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Capturing the Multidimensionality of Motivation in Physical Education: A Self-Organizing Maps Approach to Profiling Students

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Title: Capturing the Multidimensionality of Motivation in Physical Education: A Self-Organizing Maps Approach to Profiling Students
Language: English
Authors: Peiró-Velert, Carmen (ORCID 0000-0003-4794-6541), García-Massó, Xavier, Pérez-Gimeno, Esther, Lizandra, Jorge, Valencia-Peris, Alexandra (ORCID 0000-0002-2031-9743), Devís-Devís, José
Source: European Physical Education Review. Nov 2022 28(4):852-872.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 21
Publication Date: 2022
Document Type: Journal Articles
Reports - Research
Education Level: Secondary Education
Descriptors: Adolescents, Student Motivation, Physical Education, Student Needs, Self Determination, Affective Behavior, Student Behavior, Student Participation, Self Efficacy, Personal Autonomy, Student Satisfaction, Gender Differences, Physical Activity Level, Competence, Relevance (Education), Foreign Countries, Secondary School Students
Geographic Terms: Spain
DOI: 10.1177/1356336X221088396
ISSN: 1356-336X
1741-2749
Abstract: This study aimed to capture the multidimensionality of adolescents' motivation in the physical education (PE) setting, within self-determination theory, by employing self-organizing maps (SOM) analysis. Particularly, it examined the topological relationships among students' basic psychological needs satisfaction, their perception of more or less self-determined motivation and the affective and behavioural consequences in PE lessons across several sociodemographic variables. A nationally representative sample of 3029 Spanish students (51% girls), aged 12 to 18 years, was surveyed. SOM mapped well-defined students' profiles that embraced interrelatedly a considerable number of students' motivational characteristics. Four target profiles, out of 10, were explored. The first two profiles, highly motivated to be active girls and boys, mainly experienced senses of self-determination, but also controlled reasons for participating in PE lessons, high perceived competence, relatedness and autonomy fulfilment, perceived exerted effort and satisfaction. However, the reluctance to be physically active presented two gendered motivational profiles. Barely motivated to be active girls showed the lowest levels of self-determined motivation, including introjected regulation, low perceptions of competence, autonomy, relatedness, and dissatisfaction in PE. Vaguely motivated to be active boys revealed that despite their perceptions of competence the neglect of the other two psychological needs was more likely to determine a controlled motivation and, consequently, maladaptive outcomes. SOM proved to be a more robust and accurate clustering technique than the k-means algorithm and helped to portray and visualize the complexity behind the decision to become an active person considering the motivational processes in PE. Implications are provided for practitioners.
Abstractor: As Provided
Entry Date: 2022
Accession Number: EJ1350616
Database: ERIC
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  Value: <anid>AN0159219635;53x01nov.22;2022Sep22.06:10;v2.2.500</anid> <title id="AN0159219635-1">Capturing the multidimensionality of motivation in physical education: A self-organizing maps approach to profiling students </title> <p>This study aimed to capture the multidimensionality of adolescents' motivation in the physical education (PE) setting, within self-determination theory, by employing self-organizing maps (SOM) analysis. Particularly, it examined the topological relationships among students' basic psychological needs satisfaction, their perception of more or less self-determined motivation and the affective and behavioural consequences in PE lessons across several sociodemographic variables. A nationally representative sample of 3029 Spanish students (51% girls), aged 12 to 18 years, was surveyed. SOM mapped well-defined students' profiles that embraced interrelatedly a considerable number of students' motivational characteristics. Four target profiles, out of 10, were explored. The first two profiles, highly motivated to be active girls and boys, mainly experienced senses of self-determination, but also controlled reasons for participating in PE lessons, high perceived competence, relatedness and autonomy fulfilment, perceived exerted effort and satisfaction. However, the reluctance to be physically active presented two gendered motivational profiles. Barely motivated to be active girls showed the lowest levels of self-determined motivation, including introjected regulation, low perceptions of competence, autonomy, relatedness, and dissatisfaction in PE. Vaguely motivated to be active boys revealed that despite their perceptions of competence the neglect of the other two psychological needs was more likely to determine a controlled motivation and, consequently, maladaptive outcomes. SOM proved to be a more robust and accurate clustering technique than the k-means algorithm and helped to portray and visualize the complexity behind the decision to become an active person considering the motivational processes in PE. Implications are provided for practitioners.</p> <p>Keywords: Neural networks; physical activity; basic psychological needs; motivation; intention of practice</p> <hd id="AN0159219635-2">Introduction</hd> <p>It is generally recognized that school physical education (PE) plays an important role in promoting physically active lifestyles ([<reflink idref="bib40" id="ref1">40</reflink>]). It has the potential to have a significant impact on public health since it reaches a broad range of age cohorts, from infants to adolescents ([<reflink idref="bib17" id="ref2">17</reflink>]). In particular, PE is facing the challenge of providing students with the knowledge and resources for lifelong physical activity (PA; [<reflink idref="bib19" id="ref3">19</reflink>]).</p> <p>However, engagement in PA and the intention to be physically active often decline as children transition into adolescence ([<reflink idref="bib5" id="ref4">5</reflink>]; [<reflink idref="bib29" id="ref5">29</reflink>]). The type of motivation that results from the influence of social and situational factors is a pivotal issue in understanding PE experiences and its relationship with adolescents' intention to participate in PA. For instance, if meaningful movement experiences, feelings of competence and students' self-regulation of their actions are enabled, and/or if they can build appropriate interpersonal interactions with PE teachers and peers, this may enhance their motivation to actively partake in extracurricular PA ([<reflink idref="bib8" id="ref6">8</reflink>]). Conversely, negative and thwarting experiences in PE will lead to unsuccessful participation in leisure-time PA as, for example, a lack of engagement in leisure-time PA ([<reflink idref="bib3" id="ref7">3</reflink>]). Understanding the role of motivation in PE can help teachers to better evaluate students' behaviours and incline them towards curricular and pedagogical strategies to facilitate positive and meaningful experiences, improving the quality of students' learning and their curricular and extracurricular participation ([<reflink idref="bib6" id="ref8">6</reflink>]).</p> <p>Self-determination theory (SDT) is a particularly suitable theoretical approach for understanding the onset of individual behaviour and perseverance in it ([<reflink idref="bib7" id="ref9">7</reflink>]; [<reflink idref="bib34" id="ref10">34</reflink>]) and has been applied to different contexts, including PE. According to SDT, students' motivation towards PE is multidimensional since they may endorse multiple reasons for participating ([<reflink idref="bib39" id="ref11">39</reflink>]; [<reflink idref="bib41" id="ref12">41</reflink>]). Empirical research on SDT has tried to capture this multidimensionality by employing variable-centred or person-centred approaches, the latter being increasingly used in PE research ([<reflink idref="bib1" id="ref13">1</reflink>]; [<reflink idref="bib13" id="ref14">13</reflink>]; [<reflink idref="bib18" id="ref15">18</reflink>]; [<reflink idref="bib39" id="ref16">39</reflink>]).</p> <p>These person-centred studies have analysed how different motivational dimensions are combined and group students into diverse motivational profiles by conducting both hierarchical and non-hierarchical cluster analyses. To date, several clusters have emerged and independent associations of each motivational profile with theoretical social antecedents and consequences have been examined. However, as some authors have claimed, further research is necessary to capture a wider range of students' potential motivational profiles coexisting in PE, and the implementation of an appropriate methodology is required that provides complex information on the clustering of students' motivation ([<reflink idref="bib13" id="ref17">13</reflink>]; [<reflink idref="bib37" id="ref18">37</reflink>]). In this regard, self-organizing maps (SOM) analysis can help to bring out the nuances in motivational behaviour patterns overlooked by conventional cluster analyses and provide the possibility of establishing complex relationships among a greater number of variables for large samples. SOM analysis allows researchers to visualize a wider non-linear landscape and may offer alternative explanations on how the different constructs of students' motivation in PE combine to give multidimensional profiles. This contributes to understanding students' experiences in PE and their implications for the PE curriculum to facilitate positive experiences leading to students' regular participation in PA and improved well-being.</p> <hd id="AN0159219635-3">SDT in PE</hd> <p>[<reflink idref="bib7" id="ref19">7</reflink>] SDT posits that motivation is not a unique concept, but different types of motivation can be identified and represented in a continuum (a self-determination continuum) that reflects the extent to which a person has internalized a behaviour. Intrinsic motivation is the most autonomous, self-determined or internalized motivation while four types of extrinsic motivation show a significant variation in their level of autonomy. Integrated and identified regulations are regarded as autonomous or self-determined, while introjected and external regulations are more controlled or externally regulated types of motivation. At the opposite end of the continuum, amotivation reflects an absence of intention to act or engage in an activity. When applied to the PE context, students show autonomous motivation when they participate in an activity for its own sake, or they find it enjoyable and exciting (intrinsic motivation) or when they perceive the activity to be highly valued and personally relevant (identified regulation) as, for instance, engaging in PA for health purposes. Conversely, if students perceive their behaviour to be performed for external reasons to avoid punishment or receive an award (external regulation) or they act to avoid guilt, to please the teacher or gain pride (introjected regulation), they are expressing what is referred to as controlled motivation ([<reflink idref="bib42" id="ref20">42</reflink>]; [<reflink idref="bib43" id="ref21">43</reflink>]).</p> <p>According to SDT, students' perceptions of three basic psychological needs (BPN) are the theoretically relevant antecedents of these motivational regulations: competence, autonomy and relatedness ([<reflink idref="bib7" id="ref22">7</reflink>]). With regard to educational settings, students that experience feelings of confidence and ability to complete a task effectively (competence), a sense of control of their own actions and perceived choice (autonomy) and feelings of being connected with, integrated into and cared for by the peer group (relatedness) will more likely experience autonomous forms of motivation. An essential focus when analysing these settings is on the extent to which these innate basic needs are satisfied or frustrated ([<reflink idref="bib34" id="ref23">34</reflink>]). Previous research in PE suggests that teachers who facilitate and support students' needs satisfaction will generate a more self-determined type of motivation, while those who thwart these needs will more likely cause controlled forms of motivation and amotivation ([<reflink idref="bib12" id="ref24">12</reflink>]).</p> <p>In the PE domain, the literature on the SDT approach and the transcontextual model ([<reflink idref="bib14" id="ref25">14</reflink>]) also suggests that lifelong participation can be promoted through emphasizing intrinsically regulated forms of motivation in school PE ([<reflink idref="bib19" id="ref26">19</reflink>]). This type of autonomous motivation (i.e. intrinsic motivation and identified regulation) will positively relate to affective, cognitive and behavioural consequences (e.g. satisfaction, values and effort) and will more likely predict, among other processes, students' intentions to be physically active during their leisure time ([<reflink idref="bib22" id="ref27">22</reflink>]). By displaying important levels of internally regulated forms of motivation in PE lessons, students will be more likely to behave for reasons inherent to themselves and beyond the influence of the context ([<reflink idref="bib23" id="ref28">23</reflink>]). However, controlled forms of extrinsic motivation (i.e. introjected regulation and external regulation) and amotivation may be negative for involving young people in PA ([<reflink idref="bib1" id="ref29">1</reflink>]; [<reflink idref="bib24" id="ref30">24</reflink>]).</p> <p>These types of motivation are generally associated with negative cognitive, affective and behavioural processes, such as perceiving lessons as boring and a waste of time, feeling pressure to participate, or perceiving their physical competence being questioned publicly, as well as negative behavioural intentions ([<reflink idref="bib12" id="ref31">12</reflink>]).</p> <p>Together, the research suggests that when students are intrinsically motivated in PE and perceive that the PE context supports, and does not thwart their BPN, they are more likely to show an adaptive and positive attitude and behaviour as, for instance, participation in PA outside the school ([<reflink idref="bib45" id="ref32">45</reflink>]) and perceived effort in PE ([<reflink idref="bib31" id="ref33">31</reflink>]; [<reflink idref="bib39" id="ref34">39</reflink>]). An effort also becomes a critical motivational outcome in learning environments such as PE and it is strongly predicted by autonomous forms of motivation and the satisfaction of psychological needs ([<reflink idref="bib38" id="ref35">38</reflink>]). Students who enjoy and feel satisfied in PE lessons are more likely to consider it worthwhile to make an effort to learn the curricular content and consequently find that their motor competence improves, thus enhancing their perception of feeling competent and motivated to keep involved in the lessons ([<reflink idref="bib24" id="ref36">24</reflink>]).</p> <p>Gender differences have also emerged when studying motivation in PE and which BPN best predicts the diverse types of motivation in PE. Research indicates that female students have less optimal motivational profiles reporting less perceived autonomy and competence needs satisfaction than males, as well as the importance of keeping a needs satisfaction balance for optimal motivation ([<reflink idref="bib13" id="ref37">13</reflink>]; [<reflink idref="bib30" id="ref38">30</reflink>]). However, other studies have shown no associations between students' gender and more or less desirable motivational profiles ([<reflink idref="bib32" id="ref39">32</reflink>]; [<reflink idref="bib45" id="ref40">45</reflink>]). Some studies suggest that these contradictory findings, and particularly differences in the gendered perception of BPN satisfaction and types of motivation, may derive from the teaching methodology employed in PE lessons or even the content area developed in the classroom ([<reflink idref="bib27" id="ref41">27</reflink>]).</p> <hd id="AN0159219635-4">PE students' profiling: The SOM analysis contribution</hd> <p>Several studies concur that students' negative experiences in PE, or feelings that PE is not meaningful to them, are related to lower PA participation or a lack of intention to be active after schooling ([<reflink idref="bib3" id="ref42">3</reflink>]). The ability of physical educators to engage students, particularly those who dislike PE, and make them feel enthusiastic when participating in school lessons (e.g. encouraging positive learning behaviours and fostering an internal locus of causality) are challenging tasks to deal with ([<reflink idref="bib23" id="ref43">23</reflink>]). It is therefore important for teachers and researchers to better understand adolescents' motivational, cognitive and affective processes in PE in order to build strategies to improve PE teaching and establish foundations for adolescents' positive attitudes and lifelong healthy lifestyles.</p> <p>Most studies examining associations between types of motivation, BPN and behavioural, affective or cognitive consequences have traditionally employed a variable-centred approach (i.e. to determine relationships between variables). Nevertheless, the newly developed statistical methods of classifying participants according to their characteristics have led to the emergence of the person-centred approach. This approach is recommended to provide a better understanding of how different types of motivation can coexist in the same person and may be combined in various motivational profiles. Several studies have established PE motivational profiles by using conventional clustering methods such as k-means and hierarchical algorithms ([<reflink idref="bib13" id="ref44">13</reflink>]; [<reflink idref="bib32" id="ref45">32</reflink>]; [<reflink idref="bib45" id="ref46">45</reflink>]). Three motivational profiles were found in Ntoumanis' ([<reflink idref="bib32" id="ref47">32</reflink>]) study on 428 British secondary school students (labelled <emph>self-determined, moderate motivation</emph> and <emph>controlling motivation/amotivation</emph>). The findings showed positive associations of self-determined motivation with desirable behavioural and affective outcomes in PE. In the higher education setting, [<reflink idref="bib13" id="ref48">13</reflink>]) cluster analysis resulted in five profiles (<emph>pronounced amotivated, combined amotivated controlled, lowly motivated, combined autonomous controlled</emph> and <emph>relatively autonomously motivated</emph>). Differences in students' self-reported concurrent and delayed transfer of what they have learnt in PE according to motivational profiles and PA levels were analysed. Those with more autonomous motivational profiles showed more transfer and were more active at secondary school and in early adulthood. Furthermore, three motivational profiles (labelled <emph>negative perceivers</emph>, <emph>moderate perceivers</emph> and <emph>positive perceivers)</emph> emerged in the study by [<reflink idref="bib45" id="ref49">45</reflink>] with Dutch secondary school students, who differed regarding the perceived motivational climate, psychological need satisfaction and frustration, but not in terms of gender and age.</p> <p>However, no studies have so far explored SOM as a clustering method to obtain evidence on the motivational characteristics of adolescent students in PE classes. SOM provides some advantages regarding cluster or principal component analyses ([<reflink idref="bib2" id="ref50">2</reflink>]): (<reflink idref="bib1" id="ref51">1</reflink>) more reliable and accurate clustering, (<reflink idref="bib2" id="ref52">2</reflink>) visualization options (easy to interpret and visualize relationships between variables), and (<reflink idref="bib3" id="ref53">3</reflink>) it takes into account non-linear relationships in the data, which facilitates testing conditional relationships. Some disadvantages, however, should be mentioned: (<reflink idref="bib1" id="ref54">1</reflink>) a high computational cost and (<reflink idref="bib2" id="ref55">2</reflink>) often high complexity of the models. Overall, there is some evidence of the higher accuracy of SOM classification regarding the k-means algorithm ([<reflink idref="bib2" id="ref56">2</reflink>]; [<reflink idref="bib26" id="ref57">26</reflink>]), which can be considered as one of the most important strengths of SOM compared to traditional clustering techniques.</p> <p>Therefore, the purpose of the present study was to capture the multidimensionality of motivation in PE by employing SOM analysis to obtain a wider overview and understanding of adolescents' motivation in PE lessons. In doing so, we stress the coherence between the purpose and the method used in this study: the choice of the second, the innovative way of clustering participants, helps to achieve the first, capturing multidimensionality. In fact, the true contribution of this study rests on this coherent relationship. More specifically, the study examines the topological relationships in the satisfaction of students' BPN (competence, autonomy and relatedness), their perception of more or less self-determined motivation (intrinsic, identified, introjected or external regulation) and amotivation, their satisfaction and boredom in PE lessons, their perception of effort and intention of practising PA in their leisure-time, together with other demographic variables (i.e. gender, age and weight status).</p> <hd id="AN0159219635-5">Materials and methods</hd> <p></p> <hd id="AN0159219635-6">Participants</hd> <p>The participants were 3029 Spanish adolescents (females <emph>n</emph> = 1556, and males <emph>n</emph> = 1473), aged 12 to 18 years (M<subs>age</subs> = 14.56, SD = 1.81) recruited from seven state and eight private schools. The sample was selected by following a proportional stratified sample procedure from a population of students enrolled in the Spanish secondary education system, according to the type of school (state and private) and geographical area (the country was divided into six areas) (see Table 1) as previously performed in other studies ([<reflink idref="bib33" id="ref58">33</reflink>]). Postcodes from each area and schools from each code were randomly selected and adolescents were chosen according to proportional quotas by gender and year.</p> <p>Graph</p> <p>Table 1. Frequencies and percentages for the demographic variables of the study sample (n = 3029).</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="center" /></colgroup><thead><tr><th align="left" /><th align="center"><italic>n</italic> (%)</th></tr></thead><tbody><tr><td colspan="2">Gender</td></tr><tr><td> Girls</td><td>1556 (51.4)</td></tr><tr><td> Boys</td><td>1473 (48.6)</td></tr><tr><td colspan="2">Age</td></tr><tr><td> 11–13 years old</td><td>1002 (33.2)</td></tr><tr><td> 14–16 years old</td><td>1484 (49.2)</td></tr><tr><td> 17–19 years old</td><td>527 (17.6)</td></tr><tr><td colspan="2">Type of school</td></tr><tr><td> State</td><td>1974 (65.2)</td></tr><tr><td> Private</td><td>1055 (34.8)</td></tr><tr><td colspan="2">Weight status</td></tr><tr><td> Underweight</td><td>195 (6.5)</td></tr><tr><td> Normal weight</td><td>1825 (61.2)</td></tr><tr><td> Overweight</td><td>695 (23.3)</td></tr><tr><td> Obese</td><td>269 (9.0)</td></tr></tbody></table> </ephtml> </p> <p>The study was approved by the Ethics Committee of the Universitat de València (Spain). Materials and procedures were also approved by the individual schools and the school districts. Parents and participants over 18 years of age signed a written informed consent.</p> <hd id="AN0159219635-7">Measures</hd> <p>A set of standardized self-reported questionnaires was employed to collect demographic data on gender and age, and data from the following study variables.</p> <hd id="AN0159219635-8">Anthropometric factor</hd> <p>Body mass index (BMI) was calculated and recorded as weight (kg)/height (m<sups>2</sups>), using a Stadiometer (MOD.1-S-B,6615) and a digital balance (Body Balance Comfort-F5, Soehnle).</p> <hd id="AN0159219635-9">Psychological need satisfaction and perceived effort</hd> <p>Six items from the perceived competence and five items from the perceived effort subscales of the intrinsic motivation inventory ([<reflink idref="bib25" id="ref59">25</reflink>]) were employed to measure adolescents' perceived competence and effort in the PE classes, respectively. To measure autonomy and relatedness need satisfaction, four items (two each) from [<reflink idref="bib31" id="ref60">31</reflink>] were added. Items were reworded to be PE-specific (e.g. 'I think I am pretty good in the PE class' (competence), 'I put forth a lot of effort in the PE subject' (effort), 'I can decide what activities I want to practice in most of the PE classes' (autonomy) and 'Participating in the PE classes makes me feel closer to my schoolmates' (relatedness)). Answers to the four dimensions were provided on a 1 (<emph>strongly disagree</emph>) to 5 (<emph>strongly agree</emph>) scale. The psychometric properties of the scale with the data of the study were obtained using CFA (χ<sups>2</sups> = 1561; df = 84; <emph>p</emph> < 0.001; χ<sups>2</sups>/df = 18.6; CFI = 0.9; TLI = 0.88; SRMR = 0.06; RMSEA = 0.07 (confidence interval (CI): 0.073–0.079)). The internal consistency (ω) was 0.82 for competence, 0.81 for effort, 0.58 for autonomy and 0.76 for relatedness.</p> <hd id="AN0159219635-10">Motivational regulations</hd> <p>The perceived locus of causality (PLOC) scale was employed to determine the level of students' perceptions of contextual self-determined motivation in PE classes. This scale was originally created by [<reflink idref="bib11" id="ref61">11</reflink>] to measure intrinsic motivation and different types of extrinsic motivation (identified, introjected and external regulation), as well as amotivation in adolescent students in the PE domain. The scale was headed by the stem 'I participate in the PE class..." and consisted of 20 items. Example items for the five factors were: intrinsic motivation (e.g. 'because it's fun'), identified regulation (e.g. 'because I want to learn sport skills'), introjected regulation (e.g. 'because I want the PE teacher to think I'm a good student'), external regulation (e.g. 'because that's what I am supposed to do') and amotivation (e.g. 'but I really feel I'm wasting my time in PE'). Students responded on a Likert-type scale ranging from 1 (<emph>nothing to do with me</emph>) to 7 (<emph>it strongly suits me</emph>). The internal consistency (ω) was 0.83 for intrinsic motivation, 0.83 for identified regulation, 0.65 for introjected regulation, 0.69 for external regulation and 0.77 for amotivation. The data from this study revealed adequate psychometric properties of the PLOC in PE using CFA (χ<sups>2</sups> = 2383; df = 160; <emph>p</emph> < 0.001; χ<sups>2</sups>/df = 14.9; CFI = 0.91; TLI = 0.89; SRMR = 0.05; RMSEA = 0.07 (CI: 0.065–0.07)).</p> <hd id="AN0159219635-11">Satisfaction in PE</hd> <p>The satisfaction in PE scale ([<reflink idref="bib9" id="ref62">9</reflink>]) was employed. This scale consists of eight items divided into two factors: five items measuring satisfaction in PE (e.g. 'I usually have fun in PE') and three items measuring boredom in PE (e.g. 'I usually become bored in the PE class'). Students responded to the stem 'How do you find PE classes?' on scales ranging from 1 (<emph>strongly disagree</emph>) to 5 (<emph>strongly agree</emph>). The psychometric properties of satisfaction in PE with the data of the present study were obtained using CFA (χ<sups>2</sups> = 316; df = 19; <emph>p</emph> < 0.001; χ<sups>2</sups>/df = 16.6; CFI = 0.97; TLI = 0.95; SRMR = 0.03; RMSEA = 0.07 (CI: 0.065–0.079)). The internal consistency (ω) was 0.85 and 0.65 for satisfaction and boredom, respectively.</p> <hd id="AN0159219635-12">Future intention of being involved in PA</hd> <p>Students responded to the following item: 'I intend to keep engaged in physical activity even when I have finished my Secondary School/Sixth Form', on a Likert-type scale ranging from 1 (<emph>no intention</emph>) to 5 (<emph>yes, I intend to</emph>).</p> <hd id="AN0159219635-13">Data analysis and procedure</hd> <p>Matlab R2008a program (MathWorks Inc., Natick, MA, USA) was used to perform the data analysis. SOM analysis, which employs competitive (each neuron competes for each case accordingly with their similitudes), non-supervised (there are no predefined groups) artificial neural networks, was used for the study using the SOM toolbox (version 2.0 beta) for Matlab. A brief introduction to SOM is provided subsequently and readers who want to expand the information provided can consult [<reflink idref="bib4" id="ref63">4</reflink>], [<reflink idref="bib16" id="ref64">16</reflink>], [<reflink idref="bib20" id="ref65">20</reflink>] and [<reflink idref="bib35" id="ref66">35</reflink>].</p> <p>The main overall advantages of this analysis are ([<reflink idref="bib4" id="ref67">4</reflink>]; [<reflink idref="bib16" id="ref68">16</reflink>]; [<reflink idref="bib36" id="ref69">36</reflink>]): (<reflink idref="bib1" id="ref70">1</reflink>) SOM neurons or nodes are ordered into two-dimensional maps according to the distance between neurons in their weight vectors (i.e. values of input variables for the neuron), (<reflink idref="bib2" id="ref71">2</reflink>) the weight vector of a neuron is representative of the participants' characteristics clustered in such a neuron, (<reflink idref="bib3" id="ref72">3</reflink>) it establishes relationships among a large number of variables plotted on maps to improve the visualization and interpretation of the results, (<reflink idref="bib4" id="ref73">4</reflink>) it is an unsupervised algorithm useful for non-linear models (during the process, non-linear functions are applied, for example, neighbourhood function), as the relationships between the parameters in biological systems are usually non-linear ([<reflink idref="bib28" id="ref74">28</reflink>]), and (<reflink idref="bib5" id="ref75">5</reflink>) the analysis did not decline in power as more input variables or factors were added. The last is a typical feature of inferential analysis and SOM, as an exploratory analysis tool, is free of statistical power issues. It should be noted that some of these advantages are also present in other clustering techniques.</p> <p>SOM analysis can be divided into three steps. First, a neural network is created in which the lattice size (i.e. 21 × 13 neurons in our study) depends on the sample size. The greater the sample size the greater the lattice size ([<reflink idref="bib16" id="ref76">16</reflink>]). The neural network is a set of neurons or nodes ordered into the form of a net. Each neuron or node is a vector with a value for each input variable (i.e. weight vector). Each neuron is thus a vector with 15 values in our study, one for each input variable (i.e. age, gender, BMI, competence, autonomy, relatedness, intrinsic motivation, identified regulation, introjected regulation, external regulation, amotivation, effort, satisfaction, boredom and intention). A hexagonal neuron shape was used, which means that each neuron has six neighbours, one on each side of the hexagon.</p> <p>Secondly, as the neurons start with empty weight vectors (no values for each input variable), a procedure is required to assign initial values to them. This procedure is called <emph>network initialization</emph>. During initialization, a preliminary weight vector with a value for each input variable is given to each neuron. We employed two methods to initialize the neurons: (<reflink idref="bib1" id="ref77">1</reflink>) random and (<reflink idref="bib2" id="ref78">2</reflink>) linear ([<reflink idref="bib21" id="ref79">21</reflink>]). In the first method, small random values were assigned to each neuron's weight vector. In the linear initialization, weight vectors were initialized in an orderly fashion along the linear subspace spanned by the two principal eigenvectors of the input data set.</p> <p>The values of the neurons' weight vectors are then adapted to the experimental data (third step). To do this, the network is <emph>trained</emph> using the following equation ([<reflink idref="bib4" id="ref80">4</reflink>]): <ephtml> <math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>ω</mi><mi>j</mi></msub><mo stretchy="false">(</mo><mi>n</mi><mo>+</mo><mn>1</mn><mo stretchy="false">)</mo><mo>=</mo><msub><mi>ω</mi><mi>j</mi></msub><mo stretchy="false">(</mo><mi>n</mi><mo stretchy="false">)</mo><mo>+</mo><mi>η</mi><mo stretchy="false">(</mo><mi>n</mi><mo stretchy="false">)</mo><msub><mi>h</mi><mrow><mspace width=".1em" /><mi>j</mi><mo>,</mo><mi>i</mi><mo stretchy="false">(</mo><mi>x</mi><mo stretchy="false">)</mo></mrow></msub><mo stretchy="false">(</mo><mi>n</mi><mo stretchy="false">)</mo><mo stretchy="false">(</mo><mi>x</mi><mo>−</mo><msub><mi>ω</mi><mi>j</mi></msub><mo stretchy="false">(</mo><mi>n</mi><mo stretchy="false">)</mo><mo stretchy="false">)</mo></math> </ephtml></p> <p>Graph</p> <p>where <emph>w<subs>j</subs></emph> is the weight vector of the <emph>j</emph>th neuron, <emph>η</emph> is the learning ratio, <emph>h<subs>j,i</subs></emph><subs>(<emph>x</emph>)</subs> is the neighbourhood function, <emph>x</emph> is the input vector (each case or subject in our study), <emph>n</emph> is the iteration and <emph>i</emph>(<emph>x</emph>) is the winning neuron of the <emph>x</emph> input vector ([<reflink idref="bib4" id="ref81">4</reflink>]). Overall, training is an iterative process in which neuron weights are modified in a non-linear model since the learning ratio and neighbourhood functions are not linear. The modification of the neuronal weights in each iteration depends on several factors (described in equation (<reflink idref="bib1" id="ref82">1</reflink>)). First of all, an input vector (i.e. a case or subject of the study) is presented to the network. The neurons in the lattice then 'compete' (i.e. compare the Euclidian distance of their weight vector and the case values) to win the input vectors. The winning neuron is the one that achieves the smallest Euclidean distance between its weight vector and the input vector, so that the weight vector of the winning neuron has the closest values to the input vector values. All the neurons in the lattice then adapt their weight values closest to the values of the input case. The magnitude of the adaptation depends on the learning ratio and the neighbour function. The learning ratio has a high value at the beginning of the training process and is gradually reduced as it goes on and the neighbour function maximizes the adaptation of the winning neuron. The rest of the neurons also adapt their weights according to this function; the further the neuron from the winner, the smaller the adaptation magnitude. This process is repeated until the training process ends ([<reflink idref="bib33" id="ref83">33</reflink>]).</p> <p>Due to random factors in SOM training and the different setting options of the training methods (i.e. batch or sequential), the initialization (i.e. linear and random) and the neighbourhood function (i.e. Gaussian, cut Gaussian, Epanechicov and Bubble) 1600 maps were obtained. The best SOM was selected using the minimum product of quantization (i.e. 0.54 in our study) and topographic errors (i.e. 0.02 in our study) as criteria. It should be noted that these parameters are considered as indicators of the internal consistency of SOM ([<reflink idref="bib10" id="ref84">10</reflink>]).</p> <p>Cases with similar characteristics were grouped by SOM in the same neurons (i.e. each neuron represents a cluster in itself). However, occasionally a cluster analysis is performed to establish larger groups of people. We used a k-means method to test the possibility of setting between two and 10 clusters. These clusters are shown in Figure 1 (colours of the <emph>Hits</emph> map) and the Davies–Bouldin index was the criterion used to evaluate the number of clusters (i.e. 0.79 in our study, see Supplemental Material for more detailed information). Finally, Spearman correlations (variables did not meet normality assumption) were requested to establish linear relationships between the neuronal weights for each variable instead of using the participants' values. The non-linear transformation performed by SOM is thus taken into account in the correlation values. The level of significance was set at <emph>p</emph> < 0.05.</p> <p>MAP: Figure 1. Component planes/maps, hits and target clusters. In the Hits map (at the bottom), empty cells show a lack of cases and cells with a denser colour indicate a large number of adolescents accumulated in them. Red numbers designate selected target zones/clusters with the lowest and highest values of intention to engage in future PA. Numbers in black (1–4, 8–9) refer to quantitatively analysed clusters with results presented in Table 3 and the Supplemental Material. The 15 variables included in the analysis appear from top to bottom rows and from left to right columns. Rectangles on the right of each component map indicate the lower (bluish) and higher (reddish) values of each variable. Weight status is represented in BMI z scores. To better understand the maps, it is important to note that participants included in every neuron (hexagon) are the same in all component planes. Moreover, the neurons close to each other are more similar than those which are far. Therefore, the x and y axis are related with the place of the neuron in a multidimensional space.</p> <p>Graph</p> <p>Table 3. Descriptive statistics of the neuronal weights of the different clusters.</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="left" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /></colgroup><thead><tr><th align="left" /><th align="center" colspan="11">Clusters</th></tr><tr><th align="left" /><th align="left" /><th align="center">1(<italic>n</italic> = 417 boys)</th><th align="center">2(<italic>n</italic> = 243 girls)</th><th align="center">3(<italic>n</italic> = 326 boys)</th><th align="center">4(<italic>n </italic>= 235 girls)</th><th align="center">5(<italic>n</italic> = 379 boys)</th><th align="center">6(<italic>n</italic> = 351 boys)</th><th align="center">7(<italic>n</italic> = 319 girls)</th><th align="center">8(<italic>n</italic> = 364 girls)</th><th align="center">9(<italic>n</italic> = 0)</th><th align="center">10(<italic>n</italic> = 395 girls)</th></tr></thead><tbody><tr><td rowspan="2">Participants' characteristics</td><td>Age</td><td>14.80(14.60–14.90)</td><td>14.20(14.10–14.40)</td><td>13.80(13.70–13.80)</td><td>14.20(14.21–14.28)</td><td>14.70(14.60–14.80)</td><td>14.80(14.70–14.90)</td><td>14.80(14.70–15.00)</td><td>15.09(14.90–15.20)</td><td>14.10(14.10–14.20)</td><td>14.07(13.90–14.20)</td></tr><tr><td>BMI</td><td>21.90(21.70–22.03)</td><td>21.48(21.40–21.50)</td><td>21.42(21.30–21.40)</td><td>21.80(21.70–21.80)</td><td>22.01(21.90–22.11)</td><td>21.97(21.90–22.04)</td><td>22.26(22.10–22.30)</td><td>21.89(21.70–22.02)</td><td>21.66(21.60–21.70)</td><td>21.35(21.10–21.50)</td></tr><tr><td rowspan="3">Basic psychological needs</td><td>Competence</td><td>3.79(3.76–3.82)</td><td>3.54(3.52–3.57)</td><td>4.03(3.97–4.10)</td><td>3.21(3.16–3.26)</td><td>3.50(3.46–3.55)</td><td>4.24(4.20–4.29)</td><td>2.82(2.78–2.87)</td><td>3.28(3.22–3.33)</td><td>3.58(3.55–3.61)</td><td>3.73(3.67–3.79)</td></tr><tr><td>Autonomy</td><td>2.25(2.18–2.32)</td><td>1.89(1.88–1.91)</td><td>2.03(1.99–2.07)</td><td>1.82(1.80–1.84)</td><td>2.17(2.13–2.20)</td><td>2.64(2.53–2.74)</td><td>1.95(1.86–2.03)</td><td>2.26(2.14–2.37)</td><td>1.99(1.97–2.01)</td><td>2.50(2.35–2.66)</td></tr><tr><td>Relatedness</td><td>3.19(3.14–3.23)</td><td>3.37(3.32–3.42)</td><td>3.45(3.34–3.56)</td><td>3.05(3.02–3.08)</td><td>2.90(2.83–2.96)</td><td>3.76(3.64–3.88)</td><td>2.86(2.81–2.91)</td><td>3.28(3.22–3.34)</td><td>3.22(3.20–3.23)</td><td>3.70(3.62–3.78)</td></tr><tr><td rowspan="5">Motivational regulation</td><td>Intrinsic motivation</td><td>4.51(4.40–4.60)</td><td>4.81(4.60–4.90)</td><td>5.40(5.20– 5.50)</td><td>3.86(3.70–3.90)</td><td>3.71(3.50–3.80)</td><td>5.74(5.60–5.80)</td><td>2.97(2.80–3.09)</td><td>4.01(3.80–4.12)</td><td>4.60(4.50–4.60)</td><td>5.24(5.09–5.30)</td></tr><tr><td>Identified regulation</td><td>4.91(4.70–5.03)</td><td>5.26(5.10–5.40)</td><td>5.80(5.60–5.90)</td><td>4.36(4.20–4.40)</td><td>4.08(3.90–4.20)</td><td>6.06(5.90–6.10)</td><td>3.33(3.10–3.40)</td><td>4.27(4.10–4.30)</td><td>5.03(4.90–5.09)</td><td>5.53(5.30–5.60)</td></tr><tr><td>Introjected regulation</td><td>3.76(3.62–3.98)</td><td>4.41(4.27–4.54)</td><td>5.11(4.98–5.23)</td><td>4.02(3.94–4.11)</td><td>3.43(3.24–3.61)</td><td>4.58(4.36–4.79)</td><td>3.09(2.94–3.24)</td><td>3.30(3.23–3.37)</td><td>4.39(4.31–4.47)</td><td>4.09(3.96–4.23)</td></tr><tr><td>External regulation</td><td>3.22(3.06–3.38)</td><td>3.88(3.73–4.03)</td><td>4.42(4.25–4.59)</td><td>4.34(4.19–4.49)</td><td>3.75(3.58–3.93)</td><td>3.17(2.94–3.41)</td><td>3.88(3.66–4.10)</td><td>2.89(2.80–2.98)</td><td>4.19(4.06–4.31)</td><td>2.87(2.76–2.98)</td></tr><tr><td>Amotivation</td><td>1.92(1.82–2.01)</td><td>1.77(1.71–1.83)</td><td>2.26(2.06–2.46)</td><td>2.57(2.39–2.75)</td><td>2.88(2.75–3.01)</td><td>1.47(1.43–1.51)</td><td>3.03(2.84–3.23)</td><td>1.72(1.63–1.80)</td><td>2.36(2.20–2.53)</td><td>1.45(1.43–1.48)</td></tr><tr><td rowspan="3">Outcomes</td><td>Effort</td><td>3.82(3.77–3.87)</td><td>3.93(3.88–3.97)</td><td>4.15(4.08–4.22)</td><td>3.57(3.53–3.61)</td><td>3.43(3.37–3.48)</td><td>4.37(4.32–4.43)</td><td>3.14(3.08–3.19)</td><td>3.66(3.60–3.72)</td><td>3.80(3.77–3.82)</td><td>4.20(4.14–4.26)</td></tr><tr><td>Satisfaction</td><td>4.02(3.97–4.06)</td><td>3.98(3.92–4.05)</td><td>4.30(4.24–4.36)</td><td>3.46(3.40–3.51)</td><td>3.42(3.33–3.50)</td><td>4.51(4.46–4.55)</td><td>2.96(2.87–3.05)</td><td>3.71(3.65–3.78)</td><td>3.87(3.84–3.90)</td><td>4.29(4.22–4.36)</td></tr><tr><td>Boredom</td><td>1.96(1.90–2.01)</td><td>2.00(1.96–2.04)</td><td>1.94(1.85–2.03)</td><td>2.58(2.49–2.66)</td><td>2.56(2.49–2.64)</td><td>1.62(1.61–1.64)</td><td>2.94(2.82–3.06)</td><td>2.08(2.02–2.15)</td><td>2.23(2.16–2.30)</td><td>1.64(1.60–1.69)</td></tr><tr><td colspan="2">Intention physical activity(PA)</td><td>4.48(4.43–4.53)</td><td>4.42(4.39–4.44)</td><td>4.54(4.51–4.58)</td><td>4.08(3.99–4.17)</td><td>4.02(3.98–4.06)</td><td>4.79(4.77–4.80)</td><td>3.12(2.96–3.29)</td><td>3.67(3.49–3.85)</td><td>4.28(4.23–4.32)</td><td>4.47(4.41–4.53)</td></tr></tbody></table> </ephtml> </p> <p>1 Data are expressed as mean (95% confidence interval).</p> <hd id="AN0159219635-14">Results</hd> <p>For the sake of clarity and to help the reader to interpret the SOM, some key points are highlighted: (<reflink idref="bib1" id="ref85">1</reflink>) sample adolescents with similar characteristics are grouped next to each other and mapped onto the same graphical area in all the component planes (also called maps). Regardless of the variable being observed either individually or interrelated, adolescents will thus always be placed in the same neuron throughout the different maps; (<reflink idref="bib2" id="ref86">2</reflink>) adolescents sharing a neuron will have similar values, but less similar to those mapped wide apart; (<reflink idref="bib3" id="ref87">3</reflink>) the map of winner neurons (bottom right map, 'Hits') represents the cells holding the number of participants, with the darker cells harbouring the largest number of adolescents and the whiter with fewer; and (<reflink idref="bib4" id="ref88">4</reflink>) cluster nine did not win any case, but the neurons in this cluster have neuronal weights because they participated in the initialization and training process.</p> <hd id="AN0159219635-15">Topological relationships of motivational constructs</hd> <p>As can be seen in Figure 1, a definitive group of 15 component planes or maps, belonging to the 15 variables of study, arose as a result of the SOM analysis. When examining these variables, by visualizing the component planes, diverse reciprocal links or topological relationships can be established among them. The 15 variables can thus be analysed by considering each particular colour area in every component plane at the same time and establishing topological relationships. According to the gender map, female participants are located in the lower blue zone (in the lower part of each map) and male adolescents in the upper red zone (upper part of each map).</p> <p>Following a general visualization, and considering the values in the vertical axis to the right of each map, those male and female participants nested in the reddish zones on the maps of intrinsic motivation and identified regulation showed the most self-determined motivation. At the same time, they were placed in the bluish area on the maps of the least self-determined types of motivation (external regulation) and lower levels of amotivation, particularly girls. However, the orange and yellow colour ranges on the map of introjected regulation (values between 4.5 and 5) indicated that these adolescents also participated in PE lessons for other extrinsic reasons, although giving them less importance than those related to self-determined types of motivation (values between 5 and 7). In the overall observation of the topological links in these five maps, an east-west structure appeared which showed a progressive change of colours indicating the evolution of some constructs of motivation.</p> <p>By observing the remaining component planes, other topological relationships indicated that those boys and girls who were more intrinsically motivated were also placed in the reddish areas of the maps of perceived effort and two of the three BPN. In particular, they showed high values of perceived competence, particularly boys, relatedness and exerted effort (values between 3.5 and 4.5), but lower levels of perceived autonomy. They were also situated in the reddish area of the maps of satisfaction (values higher than 4.2) and intention of getting involved in PA in the future (values higher than 4.4 and close to 5 in boys), and also the bluish zone of boredom (values lower than 1.7). Finally, this pattern also encompassed the adolescents with a BMI range between 20 and 22 (normal weight), the younger girls (13 and 14 years of age) and boys aged between 14 and 15 years. These results were also supported by parametric analysis, particularly Spearman correlations (see Table 2).</p> <p>Graph</p> <p>Table 2. Spearman correlation between quantitative variables using neuronal weights (n = 273).</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /><col align="center" /></colgroup><thead><tr><th align="left" /><th align="left" /><th align="center" colspan="2">Participants' characteristics</th><th align="center" colspan="3">Basic psychological needs</th><th align="center" colspan="5">Motivational regulation and amotivation</th><th align="center" colspan="3">Outcomes</th></tr><tr><th align="left" /><th align="left" /><th align="left">Age</th><th align="left">BMI</th><th align="left">Perceived competence</th><th align="left">Perceived autonomy</th><th align="left">Perceived relatedness</th><th align="left">Intrinsic motivation</th><th align="left">Identified regulation</th><th align="left">Introjected regulation</th><th align="left">External regulation</th><th align="left">Amotivation</th><th align="left">Perceived effort</th><th align="left">Satisfaction</th><th align="left">Boredom</th></tr></thead><tbody><tr><td rowspan="2"> Participants' characteristics </td><td>Age</td><td>1.00</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>BMI</td><td>0.75(0.68,0.81)</td><td>1.00</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td rowspan="3"> Basic psychological needs </td><td>Perceived competence</td><td>−0.24(−0.37, −0.10)</td><td>−0.34(−0.46, −0.21)</td><td>1.00</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Perceived autonomy</td><td>0.45(0.33, 0.55)</td><td>0.34(0.21, 0.46)</td><td>0.47(0.36, 0.58)</td><td>1.00</td><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Perceived relatedness</td><td>−0.19(−0.32, −0.05)</td><td>−0.28(−0.40, −0.14)</td><td>0.62(0.52, 0.70)</td><td>0.48(0.36, 0.58)</td><td>1.00</td><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td rowspan="5"> Motivational regulation and amotivation</td><td>Intrinsic motivation</td><td>−0.46(−0.56, −0.34)</td><td>−0.50(−0.60, −0.39)</td><td>0.85(0.81, 0.88)</td><td>0.31(0.18, 0.43)</td><td>0.84(0.79, 0.88)</td><td>1.00</td><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Identified regulation</td><td>−0.50(−0.60, −0.39)</td><td>−0.54(−0.63, −0.43)</td><td>0.85(0.80, 0.88)</td><td>0.23(0.09, 0.36)</td><td>0.79(0.73, 0.84)</td><td>0.99(0.99, 0.99)</td><td>1.00</td><td /><td /><td /><td /><td /><td /></tr><tr><td>Introjected regulation</td><td>−0.77(−0.82, −0.71)</td><td>−0.61(−0.69, −0.51)</td><td>0.59(0.50, 0.68)</td><td>−0.16(−0.29, −0.02)</td><td>0.52(0.41, 0.62)</td><td>0.79(0.74, 0.84)</td><td>0.83(0.79, 0.87)</td><td>1.00</td><td /><td /><td /><td /><td /></tr><tr><td>External regulation</td><td>−0.63(−0.71, −0.53)</td><td>−0.22(−0.34, −0.08)</td><td>−0.14(−0.27, 0.00)</td><td>−0.57(−0.66, −0.47)</td><td>−0.24(−0.37, −0.11)</td><td>−0.03(−0.17, 0.11)</td><td>0.03(−0.11, 0.16)</td><td>0.53(0.42, 0.62)</td><td>1.00</td><td /><td /><td /><td /></tr><tr><td>Amotivation</td><td>−0.12(−0.25, 0.02)</td><td>0.24(0.11, 0.37)</td><td>−0.49(−0.59, −0.37)</td><td>−0.39(−0.50, −0.27)</td><td>−0.72(−0.78, −0.65)</td><td>−0.62(−0.70, −0.53)</td><td>−0.59(−0.67, −0.49)</td><td>−0.15(−0.28, −0.01)</td><td>0.69(0.61, 0.76)</td><td>1.00</td><td /><td /><td /></tr><tr><td rowspan="3"> Outcomes</td><td>Perceived effort</td><td>−0.38(−0.49, −0.25)</td><td>−0.51(−0.60, −0.39)</td><td>0.83(0.78, 0.87)</td><td>0.32(0.19, 0.44)</td><td>0.86(0.82, 0.89)</td><td>0.97(0.96, 0.98)</td><td>0.96(0.95, 0.97)</td><td>0.70(0.62, 0.77)</td><td>−0.18(−0.31, −0.04)</td><td>−0.75(−0.80, −0.68)</td><td>1.00</td><td /><td /></tr><tr><td>Satisfaction</td><td>−0.31(−0.43, −0.18)</td><td>−0.43(−0.54, −0.31)</td><td>0.89(0.86, 0.92)</td><td>0.42(0.30, 0.53)</td><td>0.84(0.80, 0.88)</td><td>0.97(0.96, 0.98)</td><td>0.95(0.94, 0.96)</td><td>0.65(0.57, 0.73)</td><td>−0.22(−0.35, −0.09)</td><td>−0.72(−0.78, −0.65)</td><td>0.98(0.97, 0.98)</td><td>1.00</td><td /></tr><tr><td>Boredom</td><td>0.09(−0.05, 0.23)</td><td>0.36(0.23, 0.47)</td><td>−0.76(−0.81, −0.70)</td><td>−0.46(−0.56, −0.34)</td><td>−0.80(−0.84, −0.74)</td><td>−0.84(−0.87, −0.79)</td><td>−0.81(−0.85, −0.76)</td><td>−0.41(−0.52, −0.28)</td><td>0.52(0.41, 0.61)</td><td>0.91(0.89, 0.93)</td><td>−0.91(−0.93, −0.88)</td><td>−0.92(−0.94, −0.90)</td><td>1.00</td></tr><tr><td colspan="2">Intention PA</td><td>−0.30(−0.42, −0.16)</td><td>−0.47(−0.57, −0.36)</td><td>0.89(0.86, 0.92)</td><td>0.24(0.10, 0.36)</td><td>0.61(0.51, 0.69)</td><td>0.86(0.82, 0.89)</td><td>0.88(0.85, 0.91)</td><td>0.62(0.53, 0.70)</td><td>−0.17(−0.30, −0.03)</td><td>−0.63(−0.71, −0.54)</td><td>0.89(0.85, 0.91)</td><td>0.90(0.87, 0.92)</td><td>−0.83(−0.87, −0.78)</td></tr></tbody></table> </ephtml> </p> <ulist> <item>2 BMI: body mass index; PA: physical activity.</item> <item>3 Data are expressed as rho (95% confidence interval).</item> </ulist> <hd id="AN0159219635-16">Multidimensionality of motivation through students' profiles</hd> <p>When clustering from the SOM outcomes, 10 areas or clusters emerged, as shown in the <emph>Hits</emph> map in Figure 1. The descriptive data and confidence intervals of each cluster can be seen in Table 3. Four target clusters (clusters 10, 7, 6 and 5) gathering 47.67% of the participants were chosen from the whole sample. Given the particular patterns featured by these four groups of adolescents (female, male, the highest and the lowest intention to be physically active) and their potential consequences on (in) active behaviours in the future, they were explored in more detail.</p> <p>Cluster 10 (<emph>n</emph> = 395, 25% of female sample) was the largest of the female participants. It comprised those girls who intended to practice PA in the future, who were the least amotivated of the entire sample and those whose reasons for engaging in PE responded predominantly to self-determined ways of motivation, although they also gave some importance to introjected regulation. These girls were also characterized by showing the highest perception of competence, relatedness and autonomy among the female clusters. Cluster 10 showed the highest values of perceived effort and satisfaction and the lowest of boredom in PE lessons. This group was the youngest and the one with a lower BMI level and were labelled as <emph>highly motivated to be active girls</emph>.</p> <p>Cluster 7 consisted of a group of 319 girls (20.5% of female sample) with an average age of 15 and a BMI of 22.26. These adolescents expressed the lowest intention of engaging in future PA, were the most amotivated, their reasons for engaging in PE responded to a less autonomous type of extrinsic motivation, i.e. external regulation, and their perceptions of competence, relatedness and autonomy were rather low. Cluster 7 also showed the lowest perception of exerted effort and satisfaction and the highest feelings of boredom in PE classes and was labelled as <emph>barely motivated to be active girls</emph>.</p> <p>Cluster 6 involved a group of 351 boys (∼24% of the male sample), with an average age of 15 years and a BMI of 21.97. This profile was similar to Cluster 10 (girls), but these boys showed the highest values of the entire sample in all the variables. They claimed a higher intention to practice PA in the future, and perceived themselves as very competent, peer-related and autonomous in PE classes. They also showed high values of satisfaction and low values of boredom and considered themselves to have exerted lots of effort in PE. Cluster 6 was also characterized by students showing the highest values of self-determined motivation, particularly identified regulation. Of particular note were the high values in another kind of extrinsic motivation, i.e. introjected regulation, as important reasons for engaging in PE classes. Finally, they showed the lowest average in external regulation and amotivation of the whole sample. They were labelled as <emph>highly motivated to be active boys</emph>.</p> <p>Cluster 5 (379 boys, 25.72% of the male sample) comprised boys nearly 15 years of age and with an average BMI of 22.01 who claimed the possibility of getting involved in PA in the future, but they displayed nonetheless the lowest value among boys. They also showed a low perception of autonomy and the lowest perception of relatedness and competence within their male classmates, although they felt quite competent. They were the most amotivated among male students and those showing the lowest self-determined motivation (identified regulation and intrinsic motivation) and introjected regulation, as well as moderate levels of external regulation. Finally, Cluster 5 was characterized by perceiving themselves as not having exerted special effort in PE classes, not having enjoyed them as much, and for being the most bored male group in these classes. They were named <emph>vaguely motivated to be active boys</emph>.</p> <hd id="AN0159219635-17">Discussion and concluding thoughts</hd> <p>This is the first empirical study that captures the multidimensionality of motivation within SDT in a PE setting by employing SOM analysis, a more robust and accurate innovative clustering technique than the k-means algorithm ([<reflink idref="bib2" id="ref89">2</reflink>]; [<reflink idref="bib26" id="ref90">26</reflink>]). The novelty of this study lies in its capacity to examine interrelatedly a large amount of input variables and reveal the complexity behind the decision of becoming an active person, considering the motivational processes played by the satisfaction of BPN, autonomous or/and controlled motivation and affective and behavioural outcomes across several sociodemographic variables.</p> <p>The findings of the SOM analysis in the present study confirm that it is an adequate method of exploring the complex relationships among 15 input variables representing the antecedents, motivation regulations and consequences, according to SDT, and several sociodemographic variables, in a representative sample of Spanish adolescents (<emph>n</emph> = 3029). The component planes (or maps) in Figure 1 reveal the reciprocal links established among the considerable number of variables resulting in a wide range of students' profiles with different and similar experiences in PE lessons. It is important to note that the adolescents included in every neuron (hexagon) in the maps remain in the same neuron in each of the 15 maps to facilitate visualizing their profiles.</p> <hd id="AN0159219635-18">An overall visualization of maps</hd> <p>A first overview of the five maps of the types of motivation reveals that when the top right and bottom left edge of each map are overlapped, they display a colour spectrum changing progressively from red to blue. They represent those male and female students that showed they were not only highly intrinsically motivated and with an identified regulation in their participation in PE, but who also expressed a desire to engage in these classes for other extrinsic reasons, mainly related to introjected regulation (although giving them rather less importance), and they are in disagreement with amotivated reasons for being involved in PE. Beyond what the SDT continuum represents and in accordance with theoretical approaches and qualitative research ([<reflink idref="bib15" id="ref91">15</reflink>]; [<reflink idref="bib34" id="ref92">34</reflink>]), these results indicate that although represented in the continuum as diametrically distant constructs, autonomous and controlled types of motivation are not mutually exclusive, but coexist in students when participating in PE, albeit at a different level and one prevailing over the other, depending on the situation or task engaged, among other issues ([<reflink idref="bib13" id="ref93">13</reflink>]; [<reflink idref="bib32" id="ref94">32</reflink>]; [<reflink idref="bib45" id="ref95">45</reflink>]).</p> <p>In a second focused visualization of the maps in Figure 1, we concentrate on those representing the three BPN combined with the five types of motivation. Previous research on the PE domain has shown that the satisfaction of each independent psychological need predicts autonomous motivation towards PE ([<reflink idref="bib8" id="ref96">8</reflink>]). More specifically, findings from some models tested in school PE and the recent meta-analysis conducted by [<reflink idref="bib43" id="ref97">43</reflink>] reported that the satisfaction of autonomy and competence explained intrinsic motivation more strongly than relatedness. However, the results of the present study emphasize that the fulfilment of relatedness may be as crucial as the other two needs for internalization, active involvement in PE activities, social integration and well-being in PE lessons and add evidence for the importance of students' fairly balanced perception of the satisfaction of the three needs in developing autonomous motivation.</p> <hd id="AN0159219635-19">Clustering students' motivation multidimensionality profiles</hd> <p>While recognizing the importance of determining the antecedents of young people's participation in PA (e.g. socioecological models; see [<reflink idref="bib44" id="ref98">44</reflink>]), exploring the multidimensionality of motivation in PA settings becomes a key issue in the adoption of an active lifestyle. Much recent research has used a person-centred approach and conducted conventional hierarchical and non-hierarchical cluster analyses to explore multidimensionality of motivation in PE ([<reflink idref="bib13" id="ref99">13</reflink>]; [<reflink idref="bib18" id="ref100">18</reflink>]; [<reflink idref="bib45" id="ref101">45</reflink>]).</p> <p>The findings of the present study show that SOM analysis classifies students differently from the k-means algorithm and is a more robust and accurate clustering technique (see Supplemental Material). It has provided additional relevant information when exploring the multidimensionality of motivation in the PE setting since the profiles can be better adjusted to the real situation than those obtained from other clustering techniques.</p> <p>Previous research has clustered students' profiles including the types of motivation identified in SDT (known as motivational profiles) and then related them to theoretical antecedents and motivational outcomes as well as sociodemographic variables. To date, three- to five-cluster solutions have emerged. In this study, the <emph>Hits</emph> map in Figure 1 represents 10 emerging clusters from SOM output combining the 15 variables simultaneously and identifying areas or niches of interest in the students' profiles.</p> <p>The four selected profiles of interest allowed an in-depth study of the target groups of students in line with the aim of the study. Clusters 10 and 6 bring together female and male students with a strong intention of being involved in PA in the future, and 7 and 5 represent those female and male students who are most hesitant in becoming involved in future PA. The four clusters also trace different combinations of some SDT constructs: perceived BPN satisfaction, motivational regulations and motivational consequences.</p> <p>Research on the consequences of adaptive autonomous motivation in PE supports the idea that students who possess more self-determined motivation will experience more adaptive cognitive, affective and behavioural consequences (see [<reflink idref="bib42" id="ref102">42</reflink>]). We obtained support for this theoretical postulation in the present study. Both the profiles of <emph>highly motivated to be active girls</emph> and <emph>boys</emph> (10 and 6, respectively) embrace the least amotivated students and predominantly those who experience self-determination in PE classes. These adolescents also find some reasons for engaging in PE related to an internal pressure to do so (introjected regulation) and to prevent problems with the PE teacher (external regulation). They also express the highest perceptions in the fulfilment of competence, relatedness and autonomy, and are the students with the strongest intention of engaging in future PA, those with the highest perceived exerted effort and satisfaction and the least feelings of boredom in PE classes.</p> <p>The second group of profiles were the <emph>barely motivated to be active girls</emph> and <emph>vaguely motivated boys</emph>. These girls are the most reluctant to participate in PA after finishing secondary school ([<reflink idref="bib29" id="ref103">29</reflink>]). SDT posits that amotivation, introjected and external regulation, and low levels of satisfaction of the three psychological needs (particularly competence) are assumed to be related to maladaptive outcomes. However, previous PE-based cross-sectional and longitudinal studies found no relationships among introjected regulation, autonomy and relatedness needs satisfaction, and intention of being involved in PA in the future ([<reflink idref="bib38" id="ref104">38</reflink>]). The results of our study are partially consistent with the previous research. The <emph>barely motivated to be active girls</emph> report the lowest levels of self-determined regulations and surprisingly also of introjected regulation. Their perceptions of low competence, not being able to make choices nor feel related to their classmates are also central to their reluctance to be physically active in the future. These female students also perceive they may be wasting their time on this subject (they are the most amotivated) and they participate in PE partly because they are supposed to do so and might be in trouble if they do not (moderate levels of external regulation). Actually, they report themselves to be moderately dissatisfied with PE lessons, to put little effort into them and they are the ones who find these lessons most boring. This profile therefore appears to have the most maladaptive perceived experiences in PE by revealing that a combination of low levels of self-determined forms of motivation, but also low of introjected regulation, aligned with moderate levels of external regulation, result in less positive PE experiences and are detrimental to the adoption of an active lifestyle.</p> <p>Although male adolescents in Cluster 5 share similarities with the above profile, they show a peculiar poorly defined profile regarding their type of motivation. Although these <emph>vaguely motivated to be active boys</emph> intend to be physically active in the future, they represent the least adaptive profile on the motivation-related constructs concerning male students. They report perceiving themselves as not having put a special effort into PE lessons, not enjoying them much, getting rather bored in them, and having low perceptions of relatedness and autonomy. However, compared to the same profile in girls, these boys perceive themselves to be more competent and less hesitant to engage in PA in their leisure time. This result may suggest that male students who feel competent in the PE setting, regardless of their low level of autonomous forms of motivation, are more likely to be physically active. The need satisfaction of feeling competent could be considered a crucial motivational asset in certain male adolescents with a <emph>vaguely motivated to be active</emph> profile greater than the rest of the motivational constructs. However, these boys can be considered more vulnerable, since although they fulfil their perceptions of competence, the neglect of the other two psychological needs, particularly relatedness, is more likely to determine their controlled motivation (they exhibit a predominant external regulation) and consequently they are more prone to maladaptive behaviours.</p> <p>Some potential weaknesses of this study should be considered. First, a considerable number of profiles were identified due to the exploratory nature of SOM analysis; however, only four of these were investigated to be consistent with the focus of our study. Other research interests may lead authors to choose different clusters and approach different areas of analysis in the future. The second limitation is inherent to cross-sectional studies. This form of research takes place at a single point in time and limits the possibility of determining changes over time in all the variables. It would thus be interesting to use longitudinal designs to examine the long-term effects of BPN satisfaction and types of motivation on students' intention to engage in PA in the future. Finally, a qualitative research approach would provide further holistic explanations from the students' perspectives of the reasons and ways different experiences and outcomes emerge in PE classes and how they are influenced by the different motivational atmospheres and social agents involved in it ([<reflink idref="bib46" id="ref105">46</reflink>]).</p> <p>Despite the aforementioned limitations, the present study also has several strengths regarding the SOM-mapping method:</p> <p></p> <ulist> <item> It captures a wider combination of more complex relationships among a considerable set of variables when approaching motivational constructs in PE, resulting in a higher in number and a more holistic view of the multidimensional profiles coexisting in PE lessons than those emerging from other clustering techniques.</item> <p></p> <item> When the number of clusters is relatively high (9–10 in this case), it can improve the interpretation of the results by visualising the emerging maps. This paper also provides sufficient information for future researchers to proceed with the same protocol of analysis used here (see also Supplemental Material).</item> </ulist> <p>From an applied perspective, the present study provides useful information for researchers and practitioners to understand that different types of motivation combine and interact affecting students' learning, their values towards PA culture and behaviours towards an active lifestyle. It highlights no gender differences in students with a <emph>h</emph><emph>ighly motivated to be active</emph> profile, showing a prevalence of autonomous motivation, but also some controlled reasons to engage in PE, although to a lesser extent, and a fairly balanced perception of the three needs satisfaction, and high values of adaptive consequences. These findings are useful for reinforcing an inclusive climate in PE, where the three BPN are supported to integrate and fulfil both females' and males' interests and needs.</p> <p>However, some gender and BPN variations affecting students more reluctant to engage in PA are of special interest to tailoring interventions in these profiles. Since <emph>barely motivated to be active girls</emph> (Cluster 7) are extrinsically regulated and show fewer positive PE experiences, it is crucial for teachers to facilitate self-determined types of regulations to this particular student profile by supporting autonomous learning, listening to the students' views and accepting their perspectives ([<reflink idref="bib37" id="ref106">37</reflink>]). Thus, female students' preferences, choice-making, competence, and personally challenging and captivating activities become critical issues in PE lessons. Regarding the <emph>vaguely motivated to be active boys</emph>, even though they fulfil their perceptions of competence, the neglect of the other two psychological needs (particularly relatedness) is more likely to determine their controlled motivation. If one of the main goals of this subject is helping students to shape active identities by progressively identifying meaningful PA and including it in their lifestyle, detrimental experiences for the adoption of an active lifestyle should be avoided by: (a) combining both intrinsic motivation and identified regulation and fostering feelings of responsibility for behaving well; (b) evenly fulfilling students' needs of feeling competent, autonomous and socially related, focusing particularly on relatedness; (c) rewarding effort; and (d) proposing enjoyable and satisfying activities.</p> <p>To conclude, the present article submits SDT to review from a different type of clustering analysis, named SOM, and its findings support and consolidate this motivational theory. It also contributes to understanding students' experiences in PE and their implications for PE curricula to facilitate positive experiences leading to students' regular participation in PA and well-being.</p> <hd id="AN0159219635-20">Supplemental Material</hd> <p>sj-docx-1-epe-10.1177_1356336X221088396.docx</p> <p>sj-docx-1-epe-10.1177_1356336X221088396 - Supplemental material for Capturing the multidimensionality of motivation in physical education: A self-organizing maps approach to profiling students</p> <p></p> <p>Supplemental material, sj-docx-1-epe-10.1177_1356336X221088396 for Capturing the multidimensionality of motivation in physical education: A self-organizing maps approach to profiling students by Carmen Peiró-Velert, Xavier García-Massó, Esther Pérez-Gimeno, Jorge Lizandra, Alexandra Valencia-Peris and José Devís-Devís in European Physical Education Review</p> <p></p> <hd id="AN0159219635-21">Acknowledgements</hd> <p>We express our sincere thanks to all the schools and adolescents involved in this study. Finally, we thank the editor and the reviewers for their helpful comments.</p> <hd id="AN0159219635-22">Author biographies</hd> <p> <bold>Carmen Peiró-Velert</bold> is a Professor of Didactics of Corporal Expression at the Universitat de València and coordinator of the Doctoral Programme in Specific Didactics. Her research focuses on health-related physical education, motivation and physical education teacher education.</p> <p> <bold>Xavier García-Massó</bold> is an Associate Professor in the Department of Teaching of Music, Art and Corporal Expression at the Universitat de València. His main research interest includes the study of the maturation process of motor control from childhood to adulthood and the development of motor learning strategies to be applied in the physical education context.</p> <p> <bold>Esther Pérez-Gimeno</bold> is a PhD student at the Universitat de València. Her main research interest is focused on physical activity promotion and motivation.</p> <p> <bold>Jorge Lizandra</bold> is a Lecturer in the Department of Teaching of Music, Art and Corporal Expression at the Universitat de València. His main research interest is the promotion of health-related physical activity in physical education.</p> <p> <bold>Alexandra Valencia-Peris</bold> is an Associate Professor in the Department of Teaching of Music, Art and Corporal Expression, at the Universitat de València. Her research focuses on physical activity and health promotion, as well as physical education pedagogy.</p> <p> <bold>José Devís-Devís</bold> is a Professor of Physical Education and Sport in the Universitat de València and coordinator of the 'Physical Activity, Education and Society' research group. 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Teaching and Teacher Education99: 103247.</bibtext> </blist> </ref> <ref id="AN0159219635-24"> <title> Footnotes </title> <blist> <bibtext> The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.</bibtext> </blist> <blist> <bibtext> The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Ministry of Science and Innovation (Spain) (EDU2009-13664). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</bibtext> </blist> <blist> <bibtext> Carmen Peiró-Velert https://orcid.org/0000-0003-4794-6541 Alexandra Valencia-Peris https://orcid.org/0000-0002-2031-9743</bibtext> </blist> <blist> <bibtext> Supplemental Material for this article is available online.</bibtext> </blist> </ref> <aug> <p>By Carmen Peiró-Velert; Xavier García-Massó; Esther Pérez-Gimeno; Jorge Lizandra; Alexandra Valencia-Peris and José Devís-Devís</p> <p>Reported by Author; Author; Author; Author; Author; Author</p> <p></p> <p>Carmen Peiró-Velert is a Professor of Didactics of Corporal Expression at the Universitat de València and coordinator of the Doctoral Programme in Specific Didactics. Her research focuses on health-related physical education, motivation and physical education teacher education.</p> <p>Xavier García-Massó is an Associate Professor in the Department of Teaching of Music, Art and Corporal Expression at the Universitat de València. His main research interest includes the study of the maturation process of motor control from childhood to adulthood and the development of motor learning strategies to be applied in the physical education context.</p> <p>Esther Pérez-Gimeno is a PhD student at the Universitat de València. Her main research interest is focused on physical activity promotion and motivation.</p> <p>Jorge Lizandra is a Lecturer in the Department of Teaching of Music, Art and Corporal Expression at the Universitat de València. His main research interest is the promotion of health-related physical activity in physical education.</p> <p>Alexandra Valencia-Peris is an Associate Professor in the Department of Teaching of Music, Art and Corporal Expression, at the Universitat de València. Her research focuses on physical activity and health promotion, as well as physical education pedagogy.</p> <p>José Devís-Devís is a Professor of Physical Education and Sport in the Universitat de València and coordinator of the 'Physical Activity, Education and Society' research group. His research focuses on physical education and physical education teacher education, as well as on leisure time physical activity in different vulnerable groups.</p> </aug> <nolink nlid="nl1" bibid="bib40" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib17" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib19" firstref="ref3"></nolink> <nolink nlid="nl4" bibid="bib29" firstref="ref5"></nolink> <nolink nlid="nl5" bibid="bib34" firstref="ref10"></nolink> <nolink nlid="nl6" bibid="bib39" firstref="ref11"></nolink> <nolink nlid="nl7" bibid="bib41" firstref="ref12"></nolink> <nolink nlid="nl8" bibid="bib13" firstref="ref14"></nolink> <nolink nlid="nl9" bibid="bib18" firstref="ref15"></nolink> <nolink nlid="nl10" bibid="bib37" firstref="ref18"></nolink> <nolink nlid="nl11" bibid="bib42" firstref="ref20"></nolink> <nolink nlid="nl12" bibid="bib43" firstref="ref21"></nolink> <nolink nlid="nl13" bibid="bib12" firstref="ref24"></nolink> <nolink nlid="nl14" bibid="bib14" firstref="ref25"></nolink> <nolink nlid="nl15" bibid="bib22" firstref="ref27"></nolink> <nolink nlid="nl16" bibid="bib23" firstref="ref28"></nolink> <nolink nlid="nl17" bibid="bib24" firstref="ref30"></nolink> <nolink nlid="nl18" bibid="bib45" firstref="ref32"></nolink> <nolink nlid="nl19" bibid="bib31" firstref="ref33"></nolink> <nolink nlid="nl20" bibid="bib38" firstref="ref35"></nolink> <nolink nlid="nl21" bibid="bib30" firstref="ref38"></nolink> <nolink nlid="nl22" bibid="bib32" firstref="ref39"></nolink> <nolink nlid="nl23" bibid="bib27" firstref="ref41"></nolink> <nolink nlid="nl24" bibid="bib26" firstref="ref57"></nolink> <nolink nlid="nl25" bibid="bib33" firstref="ref58"></nolink> <nolink nlid="nl26" bibid="bib25" firstref="ref59"></nolink> <nolink nlid="nl27" bibid="bib11" firstref="ref61"></nolink> <nolink nlid="nl28" bibid="bib16" firstref="ref64"></nolink> <nolink nlid="nl29" bibid="bib20" firstref="ref65"></nolink> <nolink nlid="nl30" bibid="bib35" firstref="ref66"></nolink> <nolink nlid="nl31" bibid="bib36" firstref="ref69"></nolink> <nolink nlid="nl32" bibid="bib28" firstref="ref74"></nolink> <nolink nlid="nl33" bibid="bib21" firstref="ref79"></nolink> <nolink nlid="nl34" bibid="bib10" firstref="ref84"></nolink> <nolink nlid="nl35" bibid="bib15" firstref="ref91"></nolink> <nolink nlid="nl36" bibid="bib44" firstref="ref98"></nolink> <nolink nlid="nl37" bibid="bib46" firstref="ref105"></nolink>
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  Group: Ti
  Data: Capturing the Multidimensionality of Motivation in Physical Education: A Self-Organizing Maps Approach to Profiling Students
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  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Peiró-Velert%2C+Carmen%22">Peiró-Velert, Carmen</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-4794-6541">0000-0003-4794-6541</externalLink>)<br /><searchLink fieldCode="AR" term="%22García-Massó%2C+Xavier%22">García-Massó, Xavier</searchLink><br /><searchLink fieldCode="AR" term="%22Pérez-Gimeno%2C+Esther%22">Pérez-Gimeno, Esther</searchLink><br /><searchLink fieldCode="AR" term="%22Lizandra%2C+Jorge%22">Lizandra, Jorge</searchLink><br /><searchLink fieldCode="AR" term="%22Valencia-Peris%2C+Alexandra%22">Valencia-Peris, Alexandra</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-2031-9743">0000-0002-2031-9743</externalLink>)<br /><searchLink fieldCode="AR" term="%22Devís-Devís%2C+José%22">Devís-Devís, José</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22European+Physical+Education+Review%22"><i>European Physical Education Review</i></searchLink>. Nov 2022 28(4):852-872.
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  Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
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  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 21
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2022
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Secondary+Education%22">Secondary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Adolescents%22">Adolescents</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Motivation%22">Student Motivation</searchLink><br /><searchLink fieldCode="DE" term="%22Physical+Education%22">Physical Education</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Needs%22">Student Needs</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Determination%22">Self Determination</searchLink><br /><searchLink fieldCode="DE" term="%22Affective+Behavior%22">Affective Behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Behavior%22">Student Behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Participation%22">Student Participation</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Efficacy%22">Self Efficacy</searchLink><br /><searchLink fieldCode="DE" term="%22Personal+Autonomy%22">Personal Autonomy</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Satisfaction%22">Student Satisfaction</searchLink><br /><searchLink fieldCode="DE" term="%22Gender+Differences%22">Gender Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Physical+Activity+Level%22">Physical Activity Level</searchLink><br /><searchLink fieldCode="DE" term="%22Competence%22">Competence</searchLink><br /><searchLink fieldCode="DE" term="%22Relevance+%28Education%29%22">Relevance (Education)</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Secondary+School+Students%22">Secondary School Students</searchLink>
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  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Spain%22">Spain</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1177/1356336X221088396
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  Label: ISSN
  Group: ISSN
  Data: 1356-336X<br />1741-2749
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  Label: Abstract
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  Data: This study aimed to capture the multidimensionality of adolescents' motivation in the physical education (PE) setting, within self-determination theory, by employing self-organizing maps (SOM) analysis. Particularly, it examined the topological relationships among students' basic psychological needs satisfaction, their perception of more or less self-determined motivation and the affective and behavioural consequences in PE lessons across several sociodemographic variables. A nationally representative sample of 3029 Spanish students (51% girls), aged 12 to 18 years, was surveyed. SOM mapped well-defined students' profiles that embraced interrelatedly a considerable number of students' motivational characteristics. Four target profiles, out of 10, were explored. The first two profiles, highly motivated to be active girls and boys, mainly experienced senses of self-determination, but also controlled reasons for participating in PE lessons, high perceived competence, relatedness and autonomy fulfilment, perceived exerted effort and satisfaction. However, the reluctance to be physically active presented two gendered motivational profiles. Barely motivated to be active girls showed the lowest levels of self-determined motivation, including introjected regulation, low perceptions of competence, autonomy, relatedness, and dissatisfaction in PE. Vaguely motivated to be active boys revealed that despite their perceptions of competence the neglect of the other two psychological needs was more likely to determine a controlled motivation and, consequently, maladaptive outcomes. SOM proved to be a more robust and accurate clustering technique than the k-means algorithm and helped to portray and visualize the complexity behind the decision to become an active person considering the motivational processes in PE. Implications are provided for practitioners.
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  Data: 2022
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  Data: EJ1350616
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      – SubjectFull: Adolescents
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