeldia (2019) whose study, conducted with 1468 high school students, established a
positive link between presenting a good academic self-concept and the academic performance
finally obtained. Therefore, it seems that the fact of presenting high levels of self-concept in
different fields or areas of life, leads the person to realize themselves more deeply within that
field or subject. On the other hand, following the results obtained in the longitudinal study by
Taylor et al. (2014), it can be known that when there is a decrease in physical self-concept,
physical activity levels also decline. It is therefore known that there is a relationship between
the student's perception of themselves and how it determines the quality of motivation mani-
María Jesús Lirola & Christopher M. Spray
430 Electronic Journal of Research in Educational Psychology, 19(2), 416-436. ISSN:1696-2095. 2021. no. 54
fested in the context of physical education. Hence, a negative theoretical relationship was es-
tablished between the constructs of amotivation and a positive physical self-concept.
Although, in general, the results of this study provide psychometric support to the
Spanish version of the AI-PE, some limitations should be taken into account. First, this in-
strument allows the measurement of four factors (i.e., ability beliefs, effort beliefs, character-
istics of the task and task value), according to the conceptualization established by Shen et al.
(2010b). Nevertheless, this multidimensional view of amotivation is currently being studied
and new dimensions may emerge for its more accurate measurement. Along these lines, sev-
eral authors propose the study of amotivation as a multifaceted and multidimensional con-
struct, thus suggesting a broader framework that promotes a better understanding of the con-
struct of amotivation with the purpose of improving strategies that encourage greater adher-
ence to the exercise in students (Legault, Green-Demers & Pelletier, 2006; Shen, McCaughtry
& Martin, 2008). In this way, a better and deeper understanding of this variable could result
from approaching amotivation as a multi-faceted construct, and therefore favour the under-
standing of the variables that need to be addressed by education professionals in order to
avoid amotivation in their classes and improve student participation.
Future studies should evaluate the psychometric properties of the Spanish version of
the AI-PE in more age-diverse populations (e.g., first grades of Primary Education). Finally,
although the validity of the construct of amotivation was shown in its levels of prediction of
physical activity and physical self-concept, these are preliminary results of a first Spanish
version of the AI-PE, and it must be taken into account that the development of a scale is a
continuous process. Prospective research could increase the value of this construct by analyz-
ing the effect of prediction on other specific consequences or those derived from lack of mo-
tivation (e.g., frustration of basic psychological needs, level of school absenteeism, satisfac-
tion with exercise, oppositional defiant behaviour).
In summary, the AI-PE has proven to be a reliable and valid measuring instrument to
evaluate the amotivation in Physical Education lessons in Spanish language. It is possible to
measure the reasons or motives for feeling amotivation when doing Physical Education in
Primary Education lessons along the lines of the definition set out by Shen et al. (2010a,
2010b) by using this questionnaire. Therefore, this instrument can be interesting insofar as it
distinguishes different variables that influence amotivation, thus being a multidimensional
Validation of the Amotivation Inventory in Physical Education: exercise level and physical self-concept
Electronic Journal of Research in Educational Psychology, 19 (2), 416-436. ISSN:1696-2095. 2021. no. 54 431
instrument that allows the establishment of links with different possible motives and a better
understanding of the nature of the amotivation. This tool can be of interest to experts in the
teaching of Physical Education in different centres or educational institutions.
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Received: 04-06-2020
Accepted: 29-03-2021
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Appendix
Adapted version to Spanish context of the Amotivation Inventory-Physical Education
1. Porque para mí, E.F. no es interesante
2. Porque no soy bueno/a en E.F.
3. Porque no soy lo suficientemente enérgico para E.F.
4. Porque participar en E.F. no es importante para mí.
5. Porque participar en E.F. no es valioso para mí
6. Porque no tengo lo que se necesita para hacer bien E.F.
7. Porque soy un poco perezoso/a
8. Porque no me gusta el deporte/actividad física que se juega en E.F.
9. Porque no tengo ninguna buena razón para participar en E.F.
10. Porque el deporte/actividad que se juega es aburrido
11. Porque no me gusta tener que hacer esfuerzo para hacer E.F.
12. Porque tengo la impresión que cada día en E.F. se hace lo mismo
13. Porque no tengo el conocimiento/habilidad requerida para tener éxito en E.F.
14. Porque no tengo energía para participar en E.F.
15. Porque las actividades en E.F. no son estimulantes
16. Porque los ejercicios que me exigen en E.F. superan mi capacidad
Items composing the dimensions of the Inventory according to the structure of Shen et al.,
(2010): Ability beliefs: 2, 6, 13, 16; Effort belief: 3, 7, 11, 14; Value of task: 1, 4, 5, 9; Task
characteristics: 8, 10, 12, 15.
