Journal of Physical Activity and Health, 2014, 11, 1565 -1572 http://dx.doi.org/10.1123/jpah.2013-0080 © 2014 Human Kinetics, Inc.
Official Journal of ISPAH www.JPAH-Journal.com ORIGINAL RESEARCH
Impact of Social-Ecologic Intervention on Physical Activity Knowledge and Behaviors of Rural Students Cevdet Cengiz and Mustafa Levent Ince Background: The purpose of the study was to determine the effects of a social-ecologic intervention on health-related fitness (HRF) knowledge and behaviors of students (n = 62) living in rural areas. Methods: A prepost test control group design was constructed. In addition, qualitative data were collected by focus group discussions in the experimental group. Physical activity environment of a middle school was changed based on the social-ecologic model (SEM) with a focus on intrapersonal, interpersonal, community level, organizational factors, and public policies related to physical activity behavior. Health related fitness knowledge (HRFK) test, pedometer, and perceived physical activity self-efficacy and social support questionnaires were used for data collection. Results: Experimental group had significant improvement in HRF knowledge scores, physical activity levels, and social support compared with the control school students. The focus group results also supported the quantitative findings by indicating a perceived increase in physical activity opportunities; knowledge sources; and support from others. Conclusions: This study underlines the importance and positive outcomes of SEM in improving HRF knowledge, physical activity level, and social support of students in rural middle school settings. Keywords: intervention study, health promotion, health behavior Physical activity (PA) behaviors of children are established at an early age, and childhood experiences with physical activity have a significant impact on lifelong health behavior of individuals.1 There seem to be various factors shaping students’ exercise behavior. Among these factors are specific physical and social environments that children experience such as class, school, and family environments.2,3 Recently, researchers and health organizations have shown an increased interest in school-based interventions to promote the health behavior of students.4–6 The reasons underlying this interest were 2-fold; an average pupil was thought to spend 50% of their time in school4,7 and was active during after-school period.8 In line with this, Cale and Harris9 commented on the effectiveness of schoolbased physical activity interventions and stressed the importance of using effective strategies such as employing school or community physical activity programs and adopting ecologic approaches. This highlights the notion that school settings need to be structured with an emphasis on effective strategies including multilevel approaches. Parallel with the focus on effective strategies, individual-based theories (eg, Transtheoretical Model,10 Health Belief Model,11 and Theory of Planned Behavior12) have been used extensively for behavioral changes to date.13 Ecological variables, such as environmental (physical and social) constructs have been found effective for longlasting results in health of students.14–18 The social-ecologic model16,18,20 (SEM) is one of the ecological model that aims to improve various levels of individual, social, and environmental variables. Basically, the model focuses on intrapersonal, interpersonal, organizational, community, physical environment, and policy levels.2,18,20 Each level of influence in the SEM is named accordingly (see Figure 1). Here, it is important to note that there have been few studies on SEM and physical education.14,19 These studies have focused on
different levels of influence, such as individual, family, and physical environments of schools.20 To illustrate, Casey et al14 used the SEM to increase physical activity and participation in sports among rural adolescent girls. The results indicated that teachers or practitioners needed to assure that developmentally-appropriate activities were fun, noncompetitive, and self-referencing to facilitate participation in sports and physical activities. The related literature reveals that urban studies related to the physical activity behaviors of students are more common than rural studies.22,23 However, limited research has examined the rural settings, physical activity behaviors,14,24,25 physical activity level of students26 and Health Related Fitness27,28 (HRF). It seems that physical activity behaviors of students are restricted in the rural settings and students have limited accesses to structured physical activity opportunities,29 which makes supporting physical and social environments with a social-ecologic perspective a promising strategy to improve physical activity behaviors of students. In line with this, this paper aimed to analyze the effects of SEM on HRF knowledge and the physical activity behaviors of students in a rural setting in Turkey. It builds on the hypothesis that a multilevel social-ecologic approach would increase HRF knowledge and the level of physical activity of students, and influence the promotion of physical activity behavior in rural middle school settings. The social-ecologic model as it relates to HRF knowledge, the level of physical activity, and exercise behaviors of middle school students living in rural settings has not been studied in a Turkish sample. Accordingly, this paper has wider implications for the use of SEM which are discussed within a Turkish setting.
Cengiz ([email protected]) is with the Dept of Teaching Physical Education and Sport, Canakkale Onsekiz Mart University, Merkez, Turkey. Ince is with the Dept of Physical Education and Sport, Middle East Technical University, Ankara, Turkey.
Overall Study Design
Methods Two elementary schools from rural towns in Ankara were asked to participate in this research. A prepost test control group design 1565
1566 Cengiz and Ince
and 16 girls) and the classes from the other school were designated as the control group (15 boys and 16 girls). Experimental school students were mostly (78.6%) from low SES and from middle SES (21.4%) neighborhood. However, control school students were mostly (79.2%) from middle SES and rich SES (20.8%) neighborhood. Body Mass Index (BMI = Kg/m2) of students was in 15th to 50th percentile (see Table 1) categorized as normal weight and height in both schools.31
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Intervention
Figure 1 — The social-ecological model: levels of influence.15,16
with a focus group interview in the experimental group at the end of the intervention was used.30 Approval was received from the Ethics Committee of the university prior the research. A signed consent from parents and pupils was also provided before the study commenced. The participation rate at baseline and completion was 91%.
Study Settings and Participants Sixty-two students aged between 12 and 14 years from 2 middle schools were recruited for this study. Similar school settings, populations, and socioeconomic status (SES) were chosen according to the Turkish Statistical Institute. The control school was included as a group with no intervention (sedentary group) to compare the results. Both rural towns of Ankara were 40 to 50 miles away from the city and had 1 middle school located in the center. Participants from each school (32 girls and 30 boys) volunteered to participate (Table 1) in the study. The classes from one school were designated as the experimental group where the researcher worked (15 boys
The intervention was 12 weeks in duration and 1 part of the intervention took place after school hours (started at 3.00 PM; finished at 4.20 PM) for 80 minutes 3 times weekly in a government middle school. A typical classroom size was between 20 to 25 students in both schools. In addition to the after-school period, PE hours, school notice boards, the school PA environment, community support, and school council were actively used. Informational health bulletins were also sent (every month) to families during the intervention. A part of the intervention, the physical environment of the school garden and inside of the school, was improved in terms of physical activity facilities. At the beginning, the experimental school had only a basketball court. During the intervention, new equipment was added for physical activity, including a climbing iron, horizontal bar, goalposts for soccer, a volleyball court, and volleyball net. Inside the school, physical education school boards (monthly changed with different health topics related to physical activity), news about sports, sport posters and a table tennis room was constructed. For the school physical activity opportunities, support was requested from different organizations and from sport federations. For example, sand for the long jump was provided from the local municipality through a written request. Similarly, soccer goalposts were provided from the School Council budget. The control school was similar to experimental school and had weekly 2 hours regular physical education lesson. The PE teacher had 2 years of experience and has been working for 1 year in the control school. Considering the school physical activity facilities; there was only a basketball court and school garden in front of the school. The content of HRF knowledge was discussed with pupils in an after-school physical activity program and during physical education lessons. Sport types were decided by the students before the intervention; boys participated in soccer, and at the same time girls participated in volleyball activity that was supervised by a volleyball instructor. During the after-school period in experimental school, a typical lesson started with 10 minutes of warm-up or games. The lesson continued with instruction about the lesson objectives and
Table 1 Characteristics of Participants and Enrollment Rate of Experimental and Control Schools Variables
Grade
N
n/%
Gender Boy / Girls
BMI (kg/m2) Mean/SD
Age Mean/SD
Experimental school
Class 6
19
13 (68.42)
6/7
16.67 ± 1.42
12.00 ± .00
Class 7
20
10 (50.00)
4/6
18.99 ± 1.57
13.00 ± .00
Class 8
13
8 (61.54)
5/3
19.12 ± 2.18
13.87 ± .35
Class 6
29
13 (44.83)
6/7
17.77 ± 1.53
12.08 ± .28
Class 7
27
10 (37.04)
4/6
18.12 ± 1.70
13.00 ± .00
Class 8
30
8 (26.67)
5/3
18.98 ± 1.29
14.00 ± .00
Control school
Abbreviations: N, total number of students in the school by grade; n, number of students voluntarily participated in the study; %, percentage of students regarding the total number of students (N) in the school by grade; BMI, Body Mass Index (BMI = kg/m2).
Social-Ecologic Intervention in Rural Middle Schools 1567
practice (30 minutes). After ten minutes break a short game (20 minutes) and ended with short discussion (10 minutes) about health related fitness knowledge based on the PE standards. The volleyball instructor worked with the girls and was supported by a university grant; she had been teaching volleyball for 3 years in a professional junior club as a second coach. In addition, the physical education lesson content was structured according to the HRF knowledge standards of the middle school physical education curriculum by Ministry of National Education (MoNE).32
Data Collection and Instruments For the data collection, there were different questionnaires for each level of SEM and focus group discussions at the end of the intervention (Figure 2). These levels of influence were aimed to develop within a 12-week period of time with the following instruments.
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Intrapersonal Level of the Social-Ecologic Model Health-Related Fitness Knowledge. HRF knowledge was
assessed using the translated version of the Super Kids-Superfit questionnaire.33 The Turkish version of the Super Kids-Superfit questionnaire was adapted according to the Turkish physical education curriculum for HRF knowledge standards of primary schools32 and validated by Hunuk and Ince.34
Physical Activity Level. Student physical activity level was
assessed at the beginning and end of the intervention using pedometers (SILVA) [Sollentuna, Sweden] for 7 consecutive days. The pedometer is an accurate, objective, and low-cost measure of walking compared with pen and paper questionnaires and acceptable tool for estimating PA levels of children.35 Every student in the study wore a pedometer on their right hip, and every day the students wrote down the number of daily steps for 1 week before and during the last week of the intervention.
Figure 2 — Overall designs of the study and data collection methods.
Self-Efficacy and Proxy Efficacy of Children for After-School Physical Activity. Proxy efficacy was defined as the confidence
of children in their skills and abilities to get parents to respond to their interest in providing physical activity opportunities. The proxy efficacy of participants was measured under 3 subcategories; selfefficacy to be physically active (SEPA, 5 items), proxy efficacy to influence after-school staff to provide PA opportunities (PEPA-S’ 4 items) and proxy efficacy to influence parents to provide PA opportunities (PEPA-P, 6 items) using 3-point Likert-type scales choosing from “not agree at all (1),” “somewhat agree (2),” and “completely agree (3).” The maximum score from each subscale were 15, 12 and 18 (high efficacy). Self-efficacy and proxy efficacy scales were developed and validated among children by Dzewaltowski et al.36 The Turkish version of the instrument was validated by Cengiz and Ince.37
Interpersonal Level of SEM Perceived Social Support for Physical Activity. The instrument,
which consisted of 14 items on a 5-Point Likert-type scale with anchors 1: Never and 5: Every day. The maximum score from each subscale was 25, 25 and 20 (high support). The questionnaire was developed by Sallis et al.38 The aim of the questionnaire was to evaluate the opinions of parents and peer about perceived social support related to participation in physical activities. The Turkish version was validated in a middle school sample by Hunuk et al.39
Organizational and Community Level of SEM The third and fourth levels of the SEM focus on organization level, such as rules, regulations, policies, and informal structures, which may constrain or promote the recommended behavior. The community level mainly focuses on social networks and norms or standards which are formal or informal among individuals, groups, and organizations.
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Public Policy Level of the SEM Educational Policy Drivers. The Turkish context has been supported by 3 main policy drivers, as follows: (1) talent identification and developing athletes performing at the international level, (2) improving the HRF knowledge in everyone, and (3) education through physical activity or education. The first perspective was mainly stated by the General Directory of Youth and Sports.40 Specifically, the formal school system (the MoNE) supports improving the HRF from all perspectives. The report of the Turkish National Burden of Disease41 by the Ministry of Health42 (MoH) emphasized the increased health expenses and lowered health quality due to a sedentary lifestyle among the Turkish population. Overall, the MoH was supporting physical activity-based health promotion programs for all ages, including school-aged children (eg, educational materials and information bulletins). In another perspective, the HRF reflected the school physical education curriculum by the MoNE. The primary physical education curriculum was mainly rooted in 2 main learning areas (development of skills and HRF knowledge). The last perspective was aimed at education through physical activity or education that was supported by the MoNE documents. The main role of physical activity and physical education was emphasized not only for psychomotor development, but also for affective, social, and cognitive development of pupils in the curricular documents. Focus Groups. Two focus groups with boys (N = 12) and 2 focus groups with girls (N = 14) were randomly selected from the intervention group and discussions were conducted by independent expert researchers from the Physical Education and Sports Department. The groups were separated by gender to help the participants feel comfortable and share experiences.43 Discussions were conducted in the experimental school in an empty classroom during lunch breaks or class time, which lasted between 30 and 45 minutes. Each session was tape recorded and notes were transcribed by the researcher. Four main themes were constructed after the content analysis.
Data Analysis Quantitative data were examined by descriptive (mean and standard deviation) and inferential statistics, including repeated measures of
analyses of variance (RM ANOVA) after the normality assumption checks by Kolmogorow-Smirnov, Skewness and Kurtosis, Box’s M test, and Levene’s Test (P < . 05). Focus group transcriptions were examined with the content analysis method.43 After audio-taped focus group interviews were fully transcribed, data were read word by word to drive codes. Then, codes were sorted into categories. These categories were used to organize and group codes into meaningful clusters. Lastly, exemplars for each cluster were identified.
Results Intrapersonal Level of the Social-Ecologic Model The results of HRF knowledge test with RM ANOVA indicated that there was a statistically significant main effect for school (Wilks’s λ = .84; F(1,60) = 59.83; P < .05). The multivariate η2 based on Wilks’s λ was quite strong (η2 = . 50) based on Cohen’s classification.44 In addition, descriptive statistics demonstrated an increase in the experimental group (Table 2) compared with the control school. Similarly, the physical activity levels of students were examined with RM ANOVA in both schools with respect to the second research question. The results showed that there was a statistically significant main effect for school (Wilks’s λ = .88; F(1,60) = 7.83; P < .05). The multivariate η2 based on Wilks’s λ was moderate44 (η2 = . 11). The descriptive statistics also indicated an increase in the level of physical activity in the experimental group (Table 2). RM ANOVA was performed to determine school differences in perceived physical activity of the self-efficacy, staff and parent efficacies of students. There were no significant differences between self-efficacy and schools (Wilks’s λ = .93; F(3,58) = 1.50; P > .05). In contrast, the descriptive statistics indicated an increase in the selfefficacy of the experimental group (Table 2); however, this increase was not statistically sufficient for a significant effect (P > .05).
Interpersonal Level of SEM For research question 4, the perceived social support of students was examined with RM ANOVA and the findings indicated that there was a statistically significant main effect for school (Wilks’s λ = .86;
Table 2 Descriptive Statistics of Health-Related Fitness Knowledge, Physical Activity Levels, Self-Efficacy, Staff Efficacy, Parent Efficacy, Mother Support, Father Support, and Friend Support Pretest
Posttest
Experimental
Control
Experimental
Control
Mean/SD
Mean/SD
Mean/SD
Mean/SD
20.67 ± 4.92
20.84 ± 3.26
27.71*±4.92
19.74 ± 4.19
Weekly steps (daily)
12322.60 ± 3160.23
9743.30 ± 3386.25
14752.42*±3189.15
10535.50 ± 3535.62
Steps (weekdays)
12986.13 ± 3348.15
9894.30 ± 3496.85
14629.54 ± 3332.89
10691.04 ± 3754.99
Steps (weekends)
10663.77 ± 4156.20
9365.81 ± 4001.99
15059.61 ± 4086.04
10146.66 ± 4488.95
10.03 ± 2.01
9.74 ± 2.11
10.93 ± 2.20
9.77 ± 2.23
HRFK
Self-efficacy Staff-efficacy
8.48 ± 1.31
7.77 ± 1.76
8.97 ± 1.89
7.39 ± 1.86
Parent-efficacy
11.97 ± 2.01
11.74 ± 3.04
13.87 ± 2.36
12.42 ± 2.75
Mother support
7.74 ± 3.57
8.03 ± 3.32
11.48*±4.17
8.64 ± 4.28
Father support
8.00 ± 3.89
8.13 ± 3.72
10.93*±4.37
8.48 ± 4.81
Friend support
10.74 ± 4.43
10.52 ± 3.27
11.51 ± 3.59
10.23 ± 3.84
* P < .05. Abbreviations: HRFK, Health Related Fitness Knowledge.
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Social-Ecologic Intervention in Rural Middle Schools 1569
F(3,58) = 3.08; P < .05). The multivariate η2 based on Wilks’s λ was a moderate effect44 (η2 = .14). Before conducting further analysis (paired sample t test) to detect the significant difference, alpha level was adjusted (P = .016) using the Bonferroni correction method to avoid the risk of making a type II error.45 The dependent sample t test results indicated that students in the treatment school made a difference (MD = –3.74, SD = 3.73) for the mother, (MD = –2.93, SD = 4.08) for the father, and (MD = –.77, SD = 4.59) for friends from the pre- to posttest. Except for support from the friend, this difference was statistically significant for support from the mother [t(30) = –5.58, P < .016] and support from the father [t(30) = –4.00, P < .016]. In contrast, the control school had no significant effect on the support from the mother [t(30) = –.76, P > .016], support from the father [t(30) = –.39, P > .016], and support from the friend [t(30) = –.39, P > .016]. The results obtained from the descriptive statistics of perceived social support indicated an increase in the scores (Table 2). To understand whether the social-ecologic approach changed the knowledge about physical activity among rural middle school students, level and social support focus group interviews were conducted. Four separate groups were randomly selected from the EXP school and conducted by independent expert researchers. Four main themes were constructed and listed by content analyses, as follows: (1) increased physical activity opportunities by the physical activity preferences and physical activity needs of students, (2) increased data sources to reach sport- and physical activity–related knowledge, (3) increased perceived support from significant others, and (4) influence of perceived stress of the academic exam for secondary schools (AESS) on extracurricular activity participation. The following statements from students indicated their views about the changes in physical activity knowledge and behaviors of each theme. Students commented that their physical activity participation was increased by new school physical activity opportunities. Physical activities in courses were chosen according to student preferences in after-school activities. Different physical activity opportunities were provided and supported by the school principal, families, school Council, and local municipality for both genders. Students commented about this in the interview, as follows: “From the beginning of the spring semester, we do sports 3 times a week and we have had facilities since then. The new facilities included a climbing iron, horizontal bar, soccer goalposts, volleyball court, volleyball net, balls, sandbox for long jump, and table tennis.” (a 13-year-old male student) “I love soccer most. As a hobby, I play table tennis. Because soccer is the opportunity we have most here (in school) we can play. At the basement, there is a table tennis.” (a 13-year-old male student) “. . . Last year, there were only basketball poles. Our teacher provided soccer goalposts, then a horizontal bar, a volleyball court, and a climbing rope.” (a 13-year-old female student) “When he (physical education teacher) came, he brought balls. . . . There was no volleyball net or soccer goalposts, but our physical education teacher provided them. There was no climbing iron, and he provided that, too. Because of him, we can participate in many physical activities. . . .” (a 12-year-old male student) Students also commented about the increased data sources to reach sport- and physical activity–related knowledge in the focus group, as follows:
“We were receiving information through the internet, television, school library, notice boards, and encyclopedias. In addition, this year we had an instructor who is a specialist in volleyball for 80 minutes during the after-school period. We have learned volleyball rules and techniques, such as passes (overhand pass etc.) and attack. . . .” (a 14-year-old female student) “We searched different types of sports (tennis, triathlon, and rugby) related to performance work in the physical education course. The basic sources were the internet, school library, and teachers.” (a 13-year-old male student) “. . . For example, we learned basketball. He gave us information about them. . . . For example, what causes lifting weight? Increases muscle size.” (a 13-year-old male student) “PowerPoint presentations, heart rate of our bodies, what should be the recommended daily steps for healthy life. . . .” (a 13-year-old female student) The third theme was the influence of increased perceived support from significant others. Students described the increased social support in the following way: “Our families supported our participation in this after-school program to become healthier. They provided transportation. Other than our families, my big brother, physical education teacher, and volleyball instructor supported our participation.” (a 13-year-old female student) “I am supported by my family, too, physical education teacher, and volleyball coach. . . . My family wanted me to become taller, muscular, and healthier.” (a 12-year-old female student) The last theme was the influence of perceived stress of the AESS on extracurricular activity participation. Participants in the focus group also discussed the perceived stress to participate in physical activities lately as follows: “There is no one or any condition preventing us from this program. The only condition is we do not have much time from the other subjects that are in the middle-school curriculum.” (a 13-year-old male student) “No, there is not, except our courses. But there is the academic exam for secondary school and we must get high scores in the exam so we have to study. We have term projects and performance work; therefore we do not have time for sports. Always courses!” (a 13-year-old female student) “This program did not affect my other subjects.” (a 14-yearfemale student) The overall findings of the focus group discussions supported the quantitative findings of the SEM. Changes related to physical activity knowledge and behavior were evident in the current study.
Discussion The findings of the current study indicated that a 12-week socialecologic intervention was effective in improving HRF knowledge, the level of physical activity, and perceived social support of rural middle school students. Each research question of the study will be discussed in order. The baseline measurements involving 36 items in the HRF knowledge average test scores showed significant improvements in the posttest evaluation. In addition to descriptive statistics, the RM ANOVA results indicated that there was a statistically significant effect for the intervention school (P < .05).
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1570 Cengiz and Ince
As Dilorenzo et al46 noted that the HRF knowledge of middle school students was a determinant of the exercise behavior of children. Stewart and Mitchell47 summarized that most students were not able to identify correct fitness components and were not able to match the HRF construct with the Fitnessgram test item.48 In this context, the social-ecologic intervention was fairly effective and students increased their HRF knowledge significantly. The Turkish primary physical education curriculum32 and HRF knowledge standards and their objectives need to be examined in a larger sample with HRF knowledge tests in elementary schools. Another study by Placek et al49 used qualitative methods to investigate middle school student HRF knowledge. Researchers found that students had misconceptions concerning fitness variables. More importantly, the authors reported pupils had the same erroneous fitness knowledge as students have 20 years earlier.28 Similar results and misconceptions were also found among high school pupils in fundamental HRF knowledge28,47 and elementary schools.27,50 Therefore, the HRF knowledge of pupils needs to be increased with effective strategies and methodologies. As a second research question, this study aimed to increase the level of physical activity of students. The results revealed that SEM had a statistically significant effect on physical activity levels of experimental students. The measurements were obtained over 7 consecutive days of a week. Based on daily steps, boys were more active than girls in the experimental group at the baseline measurement. In the control group, similar findings were also identified in both sexes. After the 12-week period of intervention based on the SEM, the treatment school had increased their level of physical activity in both sexes compared with the control school. Overall, the average steps taken in a weekdays increased significantly in the experimental school for both sexes. These results raise the possibility that supporting the school environment with multilevel approaches could increase the level of physical activity of students. These findings were also consistent with previous research that identified a significant effect on the level of physical activity in children with pedometer measurements.26,51,52 Experimental school students also increased their steps at weekends for both sexes. As a result of weather conditions this increase seemed to be high. However, Loucaides et al53 concluded that the levels of physical activity varied by season among rural and urban children. Those children in rural areas were most physically active in the summer months24 compared with urban children who were most physically active in the winter months. Lastly, type of sport was another contribution to the PA level of students. Perceived self-efficacy results indicated no significant differences between the groups. Although there was no statistical significance between the groups and subjects, there were small improvements noted between the group variables with higher improvements in the experimental school. These findings revealed that the SEM has an effect on self-efficacy variables, but this improvement was not sufficient for a statistically significance difference among the students. The limited number of pupils that participated in the school could be an important factor on the outcomes. The second factor may have been the self-efficacy of physical activity levels that was already high before the study; however, high parent efficacy values supported that the perceived social support of students was critical between self-efficacy and parental support. This striking finding was crucial when studies focused on increasing the parental support of students. We need to support both dimensions when increasing physical activity knowledge, level, and behavior of middle school students. Similarly, Shield et al54 examined self-efficacy and
parental social influence related to physical activity. The results of this research revealed support for self-regulatory efficacy as a mediator and the parental influence effect on youth and adolescent physical activity. Lastly, the activity type that was chosen by the pupils before the study might have affected the self-efficacy scores. Playing soccer and volleyball may not be effective in increasing self-efficacy as compared with individual sports (eg, gymnastics, tennis, or track and field). The perceived social support of the current study revealed a significant effect on the physical activity behavior of pupils in the middle school sample. As the literature suggested, parental support was one of the key correlations of physical activity behavior in children.4,55 However, little is known about which component of parental support was more effective in promoting physical activity behavior, and how it contributed to the exercise behavior of children. The current study analyzed the perceived social support of parents to physical activity behavior. Statistical analyses revealed that social support for physical activity increased through the SEM. Further analysis with descriptive statistics indicated that mother and father support values were higher in the treatment school related to the physical activity behavior of students. Notably, we found no evidence of a statistically significant effect on peer support for physical activity behavior of students. Similar findings were reported by Hunuk and colleagues39 in a private Turkish middle school sample. Participants received more support for their physical activity participation from their families compared with their friends. This cross-sectional design was further analyzed in the current study, thus providing stronger design and a different sample. Another reason for the significant effect of parental support could be the health bulletins related to the social-ecologic intervention and health benefits of physical activity were sent to every family, and usually mothers or fathers read or received the information. In the same manner, findings of focus group discussions indicated that students positively perceived the changes in their environment which were guided by the social-ecological framework. Students were able to identify the increased physical activity opportunities and facilities in their environment, integration of physical education lessons with extracurricular activities and life, increased physical activity participation, increased data sources to reach sport and physical activity–related knowledge, increased knowledge sources in the library, and increased perceived support from the significant others. It is clear that if the learning environment of the students is changed with a social-ecologic framework, student learning in physical education will be stimulated toward the current physical education curriculum goals in primary schools. The primary school curriculum underlines the importance of connecting physical education lesson with extracurricular activities and life.29 The focus group discussions proved that this connection was achieved. In the physical education literature, integration of physical education lessons with life and developing lifelong physical activity behavior has been the most discussed topic55,56 however; it has been an unresolved issue. The perceptions of the students in this study present encouraging results toward effective methods to ensure reaching this outcome by the SEM. Student statements about sports- and physical education-related knowledge and data sources were also important findings in focus group interviews. The findings indicated that students used alternative knowledge sources, including physical education lessons, internet data sources, books, and significant others, instead of using very limited sources, such as using only physical education teachers or friends. This finding implied that the teacher’s role in
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Social-Ecologic Intervention in Rural Middle Schools 1571
guiding students to use alternative knowledge sources is important and effective in learning. Focus group interviews also indicated some of the students’ negative perceptions of the AESS as a limiting factor in participating in physical activity. This is a very important public concern in Turkey. There is a need to work on why students perceive this issue as limiting factor for participation. Normally, HRF-related physical activity participation does not require as much time as performance- or skill-related sports participation. Instead, it can be expected that through participation in HRF related to physical activity, students would probably relax, improve the stress level, and increase academic performance.57,58 These findings suggest that in general the value of SEM in improving HRF knowledge, physical activity level, and social support of students in rural middle school settings. The evidences from this study suggest that SEM is an effective model which supports physical activity behavior of middle school students living in rural settings. Further studies on SEM and applying with different levels of the model in urban settings are strongly recommended. In addition, using a sedentary group with no intervention is recommended for future studies. Acknowledgments This research was supported by a grant (Grant No: BAP- 05-04-2010-03) from Middle East Technical University, Scientific Project Support Program.
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11. Rosenstock IM. Historical origins of the health belief model. Health Educ Monogr. 1974;2:328–335. 12. Ajzen I, Fishbein M. Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice Hall; 1980. 13. Glanz K, Rimer BK, Viswanath K. Health behavior and health education: theory, research, and practice. 3rd ed. San Francisco, CA: Jossey-Bass; 2008. 14. Casey MM, Eime RM, Payne WR, Harvey JT. Using socioecological approach to examine participation in sport and physical activity among rural adolescent girls. Qual Health Res. 2009;19(7):881–893. PubMed doi:10.1177/1049732309338198 15. Golden SD, Earp JAL. Social ecological approaches to individuals and their contexts: twenty years of health education and behavior health promotion interventions. Health Educ Behav. 2012;39(3):364–372. PubMed doi:10.1177/1090198111418634 16. Denver Department of Public Health. (2007). Socio-ecological model definitions. Retrieved December 28, 2012, from http://www.balancedweightmanagement. com/The-socio-ecological-model%20definitions. pdf 17. Langille JD, Rodgers WM. Exploring the influence of a social ecological model on school-based physical activity. Health Educ Behav. 2010;37(6):879–894. PubMed doi:10.1177/1090198110367877 18. Stokols D. Translating social ecological theory into guidelines for community health promotion. Am J Health Promot. 1996;10(4):282–298. PubMed doi:10.4278/0890-1171-10.4.282 19. Fleury J, Lee SM. The social ecological model and physical activity in African American women. Am J Community Psychol. 2006;37(1/2):129–139. PubMed doi:10.1007/s10464-005-9002-7 20. McLeroy KR, Bibeau D, Steckler A, Glanz K. An ecological perspective on health promotion programs. Health Educ Q. 1988;15:351–377. PubMed doi:10.1177/109019818801500401 21. Naylor PJ, MacDonald HM, Reed KE, McKay HA. Action schools! BC: a socioecological approach to modifying chronic disease risk factors in elementary school children. Preventing Chronic Disease Public Health Research, Practice, and Policy. 2006;3(2):1–8. PubMed 22. Hanlon TE, Simon BD, O’Grady KE, Carswell SB, Callaman JM. The effectiveness of an after-school program targeting urban African American youth. Educ Urban Soc. 2009;42(1):96–118. PubMed doi:10.1177/0013124509343144 23. Monge-Rojas R, Garita-Arce C, Sanchez-Lopez M, Colon-Ramos U. Barriers to suggestions for a healthful, active lifestyle as perceived by rural and urban Costa Rican adolescents. J Nutr Educ Behav. 2009;41:152–160. PubMed doi:10.1016/j.jneb.2008.03.002 24. Bathrellou E, Lazarou C, Panagiotakos DB, Sidossis LS. Physical activity patterns and sedentary behaviors of children from urban and rural areas of Cyprus. Eur J Public Health. 2007;15(2):66–70. PubMed 25. Alikasifoglu M, Erginoz E, Ercan O, et al. Differences in health and health behaviors between urban and rural school children aged 11-13years in Turkey: findings from the health behavior in school-aged children study 2006. Turkish Arch Pediatr. 2010;45:96–104. 26. Johnson TG, Brusseau TA, Graser SV, Darst PW, Kulinna PH. Step counts of 10-11 year old children by ethnicity and metropolitan status. J Phys Act Health. 2010;7:355–363. PubMed 27. Kulinna PH Physical activity and fitness knowledge: how much 1-6 grade students know. Int J Phys Educ. 2004;XLJ:111–121. 28. Keating XD, Harrison L, Chen L, et al. An analysis of research on student health-related fitness knowledge in K-16 physical education programs. J Teach Phys Educ. 2009;28:333–349. 29. Eime RM, Payne WR, Casey MM, Harvey JT. Transition in participation in sport and unstructured physical activity for rural living adolescent girls. Health Educ Res. 2010;5(2):282–293. PubMed doi:10.1093/ her/cyn060
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1572 Cengiz and Ince 30. Creswell JW, Plano Clark VL. Designing and conducting mixed methods research. 1st ed. Thousands Oaks, CA: Sage Publications Inc; 2007. 31. Neyzi O, Gunoz H, Furman A, et al. Weight, height, head circumference and body mass index references for Turkish children. Turk J Pediatr. 2008;51:1–14. 32. Ministry of National Education (MoNE). Primary physical education curriculum. Ankara: Ministry of Education Publication; 2007. 33. Mott DS, Virgilio SJ, Warren BL, Berenson GS. Effectiveness of a personalized fitness module on knowledge, attitude, and cardiovascular endurance of fifth-grade students ‘Heart Smart’. Percept Mot Skills. 1991;73:847–858. PubMed 34. Hunuk D, Ince ML. Development of health-related fitness knowledge test for Turkish middle school students. Proceedings of 15th annual congress of the European College of Sport Science; 2010 Jun 23–26; Antalya, Turkey. 554–555. 35. Tudor-Locke C, Williams JE, Reis JP, Pluto D. Utility of pedometers for assessing physical activity: convergent validity. Sports Med. 2002;32:795–808. PubMed doi:10.2165/00007256-200232120-00004 36. Dzewaltowski DA, Geller KS, Rosenkranz RR, Karteroliotis K. Children’s self-efficacy and proxy efficacy for after-school physical activity. Psychol Sport Exerc. 2010;11:100–106. doi:10.1016/j. psychsport.2009.08.001 37. Cengiz C, Ince ML. Children’s self-efficacy for after-school physical activity in different school contexts. J Administrative Sciences. 2013;21:135–147. 38. Sallis JF, Condon K, Goggin JR, Kolody B, Alcares J. The development of self-administered physical activity surveys for 4 grade students. Res Q Exerc Sport. 1993;64:25–31. PubMed doi:10.1080/02701367.199 3.10608775 39. Hunuk D, Ozdemir RA, Yildirim G, Asci FH. An examination of social support types with regard to physical activity level: a private school sample. Proceedings of 10th International Sport Sciences Congress; 2008 Oct 23-25; Bolu, Turkey. 690 p. 40. General Directory of Youth and Sport [Internet]. Ankara (Turkey) 2012 [cited 2011 December 14] Available from: http://www.gsgm.gov.tr 41. Turkish National Burden of Disease. Turkish National Burden of Disease Study. Turkish Republic Ministry of Health Refik Saydam Institute and Baskent University, Retrieved September 21, 2010, from http://www.tusak.saglik.gov.tr/pdf/nbd/raporlar/burdenofdiseaseENG. pdf. 42. Ministry of Health [Internet]. Ankara (Turkey) 2012 [cited 2012 January 10] Available from: http://www.saglik.gov.tr/EN/anasayfa/2-0/20130708.html. 43. Krueger RA, Casey MA. Focus groups: a practical guide for applied research. 3rd ed. Thousand Oaks, CA: Sage Publications; 2000. 44. Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum Associates; 1998.
45. Stevens J. Applied multivariate statistics for the social sciences. 4th ed. Hillsdale, NJ: Lawrence Erlbaum Publishing; 2002. 46. Dilorenzo TM, Stucky-Ropp RC, Vander Wal JS, Gotham HJ. Determinants of exercise among children. II. A longitudinal analysis. Prev Med. 1998;27:470–477. PubMed doi:10.1006/pmed.1998.0307 47. Stewart S, Mitchell M. Instructional variables and student knowledge and conceptions of fitness. J Teach Phys Educ. 2003;22:533–551. 48. Welk GJ, Meredith MD. Fitnessgram / Activitygram reference guide. Dallas, TX: The Cooper Institute; 2008. 49. Placek JH, Griffin LL, Dodds P, Raymond C, Tremino F, James A. Middle school students’ conceptions of fitness: the long road to a healthy lifestyle. J Teach Phys Educ. 2001;20(4):314–323. 50. Brusseau T, Kulinna PH, Cothran DJ. Health and physical activity content of Pima children. Phys Educator. 2011;68:66–77. 51. Beets MW, Bornstein D, Beighle A, Cardinal BJ, Morgan JF. Pedometer-measured physical activity patterns of youth: A 13-country review. Am J Prev Med. 2010;38(2):208–216. PubMed doi:10.1016/j. amepre.2009.09.045 52. Hardman CA, Horne PJ, Rowlands AV. Children’s pedometer-determined physical activity during school-time and leisure-time. J Exerc Sci Fit. 2009;7(2):129–134. doi:10.1016/S1728-869X(09)60016-2 53. Loucaides CA, Plotnikoff RC, Bercovitz K. Differences in the correlates of physical activity between urban and rural Canadian youth. J Sch Health. 2007;77(4):164–170. PubMed doi:10.1111/j.17461561.2007.00187.x 54. Shields CA, Spink KS, Chad K, Muhajarine N, Humbert L, Odnokon P. Youth and adolescent physical activity lapsers: examining self-efficacy as a mediator of the relationship between family social influence and physical activity. J Health Psychol. 2008;13(1):121–130. PubMed doi:10.1177/1359105307084317 55. Kohl HW, Hobbs KE. Development of physical activity behaviors among children and adolescents. Pediatrics. 1998;101:549–554. PubMed 56. Sallis JF, McKenzie TL, Kolody B, Lewis M, Marshall S, Rosengard P. Effects of health-related physical education on academic achievement: Project SPARK. Res Q Exerc Sport. 1999;70(2):127–134. PubMed doi:10.1080/02701367.1999.10608030 57. Fox CK, Barr-Anderson D, Neumark-Sztainer D, Wall M. Physical activity and sports team participation: Associations with academic outcomes in middle school and high school students. J Sch Health. 2010;80(1):31–37. PubMed doi:10.1111/j.1746-1561.2009.00454.x 58. Sallis JF, Owen N, Fisher EB. Ecological models of health behavior. In: Glanz K, Rimer BK, Viswanath K, eds. Health behavior and health education: theory, research, and practice. San Francisco, CA: Jossey- Bass; 2008:465–485.
Official Journal of ISPAH www.JPAH-Journal.com ORIGINAL RESEARCH
Impact of Social-Ecologic Intervention on Physical Activity Knowledge and Behaviors of Rural Students Cevdet Cengiz and Mustafa Levent Ince Background: The purpose of the study was to determine the effects of a social-ecologic intervention on health-related fitness (HRF) knowledge and behaviors of students (n = 62) living in rural areas. Methods: A prepost test control group design was constructed. In addition, qualitative data were collected by focus group discussions in the experimental group. Physical activity environment of a middle school was changed based on the social-ecologic model (SEM) with a focus on intrapersonal, interpersonal, community level, organizational factors, and public policies related to physical activity behavior. Health related fitness knowledge (HRFK) test, pedometer, and perceived physical activity self-efficacy and social support questionnaires were used for data collection. Results: Experimental group had significant improvement in HRF knowledge scores, physical activity levels, and social support compared with the control school students. The focus group results also supported the quantitative findings by indicating a perceived increase in physical activity opportunities; knowledge sources; and support from others. Conclusions: This study underlines the importance and positive outcomes of SEM in improving HRF knowledge, physical activity level, and social support of students in rural middle school settings. Keywords: intervention study, health promotion, health behavior Physical activity (PA) behaviors of children are established at an early age, and childhood experiences with physical activity have a significant impact on lifelong health behavior of individuals.1 There seem to be various factors shaping students’ exercise behavior. Among these factors are specific physical and social environments that children experience such as class, school, and family environments.2,3 Recently, researchers and health organizations have shown an increased interest in school-based interventions to promote the health behavior of students.4–6 The reasons underlying this interest were 2-fold; an average pupil was thought to spend 50% of their time in school4,7 and was active during after-school period.8 In line with this, Cale and Harris9 commented on the effectiveness of schoolbased physical activity interventions and stressed the importance of using effective strategies such as employing school or community physical activity programs and adopting ecologic approaches. This highlights the notion that school settings need to be structured with an emphasis on effective strategies including multilevel approaches. Parallel with the focus on effective strategies, individual-based theories (eg, Transtheoretical Model,10 Health Belief Model,11 and Theory of Planned Behavior12) have been used extensively for behavioral changes to date.13 Ecological variables, such as environmental (physical and social) constructs have been found effective for longlasting results in health of students.14–18 The social-ecologic model16,18,20 (SEM) is one of the ecological model that aims to improve various levels of individual, social, and environmental variables. Basically, the model focuses on intrapersonal, interpersonal, organizational, community, physical environment, and policy levels.2,18,20 Each level of influence in the SEM is named accordingly (see Figure 1). Here, it is important to note that there have been few studies on SEM and physical education.14,19 These studies have focused on
different levels of influence, such as individual, family, and physical environments of schools.20 To illustrate, Casey et al14 used the SEM to increase physical activity and participation in sports among rural adolescent girls. The results indicated that teachers or practitioners needed to assure that developmentally-appropriate activities were fun, noncompetitive, and self-referencing to facilitate participation in sports and physical activities. The related literature reveals that urban studies related to the physical activity behaviors of students are more common than rural studies.22,23 However, limited research has examined the rural settings, physical activity behaviors,14,24,25 physical activity level of students26 and Health Related Fitness27,28 (HRF). It seems that physical activity behaviors of students are restricted in the rural settings and students have limited accesses to structured physical activity opportunities,29 which makes supporting physical and social environments with a social-ecologic perspective a promising strategy to improve physical activity behaviors of students. In line with this, this paper aimed to analyze the effects of SEM on HRF knowledge and the physical activity behaviors of students in a rural setting in Turkey. It builds on the hypothesis that a multilevel social-ecologic approach would increase HRF knowledge and the level of physical activity of students, and influence the promotion of physical activity behavior in rural middle school settings. The social-ecologic model as it relates to HRF knowledge, the level of physical activity, and exercise behaviors of middle school students living in rural settings has not been studied in a Turkish sample. Accordingly, this paper has wider implications for the use of SEM which are discussed within a Turkish setting.
Cengiz ([email protected]) is with the Dept of Teaching Physical Education and Sport, Canakkale Onsekiz Mart University, Merkez, Turkey. Ince is with the Dept of Physical Education and Sport, Middle East Technical University, Ankara, Turkey.
Overall Study Design
Methods Two elementary schools from rural towns in Ankara were asked to participate in this research. A prepost test control group design 1565
1566 Cengiz and Ince
and 16 girls) and the classes from the other school were designated as the control group (15 boys and 16 girls). Experimental school students were mostly (78.6%) from low SES and from middle SES (21.4%) neighborhood. However, control school students were mostly (79.2%) from middle SES and rich SES (20.8%) neighborhood. Body Mass Index (BMI = Kg/m2) of students was in 15th to 50th percentile (see Table 1) categorized as normal weight and height in both schools.31
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Intervention
Figure 1 — The social-ecological model: levels of influence.15,16
with a focus group interview in the experimental group at the end of the intervention was used.30 Approval was received from the Ethics Committee of the university prior the research. A signed consent from parents and pupils was also provided before the study commenced. The participation rate at baseline and completion was 91%.
Study Settings and Participants Sixty-two students aged between 12 and 14 years from 2 middle schools were recruited for this study. Similar school settings, populations, and socioeconomic status (SES) were chosen according to the Turkish Statistical Institute. The control school was included as a group with no intervention (sedentary group) to compare the results. Both rural towns of Ankara were 40 to 50 miles away from the city and had 1 middle school located in the center. Participants from each school (32 girls and 30 boys) volunteered to participate (Table 1) in the study. The classes from one school were designated as the experimental group where the researcher worked (15 boys
The intervention was 12 weeks in duration and 1 part of the intervention took place after school hours (started at 3.00 PM; finished at 4.20 PM) for 80 minutes 3 times weekly in a government middle school. A typical classroom size was between 20 to 25 students in both schools. In addition to the after-school period, PE hours, school notice boards, the school PA environment, community support, and school council were actively used. Informational health bulletins were also sent (every month) to families during the intervention. A part of the intervention, the physical environment of the school garden and inside of the school, was improved in terms of physical activity facilities. At the beginning, the experimental school had only a basketball court. During the intervention, new equipment was added for physical activity, including a climbing iron, horizontal bar, goalposts for soccer, a volleyball court, and volleyball net. Inside the school, physical education school boards (monthly changed with different health topics related to physical activity), news about sports, sport posters and a table tennis room was constructed. For the school physical activity opportunities, support was requested from different organizations and from sport federations. For example, sand for the long jump was provided from the local municipality through a written request. Similarly, soccer goalposts were provided from the School Council budget. The control school was similar to experimental school and had weekly 2 hours regular physical education lesson. The PE teacher had 2 years of experience and has been working for 1 year in the control school. Considering the school physical activity facilities; there was only a basketball court and school garden in front of the school. The content of HRF knowledge was discussed with pupils in an after-school physical activity program and during physical education lessons. Sport types were decided by the students before the intervention; boys participated in soccer, and at the same time girls participated in volleyball activity that was supervised by a volleyball instructor. During the after-school period in experimental school, a typical lesson started with 10 minutes of warm-up or games. The lesson continued with instruction about the lesson objectives and
Table 1 Characteristics of Participants and Enrollment Rate of Experimental and Control Schools Variables
Grade
N
n/%
Gender Boy / Girls
BMI (kg/m2) Mean/SD
Age Mean/SD
Experimental school
Class 6
19
13 (68.42)
6/7
16.67 ± 1.42
12.00 ± .00
Class 7
20
10 (50.00)
4/6
18.99 ± 1.57
13.00 ± .00
Class 8
13
8 (61.54)
5/3
19.12 ± 2.18
13.87 ± .35
Class 6
29
13 (44.83)
6/7
17.77 ± 1.53
12.08 ± .28
Class 7
27
10 (37.04)
4/6
18.12 ± 1.70
13.00 ± .00
Class 8
30
8 (26.67)
5/3
18.98 ± 1.29
14.00 ± .00
Control school
Abbreviations: N, total number of students in the school by grade; n, number of students voluntarily participated in the study; %, percentage of students regarding the total number of students (N) in the school by grade; BMI, Body Mass Index (BMI = kg/m2).
Social-Ecologic Intervention in Rural Middle Schools 1567
practice (30 minutes). After ten minutes break a short game (20 minutes) and ended with short discussion (10 minutes) about health related fitness knowledge based on the PE standards. The volleyball instructor worked with the girls and was supported by a university grant; she had been teaching volleyball for 3 years in a professional junior club as a second coach. In addition, the physical education lesson content was structured according to the HRF knowledge standards of the middle school physical education curriculum by Ministry of National Education (MoNE).32
Data Collection and Instruments For the data collection, there were different questionnaires for each level of SEM and focus group discussions at the end of the intervention (Figure 2). These levels of influence were aimed to develop within a 12-week period of time with the following instruments.
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Intrapersonal Level of the Social-Ecologic Model Health-Related Fitness Knowledge. HRF knowledge was
assessed using the translated version of the Super Kids-Superfit questionnaire.33 The Turkish version of the Super Kids-Superfit questionnaire was adapted according to the Turkish physical education curriculum for HRF knowledge standards of primary schools32 and validated by Hunuk and Ince.34
Physical Activity Level. Student physical activity level was
assessed at the beginning and end of the intervention using pedometers (SILVA) [Sollentuna, Sweden] for 7 consecutive days. The pedometer is an accurate, objective, and low-cost measure of walking compared with pen and paper questionnaires and acceptable tool for estimating PA levels of children.35 Every student in the study wore a pedometer on their right hip, and every day the students wrote down the number of daily steps for 1 week before and during the last week of the intervention.
Figure 2 — Overall designs of the study and data collection methods.
Self-Efficacy and Proxy Efficacy of Children for After-School Physical Activity. Proxy efficacy was defined as the confidence
of children in their skills and abilities to get parents to respond to their interest in providing physical activity opportunities. The proxy efficacy of participants was measured under 3 subcategories; selfefficacy to be physically active (SEPA, 5 items), proxy efficacy to influence after-school staff to provide PA opportunities (PEPA-S’ 4 items) and proxy efficacy to influence parents to provide PA opportunities (PEPA-P, 6 items) using 3-point Likert-type scales choosing from “not agree at all (1),” “somewhat agree (2),” and “completely agree (3).” The maximum score from each subscale were 15, 12 and 18 (high efficacy). Self-efficacy and proxy efficacy scales were developed and validated among children by Dzewaltowski et al.36 The Turkish version of the instrument was validated by Cengiz and Ince.37
Interpersonal Level of SEM Perceived Social Support for Physical Activity. The instrument,
which consisted of 14 items on a 5-Point Likert-type scale with anchors 1: Never and 5: Every day. The maximum score from each subscale was 25, 25 and 20 (high support). The questionnaire was developed by Sallis et al.38 The aim of the questionnaire was to evaluate the opinions of parents and peer about perceived social support related to participation in physical activities. The Turkish version was validated in a middle school sample by Hunuk et al.39
Organizational and Community Level of SEM The third and fourth levels of the SEM focus on organization level, such as rules, regulations, policies, and informal structures, which may constrain or promote the recommended behavior. The community level mainly focuses on social networks and norms or standards which are formal or informal among individuals, groups, and organizations.
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Public Policy Level of the SEM Educational Policy Drivers. The Turkish context has been supported by 3 main policy drivers, as follows: (1) talent identification and developing athletes performing at the international level, (2) improving the HRF knowledge in everyone, and (3) education through physical activity or education. The first perspective was mainly stated by the General Directory of Youth and Sports.40 Specifically, the formal school system (the MoNE) supports improving the HRF from all perspectives. The report of the Turkish National Burden of Disease41 by the Ministry of Health42 (MoH) emphasized the increased health expenses and lowered health quality due to a sedentary lifestyle among the Turkish population. Overall, the MoH was supporting physical activity-based health promotion programs for all ages, including school-aged children (eg, educational materials and information bulletins). In another perspective, the HRF reflected the school physical education curriculum by the MoNE. The primary physical education curriculum was mainly rooted in 2 main learning areas (development of skills and HRF knowledge). The last perspective was aimed at education through physical activity or education that was supported by the MoNE documents. The main role of physical activity and physical education was emphasized not only for psychomotor development, but also for affective, social, and cognitive development of pupils in the curricular documents. Focus Groups. Two focus groups with boys (N = 12) and 2 focus groups with girls (N = 14) were randomly selected from the intervention group and discussions were conducted by independent expert researchers from the Physical Education and Sports Department. The groups were separated by gender to help the participants feel comfortable and share experiences.43 Discussions were conducted in the experimental school in an empty classroom during lunch breaks or class time, which lasted between 30 and 45 minutes. Each session was tape recorded and notes were transcribed by the researcher. Four main themes were constructed after the content analysis.
Data Analysis Quantitative data were examined by descriptive (mean and standard deviation) and inferential statistics, including repeated measures of
analyses of variance (RM ANOVA) after the normality assumption checks by Kolmogorow-Smirnov, Skewness and Kurtosis, Box’s M test, and Levene’s Test (P < . 05). Focus group transcriptions were examined with the content analysis method.43 After audio-taped focus group interviews were fully transcribed, data were read word by word to drive codes. Then, codes were sorted into categories. These categories were used to organize and group codes into meaningful clusters. Lastly, exemplars for each cluster were identified.
Results Intrapersonal Level of the Social-Ecologic Model The results of HRF knowledge test with RM ANOVA indicated that there was a statistically significant main effect for school (Wilks’s λ = .84; F(1,60) = 59.83; P < .05). The multivariate η2 based on Wilks’s λ was quite strong (η2 = . 50) based on Cohen’s classification.44 In addition, descriptive statistics demonstrated an increase in the experimental group (Table 2) compared with the control school. Similarly, the physical activity levels of students were examined with RM ANOVA in both schools with respect to the second research question. The results showed that there was a statistically significant main effect for school (Wilks’s λ = .88; F(1,60) = 7.83; P < .05). The multivariate η2 based on Wilks’s λ was moderate44 (η2 = . 11). The descriptive statistics also indicated an increase in the level of physical activity in the experimental group (Table 2). RM ANOVA was performed to determine school differences in perceived physical activity of the self-efficacy, staff and parent efficacies of students. There were no significant differences between self-efficacy and schools (Wilks’s λ = .93; F(3,58) = 1.50; P > .05). In contrast, the descriptive statistics indicated an increase in the selfefficacy of the experimental group (Table 2); however, this increase was not statistically sufficient for a significant effect (P > .05).
Interpersonal Level of SEM For research question 4, the perceived social support of students was examined with RM ANOVA and the findings indicated that there was a statistically significant main effect for school (Wilks’s λ = .86;
Table 2 Descriptive Statistics of Health-Related Fitness Knowledge, Physical Activity Levels, Self-Efficacy, Staff Efficacy, Parent Efficacy, Mother Support, Father Support, and Friend Support Pretest
Posttest
Experimental
Control
Experimental
Control
Mean/SD
Mean/SD
Mean/SD
Mean/SD
20.67 ± 4.92
20.84 ± 3.26
27.71*±4.92
19.74 ± 4.19
Weekly steps (daily)
12322.60 ± 3160.23
9743.30 ± 3386.25
14752.42*±3189.15
10535.50 ± 3535.62
Steps (weekdays)
12986.13 ± 3348.15
9894.30 ± 3496.85
14629.54 ± 3332.89
10691.04 ± 3754.99
Steps (weekends)
10663.77 ± 4156.20
9365.81 ± 4001.99
15059.61 ± 4086.04
10146.66 ± 4488.95
10.03 ± 2.01
9.74 ± 2.11
10.93 ± 2.20
9.77 ± 2.23
HRFK
Self-efficacy Staff-efficacy
8.48 ± 1.31
7.77 ± 1.76
8.97 ± 1.89
7.39 ± 1.86
Parent-efficacy
11.97 ± 2.01
11.74 ± 3.04
13.87 ± 2.36
12.42 ± 2.75
Mother support
7.74 ± 3.57
8.03 ± 3.32
11.48*±4.17
8.64 ± 4.28
Father support
8.00 ± 3.89
8.13 ± 3.72
10.93*±4.37
8.48 ± 4.81
Friend support
10.74 ± 4.43
10.52 ± 3.27
11.51 ± 3.59
10.23 ± 3.84
* P < .05. Abbreviations: HRFK, Health Related Fitness Knowledge.
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F(3,58) = 3.08; P < .05). The multivariate η2 based on Wilks’s λ was a moderate effect44 (η2 = .14). Before conducting further analysis (paired sample t test) to detect the significant difference, alpha level was adjusted (P = .016) using the Bonferroni correction method to avoid the risk of making a type II error.45 The dependent sample t test results indicated that students in the treatment school made a difference (MD = –3.74, SD = 3.73) for the mother, (MD = –2.93, SD = 4.08) for the father, and (MD = –.77, SD = 4.59) for friends from the pre- to posttest. Except for support from the friend, this difference was statistically significant for support from the mother [t(30) = –5.58, P < .016] and support from the father [t(30) = –4.00, P < .016]. In contrast, the control school had no significant effect on the support from the mother [t(30) = –.76, P > .016], support from the father [t(30) = –.39, P > .016], and support from the friend [t(30) = –.39, P > .016]. The results obtained from the descriptive statistics of perceived social support indicated an increase in the scores (Table 2). To understand whether the social-ecologic approach changed the knowledge about physical activity among rural middle school students, level and social support focus group interviews were conducted. Four separate groups were randomly selected from the EXP school and conducted by independent expert researchers. Four main themes were constructed and listed by content analyses, as follows: (1) increased physical activity opportunities by the physical activity preferences and physical activity needs of students, (2) increased data sources to reach sport- and physical activity–related knowledge, (3) increased perceived support from significant others, and (4) influence of perceived stress of the academic exam for secondary schools (AESS) on extracurricular activity participation. The following statements from students indicated their views about the changes in physical activity knowledge and behaviors of each theme. Students commented that their physical activity participation was increased by new school physical activity opportunities. Physical activities in courses were chosen according to student preferences in after-school activities. Different physical activity opportunities were provided and supported by the school principal, families, school Council, and local municipality for both genders. Students commented about this in the interview, as follows: “From the beginning of the spring semester, we do sports 3 times a week and we have had facilities since then. The new facilities included a climbing iron, horizontal bar, soccer goalposts, volleyball court, volleyball net, balls, sandbox for long jump, and table tennis.” (a 13-year-old male student) “I love soccer most. As a hobby, I play table tennis. Because soccer is the opportunity we have most here (in school) we can play. At the basement, there is a table tennis.” (a 13-year-old male student) “. . . Last year, there were only basketball poles. Our teacher provided soccer goalposts, then a horizontal bar, a volleyball court, and a climbing rope.” (a 13-year-old female student) “When he (physical education teacher) came, he brought balls. . . . There was no volleyball net or soccer goalposts, but our physical education teacher provided them. There was no climbing iron, and he provided that, too. Because of him, we can participate in many physical activities. . . .” (a 12-year-old male student) Students also commented about the increased data sources to reach sport- and physical activity–related knowledge in the focus group, as follows:
“We were receiving information through the internet, television, school library, notice boards, and encyclopedias. In addition, this year we had an instructor who is a specialist in volleyball for 80 minutes during the after-school period. We have learned volleyball rules and techniques, such as passes (overhand pass etc.) and attack. . . .” (a 14-year-old female student) “We searched different types of sports (tennis, triathlon, and rugby) related to performance work in the physical education course. The basic sources were the internet, school library, and teachers.” (a 13-year-old male student) “. . . For example, we learned basketball. He gave us information about them. . . . For example, what causes lifting weight? Increases muscle size.” (a 13-year-old male student) “PowerPoint presentations, heart rate of our bodies, what should be the recommended daily steps for healthy life. . . .” (a 13-year-old female student) The third theme was the influence of increased perceived support from significant others. Students described the increased social support in the following way: “Our families supported our participation in this after-school program to become healthier. They provided transportation. Other than our families, my big brother, physical education teacher, and volleyball instructor supported our participation.” (a 13-year-old female student) “I am supported by my family, too, physical education teacher, and volleyball coach. . . . My family wanted me to become taller, muscular, and healthier.” (a 12-year-old female student) The last theme was the influence of perceived stress of the AESS on extracurricular activity participation. Participants in the focus group also discussed the perceived stress to participate in physical activities lately as follows: “There is no one or any condition preventing us from this program. The only condition is we do not have much time from the other subjects that are in the middle-school curriculum.” (a 13-year-old male student) “No, there is not, except our courses. But there is the academic exam for secondary school and we must get high scores in the exam so we have to study. We have term projects and performance work; therefore we do not have time for sports. Always courses!” (a 13-year-old female student) “This program did not affect my other subjects.” (a 14-yearfemale student) The overall findings of the focus group discussions supported the quantitative findings of the SEM. Changes related to physical activity knowledge and behavior were evident in the current study.
Discussion The findings of the current study indicated that a 12-week socialecologic intervention was effective in improving HRF knowledge, the level of physical activity, and perceived social support of rural middle school students. Each research question of the study will be discussed in order. The baseline measurements involving 36 items in the HRF knowledge average test scores showed significant improvements in the posttest evaluation. In addition to descriptive statistics, the RM ANOVA results indicated that there was a statistically significant effect for the intervention school (P < .05).
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As Dilorenzo et al46 noted that the HRF knowledge of middle school students was a determinant of the exercise behavior of children. Stewart and Mitchell47 summarized that most students were not able to identify correct fitness components and were not able to match the HRF construct with the Fitnessgram test item.48 In this context, the social-ecologic intervention was fairly effective and students increased their HRF knowledge significantly. The Turkish primary physical education curriculum32 and HRF knowledge standards and their objectives need to be examined in a larger sample with HRF knowledge tests in elementary schools. Another study by Placek et al49 used qualitative methods to investigate middle school student HRF knowledge. Researchers found that students had misconceptions concerning fitness variables. More importantly, the authors reported pupils had the same erroneous fitness knowledge as students have 20 years earlier.28 Similar results and misconceptions were also found among high school pupils in fundamental HRF knowledge28,47 and elementary schools.27,50 Therefore, the HRF knowledge of pupils needs to be increased with effective strategies and methodologies. As a second research question, this study aimed to increase the level of physical activity of students. The results revealed that SEM had a statistically significant effect on physical activity levels of experimental students. The measurements were obtained over 7 consecutive days of a week. Based on daily steps, boys were more active than girls in the experimental group at the baseline measurement. In the control group, similar findings were also identified in both sexes. After the 12-week period of intervention based on the SEM, the treatment school had increased their level of physical activity in both sexes compared with the control school. Overall, the average steps taken in a weekdays increased significantly in the experimental school for both sexes. These results raise the possibility that supporting the school environment with multilevel approaches could increase the level of physical activity of students. These findings were also consistent with previous research that identified a significant effect on the level of physical activity in children with pedometer measurements.26,51,52 Experimental school students also increased their steps at weekends for both sexes. As a result of weather conditions this increase seemed to be high. However, Loucaides et al53 concluded that the levels of physical activity varied by season among rural and urban children. Those children in rural areas were most physically active in the summer months24 compared with urban children who were most physically active in the winter months. Lastly, type of sport was another contribution to the PA level of students. Perceived self-efficacy results indicated no significant differences between the groups. Although there was no statistical significance between the groups and subjects, there were small improvements noted between the group variables with higher improvements in the experimental school. These findings revealed that the SEM has an effect on self-efficacy variables, but this improvement was not sufficient for a statistically significance difference among the students. The limited number of pupils that participated in the school could be an important factor on the outcomes. The second factor may have been the self-efficacy of physical activity levels that was already high before the study; however, high parent efficacy values supported that the perceived social support of students was critical between self-efficacy and parental support. This striking finding was crucial when studies focused on increasing the parental support of students. We need to support both dimensions when increasing physical activity knowledge, level, and behavior of middle school students. Similarly, Shield et al54 examined self-efficacy and
parental social influence related to physical activity. The results of this research revealed support for self-regulatory efficacy as a mediator and the parental influence effect on youth and adolescent physical activity. Lastly, the activity type that was chosen by the pupils before the study might have affected the self-efficacy scores. Playing soccer and volleyball may not be effective in increasing self-efficacy as compared with individual sports (eg, gymnastics, tennis, or track and field). The perceived social support of the current study revealed a significant effect on the physical activity behavior of pupils in the middle school sample. As the literature suggested, parental support was one of the key correlations of physical activity behavior in children.4,55 However, little is known about which component of parental support was more effective in promoting physical activity behavior, and how it contributed to the exercise behavior of children. The current study analyzed the perceived social support of parents to physical activity behavior. Statistical analyses revealed that social support for physical activity increased through the SEM. Further analysis with descriptive statistics indicated that mother and father support values were higher in the treatment school related to the physical activity behavior of students. Notably, we found no evidence of a statistically significant effect on peer support for physical activity behavior of students. Similar findings were reported by Hunuk and colleagues39 in a private Turkish middle school sample. Participants received more support for their physical activity participation from their families compared with their friends. This cross-sectional design was further analyzed in the current study, thus providing stronger design and a different sample. Another reason for the significant effect of parental support could be the health bulletins related to the social-ecologic intervention and health benefits of physical activity were sent to every family, and usually mothers or fathers read or received the information. In the same manner, findings of focus group discussions indicated that students positively perceived the changes in their environment which were guided by the social-ecological framework. Students were able to identify the increased physical activity opportunities and facilities in their environment, integration of physical education lessons with extracurricular activities and life, increased physical activity participation, increased data sources to reach sport and physical activity–related knowledge, increased knowledge sources in the library, and increased perceived support from the significant others. It is clear that if the learning environment of the students is changed with a social-ecologic framework, student learning in physical education will be stimulated toward the current physical education curriculum goals in primary schools. The primary school curriculum underlines the importance of connecting physical education lesson with extracurricular activities and life.29 The focus group discussions proved that this connection was achieved. In the physical education literature, integration of physical education lessons with life and developing lifelong physical activity behavior has been the most discussed topic55,56 however; it has been an unresolved issue. The perceptions of the students in this study present encouraging results toward effective methods to ensure reaching this outcome by the SEM. Student statements about sports- and physical education-related knowledge and data sources were also important findings in focus group interviews. The findings indicated that students used alternative knowledge sources, including physical education lessons, internet data sources, books, and significant others, instead of using very limited sources, such as using only physical education teachers or friends. This finding implied that the teacher’s role in
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guiding students to use alternative knowledge sources is important and effective in learning. Focus group interviews also indicated some of the students’ negative perceptions of the AESS as a limiting factor in participating in physical activity. This is a very important public concern in Turkey. There is a need to work on why students perceive this issue as limiting factor for participation. Normally, HRF-related physical activity participation does not require as much time as performance- or skill-related sports participation. Instead, it can be expected that through participation in HRF related to physical activity, students would probably relax, improve the stress level, and increase academic performance.57,58 These findings suggest that in general the value of SEM in improving HRF knowledge, physical activity level, and social support of students in rural middle school settings. The evidences from this study suggest that SEM is an effective model which supports physical activity behavior of middle school students living in rural settings. Further studies on SEM and applying with different levels of the model in urban settings are strongly recommended. In addition, using a sedentary group with no intervention is recommended for future studies. Acknowledgments This research was supported by a grant (Grant No: BAP- 05-04-2010-03) from Middle East Technical University, Scientific Project Support Program.
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