Next Article in Journal
Using Disaster Outcomes to Validate Components of Social Vulnerability to Floods: Flood Deaths and Property Damage across the USA
Next Article in Special Issue
The Effects of Team-Game-Tournaments Application towards Learning Motivation and Motor Skills in College Physical Education
Previous Article in Journal
Urban Microclimate Canopy: Design, Manufacture, Installation, and Growth Simulation of a Living Architecture Prototype
Previous Article in Special Issue
Factors Used to Make Appropriate Decisions in Youth Categories in Volleyball
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

High School Adolescents’ Physical Activity and Physical Fitness: A 3 × 2 Achievement Goal Approach

1
School of Physical Education, Shanghai University, Shanghai 200444, China
2
Department of Kinesiology, Health Promotion and Recreation, University of North Texas, Denton, TX 76203, USA
3
School of Leisure Sport, Shanghai University of Sport, Shanghai 200438, China
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(15), 6005; https://doi.org/10.3390/su12156005
Received: 21 June 2020 / Revised: 18 July 2020 / Accepted: 20 July 2020 / Published: 27 July 2020

Abstract

:
Previous research evidence showed deficient physical activity (PA) and physical fitness (PF) performance levels among high school students. Personal goal orientations motivate their behavior; therefore, it is essential to discover high school students’ goal orientations in PA and PF. Guided by the latest 3 × 2 achievement goal model, we examined the influence of six goal orientations on PA and PF in high school students. A total of 792 high school students in China (54.5% girls; Mage = 16.93 ± 0.82) completed validated measurements assessing 3 × 2 goal orientations for PA and PF. Stepwise multiple regression analyses were used to analyze whether 3 × 2 achievement goal orientations significantly influenced the study variables. Other-approach, self-approach, and task-avoidance goals significantly predicted PA, and the 50-meter dash was predicted by other-approach and self-avoidance goals. The self-approach goal was the only significant predictor of the standing long jump. In conclusion, fostering self- and other-approach-oriented environments with developmentally appropriate content in physical education may have implications for enhancing high school students’ PA and PF.

1. Introduction

The prevalence of adolescent obesity has increased dramatically across the globe including the United States and China [1,2]. The number of obese youth in China has tripled over the last three decades and is continuing to increase steadily [3,4]. Obesity causes adverse health effects, including premature death [5], high blood pressure and cholesterol levels [6], cardiovascular disease [7], depression [8], and low self-esteem [9]. Regular physical activity (PA) can be beneficial for long-term physical health and physical fitness (PF), and may prevent adolescent obesity [10,11].
The World Health Organization (WHO)’s PA guidelines recommend that school-aged youth (i.e., 5–17 years old) need to spend at least one hour of moderate-to-vigorous physical activity (MVPA) daily to achieve health benefits and decrease the risk of obesity [12]. Nevertheless, a Chinese national study demonstrated that only a few adolescents (9% boys and 2% girls; aged 9–17 years old) met the recommended daily MVPA, objectively measured using accelerometers [13]. A more recent Chinese national study found that only 24.4% of the 32,563 high school adolescents met the recommended MVPA levels of 60 min per day [14]. In addition, Chinese high school students had a high prevalence of sedentary time [13,15]. Intervention studies demonstrated that structured PA lessons may lead to higher PA [16,17]. As empirical evidence has consistently shown that student motivation is strongly linked to engagement in PA and PF [18,19,20,21,22], identifying Chinese high school students’ motivational factors for PA and PF is critical for their health promotion.
Achievement goal theory posits that individuals’ achievement goal orientations affect their behaviors and achievement [23]. In the past four decades, researchers have theoretically and empirically examined and developed achievement goal orientations to understand students’ motivation process in both educational and PA contexts [24,25,26]. Several researchers have developed and extended achievement goal theory with multiple goals. In the 1980s, achievement goal theory commenced as a dichotomous model involving mastery (i.e., task) and performance (i.e., ego) goal orientations [27,28]. Mastery goal orientation focuses on goals improving one’s competence such as self-development or skill development. In contrast, performance goal orientation emphasizes goals demonstrating one’s ability to respond to external indicators or outperforming others [23]. In addition, competence is combined with dimensions of valence, based on the distinction between approach (perceiving feasibility) and avoidance (perceiving unfeasibility [29]). Since the inception of achievement goals, theorists have developed trichotomous (mastery approach, performance approach, and performance avoidance [29]), 2 × 2 (mastery approach and avoidance, performance approach and avoidance [30]), and 3 × 2 models (task-approach and avoidance, self-approach and avoidance, other-approach and avoidance [31]).
The latest 3 × 2 achievement goal model [31] elucidates individuals’ goals with six goal orientations, including three dimensions—task (improving one’s own task), self (improving individuals’ performance by comparing their own performance over time), and other (comparing one’s own performance with others)—that are each split into two valences (i.e., approach and avoidance). For instance, in judo, participants’ achievement goals can indicate the task-approach (e.g., “quickly grip the opponent’s arms”), task-avoidance (e.g., “do not grip the opponent’s arms too slowly”), self-approach (e.g., “move faster toward opponents than I usually move”), self-avoidance (e.g., “do not move more slowly toward opponents than I usually move”), other-approach (e.g., “outperform my opponents”), and other-avoidance (e.g., “avoid embarrassment or defeat from my opponents”). A previous study using 3 × 2 achievement goal orientations showed that task-approach goals are positively linked to perceived benefits of engagement in recreational sport, whereas other-approach goals were not significantly associated with the study outcome [32]. Another study indicated that task-approach and other-approach goals were positively related to perceived competence, but task-approach and self-approach goals were positively linked to intrinsic interest in sport [33].
Previous studies applied the 2 × 2 achievement goal model to examine adolescents’ PA inside and outside of physical education (PE [34,35,36,37]). Few studies used the latest 3 × 2 achievement goal model to explain students’ achievement goal orientations in PA and sport, predominantly among college students [32,33,38], but not in K–12 PE settings [36]. As establishing behavioral patterns in adolescence is significant for increasing long-term health benefits and preventing chronic disease risk in young adulthood [39], investigating high school students’ achievement goal orientations in PA and PF is necessary for developing effective PA interventions in PE settings [40]. Expanding on the current knowledge of achievement goal orientations in high school students using the latest 3 × 2 achievement goal model, we aimed to investigate the associations of six goal orientations with PA and PF among high school students in PE settings. We hypothesized that task-approach and self-approach goals have positive effects on PA and PF outcomes, whereas task-avoidance and self-avoidance negatively affect the study variables. In addition, other-approach and other-avoidance goals have negative influences on high school students’ PA and PF. The research findings of this study add to the literature on specific adolescents’ goal orientations on PA and PF, which can be useful for PE teachers and practitioners in promoting student engagement in various physical activities.

2. Methods

2.1. Participants

Participants were 792 adolescents (54.5% girls; Mage = 16.93 ± 0.82; Mheight = 168.96 ± 10.45; Mweight = 60.24 ± 14.04) from four public high schools at the same school district in the Baoshan District of Shanghai, China. PA surroundings, such as facilities, equipment, size of place, and supplies, in the participating schools were similar. Initially, we randomly selected 860 10th and 11th grade students at convenient schools with good connections to recruit the participants (12 classes total) [41]. However, 68 students’ data were excluded due to incomplete and/or missing assessments (i.e., PA, PF performance). Thus, the participation rate was appropriately 92% in the present study. Students voluntarily participated in the study without rewards or incentives.

2.2. Measures

2.2.1. Achievement Goal Orientations

The 3 × 2 Achievement Goal Questionnaire (3 × 2 AGQ) [31] was employed to assess participants’ achievement goal orientation. The questionnaire includes a total of 18 items, with three items representing each of the six achievement goal orientations: task-approach, self-approach, other-approach, task-avoidance, self-avoidance, and other-avoidance. The 3 × 2 AGQ was initially developed to investigate undergraduate students’ goal orientations toward academic achievements in a school context; thus, we revised it for applicability to the PE domain for the purpose of this study. An example of a question identifying a task-approach goal is, “In PE, my goal is to perform well.” Participants rated a 7-point Likert scale ranging from not true of me (1) to extremely true of me (7). By employing structural equation modeling (SEM) in SPSS AMOS 25 (Arbuckle, 2017 [42]), we assessed the convergent validity of the 3 × 2 AGQ to examine the degree of confidence if the shared indicators were accurate indicators of latent variables. The average variance extracted (AVE) values ranged from 0.73 to 0.89, and the composite reliability (CR) values ranged from 0.89 to 0.96, demonstrating sufficient reliability and validity [43].

2.2.2. Physical Activity

Students’ PA levels were measured using the 7-day recall Physical Activity Questionnaire for Older Adolescents (PAQ-A) [44], assessing participation in various physical activities during spare time, PE, lunch break, after school, evening, and weekends. The PAQ-A includes six items with a 5-point Likert scale from low (1) to high (5); the mean of sum scores is calculated. High scores indicate a high level of general PA. The PAQ-A demonstrated sufficient test-retest reliability of general PA levels among adolescents (intraclass correlation coefficient [ICC] = 0.71) [45], and the scale showed relatively high in the internal reliability coefficient among Chinese adolescents in the current study (Cronbach’s α = 0.79).

2.2.3. Physical Fitness

Students’ PF performances were evaluated using the 50-meter dash and standing long jump in the present study [46]. Participants’ running speed and agility were assessed using the 50-meter dash. The students were required to run as fast as possible between two lines 50 meters apart; they did this twice, and the best performance was recorded. The standing long jump was measured to evaluate the participants’ power, which is the ability to exert muscle force quickly. The students were required to jump horizontally, as far as possible, using a two-footed takeoff and landing. They did this twice, and the best test trial was used in this study. Both skill-related PF tests showed acceptable validity and reliability among adolescents in a previous research [46].

2.3. Procedures

This cross-sectional research was undertaken in the spring 2017 semester. The study was approved by the university’s institutional review board based on the Declaration of Helsinki (Project identification code: SHU-2017-00145). The researchers met with the participating school principals and PE teachers, who permitted and supported the study’s data collection. All participants were offered written informed consent and children’s assent forms; those participants who turned in the consent forms received a detailed explanation of the study’s purpose, the process of data collection, potential benefits and risks, and withdrawal rights. The students were also informed that all of their answers would remain anonymous and confidential to encourage them to answer truthfully. Three bilingual translators translated all the survey items from English to Chinese and then re-translated them from Chinese to English to enhance the validity of the study measures used in this study. The students spent approximately 20–30 min completing all surveys during regularly scheduled PE classes. The graduate research assistants provided the participants, if requested, with an additional guide to ensure students’ understanding of the questions in the survey. The PE teachers in the participating schools administered the PF tests (i.e., 50-meter dash and standing long jump). The trained research assistants visited each school and observed the fitness tests to ensure that the procedures complied and the testing were reliable.

2.4. Data Analysis

Initially, the raw data of all items was screened for accuracy, missing data, normality, and outliers. Three steps were taken using the statistics program SPSS version 25.0 for Mac to analyze the final data in this study. First, confirmatory factor analysis using SEM was carried out to explore the validity and reliability of the 3 × 2 AGQ. Second, Cronbach’s α coefficients and Pearson product–moment correlations were calculated to investigate the internal consistencies of the measures and bivariate correlations among the study variables. Third, three stepwise multiple regression analyses were applied to investigate the predictive strengths of six goal orientations on PA and PF (50-meter dash and standing long jump) among high school students.

3. Results

3.1. Correlation Analysis

The Pearson product–moment correlation results revealed that three approach goal orientations (task, self, and other) were statistically significantly associated with PA, 50-meter dash, and standing long jump (rs from −0.10 to 0.27, all p < 0.01). Three avoidance goal orientations (task, self, and other) were also weakly connected with PA (rs ranged from 0.10 to 0.13, all p < 0.01), but not with PF performance (50-meter dash and standing long jump) (Table 1). In addition, PA was negatively related to 50-meter dash, but was positively associated with standing long jump.

3.2. Stepwise Multiple Regression

The predictive function of PA and PF performance was derived by three stepwise regression analyses with six independent variables (3 × 2 achievement goals). The results indicated that other-approach goals (β = 0.19), self-approach goals (β = 0.18), and task-avoidance goals (β = −0.09) significantly predicted the students’ PA, F (3, 788) = 26.96, p < 0.001, R2 = 0.09. Other-approach goals (β = −0.19) and self-avoidance goals (β = 0.10) were significant predictors of the 50-meter dash, F (2, 789) = 8.42, p < 0.001, R2 = 0.03. The self-approach goal (β = 0.14) was the only predictor for the standing long jump, F (1, 790) = 12.39, p < 0.001, R2 = 0.02 (Table 2).

4. Discussion

Guided by the latest 3 × 2 achievement goal model, the purpose of this study was to understand the roles of the six goal orientations on PA and PF among Chinese high school students. This study was the first attempt to examine the influence of 3 × 2 achievement goal orientations on high school students’ PA and PF using the latest 3 × 2 achievement goal model as a framework. Previous studies predominantly focused on examining PA using 2 × 2 achievement goal constructs in adolescents [34,47] or using 3 × 2 achievement goal constructs in college students [32,38]. Examining clear distinctiveness of various achievement goals using the up-to-date 3 × 2 achievement goal model in adolescents was needed to add to the literature on the effects of detailed 3 × 2 goal orientations on PA and PF among adolescents. [31,48]. Therefore, the broad scope of the potential advantages from this study may provide insights to highlight the importance of goal orientations and for developing effective PA interventions to improve high school students’ PA and PF in school settings.
Stepwise multiple regression analysis revealed that task-avoidance, self-approach, and other-approach goal orientations were significant predictors of PA. These findings are partially consistent or inconsistent with results from previous studies about the relationship between achievement goals and PA. The other-approach goal was a significant predictor of Chinese adolescents’ PA. The finding is consistent with empirical studies suggesting a positive association between a performance-approach goal and PA among college students using the 2 × 2 achievement goal framework [49]. Lochbaum and colleagues (2013) revealed that performance-approach goal predicted long-term maintenance in exercise participation. It seems that the other-approach goal provides more positive and motivationally beneficial effects on adolescents’ participating in PA compared to elementary-school-aged children [50]. Zhang and colleagues (2016) as well as Lochbaum and colleagues (2013) indicated that mastery-avoidance goals were unrelated to PA among college students using the 2 × 2 achievement goal model, whereas the findings of this study showed that task-avoidance and self-approach goals using the 3 × 2 achievement goal model significantly predicted PA. High school students with higher task-avoidance and self-approach goals were likely to be more physically active compared to college students. This result also provides a critical suggestion that examining task-based and self-based achievement goals could allow us to deeply understand students’ mastery goals, and could provide more precise and clearer information about variants of mastery-based achievement goals [33,51]. Generally, mastery-based achievement goals are related to positive motivational patterns and outcomes, showing that adolescents with higher mastery-based achievement goals often demonstrate higher engagement and effort in PA during PE [52,53]. However, it was unclear whether results from the mastery-based achievement goals would be task-based goals, self-based goals, or both because individuals’ engagement in PA may be driven by achievement goals focusing on one’s action and task (task-based) or focusing on comparing one’s past, current, and future performances (self-based) [33]. Thus, the findings of this study using the 3 × 2 achievement goal model might add meaningful empirical evidence that high school students focus more on how they are doing related to their past or future potential and how they are trying to avoid performing poorly when participating in PA.
Another important finding of this study was that other-approach, self-avoidance, and self-approach goal orientations significantly influenced high school students’ PF outcomes such as 50-meter dash and standing long jump. The results showed that other-approach and self-avoidance goals significantly contributed to the 50-meter dash, but only self-approach goals significantly predicted standing long jump. The reason for these results may be because different PF outcomes have different psychological needs [54,55]. The 50-meter dash asks students to focus on the attainment of the individual’s own task compared to others and avoid performing worse than before. In comparison, the standing long jump requires students to focus on the attainment of the individual’s task compared to previous experience and perform better than before. Thus, self-approach goals should be important to predict standing long jump in this study.
Empirical evidence supported that mastery-approach and performance-approach goals are strongly associated with cardiorespiratory fitness using the 2 × 2 achievement goal model [56]. The current research using the 3 × 2 achievement goal model also supported the relation between the other-approach (i.e., performance-approach) and the 50-meter dash, which is one of the cardiorespiratory fitness tests. We found that self-avoidance goals strongly predicted Chinese adolescents’ 50-meter dash performance, which contradicted results from previous findings of maladaptive patterns between mastery-avoidance and health-related PF outcomes [56,57]. This may be due to different achievement goals when participating in sport activities or physical tasks based on cultural differences between the United Stated and China [58] because we collected data among Chinese high school students. In addition, the 3 × 2 achievement goal construct split the mastery-based goals into two dimensions (task-based and self-based goals), providing more precise differentiated mastery-based goals than the 2 × 2 achievement goal constructs [31]. Based on these findings, we recommend that future studies examine the relationship between adolescents’ achievement goal orientations and PF employing the 3 × 2 achievement goal model to accurately clarify their mastery-based goal orientations.
This study has several important limitations. The first limitation was the use of a self-reported PA measure. Further investigations are necessary to use an objective tool, such as accelerometers or pedometers, to track students’ PA to reduce the potential personal bias in measuring PA. Second, the variances explained by stepwise multiple regression models were relatively low, but we also used a large sample size in this study. In addition, using structural equation modeling (SEM) has more advantages than multiple regression analyses for examining the predictive strengths of six goals orientations on PA and PF with good Type 1 error controls. Third, other psychosocial variables should be included (i.e., motivational climate and social support) in future studies to examine various psychosocial variables on students’ PA and PF. Finally, the 50-meter dash and standing long jump were the sole performance-related PF outcomes measured in this study; thus, more research is needed to explore the relations between students’ goal orientations and other health-related components of PF, such as flexibility, muscular fitness, and body composition, using the 3 × 2 achievement goal model as a framework.

5. Practical Implications

The results of the present study have many practical implications. For example, PE teachers or practitioners can apply the latest wearable fitness technology (e.g., activity trackers such as accelerometers or pedometers) to measure students’ PA objectively and display students’ activity levels (e.g., heart rate, calories burned, and steps taken) on a connected big screen during PE classes or extra PA programs. This application allows students to monitor all their peers’ activity levels and try outperforming their peers (other-approach goals). In addition, PE teachers or practitioners can provide students with PF-related exercise logs to encourage them to record their PF performances. In doing so, students can set up personal goals based on their previous PF performance scores (self-approach goals).

6. Conclusions

Collectively, we provided further empirical evidence validating the 3 × 2 achievement goal model in PE settings among high school students. The findings contribute to the literature by applying the latest 3 × 2 achievement goal model to explore Chinese high school students’ achievement goal orientations in PA and performance-related PF outcomes. The research findings provide empirical evidence and a new perspective for offering effective PA programs and interventions in the high school setting. Fostering self- and other-approach-oriented environments with developmentally appropriate content in PE may hold implications for enhancing high school students’ PA and PF.

Author Contributions

Conceptualization, L.S. and T.Z.; methodology, T.Z. and J.L.; software, J.L. and T.Z..; validation, J.L. and C.C.; formal analysis, J.L., C.C. and T.Z.; investigation, L.S. and T.Z.; resources, L.S.; data curation, J.L., C.C., and T.Z.; writing—original draft preparation, J.L., C.C., and T.Z.; writing—review and editing, L.S. and T.Z.; visualization, J.L. and C.C.; supervision, T.Z.; project administration, L.S. and T.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Acknowledgments

We want to thank all school principals, PE teachers, high school students who supported and participated in our study. We also appreciate all research assistants who assisted in the data collection.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Ogden, C.L.; Carroll, M.D.; Kit, B.K.; Flegal, K.M. Prevalence of Childhood and Adult Obesity in the United States, 2011–2012. J. Am. Med. Assoc. 2014, 311, 806–814. [Google Scholar] [CrossRef] [PubMed][Green Version]
  2. Skinner, A.C.; Perrin, E.M.; Skelton, J.A. Prevalence of Obesity and Severe Obesity in US Children, 1999–2014. Obesity 2016, 24, 1116–1123. [Google Scholar] [CrossRef] [PubMed][Green Version]
  3. Sun, H.; Ma, Y.; Han, D.; Pan, C.W.; Xu, Y. Prevalence and Trends in Obesity among China’s Children and Adolescents, 1985–2010. PLoS ONE 2014, 9, 1–8. [Google Scholar] [CrossRef] [PubMed]
  4. Mo, Z.; Wang, H.; Zhang, B.; Du, S.; Popkin, B.M. Physical Activity and Sedentary Behaviors on Risk of Overweight and Obesity in Chinese Children and Adolescents. Curr. Dev. Nutr. 2019, 3, 1402. [Google Scholar] [CrossRef][Green Version]
  5. Hruby, A.; Manson, J.A.E.; Qi, L.; Malik, V.S.; Rimm, E.B.; Sun, Q.; Willett, W.C.; Hu, F.B. Determinants and Consequences of Obesity. Am. J. Public Health 2016, 106, 1656–1662. [Google Scholar] [CrossRef]
  6. Mokdad, A.H.; Ford, E.S.; Bowman, B.A.; Dietz, W.H.; Vinicor, F.; Bales, V.S.; Marks, J.S. Prevalence of Obesity, Diabetes, and Obesity-Related Health Risk Factors, 2001. J. Am. Med. Assoc. 2003, 289, 76–79. [Google Scholar] [CrossRef]
  7. Juonala, M.; Magnussen, C.G.; Berenson, G.S.; Venn, A.; Burns, T.L.; Sabin, M.A.; Srinivasan, S.R.; Daniels, S.R.; Davis, P.H.; Chen, W.; et al. Childhood Adiposity, Adult Adiposity, and Cardiovascular Risk Factors. N. Engl. J. Med. 2011, 365, 1876–1885. [Google Scholar] [CrossRef][Green Version]
  8. Faith, M.S.; Butryn, M.; Wadden, T.A.; Fabricatore, A.; Nguyen, A.M.; Heymsfield, S.B. Evidence for Prospective Associations among Depression and Obesity in Population-Based Studies. Obes. Rev. 2011, 12, 438–453. [Google Scholar] [CrossRef]
  9. Sharma, M. Dietary Education in School-Based Childhood Obesity Prevention Programs. Adv. Nutr. 2011, 2, 207S–216S. [Google Scholar] [CrossRef][Green Version]
  10. Lee, J.; Zhang, T.; Chu, T.L.; Zhang, X.; Weiller-Abels, K.H.; Keller, J. Comprehensive School Physical Activity Program and Physical Literacy: Exploring Preservice Elementary Classroom Teachers’ Perspectives. Adv. Phys. Educ. 2019, 9, 314–330. [Google Scholar] [CrossRef][Green Version]
  11. Doherty, B.; Lee, J.; Keller, J.; Zhang, T. Promoting School-Aged Children’s Physical Literacy in Schools: A Brief Review. J. Teach. Res. Media Kinesiol. 2019, 5, 45–49. [Google Scholar]
  12. World Health Organization. Global Recommendations on Physical Activity for Health; World Health Organization: Geneva, Switzerland, 2010. [Google Scholar]
  13. Wang, C.; Chen, P.; Zhuang, J. A National Survey of Physical Activity and Sedentary Behavior of Chinese City Children and Youth Using Accelerometers. Res. Q. Exerc. Sport 2013, 84 (Suppl. 2). [Google Scholar] [CrossRef] [PubMed]
  14. Fan, X.; Cao, Z.B. Physical Activity among Chinese School-Aged Children: National Prevalence Estimates from the 2016 Physical Activity and Fitness in China—The Youth Study. J. Sport Heal. Sci. 2017, 6, 388–394. [Google Scholar] [CrossRef] [PubMed]
  15. Wang, X.; Hui, Z.; Terry, P.D.; Ma, M.; Cheng, L.; Deng, F.; Gu, W.; Zhang, B. Correlates of Insufficient Physical Activity among Junior High School Students: A Cross-Sectional Study in Xi’an, China. Int. J. Environ. Res. Public Health 2016, 13. [Google Scholar] [CrossRef] [PubMed][Green Version]
  16. Lee, J.; Zhang, T.; Chu, T.L.; Gu, X.; Zhu, P. Effects of a Fundamental Motor Skill-Based Afterschool Program on Children’s Physical and Cognitive Health Outcomes. Int. J. Environ. Res. Public Health 2020, 17, 733. [Google Scholar] [CrossRef] [PubMed][Green Version]
  17. Lee, J.; Zhang, T.; Chu, T.L.; Gu, X. Effects of a Need-Supportive Motor Skill Intervention on Children’s Motor Skill Competence and Physical Activity. Children 2020, 7, 21. [Google Scholar] [CrossRef][Green Version]
  18. Harwood, C.G.; Keegan, R.J.; Smith, J.M.J.; Raine, A.S. A Systematic Review of the Intrapersonal Correlates of Motivational Climate Perceptions in Sport and Physical Activity. Psychol. Sport Exerc. 2015, 18, 9–25. [Google Scholar] [CrossRef][Green Version]
  19. Chen, C.; Zhang, T.; Gu, X.; Lee, J.; Ren, S.; Wang, H. Understanding Adolescents’ Need Support, Need Satisfaction, and Health-Related Outcomes: A Self-Determination Health Behavior Perspective. Int. J. Environ. Res. Public Health 2020, 17, 104. [Google Scholar] [CrossRef][Green Version]
  20. Gu, X.; Solmon, M.A.; Zhang, T. Using Expectancy-Value Model to Examine Students’ Physical Activity Engagement and Cardiovascular Fitness in Physical Education. J. Sport Psychol. 2012, 43, 385–402. [Google Scholar] [CrossRef]
  21. Gu, X.; Zhang, T.; Chu, T.L.; Keller, M.J.; Zhang, X. The Direct and Indirect Effects of Motor Competence on Adolescents’ Mental Health through Health-Related Physical Fitness. J. Sports Sci. 2019, 37, 1927–1933. [Google Scholar] [CrossRef]
  22. Xiang, M.; Gu, X.; Jackson, A.; Zhang, T.; Wang, X.; Guo, Q. Understanding Adolescents’ Mental Health and Academic Achievement: Does Physical Fitness Matter? Sch. Psychol. Int. 2017, 38, 647–663. [Google Scholar] [CrossRef]
  23. Elliott, E.S.; Dweck, C.S. Goals: An Approach to Motivation and Achievement. J. Pers. Soc. Psychol. 1988, 54, 5–12. [Google Scholar] [CrossRef] [PubMed]
  24. Duda, J.L.; Nicholls, J.G. Dimensions of Achievement Motivation in Schoolwork and Sport. J. Educ. Psychol. 1992, 84, 290–299. [Google Scholar] [CrossRef]
  25. Cano, F.; Berbén, A.B.G. University Students’ Achievement Goals and Approaches to Learning in Mathematics. Br. J. Educ. Psychol. 2009, 79, 131–153. [Google Scholar] [CrossRef]
  26. Zhang, T.; Xiang, P.; Gu, X.; Rose, M. College Students’ Physical Activity and Health-Related Quality of Life: An Achievement Goal Perspective. Res. Q. Exerc. Sport 2016, 87, 182–190. [Google Scholar] [CrossRef]
  27. Dweck, C.S. Motivational Processes Affecting Learning. Am. Psychol. 1986, 41, 1040–1048. [Google Scholar] [CrossRef]
  28. Nicholls, J.G. Achievement Motivation: Conceptions of Ability, Subjective Experience, Task Choice, and Performance. Psychol. Rev. 1984, 91, 328–346. [Google Scholar] [CrossRef]
  29. Elliot, A.J.; Harackiewicz, J.M. Approach and Avoidance Achievement Goals and Intrinsic Motivation: A Meditational Analysis. J. Pers. Soc. Psychol. 1996, 70, 461–475. [Google Scholar] [CrossRef]
  30. Elliot, A.J.; Mcgregor, H.A. A 2 × 2 Achievement Goal Model. J. Pers. Soc. Psychol. 2001, 80, 501–519. [Google Scholar] [CrossRef]
  31. Elliot, A.J.; Murayama, K.; Pekrun, R. A 3 × 2 Achievement Goal Model. J. Educ. Psychol. 2011, 103, 632–648. [Google Scholar] [CrossRef][Green Version]
  32. Lower, L.M.; Turner, B.A.; Newman, T.J.; Pollard, W.S. Examination of the 3 × 2 Achievement Goal Model in Collegiate Recreation: Comparison across Sport Programs. Int. J. Sport Manag. Recreat. Tour. 2016, 26, 44–53. [Google Scholar] [CrossRef][Green Version]
  33. Mascret, N.; Elliot, A.J.; Cury, F.F. Extending the 3 × 2 Achievement Goal Model to the Sport Domain: The 3×2 Achievement Goal Questionnaire for Sport. Psychol. Sport Exerc. 2015, 17, 7–14. [Google Scholar] [CrossRef]
  34. Estrada, J.A.C.; González-Mesa, C.G.; Méndez-Giménez, A.; Fernández-Río, J. Achievement Goals, Social Goals, and Motivational Regulations in Physical Education Settings. Psicothema 2011, 23, 51–57. [Google Scholar]
  35. Wang, C.K.J.; Biddle, S.J.H.H.; Elliot, A.J. The 2 × 2 Achievement Goal Framework in a Physical Education Context. Psychol. Sport Exerc. 2007, 8, 147–168. [Google Scholar] [CrossRef]
  36. Liu, J.; Xiang, P.; Lee, J.; Li, W. Developing Physically Literacy in K-12 Physical Education through Achievement Goal Theory. J. Teach. Phys. Educ. 2017, 36, 292–302. [Google Scholar] [CrossRef]
  37. Shen, B.; Chen, A.; Guan, J. Using Achievement Goals and Interest to Predict Learning in Physical Education. J. Exp. Educ. 2007, 75, 89–108. [Google Scholar] [CrossRef]
  38. Wang, C.K.; Liu, W.C.; Sun, Y.; Chua, L.L. Psychometric Properties of the 3 × 2 Achievement Goal Questionnaire for Sport. Int. J. Sport Exerc. Psychol. 2016, 15, 460–474. [Google Scholar] [CrossRef]
  39. Small, M.; Bailey-Davis, L.; Morgan, N.; Maggs, J. Changes in Eating and Physical Activity Behaviors across Seven Semesters of College: Living on or off Campus Matters. Heal. Educ. Behav. 2012, 40, 435–441. [Google Scholar] [CrossRef][Green Version]
  40. McEwan, D.; Harden, S.M.; Zumbo, B.D.; Sylvester, B.D.; Kaulius, M.; Ruissen, G.R.; Dowd, A.J.; Beauchamp, M.R. The Effectiveness of Multi-Component Goal Setting Interventions for Changing Physical Activity Behaviour: A Systematic Review and Meta-Analysis. Health Psychol. Rev. 2016, 10, 67–88. [Google Scholar] [CrossRef]
  41. Pajo, B. Introduction to Research Methods: A Hands-on Approach; Sage Publications: Thousand Oaks, CA, USA, 2017. [Google Scholar]
  42. Arbuckle, J. IBM SPSS AmosTM 25 User’s Guide; SPSS: Chicago, IL, USA, 2017. [Google Scholar]
  43. Bagozzi, R.P.; Yi, Y. On the Evaluation of Structural Equation Models. J. Acad. Mark. Sci. 1988, 16, 74–94. [Google Scholar] [CrossRef]
  44. Kowalski, K.C.; Crocker, P.R.E.; Donen, R.M. The Physical Activity Questionnaire for Older Children (PAQ-C) and Adolescents (PAQ-A) Manual. Coll. Kinesiol. Univ. Saskatchewan 2004, 87, 1–38. [Google Scholar]
  45. Martinez-Gomez, D.; Martinez-de-Haro, V.; Pozo, T.; Welk, G.J.; Villagra, A.; Calle, M.E.; Veiga, O.L. Reliability and Validity of the PAQ-A Questionnaire to Assess Physical Activity in Spanish Adolescents. Rev. Esp. Salud Publica 2009, 83, 427–439. [Google Scholar] [PubMed]
  46. Corbin, C.B.; Pangrazi, R.P.; Franks, B.D. Definitions: Health, Fitness, and Physical Activity. Pres. Counc. Phys. Fit. Sport. Res. Dig. 2000, 3, 1–8. [Google Scholar]
  47. Roberts, G.C.; Treasure, D.C.; Conroy, D.E. Understanding the dynamics of motivation in sport and physical activity: An achievement goal interpretation. In Handbook of Sport Psychology, 3rd ed.; John Wiley & Sons Inc.: Hoboken, NJ, USA, 2007; pp. 3–30. [Google Scholar]
  48. Wang, J.C.K.; Morin, A.J.S.; Liu, W.C.; Chian, L.K. Predicting Physical Activity Intention and Behaviour Using Achievement Goal Theory: A Person-Centred Analysis. Psychol. Sport Exerc. 2016, 23, 13–20. [Google Scholar] [CrossRef]
  49. Lochbaum, M.; Podlog, L.; Litchfield, K.; Surles, J.; Hilliard, S. Stage of Physical Activity and Approach-Avoidance Achievement Goals in University Students. Psychol. Sport Exerc. 2013, 14, 161–168. [Google Scholar] [CrossRef]
  50. Midgley, C.; Kaplan, A.; Middleton, M. Performance-Approach Goals: Good for What, for Whom, under What Circumstances, and at What Cost? J. Educ. Psychol. 2001, 93, 77–86. [Google Scholar] [CrossRef]
  51. Diseth, Å. The Advantages of Task-Based and Other-Based Achievement Goals as Standards of Competence. Int. J. Educ. Res. 2015, 72, 59–69. [Google Scholar] [CrossRef]
  52. Standage, M.; Duda, J.L.; Ntoumanis, N. A Model of Contextual Motivation in Physical Education: Using Constructs from Self-Determination and Achievement Goal Theories to Predict Physical Activity Intentions. J. Educ. Psychol. 2003, 95, 97–110. [Google Scholar] [CrossRef]
  53. Guan, J.; Xiang, P.; McBride, R.; Bruene, A. Achievement Goals, Social Goals, and Students’ Reported Persistence and Effort in High School Physical Education. J. Teach. Phys. Educ. 2006, 25, 58–74. [Google Scholar] [CrossRef]
  54. Wilson, P.M.; Rodgers, W.M.; Blanchard, C.M.; Gessell, J. The Relationship between Psychological Needs, Self-Determined Motivation, Exercise Attitudes, and Physical Fitness. J. Appl. Soc. Psychol. 2003, 33, 2373–2392. [Google Scholar] [CrossRef]
  55. Erturan-İlker, G.; Yu, C.; Alemdaroglu, U.; Köklü, Y. Basic Psychological Needs and Self-Determined Motivation in Physical Education to Predict Health-Related Fitness Level. J. Sport Heal. Res. 2018, 10, 91–100. [Google Scholar]
  56. Gao, Z.; Xiang, P.; Lochbaum, M.; Guan, J. The Impact of Achievement Goals on Cardiorespiratory Fitness: Does Self-Efficacy Make a Difference? Res. Q. Exerc. Sport 2013, 84, 313–322. [Google Scholar] [CrossRef] [PubMed]
  57. Wang, J.C.K.; Liu, W.C.; Lochbaum, M.R.; Stevenson, S.J. Sport Ability Beliefs, 2 × 2 Achievement Goals, and Intrinsic Motivation: The Moderating Role of Perceived Competence in Sport and Exercise. Res. Q. Exerc. Sport 2009, 80, 303–312. [Google Scholar] [CrossRef] [PubMed]
  58. Gao, Z.; Xiang, P.; Harrison, L.; Guan, J.; Rao, Y. A Cross-Cultural Analysis of Achievement Goals and Self-Efficacy between American and Chinese College Students in Physical Education. Int. J. Sport Psychol. 2008, 39, 312–328. [Google Scholar]
Table 1. Descriptive statistics, internal reliabilities, and correlations in study variables (N = 792).
Table 1. Descriptive statistics, internal reliabilities, and correlations in study variables (N = 792).
VariablesM ± SD123456789
1. Task-approach5.29 ± 1.18(0.89)
2. Self-approach5.28 ± 1.180.85 **(0.90)
3. Other-approach4.76 ± 1.370.69 **0.71 **(0.95)
4. Task-avoidance5.14 ± 1.250.51 **0.50 **0.53 **(0.91)
5. Self-avoidance5.11 ± 1.320.52 **0.52 **0.53 **0.87 **(0.96)
6. Other-avoidance5.03 ± 1.340.51 **0.50 **0.58 **0.81 **0.89 **(0.96)
7. PA2.26 ± 0.780.27 **0.27 **0.27 **0.10 **0.11 **0.13 **(0.79)
8. 50-meter dash8.28 ± 1.26−0.10 **−0.12 **−0.13 **0.010.010.04−0.24 **-
9. Standing longjump184.54 ± 41.450.14 **0.14 **0.13 **0.010.020.030.23 **−0.52 **-
Note: M = mean; SD = standard deviation; PA = physical activity; the diagonal in parentheses displays the Cronbach’s α values; ** p < 0.01.
Table 2. Results of stepwise multiple regression analyses (N = 792).
Table 2. Results of stepwise multiple regression analyses (N = 792).
Study VariablesPredictorsR2βt
PA 0.09 ***
Other-approach 0.19 ***3.85
Self-approach 0.18 ***3.72
Task-avoidance −0.09 *−2.18
50-meter dash 0.03 ***
Other-approach −0.19 ***−4.11
Self-avoidance 0.10 *2.21
Standing long jump 0.02 ***
Self-approach 0.14 ***3.52
Notes. PA = physical activity; β = standardized regression coefficients. *** p < 0.001, * p < 0.05.

Share and Cite

MDPI and ACS Style

Shen, L.; Lee, J.; Chen, C.; Zhang, T. High School Adolescents’ Physical Activity and Physical Fitness: A 3 × 2 Achievement Goal Approach. Sustainability 2020, 12, 6005. https://doi.org/10.3390/su12156005

AMA Style

Shen L, Lee J, Chen C, Zhang T. High School Adolescents’ Physical Activity and Physical Fitness: A 3 × 2 Achievement Goal Approach. Sustainability. 2020; 12(15):6005. https://doi.org/10.3390/su12156005

Chicago/Turabian Style

Shen, Liang, Joonyoung Lee, Changzhou Chen, and Tao Zhang. 2020. "High School Adolescents’ Physical Activity and Physical Fitness: A 3 × 2 Achievement Goal Approach" Sustainability 12, no. 15: 6005. https://doi.org/10.3390/su12156005

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop