RESEARCH ARTICLE
Effectiveness of School-Initiated Physical Activity Program on Secondary School Students’ Physical Activity Participation ´ , Meda SAMI YLI-PIIPARI, PhDb ANTHONY WATT, PhDc TIMO JAAKKOLA, PhDd JARMO LIUKKONEN, PhDe ˚ EN ARTO GRAST
ABSTRACT BACKGROUND: The promotion of physical activity and health has become a universal challenge. The Sotkamo Physical Activity as Civil Skill Program was implemented to increase students’ physical activity by promoting supportive psychological and physical school environment. The aim of this study was to evaluate the effectiveness of the school-initiated physical activity program on secondary school students’ self-reported physical activity. METHODS: The sample included 847 students (experimental condition school = 208, control school = 639) at the age of 12 to 14 years from northeast and central Finland. The program was conducted across 1 academic year and 2 measurement phases were carried out using self-report questionnaires in April 2011 and 2012. RESULTS: The findings highlighted that the program appeared to be effective as an approach to change the sharp decline in the pattern of Grade 7 students’ self-reported physical activity across 1 school year. Specifically, change in the experimental condition students’ self-reported physical activity was 13.4% higher compared the students in the control condition. CONCLUSION: On the basis of current findings, increased opportunities for school day physical activities have the potential to affect large number of students and are an efficient strategy for promoting regular physical activity. Keywords: exercise motivation; physical activity; physical education; program; secondary school. ˚ en A, Yli-Piipari S, Watt A, Jaakkola T, Liukkonen J. Effectiveness of school-initiated physical activity program on Citation: Grast´ secondary school students’ physical activity participation. J Sch Health. 2015; 85: 125-134. Received on November 29, 2013 Accepted on July 11, 2014
T
he World Health Organization has identified physical inactivity as the fourth highest risk factor for global mortality.1 Patterns of activity in adulthood are often established during adolescence, making this an important period for promoting physical activity.2 International guidelines propose that adolescents should engage in 60 minutes of daily moderate to vigorous physical activity (MVPA) to actualize health benefits optimally.3,4 Considering that less than one third of 15-year olds in countries such the US and Finland meet the current recommendation and approximately half of them exceed the sedentary behavior guideline of less than 2 hours of sedentary time per day from discretionary screen time, the promotion of
MVPA has become a universal challenge.5 To increase adolescents’ MVPA, scholars and institutions have advocated that schools could promote public health by increasing opportunities for daily activity and ensuring that students have an access to a high-quality school physical education.6,7 To address this, the European Union funded community program ‘‘Sotkamo Physical Activity as Civil Skill Program’’ was implemented to support the psychological and physical school environment in order to increase students’ daily MVPA.8 The program was developed based on attributes of the Achievement Goal Theory9 and the Social Ecological Model.10,11 Multilevel interventions have produced evidence of efficacy in changing physical
a Researcher, (agrasten@jyu.fi), Department of Sport Sciences, University of Jyvaskyla, PO Box 35, Jyvaskyla 40014, Finland. bAssistant Professor, ([email protected]), Department of Health and Sport Sciences, University of Memphis, 106 Fieldhouse, Memphis, TN 38152. c Senior Lecturer, ([email protected]), School of Education, Victoria University, PO Box 14428, Melbourne, Victoria 8001, Australia. dLecturer, (timo.jaakkola@jyu.fi), Department of Sport Sciences, University of Jyvaskyla, PO Box 35, Jyvaskyla 40014, Finland. e Professor, (jarmo.liukkonen@jyu.fi), Department of Sport Sciences, University of Jyvaskyla, PO Box 35, Jyvaskyla 40014, Finland.
Address correspondence to: Arto Gr˚ast´en, Researcher, (agrasten@jyu.fi), Department of Sport Sciences, University of Jyvaskyla, PO Box 35, Jyvaskyla 40014, Finland.
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activity behavior.10,12,13 The central assumption of the current program was that an individual’s behavior can be influenced by manipulating the psychological and physical environments. The Achievement Goal Theory recognizes the role of social environment, but also provides a plausible model to facilitate understanding the relationship between the psychological environment and student behavior in physical education. In turn, the Social Ecological Model covers the multilevel relationships between individual characteristics, social environment, physical environment, and physical activity behavior.10 In accordance with these conceptual perspectives, the current program was designed to promote an increase in secondary school students’ physical activity by modifying their task-involving climate in physical education classes and physical school environment. The task-involving climate treatment was grounded in the Achievement Goal Theory9 and designed to influence students’ task orientation, and subsequently MVPA through supportive task-involving motivational climate in regular physical education classes. The focal tenet of the theory is that there are 2 key concepts for defining competence and success in activity, namely task (learning) and ego (performance) orientation. Task orientation corresponds a perception of self-referenced ability, such as effort and learning. The focus of activity involvement is in mastering the current tasks and improvement, resulting in increased physical education motivation.9,14 This means that an individual has adopted personal improvement and learning (task orientation) as criteria for success.15 In contrast, ego-oriented individuals ascribe success to other referenced criteria such as ability, and the main objective of engagement in an activity is to demonstrate normative competence and outperform others.9,16,17 Thus, the perception of competence is not depending on their own control.18 Additionally, these 2 conceptualizations of competence and success are also described as the situational goal structure, namely perceived motivational climate, which reflects students’ perceptions of the emphasis placed on developing (task-involving climate) or demonstrating normative competence (ego-involving climate) by social agents.15 Positive development of physical education motivation is most likely to occur when task-involving climate is emphasized.15 According to the model of Weiss19 physical education teachers have a tremendous impact on student’s physical activity behavior through the regulation of motivational climate via feedback, reinforcement, modeling, and structuring of physical activity opportunities. Perceptions of taskinvolving climate in physical education can influence students’ perceptions of task orientation19,20 whereas an ego-involving climate advances social comparison and ego orientation.21 Teachers who structure a motivational climate that encourages task orientation 126
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are likely to positively influence students’ MVPA in physical education,19,20 MVPA outside physical education classes,22 out-of-school MVPA,23 physical activity participation,24 perceived effort and persistence,20,25 and perceptions of physical condition in physical education classes.26 For instance, in a yearlong intervention in Greek junior high school, the experimental school students had higher task orientaton, lower ego orientation, and more positive attitudes toward exercise than the control group, when a task-involving climate in physical education was supported.23 Wallhead and Ntoumanis suggested that the curriculum associated with sport education may increase the perceptions of motivational climate, and in so doing, enchance task orientation toward physical education in high school students.25 For instance, according to Vallerand’s27 proposed motivational climate model, social factors (motivational climate) result in positive consequences (physical activity) through psychological mediator (task orientation) and exercise motivation in physical education context. Because, the quantity of school physical education classes cannot be dramatically increased, improving content and quality is a feasible practice to use in physical education as a mean ˚ en ´ et al28 highto enhance students’ daily MVPA. Grast lighted that MVPA in physical education classes was linked to out-of-school MVPA, especially for boys. Therefore, the psychological mechanism underlying physical activity behavior19,27 has yet to be investigated to clarify the long-term effects of task-involving climate treatment on students’ task orientation and daily MVPA.29 The physical school environment treatment was focused on the students’ physical environment at the school with the objective to increase opportunities for physical activity during their attendance. The intervention’s adoption of the social ecological model can be broadly divided into intra-individual and inter-individual.10 Intra-individual influences might include individual attributes, beliefs, attitudes, and behaviors, whereas inter-individual influences might include environmental, social, and cultural contexts.10 For example, change at an intra-individual level of influence might include improving attitudes toward physical activity, thereby increasing the probability that physical activity increases. Change at an inter-individual level of influence might include providing facilities for activities, also increasing physical activity levels.30 Sallis et al31 reported that an inter-individual intervention based on the ecological model (including physical education classes’ structural changes, organized activities, and access to equipment throughout school day) increased middle school student’s daily MVPA. Furthermore, many school-based interventions highlighted that an effective way to counter low MVPA levels is to enhance MVPA with an increase in frequency and duration of physical activities in physical •
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Figure 1. The Path Model of the Theorized Relationships Between Motivational Climate, Goal Orientations, SelfReported MVPA, and Hypothesized Treatment Effects From T0 to T1
education,32-34 in the school environment during nonacademic periods,12,35,36 and redesigning school yard.37,38 The review of interventions previously considered introduces a large variation of methods to increase MVPA during the school day. However, Tammelin, Laine, and Turpeinen noted, especially during school-based interventions, students’ total MVPA may decrease, if students reduce their after school activity, respectively.39 Therefore, it is important to study, whether total MVPA including activities during the school day and out-of-school is enhanced as an outcome of the physical school environment program. Thise study aimed to evaluate the effectiveness of school-initiated physical activity program that was implemented at the secondary school level across 1 school year (Figure 1). On the basis of previously established relationships,10,23,24,40 the effectiveness of the program, including task-involving climate and physical school environment treatments, on students’ MVPA was tested. It was hypothesized that the manipulation of physical education students’ motivational climate has an impact on their physical activity through their motivational orientations.19,27 In addition, to determine if task-involving climate or physical school environment treatment had a stronger effect on students’ self-reported MVPA, the effect sizes were examined.
METHODS Participants and Setting The sample comprised 847 students (422 girls, 425 boys) aged 12 to 14 years from 2 school districts. The experimental condition school (N = 208) and 4 control schools (N = 639) were recruited from northeast and central Finland through direct contact with school principals. Both school districts were typical Finnish midsized cities with 96% of students being Caucasian. All Grade 7 students in each class were invited to participate and 75% (experimental school) and 73% Journal of School Health
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(control schools) of the students asked were able to return both the student consent and parental consent. Participation in this study was voluntary and no extra credit was awarded for participation. Instruments Motivational climate was measured using the Motivation Climate in Physical Education Scale,41 which consists of 2 subscales representing task- and egoinvolving climate. The individual item stem used in the measure was ‘‘In my physical education classes . . . ’’ Both the task-involving climate dimension (‘‘It is important for students to try their best in physical education classes’’), and the ego-involving climate dimension (‘‘It is important for students to succeed better than others in physical education classes’’) consisted of 4 items. Responses were indicated on a 5-point Likert-scale ranging from strongly disagree (1) to strongly agree (5). Previous confirmatory factor analysis supported the construct validity (Tucker Lewis index [TLI] = 0.97, comparative fit index [CFI] = 0.97, root mean square error of approximation [RMSEA] = 0.037) and internal consistency (Cronbach’s α > 0.78) of the subscales for Finnish secondary school students.41 Achievement goal orientations were analyzed using the Perception of Success Questionnaire.42 The scale consists of 12 items, 6 measuring task orientation (‘‘I really improve’’), and 6 ego orientation ( ‘‘I do better than others’’). Items were rated on a 5-point Likert-scale ranging from strongly disagree (1) to strongly agree (5). The questionnaire used in the current study had the individual item stem of ‘‘I feel most successful in physical education lessons, when. . . . ’’ According to Yli-Piipari et al43 a confirmatory factor analysis supported the construct validity (TLI = 0.97, CFI = 0.97, RMSEA = 0.03) and internal consistency of the scale for a sample of Finnish secondary school students was acceptable (Cronbach’s α > 0.88). Self-reported MVPA was assessed using the Health Behavior in School-aged Children Research Protocol.44 The scale consists of 2 items rated on an 8-point response scale (0 to 7 days of the week) (‘‘When you think about your typical week, on how many days are you physically active for a total of at least 60 minutes per day?’’). The mean scores of the 2 items were used as MVPA scores. Prochaska et al45 reported that for a sample of 138 US children and adolescents with a mean age of 12.1 years, the moderate to vigorous MVPA items were reliable (ICC = 0.77) and had moderate correlation (r = .40) with accelerometer data in a study based on a 5-day data collection period. Similarly, Pearson’s correlation coefficients between self-reported MVPA and accelerometer data scores ranged from weak (r = .32) to strong (r = .66) when self-report scores were assessed using this protocol in the sample of 96 Finnish secondary school students for a 7-day period.46
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Procedure This study was implemented across the academic year 2011-2012. The 2 data collection sessions were conducted in April 2011 (T0 = Grade 7) and 2012 (T1 = Grade 8). Subjects completed the questionnaires under the supervision of the researchers during 45minute classes, typically held in the classroom or gym. The subjects were advised to ask for help if confused concerning either the instructions or the clarity of a particular item. To minimize students’ tendency to give socially desirable responses, students were encouraged to answer honestly and were assured that their responses were confidential. The students were told that their involvement was voluntary and could withdraw at any time as subjects in the study. All Finnish secondary school students have 2 45minute physical education classes per week, usually combined as 1 90-minute class. The majority of schools have sex groups in physical education classes. The recess breaks, average 30 breaks (at least 10 minutes) per week, and daily lunch break (30 minutes) are mandatory to all students.47 Typically, secondary school students spend their recess breaks indoors, mainly accumulating sedentary time.39 The control group was taught following the guidelines of the Finnish national curriculum;48 no task-involving climate support or extra physical activities were provided. The experimental condition school students received the treatments across the academic year 20112012 (Table 1). The task-involving climate treatment comprised supplementary teacher training and task-involving climate support in regular physical education classes. Four physical education teachers from the experimental school participated in four 90-minute workshops to extend and develop their current physical education teaching practices. The teacher workshops were organized during the academic year 2010-2011 by the project leaders. The workshops were a part of teacher’s collective bargaining agreement of supplementary training. Teachers were informed about the goals, methods, and procedures of the program and subsequent treatment. The workshops and treatment had the following features: (1) Task-involving teaching practices; students work together within a small cooperative group structure, students are responsible for setting up equipment, during lesson time students dictate the rate of progression through specific practices, (2) Task orientation support; evaluation emphasizes individual improvement, (3) Improving students personal skills; students choose practices from a range of offered practices with the different skill requirements, more activity, and less waiting during physical education classes, and (4) Positive feedback and encouragement; recognition and feedback is based on the individual progress. The teachers 128
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completed the structured questionnaires regarding the self-evaluation on task-involving teaching practices. The physical school environment treatment focused on developing the physical environment of the school and providing equipment. The activities were organized during extended and regular breaks. The students were given a lot of autonomy when selecting activities. The recess activities and treatment included the following actions: (1) Extended break; daily extended break of 30 minutes in addition to the lunch break and regular breaks, (2) Access to fitness hall; students were allowed to use fitness facilities during the extended and regular breaks to exercise or play games, (3) Controlled ballgames; students were responsible for setting up ballgames and refereeing during extended breaks (5 days × 30 minutes × 12 weeks) under the teachers’ supervision, (4) Equipment supply; exercise equipment was available to all students during the extended and regular breaks, students were responsible for setting up equipment. The project leaders monitored the school breaks twice a month. Data Analyses Data analyses were conducted in the following order. First, descriptive analyses to determine means, standard deviations, Pearson’s correlation coefficients, and Crohnbach’s alpha were conducted. Second, independent t tests were performed to examine if the experimental and control conditions differed in motivational climate, goal orientation, or self-reported MVPA. Third, a 2 (treatment: yes, no) × 2 (time: pretest, posttest) analysis of covariance (ANCOVA) was employed to examine whether subjects who received the treatment displayed changes in perceptions of motivational climate and MVPA participation. Fourth, 2 path analyses were conducted to test the study hypotheses: Model 0 - a default model with hypothesized relationships between variables without the treatment effects (Figure 1); Model 1 - the effect of the program was tested, in which treatments (task-involving climate and physical school environment) were added as covariates to regress students’ perception of task- and ego-involving climate and self-reported MVPA. All analyses were performed within a structural equation modeling framework using the Mplus statistical package version 6.1.49 CFI, TLI, and Root Mean Square Residual (RMSR) were utilized as a means of evaluating the fit of the models because previous research has shown that these fit indices displayed restricted random variation when utilized within a range of conditions associated with model misspecification, sample size, and estimation method.50,51 A model fits the data well when the p-value associated with the chi-square test is nonsignificant. A cutoff
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Table 1. The Procedures of School-initiated Physical Activity Program Object
Method
Duration/Amount
Time
Evaluation
1× 90minute
September 2010
Structured self-report form to teachers, November 2011 and April 2012
1× 90minute 1× 90minute
August 2011 November 2011
1× 90minute
November 2011
5× 30minutes × 38weeks
September 2011 to May 2013
(2) Access to fitness hall
5× 30minutes × 38weeks
September 2011 to May 2013
(3) Controlled ballgames (1) Dance pad
5× 30minutes × 12weeks 2 pieces
(2) Floor hockey stick (3) Volleyball (4) Basketball (5) Ball bouncer stick (6) Table tennis table (7) Table tennis racket (8) Table tennis ball (9) Disc golf disc
30 pieces 2 pieces 2 pieces 20 pieces 6 pieces 12 pieces 100 pieces 6 pieces
Task-involving climate treatment Teacher workshops (1) Lecture: Task-involving teaching practices (2) Demo: Task orientation support (3) Demo: Improving students’ personal skills (4) Demo: Positive feedback and encouragement Physical school environment treatment Recess activities (1) Extended break
Equipment supply
value close and above 0.95 for the CFI and TLI and a cutoff value under 0.06 for RMSEA were considered as a good fit between the hypothesized model and the observed data.52
RESULTS Exploratory Analyses Pearson’s correlation coefficients, means, standard deviations, and Cronbach’s alpha are presented in Table 2. For both experiment and control conditions, correlation coefficients showed either negligible or weak positive relationships between task-involving climate and ego-involving climate, weak to moderate positive relationships between task and ego orientation, and moderate and strong positive relationships between self-reported MVPA at Grades 7 and 8. The Bonferroni-corrected (significance level of 0.006) independent t tests showed that the control group had higher levels of ego-involving climate (T0: t[754] = 40.06, p < .001, d = 0.30; T1: t[834] = 2.93, p = .004, d = 0.20), ego orientation (t[845] = 2.72, p < .001, d = 0.19), and MVPA (t[764] = 2.77, p < .01, d = 0.20). In other words, the students in control condition had a higher ego-involving motivational climate in physical education classes and total MVPA at the baseline measures than students in experimental condition. Additionally, higher ego-involving climate and ego orientation were detected in follow-up measures for the control condition. Journal of School Health
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Teachers informed project leader twice a month; Project leader monitored the school breaks twice a month
Students responsible for setting up equipment under teachers’ supervision
ANCOVAs showed that there was a significant treatment effect on ego-involving climate (F[2,757] = 15.10, p < .001, η2 = 0.02) and MVPA (F[2,763] = 15.56, p < .001, η2 = 0.20) but no statistically significant effect on task-involving climate (F[2,758] = 2.93, p = .088, η2 < 0.01). The examination of the pre- and posttest values showed that experimental condition students’ self-reported MVPA increased, whereas control condition students’ MVPA decreased across 1 year of program, respectively. Main Analyses To test the theorized relationships of the research variables without treatment effects Model 0 was implemented (Figure 1). Although the χ 2 test achieved statistical significance (typical in case of large sample sizes) the rest of the fit indicators suggested an appropriate data fit: χ 2 (22) = 55.680, p < .001, CFI = 0.97, TLI = 0.95, RMSEA = 0.056, 90%, CI [0.05, 0.08]. The study showed that the perceptions of taskinvolving climate (β = 0.49), ego-involving climate (β = 0.27) climate, and self-reported MVPA (β = 0.54) at the baseline (T0) were significant predictors of subsequent (T1) perceptions of task- and ego-involving climate and self-reported MVPA. In addition, expected relationships emerged, because task-involving climate predicted task orientation (β = 0.60), ego-involving climate ego orientation (β = 0.37), and task orientation predicted MVPA (β = 0.17). The sizes of the effects were weak to moderate explaining 16% to 37% of
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Table 2. Summary of Intercorrelations, Means, Standard Deviations, and Cronbach’s Alphas for Self-Reported MVPA, Goal Orientations, and Motivational Climate Variables 1. Self-reported MVPA (T0) 2. Self-reported MVPA (T0) 3. Task orientation (T1) 4. Ego orientation (T1) 5. Task-involving climate (T0) 6. Task-involving climate (T1) 7. Ego-involving climate (T0) 8. Ego-involving climate (T1) M SD α
1 — 0.47** 0.11* 0.09* 0.13* 0.11* 0.08* 0.001 4.24 1.58 0.91
2
3
0.85**
0.23**
— 0.27** 0.23** 0.14** 0.27** 0.05 0.08* 3.86 1.75 0.91
0.25** — 0.34** 0.33** 0.60** −0.06 0.19** 3.81 0.85 0.94
4 0.08 0.05 0.39** — 0.02 0.18** 0.18*** 0.39** 3.04 0.95 0.95
5
6
0.08 0.11 0.26** −0.12 — 0.44** 0.10* 0.05 3.59 0.74 0.99
0.25** 0.26** 0.66** 0.20* 0.48** — 0 0.28** 3.53 0.81 0.7
7 0.14 0.19* −0.09 0.09 −0.13 −0.1 — 0.25** 2.99 0.72 0.98
8 0.08 0.06 0.09 0.35** −0.20* 0.19* 0.26** — 3.04 0.83 0.75
M 3.90a 4.07 3.77 2.76a 3.64 3.65 2.76a 2.85a
SD 1.51 1.44 0.75 0.87 0.63 0.67 0.62 0.76
α na na 0.93 0.94 0.79 0.8 0.75 0.81
MVPA, moderate to vigorous physical activity; SD, standard deviation; na, not available. *** p < .001, ** p < .01, * p < .05, a higher means of the control group at the Bonferroni-corrected significance level (p = .006). Note 1. Intercorrelations for the experimental group (n = 208) are presented above the diagonal and intercorrelations for the control group (n = 639) are presented below the diagonal. Means, standard deviations, and Cronbach’s alpha for the experimental group are presented in vertical columns and means, deviations, and Cronbach’s alpha for the control group are presented in horizontal columns. Note 2. Cronbach’s alphas for the experimental group’s measurements (T0): Self-reported MVPA (0.92), task orientation (0.85), ego orientation (0.40), task-involving climate (0.65), and ego-involving climate (0.40). Note 3. Cronbach’s alphas for the control group’s measurements (T0): Self-reported MVPA (0.67), task orientation (0.64), ego orientation (0.62), task-involving climate (0.65), and ego-involving climate (0.42).
the variance of students’ task and ego orientation and MVPA (R2 task = .37, R2 ego = .16, R2 MVPA = .34). To examine the effects of the program on Grade 7 students’ self-reported MVPA over a 1-year time period, Model 1 was estimated, in which treatment effects (task-involving climate treatment and physical school environment treatment) were added into the Model 0 as covariates. The model fit was within acceptable limits: χ 2 (16) = 32.676, p = .003, CFI = 0.98, TLI = 0.98, RMSEA = 0.044, 90%, CI [0.04, 0.07]. The results showed that the program had a positive effect on students’ self-reported MVPA. Regression coefficients showed that program had a weak negative influence on ego-orientation (β = −0.07), no influence on task-orientation (β = 0.04), and moderate effect on self-reported MVPA (β = 0.19). The effect sizes were moderate (R2 task = .37, R2 ego = .16, R2 MVPA = .39). Taken together, the model including both taskinvolving motivational climate treatment (actions to increase physical activity through manipulation of motivational climate in physical education) and physical school environment treatment (providing students increased opportunities for school-day physical activities) indicated to be an effective strategy to prohibit declining levels of students’ MVPA participation across 1-year period. However, the closer examination of the effects emerged that the treatments yielded only a small negative effect on students’ ego orientation. All fit indices and parameter estimates are presented in Table 3.
program on Grade 7 students’ self-reported MVPA across 1 school year. According to the findings presented in the previous literature, task-involving motivational climate has been evidenced to increase students’ task orientation in physical education classes, however, it was still unclear whether students’ total daily MVPA can be increased by promoting taskinvolving climate and the physical school environment without additional physical education classes. This study examined the treatment effects using the task-involving motivational climate model,19,27 in which task-involving motivational climate in addition to extra physical activities was assumed to have long-term effects on students’ total MVPA via goal orientations rather than direct short-term effects on students’ MVPA in physical education classes. The Sotkamo Physical Activity as Civil Skill Program8 appeared to be effective as an approach to change the sharp decline in the pattern of Grade 7 students’ MVPA across the school year. Specifically, change in the experimental condition students’ total MVPA was 13.4% higher compared to MVPA of the students in the control condition across 1 year of program. For comparison, Simon et al38 reported that the additional opportunities for MVPA led to increases of 18% in the active participation of US middle school students over a 4-year intervention including in-school and out-of-school activities. A similar Finnish report detailed that secondary school students’ daily MVPA could be sustained at the same level, when longer school breaks, games during breaks, equipment supply, and an extra 45-minute physical education class after school days were provided.39 Several previous multilevel interventions have been evidenced as being
DISCUSSION The aim of the study was to examine the effectiveness of the school-initiated physical activity 130 •
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Table 3. Regression and Correlation Coefficients for the Path Models
Parameter Estimates
Model 0 Standardized Values (β)
Model 1 Standardized Values (β)
Regression coefficients 0.48 (0.03)** Task climate T0→ task climate T1 0.49 (0.03)** Task climate T0→ ego climate T1 0.01 (0.04) −0.02 (0.04) Ego climate T0) → ego climate T1 0.27 (0.05)** 0.27 (0.05)** Ego climate T0→ task climate T1 −0.05 (0.04) −0.05 (0.04) Task climate T1→ task orientation T1 0.60 (0.03)** 0.61 (0.03)** Task climate T1→ ego orientation T1 0.09 (0.04) 0.05 (0.04) Ego climate T1→ ego orientation T1 0.37 (0.03)** 0.36 (0.04)** Ego climate T1→ task orientation T1 0.02 (0.03) 0.01 (0.03) Task orientation T1→ MVPA T1 0.17 (0.04)** 0.15 (0.04)** * Ego orientation T1→ MVPA T1 0.07 (0.03) 0.07 (0.03)** MVPA T0→ MVPA T1 0.54 (0.03)** 0.56 (0.03)** Treatment effects Task treatment → task climate T1 ne 0.04 (0.03) Task treatment → ego climate T1 ne −0.07 (0.03)* Physical treatment → MVPA T1 ne 19 (0.02)** Correlation coefficients Task climate T0 - Ego climate T0 0.03 (0.03) 0.03 (0.03) Task climate T1 - Ego climate T1 0.17 (0.03)** 0.16 (0.03)** Task orientation T1 - Ego orientation T1 0.19 (0.03)** 0.18 (0.02)** Fit of the model χ 2(22) = 55.680 χ 2(14) = 32.676 p< .001 p= .003 CFI = 0.97 CFI = 0.98 TLI = 0.95 TLI = 0.98 RMSEA= 0.056 RMSEA= 0.044 90%, CI [0.05, 90%, CI [0.04, 0.07] 0.08] AIC= 13,602.010 AIC= 14,742.710 BIC= 13,764.452 BIC= 14,894.445 MVPA, moderate to vigorous physical activity; CFI, comparative fit index, TLI, Tucker Lewis index; RMSEA, root mean square error of approximation; AIC, Akaike Information Criterion; BIC, Bayes Information Criterion; ne, not estimated. * p < .05, ** p < .001. Standard deviations in parentheses.
effective in changing students’ MVPA behavior in the physical education context.10,12,13 Considering that the Sotkamo program provided increased MVPA opportunities only during the school days, the current increase in total MVPA should be seen as relatively high. The current finding provided important insights into the activity levels of secondary school students across the multilevel school-initiated program without additional physical education classes. This study introduced the potential for substantial methodological variation reported in the literature, when both psychological and physical treatments were provided concurrently across the school year. Taken together, the present and previous findings32,34,36,38,53 provide further impetus to advocate recess and breaks Journal of School Health
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during the school days as a process to improve students’ MVPA participation using the multilevel settings.30 It is noticeable that the program had a stronger effect on physical activity compared to students’ goal orientations. It is possible that structural changes in school context (extended break, access to sport facilities, and equipment supply) are easier to facilitate than motivational climate change in physical education classes. Although the study showed that the program decreased students’ perception of ego-involving climate and had a positive reducing effect on their ego-orientation, the treatments did not have a significant effect on students’ task orientation. This was unexpected, because previous intervention studies have shown that several school-based interventions were positively related to students’ task orientation in school physical education,23,25,40,54 MVPA engagement,55 and MVPA participation in school physical education.24 The baseline scores for task orientation in both experiment and control conditions could be considered to be relatively high, which may be reason why the change did not materialize. Alternatively, it may be that the program effect via task orientation was more difficult to verify. Perhaps, the effect should be measured using more specific MVPA measures to manifest changes in self-reported MVPA through task orientation. In this sense, the results did not provide complete support for the models of Vallerand27 and Weiss.19 This program focused on improving physical education instruction for all students across a relatively short period. Although, the period of investigation covered the whole academic year, students had only 1 allotted 90-minute physical education class per each week. In earlier studies task-involving motivational climate was manipulated across relatively intensive periods.23,25,29 For instance, in the study of Digelidis et al23 the experimental group had 3 45-minute classes per week for each student across the academic year. The intervention of Wallhead and Ntoumanis25 targeted a sport education group of 25 students, who received 8 60-minute basketball classes. Hence, the present finding may be a consequence of a relatively small number of classes undertaken during the school year. Perhaps, outcomes such as self-reported MVPA of at least 60 minutes per day including school breaks, out-of-school, and physical education classes would require a more specific measurement method for an appropriate effect via task orientation. Although, the program effect on students’ goal orientations was weak in the current study, several previous studies have revealed that school physical education was effective when based on taskinvolving motivational climate structures.20,22,23,25,26 Therefore, to enhance students’ MVPA engagement in physical education classes, the main objective should be increasing students’ task-involving climate.
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Limitations This program took place in Finland and may not be replicable equally in other international school contexts, for instance, considering mandatory regular breaks in Finnish comprehensive schools. Although the research plan included a treatment and control conditions the sampling process was not randomized and, therefore, the conclusions regarding cause and effect require careful scrutiny. In addition, MVPA was measured using self-report questionnaires. Researchers have advocated the usage of objective methods, such as, accelerometers and pedometers to strengthen the reliability and validity of MVPA assessments.46,56,57 However, the validity and reliability of the World Health Organization’s scale has been shown to be acceptable when measuring adolescents’ MVPA participation.58,59 Finally, treatment fidelity was not controlled for in this study. It is recommended that for future investigations, the teachers’ teaching practices could be observed and the students’ perceptions of teaching practices surveyed using several methods to standardize the practices as accurately as possible.
people. On the basis of previous and current results, schools should take advantage of breaks and recess periods as means to promote greater MVPA during the school days providing personalized and group activities to all students.
IMPLICATIONS FOR SCHOOL HEALTH It remains an unrealistic challenge for secondary physical education classes to provide young people with sufficient opportunities to achieve the recommended levels of daily MVPA.60 The results of this study yielded following practical implications for school communities and physical educators. Schools could provide increased opportunities for physical activities during school days, for instance a daily extended break of 30 minutes in addition to the lunch break and regular breaks. These structural changes are inexpensive to implement. Schools could allow students to have access to sport facilities during extended and regular breaks. These facilities may be unoccupied for most of the breaks or recess time, when more effective use is recommended. Schools could provide several personalized and group activities in addition to the regular physical education classes, such as ballgames and equipment supply. Students should be involved in organization, distribution, and storage. Although the effect of task-involving climate treatment was low in the current study, based on previous findings, the main objective of physical education classes should be increasing students’ perceived physical competence and intrinsic motivation to enhance students’ MVPA engagement.20,22,23,25,26
Conclusions Half of 11- to 15-year-olds in several Western countries exceed the sedentary behavior guideline of less than 2 hours of sedentary time per day from discretionary screen time. Computer and console games are problematic mainly for boys, especially on weekends.1 Regular and adequate levels of physical in children and youth improves cardiorespiratory and muscular fitness, bone health, coordination, and movement control, maintenances of a healthy body weight, and has been associated with higher cognitive skills in academic learning processes.4 Amounts of physical activity greater than 60 minutes on a daily basis provide additional health benefits.4 Therefore, it is an extremely important objective for schools, for instance, in the United States and Finland, to find effective strategies to increase youth’s MVPA levels, because patterns of activity in adulthood are often established during adolescence 2 and most students do not meet the current physical activity guidelines and exceed the recommended levels of sedentary behavior.4 The effect of the physical activity program was stronger on students’ physical activity compared to the effect on ego orientation. The findings of this study suggest that exposing students to additional physical activities across the school days and providing access to equipment and facilities during recess and breaks may be the most tangible way to increase their physical activity. Increased opportunities for school day MVPA have the potential to influence a large number of adolescents and are an efficient strategy for promoting regular physical activity among young 132
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Human Subjects Approval Statement This study was approved by the Ethical Committee of the University of Jyv¨askyl¨a, and parental consent to participate in the study was obtained for all students of the sample.
REFERENCES 1. World Health Organization. Global Recommendations on Physical Activity for Health. Available at: http://whqlibdoc.who. int/publications/2010/9789241599979_eng.pdf. Accessed November 5, 2013. 2. Telama R, Yang X, Viikari J, V¨alim¨aki I, Wanne O, Raitakari O. Physical activity from childhood to adulthood: a 21-year tracking study. Am J Prev Med. 2005;28(3):267-273. 3. U.S. Department of Health and Human Services. Physical Activity Guidelines for Americans. Available at: http://www. health.gov/paguidelines/pdf/paguide.pdf. Accessed October 1, 2013. 4. World Health Organization. Social Determinants of Health and Well-being among Young People: Health Behaviour in SchoolAged Children (HBSC) Study: International Report from the 2009/2010 Survey. Available at: http://www.euro.who. int/data/assets/pdf_file/0003/163857/Social-determinants-of-h ealth-and-well-being-among-young-people.pdf. Accessed November 5, 2013. •
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5. Coulter M, Woods C. An exploration of children’s perceptions and enjoyment of school-based physical activity and physical education. J Phys Act Health. 2011;8(5):645-654. 6. Institute of Medicine. Accelerating Progress in Obesity Prevention: Solving the Weight of the Nation. Consensus Report. Available at: http://www.iom.edu/ Reports/2012/AcceleratingProgress-in-Obesity-Prevention.aspx. Accessed May 12, 2013. 7. Sallis J, McKenzie T, Beets M, Beighle A, Erwin H, Lee S. Physical education’s role in public health: steps forward and backward over 20 years and HOPE for the future. Res Q Exerc Sport. 2012;83(2):125-135. 8. Sotkamo Physical Activity as Civil Skill Program 2010-2014. Available at: http://www.liikaha.fi/yhteystiedot/liikaha-hanke. Accessed November 6, 2013. 9. Nicholls J. The Competitive Ethos and Democratic Education. Cambridge, MA: Harvard University Press; 1989. 10. Sallis J, Owen N. Physical Activity and Behavioral Medicine. Thousand Oaks, CA: Sage; 1999. 11. Stokols D. Translating social ecological theory into guidelines for community health promotion. Am J Health Promot. 1996;10(4):282-298. 12. Murillo P, Garc´ıa B, Generelo L, et al. Promising schoolbased strategies and intervention guidelines to increase physical activity of adolescents. Health Educ Res. 2013;28(3):523-538. 13. van Sluijs E, McMinn A, Griffin S. Effectiveness of interventions to promote physical activity in children and adolescents: systematic review of controlled trials. BMJ. 2007;335:703. 14. Deci E, Ryan R. The ”what” and ”why” of goal pursuits: human needs and the self-determination of behavior. Psychol Inq. 2000;11(4):227-268. 15. Ames C. Achievement goal, motivational climate, and motivational processes. In: Roberts G, ed. Motivation in Sport and Exercise. Champaign, IL: Human Kinetics; 1992:161-176. 16. Roberts G. Understanding the dynamics of motivation in physical activity: the influence of achievement goals on motivational processes. In: Roberts G, ed. Advances in Motivation in Sport and Exercise. Champaign, IL: Human Kinetics; 2001:1-50. 17. Standage M, Duda J, Ntoumanis N. A model of contextual motivation in physical education: using constructs from selfdetermination and achievement goal theories to predict physical activity intentions. J Educ Psychol. 2003;95(1):97-110. 18. Duda J. Motivation in sport settings. A goal perspective approach. In: Smith D, Bar-Eli M, eds. Essential Readings in Sport and Exercise Psychology. Champaign, IL: Human Kinetics; 2007:78-93. 19. Weiss, M. Motivating kids in physical activity. President’s Council on Physical Fitness and Sports Research Digest. 2000;3(11):1-8. 20. Ferrer-Caja E, Weiss M. Predictors of intrinsic motivation among adolescent students in physical education. Res Q Exerc Sport. 2000;71(3):267-279. 21. Duda J, Balaguer I. Coach-created motivational climate. In: Jowett S, Lavallee D, eds. Social Psychology in Sport. Champaign, IL: Human Kinetics; 2007:117-130. 22. Wang J, Chatzisarantis N, Spray C, Biddle S. Achievement goal profiles in school physical education: differences in selfdetermination, sport ability beliefs, and physical activity. Br J Educ Psychol. 2002;72(3):433-445. 23. Digelidis N, Papaioannou A, Laparidis K, Christodoulidis T. A one-year intervention in 7th grade physical education classes aiming to change motivational climate and attitudes towards exercise. Psychol Sport Exerc. 2003;4(3):195-210. 24. Papaioannou A, Bebetsos E, Theodorakis Y, Christodoulidis T, Kouli O. Causal relationships of sport and exercise involvement with goal orientations, perceived competence and intrinsic motivation in physical education: a longitudinal study. J Sports Sci. 2006;24(4):367-382. 25. Wallhead T, Ntoumanis N. Effects of a Sport Education intervention on students’ motivational responses in physical education. J Teach Phys Educ. 2004;23(1):4-18.
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26. Moreno J. Goal orientations, motivational climate, discipline and physical self-perception related to the teacher’s gender, satisfaction and sport activity of a sample of Spanish adolescent physical education students. Int J Appl Sport Sci. 2005;17(2): 57-68. 27. Vallerand R. Toward a hierarchical model of intrinsic and extrinsic motivation. In: Zanna M, ed. Advances in Experimental Social Psychology. New York, NY: Academic Press; 1997:271-359. ˚ en ´ A, Watt A, Hagger M, Jaakkola T, Liukkonen J. 28. Grast Secondary school students’ physical activity participation across physical education classes - The Expectancy-Value Theory approach. Phys Educator. In press 2014;71(4). 29. Bowler M. The influence of the TARGET motivational climate structures on pupil physical activity levels during year 9 athletics lessons. British Educational Research Association Annual Conference. Manchester: University of Manchester; September 2-5, 2009. 30. Spence J, Lee R. Toward a comprehensive model of physical activity. Psychol Sport Exerc. 2003;4(1):7-24. 31. Sallis J, McKenzie T, Conway T, et al. Environmental interventions for eating and physical activity. A randomized controlled trial in middle schools. Am J Prev Med. 2003;24(3):209-217. 32. Carrell A, Clark R, Peterson S, Nemeth B, Sullivan J, Allen D. Improvement of fitness, body composition, and insulin sensitivity in overweight children in a school-based exercise program. A randomized, controlled study. Arch Pediatr Adolesc Med. 2005;159(10):963-968. 33. Fairclough S, Stratton G. Improving health-enhancing physical activity in girls’ physical education. Health Educ Res. 2005;20(4):448-457. 34. Jamner M, Spruijt-Metz D, Bassin S, Cooper D. A controlled evaluation of a school-based intervention to promote physical activity among sedentary adolescent females: project FAB. J Adolesc Health. 2004;34(4):279-289. 35. Verstraete S, Cardon G, De Clercq D, Bourdeaudhuij I. Increasing children’s physical activity levels during recess periods in elementary schools: the effects of providing game equipment. Eur J Public Health. 2006;16(4):415-419. 36. Webber L, Catellier D, Lytle L, et al. Promoting physical activity in middle school girls: trial of activity for adolescent girls. Am J Prev Med. 2008;34(3):173-184. 37. Ridgers N, Stratton G, Fairclough S. Physical activity levels of children during school playtime. Sports Med. 2006;36(4):359371. 38. Simon C, Wagner A, DiVita C, et al. Intervention centred on adolescents’ physical activity and sedentary behaviour (ICAPS): concept and 6-month results. Int J Obes Relat Metab Disord. 2004;28(3):96-103. 39. Tammelin T, Laine K, Turpeinen S. Physical Activity of School-aged Children. Research Reports on Sport and Health 272. Jyv¨askyl¨a: LIKES; 2013. 40. Jaakkola T, Liukkonen J. Changes in students’ self-determined motivation and goal orientation as a result of motivational climate intervention within high school physical education classes. Int J Sport Exerc Psychol. 2006;4(3):302-324. 41. Soini M, Liukkonen J, Watt A, Yli-Piipari S, Jaakkola T. Construct validity and internal consistency of the motivation climate in physical education scale. J Sports Sci Med. 2014;13(1):137-144. 42. Roberts G, Treasure D, Balague´ G. Achievement goals in sport: the development and validation of the Perception of Success Questionnaire. J Sports Sci. 1998;16(4):337-347. 43. Yli-Piipari S, Barkoukis V, Jaakkola T, Liukkonen J. The effect of physical education goal orientations and enjoyment in adolescent physical activity: a parallel process latent growth analysis. Sport Exerc Perform Psychol. 2013;2(1):15-31. 44. Currie C, Samdal O, Boyce W, Smith B. Health Behavior in SchoolAged Children: A WHO Cross-National Study. Research Protocol for the 2001-2002 Survey. Scotland: University of Edinburgh; 2002.
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54. Weigand D, Burton S. Manipulating achievement motivation in physical education by manipulating the motivational climate. Eur J Sport Sci. 2002;2(1):1-14. 55. Braithwaite R, Spray C, Warburton V. Motivational climate interventions in physical education: a meta-analysis. Psychol Sport Exerc. 2011;12(6):628-638. 56. Shephard R. Limits to the measurement of habitual physical activity by questionnaires. Br J Sports Med. 2003;37(3):197-206. 57. Troiano R. A timely meeting: objective measurement of physical activity. Med Sci Sports Exerc. 2005;37(11):487-489. 58. Booth M, Okely A, Chey T, Bauman A. The reliability and validity of the physical activity questions in the WHO health behaviour in schoolchildren (HBSC) survey: a population study. Br J Sports Med. 2001;35(4):263-267. 59. Vuori M, Ojala K, Tynj¨al¨a J, Villberg J, V¨alimaa R, Kannas L. Liikunta-aktiivisuutta koskevien kysymysten stabiliteetti WHOKoululaistutkimuksessa [Stability of the Finnish WHO physical activity questionnaire]. Liikunta & Tiede. 2005;42(1):39-46. 60. McKenzie T, Sallis J, Prochaska J, Conway T, Marshall S, Rosengard P. Evaluation of a two-year middle-school physical education intervention: M-SPAN. Med Sci Sports Exerc. 2004; 36(8):1382-1388.
45. Prochaska J, Sallis J, Long B. A physical activity screening measure for the use with adolescents in primary care. Arch Pediatr Adolesc Med. 2001;155(5):554-559. ˚ en ´ A, Watt A, Jaakkola T, Liukkonen J. Directly measured 46. Grast and self-reported physical activity in a sample of Finnish secondary school students. Adv Phys Edu. 2012;2(3):132-138. 47. Basic Education Act 27.11.1992/1174/§23. Helsinki, Finland: Ministry of Education and Culture; 1992. 48. Finnish National Board of Education. National Core Curriculum for Basic Education 2004. Vammala, Finland: Vammalan Kirjapaino Oy; 2004. ´ L, Muthen ´ B. Mplus User’s Guide. 6th ed. Los Angeles, 49. Muthen ´ & Muthen; ´ 1998-2010. CA: Muthen 50. Fan X, Thompson B, Wang L. The effects of sample size, estimation methods, and model specification on SEM fit indices. Struct Equ Model. 1999;6(1):56-83. 51. Schreiber J, Stage F, King J, Nora A, Barlow E. Reporting structural equation modeling and confirmatory factor analysis results: a review. J Educ Res. 2006;99(6):323-337. 52. Hu L, Bentler P. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model. 1999;6(1):1-55. 53. Ward D. School Policies on Physical Education and Physical Activity. Research Synthesis. Princeton, NJ: Robert Wood Johnson Foundation; 2011.
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Copyright of Journal of School Health is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
Effectiveness of School-Initiated Physical Activity Program on Secondary School Students’ Physical Activity Participation ´ , Meda SAMI YLI-PIIPARI, PhDb ANTHONY WATT, PhDc TIMO JAAKKOLA, PhDd JARMO LIUKKONEN, PhDe ˚ EN ARTO GRAST
ABSTRACT BACKGROUND: The promotion of physical activity and health has become a universal challenge. The Sotkamo Physical Activity as Civil Skill Program was implemented to increase students’ physical activity by promoting supportive psychological and physical school environment. The aim of this study was to evaluate the effectiveness of the school-initiated physical activity program on secondary school students’ self-reported physical activity. METHODS: The sample included 847 students (experimental condition school = 208, control school = 639) at the age of 12 to 14 years from northeast and central Finland. The program was conducted across 1 academic year and 2 measurement phases were carried out using self-report questionnaires in April 2011 and 2012. RESULTS: The findings highlighted that the program appeared to be effective as an approach to change the sharp decline in the pattern of Grade 7 students’ self-reported physical activity across 1 school year. Specifically, change in the experimental condition students’ self-reported physical activity was 13.4% higher compared the students in the control condition. CONCLUSION: On the basis of current findings, increased opportunities for school day physical activities have the potential to affect large number of students and are an efficient strategy for promoting regular physical activity. Keywords: exercise motivation; physical activity; physical education; program; secondary school. ˚ en A, Yli-Piipari S, Watt A, Jaakkola T, Liukkonen J. Effectiveness of school-initiated physical activity program on Citation: Grast´ secondary school students’ physical activity participation. J Sch Health. 2015; 85: 125-134. Received on November 29, 2013 Accepted on July 11, 2014
T
he World Health Organization has identified physical inactivity as the fourth highest risk factor for global mortality.1 Patterns of activity in adulthood are often established during adolescence, making this an important period for promoting physical activity.2 International guidelines propose that adolescents should engage in 60 minutes of daily moderate to vigorous physical activity (MVPA) to actualize health benefits optimally.3,4 Considering that less than one third of 15-year olds in countries such the US and Finland meet the current recommendation and approximately half of them exceed the sedentary behavior guideline of less than 2 hours of sedentary time per day from discretionary screen time, the promotion of
MVPA has become a universal challenge.5 To increase adolescents’ MVPA, scholars and institutions have advocated that schools could promote public health by increasing opportunities for daily activity and ensuring that students have an access to a high-quality school physical education.6,7 To address this, the European Union funded community program ‘‘Sotkamo Physical Activity as Civil Skill Program’’ was implemented to support the psychological and physical school environment in order to increase students’ daily MVPA.8 The program was developed based on attributes of the Achievement Goal Theory9 and the Social Ecological Model.10,11 Multilevel interventions have produced evidence of efficacy in changing physical
a Researcher, (agrasten@jyu.fi), Department of Sport Sciences, University of Jyvaskyla, PO Box 35, Jyvaskyla 40014, Finland. bAssistant Professor, ([email protected]), Department of Health and Sport Sciences, University of Memphis, 106 Fieldhouse, Memphis, TN 38152. c Senior Lecturer, ([email protected]), School of Education, Victoria University, PO Box 14428, Melbourne, Victoria 8001, Australia. dLecturer, (timo.jaakkola@jyu.fi), Department of Sport Sciences, University of Jyvaskyla, PO Box 35, Jyvaskyla 40014, Finland. e Professor, (jarmo.liukkonen@jyu.fi), Department of Sport Sciences, University of Jyvaskyla, PO Box 35, Jyvaskyla 40014, Finland.
Address correspondence to: Arto Gr˚ast´en, Researcher, (agrasten@jyu.fi), Department of Sport Sciences, University of Jyvaskyla, PO Box 35, Jyvaskyla 40014, Finland.
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activity behavior.10,12,13 The central assumption of the current program was that an individual’s behavior can be influenced by manipulating the psychological and physical environments. The Achievement Goal Theory recognizes the role of social environment, but also provides a plausible model to facilitate understanding the relationship between the psychological environment and student behavior in physical education. In turn, the Social Ecological Model covers the multilevel relationships between individual characteristics, social environment, physical environment, and physical activity behavior.10 In accordance with these conceptual perspectives, the current program was designed to promote an increase in secondary school students’ physical activity by modifying their task-involving climate in physical education classes and physical school environment. The task-involving climate treatment was grounded in the Achievement Goal Theory9 and designed to influence students’ task orientation, and subsequently MVPA through supportive task-involving motivational climate in regular physical education classes. The focal tenet of the theory is that there are 2 key concepts for defining competence and success in activity, namely task (learning) and ego (performance) orientation. Task orientation corresponds a perception of self-referenced ability, such as effort and learning. The focus of activity involvement is in mastering the current tasks and improvement, resulting in increased physical education motivation.9,14 This means that an individual has adopted personal improvement and learning (task orientation) as criteria for success.15 In contrast, ego-oriented individuals ascribe success to other referenced criteria such as ability, and the main objective of engagement in an activity is to demonstrate normative competence and outperform others.9,16,17 Thus, the perception of competence is not depending on their own control.18 Additionally, these 2 conceptualizations of competence and success are also described as the situational goal structure, namely perceived motivational climate, which reflects students’ perceptions of the emphasis placed on developing (task-involving climate) or demonstrating normative competence (ego-involving climate) by social agents.15 Positive development of physical education motivation is most likely to occur when task-involving climate is emphasized.15 According to the model of Weiss19 physical education teachers have a tremendous impact on student’s physical activity behavior through the regulation of motivational climate via feedback, reinforcement, modeling, and structuring of physical activity opportunities. Perceptions of taskinvolving climate in physical education can influence students’ perceptions of task orientation19,20 whereas an ego-involving climate advances social comparison and ego orientation.21 Teachers who structure a motivational climate that encourages task orientation 126
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are likely to positively influence students’ MVPA in physical education,19,20 MVPA outside physical education classes,22 out-of-school MVPA,23 physical activity participation,24 perceived effort and persistence,20,25 and perceptions of physical condition in physical education classes.26 For instance, in a yearlong intervention in Greek junior high school, the experimental school students had higher task orientaton, lower ego orientation, and more positive attitudes toward exercise than the control group, when a task-involving climate in physical education was supported.23 Wallhead and Ntoumanis suggested that the curriculum associated with sport education may increase the perceptions of motivational climate, and in so doing, enchance task orientation toward physical education in high school students.25 For instance, according to Vallerand’s27 proposed motivational climate model, social factors (motivational climate) result in positive consequences (physical activity) through psychological mediator (task orientation) and exercise motivation in physical education context. Because, the quantity of school physical education classes cannot be dramatically increased, improving content and quality is a feasible practice to use in physical education as a mean ˚ en ´ et al28 highto enhance students’ daily MVPA. Grast lighted that MVPA in physical education classes was linked to out-of-school MVPA, especially for boys. Therefore, the psychological mechanism underlying physical activity behavior19,27 has yet to be investigated to clarify the long-term effects of task-involving climate treatment on students’ task orientation and daily MVPA.29 The physical school environment treatment was focused on the students’ physical environment at the school with the objective to increase opportunities for physical activity during their attendance. The intervention’s adoption of the social ecological model can be broadly divided into intra-individual and inter-individual.10 Intra-individual influences might include individual attributes, beliefs, attitudes, and behaviors, whereas inter-individual influences might include environmental, social, and cultural contexts.10 For example, change at an intra-individual level of influence might include improving attitudes toward physical activity, thereby increasing the probability that physical activity increases. Change at an inter-individual level of influence might include providing facilities for activities, also increasing physical activity levels.30 Sallis et al31 reported that an inter-individual intervention based on the ecological model (including physical education classes’ structural changes, organized activities, and access to equipment throughout school day) increased middle school student’s daily MVPA. Furthermore, many school-based interventions highlighted that an effective way to counter low MVPA levels is to enhance MVPA with an increase in frequency and duration of physical activities in physical •
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Figure 1. The Path Model of the Theorized Relationships Between Motivational Climate, Goal Orientations, SelfReported MVPA, and Hypothesized Treatment Effects From T0 to T1
education,32-34 in the school environment during nonacademic periods,12,35,36 and redesigning school yard.37,38 The review of interventions previously considered introduces a large variation of methods to increase MVPA during the school day. However, Tammelin, Laine, and Turpeinen noted, especially during school-based interventions, students’ total MVPA may decrease, if students reduce their after school activity, respectively.39 Therefore, it is important to study, whether total MVPA including activities during the school day and out-of-school is enhanced as an outcome of the physical school environment program. Thise study aimed to evaluate the effectiveness of school-initiated physical activity program that was implemented at the secondary school level across 1 school year (Figure 1). On the basis of previously established relationships,10,23,24,40 the effectiveness of the program, including task-involving climate and physical school environment treatments, on students’ MVPA was tested. It was hypothesized that the manipulation of physical education students’ motivational climate has an impact on their physical activity through their motivational orientations.19,27 In addition, to determine if task-involving climate or physical school environment treatment had a stronger effect on students’ self-reported MVPA, the effect sizes were examined.
METHODS Participants and Setting The sample comprised 847 students (422 girls, 425 boys) aged 12 to 14 years from 2 school districts. The experimental condition school (N = 208) and 4 control schools (N = 639) were recruited from northeast and central Finland through direct contact with school principals. Both school districts were typical Finnish midsized cities with 96% of students being Caucasian. All Grade 7 students in each class were invited to participate and 75% (experimental school) and 73% Journal of School Health
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(control schools) of the students asked were able to return both the student consent and parental consent. Participation in this study was voluntary and no extra credit was awarded for participation. Instruments Motivational climate was measured using the Motivation Climate in Physical Education Scale,41 which consists of 2 subscales representing task- and egoinvolving climate. The individual item stem used in the measure was ‘‘In my physical education classes . . . ’’ Both the task-involving climate dimension (‘‘It is important for students to try their best in physical education classes’’), and the ego-involving climate dimension (‘‘It is important for students to succeed better than others in physical education classes’’) consisted of 4 items. Responses were indicated on a 5-point Likert-scale ranging from strongly disagree (1) to strongly agree (5). Previous confirmatory factor analysis supported the construct validity (Tucker Lewis index [TLI] = 0.97, comparative fit index [CFI] = 0.97, root mean square error of approximation [RMSEA] = 0.037) and internal consistency (Cronbach’s α > 0.78) of the subscales for Finnish secondary school students.41 Achievement goal orientations were analyzed using the Perception of Success Questionnaire.42 The scale consists of 12 items, 6 measuring task orientation (‘‘I really improve’’), and 6 ego orientation ( ‘‘I do better than others’’). Items were rated on a 5-point Likert-scale ranging from strongly disagree (1) to strongly agree (5). The questionnaire used in the current study had the individual item stem of ‘‘I feel most successful in physical education lessons, when. . . . ’’ According to Yli-Piipari et al43 a confirmatory factor analysis supported the construct validity (TLI = 0.97, CFI = 0.97, RMSEA = 0.03) and internal consistency of the scale for a sample of Finnish secondary school students was acceptable (Cronbach’s α > 0.88). Self-reported MVPA was assessed using the Health Behavior in School-aged Children Research Protocol.44 The scale consists of 2 items rated on an 8-point response scale (0 to 7 days of the week) (‘‘When you think about your typical week, on how many days are you physically active for a total of at least 60 minutes per day?’’). The mean scores of the 2 items were used as MVPA scores. Prochaska et al45 reported that for a sample of 138 US children and adolescents with a mean age of 12.1 years, the moderate to vigorous MVPA items were reliable (ICC = 0.77) and had moderate correlation (r = .40) with accelerometer data in a study based on a 5-day data collection period. Similarly, Pearson’s correlation coefficients between self-reported MVPA and accelerometer data scores ranged from weak (r = .32) to strong (r = .66) when self-report scores were assessed using this protocol in the sample of 96 Finnish secondary school students for a 7-day period.46
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Procedure This study was implemented across the academic year 2011-2012. The 2 data collection sessions were conducted in April 2011 (T0 = Grade 7) and 2012 (T1 = Grade 8). Subjects completed the questionnaires under the supervision of the researchers during 45minute classes, typically held in the classroom or gym. The subjects were advised to ask for help if confused concerning either the instructions or the clarity of a particular item. To minimize students’ tendency to give socially desirable responses, students were encouraged to answer honestly and were assured that their responses were confidential. The students were told that their involvement was voluntary and could withdraw at any time as subjects in the study. All Finnish secondary school students have 2 45minute physical education classes per week, usually combined as 1 90-minute class. The majority of schools have sex groups in physical education classes. The recess breaks, average 30 breaks (at least 10 minutes) per week, and daily lunch break (30 minutes) are mandatory to all students.47 Typically, secondary school students spend their recess breaks indoors, mainly accumulating sedentary time.39 The control group was taught following the guidelines of the Finnish national curriculum;48 no task-involving climate support or extra physical activities were provided. The experimental condition school students received the treatments across the academic year 20112012 (Table 1). The task-involving climate treatment comprised supplementary teacher training and task-involving climate support in regular physical education classes. Four physical education teachers from the experimental school participated in four 90-minute workshops to extend and develop their current physical education teaching practices. The teacher workshops were organized during the academic year 2010-2011 by the project leaders. The workshops were a part of teacher’s collective bargaining agreement of supplementary training. Teachers were informed about the goals, methods, and procedures of the program and subsequent treatment. The workshops and treatment had the following features: (1) Task-involving teaching practices; students work together within a small cooperative group structure, students are responsible for setting up equipment, during lesson time students dictate the rate of progression through specific practices, (2) Task orientation support; evaluation emphasizes individual improvement, (3) Improving students personal skills; students choose practices from a range of offered practices with the different skill requirements, more activity, and less waiting during physical education classes, and (4) Positive feedback and encouragement; recognition and feedback is based on the individual progress. The teachers 128
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completed the structured questionnaires regarding the self-evaluation on task-involving teaching practices. The physical school environment treatment focused on developing the physical environment of the school and providing equipment. The activities were organized during extended and regular breaks. The students were given a lot of autonomy when selecting activities. The recess activities and treatment included the following actions: (1) Extended break; daily extended break of 30 minutes in addition to the lunch break and regular breaks, (2) Access to fitness hall; students were allowed to use fitness facilities during the extended and regular breaks to exercise or play games, (3) Controlled ballgames; students were responsible for setting up ballgames and refereeing during extended breaks (5 days × 30 minutes × 12 weeks) under the teachers’ supervision, (4) Equipment supply; exercise equipment was available to all students during the extended and regular breaks, students were responsible for setting up equipment. The project leaders monitored the school breaks twice a month. Data Analyses Data analyses were conducted in the following order. First, descriptive analyses to determine means, standard deviations, Pearson’s correlation coefficients, and Crohnbach’s alpha were conducted. Second, independent t tests were performed to examine if the experimental and control conditions differed in motivational climate, goal orientation, or self-reported MVPA. Third, a 2 (treatment: yes, no) × 2 (time: pretest, posttest) analysis of covariance (ANCOVA) was employed to examine whether subjects who received the treatment displayed changes in perceptions of motivational climate and MVPA participation. Fourth, 2 path analyses were conducted to test the study hypotheses: Model 0 - a default model with hypothesized relationships between variables without the treatment effects (Figure 1); Model 1 - the effect of the program was tested, in which treatments (task-involving climate and physical school environment) were added as covariates to regress students’ perception of task- and ego-involving climate and self-reported MVPA. All analyses were performed within a structural equation modeling framework using the Mplus statistical package version 6.1.49 CFI, TLI, and Root Mean Square Residual (RMSR) were utilized as a means of evaluating the fit of the models because previous research has shown that these fit indices displayed restricted random variation when utilized within a range of conditions associated with model misspecification, sample size, and estimation method.50,51 A model fits the data well when the p-value associated with the chi-square test is nonsignificant. A cutoff
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Table 1. The Procedures of School-initiated Physical Activity Program Object
Method
Duration/Amount
Time
Evaluation
1× 90minute
September 2010
Structured self-report form to teachers, November 2011 and April 2012
1× 90minute 1× 90minute
August 2011 November 2011
1× 90minute
November 2011
5× 30minutes × 38weeks
September 2011 to May 2013
(2) Access to fitness hall
5× 30minutes × 38weeks
September 2011 to May 2013
(3) Controlled ballgames (1) Dance pad
5× 30minutes × 12weeks 2 pieces
(2) Floor hockey stick (3) Volleyball (4) Basketball (5) Ball bouncer stick (6) Table tennis table (7) Table tennis racket (8) Table tennis ball (9) Disc golf disc
30 pieces 2 pieces 2 pieces 20 pieces 6 pieces 12 pieces 100 pieces 6 pieces
Task-involving climate treatment Teacher workshops (1) Lecture: Task-involving teaching practices (2) Demo: Task orientation support (3) Demo: Improving students’ personal skills (4) Demo: Positive feedback and encouragement Physical school environment treatment Recess activities (1) Extended break
Equipment supply
value close and above 0.95 for the CFI and TLI and a cutoff value under 0.06 for RMSEA were considered as a good fit between the hypothesized model and the observed data.52
RESULTS Exploratory Analyses Pearson’s correlation coefficients, means, standard deviations, and Cronbach’s alpha are presented in Table 2. For both experiment and control conditions, correlation coefficients showed either negligible or weak positive relationships between task-involving climate and ego-involving climate, weak to moderate positive relationships between task and ego orientation, and moderate and strong positive relationships between self-reported MVPA at Grades 7 and 8. The Bonferroni-corrected (significance level of 0.006) independent t tests showed that the control group had higher levels of ego-involving climate (T0: t[754] = 40.06, p < .001, d = 0.30; T1: t[834] = 2.93, p = .004, d = 0.20), ego orientation (t[845] = 2.72, p < .001, d = 0.19), and MVPA (t[764] = 2.77, p < .01, d = 0.20). In other words, the students in control condition had a higher ego-involving motivational climate in physical education classes and total MVPA at the baseline measures than students in experimental condition. Additionally, higher ego-involving climate and ego orientation were detected in follow-up measures for the control condition. Journal of School Health
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Teachers informed project leader twice a month; Project leader monitored the school breaks twice a month
Students responsible for setting up equipment under teachers’ supervision
ANCOVAs showed that there was a significant treatment effect on ego-involving climate (F[2,757] = 15.10, p < .001, η2 = 0.02) and MVPA (F[2,763] = 15.56, p < .001, η2 = 0.20) but no statistically significant effect on task-involving climate (F[2,758] = 2.93, p = .088, η2 < 0.01). The examination of the pre- and posttest values showed that experimental condition students’ self-reported MVPA increased, whereas control condition students’ MVPA decreased across 1 year of program, respectively. Main Analyses To test the theorized relationships of the research variables without treatment effects Model 0 was implemented (Figure 1). Although the χ 2 test achieved statistical significance (typical in case of large sample sizes) the rest of the fit indicators suggested an appropriate data fit: χ 2 (22) = 55.680, p < .001, CFI = 0.97, TLI = 0.95, RMSEA = 0.056, 90%, CI [0.05, 0.08]. The study showed that the perceptions of taskinvolving climate (β = 0.49), ego-involving climate (β = 0.27) climate, and self-reported MVPA (β = 0.54) at the baseline (T0) were significant predictors of subsequent (T1) perceptions of task- and ego-involving climate and self-reported MVPA. In addition, expected relationships emerged, because task-involving climate predicted task orientation (β = 0.60), ego-involving climate ego orientation (β = 0.37), and task orientation predicted MVPA (β = 0.17). The sizes of the effects were weak to moderate explaining 16% to 37% of
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Table 2. Summary of Intercorrelations, Means, Standard Deviations, and Cronbach’s Alphas for Self-Reported MVPA, Goal Orientations, and Motivational Climate Variables 1. Self-reported MVPA (T0) 2. Self-reported MVPA (T0) 3. Task orientation (T1) 4. Ego orientation (T1) 5. Task-involving climate (T0) 6. Task-involving climate (T1) 7. Ego-involving climate (T0) 8. Ego-involving climate (T1) M SD α
1 — 0.47** 0.11* 0.09* 0.13* 0.11* 0.08* 0.001 4.24 1.58 0.91
2
3
0.85**
0.23**
— 0.27** 0.23** 0.14** 0.27** 0.05 0.08* 3.86 1.75 0.91
0.25** — 0.34** 0.33** 0.60** −0.06 0.19** 3.81 0.85 0.94
4 0.08 0.05 0.39** — 0.02 0.18** 0.18*** 0.39** 3.04 0.95 0.95
5
6
0.08 0.11 0.26** −0.12 — 0.44** 0.10* 0.05 3.59 0.74 0.99
0.25** 0.26** 0.66** 0.20* 0.48** — 0 0.28** 3.53 0.81 0.7
7 0.14 0.19* −0.09 0.09 −0.13 −0.1 — 0.25** 2.99 0.72 0.98
8 0.08 0.06 0.09 0.35** −0.20* 0.19* 0.26** — 3.04 0.83 0.75
M 3.90a 4.07 3.77 2.76a 3.64 3.65 2.76a 2.85a
SD 1.51 1.44 0.75 0.87 0.63 0.67 0.62 0.76
α na na 0.93 0.94 0.79 0.8 0.75 0.81
MVPA, moderate to vigorous physical activity; SD, standard deviation; na, not available. *** p < .001, ** p < .01, * p < .05, a higher means of the control group at the Bonferroni-corrected significance level (p = .006). Note 1. Intercorrelations for the experimental group (n = 208) are presented above the diagonal and intercorrelations for the control group (n = 639) are presented below the diagonal. Means, standard deviations, and Cronbach’s alpha for the experimental group are presented in vertical columns and means, deviations, and Cronbach’s alpha for the control group are presented in horizontal columns. Note 2. Cronbach’s alphas for the experimental group’s measurements (T0): Self-reported MVPA (0.92), task orientation (0.85), ego orientation (0.40), task-involving climate (0.65), and ego-involving climate (0.40). Note 3. Cronbach’s alphas for the control group’s measurements (T0): Self-reported MVPA (0.67), task orientation (0.64), ego orientation (0.62), task-involving climate (0.65), and ego-involving climate (0.42).
the variance of students’ task and ego orientation and MVPA (R2 task = .37, R2 ego = .16, R2 MVPA = .34). To examine the effects of the program on Grade 7 students’ self-reported MVPA over a 1-year time period, Model 1 was estimated, in which treatment effects (task-involving climate treatment and physical school environment treatment) were added into the Model 0 as covariates. The model fit was within acceptable limits: χ 2 (16) = 32.676, p = .003, CFI = 0.98, TLI = 0.98, RMSEA = 0.044, 90%, CI [0.04, 0.07]. The results showed that the program had a positive effect on students’ self-reported MVPA. Regression coefficients showed that program had a weak negative influence on ego-orientation (β = −0.07), no influence on task-orientation (β = 0.04), and moderate effect on self-reported MVPA (β = 0.19). The effect sizes were moderate (R2 task = .37, R2 ego = .16, R2 MVPA = .39). Taken together, the model including both taskinvolving motivational climate treatment (actions to increase physical activity through manipulation of motivational climate in physical education) and physical school environment treatment (providing students increased opportunities for school-day physical activities) indicated to be an effective strategy to prohibit declining levels of students’ MVPA participation across 1-year period. However, the closer examination of the effects emerged that the treatments yielded only a small negative effect on students’ ego orientation. All fit indices and parameter estimates are presented in Table 3.
program on Grade 7 students’ self-reported MVPA across 1 school year. According to the findings presented in the previous literature, task-involving motivational climate has been evidenced to increase students’ task orientation in physical education classes, however, it was still unclear whether students’ total daily MVPA can be increased by promoting taskinvolving climate and the physical school environment without additional physical education classes. This study examined the treatment effects using the task-involving motivational climate model,19,27 in which task-involving motivational climate in addition to extra physical activities was assumed to have long-term effects on students’ total MVPA via goal orientations rather than direct short-term effects on students’ MVPA in physical education classes. The Sotkamo Physical Activity as Civil Skill Program8 appeared to be effective as an approach to change the sharp decline in the pattern of Grade 7 students’ MVPA across the school year. Specifically, change in the experimental condition students’ total MVPA was 13.4% higher compared to MVPA of the students in the control condition across 1 year of program. For comparison, Simon et al38 reported that the additional opportunities for MVPA led to increases of 18% in the active participation of US middle school students over a 4-year intervention including in-school and out-of-school activities. A similar Finnish report detailed that secondary school students’ daily MVPA could be sustained at the same level, when longer school breaks, games during breaks, equipment supply, and an extra 45-minute physical education class after school days were provided.39 Several previous multilevel interventions have been evidenced as being
DISCUSSION The aim of the study was to examine the effectiveness of the school-initiated physical activity 130 •
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Table 3. Regression and Correlation Coefficients for the Path Models
Parameter Estimates
Model 0 Standardized Values (β)
Model 1 Standardized Values (β)
Regression coefficients 0.48 (0.03)** Task climate T0→ task climate T1 0.49 (0.03)** Task climate T0→ ego climate T1 0.01 (0.04) −0.02 (0.04) Ego climate T0) → ego climate T1 0.27 (0.05)** 0.27 (0.05)** Ego climate T0→ task climate T1 −0.05 (0.04) −0.05 (0.04) Task climate T1→ task orientation T1 0.60 (0.03)** 0.61 (0.03)** Task climate T1→ ego orientation T1 0.09 (0.04) 0.05 (0.04) Ego climate T1→ ego orientation T1 0.37 (0.03)** 0.36 (0.04)** Ego climate T1→ task orientation T1 0.02 (0.03) 0.01 (0.03) Task orientation T1→ MVPA T1 0.17 (0.04)** 0.15 (0.04)** * Ego orientation T1→ MVPA T1 0.07 (0.03) 0.07 (0.03)** MVPA T0→ MVPA T1 0.54 (0.03)** 0.56 (0.03)** Treatment effects Task treatment → task climate T1 ne 0.04 (0.03) Task treatment → ego climate T1 ne −0.07 (0.03)* Physical treatment → MVPA T1 ne 19 (0.02)** Correlation coefficients Task climate T0 - Ego climate T0 0.03 (0.03) 0.03 (0.03) Task climate T1 - Ego climate T1 0.17 (0.03)** 0.16 (0.03)** Task orientation T1 - Ego orientation T1 0.19 (0.03)** 0.18 (0.02)** Fit of the model χ 2(22) = 55.680 χ 2(14) = 32.676 p< .001 p= .003 CFI = 0.97 CFI = 0.98 TLI = 0.95 TLI = 0.98 RMSEA= 0.056 RMSEA= 0.044 90%, CI [0.05, 90%, CI [0.04, 0.07] 0.08] AIC= 13,602.010 AIC= 14,742.710 BIC= 13,764.452 BIC= 14,894.445 MVPA, moderate to vigorous physical activity; CFI, comparative fit index, TLI, Tucker Lewis index; RMSEA, root mean square error of approximation; AIC, Akaike Information Criterion; BIC, Bayes Information Criterion; ne, not estimated. * p < .05, ** p < .001. Standard deviations in parentheses.
effective in changing students’ MVPA behavior in the physical education context.10,12,13 Considering that the Sotkamo program provided increased MVPA opportunities only during the school days, the current increase in total MVPA should be seen as relatively high. The current finding provided important insights into the activity levels of secondary school students across the multilevel school-initiated program without additional physical education classes. This study introduced the potential for substantial methodological variation reported in the literature, when both psychological and physical treatments were provided concurrently across the school year. Taken together, the present and previous findings32,34,36,38,53 provide further impetus to advocate recess and breaks Journal of School Health
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during the school days as a process to improve students’ MVPA participation using the multilevel settings.30 It is noticeable that the program had a stronger effect on physical activity compared to students’ goal orientations. It is possible that structural changes in school context (extended break, access to sport facilities, and equipment supply) are easier to facilitate than motivational climate change in physical education classes. Although the study showed that the program decreased students’ perception of ego-involving climate and had a positive reducing effect on their ego-orientation, the treatments did not have a significant effect on students’ task orientation. This was unexpected, because previous intervention studies have shown that several school-based interventions were positively related to students’ task orientation in school physical education,23,25,40,54 MVPA engagement,55 and MVPA participation in school physical education.24 The baseline scores for task orientation in both experiment and control conditions could be considered to be relatively high, which may be reason why the change did not materialize. Alternatively, it may be that the program effect via task orientation was more difficult to verify. Perhaps, the effect should be measured using more specific MVPA measures to manifest changes in self-reported MVPA through task orientation. In this sense, the results did not provide complete support for the models of Vallerand27 and Weiss.19 This program focused on improving physical education instruction for all students across a relatively short period. Although, the period of investigation covered the whole academic year, students had only 1 allotted 90-minute physical education class per each week. In earlier studies task-involving motivational climate was manipulated across relatively intensive periods.23,25,29 For instance, in the study of Digelidis et al23 the experimental group had 3 45-minute classes per week for each student across the academic year. The intervention of Wallhead and Ntoumanis25 targeted a sport education group of 25 students, who received 8 60-minute basketball classes. Hence, the present finding may be a consequence of a relatively small number of classes undertaken during the school year. Perhaps, outcomes such as self-reported MVPA of at least 60 minutes per day including school breaks, out-of-school, and physical education classes would require a more specific measurement method for an appropriate effect via task orientation. Although, the program effect on students’ goal orientations was weak in the current study, several previous studies have revealed that school physical education was effective when based on taskinvolving motivational climate structures.20,22,23,25,26 Therefore, to enhance students’ MVPA engagement in physical education classes, the main objective should be increasing students’ task-involving climate.
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Limitations This program took place in Finland and may not be replicable equally in other international school contexts, for instance, considering mandatory regular breaks in Finnish comprehensive schools. Although the research plan included a treatment and control conditions the sampling process was not randomized and, therefore, the conclusions regarding cause and effect require careful scrutiny. In addition, MVPA was measured using self-report questionnaires. Researchers have advocated the usage of objective methods, such as, accelerometers and pedometers to strengthen the reliability and validity of MVPA assessments.46,56,57 However, the validity and reliability of the World Health Organization’s scale has been shown to be acceptable when measuring adolescents’ MVPA participation.58,59 Finally, treatment fidelity was not controlled for in this study. It is recommended that for future investigations, the teachers’ teaching practices could be observed and the students’ perceptions of teaching practices surveyed using several methods to standardize the practices as accurately as possible.
people. On the basis of previous and current results, schools should take advantage of breaks and recess periods as means to promote greater MVPA during the school days providing personalized and group activities to all students.
IMPLICATIONS FOR SCHOOL HEALTH It remains an unrealistic challenge for secondary physical education classes to provide young people with sufficient opportunities to achieve the recommended levels of daily MVPA.60 The results of this study yielded following practical implications for school communities and physical educators. Schools could provide increased opportunities for physical activities during school days, for instance a daily extended break of 30 minutes in addition to the lunch break and regular breaks. These structural changes are inexpensive to implement. Schools could allow students to have access to sport facilities during extended and regular breaks. These facilities may be unoccupied for most of the breaks or recess time, when more effective use is recommended. Schools could provide several personalized and group activities in addition to the regular physical education classes, such as ballgames and equipment supply. Students should be involved in organization, distribution, and storage. Although the effect of task-involving climate treatment was low in the current study, based on previous findings, the main objective of physical education classes should be increasing students’ perceived physical competence and intrinsic motivation to enhance students’ MVPA engagement.20,22,23,25,26
Conclusions Half of 11- to 15-year-olds in several Western countries exceed the sedentary behavior guideline of less than 2 hours of sedentary time per day from discretionary screen time. Computer and console games are problematic mainly for boys, especially on weekends.1 Regular and adequate levels of physical in children and youth improves cardiorespiratory and muscular fitness, bone health, coordination, and movement control, maintenances of a healthy body weight, and has been associated with higher cognitive skills in academic learning processes.4 Amounts of physical activity greater than 60 minutes on a daily basis provide additional health benefits.4 Therefore, it is an extremely important objective for schools, for instance, in the United States and Finland, to find effective strategies to increase youth’s MVPA levels, because patterns of activity in adulthood are often established during adolescence 2 and most students do not meet the current physical activity guidelines and exceed the recommended levels of sedentary behavior.4 The effect of the physical activity program was stronger on students’ physical activity compared to the effect on ego orientation. The findings of this study suggest that exposing students to additional physical activities across the school days and providing access to equipment and facilities during recess and breaks may be the most tangible way to increase their physical activity. Increased opportunities for school day MVPA have the potential to influence a large number of adolescents and are an efficient strategy for promoting regular physical activity among young 132
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Human Subjects Approval Statement This study was approved by the Ethical Committee of the University of Jyv¨askyl¨a, and parental consent to participate in the study was obtained for all students of the sample.
REFERENCES 1. World Health Organization. Global Recommendations on Physical Activity for Health. Available at: http://whqlibdoc.who. int/publications/2010/9789241599979_eng.pdf. Accessed November 5, 2013. 2. Telama R, Yang X, Viikari J, V¨alim¨aki I, Wanne O, Raitakari O. Physical activity from childhood to adulthood: a 21-year tracking study. Am J Prev Med. 2005;28(3):267-273. 3. U.S. Department of Health and Human Services. Physical Activity Guidelines for Americans. Available at: http://www. health.gov/paguidelines/pdf/paguide.pdf. Accessed October 1, 2013. 4. World Health Organization. Social Determinants of Health and Well-being among Young People: Health Behaviour in SchoolAged Children (HBSC) Study: International Report from the 2009/2010 Survey. Available at: http://www.euro.who. int/data/assets/pdf_file/0003/163857/Social-determinants-of-h ealth-and-well-being-among-young-people.pdf. Accessed November 5, 2013. •
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5. Coulter M, Woods C. An exploration of children’s perceptions and enjoyment of school-based physical activity and physical education. J Phys Act Health. 2011;8(5):645-654. 6. Institute of Medicine. Accelerating Progress in Obesity Prevention: Solving the Weight of the Nation. Consensus Report. Available at: http://www.iom.edu/ Reports/2012/AcceleratingProgress-in-Obesity-Prevention.aspx. Accessed May 12, 2013. 7. Sallis J, McKenzie T, Beets M, Beighle A, Erwin H, Lee S. Physical education’s role in public health: steps forward and backward over 20 years and HOPE for the future. Res Q Exerc Sport. 2012;83(2):125-135. 8. Sotkamo Physical Activity as Civil Skill Program 2010-2014. Available at: http://www.liikaha.fi/yhteystiedot/liikaha-hanke. Accessed November 6, 2013. 9. Nicholls J. The Competitive Ethos and Democratic Education. Cambridge, MA: Harvard University Press; 1989. 10. Sallis J, Owen N. Physical Activity and Behavioral Medicine. Thousand Oaks, CA: Sage; 1999. 11. Stokols D. Translating social ecological theory into guidelines for community health promotion. Am J Health Promot. 1996;10(4):282-298. 12. Murillo P, Garc´ıa B, Generelo L, et al. Promising schoolbased strategies and intervention guidelines to increase physical activity of adolescents. Health Educ Res. 2013;28(3):523-538. 13. van Sluijs E, McMinn A, Griffin S. Effectiveness of interventions to promote physical activity in children and adolescents: systematic review of controlled trials. BMJ. 2007;335:703. 14. Deci E, Ryan R. The ”what” and ”why” of goal pursuits: human needs and the self-determination of behavior. Psychol Inq. 2000;11(4):227-268. 15. Ames C. Achievement goal, motivational climate, and motivational processes. In: Roberts G, ed. Motivation in Sport and Exercise. Champaign, IL: Human Kinetics; 1992:161-176. 16. Roberts G. Understanding the dynamics of motivation in physical activity: the influence of achievement goals on motivational processes. In: Roberts G, ed. Advances in Motivation in Sport and Exercise. Champaign, IL: Human Kinetics; 2001:1-50. 17. Standage M, Duda J, Ntoumanis N. A model of contextual motivation in physical education: using constructs from selfdetermination and achievement goal theories to predict physical activity intentions. J Educ Psychol. 2003;95(1):97-110. 18. Duda J. Motivation in sport settings. A goal perspective approach. In: Smith D, Bar-Eli M, eds. Essential Readings in Sport and Exercise Psychology. Champaign, IL: Human Kinetics; 2007:78-93. 19. Weiss, M. Motivating kids in physical activity. President’s Council on Physical Fitness and Sports Research Digest. 2000;3(11):1-8. 20. Ferrer-Caja E, Weiss M. Predictors of intrinsic motivation among adolescent students in physical education. Res Q Exerc Sport. 2000;71(3):267-279. 21. Duda J, Balaguer I. Coach-created motivational climate. In: Jowett S, Lavallee D, eds. Social Psychology in Sport. Champaign, IL: Human Kinetics; 2007:117-130. 22. Wang J, Chatzisarantis N, Spray C, Biddle S. Achievement goal profiles in school physical education: differences in selfdetermination, sport ability beliefs, and physical activity. Br J Educ Psychol. 2002;72(3):433-445. 23. Digelidis N, Papaioannou A, Laparidis K, Christodoulidis T. A one-year intervention in 7th grade physical education classes aiming to change motivational climate and attitudes towards exercise. Psychol Sport Exerc. 2003;4(3):195-210. 24. Papaioannou A, Bebetsos E, Theodorakis Y, Christodoulidis T, Kouli O. Causal relationships of sport and exercise involvement with goal orientations, perceived competence and intrinsic motivation in physical education: a longitudinal study. J Sports Sci. 2006;24(4):367-382. 25. Wallhead T, Ntoumanis N. Effects of a Sport Education intervention on students’ motivational responses in physical education. J Teach Phys Educ. 2004;23(1):4-18.
Journal of School Health
•
26. Moreno J. Goal orientations, motivational climate, discipline and physical self-perception related to the teacher’s gender, satisfaction and sport activity of a sample of Spanish adolescent physical education students. Int J Appl Sport Sci. 2005;17(2): 57-68. 27. Vallerand R. Toward a hierarchical model of intrinsic and extrinsic motivation. In: Zanna M, ed. Advances in Experimental Social Psychology. New York, NY: Academic Press; 1997:271-359. ˚ en ´ A, Watt A, Hagger M, Jaakkola T, Liukkonen J. 28. Grast Secondary school students’ physical activity participation across physical education classes - The Expectancy-Value Theory approach. Phys Educator. In press 2014;71(4). 29. Bowler M. The influence of the TARGET motivational climate structures on pupil physical activity levels during year 9 athletics lessons. British Educational Research Association Annual Conference. Manchester: University of Manchester; September 2-5, 2009. 30. Spence J, Lee R. Toward a comprehensive model of physical activity. Psychol Sport Exerc. 2003;4(1):7-24. 31. Sallis J, McKenzie T, Conway T, et al. Environmental interventions for eating and physical activity. A randomized controlled trial in middle schools. Am J Prev Med. 2003;24(3):209-217. 32. Carrell A, Clark R, Peterson S, Nemeth B, Sullivan J, Allen D. Improvement of fitness, body composition, and insulin sensitivity in overweight children in a school-based exercise program. A randomized, controlled study. Arch Pediatr Adolesc Med. 2005;159(10):963-968. 33. Fairclough S, Stratton G. Improving health-enhancing physical activity in girls’ physical education. Health Educ Res. 2005;20(4):448-457. 34. Jamner M, Spruijt-Metz D, Bassin S, Cooper D. A controlled evaluation of a school-based intervention to promote physical activity among sedentary adolescent females: project FAB. J Adolesc Health. 2004;34(4):279-289. 35. Verstraete S, Cardon G, De Clercq D, Bourdeaudhuij I. Increasing children’s physical activity levels during recess periods in elementary schools: the effects of providing game equipment. Eur J Public Health. 2006;16(4):415-419. 36. Webber L, Catellier D, Lytle L, et al. Promoting physical activity in middle school girls: trial of activity for adolescent girls. Am J Prev Med. 2008;34(3):173-184. 37. Ridgers N, Stratton G, Fairclough S. Physical activity levels of children during school playtime. Sports Med. 2006;36(4):359371. 38. Simon C, Wagner A, DiVita C, et al. Intervention centred on adolescents’ physical activity and sedentary behaviour (ICAPS): concept and 6-month results. Int J Obes Relat Metab Disord. 2004;28(3):96-103. 39. Tammelin T, Laine K, Turpeinen S. Physical Activity of School-aged Children. Research Reports on Sport and Health 272. Jyv¨askyl¨a: LIKES; 2013. 40. Jaakkola T, Liukkonen J. Changes in students’ self-determined motivation and goal orientation as a result of motivational climate intervention within high school physical education classes. Int J Sport Exerc Psychol. 2006;4(3):302-324. 41. Soini M, Liukkonen J, Watt A, Yli-Piipari S, Jaakkola T. Construct validity and internal consistency of the motivation climate in physical education scale. J Sports Sci Med. 2014;13(1):137-144. 42. Roberts G, Treasure D, Balague´ G. Achievement goals in sport: the development and validation of the Perception of Success Questionnaire. J Sports Sci. 1998;16(4):337-347. 43. Yli-Piipari S, Barkoukis V, Jaakkola T, Liukkonen J. The effect of physical education goal orientations and enjoyment in adolescent physical activity: a parallel process latent growth analysis. Sport Exerc Perform Psychol. 2013;2(1):15-31. 44. Currie C, Samdal O, Boyce W, Smith B. Health Behavior in SchoolAged Children: A WHO Cross-National Study. Research Protocol for the 2001-2002 Survey. Scotland: University of Edinburgh; 2002.
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54. Weigand D, Burton S. Manipulating achievement motivation in physical education by manipulating the motivational climate. Eur J Sport Sci. 2002;2(1):1-14. 55. Braithwaite R, Spray C, Warburton V. Motivational climate interventions in physical education: a meta-analysis. Psychol Sport Exerc. 2011;12(6):628-638. 56. Shephard R. Limits to the measurement of habitual physical activity by questionnaires. Br J Sports Med. 2003;37(3):197-206. 57. Troiano R. A timely meeting: objective measurement of physical activity. Med Sci Sports Exerc. 2005;37(11):487-489. 58. Booth M, Okely A, Chey T, Bauman A. The reliability and validity of the physical activity questions in the WHO health behaviour in schoolchildren (HBSC) survey: a population study. Br J Sports Med. 2001;35(4):263-267. 59. Vuori M, Ojala K, Tynj¨al¨a J, Villberg J, V¨alimaa R, Kannas L. Liikunta-aktiivisuutta koskevien kysymysten stabiliteetti WHOKoululaistutkimuksessa [Stability of the Finnish WHO physical activity questionnaire]. Liikunta & Tiede. 2005;42(1):39-46. 60. McKenzie T, Sallis J, Prochaska J, Conway T, Marshall S, Rosengard P. Evaluation of a two-year middle-school physical education intervention: M-SPAN. Med Sci Sports Exerc. 2004; 36(8):1382-1388.
45. Prochaska J, Sallis J, Long B. A physical activity screening measure for the use with adolescents in primary care. Arch Pediatr Adolesc Med. 2001;155(5):554-559. ˚ en ´ A, Watt A, Jaakkola T, Liukkonen J. Directly measured 46. Grast and self-reported physical activity in a sample of Finnish secondary school students. Adv Phys Edu. 2012;2(3):132-138. 47. Basic Education Act 27.11.1992/1174/§23. Helsinki, Finland: Ministry of Education and Culture; 1992. 48. Finnish National Board of Education. National Core Curriculum for Basic Education 2004. Vammala, Finland: Vammalan Kirjapaino Oy; 2004. ´ L, Muthen ´ B. Mplus User’s Guide. 6th ed. Los Angeles, 49. Muthen ´ & Muthen; ´ 1998-2010. CA: Muthen 50. Fan X, Thompson B, Wang L. The effects of sample size, estimation methods, and model specification on SEM fit indices. Struct Equ Model. 1999;6(1):56-83. 51. Schreiber J, Stage F, King J, Nora A, Barlow E. Reporting structural equation modeling and confirmatory factor analysis results: a review. J Educ Res. 2006;99(6):323-337. 52. Hu L, Bentler P. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model. 1999;6(1):1-55. 53. Ward D. School Policies on Physical Education and Physical Activity. Research Synthesis. Princeton, NJ: Robert Wood Johnson Foundation; 2011.
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© 2015, American School Health Association
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