The Effect of the Physical Activity Program Developed According to the Precede-Proceed Model on the Physical Activity Level and Physical Activity Behavior of Elementary School Students

doi:10.21203/rs.3.rs-3687443/v1

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The Effect of the Physical Activity Program Developed According to the Precede-Proceed Model on the Physical Activity Level and Physical Activity Behavior of Elementary School Students

https://doi.org/10.21203/rs.3.rs-3687443/v1

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Background

While obesity rates among children and adolescents have increased significantly in recent years, a decrease in physical activity among children has been widely attributed to this alarming situation. The present study aims to investigate the effect of the physical activity program developed according to the Precede-Proceed Model on children's physical activity level and physical activity self-efficacy, attitude, enjoyment level, and exercise change behaviors.

Methods

This study was developed according to the Precede-Proceed model and carried out in an experimental design with the pre-test-post-test control group. Considering the possibility of data loss during the research, 178 students were included in the study, 89 in the intervention group and 89 in the control group. The study period was from October 2021 to March 2022. Data was collected using Child Information Form, The Physical Activity Questionnaire for Older Children (PAQ-C), Physical Activity Self-Efficacy Scale (PASS) and Attitude toward Physical Activity Scale (APAS). In consultation with school administrators and classroom teachers, a physical activity program was developed using the Precede-Proceed model so as not to disrupt student instruction. The exercises were carried out three days a week for 30 minutes in the school garden and gym, and the training was carried out in the classrooms one day a week.

Results

It is seen that there is a significant difference between the mean scores of the children's physical activity questionnaire at interim follow-up (t=2.885, p<0.01) and post-test (t=12.588, p<0.01) between the groups of students (p<0.05). There was a significant difference between the two groups in terms of post-test physical activity self-efficacy scale scores (p <0.05). It is seen that there is a significant difference between the groups in terms of the APAS at the interim follow-up (t=4.157, p<0.01) and post-test (t=9.197, p<0.01) scores (p<0.05).

Conclusions

The physical activity program developed according to the Precede-Proceed Model increased children's physical activity levels as well as their self-efficacy and attitudes toward physical activity.

Precede-proceed model

School nursing

Physical activity

Child

While obesity rates among children and adolescents have increased significantly in recent years, a decrease in physical activity among children has been widely attributed to this alarming situation [1]. Due to environmental factors, changes in children's play methods with the development of technology, a decrease in the rate of active travel, changing parental rules and school policies due to the COVID-19 (2019 Coronavirus disease) pandemic, the opportunity for children and young people to be physically active has decreased in many countries in recent years. Only one-fifth of children today can do the recommended 60 minutes of moderate-intensity physical activity seven days a week [1, 2]. Thus, public health strategies are needed to encourage children to be physically active when school education resumes. It is believed that children participating in the recommended exercises during school days will allow them to follow the healthy lifestyle behaviors provided by physical activity again and regularly [3].

Given that the habits acquired during childhood shape adult behaviors, acquiring exercise and movement habits during childhood is vital to community health [4, 5]. Considering that children spend a significant part of the day at school or preschool education, school environments provide access to a large number of children with different socioeconomic and sociocultural levels, creating opportunities for initiatives to be implemented in the protection and development of health [6]. Since behavioral development is acquired at a young age, health improvement programs prepared and conducted by a good guide in the school environment help children achieve a healthy lifestyle [7]. The pediatric nurse plays a key role in the development of health protection and development programs that involve educating students, cooperating with other professionals, coordinating activities, communicating and consulting with members of the society in which they operate [8, 9]. Nurses use different models and theories in the creation of health promotion programs. Models and theories ensure that nursing care is provided in a professional manner, that care practices are understandable, and that situations that may be overlooked are identified in advance. One of the models used to create behavioral change in the protection and promotion of health is the ' Precede-Proceed Model '. The Precede-Proceed Model is a model that takes into account factors that are effective in improving health behavior in people and directs programs created to improve public health [10, 11]. Precede-Proceed is a structured health program planning model aimed at improving the quality of life of the target group by using educational and planned initiatives. It provides a logic model that can form the basis for health promotion programs and projects [12]. Precede, the first stage of the model, is the diagnostic part of the process and forms the stage of determining and planning requirements. Meanwhile, proceed is the treatment part of the model with the initiatives to be implemented and includes the design, plan, implementation, and evaluation of the initiative [12–14]. It has been noted in the literature that children's physical activity behaviors have changed in recent years as a result of changing living conditions and environments [1, 4, 6, 8, 15]. Parents, siblings, teachers, and friends in the child's social environment have a significant impact on the decrease in physical activity levels. Parents' physical activity behaviors, changing environmental conditions, and developing technology directly affect children's self-efficacy, attitude, expectation of exercise, health perception, and physical activity behaviors [16, 17]. Physical activity in children will create behavioral changes and the preparatory, empowering, and enabling factors that will enable them to maintain this behavior have been classified. The preparatory factors were defined as students' knowledge of the health benefits of physical activity and belief that physical activity is important for a healthy lifestyle, physical activity level, physical activity attitude, and physical activity self-efficacy. Empowering factors include social support networks such as the influence of parents, peers, teachers, and mentors. Teachers, classmates, and parents are involved in the physical activity program applied to the students. The physical activity program was implemented in the school environment under the leadership of teachers and nurses, and peer and guidance support was provided. The students reinforced the skills and health information they learned every week in the physical activity program by sharing with their parents with the help of brochures prepared by the researcher and learned with their influence. The enabling factor includes the design of the physical activity program implemented for the purpose of developing children's physical activity behavior and the environment created for children to demonstrate their physical activity skills.

The present study aims to investigate the effect of the physical activity program developed according to the Precede-Proceed Model on children's physical activity level and physical activity self-efficacy, attitude, enjoyment level, and exercise change behaviors.

The Precede-Proceed Model is an effective process to guide every step in the development of sustainable health behavior and provides a template for the design, planning, implementation, and evaluation processes of the initiative to be applied to a target audience [12].

Design and sample

This study was developed according to the Precede-Proceed model and carried out in an experimental design with the pre-test-post-test control group. The study period was from October 2021 to March 2022. The population of the research consisted of the students of [A] and [B] Primary School, affiliated with the Directorate of National Education, located in the [Y] district of [X]province. To avoid any interaction between the students, lots were drawn between the two schools, and the fourth-grade students of [A] Primary School were selected as the intervention group and the fourth-grade students of [B] Primary School were selected as the control group. Power analysis program (G-Power 3.1.9.4.) was used to calculate the sample size [18]. Taking into account the research design with 2 groups (1 Intervention, 1 Control) and 3 measurements (Pretest, Posttest 1, Posttest 2) while calculating the ANOVA Test for Repeated Measures (Pepeated Measures ANOVA), the required number of samples was determined as 142 based on an average effect size of 0.25, a margin of error of 0.05 and a power of 95% [19]. Considering the possibility of data loss during the research, 178 students were included in the study, 89 in the intervention group and 89 in the control group. A total of participants were included in the study, who were enrolled in the fourth grade at the designated schools, did not have chronic and metabolic diseases or disabilities, did not have significant mobility limitations, could read and write, and whose families agreed to participate and gave their consent.

Data collection instruments

Child Information Form

The 'Child Information Form' was created by the researcher to determine the student's personal information, physical activity characteristics, body weight, height, and demographic characteristics. Body weight was measured without the students' heavy clothing (shoes, coats, etc.) using a precision scale that was regularly calibrated. The height of each individual was measured using a height meter placed on a flat surface without shoes on. To evaluate the Body Mass Index (BMI) of the students, the national percentile curves appropriate for age and gender were utilized, as developed by Neyzi et al. (2008) [20].

The Physical Activity Questionnaire for Older Children (PAQ-C)

The scale developed by Kowalski et al. (1997) is used to determine the physical activity level of adolescents [21]. The validity and reliability study of PAQ-C in Turkish was conducted by Erdim et al. (2012) with Turkish children aged 9–14 attending primary school (Cronbach's alpha coefficient: 0.86). Developed to assess children's physical activity, the questionnaire form consists of 10 questions the child can fill out on his or her own. The questions assess the child's activity level over the previous seven days. A 5-point Likert scale was used in the survey, where a rating of 1 indicates the lowest level of physical activity and a rating of 5 indicates the highest level of activity. To calculate the total score for the first question, the sum of the scores given to all activity items is divided by 14. Similarly, the 9th question, which evaluates physical activity over a seven-day period, is scored by dividing the weekly total by seven. The remaining 7 questions are scored on a 5-point scale, with higher scores indicating higher levels of activity. A child's total physical activity score is calculated by adding up their responses to the first, second, third, fourth, fifth, sixth, seventh, eighth, and ninth questions and dividing by the number of questions. An average score of "1" indicates a low level of physical activity, while an average score of "5" indicates a high level of physical activity [22]. Cronbach's alpha was found to be 0.85 in the pre-test measurements.

Physical Activity Self-Efficacy Scale (PASS)

The Child Physical Activity Self-Efficacy Scale (PASS) was developed by Edmundson et al .(1996). The Turkish validity and reliability study of the scale was conducted by Meydanlıoğlu and Ergün (2013) with fourth-grade primary school students. It consists of five items and is a three-item Likert-type scale. Cronbach's alpha coefficient for the scale is 0.67 [23]. The scale, consisting of five items, is designed as a triple Likert-type scale with a single-factor structure. The items are rated as -1 (uncertain), 0 (somewhat confident), and + 1 (very confident), with a total score ranging from − 5 to + 5. High scores obtained from the scale indicate higher self-efficacy. Cronbach's alpha was found to be 0.66 in pre-test measurements.

Attitude toward Physical Activity Scale (APAS)

The APAS, which is used to determine primary school students' physical activity participation, was developed by Yıldızer et al. (2019). It has been reported that the scale is a valid and reliable measurement tool for determining the physical activity attitudes of primary school students aged 12–15. The reliability values of the sub-dimensions calculated according to the Cronbach Alpha coefficient were calculated as Willingness 0.85, Affection 0.83, Socialization 0.82, Benefit 0.75, and Self-Confidence 0.70. When all items were assessed together, the reliability coefficient was calculated as 0.91. In the measurement tool designed in 5-point Likert type, the answering scale is "1 = Strongly Disagree", 2 = Disagree", "3 = Unsure", "4 = Agree", "5 = Strongly Agree" and according to the total score of the answers given to the items, the high score obtained from a sub-dimension indicates a high attitude, while the low score indicates a low attitude. 'APAS' consists of willingness, affection, benefit, socialization, and self-confidence sub-dimensions. The obtained sub-dimensions were expressed as Affection (5 items), Willingness (7 items), Benefit (5 items), Socialization (4 items) and Self-Confidence (4 items). 1,2,3,4,5,6,7,22,23,24,25. the substances are encoded in reverse [24]. Cronbach's alpha was found to be 0.88 in pre-test measurements.

Figure 1 is here.

Intervention

“The Physical Activity Program Developed According to the Precede-Proceed Model consists of "exercises that primary school children can do and training that include the effects of physical activity on health. The physical activity program consists of two parts: exercise and education. Program content validity was presented to expert opinion (eight academicians, two sports physicians, three physical education and sports specialists, and three child health and disease nursing specialists) with the Quality Criteria for Consumer Health Information (DISCERN) tool and Necessary headings have been edited. Mean, standard deviation and Kendall correlation tests were used in the evaluation of expert opinions [25]. In expert opinions, the reliability mean score was determined as 35.2 ± 3.90, the information quality mean score was determined as 28.2 ± 5.21, and the general evaluation was 4.80 ± 0.52 (Fig. 1).

In consultation with school administrators and classroom teachers, a physical activity program was implemented so that students' classes would not be disrupted. Exercises in the program include light and moderate movements that may be performed by a healthy fourth-grade student (9–10 years of age). Sport physicians have advised that there is no need for any health screening, as children's hearts, pulses, and muscles are not affected by light and moderate exercises. The exercises were carried out three days a week for 30 minutes in the school garden and gym, and the training was carried out in the classrooms one day a week. Classroom teachers and teachers in the school administration were also involved in the exercises. On exercise days, students were encouraged to come to school in comfortable clothes. Throughout the program, exercises included ' belly and abdominal movement sets ' in the first four weeks, ' leg and hip movement sets ' in the following four weeks, and ' arms, shoulder, and chest movement sets ' in the final four weeks, as well as yoga movements. The brochures prepared for the training were presented to the students by the researcher on a smart board in the classroom environment (one class was taught every day). The training content includes the following titles: exercises, basic movements and different types of physical activity, benefits of physical activity for our bodies, harms caused by sedentary lifestyles, obstacles to physical activity, stories of successful people with active lives, simple exercises that can be performed at home, and methods for having fun while performing physical activity. The educational content was based on a health theme each week, and the learning goals were met. Themes are ' be active and stay healthy ', ' discover your body ', ' move for health ', ' determine your style ', ' stay still ', ' I know no obstacles ', ' stay up and survive ', ' succeed with exercise ', 'exercise fits at home ', ' choose the activity you like', ' have fun while staying active ' were created specifically for each week and repeated with the students during the exercises. For the continuous benefit of families and children, brochures have been published on the school's website under the title ' Physical Activity Program', with the permission of the school administration ( https://xxxxxx ). In addition, a message from the classroom communication group was sent to the parents of the students by the teachers informing them of the Internet link containing these brochures and exercises. Involving teachers and parents in the implementation process of the physical activity program is aimed at strengthening the attitudes and behaviors that are expected to change in students. Teachers also participated in physical activities together with children. The responsible teacher of each class and the branch teachers who did not have a lesson practiced the exercises together with the children three times a week. Parents did not participate in the school exercise part of the program. The physical activity program was shared with parents through teachers and they were informed to practice the exercises with their children at home. Brochures were shared with parents via mobile application.

Data analysis

The data of the study were analyzed using SPSS 22 (IBM Corp. Released 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp.) Statistical methods (number, percentage, mean, standard deviation) were used to evaluate socio-demographic data. Chi-square analysis was conducted to analyze the homogeneity of the groups. It was tested whether the data used fit the normal distribution. Compliance with the normal distribution can be examined by drawing a Q-Q Plot [26]. In addition, the normal distribution of the data used depends on the skewness and kurtosis values being between ± 2 [27]. Independent t-test was used for the difference between two independent groups in the comparison of quantitative data in normally distributed data, whereas in the comparison of more than two dependent stages, repeated measures multivariate analysis of variance was applied and Bonferroni test was used to find the stage that made a difference. In further analysis of the difference between groups, two-way analysis of variance in repeated measurements was applied to determine the difference in terms of Group*Time interaction. There was no data loss in the study for any reason. There are no students who had to be excluded from the research sample.

Procedure

Students and their parents who participated in the research were informed that the information received will be kept confidential and will not be used in any other manner. When the data collection phase of the research was completed, the program was also applied to the students of the school in the control group.

When the socio-demographic characteristics of the students were analyzed, the mean age was 9.21 ± 0.53 in the intervention group and 9.21 ± 0.43 in the control group, 47.2% of the intervention group were female and 52.8% were male, and 44.9% of the control group were female and 55.1% were male. The mean number of siblings of the students in the intervention group was 1.13 ± 0.56 and the mean number of siblings in the control group was 1.19 ± 0.83. When the characteristics of the parents of the students were analyzed, it was found that 57.3% of the mothers of the students in the intervention group and 551.7% of the mothers of the students in the control group were employed. There was no difference between the groups (Table 1).

Table 1

Distribution of intervention and control groups by sociodemographic characteristics
Variables		Intervention		Control		Test value	p
Variables		\(\stackrel{-}{\varvec{X}}\)	SS	\(\stackrel{-}{\varvec{X}}\)	SS	Test value	p
Age		9.21	0.53	9.21	0.43	0.000**	1.000
Number of siblings		1.13	0.56	1.19	0.83	-0.524**	0.601
Gender	Female	42	47.2	40	44.9	0.090***	0.764
Gender	Male	47	52.8	49	55.1	0.090***	0.764
Level of income	Low	4	4.5	5	5.6	0.118***	0.943
	Medium	71	79.8	70	78.7
	High	14	15.7	14	15.7
Mother's employment	Yes	51	57.3	46	51.7	0.566***	0.452
Mother's employment	No	38	42.7	43	48.3	0.566***	0.452
Mother's education level	Literate	4	4.5	1	1.1	4.968***	0.291
	Primary school	7	7.9	6	6.7
	Middle school	10	11.2	14	15.7
	High school	25	28.1	34	38.2
	University and above	43	48.3	34	38.2
Father's employment	Not working	8	9.0	2	2.2	12.132***	0.025*
	Worker	37	41.6	35	39.3
	Officer	24	27.0	19	21.3
	Tradesmen	13	14.6	29	32.6
	Other	7	7.9	4	4.5
Father's education level	Literate	6	6.7	2	2.2	5.578***	0.233
	Primary school	6	6.7	3	3.4
	Middle school	10	11.2	14	15.7
	High school	23	25.8	32	36.0
	University and above	44	49.4	38	42.7
Total		89	100.0	89	100.0
p < 0.05, * Independent samples t-test, *** Chi-square analysis

Table 1 is here.

Body Mass Index

In pre-test measurements, it was determined that 2.2% (n = 2) of the students in the intervention group were underweight, 86.5% (n = 77) were normal, and 11.2% (n = 10) were overweight, while in the control group, 2.2% (n = 2) of the students were underweight, 87.6% (n = 78) were normal weight, and 10.1% (n = 9) were overweight. Considering the mean BMI values of the students, there is no significant difference between the groups (p > 0.05). It is seen that there is no significant difference between the pre-test, interim follow-up, and post-test BMI values of the intervention group (p > 0.05) (Table 2).

Table 2

Comparison of BMI values of intervention and control groups
			Intervention		Control		Test value	p
			\(\stackrel{-}{\varvec{X}}\)	SS	\(\stackrel{-}{\varvec{X}}\)	SS	Test value	p
BMI	Pre-test	19.11	3.57	18.71	3.57	0.758**		0.450
	Follow up	18.96	3.74	18.66	3.49	0.556**		0.579
	Post-test	18.92	3.74	18.80	3.62	0.217**		0.828
Test value		2.071***		0.786***
p		0.129		0.457
		\({F}_{group}\)= 0.264, 0.608 \({F}_{time}\)= 0.427, 0.840 \({F}_{group*time}\)= 0.936, 1.842
p < 0.05, * Independent samples t-test, ***Analysis of variance in repeated measures

Table 2 is here.

Physical Activity Level

It is seen that there is a significant difference between the mean scores of the children's physical activity questionnaire at interim follow-up (t = 2.885, p < 0.01) and post-test (t = 12.588, p < 0.01) between the groups of students (p < 0.05). It is seen that the interim follow-up and post-test child physical activity survey score averages of the intervention group are higher than the control group. There was a significant difference between the intervention group's child physical activity questionnaire mean scores of pre-test and interim follow-up (p < 0.01), pre-test and post-test (p < 0.01), and interim follow-up and post-test (p < 0.01). It is noticed that the mean score of the post-test child physical activity questionnaire is higher than the mean scores of the pre-test and interim follow-up. It is seen that the mean score of the interim follow-up child physical activity questionnaire is higher than the mean pre-test score. Regarding the group*time interaction of groups according to time, when the child physical activity questionnaire scores were examined, it was seen that the difference between groups (F = 27.164, p < 0.01), the difference between times (F = 39.905, p < 0.01) and the interaction of group*time (F = 67.526, p < 0.01) was significant (p < 0.05). Dec.1, Dec.1, p < 0.01, p < 0.01).

It is seen that there is a significant difference between the post-test (t = 9.407, p < 0.01) score averages of the students in the extracurricular physical activity dimension according to their groups (p < 0.05). It was found that the post-test mean scores of the intervention group in the extracurricular physical activity dimension were higher than the control group (Table 3). In the intervention group, there was a significant difference between pre-test and follow-up (p < 0.01), pre-test and post-test (p < 0.01), and follow-up and post-test (p < 0.01) extracurricular physical activity dimension mean scores. It is seen that the post-test extracurricular physical activity dimension score average is higher than the pre-test and interim follow-up score averages. The mean score of the extracurricular physical activity dimension of the interim follow-up was higher than the pre-test scores. When the extracurricular physical activity dimension scores of the groups were analyzed in terms of group*time interaction, it was determined that the difference between groups (F = 9.656, p < 0.01), the difference between times (F = 38.076, p < 0.01) and the interaction of group*time (F = 46.037, p < 0.01) were significant (p < 0.05) (Fig. 2).

There was a significant difference (p < 0.05) between the interim follow-up (t = 5.481, p < 0.01) and post-test (t = 13.511, p < 0.01) mean scores of physical activities at school dimension between the two student groups. Besides, it was found that the interim follow-up and post-test physical activities at school dimension mean scores of the intervention group were higher than the control group. Moreover, there was a significant difference between the mean scores of the intervention group's pre-test and interim follow-up (p < 0.01), pre-test and post-test (p < 0.01), and interim and post-test (p < 0.01) physical activities at school dimension. It is seen that the post-test physical activities at school dimension score average is higher than the pre-test and interim follow-up score averages. Furthermore, the interim follow-up physical activities at school dimension mean score is higher than the pre-test score mean. When the physical activities at school dimension scores of the groups were analyzed in terms of group*time interaction according to time, it was found that the difference between groups (F = 52.960, p < 0.01), the difference between times (F = 11.776, p < 0.01) and group*time (F = 44.068), the interaction was significant (p < 0.05).

Table 3

Comparison of physical activity questionnaire scores of intervention and control groups
		Intervention		Control		Test value	p
		\(\stackrel{-}{\varvec{X}}\)	SS	\(\stackrel{-}{\varvec{X}}\)	SS
extracurricular physical activity	Pre-test (1)	2.86	0.79	3.01	0.84	-1.196**	0.233
	Follow up (2)	3.41	0.82	3.29	0.89	0.935**	0.351
	Pos-test (3)	3.86	0.59	2.94	0.71	9.407**	0.000*
	Test value	75.643***		10.033***
	p	0.000*		0.000*
	Effect size η²	0.462		0.102
	Boferroni	3 > 1, 3 > 2, 2 > 1		2 > 3
	\({F}_{group}\)= 9.656, 0.002* \({F}_{time}\)= 38.076, 0.000* \({F}_{grouptime}\)= 46.037, 0.000
		Intervention		Control		Test value		p
		\(\stackrel{-}{\varvec{X}}\)	SS	\(\stackrel{-}{\varvec{X}}\)	SS
physical activities at school	Pre-test (1)	3.44	1.02	3.42	0.93	0.128**		0.898
	Follow up (2)	4.10	0.83	3.37	0.94	5.481**		0.000*
	Pos-test (3)	4.43	0.55	3.04	0.78	13.511**		0.000*
	Test value	54.921***		6.929***
	p	0.000*		0.001*
	Effect size η²	0.384		0.073
	Boferroni	3 > 1, 3 > 2, 2 > 1		1 > 3, 2 > 3
	\({F}_{group}\)= 52.960, 0.000* \({F}_{time}\)= 11.776, 0.000* \({F}_{grouptime}\)= 44.068, 0.000
		Intervention		Control		Test value			p
		\(\stackrel{-}{\varvec{X}}\)	SS	\(\stackrel{-}{\varvec{X}}\)	SS
Physical activity questionnaire scores	Pre-test (1)	3.05	0.70	3.15	0.72	-0.855**			0.394
	Follow up (2)	3.64	0.72	3.32	0.77	2.885**			0.004*
	Pos-test (3)	4.05	0.51	2.97	0.62	12.588**			0.000*
	Test value	100.249***		10.865***
	p	0.000*		0.000*
	Effect size η²	0.533		0.110
	Boferroni	3 > 1, 3 > 2, 2 > 1		2 > 3
	\({F}_{group}\)= 27.164, 0.000* \({F}_{time}\)= 39.905, 0.000* \({F}_{grouptime}\)= 67.526, 0.000
p < 0.05, * Independent samples t-test, ***Analysis of variance in repeated measures

Table 3 is here.

Figure 2 is here.

Physical Activity Self-Efficacy

There was a significant difference between the two groups in terms of post-test physical activity self-efficacy scale scores (p < 0.05). It is seen that the post-test (t = 11.548, p < 0.01) physical activity self-efficacy scale scores of the intervention group were higher than the control group (Table 4). In the intervention group, there was a significant difference between pre-test and interim follow-up (p < 0.01), pre-test and post-test (p < 0.01), interim follow-up, and post-test (p < 0.01) physical activity self-efficacy scale scores. Bonferroni correction was applied to determine which measurement caused the difference. It is seen that the post-test physical activity self-efficacy scale scores are higher than the pre-test and interim follow-up scores. Besides, the interim follow-up physical activity self-efficacy scale scores are higher than the pre-test scores. When the physical activity self-efficacy scale scores were examined in terms of the group*time interaction of the groups according to time, it was seen that the difference between groups (F = 13.589, p < 0.01), the difference between times (F = 5.730, p < 0.01) and group*time (F = 32.791, p < 0.01) interaction appears to be significant (p < 0.05) (Fig. 3).

Table 4

Comparison of physical activity self-efficacy scale scores of the intervention and control groups
		Intervention		Control		Test value	p
		\(\stackrel{-}{\varvec{X}}\)	SS	\(\stackrel{-}{\varvec{X}}\)	SS
Physical activity self-efficacy scale scores	Pre-test (1)	1.76	2.50	2.02	2.15	-0.738**	0.461
	Follow up (2)	2.53	2.04	2.29	2.38	0.742**	0.459
	Pos-test (3)	3.12	0.97	0.64	1.77	11.548**	0.000*
	Test value	15.707***		22.243***
	p	0.000*		0.000*
	Effect size η²	0.151		0.202
	Boferroni	3 > 1, 3 > 2, 2 > 1		1 > 3, 2 > 3
	\({F}_{group}\)= 13.589, 0.000* \({F}_{time}\)= 5.730, 0.004* \({F}_{grouptime}\)= 32.791, 0.000
p < 0.05, * Independent samples t-test, ***Analysis of variance in repeated measures

Table 4 is here

Figure 3 is here.

Attitude Towards Physical Activity

It is seen that there is a significant difference between the groups in terms of the APAS at the interim follow-up (t = 4.157, p < 0.01) and post-test (t = 9.197, p < 0.01) scores (p < 0.05). It is noticed that the interim follow-up and post-test APAS scores of the intervention group are higher than the control group. When the sub-dimensions were examined, it was determined that the interim follow-up and post-test scores of the intervention group were significantly higher than the control group in the sub-dimensions of affinity, benefit, socialization, and self-trust (Table 5).

Moreover, in the intervention group, there was a significant difference between the APAS pre-test and interim follow-up (p < 0.01), pre-test and post-test (p < 0.01), and interim follow-up and post-test (p < 0.01) scores. It is seen that the APAS post-test scores are higher than the pre-test and interim follow-up scores. Furthermore, the interim follow-up APAS scores are higher than the pre-test scores.

When the APAS scores of the groups were analyzed in terms of group*time interaction, it was observed that the difference between the groups (F = 23.889, p < 0.01) and the group*time interaction (F = 26.673, p < 0.01) was significant (p < 0.05) (Fig. 4).

Table 5

Comparison of the physical activity attitude scale scores of the intervention and control groups
		Intervention						Control					Test value		p
		\(\stackrel{-}{\varvec{X}}\)	SS					\(\stackrel{-}{\varvec{X}}\)		SS
Willingness sub-dimension	Pre-test	27.61	7.19					28.20		6.18			-0.581**		0.562
	Follow-up	26.44	5.20					27.15		7.33			-0.743**		0.459
	Post-test	25.89	4.46					27.12		5.68			-1.597**		0.112
	Test value	2.358***						1.305***
	p	0.098						0.274
	\({F}_{grup}\)= 1.652, 0.200 \({F}_{zaman}\)= 3.542, 0.030* \({F}_{grup*zaman}\)= 0.188, 0.829
		Intervention						Control					Test value				p
		\(\stackrel{-}{\varvec{X}}\)			SS			\(\stackrel{-}{\varvec{X}}\)			SS
Affinity sub-dimension	Pre-test (1)	17.71			6.03			17.68			5.23		0.040**				0.968
	Follow up (2)	20.22			3.41			17.32			5.60		4.167**				0.000*
	Pos-test (3)	21.83			2.82			15.94			4.56		10.336**				0.000*
	Test value	25.600***						5.195***
	p	0.000*						0.006*
	Effect size η²	0.225						0.056
	Boferroni	3 > 1, 3 > 2, 2 > 1						1 > 3, 2 > 3
	\({F}_{group}\)= 5.182, 0.006* \({F}_{time}\)= 25.925, 0.000* \({F}_{grouptime}\)= 30.016, 0.000
		Intervention						Control					Test value	p
		\(\stackrel{-}{\varvec{X}}\)				SS		\(\stackrel{-}{\varvec{X}}\)		SS
Benefit sub-dimension	Pre-test (1)	17.38				5.67		17.53		5.17			-0.193**	0.847
	Follow up (2)	20.61				3.16		16.84		5.58			5.552**	0.000*
	Pos-test (3)	21.86				2.10		15.67		4.39			11.973**	0.000*
	Test value	37.616***						5.624***
	p	0.000*						0.004*
	Effect size η²	0.299						0.060
	Boferroni	3 > 1, 3 > 2, 2 > 1						1 > 3, 2 > 3
	\({F}_{group}\)= 40.460, 0.000* \({F}_{time}\)= 7.387, 0.001* \({F}_{grouptime}\)= 34.192, 0.000
		Intervention						Control					Test value					p
		\(\stackrel{-}{\varvec{X}}\)		SS				\(\stackrel{-}{\varvec{X}}\)	SS
Socialization sub-dimension	Pre-test (1)	13.69		4.88				14.58	4.62				-1.245**					0.215
	Follow up (2)	15.76		2.23				13.37	4.72				4.315**					0.000*
	Pos-test (3)	16.77		1.86				12.03	3.29				11.810**					0.000*
	Test value	21.593***						12.549***
	p	0.000*						0.000*
	Effect size η²	0.197						0.125
	Boferroni	3 > 1, 3 > 2, 2 > 1						1 > 3, 2 > 3
	\({F}_{group}\)= 26.563, 0.000* \({F}_{time}\)= 0.762, 0.468 \({F}_{grouptime}\)= 32.799, 0.000
		Intervention						Control					Test value			p
		\(\stackrel{-}{\varvec{X}}\)				SS		\(\stackrel{-}{\varvec{X}}\)			SS
Self-Trust sub-dimension	Pre-test (1)	14.83				4.05		14.62			3.94		0.337**			0.736
	Follow up (2)	16.06				2.81		13.56			4.26		4.622**			0.000*
	Pos-test (3)	15.51				2.94		13.41			3.20		4.556**			0.000*
	Test value	3.684***						3.947***
	p	0.027*						0.021*
	Effect size η²	0.040						0.043
	Boferroni	2 > 1						1 > 3
	\({F}_{group}\)= 17.693, 0.000* \({F}_{time}\)= 0.614, 0.542 \({F}_{grouptime}\)= 7.025, 0.001
		Intervention						Control					Test value					p
		\(\stackrel{-}{\varvec{X}}\)					SS	\(\stackrel{-}{\varvec{X}}\)				SS
Physical activity attitude scale scores	Pre-test (1)	91.24					18.66	92.64				15.97	-0.535**					0.593
	Follow up (2)	99.12					11.29	88.25				21.91	4.157**					0.000*
	Pos-test (3)	101.88					8.41	84.19				16.08	9.197**					0.000*
	Test value	18.893***						9.427***
	p	0.000*						0.000*
	Effect size η²	0.177						0.097
	Boferroni	3 > 1, 3 > 2, 2 > 1						1 > 3, 2 > 3
	\({F}_{group}\)= 23.889, 0.000* \({F}_{time}\)= 0.889, 0.412 \({F}_{grouptime}\)= 26.673, 0.000
p < 0.05, * Independent samples t-test, ***Analysis of variance in repeated measures

Table 5 is here.

Figure 4 is here.

A major factor contributing to the spread of obesity in children and young people has been the decrease in physical activity among them in recent years [28, 29]. In recent years, the decrease in physical activity among children and the increase in screen-viewing behavior has resulted in a decline in motor development, physical fitness, cognitive and attention parameters, and mental health parameters, as well as an increase in body weight [30–32]. In the present study, it was determined that 11.2% (n = 10) of the students in the intervention group and 10.1% (n = 9) of the students in the control group were overweight in the pre-test measurements. According to the measurements taken after physical activity, there was no significant difference between the pre-test, interim follow-up, and post-test BMI averages of the intervention and control groups. A review of the literature revealed that Centeio et al. (2018) conducted an extensive study of 628 overweight and obese fifth-grade students. Compared to the control group, students in the treatment group significantly reduced their BMI and waist-height ratio as a result of a comprehensive health program provided for eight months to prevent obesity [28]. Lee et al., in a study examining the effects of a school-based physical activity program on health-related physical fitness in Korean adolescents, applied a program including badminton and table tennis for 35 minutes each day, three days a week, for 15 weeks to the students. Based on measurements taken after the program, it was determined that students' physical activity development systems, such as muscle strength, power, cardiorespiratory fitness, and flexibility, had significantly improved as compared to before, but their BMI values had not significantly changed [30].

Since children spend a considerable amount of time at school, school-based programs should be prioritized for promoting beneficial health behaviors and habits. Current research has proven that school-based physical activity programs have effective results on physical activity levels, academic achievement, and obesity [33–35]. In the present study, it was determined that there was a significant difference between the physical activity survey mean scores of the intervention and control groups according to group, time, and group*time, and that the interim follow-up and post-test scores of the intervention group were significantly higher than the pre-test. It is seen that exercise programs, in-class training, and brochures carried out throughout a teaching period increase children's physical activity levels in and out of school. When the studies evaluating the effects of school-based programs on physical activity were examined, Yeşilfidan and Adana (2017) provided four sessions of health behavior development training to 78 children at risk of obesity. It was found that the total scores of the children's first and second follow-up health awareness, physical activity, and nutrition were significantly higher than their pre-education scores [33]. In the study by Santina et al. (2021), in which a school-based physical activity program was implemented, it was observed that there was a significant difference between the physical activity levels of the students in the intervention group and the control group [35]. In their research, Meydanlıoğlu and Ergün (2019) examined the effect of a diet and physical activity program for health, which was implemented for a total of 12 hours for six weeks under the leadership of a nurse, on the nutrition and physical activity behaviors of primary school students. As a result of the research, it was determined that the in-school and out-of-school physical activity scores of the students in the intervention group increased over time, and the post-test and follow-up scores were significantly higher in the control group [36].

The modern lifestyle, excessive use of technology, and the intensive school curriculum have led to an increase in children's sitting time which has resulted in a decrease in physical activity. Lack of motivation, poor infrastructure, gender, being in adolescence and bad weather conditions are also factors that contribute to a sedentary lifestyle. It has been shown that peer influence and parental and teacher support are directly effective in the development of healthy behaviors in children. It has been reported that the creation of fun programs and the participation of school staff make a significant contribution to increasing physical activity in children [35]. In the present study, it was determined that there was a significant difference between the physical activity self-efficacy scale scores of the intervention and control groups according to group, time, and group*time, and that the interim follow-up and post-test scores of the intervention group were significantly higher than the pre-test. Robbins et al. (2021) found that the planned physical activity program they applied to students in the 5th-7th grades resulted in significantly higher averages of motivation and self-efficacy scores among students who participated in the program, compared to students who did not participate, and that students who participated in the physical activity program spent less time on screens on weekends (watching television, movies, etc.) [29]. A study conducted by Cataldi et al. (2021) examined the effects of eight-week CrossFit training on the psycho-physical health of students during the COVID-19 pandemic. As a result of the exercises, it was determined that the students in the intervention group had significant improvements in their emotional perceived self-sufficiency as well as physical fitness tests, and CrossFit training was suggested to be a good school exercise activity [31]. In another study, it was stated that interventions aimed at children aged 8–12 years with high BMI improve activity levels by increasing self-efficacy for physical activity [37]. Self-efficacy is the belief in motivating one's behavior in order to achieve the desired health outcomes. Behaviors related to physical activity are a component of social learning and motivation theories since they include certain psychological factors at the individual level, such as self-efficacy, knowledge, and attitudes toward physical activity. When self-efficacy is considered a measure of a child's ability to achieve a certain level of performance, it can be stated that it is the most powerful factor in improving children's physical activity levels [38]. The planning of the physical activity program developed according to the Precede-proceed model in accordance with the preparatory (education aimed at increasing health belief), empowering (parent, peer, teacher, and guide influence), and enabling (exercise, play, and yoga created on the basis of entertainment) factors to increase children's self-efficacy explains the significant increase in the physical activity self-efficacy of the initiative group.

We once again see how important the attitudes acquired during childhood are in promoting our holistic health, now that we can appreciate the positive contribution of healthy physical activity habits acquired during childhood and adolescence. Schools are important institutions for promoting physical activity and healthy lifestyles, as they provide easy access to children, do not impose additional costs on parents, and provide a controlled and reliable environment [39]. In-school factors such as physical education lessons, teacher and peer influence, as well as parents and siblings outside school, directly affect children's development of healthy behavioral attitudes [39, 40]. In addition to a good education, the school gives children the chance to acquire healthy lifestyle behaviors from a young age. In the present study, it was found that there was a significant difference between the APAS scores of the intervention and control groups according to group and group*time. It is noticed that the interim follow-up and post-test APAS scores of the intervention group are higher than the control group. When the sub-dimensions were examined, it was determined that the interim follow-up and post-test scores of the intervention group were significantly higher than the control group in the sub-dimensions of affinity, benefit, socialization, and self-trust. When studies evaluating the effects of school-based programs on students' physical activity attitudes and behaviors are examined, in Mok et al. 's (2020) two-group quasi-experimental study, conducted by including 3036 children aged 8–11 in eight countries, Brain Breaks® physical activity solutions (group activity with exercise video) were evaluated on students' physical activity attitudes. It was determined that Brain Breaks®, which lasted for four months and included classroom-based exercise videos, created significant changes in the physical activity attitude sub-dimensions (benefit, importance, learning, self-efficacy, fun, suitability) of the students in the intervention group [41]. In a similar study, the effect of a video exercise initiative applied to elementary school students for 5–9 minutes every school day for three months on students' physical activity attitudes and self-efficacy behaviors was examined. The study concluded that the intervention program implemented through video exercise during breaks in primary school was effective not only for increasing physical activity but also for the development of physical activity attitudes (motivation for exercise, exercise knowledge, physical self-confidence) and self-efficacy behaviors [40]. The child's social environment has a direct impact on physical activity attitudes. A moderate correlation was determined in a study examining the relationship between parent-child physical activity levels. Based on accelerometry measurements made during the day, evening, and weekend, it has been shown that children's physical activity levels correlate significantly with their parents' [42]. In the present study, it is considered that the inclusion of parents, peers, and teachers in the physical activity program in line with the precede-proceed model has a significant impact on changing children's physical activity attitudes.

Limitations

Because of the semester holiday, the 12-week intervention program was completed in 14 weeks in this study. Due to the absence of students, some interim follow-up and post-test data were collected on different days during the same week. This study has several strengths, including the fact that it used a theory-based program, had a long-term implementation, and used a substantial sample size.

According to this study, the physical activity program developed according to the Precede-Proceed Model increased children's physical activity levels as well as their self-efficacy and attitudes toward physical activity. It was concluded that school health nurses' direct access to adolescents, parents, educators, and students will serve as a guide in establishing a healthy school climate and teaching healthy life habits.

It is recommended that families and educators participate in physical activity programs to be implemented in schools to become role models for children, to have a school nurse in educational institutions, to plan training and practices that improve children's health, and to comprehend the importance of physical activity for health.

Acknowledgments

We would like to express our sincere gratitude and respect to the Ministry of National Education for permitting the research to be conducted, to the valuable school administration and teachers who supported the research process, and to the valuable students and their parents who voluntarily participated in the research and took part in the activities with great enthusiasm.

Ethics approval and Consent to Participate

In order to conduct the research, ethical approval was obtained from the Muğla Sıtkı Koçman University Medical Research Ethics Committee (date: 24.06.2021 and decision no: 21-6.1T/37). For the implementation of the research, preliminary permission was obtained from Fethiye Gazi Primary School and Central Atatürk Primary School, and permission was obtained from Muğla Provincial Directorate of National Education by applying to the Ministry of National Education Research, Competition and Social Activity. Verbal consent was obtained from children who agreed to participate in the study, and written consent was obtained from their parents. Informed consent was obtained from all children their legal guardian. All procedures involving human participants adhered to the ethical standards set by the institutional and/or national research committee and complied with the 1964 Helsinki Declaration, as well as its later amendments or comparable ethical standards.

Availability of Data and Materials

Upon completion of the study, the datasets used and/or analysed during the current study are available from the corresponding author on reasonable request and with a data sharing agreement.

Consent for Publication

Not Applicable

Funding

No funding was received to assist with the preparation of this manuscript.

Competing Interests

The authors have no financial or competing interests relevant to this study to declare.

Authors’ Contributions

RK, ZB, design of the work; RK, ZB, the acquisition, RK analysis, RK, ZB interpretation of data; RK the creation of new software used in the work.

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No competing interests reported.

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The Effect of the Physical Activity Program Developed According to the Precede-Proceed Model on the Physical Activity Level and Physical Activity Behavior of Elementary School Students

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Abstract

Figures

Background

Methods

Design and sample

Data collection instruments

Child Information Form

The Physical Activity Questionnaire for Older Children (PAQ-C)

Physical Activity Self-Efficacy Scale (PASS)

Attitude toward Physical Activity Scale (APAS)

Intervention

Data analysis

Procedure

Results

Body Mass Index

Physical Activity Level

Physical Activity Self-Efficacy

Attitude Towards Physical Activity

Discussion

Limitations

Conclusions

Declarations

References

Additional Declarations

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