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A longitudinal assessment of the links between physical activity and physical self-worth in adolescent females a

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Lennart Raudsepp , Inga Neissaar & Merike Kull

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Institute of Sport Pedagogy and Coaching Science, University of Tartu, Tartu, Estonia Published online: 12 Mar 2013.

To cite this article: European Journal of Sport Science (2013): A longitudinal assessment of the links between physical activity and physical self-worth in adolescent females, European Journal of Sport Science, DOI: 10.1080/17461391.2013.775349 To link to this article: http://dx.doi.org/10.1080/17461391.2013.775349

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European Journal of Sport Science, 2013 http://dx.doi.org/10.1080/17461391.2013.775349

ORIGINAL ARTICLE

A longitudinal assessment of the links between physical activity and physical self-worth in adolescent females

LENNART RAUDSEPP, INGA NEISSAAR, & MERIKE KULL

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Institute of Sport Pedagogy and Coaching Science, University of Tartu, Tartu, Estonia

Abstract A longitudinal framework was used to examine the hypotheses of (1) whether physical activity predicts changes in physical self-worth or (2) whether physical self-worth predicts changes in physical activity in adolescent girls. Participants (n 272) completed measures of physical self-worth and participation in physical activities at three different points spanning a twoyear interval. A cross-lagged panel model using structural equation modelling analyses indicated that physical self-worth predicted subsequent physical activity and physical activity in turn predicted subsequent physical self-worth across time. Findings demonstrated a reciprocal relationship between physical self-worth and physical activity during early adolescence. This study supports the use of the reciprocal effects model (REM) in gaining an understanding of the cross-lagged relationships between physical self-worth and participation in physical activities amongst adolescent girls.

Keywords: Physical self-worth, physical activity, reciprocal effects model, adolescent girls

The benefits of regular physical activity in children and youths are well documented (Strong et al., 2005). Physical activity has been shown to assist in youths’ psychological well-being and may assist in their adherence to regular participation in physical activity into adulthood (Shephard, 1995). Despite this, adolescence has been identified as a risk period for physical activity attrition, particularly amongst girls (Kimm et al., 2002). To date, research has indicated that there are multiple reasons why girls are inactive, including lack of time, involvement in other activities, peer and environmental influences, and psychological influences such as low perceived competence and body-related concerns (Biddle, Gorely, & Stensel, 2004). Therefore, to engage girls more effectively, the factors that influence behaviours related to physical activity need to be better understood (Inchley, Kirby, & Currie, 2011). Self-esteem is the evaluative component of selfconcept and relates to the degree to which an individual feels valued by others, experiences success in achieving their aspirations and feels significant and competent (Fox, 2000). Self-esteem processes

are associated with motivated behaviour in physical activity settings (Schmalz, Deane, Birch, & Davison, 2007) and physical self-concept was one of the strongest independent predictors of global self-esteem during young adulthood (Donnellan, Trzesniewski, Conger, & Conger, 2007). In addition, physical self-concept is known to be an important part of self-definition in childhood (Harter, 1999), and research has documented longitudinal relations between physical self-concept and physical activity in adolescents (Crocker, Sabiston, Kowalski, McDonough, & Kowalski, 2006; Inchley et al., 2011; Schmalz et al., 2007). Marsh (1990), largely due to theoretical limitations as well as to shortcomings in statistical techniques for testing models in earlier studies, proposed a ‘reciprocal effects model’ (REM), according to which prior self-concept affects subsequent achievement, and prior achievement affects subsequent selfconcept. A large body of research in support of the REM is based on the academic self-concept and academic achievement in schoolchildren (Valentine, DuBois, & Cooper, 2004), but there have also been

Correspondence: Lennart Raudsepp, Institute of Sport Pedagogy and Coaching Science, University of Tartu, Jakobi 5 Street, Tartu, Estonia 51014, Estonia. E-mail: [email protected] # 2013 European College of Sport Science

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several tests of REM in the physical domain (Marsh, Papaioannou, & Theodorakis, 2006; Schmalz et al., 2007). For example, Marsh et al. (2006) studied the reciprocal effects of physical self-concept and exercise behaviour at the beginning and end of the school year in a large sample of 2786 students at different levels of schooling. When initial exercise behaviour was controlled, physical self-concept significantly predicted subsequent exercise behaviour, and, subsequently, exercise behaviour significantly predicted self-concept. The co-variation between change in physical activity and physical self-perceptions provides support for the contention that the physical self plays an important role in the adoption and maintenance of physical activity (Fox, 2000). Crocker et al. (2006) also suggested that a focus on early adolescent girls may be more appropriate in understanding physical activity behaviour because physical self-perceptions become relatively stable during mid- to late adolescence. During adolescence, there is also a documented maturity-related decrease in physical activity (Kimm et al., 2002; Knowles, Niven, Fawkner, & Henretty, 2009). Girls are also at a higher risk of depressive symptoms, starting in early adolescence (Hyde, Mezulis, & Abramson, 2008), and evidence suggests that engaging in physical activity can help alleviate depression (Craft & Landers, 1998). Therefore, understanding the longitudinal relationship between the physical self-concept and physical activity participation in adolescent girls has important public health ramifications (Crocker et al., 2006). Based on the difficulty in understanding the causal nature of the relationships between physical activity and physical self-concept, the purpose of the present study was to examine the strength of associations among the latter variables longitudinally over a two-year period. Following the REM, we hypothesised that (1) prior physical self-worth would predict subsequent physical activity and (2) prior physical activity would predict subsequent physical self-worth.

Methods Procedures and participants Five schools from the city Tartu (Estonia) were randomly selected, informed regarding the purpose of the study, invited to take part in the study and informed that there would be three waves of data collection. Within those five schools, all sixth grade girls were invited to participate. In the first year (T1), 368 girls (mean age 12.3 years, SD 0.6) participated, representing a range of socioeconomic backgrounds. Approximately 12 months later, the same children were re-contacted and asked to

complete the questionnaires again. A total of 327 (88.8% of the original sample) participated at T2. T3 measurement was carried out approximately 24 months later, and these 272 girls represent the basis for current study. The questionnaires were administered during regular school hours. To guarantee the quality of the data collected, a trained research assistant administered the questionnaires to small groups of about six students. Students were encouraged to ask for help if they did not understand a question. Parents of all participants provided written, informed consent and all of the adolescents provided their written assent. All procedures were approved by the University’s Ethics Committee. Permission to conduct the study was also obtained from the schools’ principals. Measures Physical self-worth. Six items from Estonian adaption of the Children’s Physical Self-Perception Profile (CY-PSPP, Whitehead, 1995) were administered to assess the global physical self-worth. The item score ranges from 1 (low) to 4 (high) on a structured alternative scale, offering two opposing statements. The participant was first asked which of two statements best described themselves followed by providing a rating of whether the statement was a really true description or only a somewhat true description. Internal consistency (Cronbach’s a) was 0.75 at T1, 0.78 at T2 and 0.77 at T3. Physical activity. Physical activity was assessed using the 3-Day Physical Activity Recall (3DPAR) (Motl, Dishman, Dowda, & Pate, 2004). The 3DPAR required participants to recall physical activity behaviour from three previous days of the week (first Tuesday, then Monday, then Sunday); the instrument was always completed on Wednesday. Those three days were selected to capture physical activity on one weekend day and two weekdays. To improve the accuracy of physical activity recall, the three days were segmented into 34 30-minute blocks, beginning at 7.00 a.m. and continuing through to 12.00 a.m. To further aid recall, the 34 30-minute blocks were grouped into broader time periods (i.e. before school, during school, lunchtime, after school, supper time and evening). The 3DPAR included a list of 55 commonly performed activities grouped into broad categories (i.e. eating, work, after school/ spare time/hobbies, transportation, sleeping/bathing, school, physical activities and sports) to improve activity recall. For each block of each day, participants entered the main activity in which they participated during each 30-minute time period. Participants also rated the relative intensity of the

Links between physical activity and physical self-worth

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designated activity as light, moderate, hard or very hard. The validity of the 3DPAR as a measure of usual activity has been established based on correlations with the objective measures (CSA 7164 accelerometer) of physical activity. Self-reported total METs, 30-minute blocks of moderate and vigorous physical activity, and 30-minute blocks of vigorous physical activity were all significantly correlated with analogous CSA variables (Pate, Ross, Dowda, Trost, & Sirard, 2003). In addition, Stanley, Boshoff, and Dollman (2007) found significant correlations (0.490.57) between 3DPAR intensity and accelerometer data in 1214-year-old girls. To help participants select the correct intensity level, the instrument provides pictorial representations of the four levels of relative intensity. Data analyses We applied maximum likelihood estimation using structural equation modelling (SEM) with the AMOS 6.0 (Arbuckle, 2005). We evaluated structural relationships among latent variables using a crosslagged panel design (see: Martens & Haase, 2006). In SEM, latent variables are hypothetical factors measured by means of multiple observed indicators. In the present study, physical self-worth at the three time points constituting our latent variables and the three days total physical activity was assessed as an observed variable. The latent variable of physical selfworth was represented by the six observed indicators (i.e. the six individual items) at each time point. Martens and Haase (2006) outlined a process for testing the fit of a baseline model with only autoregressive effects (i.e. no cross-lagged pathways) and then comparing this against alternative models. These include (1) a model with autoregressive effects and subscale of physical self-worth predicting subsequent physical activity, (2) a model with autoregressive effects and physical activity predicting subsequent physical self-worth and (3) a fully crosslagged model with autoregressive effects and both cross-lagged pathways. Given that alternative models are nested within the baseline model, the chi-square change statistic can be used to compare the fit of each model before the parameters of the best-fitting model are interpreted (Martens & Haase, 2006). Model fit was assessed using a variety of fit measures, including both absolute and incremental fit indices as recommended by Hu and Bentler (1999). Indices used to assess the goodness of fit included the TuckerLewis index (TLI), the incremental fit index (IFI), the comparative fit index (CFI) and the root mean square error of approximation (RMSEA), in addition to the Akaike information criterion (AIC). The AIC quantifies the relative goodness of fit, examining the complexity of the

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model together with its goodness of fit to the sample data to produce a balanced measure. The preferred model is that with the lowest AIC value. As for the other measures, to demonstrate acceptable model fit, the TLI, IFI and CFI should be close to 1.0, although cut-off values in the range of 0.95 have been proposed (see Hu & Bentler, 1999). Values in the 0.95 range would indicate that most of the co-variation in the data is explained by the model. Kline (2005) suggests that RMSEA values less than 0.05 are indicative of a close fit and that values up to 0.08 represent reasonable errors of approximation. Results Descriptive statistics Means and standard deviations for physical activity and physical self-worth are presented in Table I. A repeated measures analysis of variance, with repeated contrasts between Time 1 to Time 2 and Time 2 to Time 3, indicated that there was a significant overall difference in the 3DPAR scores, F(2, 270) 54.72, pB0.01, with a significant change recorded between Time 1 and Time 2, F(1, 271) 32.84, p B0.01, and Time 2 and Time 3, F(1, 271) 21.77, p B0.01. There was a significant overall difference in the physical self-worth scores, F (2, 270) 35.15, pB0.01, with a significant change recorded between Time 1 and Time 2, F (1, 271) 23.17, p B0.01, and Time 2 and Time 3, F(1, 271) 19.25, p B0.01. Results showed a significant time effect for physical activity and physical self-worth (h2 0.27 for physical activity and h2  0.35 for physical self-worth respectively, pB0.01) across the measurements. The students who participated at the three points in time did not differ from those who dropped out in terms of physical activity and physical self-worth (both p’s 0.05). Cross-lagged panel analysis As mentioned previously, we tested four alternative models in the main cross-lagged analysis, including (1) a baseline autoregressive model, (2) a model with autoregressive effects and pathways from physical self-worth to physical activity, (3) a model with autoregressive effects and pathways from physical activity to physical self-worth, and (4) a fully crosslagged model. As recommended in the literature (Kline, 2005), we allowed within-time residuals associated with endogenous variables to co-vary, as well as error terms for corresponding manifest variables measured at different times. Preliminary data screening indicated that several measures were nonnormally distributed, and Mardia’s normalised multivariate kurtosis statistics also indicated multivariate

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Table I. Descriptive statistics for physical activity and physical self-worth (n 272). Time 1 M

Time 2

SD

M

Time 3

SD

M

SD

3DPA (METs day 1) 68.53 7.95 62.67 7.53 58.32 7.37 MPA (blocks day 1) 4.13 2.47 3.47 2.23 3.11 2.15 VPA (blocks day 1) 2.06 1.43 1.46 1.23 1.16 1.04 Physical self-worth 2.82 0.85 2.75 0.82 2.64 0.71

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*p B0.05. M, mean; SD, standard deviation; 3DPA, 3-day physical activity; MPA, moderate physical activity; VPA, vigorous physical activity.

non-normality within the data. Given that the maximum likelihood estimation method is based on assumptions of multivariate normality, we calculated the Bollen-Stine’s p to compensate for biased probability estimates. Fit indices for each model are presented in Table II. As can be seen from Table II, the autoregressive model showed a satisfactory fit to the data, as reflected in TLI, IFI, CFI and RMSEA values, which are all within the desired range. The PA 0 PSW model also showed a reasonable fit with the data, although this model did not fit the data significantly better (Dx2(2) 3.29, p 0.05) than the baseline model. The PSW 0 PA model was tested next and also fit the data well, as reflected in fit indices. Furthermore, this model provided a significantly better fit to the data than did the autoregressive model, Dx2(2) 13.72, p B0.01. Finally, the fully cross-lagged model was found to provide a good fit with the data and fit better than the other models. Given that the fully cross-lagged model demonstrated the lowest chi-square value, this was compared with the PSW 0 PA model. Results showed that the fully cross-lagged model was a significantly better fit with the data than the PSW 0 PA model, Dx2(2) 8.38, p B 0.01. Standardised parameter estimates are shown in Figure 1. Unsurprisingly, the largest effect on T2 physical self-worth is T1 physical self-worth and the largest effect on T3 physical self-worth is T2 physical Table II. Model fit statistics (n  272). Model Stability PA 0 PSW PSW 0 PA Crosslaggeda

x2

df

TLI

IFI

CFI

RMSEA

AIC

183.58 102 0.958 0.965 0.964 182.94 100 0.959 0.966 0.965

0.056 0.055

178.31 177.85

177.24 100 0.968 0.974 0.972

0.051

176.06

173.88

0.046

174.51

98 0.976 0.979 0.980

a A model which best fits the data. TLI, TuckerLewis index; IFI, incremental fit index; CFI, comparative fit index; RMSEA, root mean square error of approximation; AIC, Akaike information criterion.

self-worth. Beta coefficients for the autoregressive pathways of physical activity were also significant. Of greater interest, however, are the cross paths. Consistent with our study hypotheses, T1 physical selfworth has a significant effect on T2 physical activity and T2 physical self-worth has a significant effect on T3 physical activity. In addition, two paths from prior physical activity to subsequent physical selfworth were also significant. Results supported, however, a stronger predictive relationship from physical self-worth to physical activity than from physical activity to physical self-worth. Discussion An extensive body of research supports the REM of relations between academic self-concept and achievement in academic settings (Valentine et al., 2004). The current findings support the REM in the context of physical activity: higher levels of prior physical self-worth led to higher subsequent levels of physical activity, and higher levels of prior physical activity led to higher levels of subsequent physical self-worth in adolescent girls. Although the REM was supported by the present findings, it was interesting that the lagged effect of physical selfworth on physical activity was stronger than the lagged effect of physical activity on physical selfworth. Results of this longitudinal study, therefore, provide more definitive evidence than previous cross-sectional research of the psychological benefits of physical activity (Larson, 2000). Consistent with several studies that have reported a decline in physical activity during adolescence (Kimm et al., 2002; Knowles et al., 2009), there was a significant decrease in the overall physical activity as well as in moderate and vigorous physical activity over the 24 months. A recent review reported that, on average, the adolescents physical activity declines 7% per year (Dumith, Gigante, Domingues, & Kohl, 2011). In girls, surprisingly, this drop in physical activity was higher in early adolescence compared to later ages (Dumith et al., 2011). Our results generally confirm these findings  a large initial reduction in total physical activity from baseline to interim (8.6%) was followed by a smaller reduction in physical activity from interim to followup measurement (6.9%). For moderate and vigorous intensity physical activity categories the drop in mean scores between baseline and interim measurements were even greater. There are numerous determinants of change in adolescents’ physical activity (Craggs, Corder, van Sluijs, & Griffin, 2011). Identifying these determinants or potential causal factors of change in physical activity should strengthen the evidence base to inform the development and targeting of effective interventions (Corder, Ogilvie, & van Sluijs, 2009).

Links between physical activity and physical self-worth 1

2

3

4

PSW T1

5

6

0.61**

0.39*

0.21*

PA T1

5

PSW T2

0.24*

0.15*

0.52**

0.49**

PA T2

PSW T3

0.13*

0.47**

PA T3

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Figure 1. Standardised parameter estimates for the fully cross-lagged model (n272). Note: Straight lines depict standardised beta weights and the curved line between latent variable and observed variable is the correlation. Physical self-worth was inferred from six observed indicators (omitted for visual clarity for T2 and T3). *pB 0.05, **p B 0.01.

Recently, Craggs et al. (2011) demonstrated that higher levels of previous physical activity and selfefficacy resulted in smaller declines in physical activity in the 1013-year-olds. Other factors which were longitudinally related to physical activity decline during early adolescence were perceived behavioural control, physical self-perceptions, parental role modelling, parental activity and barriers for physical activity (Craggs et al., 2011; Inchley et al., 2011). The only determinant of change in physical activity in current study was physical self-worth which demonstrated a reciprocal relationship with physical activity over two years. However, future research should be directed towards comprehensive assessments of determinants and mediators of change in physical activity during late childhood and adolescence. Although the critical path coefficients between physical self-worth and physical activity were statistically significant, these effects may seem to be of moderate size. However, beta coefficients for crosslagged effects in the range of 0.100.15 are common in real-world, non-experimental longitudinal research on personal characteristics and can be considered meaningful (Roberts, Caspi, & Moffitt, 2003). When interpreting such cross-lagged effects, it is important to bear in mind that changes in physical self-concept and physical activity are, of course, determined to multiply (Spence, McGannon, & Poon, 2005) and that cross-lagged effects are potentially cumulative over time. Partially contrary to the present findings, Schmalz et al. (2007) found that global self-esteem of adolescent girls did not predict participation in physical activity two years later. However, physical activity at the ages of 9 and 11 predicted higher self-esteem at the ages of 11 and 13. It seems that stronger effects of self-esteem on physical activity amongst adults (Spence et al., 2005)

and adolescents (Inchley et al., 2011) may be observed at domain-specific levels. The strengths of this study include the use of a longitudinal design and the public health implications of the findings. The REM implies that physical self-concept and physical activity are reciprocally related and mutually reinforcing. Improved physical self-worth will lead to a higher level of physical activity, and a higher level of physical activity will lead to higher physical self-worth. Hence, if physical education teachers and health professionals enhance adolescents’ physical self-concepts without promoting physical activity, then the gains in self-concept are likely to be smaller and less lasting. Furthermore, if health professionals promote adolescents’ participation in physical activity without also fostering youth self-beliefs in their physical capabilities, then the exercise gains are also likely to be smaller and less lasting (Marsh et al., 2006). Although the results of the present study are encouraging, some caution should be exercised when interpreting the results. Firstly, the present study assessed the cross-lagged relationships between physical self-worth and physical activity only on three occasions. A greater number of data points and longer time intervals should be considered for change analysis. Secondly, previous studies showed that self-reported physical activity measurements underestimate differences between groups and that their reliability and validity, particularly amongst children and adolescents, are questionable (Motl et al., 2004). The use of objective measures such as pedometers and accelerometers, which are not influenced by memory and recall bias, are suggested for the pediatric population. Thirdly, given the age period during which data were collected, maturational status is potentially an important issue and may influence both physical self-worth and physical

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activity behaviour (Knowles et al., 2009). Validated measures of pubertal status should be included in any future research. Furthermore, a longitudinal relationship between physical self-worth and physical activity was assessed only on a domain but not on the subdomain (sports competence, physical condition, body image and physical strength) level. Therefore, we suggest that the cross-lagged effect of physical self-worth and physical activity would have been even greater on subdomain level of physical selfworth considered in the present study. Finally, the data is not representative on a national level, and the sample, although randomly selected, was only from one Estonian city. Therefore, the findings have limited generalisability and causal statements are limited. Additional research should be conducted using an experimental study design (Schneider, Dunton, & Cooper, 2008). In conclusion, the results of the present investigation have significant implications for the importance placed on physical self-concept as a means of facilitating girls’ physical activity, as well as being an important outcome variable. According to REM, healthcare professionals should strive to improve simultaneously both physical self-worth and participation in physical activity amongst adolescent girls. Future studies should examine the causal ordering of physical self-concept and participation in physical activity in the different age and sex groups using objective measures of physical activity, controlling potential mediators and employing experimental research design. References Arbuckle, J. L. (2005). AMOS 6.0: A structural equation modeling software. Spring House, PA: AMOS Development Corporation. Biddle, S. J. H., Gorely, T., & Stensel, D. J. (2004). Healthenhancing physical activity and sedentary behaviour in children and adolescents. Journal of Sports Sciences, 22(8), 679701. doi:10.1080/02640410410001712412 Corder, K., Ogilvie, D., & van Sluijs, E. M. (2009). Invited commentary: Physical activity over the life course  Whose behavior changes, when and why? American Journal of Epidemiology, 170(9), 10781081. doi:10.1093/aje/kwp273 Craft, L. L., & Landers, D. M. (1998). The effect of exercise on clinical depression and depression resulting from mental illness: A meta-analysis. Journal of Sport and Exercise Psychology, 20, 339357. Craggs, C., Corder, K., van Sluijs, E. M. F., & Griffin, S. J. (2011). Determinants of change in physical activity in children and adolescents. A systematic review. American Journal of Preventive Medicine, 40(6), 645658. doi:10.1016/j.amepre. 2011.02.025 Crocker, P. R. E., Sabiston, C. M., Kowalski, K. C., McDonough, M. H., & Kowalski, N. (2006). Longitudinal assessment of the relationship between physical self-concept and healthrelated behavior and emotion in adolescent girls. Journal of Applied Sport Psychology, 18(3), 185200. doi:10.1080/104132 00600830257

Donnellan, M. B., Trzesniewski, K. H., Conger, K. J., & Conger, R. D. (2007). A three-way longitudinal study of self-evaluations during young adulthood. Journal of Research in Personality, 41(2), 453472. doi:10.1016/j.jrp.2006.06.004 Dumith, S. C., Gigante, D. P., Domingues, M. R., & Kohl, H. W. (2011). Physical activity change during adolescence: A systematic review and a pooled analysis. International Journal of Epidemiology, 40(3), 685698. doi:10.1093/ije/dyq272 Fox, K. R. (2000). Self-esteem, self-perceptions, and exercise. International Journal of Sport Psychology, 31, 228240. Harter, S. (1999). The construction of self: A developmental perspective. New York, NY: Guilford Press. Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 155. doi:10.1080/10705519909540118 Hyde, J. S., Mezulis, A. H., & Abramson, L. Y. (2008). The ABCs of depression: Integrating affective, biological, and cognitive models to explain the emergence of the gender difference in depression. Psychological Review, 115(2), 291313. doi:10.1037/0033-295X.115.2.291 Inchley, J., Kirby, J., & Currie, C. (2011). Longitudinal changes in physical self-perceptions and associations with physical activity during adolescence. Pediatric Exercise Science, 23, 237249. Kimm, S. Y. S., Glynn, N. W., Kriska, A. M., Barton, B. A., Kronsberg, S. S., Daniels, S. R., . . . Liu, K. (2002). Decline in physical activity in black girls and white girls during adolescence. New England Journal of Medicine, 347(10), 709715. doi:10.1056/NEJMoa003277 Kline, R. (2005). Principles and practice of structural equation modeling (2nd ed.). New York, NY: Guilford Press. Knowles, A.-M., Niven, A. G., Fawkner, S. G., & Henretty, J. M. (2009). A longitudinal examination of the influence of maturation on physical self-perceptions and the relationship with physical activity in early adolescent girls. Journal of Adolescence, 32(3), 555566. doi:10.1016/j.adolescence.2008.06.001 Larson, R. W. (2000). Toward a psychology of positive youth development. American Psychologist, 55(1), 170183. doi:10. 1037/0003-066X.55.1.170 Marsh, H. W. (1990). The causal ordering of academic selfconcept and academic achievement: A multiwave, longitudinal panel analysis. Journal of Educational Psychology, 82(4), 646 656. doi:10.1037/0022-0663.82.4.646 Marsh, H. W., Papaioannou, A., & Theodorakis, Y. (2006). Causal ordering of physical self-concept and exercise behavior: Reciprocal effects model and the influence of physical education teachers. Health Psychology, 25(3), 316328. doi:10.1037/ 0278-6133.25.3.316 Martens, M. P., & Haase, R. F. (2006). Advanced applications of structural equation modeling in counseling psychology research. The Counseling Psychologist, 34(6), 878911. doi:10.1177/0011000005283395 Motl, R. W., Dishman, R. K., Dowda, M., & Pate, R. R. (2004). Factorial validity and invariance of a self-report measure of physical activity among adolescent girls. Research Quarterly for Exercise and Sport, 75, 259271. Pate, R. R., Ross, R., Dowda, M., Trost, S. G., & Sirard, J. R. (2003). Validation of a 3-day physical activity recall instrument in female youth. Pediatric Exercise Science, 15, 257265. Roberts, B. W., Caspi, A., & Moffitt, T. E. (2003). Work experiences and personality development in young adulthood. Journal of Personality and Social Psychology, 84(3), 582593. doi:10.1037/0022-3514.84.3.582 Schmalz, D. L., Deane, G. D., Birch, L. L., & Davison, K. K. (2007). A longitudinal assessment of the links between physical activity and self-esteem in early adolescent non-hispanic females. Journal of Adolescent Health, 41(6), 559565. doi:10.1016/j.jadohealth.2007.07.001

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Downloaded by [Universite De Paris 1] at 00:07 19 August 2013

Schneider, M., Dunton, G. F., & Cooper, D. M. (2008). Physical activity and physical self-concept among sedentary adolescent females: An intervention study. Psychology of Sport and Exercise, 9(1), 114. doi:10.1016/j.psychsport.2007.01.003 Shephard, R. J. (1995). Physical activity, health, and well-being at different life stages. Research Quarterly for Exercise and Sport, 66, 298302. Spence, J. C., McGannon, K. R., & Poon, P. (2005). The effects of exercise on global selfesteem: A quantitative review. Journal of Sport and Exercise Psychology, 27, 311334. Stanley, R., Boshoff, K., & Dollman, J. (2007). The concurrent validity of the 3-day physical activity recall questionnaire administered to female adolescents aged 1214 years. Australian Occupational Therapy Journal, 54, 294302.

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Strong, W. B., Malina, R. M., Blimkie, C. J. R., Daniels, S. R., Dishman, R. K., Gutin, B., Hergenroeder, A. C., . . . Trudeau, F. (2005). Evidence based physical activity for school-aged youth. Journal of Pediatrics, 146(6), 732737. doi:10.1016/ j.jpeds.2005.01.055 Valentine, J. C., DuBois, D. L., & Cooper, H. (2004). The relations between self-beliefs and academic achievement: A systematic review. Educational Psychology, 39(2), 111133. doi:10.1207/s15326985ep3902_3 Whitehead, J. R. (1995). A study of children’s physical selfperceptions using an adapted physical self-perceptions profile questionnaire. Pediatric Exercise Science, 7, 132151.

A longitudinal assessment of the links between physical activity and physical self-worth in adolescent females.

A longitudinal framework was used to examine the hypotheses of (1) whether physical activity predicts changes in physical self-worth or (2) whether ph...
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