Students’ physical activity intensity and sedentary behaviour by physical self-concept profiles : A latent profile analysis

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY-NC-ND 4.0 https://creativecommons.org/licenses/by-nc-nd/4.0/ Students’ physical activity intensity and sedentary behaviour by physical self-concept profiles : A latent profile analysis © 2020 the Author(s) Published version Guijarro-Romero, Santiago; Mayorga-Vega, Daniel; Viciana, Jesús; Casado-Robles, Carolina; Gråstén, Arto; Jaakkola, Timo Guijarro-Romero, S., Mayorga-Vega, D., Viciana, J., Casado-Robles, C., Gråstén, A., & Jaakkola, T. (2020). Students’ physical activity intensity and sedentary behaviour by physical self-concept profiles : A latent profile analysis. RICYDE: Revista Internacional de Ciencias del Deporte, 16(59), 85-101. https://doi.org/10.5232/ricyde2020.05907 2020 Students’ physical activity intensity and sedentary behaviour by physical self-concept profiles: A latent profile analysis Intensidad de la actividad física y comportamiento sedentario de los estudiantes por perfiles de autoconcepto físico: Un análisis de perfil latente Santiago Guijarro-Romero 1 ; Daniel Mayorga-Vega 2 ; Jesús Viciana 1 ; Carolina Casado-Robles 1 ; Arto Gråstén 3 , & Timo Jaakkola 4 1.Department of Physical Education and Sport, University of Granada, Granada, Spain 2.Department of Didactic of Musical, Plastic and Corporal Expression, University of Jaen, Jaen, Spain 3.Faculty of Education, University of Tasmania, Launceston, Tasmania, Australia 4.Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland Abstract Aims of this study were to identify student clusters in physical appearance, sport competence, global physical self-concept and self-esteem, and to examine whether different physical self-concept groups differ in their moderate-to-vigorous physical activity (MVPA) and sedentary behaviour. Participants of the study were 211 boys and 183 girls aged 13-16 years. MVPA and sedentary behaviour were monitored by GT3X accelerometers during seven days. Participants’ physical self-concept was measured by the short Physical Self-Description Questionnaire. Latent profile analyses revealed a four-cluster solution: 1) “low sport competence, moderate global physical self-concept and self-esteem, and high physical appearance”; 2) “high sport competence, moderate global physical self-concept and self-esteem, and low physical appearance”; 3) “moderate sport competence, global physical self-concept, self-esteem, and physical appearance”, and 4) “moderate sport competence and global physical self-concept, high self-esteem, and low physical appearance”. Multivariate analysis of variance showed differences in MVPA between boys’ in clusters 2 and 3 (p < .05). Students’ MVPA levels differ by physical self-concept profiles . Key words: physical self-perceptions; physical activity; sedentary behaviour; clusters; accelerometry. Resumen Los objetivos del estudio fueron identificar grupos de estudiantes en apariencia física, competencia deportiva, autoconcepto físico global y autoestima, y examinar si los diferentes grupos de autoconcepto físico difieren en su actividad física moderada-vigorosa (AFMV) y comportamiento sedentario. Los participantes del estudio fueron 211 varones y 183 mujeres de 13-16 años. La AFMV y el comportamiento sedentario fueron monitorizados por acelerómetros GT3X durante siete días. El autoconcepto físico de los estudiantes fue medido por la versión corta del Physical Self-Description Questionnaire. Los análisis de perfil latente revelaron una solución de cuatro grupos: 1) “baja competencia deportiva, moderado autoconcepto físico global y autoestima, y alta apariencia física”; 2) alta competencia deportiva, moderado autoconcepto físico global y autoestima, y baja apariencia física”; 3) “moderada competencia deportiva, autoconcepto físico global, autoestima, y apariencia física”; y 4) “moderada competencia deportiva y autoconcepto físico global, alta autoestima, y baja apariencia física”. Los análisis multivariados de la varianza mostraron diferencias en la AFMV entre los grupos de chicos 2 y 3 (p < ,05). Los niveles de AFMV de los estudiantes difieren según los perfiles de autoconcepto físico. Palabras clave: autopercepciones físicas; actividad física; comportamiento sedentario; clusters; acelerometría. Correspondence/correspondencia: Daniel Mayorga-Vega Department of Didactic of Musical, Plastic and Corporal Expression, University of Jaen, Jaen, Spain Email: dmayorga[email protected] RICYDE. Revista Internacional de Ciencias del Deporte doi: 10.5232/ricyde Rev. Int. cienc. deporte https://doi.org/10.5232/ricyde2020.05907 RICYDE. Revista Internacional de Ciencias del Deporte Volume XVI - Year XVI Pages: 85-101 - ISSN: 1885-3137 Issue 59 - January 2020 Received: March 24, 2019; Accepted: October 11, 2019 Guijarro-Romero, S.; Mayorga-Vega, D.; Viciana, J.; Casado-Robles, C.; Gråstén, A., & Jaakkola, T. (2020). Students’ physical activity intensity and sedentary behaviour by physical self-concept profiles: A latent profile analysis. RICYDE. Revista internacional de ciencias del deporte, 59(16), 85-101. https://doi.org/10.5232/ricyde2020.05907 86 Introduction hysical activity (PA) is considered a strong health marker among children and adolescents (Poitras et al., 2016). More specifically, there is consistent evidence on favourable relationships between moderate-to-vigorous PA (MVPA) with adiposity, cardiometabolic biomarkers, physical fitness, bone health, cognition and academic performance within youth (Esteban-Cornejo, Tejero-Gonzalez, Sallis, & Veiga, 2015; Poitras et al., 2016). Participating in regular PA may also improve psychological health in adolescents and avoid mental health problems such as anxiety or depression (Biddle, Ciaccioni, Thomas, & Vergeer, 2018). Regarding, sedentary behaviour is also considered as an important health risk factor among children and adolescents (Carson et al., 2016). Higher amount of sedentary behaviour in adolescence is related with an unfavourable cardiometabolic risk, physical fitness, and body composition (Carson et al., 2016). Unfortunately, previous studies have shown that the intensity of PA participation decreases from childhood to adolescence and from adolescence to young adulthood (Corder et al., 2017; Ortega et al., 2013). Additionally, sedentary behaviour has been also shown to increase from childhood to adolescence (Ortega et al., 2013; Pearson, Haycraft, Johnston, & Atkin, 2017). Physical inactivity has been suggested as becoming a worldwide challenge (Ferreira de Moraes, Guerra, & Rossi-Menezes, 2013), which affects more than 80% of adolescents in the world (World Health Organization [WHO], 2018). Research has revealed that there are many psychological antecedents such as students’ motivation toward PA or physical selfconcept for the intensity of PA participation and sedentary behaviour (Cortis et al., 2017; Rollo, Gaston, & Prapavessis, 2016). This study aims to extend this area of research by investigating the relationship among physical self-perceptions, the intensity of PA participation and sedentariness. The way people think about themselves in achievement settings has a remarkable association on their behaviour (Babic et al., 2014; Harter, 1978). According to Shavelson, Hubner, and Stanton (1976) general self-concept represents a multidimensional structure including four sub-domains: emotional, social, academic and physical self-concept. Generally, physical selfconcept refers to a judgement a person has about his or her physical abilities when interacting with the environment (Shavelson et al., 1976). Based on Shavelson et al. (1976) model, later Marsh, Richards, Johnson, Roche, and Tremayne (1994) determined the physical self-concept by eleven components: health, coordination, activity, body fat, physical appearance, sport competence, global physical self-concept, self esteem, strength, flexibility and endurance. This study considered only four sub-domains - physical appearance (“being good looking, having a nice face”), sport competence (“being good at sports, being athletic, having good sports skills”), global physical self-concept (“feeling positive about one’s physical self”) and self-esteem (“overall positive feelings about self”) (Marsh, Martin, & Jackson, 2010, 473) - because the focus of the current study is to investigate psychological aspects of the physical self-concept. Other seven sub-domains represent physical (health, health-related fitness) and behavioural (PA participation) aspects of physical self-concept. Physical self-concept is recognized as a relevant health marker during adolescence (Esnaola, Goñi, & Madariaga, 2008). For example, research has demonstrated that physical selfconcept and its sub-domains are significantly associated with PA within youth (Babic et al., 2014; Revuelta, Esnaola, & Goñi, 2016). In contrast, negative physical self-concept is P Guijarro-Romero, S.; Mayorga-Vega, D.; Viciana, J.; Casado-Robles, C.; Gråstén, A., & Jaakkola, T. (2020). Students’ physical activity intensity and sedentary behaviour by physical self-concept profiles: A latent profile analysis. RICYDE. Revista internacional de ciencias del deporte, 59(16), 85-101. https://doi.org/10.5232/ricyde2020.05907 87 associated with low PA levels within children and adolescents (Babic et al., 2014; GraoCruces, Nuviala, Fernandez-Martinez, & Perez-Turpin, 2014). In their systematic review and meta-analysis Babic et al. (2014) highlighted the importance of understanding the structure of physical self-concept and its relationships with health-related behaviours. Previous studies within children and adolescent samples have indicated a positive association between self-esteem and PA (Carter, 2018; Reddon, Meyre, & Cariney, 2017) and between sport competence and PA (Babic et al., 2014; Utesch, Dreiskämper, Naul, & Geukes, 2018). Studies have also shown that physical appearance has a positive but weak association with PA within adolescent samples (Babic et al., 2014). More specifically, several studies have found positive associations between physical appearance and PA among boys but negative among girls (Grao-Cruces et al., 2014; Moreno-Murcia, Hellín, González-Cutre, & Martínez-Galindo, 2011). Additionally, global physical self-concept has shown been positively correlated with PA within adolescents (Contreras, Fernández, García, Palou, & Ponseti, 2010; Reigal Garrido, Videra García, Parra Flores, & Ruiz de Mier, 2012). A review of sport science literature demonstrates that there is a lack of studies investigating associations between sub-domains of physical self-concept and sedentary behaviour. Concretely, we found only three studies that analyse these associations (Carson et al., 2016; Suchert, Hanewinkel, & Isensee, 2016; Webb, Benjamin, Gammon, McKee, & Biddle, 2013). These studies showed that sedentary behaviour was negatively associated with self-esteem, physical appearance and sport competence (Carson et al., 2016; Suchert et al., 2016). However, to our knowledge, there are no studies that examine the relationships between global physical self-concept sub-domain and sedentary behaviour within adolescent samples. Only three previous cluster analytic studies have investigated physical self-concept profiles among adolescents in the physical education (PE) setting, and also demonstrated that profiles differ in the intensity of PA participation (Biddle & Wang, 2003; De Meester et al., 2016; Wang, Sun, Liu, Yao, & Pyun, 2015). Additionally, apart from self-perceptions, these studies included motivation (Biddle & Wang, 2003), and physical variables such as actual motor competence (De Meester et al., 2016) as clustering variables. Biddle and Wang (2003) clustered students based on sport competence, physical condition, strength, attractiveness and motivation. They found five types of motivation and physical self-concept profile groups: 1) amotivated; 2) very low motivation and low physical self-concept; 3) moderate motivation and physical self-concept; 4) moderate motivation and high physical self-concept; and 5) high motivation and physical self-concept. Additionally, they found that, higher profiles of motivation and physical self-concept generally showed higher PA levels than lower profiles (Biddle & Wang, 2003). De Meester et al. (2016) clustered students based on perceived and actual motor competence. They found four physical self-concept profile groups: 1) low perceived and actual motor competence; 2) average perceived and actual motor competence; 3) high perceived and low actual motor competence; and 4) high perceived and average motor competence. Their study also demonstrated that low perceived and actual motor competence cluster showed the lowest PA levels comparing with other clusters. Regarding Wang et al. (2015) clustered students based on physical activity, physical appearance, body fat, coordination, endurance, self-esteem, flexibility, global physical self-concept, health, sport competence and strength. They found three types of physical self-concept profiles groups: 1) low in each; 2) moderate in each; and 3) high in each. In this study the highest physical self-concept profile Guijarro-Romero, S.; Mayorga-Vega, D.; Viciana, J.; Casado-Robles, C.; Gråstén, A., & Jaakkola, T. (2020). Students’ physical activity intensity and sedentary behaviour by physical self-concept profiles: A latent profile analysis. RICYDE. Revista internacional de ciencias del deporte, 59(16), 85-101. https://doi.org/10.5232/ricyde2020.05907 88 showed the highest PA levels following by the moderate profile, while the lowest physical self-concept profile showed the lowest PA levels. However, it should be noticed that all these studies measured PA levels by self-reports, which can lead to underor overestimation of the intensity of PA participation (Bermúdez et al., 2013). Additionally, the aforementioned studies did not measure sedentariness. The present study expands previous cluster analytical studies by investigating MVPA and sedentariness through objective measures. The first aim of this study is to identify groups of students with homogenous profiles in physical appearance, sport competence, global physical self-concept and self-esteem. The second aim of the study is to examine whether the different physical self-concept profiles differ in their MVPA and sedentary behaviour. Methods Participants A sample of 394 adolescents, 211 boys (53.6%) and 183 girls (46.4%) from one statesubsidised high school chosen by convenience of the province of Granada (age = 13.9 ±1.1 years, body mass = 57.2 ± 12.0 kg, and body height = 162.6 ± 8.4 cm) were invited to participate in the present study. The inclusion criteria were: 1) belonged to the first to fourth grades of the secondary education level; 2) did not have any health disorder that would have made impossible the performance of the PA normally; 3) wore the accelerometer during a whole week; 4) completed the whole self-physical self-concept questionnaire; 5) presented the corresponding signed students’ assent, and; 6) presented the corresponding signed consent by their parents or legal tutors. Measures Moderate-to-vigorous physical activity and sedentary behaviour. Participants’ objective MVPA and sedentary behaviour were measured trough GT3X+ accelerometers (ActiGraph, LLC, Pensacola, FL, USA). The GT3X+ accelerometer is a triaxial monitor that registers and measures variations of acceleration in the time that range in magnitude from approximately .05 to 2.50 Gs. The ActiLife Lifestyle Monitoring System Software (version 6.9.2) was used to treat the data. The first day with the data obtained was considered as a familiarization day and it was not used for statistical analyses (Dössegger et al., 2014; Mayorga-Vega, MartínezBaena, & Viciana, 2018). Since adolescents’ PA patterns are characterized by short bursts of rapidly changing activity, the interval of time (epoch) was set at 1 s (Cain, Sallis, Conway, Van Dyck, & Calhoon, 2013). A minimum wear time of 600 min per day was established (Migueles et al., 2017). A minimum length of 60 min of consecutive zero-count epochs with up to two minutes spike tolerance was established as non-wear periods (Oliver, Badland, Schofiedl, & Shepherd, 2011). The percentage of time engaged in MVPA (e.g., ≥ 2,296 counts/min) and sedentary behaviour (e.g., 0-100 counts/min) were determined according to Evenson’s cut-off points (Evenson, Catellier, Gill, Ondrak, & McMurray, 2008; Trost, Loprinzi, Moore, & Pfeiffer, 2011). Firstly, with the purpose of avoiding potential bias due to differences in the length of total valid wear time, the percentage of time that participants spent on MVPA and sedentary behaviour in relation with the total valid wear time during the day were calculated (Mayorga-Vega et al., 2018). Then, the weighted average time of the week engaged in MVPA and sedentary behaviour was calculated (e.g., (5 x MVPA during weekdays + 2 x MVPA during weekend days)/ 7)). ActiGraph accelerometer-measured MVPA and sedentary behaviour has shown a high level of validity among adolescents Guijarro-Romero, S.; Mayorga-Vega, D.; Viciana, J.; Casado-Robles, C.; Gråstén, A., & Jaakkola, T. (2020). Students’ physical activity intensity and sedentary behaviour by physical self-concept profiles: A latent profile analysis. RICYDE. Revista internacional de ciencias del deporte, 59(16), 85-101. https://doi.org/10.5232/ricyde2020.05907 89 (MVPA, ROC-AUC = .90; Se = .88; Sp = .92; sedentary behaviour, ROC-AUC = .90; Se = 1.00; Sp = .79) (Trost et al., 2011). Physical self-concept. Physical self-concept was measured through the adapted and validated Spanish version of the short form of Physical Self-Description Questionnaire (PSDQ-S) (Marsh et al., 2010). This questionnaire consists of 40 items that measure nine specific components of physical self-concept (health, coordination, body fat, PA, sport competence, physical appearance, strength, flexibility, and cardiorespiratory fitness) and two global components (global physical self-concept and self-esteem). In this study, only sport competence (three items; e.g., “I am good at most sports”), physical appearance (three items; e.g., “I have a nice looking face”), global physical self-concept (three items; e.g., “Physically, I feel good about myself”) and self-esteem (five items; e.g., “Overall, I am no good”) scales were used. According to previous studies (e.g., Viciana, Mayorga-Vega, Guijaro-Romero, & Martínez-Baena, 2017a), a 10-point Likert-type scale (1 = “Totally false”… 10 = “Totally true”) was used. Since the self-esteem dimension had two negatively worded items, they were recoded before statistical analyses. The present data showed adequate psychometric properties among adolescents (Crombach’s alpha = .9, .87, .89 and .76; average variance extracted = .7, .7, .7 and .29; Omega = .87, .88, .88 and .60 for sport competence, physical appearance, global physical self-concept and self-esteem dimensions, respectively). Anthropometric. Participants’ body mass (Seca, Ltd., Hamburg, Germany; accuracy = 0.1 kg) and height (Holtain Ltd., Crymmych, Pembs, United Kingdom; accuracy = 0.1 cm) were measured. Participants’ body mass and height were measured in shorts, T-shirts, and barefoot. Two measurements of both body mass and height were performed and the average of each was calculated (International Society for the Advancement of Kinanthropometry, 2001). Procedure Firstly, the research protocol was approved by the Ethical Committee of the University of [omitted for peer review]. Then, the principal and PE teacher of a state-subsidised high school chosen by convenience of the province of [omitted for peer review] were informed about the project and the permission to carry out the study was requested. After the school approvals were obtained, adolescents and their legal tutors were fully informed about all the features of the study and were requested to sign an informed consent form. During the first week, students were instructed about when they should wear the accelerometer (during the whole day, from getting up until they go to sleep, less when they do aquatic activities or have a shower). Then, accelerometers were placed on the right hip by using an elastic waistband and students wore them during a whole week. Students were urged to continue with their normal PA habits. In the second week, the PSDQ-S questionnaire was administered to students in quiet conditions in an ordinary classroom (15-20 minutes approximately). Before answering the questionnaire, the researchers explained how to complete it and answered students’ questions regarding the questionnaire. A week later, the anthropometric measurements were taken during an ordinary classroom session. Guijarro-Romero, S.; Mayorga-Vega, D.; Viciana, J.; Casado-Robles, C.; Gråstén, A., & Jaakkola, T. (2020). Students’ physical activity intensity and sedentary behaviour by physical self-concept profiles: A latent profile analysis. RICYDE. Revista internacional de ciencias del deporte, 59(16), 85-101. https://doi.org/10.5232/ricyde2020.05907 90 Data analysis First, normal distribution, outliers, and missing values of the study variables were examined. A graphical display showed that the data were approximately normally distributed. No significant outliers were detected based on the standardised values (± 3.0) of the study variables (Tabachnick & Fidell, 2007). The data comprised 16.3% of missing values out of all 2,364 measured values. The Missing Completely at Random (MCAR) test (c2 = 9.05, df = 6, p = .171) indicated no differences between data with and without missing values (Little & Rubin, 2002). Missing values were not imputed, but estimated using full information maximum likelihood, which has been shown to produce unbiased parameter estimates and standard errors under MCAR conditions (Muthén & Asparouhov, 2003). Additionally, descriptive statistics including correlations, means, and standard deviations for the study variables were determined. To answer the first research question of identifying groups of students with homogenous profiles in physical appearance, sport competence, global physical self-concept, and selfesteem, a Latent Profile Analysis (LPA) was implemented. The maximum likelihood ratio (MLR) estimator was used and the maximum number of iterations was 500 (Muthén & Muthén, 2013). A model fit for one to seven cluster solutions were tested using Akaike’s Information Criterion (AIC), Bayesian Information Criterion (BIC), sample-size adjusted BIC (SSA-BIC), and Lo-Mendell-Rubin likelihood ratio test (LMR). Lower values for AIC, BIC, and SSA-BIC indicated a better model fit. In addition, the LMR test was used to compare the estimated model with a model with one class less than the estimated model. A statistically significant p-value indicated that the LMR test supported the retention of the model related to the number clusters. Finally, the estimated models with less than 1% and less than 5% of the cases were analysed. However, only clusters with more than 5% of the participants were considered as adequate, based on the relatively large sample in the current study (Marsh, Lüdtke, Trautwein, & Morin, 2009). After the most suitable cluster solution was determined, a detailed description and statistics for each cluster was provided. For the second research question of investigating whether different physical self-concept profiles differ in their MVPA and sedentary behaviour, a Multivariate Analysis of Variance (MANOVA) including gender and cluster membership as independent variables and MVPA and sedentary time as dependent variables, was conducted. Post-hoc Tukey tests were used to examine the pairwise comparisons of the clusters. Finally, adjusted squared multiple correlations were used to explain the variances in MVPA and sedentary time variables. The MCAR test for missing values and MANOVA models were performed using SPSS Version 22.0 and LPA models using Mplus Version 8.0. Results Table 1 shows means and standard deviations of the main variables for the overall sample, as well as for the boys and for the girls. Generally, students perceived high self-esteem and global physical self-concept, moderate sport competence and physical appearance, and they showed high average scores of MVPA and sedentary behaviour. Correlations demonstrated that all physical self-perceptions were positively associated among each other for the boys and for the girls. Additionally, MVPA was negatively associated with sedentary behaviour in both gender groups. Guijarro-Romero, S.; Mayorga-Vega, D.; Viciana, J.; Casado-Robles, C.; Gråstén, A., & Jaakkola, T. (2020). Students’ physical activity intensity and sedentary behaviour by physical self-concept profiles: A latent profile analysis. RICYDE. Revista internacional de ciencias del deporte, 59(16), 85-101. https://doi.org/10.5232/ricyde2020.05907 91 Table 1. Correlation coefficients for the study variables among boys (upper triangle) and among girls (lower triangle), and descriptive statistics for the overall sample, and for boys and girls Overall Boys Girls 1. 2. 3 4 5 6 n Mean SD n Mean SD n Mean SD 1. Sport competence - .34** .52** .63** -.15 .15 376 4.17 1.22 202 4.50 1.16 174 3.79 1.18 2. Physical appearance .42** - .32** .38** -.07 .00 376 3.92 1.20 202 4.03 1.22 174 3.79 1.17 3. Global physical self-concept .40** .59** - .51** .00 .10 376 4.27 1.28 202 4.48 1.23 174 4.03 1.30 4. Self-esteem .61** .57** .67** - .02 .01 376 4.56 .84 202 4.73 .77 174 4.36 .87 5. Sedentary behaviour -.00 .09 .08 .02 - -.77** 232 82.98 3.78 118 81.70 4.01 114 84.36 2.98 6. MVPA -.04 -.09 -.09 .00 -.80** - 232 6.52 2.19 118 7.37 2.20 114 5.61 1.77 Note. SD = Standard deviation; MVPA = Moderate-to-vigorous physical activity. * p < .05; ** p < .01 Guijarro-Romero, S.; Mayorga-Vega, D.; Viciana, J.; Casado-Robles, C.; Gråstén, A., & Jaakkola, T. (2020). Students’ physical activity intensity and sedentary behaviour by physical self-concept profiles: A latent profile analysis. RICYDE. Revista internacional de ciencias del deporte, 59(16), 85-101. https://doi.org/10.5232/ricyde2020.05907 92 The results of the LPA including the variables of sport competence, physical appearance, global physical self-concept, and self-esteem were examined (Table 2). The AIC, BIC, and SSA-BIC indices decreased, when the number of groups increased, but only marginally after the four-group solution. The p values of the LMR for K versus K-1 classes were also nonsignificant for each higher group solution. For instance, the four-group solution was better than the three-group solution, whereas the five-group solution was not significantly better than the four-group solution. Based on all considerations, a four-group solution was considered as most justifiable. Table 2. AICs, BICs, and sample-size adjusted BICs values for model parameterizations No. Group No. Parameters AIC BIC SSA-BIC pLMR Group sizes LT1% LT5% 1 8 4631 4662 4637 - 0 0 2 13 4252 4303 4262 .001 0 0 3 18 4149 4220 4163 .012 1 1 4 23 4114 4202 4131 .003 1 1 5 28 4113 4223 4135 .344 1 1 6 33 4072 4201 4097 .316 1 1 7 38 4056 4204 4084 .641 1 3 8 43 4055 4223 4087 .186 2 4 Note. AIC = Akaike’s information criterion; BIC = Bayesian information criterion; SSA-BIC = Sample-size adjusted bayesian information criterion; pLMR = Lo-mendell-rubin likelihood ratio test; LT = less than. Means and standard deviations of the study variables in clusters are presented in Table 3. Cluster 1 was labeled as “low sport competence, moderate global physical, self-concept and self-esteem, and high physical appearance” group. This cluster was comprised of 12 girls and 9 boys, nearly 6% of the total sample. Cluster 2 was labeled as “high sport competence, moderate global physical self-concept and self-esteem, and low physical appearance” group. This group represented 43% (73 girls, 87 boys) of the total sample. Cluster 3 was labeled as “moderate sport competence, global physical self-concept, self-esteem, and physical appearance” group. This group comprised 31% (53 girls, 62 boys) of the total sample. Cluster 4 was named as “moderate sport competence and global physical self-concept, high self-esteem, and low physical appearance” group. This profile was 21% (35 girl s, 45 boys) of the entire sample. Table 3. Means and standard deviations (in the parentheses) of the study variables in four clusters Cluster 1 (n = 21) Cluster 2 (n = 160) Cluster 3 (n = 115) Cluster 4 (n = 80) Sport competence 3.97 (1.09) 4.31 (1.21) 4.09 (1.23) 4.04 (1.27) Physical appearance 4.17 (1.19) 3.91 (1.20) 3.95 (1.26) 3.83 (1.21) Global physical selfconcept 4.30 (1.46) 4.31 (1.20) 4.26 (1.39) 4.24 (1.33) Self-esteem 4.47 (.88) 4.53 (.80) 4.58 (.89) 4.61 (.87) Sedentary time 82.50 (3.68) 82.84 (3.79) 83.29 (3.62) 82.98 (4.31) MVPA 6.65 (2.22) 6.69 (2.23) 6.09 (1.82) 6.57 (2.45) Note. MVPA = Moderate-to-vigorous physical activity. Guijarro-Romero, S.; Mayorga-Vega, D.; Viciana, J.; Casado-Robles, C.; Gråstén, A., & Jaakkola, T. (2020). Students’ physical activity intensity and sedentary behaviour by physical self-concept profiles: A latent profile analysis. RICYDE. Revista internacional de ciencias del deporte, 59(16), 85-101. https://doi.org/10.5232/ricyde2020.05907 99 Mayorga-Vega, D.; Martínez-Baena, A., & Viciana, J. (2018). Does school physical education really contribute to accelerometer-measured daily physical activity and non sedentary behaviour in high school students? Journal of Sports Sciences, 36(17), 1913–1922. https://doi.org/10.1080/02640414.2018.1425967 Mears, R. & Jago, R. (2016). Effectiveness of after-school interventions at increasing moderate-to-vigorous physical activity levels in 5to 18-year olds: A systematic review and meta-analysis. British Journal of Sports Medicine, 50(21), 1315–1324. https://doi.org/10.1136/bjsports-2015-094976 Migueles, J. H.; Cadenas-Sanchez, C.; Ekelund, U.; Delisle Nyström, C.; Mora-Gonzalez, J.; Löf, M., … Ortega, F. B. (2017). Accelerometer data collection and processing criteria to assess physical activity and other outcomes: A systematic review and practical considerations. Sports Medicine, 47(9), 1821–1845. https://doi.org/10.1007/s40279-017-0716-0 Moreno-Murcia, J. A.; Hellín, P.; González-Cutre, D., & Martínez-Galindo, C. (2011). Influence of perceived sport competence and body attractiveness on physical activity and other healthy lifestyle habits in adolescents. The Spanish Journal of Psychology, 124(1), 282–292. https://doi.org/10.5209/rev_SJOP.2011.v14.n1.25 Muthén, B. O. & Asparouhov, T. (2003). Modeling interactions between latent and observed continuous variables using maximum-likelihood estimation in Mplus. Mplus Web Notes, 1(6), 1–9. Taking March 12, 2019. From: http://statmodel2.com/download/webnotes/webnote6.pdf Muthén, L. & Muthén, B. (2013). Mplus User’s Guide (6th edition). Los Ángeles, CA: Muthén and Muthén. Nicholls, J. G. (1989). The competitive ethos and democratic education. Cambridge, MA: Harvard University Press. Oliver, M., Badland, H. M.; Schofield, G. M., & Shepherd, J. (2011). Identification of accelerometer nonwear time and sedentary behavior. Research Quarterly for Exercise and Sport, 82(4), 779–783. https://doi.org/10.1080/02701367.2011.10599814 Ortega, F. B.; Konstabel, K.; Pasquali, E.; Ruiz, J. R.; Hurtig-Wennlöf, A.; Mäestu, J.,… Sjöström, M. (2013). Objectively measured physical activity and sedentary time during childhood, adolescence and young adulthood: A cohort study. PLoS ONE, 8(4), e60871. https://doi.org/10.1371/journal.pone.0060871 Owen, M. B.; Curry, W. B.; Kerner, C.; Newson, L., & Fairclough, S. J. (2017). The effectiveness of school-based physical activity interventions for adolescent girls: A systematic review and meta-analysis. Preventive Medicine, 105, 237–249. https://doi.org/10.1016/j.ypmed.2017.09.018 Parrish, A. M.; Okely, A. D.; Stanley, R. M., & Ridgers, N. D. (2013). The effect of school recess interventions on physical activity: A systematic review. Sports Medicine, 43(4), 287–299. https://doi.org/10.1007/s40279-013-0024-2 Guijarro-Romero, S.; Mayorga-Vega, D.; Viciana, J.; Casado-Robles, C.; Gråstén, A., & Jaakkola, T. (2020). Students’ physical activity intensity and sedentary behaviour by physical self-concept profiles: A latent profile analysis. RICYDE. Revista internacional de ciencias del deporte, 59(16), 85-101. https://doi.org/10.5232/ricyde2020.05907 100 Pearson, N.; Haycraft, E.; Johnston, J. P., & Atkin, A. J. (2017). Sedentary behaviour across the primary-secondary school transition: A systematic review. Preventive Medicine, 94, 40–47. https://doi.org/10.1016/j.ypmed.2016.11.010 Poitras, V.; Gray, C.; Borghese, M.; Carson, V.; Chaput, J.; Janssen, I., … Tremblay, M. (2016). Systematic review of the relationships between objectively measured physical activity and health indicators in school-aged children and youth. Applied Physiology, Nutrition, and Metabolism, 41(6), 197–239. https://doi.org/10.1139/apnm-2015-0663 Reddon, H.; Meyre, D., & Cairney, J. (2017). Physical activity and global self-worth in a longitudinal study of children. Medicine and Science in Sports and Exercise, 49(8), 1606–1613. https://doi.org/10.1249/MSS.0000000000001275 Reigal Garrido, R.; Videra García, A.; Parra Flores, J. L., & Ruiz de Mier, R. J. (2012). Actividad físico deportiva, autoconcepto físico y bienestar psicológico en la adolescencia. Retos: Nuevas Perspectivas de Educación Física, Deporte y Recreación, (22), 19–23. Revuelta, L.; Esnaola, I., & Goñi, A. (2016). Relaciones entre el autoconcepto físico y la actividad físico-deportiva adolescente. Revista Internacional de Medicina y Ciencias de la Actividad Física y del Deporte, 16(63), 561–581. Rollo, S.; Gaston, A., & Prapavessis, H. (2016). Cognitive and motivational factors associated with sedentary behavior: A systematic review. AIMS Public Health, 3(4), 956–984. https://doi.org/10.3934/publichealth.2016.4.956 Shavelson, R. J.; Hubner, J. J., & Stanton, G. C. (1976). Self-concept: Validation of construct interpretations. Review of Educational Research, 46(3), 407–441. https://doi.org/10.3102/00346543046003407 Suchert, V.; Hanewinkel, R., & Isensee, B. (2016). Screen time, weight status and the self-concept of physical attractiveness in adolescents. Journal of Adolescence, 48, 11– 17. https://doi.org/10.1016/j.adolescence.2016.01.005 Tabachnick, B. & Fidell, L. (2007). Using multivariate statistics. Boston, MA: Allyn and Bacon. Trost, S. G.; Loprinzi, P. D.; Moore, R., & Pfeiffer, K. A. (2011). Comparison of accelerometer cut points for predicting activity intensity in youth. Medicine and Science in Sports and Exercise, 43(7), 1360–1368. https://doi.org/10.1249/MSS.0b013e318206476e Utesch, T.; Dreiskämper, D.; Naul, R., & Geukes, K. (2018). Understanding physical (in- )activity, overweight, and obesity in childhood: Effects of congruence between physical self-concept and motor competence. Scientific Reports, 8(1), 5908. https://doi.org/10.1038/s41598-018-24139-y Viciana, J.; Mayorga-Vega, D.; Guijarro-Romero, S., & Martínez-Baena, A. (2017a). Effect of two alternated teaching units of invasion team sports on the tactical learning in primary schoolchildren. International Journal of Performance Analysis in Sport, 17(3), 256–270. https://doi.org/10.1080/24748668.2017.1331575 Guijarro-Romero, S.; Mayorga-Vega, D.; Viciana, J.; Casado-Robles, C.; Gråstén, A., & Jaakkola, T. (2020). Students’ physical activity intensity and sedentary behaviour by physical self-concept profiles: A latent profile analysis. RICYDE. Revista internacional de ciencias del deporte, 59(16), 85-101. https://doi.org/10.5232/ricyde2020.05907 101 Viciana, J.; Mayorga-Vega, D., & Martínez-Baena, A. (2016). Moderate-to-vigorous physical activity levels in physical education, school recess, and after-school time: Influence of gender, age, and weight status. Journal of Physical Activity and Health, 13(10), 1117–1123. https://doi.org/10.1123/jpah.2015-0537 Viciana, J.; Mayorga-Vega, D., & Parra-Saldías, M. (2017b). Adolescents’ physical activity levels on physical education and non-physical education days according to gender, age, and weight status. European Physical Education Review, 25(1), 143– 155. https://doi.org/10.1177/1356336X17706683 Viira, R. (2011). Adolescents’ physical self-perception as related to moderate-to-vigorous physical activity: A One-year longitudinal study. Acta Kinesiologiae Universitatis Tartuensis, 17, 199–208. Wang, C. K. J.; Sun, Y.; Liu, W. C.; Yao, J., & Pyun, D. Y. (2015). Latent profile analysis of the Physical Self-Description among Chinese adolescents. Current Psychology, 34(2), 282–293. https://doi.org/10.1007/s12144-014-9257-y Webb, O. J.; Benjamin, C. C.; Gammon, C.; McKee, H. C., & Biddle, S. J. H. (2013). Physical activity, sedentary behaviour and physical self-perceptions in adolescent girls: A mediation analysis. Mental Health and Physical Activity, 6(1), 24–29. https://doi.org/10.1016/j.mhpa.2012.08.005 World Health Organization. (2010). Global recommendation on physical activity for health. Geneva: World Health Organization. World Health Organization, W. (2018). Physical activity. Retrieved March 11, 2019, from: http://www.who.int/news-room/fact-sheets/detail/physical-activity Acknowledgments The authors gratefully acknowledge all the participating students and their parents, without whom the present study could not be carried out. Additionally, the authors acknowledge all the members of the school centre for their enthusiasm and collaboration, especially to the school principal and the physical education teachers. We also thank Aliisa Hatten for the English revision of the manuscript. This work was supported by the Spanish Ministry of Science, Innovation and Universities [FPU15/02387 (Santiago Guijarro-Romero) and FPU16/03314 (Carolina Casado-Robles)].