Next Article in Journal
Do Different Patterns of Employment Quality Contribute to Gender Health Inequities in the U.S.? A Cross-Sectional Mediation Analysis
Next Article in Special Issue
Physical and Recreational Activities, Sedentary Screen Time, Time Spent with Parents and Drug Use in Adolescents
Previous Article in Journal
Possibilities of Implementing Hospital-Based Health Technology Assessment (HB-HTA) at the Level of Voivodeship Offices in Poland
Previous Article in Special Issue
Intention for Warm-Up among Children and Adolescents Scale: Development and Initial Validation
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJERPH
Volume 19
Issue 18
10.3390/ijerph191811236
ijerph-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Effect of a Three-Month HOPSports Brain Breaks® Intervention Program on the Physical Fitness Levels of Grade 6-Learners in South Africa

by
Jacqueline Bonnema
1,
Dané Coetzee
1,* and
Anita Lennox
2
1
Physical Activity, Sport and Recreation, (PhASRec) Focus Area, Faculty of Health Science, North-West University, Potchefstroom Campus, Private Bag X 6001, Potchefstroom 2531, South Africa
2
School of Management Sciences, North-West University (Vaal Triangle Campus), Vanderbijlpark 1900, South Africa
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2022, 19(18), 11236; https://doi.org/10.3390/ijerph191811236
Submission received: 29 June 2022 / Revised: 2 September 2022 / Accepted: 4 September 2022 / Published: 7 September 2022
(This article belongs to the Special Issue Physical Activity and Health Status in All Stages of Life)
Browse Figures
Review Reports Versions Notes

Abstract

:
Despite the numerous health benefits of being physically active, children are not active enough. Various researchers have indicated that intervention programs improve physical fitness levels. Still, only a few have focused on improving physical fitness levels by incorporating technology. HOPSports Brain Breaks® are designed and presented as physical activity solutions with online videos requiring the participants to imitate the movements. These videos are 2–5-min classroom activity breaks. This study determined the effect of a three-month HOPSports Brain Breaks® intervention program on the physical fitness levels of Grade 6-learners. Physical fitness was measured with the EUROFIT test battery. The experimental group consisted of 79 children (26 boys and 47 girls) and the control group of 47 children (16 boys and 33 girls). The mean age for the entire group was 11.92 (±0.36) years. The results indicated that there was a statistically (p ≤ 0.05) and practically (d ≥ 0.20) significant difference between the experimental and control group for percentage body fat; stork balance; plate tapping; sit-and-reach; standing jump; sit-ups; and 10 × 5 m shuttle run and 20 m shuttle run between the pre-and post-test. Therefore, considering the results mentioned above, the HOPSports Brain Breaks® intervention program can indeed contribute to the improvement of physical fitness, and motor skills of children. Therefore, future studies should be conducted to determine the effect of HOPSports Brain Breaks® between genders as well as what impact it will have on academic performance.

1. Introduction

Notwithstanding the numerous health benefits of physical activity (PA) and the role it plays in a child’s life [1,2,3], it is still evident that South African children are not adequately active [1]. Accordingly, the American College of Sports Medicine [4] states that movement skills, aerobic fitness, muscular strength, body composition, cholesterol, blood pressure, blood sugar, and bone health benefit from PA.
Furthermore, research has indicated that PA and physical fitness are beneficial for self-esteem, mood, and character building, positively affecting anxiety [1,5,6]. Various research studies have been conducted which indicate that children’s PA levels increase but reach a peak at the age of 12 years, after which they start to decline [2,7,8]. Recent research concurs and indicates that the prevalence and the decline in PA and physical fitness levels are prevalent and continue until early adulthood. Moreover, it is recommended by researchers that the PA and physical fitness levels of adolescents should be approached differently. Despite the potential success of multi-factor intervention programs, alternative interventions such as digital interventions are needed to address this problem [9].
Research has indicated a positive relationship between physical inactivity and obesity in this sense, negatively impacting children’s physical skills [10,11,12]. In accordance, De Milander [13] studied the relationship between PA, motor proficiency, and physical fitness in 12- to 13-year-old children and reported that lower motor and physical fitness skills result from declining PA levels. Another study by Krombholz [14] indicates that overweight and obese children are, to a lesser extent, physically active and have inferior motor skills. Van Biljon and Longhurst [15] concur and state that decreased physical fitness in obese children could be ascribable to the fact that children do not have the motor skills to perform the activities. In addition, Crane, Naylor, Cook, and Temple [16] stated that as children get older, they are more likely to opt out of PA participation when they do not have the skills to execute the activities. However, children’s confidence and perception of their motor skills could also influence their PA participation, which could improve their physical fitness levels in return [17]. Other factors include lack of resources and facilities, waiting their turn, listening to instructions, and insufficient time in the school curriculum also influence PA and physical fitness [18,19,20,21,22].
The World Health Organization (WHO) [23] defines PA as the ability of the musculoskeletal system to execute a movement, which contributes to energy expenditure. In this sense, having the ability to perform daily PA tasks and leisure-time activities without fatigue summarizes the definition of physical fitness [5,24]. Moreover, physical fitness is categorized into health-related fitness, which is essential to be physically active and preclude chronic diseases [25,26], and sport-related fitness, which includes skills that contribute to the improvement of athletic and sports performance [4,26,27]. Health-related fitness comprises body composition, flexibility, muscular strength and endurance, and cardiovascular endurance components. In contrast, sport-related fitness entails speed, agility, balance, power, reaction time, and coordination [28]. Several researchers have studied the effect of intervention programs on health-related fitness and indicated that intervention programs could improve physical fitness.
Ample research has been done abroad and in South Africa to determine the impact of school-based intervention programs on children’s PA and physical fitness [29,30,31,32,33,34,35,36,37,38]. Moreover, Dallolio et al. [29] studied the impact of a physical education (PE) intervention program and indicated that only the boys’ physical fitness skills improved and recommended that the program should be adapted to meet all the participants’ abilities [29]. In accordance, Šarkauskienė, Derkintienė, and Paplauskas [38] investigated the impact of non-formal PE (e.g., dance, sports, etc.) and found that boys’ cardiovascular fitness, upper body and abdominal strength and endurance, and explosive leg power improved profoundly. In contrast, the girls only indicated improvement in abdominal strength and endurance. Further, Lubans et al. [24] research indicated that older adolescents’ cardiorespiratory and muscular fitness levels improved significantly after a six-month intervention program. The Burn 2 Learn (B2L) program consisted of high-intensity interval training, which teachers implemented during the school’s curriculum. The learners had to complete the activities during their activity breaks, consisting of 20-min multistage fitness tests. Despite this intervention program, the study indicated that the students’ activity and fitness levels decreased when the teachers no longer presented the program [24]. Another study, the ‘Internet-based Professional Learning to help teachers support Activity in Youth’ (iPLAY) program, implemented by Lonsdale et al. [22], reported that physical activity levels, proficiency in movement skills, enjoyment of the sport, and cognitive control improved in the learners. Additionally, Lonsdale et al. [39] also examined the effect of an Internet-based intervention program on improving cardiorespiratory fitness. This study consisted of 22 schools that completed the clinical trial. The program’s content included physical education, sufficient physical activity breaks, and homework the learners needed to complete while physically active. A significant improvement in cardiorespiratory fitness was documented after the 12-month trial. In addition, the study’s results also indicated longevity, as the 24-month assessment showed a sustained improvement in cardiorespiratory fitness. For this reason, programs such as these can be successfully implemented at a population level [39].
Eather [31] investigated the effect of a “fit-for-fun” physical fitness intervention program and found that health-related fitness skills improved, particularly muscular fitness and flexibility. Conversely, Sacchetti et al. [35] studied the efficacy of a school-based intervention program to improve physical skills and performance. It was indicated that the motor performance improved in both groups, whereas the experimental group’s improvements were more significant. Moreover, since children spend most of their time with technology, researchers have recently investigated technology-based intervention programs on physical fitness and PA [11,15,40,41,42,43,44].
Gao [40] investigated the effect of a nine-month Dance Dance Revolution (DDR®) program. The results indicated that the experimental group’s daily PA levels increased compared to the control group, whose PA levels declined. In accordance, Tumynaitė et al. [11] studied a three-month HOPSports Brain Breaks® intervention program and its impact on physical fitness and sedentary behavior. It was found that physical fitness did not improve because of the program’s short duration, whereas overall sedentary behavior decreased.
A study on an exergaming intervention program was commenced on 30 overweight and obese children and indicated that physical fitness improved in the experimental group; however, speed, agility, and balance did not improve [15]. Notwithstanding, the HOPSports Brain Breaks® program could contribute to precluding lower PA levels and physical skills and improve physical fitness levels.
In this sense, the literature indicates that more research is necessary to study the effect of HOPSports Brain Breaks® on Grade 6 learners’ physical fitness. This online intervention program can be conducted during class, break, and before and after school to improve PA levels, physical fitness levels, active learning, and test grades [41]. Additionally, this technology-based intervention program incorporates physical, mental, and health videos to increase physical fitness levels and accomplish new motor skills [42].

Purpose of Research

Literature indicates that the effect of PA and fitness has been studied in detail; however, limited research has been done regarding the impact of technology-based intervention programs such as HOPSports Brain Breaks® on learners’ physical fitness levels. No research could be found on the South African population in this regard. Keeping this in mind, this research aims to study the effect of a three-month HOPSports Brain Breaks® intervention program on the physical fitness levels of Grade 6 learners.

2. Materials and Methods

A non-randomized intervention study design was employed for this study with a pre-and post-test. This study was comprised of a convenience sample. This design was chosen to answer the research question: will a HOPSports Brain Breaks® intervention program affect the physical fitness levels of Grade 6 learners in an experimental and control group?

2.1. Participants

The focus of this study was to determine the effect of a HOPSports Brain Breaks® intervention program on 114 Grade 6 learners (boys n = 56; girls n = 58), aged 11- to 12-years. After we obtained a list of all the schools in the Tlokwe Municipality district from the Department of Basic Education, three schools from similar socio-economic backgrounds were randomly selected using the stratified random sampling method. One school functioned as the experimental group (26 boys and 47 girls), and the other two schools served as the control group (16 boys and 33 girls). Please see Figure 1 for more information.

2.2. The European Test of Physical Fitness (EUROFIT)

The EUROFIT test was used to determine the physical fitness of the participants. This test is designed for children aged 6- to 18-year-olds and evaluates various fitness components. These components include cardiovascular endurance; running speed and agility; the speed of limb movement; balance; flexibility; explosive leg strength; and abdominal strength, and these were evaluated with the following tests [43]:
20 m (m) shuttle run test: This test assessed cardiovascular endurance and expected the participant to run back and forth between two marks for as long as possible. The test ended when the participant could not finish the lap at a specific time. The number of laps completed was recorded.
10 × 5 m shuttle test: Running speed and agility were evaluated with this test, where the participant had to start behind a line and run 5 m as fast as possible. The participant had to repeat this 10 times; the fastest time was recorded.
Plate tapping test: The plate tapping test evaluated the speed of limb movement. It was expected from the participant to tap two plates with the preferred hand as fast as possible until s/he had performed 25 cycles. The fastest time was recorded.
Stork balance test: The participant’s balance was evaluated with the stork balance test. S/he was expected to stand on one leg for one minute while the non-supporting foot was placed against the medial side of the supporting leg’s knee. The participant’s total time was recorded.
Sit-and-reach test: The sit-and-reach tested hamstring flexibility and required the participant to sit down with bare feet against a sit-and-reach box and keep the knee fully extended. The participant was then asked to reach as far as possible forward. The better of two attempts were recorded to the nearest half centimeter (cm).
Standing long jump test: This test assessed the participant’s explosive leg strength. The participant had to stand behind a line and jump as far as possible with both feet. The most prolonged attempt was recorded.
Sit-up test: The sit-up test was used to determine abdominal strength. The participant had to lie down on their back, knees bent at 90° with the feet flat, and execute as many sit-ups as s/he could in 30 s.
After the completion of each test, the total score was processed into a category, using the EUROFIT reference scales for each skill. Each learner was then allocated into one of the following categories for each skill: (1) Below Average, (2) Average, (3) Above Average, and (4) High Score.

2.3. Anthropometry

The measurements were taken by a qualified Level 2 ISAK-accredited anthropometrist according to the standard protocol proposed by ISAK. The following measures were taken of the participants: body mass (kg), stature (m), and skinfolds (triceps, subscapular, and calf). The participants were weighed and measured in light clothing and without shoes, using calibrated scales and a stadiometer. The BMI was calculated as weight (kg)/height (m2), and the percentage of body fat was measured by calculating the skinfold measurement using the equation of Slaughter et al. [44].

2.4. Intervention

During the intervention program, the control and experimental groups continued participating in the school’s physical education lessons. The control group and experimental group were based in different schools. Both groups were assessed before and after the intervention with the EUROFIT test to determine their physical fitness levels. In addition to the physical education lessons, the experimental group participated in the HOPSports Brain Breaks® intervention program daily for three months (which added up to 12 weeks in total). The researchers and the teachers worked closely to select from the list of various two- to five-minute videos, which included arts (dance and music); fitness skills (cardio and functional fitness); sports (skillastics, cycling, rowing); education (health issues, nutrition, and hygiene); and classroom activities (fun fitness, dynamic physical education) [18]. Each video contains a real or animated instructor to demonstrate the different exercises that would improve children’s motor and physical skills [11,45,46]. The teacher was trained regarding the choice of videos and presentation of the program.
The teachers offered the HOPSports Brain Breaks® intervention program according to the prescribed guidelines for PE as stated in the national curriculum and assessment policy (CAPS) document [47]. Additionally, the program focused on strength, speed, hand-eye and foot-eye coordination, agility, and spatial awareness, among others [18]. For this intervention program, the experimental school had access to the Internet to view the physical activity videos in their classrooms. The participants had to imitate the activities demonstrated in the online video programs, contributing to improved physical fitness and reduced inactivity. It was also expected from the participants to complete the whole video while being physically active. The video intervention program was presented daily in the classroom during school time. There were more than 250 videos in the online video program from which the teachers could choose. The content of the videos includes knowledge about health and training, nutrition, social skills education, environmental education, dance, and fitness [11,18]. Login details and a password were given to the experimental school to gain access to the online video program to present the intervention.

2.5. Research Procedure

Consent was obtained through a formal meeting with the corresponding school principals, where the aim and protocol of the study were explained. Informed consent was obtained via letters explaining the aim and protocol of this study to all the Grade 6 learners’ parents and the Grade 6 learners. Participation was entirely voluntary, and they could withdraw from the study anytime. Learners whose parents had given consent were tested to determine their physical fitness, and after that, they followed a HOPSports Brain Breaks® intervention program. The intervention program was done during school time in their classrooms for 12 weeks. The post-test was conducted one week after the intervention program was concluded.
Ethical approval was obtained for this study from the Health Research Ethics Committee of the Faculty of Health Sciences of North-West University (NWU-00003-14-A1). Permission was also obtained from the affiliated schools and the North-West Department of Education. Informed consent was obtained from the parents/legal guardians of the Grade 6 learners before participating in the study. A discussion was held to discuss the purpose of this study and what was expected from each participant whose parent(s) gave consent to participate.

2.6. Statistical Analysis

Data processing was done by using SPSS 28.0 (BMI, New York, NY, USA). For descriptive purposes, the data were analyzed by means of arithmetic means (M), standard deviation (SD), and minimum and maximum values. To determine the effect of the HOPSports Brain Breaks® intervention program within and between the experimental and control groups, use was made of independent-sample t-test, paired-sample t-tests, and ANOVA (repeated measures over-time analysis of variance), as well as a Bonferroni correction for multiple comparisons. The critical level of statistical significance was set at p ≤ 0.05, and to determine the practical significance the guidelines of Cohen [48] were used, namely: d = 0.2 (small effect), d = 0.5 (medium effect) and d = 0.8 (large effect).

3. Results

Table 1 indicates the composition of the sample population of this study. The experimental group involved 73 participants (26 boys, 47 girls), with a mean age of 11.85 (±0.38), and the control group involved 49 participants (16 boys, 33 girls), with a mean age of 12.02 (±0.31). The entire group of participants was 122, where 42 were boys and 80 were girls. The mean age for the group was 11.92 years (SD = 0.36).
To determine the significance of EUROFIT differences between the groups’ pre-and post-tests, an independent sample t-test was conducted. Table 2 reports the differences between the groups regarding the different anthropometry and physical fitness measurements during the pre-and post-test. Regarding the anthropometry measurements in the pre-test, the experimental group was statistically (p ≤ 0.05) younger and shorter than the control group compared to the post-test, where height only indicated a practical significance. During the physical fitness tests in the pre-test, the experimental group performed statistically (p ≤ 0.05) and practically (d ≥ 0.5) lower than the control group regarding the standing long jump (M = 137.29 vs. M = 148.71), sit-ups (M = 15.36 vs. M = 20.59), and the 20 m shuttle run (M = 19.22 vs. M = 25.53), but better during the sit-and-reach test (M = 27.92 vs. M = 22.79). To rectify the differences between the experimental and the control group during the pre-test, a post hoc adjustment was made using the Bonferroni method. Table 2 indicates that after the experimental group participated in the intervention program, the experimental group performed statistically (p ≤ 0.05) and practically (d ≥ 0.5) better than the control group during the stork balance (p ≤ 0.001, d ≥ 1.30), plate tapping (p ≤ 0.001, d ≥ 1.63), sit-and-reach (p ≤ 0.05, d ≥ 0.73), and 10 × 5 m shuttle run (p ≤ 0.05, d ≥ 1.13).
To evaluate if any differences occurred within the groups during the pre-and post-tests, paired sample t-test was used (see Table 3). Table 3 indicates that during the anthropometric measurements for the experimental group, statistically (p ≤ 0.05) and practically (d ≥ 0.2) significant differences were observed for the increase in height and body fat percentage, where the experimental group had a higher body fat percentage than the control group. The same tendencies were found for all the physical fitness measurements where the experimental group performed statistically (p ≤ 0.05) and practically (d ≥ 0.2) better during the post-test after the intervention was received. Regarding the control group, statistically and practically significant differences were also reported regarding the increase in height, weight, BMI, and body fat percentage. However, the control group declined statistically and practically significantly in the post-test during four physical fitness tests (stork balance, plate tapping, standing jump, 10 × 5 m shuttle run, and 20 m shuttle run), but an increase in the number of sit-ups were seen. However, this improvement was not statistically significant, but a practical significance was reported (d = 0.5).
A repeated-measures-over-time analysis (ANOVA) was performed (see Table 4) and confirmed the results in Table 2 and Table 3, with a significant group effect regarding the interaction of the two groups over time in all the anthropometric (Table 4; Figure 2a–d) and physical fitness measures (Table 4; Figure 3a–g).
From Table 4 and Figure 2a–d, there were no significant differences between the experimental and control group regarding height (f = 1.70; p = 0.195), weight ((f = 20.61; p = 0.232), and BMI (f = 1.8; p = 0.176), but the body fat percentage (f = 7.64; p = 0.007) increase significantly more in the experimental group. From Table 4 and Figure 3a–g, it appears that the experimental group reacted significant difference over time if compared to the control group. The intervention effect is visible in Figure 3a–g with regard to differences between the groups in all aspects of the physical fitness skills during the post-test, where the experimental group significantly outperformed the control group (stork balance (f = 88.98; p = ≤0.001); plate tapping (f = 83.97; p = ≤0.001); standing long jump (f = 32.19; p = ≤0.001); sit-ups (f = 18.73; p = ≤0.001); 10 × 5 m shuttle run (f = 60.22; p = ≤0.001); 20 m shuttle run (f = 381.40; p = ≤0.001).

4. Discussion

The aim of this study was to determine whether a three-month HOPSports Brain Breaks® intervention program could increase the physical fitness and PA levels of Grade 6-learners.
The experimental group who participated in the HOPSports Brain Break® videos during class and participated in regular PE lessons increased their physical fitness compared to the control group who only participated in regular PE lessons. After the two groups were compared, the results indicated statistically and practically significant differences in the pre- and post-test results. The experimental group reported lower scores for standing jump (leg strength), sit-ups (abdominal strength), and 20 m shuttle run test (cardiovascular endurance) when compared to the control group during the pre-test; however, the experimental group’s sit-and-reach (flexibility) test indicated higher scores than the control group. Accordingly, the results from the post-test indicated that the experimental group performed better in the stork balance (balance), plate tapping (speed), sit-and-reach (flexibility), 10 × 5 m shuttle run (speed and agility), as well as 20 m shuttle run tests (cardiovascular endurance) in comparison to the control group. These results are similar to a study conducted by Tian et al. [33] on 110 children 12- to 13-years old who participated in an enhanced quality PE program. However, these researchers did not make use of the technology-based intervention. The experimental group reported significant differences for sit-and-reach, standing jump, sit-ups, 20 m shuttle run, plate tapping, and 10 × 5 m shuttle run.
Subsequently, the results of our study within each group’s pre- and post-test noted the following differences. The experimental group reported practically and statistically significant improved differences between the pre- and post-test in all the physical fitness components: cardiovascular endurance, abdominal strength, explosive leg power, flexibility, balance, speed, and agility. Various research studies have been done to study the effect of intervention programs on physical fitness; however, only some of the physical fitness components results correlate with the results of this study. In this regard, a study on 113 Grade 1 to Grade 4 learners by Tumynaitė et al. [11] was done where it was expected from the experimental group participated in a three-month HOPSports Brain Breaks® intervention program. The results indicated that boys’ upper body and leg strength improved (p ≤ 0.05), whereas agility did not demonstrate any improvement. Furthermore, these results showed that overall physical fitness did not improve; however, PA levels did improve. In another study by Van Biljon and Longhurst [15] on 30 children aged 9- to 12-year-olds, the results indicated that the experimental group who participated in a six-week exergaming intervention program improved their speed, agility, and balance in contrast to the control group who indicated regression in these components. More recent research by Šarkauskienė et al. [38] studied the effect of non-formal PE on 356 Grade 6 learners’ physical fitness. The results reported that boys who participated in the non-formal PE intervention improved their cardiovascular endurance, abdominal strength, and leg strength compared to the group who did not participate in non-formal PE; moreover, no differences in flexibility were indicated. The girls who participated in the non-formal PE only indicated a significant difference in abdominal strength compared to those who did not participate in non-formal PE.
In this study, the control group’s results indicated practical significance for stork balance and sit-ups which had improved after the post-test. In contrast, plate tapping, and 10 × 5 m shuttle run reported both statistical and practical significance lower scores compared to the pre-tests and experimental group’s scores. Standing jump also indicated statistical significance but with lower scores. A possible explanation for the improvement in abdominal strength (sit-up test) can be ascribed to the fact that both boys and girls improve their abdominal strength from the age of 10 years old. In contrast, children from the age of nine years indicated a drastic increase in their balance abilities [28]. In accordance with the results of other research, the control group of this study continued with regular PE classes and might have had limited time to be physically active during the PE period [18,20,21], which could prevent these learners from learning and mastering fundamental skills [15]. However, our control group improved their sit-and-reach scores in comparison to the control group of Stadler [49]. Lastly, it was noted that both groups’ BMI increased in the three months, this could be possibly ascribed to puberty and continues during adolescents [50].
HOPSports Brain Break® video program can enhance PE classes in terms of physical fitness increases [51]. One of the possible explanations for the increase in physical fitness in the experimental group could be that after watching and participating in the various HOPSports Brain Breaks® videos, the learners’ connected the importance and advantages of physical activity with their own PA, which led to an increase in their own PA. In accordance, Bulca et al. [51] concur with this finding that HOPSports Brain Breaks® contributed to the improvement in physical fitness seen in the experimental group and may have had a good impact on students’ overall PA levels.
Therefore, considering the above-mentioned results, the HOPSports Brain Breaks® intervention program can encourage improvements in PA levels and physical fitness for learners and support the PE teachers in teaching learners PA content in an enjoyable manner. Furthermore, overweight, inactive learners or learners with poor motor skills can benefit from this program since it is non-competitive and can be executed at home [51].
The study demonstrated some limitations and should be prevented and acknowledged in future research. However, the study reported valuable outcomes regarding the improvements of physical fitness skills in Grade 6 learners. The main focus of this study was the improvement of the physical fitness levels and not the improvement of physical activity levels. During this study, no gender differences were evaluated. In light of the findings of the study, possible recommendations for future research include determining the effect of this program on the different genders, the effect of a longer intervention period, and the effect of this program on academic performance and how it correlates with PA and fitness. Lastly, it is recommended to focus more on the improvement of PA levels by making use of direct measurements by means of actigraphs.

5. Conclusions

Although extensive research has been done to study the effect of various technology-based intervention programs, the findings of the studies vary with little to no improvements. The current study’s results reported that the HOPSports Brain Breaks® intervention program improved all the physical fitness components of the EUROFIT test battery, which could contribute to an increase in PA levels. Therefore, HOPSports Brain Breaks® is an effective program that teachers can incorporate in their PE periods or during class to address the concern of physical inactivity and improve physical fitness skills.

Author Contributions

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

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Health Research Ethics Committee (HREC) of the North-West University (NWU-00003-14-A1; 2014).

Informed Consent Statement

Written informed consent and assent were obtained from the participants to publish this paper.

Data Availability Statement

The dataset is the property of the North-West University under the supervision of Dané Coetzee. In this regard, D. Coetzee should be contacted if, for any reason, the data included in this paper need to be shared. D. Coetzee is the principal investigator of this study and gave permission that the data can be used.

Acknowledgments

The authors wish to express their sincere appreciation to the Department of Education of the North-West Province, the principals of the schools, and all the learners for the permission granted to enable the researchers to complete this study. Furthermore, we would like to thank M.M.C. Mok and M.K. Chin for allowing us to use the questionnaire and all the support during this study. Lastly, we would like to thank T. Root from HOPSports for allowing us to use their program.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Monyeki, M.A. Physical activity and health in children: How much do we know? Afr. J. Phys. Health Educ. Recreat. Danc. 2014, 20, 323–342. [Google Scholar]
  2. Malina, R.M. Movement proficiency in childhood: Implications for physical activity and youth sport. Kinesiol. Slov. 2012, 18, 19–34. [Google Scholar]
  3. Du Toit, D.; Pienaar, A.E.; Truter, L. Relationship between physical fitness and academic performance in South African children. S. Afr. J. Res. Sport Phys. Educ. Recreat. 2011, 33, 23–35. [Google Scholar]
  4. American College of Sport Medicine (ACSM). Complete Guide to Fitness and Health; Human Kinetics: Champaign, IL, USA, 2011. [Google Scholar]
  5. Ortega, F.B.; Riuz, J.R.; Castillo, M.J.; Sjöström, M. Physical fitness in childhood and adolescence: A powerful marker of health. Int. J. Obes. 2008, 32, 1–11. [Google Scholar] [CrossRef] [PubMed]
  6. Wood, C.; Angus, C.; Pretty, J.; Sandercock, G.; Barton, J. A randomised control trial of physical activity in a perceived environment on self-esteem and moon in UK adolescents. Int. J. Environ. Health Res. 2012, 23, 311–320. [Google Scholar] [CrossRef] [PubMed]
  7. Robbins, L.B.; Pfeiffer, K.A.; Wesolek, S.M.; Lo, Y.J. Process evaluation for a school- based physical activity intervention for 6th- and 7th-grade boys: Reach, dose, and fidelity. Eval. Program Plan. 2014, 42, 21–31. [Google Scholar] [CrossRef]
  8. Weinberg, R.S.; Gould, D. Exercise Behaviour and Adherence, 6th ed.; Human Kinetics: Champaign, IL, USA, 2014. [Google Scholar]
  9. van Sluijs, E.M.F.; Ekelund, U.; Crochemore-Silva, I.; Guthold, R.; Ha, A.; Lubans, D.; Oyeyemi, A.L.; Ding, D.; Katzmarzyk, P.T. Physical activity behaviours in adolescence: Current evidence and opportunities for intervention. Lancet 2021, 398, 429–442. [Google Scholar] [CrossRef]
  10. Tucker, J.S.; Martin, S.; Jackson, A.W.; Morrow, J.R.; Greenleaf, C.A.; Petrie, T.A. Relations between sedentary behaviour and FITNESSGRAM healthy fitness zone achievement and physical activity. J. Phys. Act. Health 2014, 11, 1006–1011. [Google Scholar] [CrossRef]
  11. Tumynaitė, L.; Miežienė, B.; Ching Mok, M.M.; Ming-kai, C.; Putriūtė, V.; Rupainienė, V.; Stankevičienė, G.; Emeljanovas, A. Effects of intervention “HOPSports Brain Breaks” program on physical fitness and sedentary behaviour in primary school. Balt. J. Sport Health Sci. 2014, 94, 57–66. [Google Scholar] [CrossRef]
  12. Truter, L.; Pienaar, A.E.; Du Toit, D. Relationships between overweight, obesity and physical fitness of nine- to twelve-year-old South African children. S. Afr. Fam. Pract. 2010, 52, 227–233. [Google Scholar] [CrossRef]
  13. De Milander, M. Motor proficiency and physical fitness in active and inactive girls aged 12 to 13 years. S. Afr. J. Res. Sport Phys. Educ. Recreat. 2011, 33, 11–22. [Google Scholar]
  14. Krombholz, H. Motor and cognitive performance of overweight preschool children. Percept. Mot. Ski. 2013, 116, 40–57. [Google Scholar] [CrossRef] [PubMed]
  15. Van Biljon, A.; Longhurst, G.K. The influence of exergaming on the functional fitness in overweight and obese children. AJPHERD 2012, 18, 984–991. [Google Scholar]
  16. Crane, J.R.; Naylor, P.J.; Cook, R.; Temple, V. Do perceptions of competence mediate the relationship between fundamental motor skill proficiency and physical activity levels of children in kindergarten? J. Phys. Act. Health 2015, 12, 954–961. [Google Scholar] [CrossRef]
  17. Humbert, M.L.; Chad, K.E.; Spink, K.S.; Muhajarine, N.; Anderson, K.D.; Bruner, M.W.; Girolami, T.M.; Odnokon, P.; Gryba, C.R. Factors That Influence Physical Activity Participation Among High- and Low-SES Youth. Qual. Health Res. 2006, 16, 467–483. [Google Scholar] [CrossRef]
  18. Brain Breaks. To Improve the Fitness of Students, We Need to Rethink the Design and Delivery of School-Based Physical Education Programs. Available online: https://brain-breaks.com/blogs/to-improve-the-fitness-of-students-we-need-to-rethink-the-design-and-delivery-of-school-based-physical-education-programs (accessed on 24 April 2021).
  19. Cozett, C. Factors Influencing Participation in Physical Activity in 11–13 Year-Old Primary School Children in the Western Cape. Master’s Thesis, University of Western Cape, Cape Town, South Africa, 2014. Available online: http://etd.uwc.ac.za/xmlui/handle/11394/4190 (accessed on 30 April 2021).
  20. Foo, T.J.; Krasilshchikov, B.S.; Shaw, B.S.; Shaw, I. Effect of concurrent physical education and obesity-prevention training programme on anthropometry and cardiorespiratory fitness in children. Afr. J. Phys. Health Educ. Recreat. Danc. 2014, 2, 74–81. [Google Scholar]
  21. Fogel, V.A.; Miltenberger, R.G.; Graves, R.; Koehler, S. The effects of exergaming on physical activity among inactive children in a physical education classroom. J. Appl. Behav. Anal. 2010, 43, 591–600. [Google Scholar] [CrossRef]
  22. Lonsdale, C.; Sanders, T.; Cohen, K.E.; Parker, P.; Noetel, M.; Hartwig, T.; Vasconcellos, D.; Kirwan, M.; Morgan, P.; Salmon, J.; et al. Scaling-up an efficacious school-based physical activity intervention: Study protocol for the ‘Internet-based Professional Learning to help teachers support Activity in Youth’(iPLAY) cluster randomized controlled trial and scale-up implementation evaluation. BMC Public Health 2016, 16, 873. [Google Scholar]
  23. World Health Organization (WHO). Physical Activity. Available online: http://www.who.int/dietphysicalactivity/pa/en/ (accessed on 5 June 2021).
  24. Lubans, D.R.; Smith, J.J.; Eather, N.; Leahy, A.A.; Morgan, P.J.; Lonsdale, C.; Plotnikoff, R.C.; Nilsson, M.; Kennedy, S.G.; Holliday, E.G.; et al. Time-efficient intervention to improve older adolescents’ cardiorespiratory fitness: Findings from the ‘Burn 2 Learn’cluster randomised controlled trial. Br. J. Sports Med. 2021, 55, 751–758. [Google Scholar] [CrossRef] [PubMed]
  25. American College of Sports Medicine (ACSM). Physical Activity in Children and Adolescents. Available online: http://www.acsm.org/docs/default-source/brochures/physical-activity-in-children-and-adolescents.pdf (accessed on 5 June 2021).
  26. Plowman, S.A.; Smith, D.L. Exercise Physiology for Health Fitness and Performance, 4th ed.; Lippincott Williams & Wilkins: Baltimore, MD, USA, 2014; Available online: https://books.google.co.za/books?hl=en&lr=&id=GkpPLE5uQuwC&oi=fnd&pg=PP2&dq=sport-related+physical+fitness+components&ots=rXwfC6M5x_&sig=Fk0g1DDxWqSKls4BTi--SC_hsT4#v=onepage&q=sport-related%20physical%20fitness%20components&f=false (accessed on 5 June 2021).
  27. Pienaar, A.E. Perceptual-Motor Learning: Theory and Practice; North-West University: Potchefstroom, South Africa, 2012. [Google Scholar]
  28. Gallahue, D.L.; Ozmun, J.C. Understanding Motor Development: Infants, Children, Adolescent, Adults, 6th ed.; McGraw-Hill: Singapore, 2006. [Google Scholar]
  29. Dallolio, L.; Ceciliani, A.; Sanna, T.; Garulli, A.; Leoni, E. Proposal for enhanced physical education program in the primary school: Evaluating of feasibility and effectiveness in improving physical skills and fitness. J. Phys. Act. Health 2016, 13, 1025–1035. [Google Scholar] [CrossRef]
  30. Uys, M.; Bassett, S.; Draper, C.E.; Micklesfield, L.; Monyeki, A.; De Villiers, A.; Lambert, E.V. Results from South Africa’s 2016 report card on physical activity for children and youth. J. Phys. Act. Health 2016, 13, S265–S273. [Google Scholar] [CrossRef]
  31. Eather, N. The Fit-4-Fun Study: Promoting Physical Activity and Physical Fitness in Primary School-Aged Children. Ph.D. Thesis, University of Newcastle, Newcastle, Australia, 2014. Available online: http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:15245 (accessed on 10 July 2021).
  32. Ling, J.; King, K.M.; Speck, B.J.; Kim, S.; Wu, D. Preliminary assessment of school-based healthy lifestyle intervention among rural elementary school children. J. Sch. Health 2014, 84, 247–255. [Google Scholar] [CrossRef]
  33. Tian, H.; du Toit, D.; Toriola, A.L. Effects of a 12-week physical education intervention programme on physical and motor fitness of grade 7 learners in Potchefstroom, South Africa. Mediterr. J. Soc. Sci 2014, 5, 1703–1711. [Google Scholar] [CrossRef]
  34. Walter, C.M. Promoting physical activity: A low cost intervention programme for disadvantage schools in Port Elizabeth, South Africa. AJPHERD 2014, 20, 357–371. [Google Scholar]
  35. Sacchetti, R.; Ceciliani, A.; Garulli, A.; Dallolio, L.; Beltrami, P.; Leoni, E. Effects of a 2-year school-based intervention enhanced physical education in the primary school. J. Sch. Health 2013, 83, 639–646. [Google Scholar] [CrossRef]
  36. Naidoo, R.; Coopoo, Y. The impact of a primary school physical activity intervention in KwaZulu-Natal, South Africa. AJPHERD 2012, 18, 75–85. [Google Scholar]
  37. Draper, C.E.; De Kock, L.; Grimsrud, A.T.; Rudolph, M.; Nemutandani, S.; Kolbe-Alexander, T.; Lambert, E.V. Evaluation of a school-based physical activity intervention in Alexandra Township. S. Afr. J. Sports Med. 2010, 22, 12–19. [Google Scholar] [CrossRef]
  38. Šarkauskienė, A.; Derkintienė, S.; Paplauskas, Š. Non-formal physical education of children: Increase factor of physical activity and physical fitness. Balt. J. Sport Health Sci. 2016, 3, 44–51. [Google Scholar] [CrossRef]
  39. Lonsdale, C.; Sanders, T.; Parker, P.; Noetel, M.; Hartwig, T.; Vasconcellos, D.; Lee, J.; Antczak, D.; Kirwan, M.; Morgan, P.; et al. Effect of a scalable school-based intervention on cardiorespiratory fitness in Children: A Cluster Randomized Clinical Trial. JAMA Pediatrics 2021, 175, 680–688. [Google Scholar] [CrossRef]
  40. Gao, Z. The impact of an exergaming intervention on urban school children’s physical activity levels and academic outcomes. Asian J. Exerc. Sports Sci. 2013, 10, 1–10. [Google Scholar]
  41. Fitness-Gaming. Brain Breaks Boost Physical Activity and Enhance Classroom Learning. Available online: http://www.fitness-gaming.com/news/markets/schools/brain-breaks-boost-physical-activity-and-enhance-classroom-learning.html#.VzBYfeRh6oM (accessed on 30 June 2021).
  42. Mok, M.M.; Chin, M.K.; Chen, S.; Emeljanovas, A.; Mieziene, B.; Bronikowski, M.; Laudanska-Krzeminska, I.; Milanovic, I.; Pasic, M.; Balasekaran, G.; et al. Psychometric properties of the attitudes toward physical activity scale (APAS): A Rasch analysis based on data from five locations. J. Appl. Meas. 2015, 16, 379–400. [Google Scholar] [PubMed]
  43. Skowroński, W.; Horvat, M.; Nocera, J.; Roswal, G.; Croce, R. Eurofit special: European fitness battery score variation among individuals with intellectual disabilities. Adapt. Phys. Act. Q 2009, 26, 54–67. [Google Scholar] [CrossRef]
  44. Slaughter, M.H.; Lohman, T.G.; Boileau, R.A.; Horswill, C.A.; Stillman, R.J.; Van Loan, M.D.; Bemben, D.A. Skinfold equations for estimates of body fatness in children and youth. Hum. Biol. 1988, 60, 709–723. [Google Scholar] [PubMed]
  45. HOPSports. What Is Brain Breaks? Available online: http://hopsports.com/what-is-brain-breaks (accessed on 10 July 2021).
  46. McNees, L.K. The Impact of HOPSports on Adequacy in and Predilection for Physical Activity in Children. Master’s Thesis, Northwest Missouri State University, Maryville, MO, USA, 2012. Available online: http://www.nwmissouri.edu/library/theses/2012/McNeesLauren.pdf (accessed on 10 July 2021).
  47. Department of Basic Education (DBE). Curriculum and Assessment Policy Statement (CAPS); Life Orientation Grades 4–6, Final draft; Government Print: Pretoria, South Africa, 2011. [Google Scholar]
  48. Cohen, J. Statistical Power Analysis for the Behavioural Sciences, 2nd ed.; Erlbaum: Hillsdale, NJ, USA, 1988. [Google Scholar]
  49. Stadler, M.C. Die Effek van Fisieke Aktiwiteits-Intervensieprogram (FAI) op die Fisieke Fiksheidvlakke, Liggaamsamestelling en Gesondheids-Risikogedrag van 9- tot 13-Jarige Dogters. Ph.D. Thesis, Noordwes-Universiteit, Noordwes, South Africa, 2007. [Google Scholar]
  50. Albertsson-Wikland, K.; Niklasson, A.; Gelander, L.; Holmgren, A.; Nierop, A.F.M. Novel type of reference for BMI aligned for onset of puberty—using the QEPS growth model. BMC Pediatr. 2022, 22, 238–252. [Google Scholar] [CrossRef] [PubMed]
  51. Bulca, Y.; Bilgin, E.; Altay, F.; Demirhan, G. Effects of a Short Video Physical Activity Program on Physical Fitness Among Physical Education Students. Percept. Mot. Ski. 2022, 129, 932–945. [Google Scholar] [CrossRef]
Ijerph 19 11236 g001 550
Figure 1. Flow diagram of the participants of this study.
Figure 1. Flow diagram of the participants of this study.
Ijerph 19 11236 g001
Ijerph 19 11236 g002 550
Figure 2. (a–d): Group interaction over time regarding the anthropometric measurements. (a) Group × Time effect for during pre- and post-test (f = 1.70; p = 0.195). (b) Group × Time effect during pre- and post-test (f = 20.61; p = 0.232). (c) Group × Time effect during pre- and post-test (f = 1.8; p = 0.176). (d) Group × Time effect during pre- and post-test (f = 7.64; p = 0.007).
Figure 2. (a–d): Group interaction over time regarding the anthropometric measurements. (a) Group × Time effect for during pre- and post-test (f = 1.70; p = 0.195). (b) Group × Time effect during pre- and post-test (f = 20.61; p = 0.232). (c) Group × Time effect during pre- and post-test (f = 1.8; p = 0.176). (d) Group × Time effect during pre- and post-test (f = 7.64; p = 0.007).
Ijerph 19 11236 g002
Ijerph 19 11236 g003a 550Ijerph 19 11236 g003b 550
Figure 3. (a–g). Group interaction over time regarding physical fitness skills. (a) Group × Time effect during pre- and post-test (f = 88.98; p = ≤0.001); (b) Group × Time effect during pre- and post-test (f = 83.97; p = ≤0.001); (c) Group × Time effect during pre- and post-test (f = 0.52; p = 0.473); (d) Group × Time effect during pre- and post-test (f = 32.19; p = ≤0.001); (e) Group × Time effect during pre- and post-test (f = 18.73; p = ≤0.001); (f) Group × Time effect during pre- and post-test (f = 60.22; p = ≤0.001); (g) Group × Time effect during pre- and post-test (f = 381.40; p = ≤0.001).
Figure 3. (a–g). Group interaction over time regarding physical fitness skills. (a) Group × Time effect during pre- and post-test (f = 88.98; p = ≤0.001); (b) Group × Time effect during pre- and post-test (f = 83.97; p = ≤0.001); (c) Group × Time effect during pre- and post-test (f = 0.52; p = 0.473); (d) Group × Time effect during pre- and post-test (f = 32.19; p = ≤0.001); (e) Group × Time effect during pre- and post-test (f = 18.73; p = ≤0.001); (f) Group × Time effect during pre- and post-test (f = 60.22; p = ≤0.001); (g) Group × Time effect during pre- and post-test (f = 381.40; p = ≤0.001).
Ijerph 19 11236 g003aIjerph 19 11236 g003b
Table
Table 1. Descriptive statistics of study variables.
Table 1. Descriptive statistics of study variables.
SubjectsNMinMaxMeanSD
Experimental group7310.50 13.02 11.85 0.38
Control group4911.42 12.70 12.02 0.31
Total group12210.5013.0211.920.36
N = number, Min = minimum; Max = maximum; SD = standard deviation.
Table
Table 2. Differences between the experimental and control group during the pre- and post-test regarding their physical fitness levels.
Table 2. Differences between the experimental and control group during the pre- and post-test regarding their physical fitness levels.
VariablesExperimental Group
(n = 73)		Control Group (n = 49)Significance of Difference
Mean ± SDMean ± SDtdfpd
Pre-Test (PrT)
Anthropometry
Age (years)11.85 ± 0.3812.02 ± 0.31−2.786 114.305 <0.006 *0.47 #
Height (cm)149.33 ± 6.95153.28 ± 8.29−2.745 90.528 <0.007 *0.48 #
Weight (kg)46.35 ± 16.1046.89 ± 11.91−0.212 118.809 0.8320.03
BMI20.80 ± 6.3319.74 ± 3.781.152 118.631 0.2520.17
% Body fat23.02 ± 8.3025.26 ± 7.20−1.580 112.244 0.1170.27 #
Physical Fitness
Stork balance (sec)30.62 ± 14.9630.33 ± 16.820.099 94.700 0.9210.02
Plate tapping (sec)14.42 ± 2.0614.88 ± 1.44−1.466 119.790 0.1450.23 #
Sit-and-reach (cm)27.92 ± 7.3222.79 ± 8.003.594 96.769<0.001 *0.64 ##
Standing jump (cm)137.29 ± 21.40148.71 ± 19.65−3.037 108.860 <0.003 *0.53 ##
Sit-up (n)15.36 ± 4.2420.59 ± 3.14 −7.824 118.768 <0.001 *1.23 #
10 × 5 m Shuttle run (sec)21.63 ± 2.6921.37 ± 1.480.699 116.307 0.4860.10
20 m Shuttle run (n)19.22 ± 11.3425.53 ± 12.69−2.810 95.052 <0.006 *0.50 ##
Post-Test (PoT)
Anthropometry
Height (cm)150.72 ± 7.01154.30 ± 8.44−2.456 89.859 0.016 0.42 #
Weight (kg)47.22 ± 16.4448.38 ± 12.86−0.438 117.134 0.662 0.07
BMI20.63 ± 6.0820.06 ± 4.170.613 119.926 0.541 0.09
% Body fat27.12 ± 9.4226.98 ± 7.990.087 113.482 0.931 0.01
Physical Fitness
Stork balance (sec)57.08 ± 6.4533.83 ± 17.838.749 56.528 <0.001 * 1.30 ###
Plate tapping (sec)12.89 ± 1.6915.64 ± 1.59−9.141 107.365 <0.001 * 1.63 ###
Sit-and-reach (cm)29.43 ± 7.1423.47 ± 8.204.140 93.204 <0.001 * 0.73 ##
Standing jump (cm)141.52 ± 19.69144.98 ± 19.71−0.951 103.013 0.344 0.18
Sit-up (n)18.86 ± 4.6119.67 ± 8.69−0.598 66.280 0.552 0.09
10 × 5 m Shuttle run (sec)19.82 ± 2.1122.20 ± 1.88−6.512 110.775 <0.001 * 1.13 ###
20 m Shuttle run (n)28.85 ± 15.9324.82 ± 12.931.537 115.605 0.1270.25 #
SD = standard deviation; df = degrees of freedom; cm—centimeters; kg—kilogram; %—percentage; sec—seconds; n—number; t = t-value; * statistical significance p ≤ 0.05; # practical significance small effect d = ≥0.2; ## practical significance medium effect d = ≥0.5; ### practical significance large effect, d = ≥0.8.
Table
Table 3. Differences within the experimental and control group’s physical fitness levels during pre-and post-test.
Table 3. Differences within the experimental and control group’s physical fitness levels during pre-and post-test.
Pre-Test (PrT)Post-Test (PoT)Significance of Difference
VariablesMean ± SDMean ± SDtdfpd
Experimental group
Anthropometry
Height (cm)149.33 ± 6.95150.72 ± 7.01−6.939 72 <0.000 * 0.20 #
Weight (kg)46.35 ± 16.1047.22 ± 16.44−2.229 72 0.029 0.05
BMI20.80 ± 6.3320.63 ± 6.080.597 72 0.552 0.03
% Body fat23.02 ± 8.3027.12 ± 9.42 −6.622 72 <0.001 * 0.49 #
Physical Fitness
Stork balance (sec)30.62 ± 14.9657.08 ± 6.45−14.818 72 <0.001 * 1.77 ##
Plate tapping (sec)14.42 ± 2.0612.89 ± 1.698.757 72 <0.001 * 0.74 ##
Sit-and-reach (cm)27.92 ± 7.3229.43 ± 7.14−2.970 72 <0.004 * 0.21 #
Standing jump (cm)137.29 ± 21.40141.52 ± 19.69−4.867 72 <0.001 * 0.20 #
Sit-up (n)15.36 ± 4.2418.86 ± 4.61−12.343 72 <0.001 * 0.83 ###
10 × 5 m Shuttle run (sec)21.63 ± 2.6919.82 ± 2.118.175 72 <0.001 * 0.68 ##
20 m Shuttle run (n)19.22 ± 11.3428.85 ± 15.93−10.500 72 <0.001 * 0.85 ###
Control group
Anthropometry
Height (cm)153.28 ± 8.29154.30 ± 8.44−6.229 48 <0.001 *0.12
Weight (kg)46.89 ± 11.9148.38 ± 12.86 −5.828 48 <0.001 *0.13
BMI19.74 ± 3.7820.06 ± 4.17 −2.658 48 0.011 *0.08
% Body fat25.26 ± 7.2026.98 ± 7.99−3.483 48 <0.001 *0.24 #
Physical Fitness
Stork balance (sec)30.33 ± 16.8233.83 ± 17.832.425 48 0.010 *0.21 #
Plate tapping (sec)14.88 ± 1.4415.64 ± 1.59−2.665 48 <0.001 *0.52 ##
Sit-and-reach (cm)22.79 ± 8.0023.47 ± 8.20−4.798 48 0.5660.08
Standing jump (cm)148.71 ± 19.65144.98 ± 19.71−0.577 48 <0.002 *0.19
Sit-up (n)15.36 ± 4.2419.67 ± 8.693.327 48 0.4390.50 ##
10 × 5 m Shuttle run (sec)21.37 ± 1.4822.20 ± 1.880.781 48 <0.002 *0.56 ##
20 m Shuttle run (n)25.53 ± 12.6924.82 ± 12.93−3.290 48 0.019 *0.06
SD = standard deviation; df = degrees of freedom; cm—centimeters; kg—kilogram; %—percentage; sec—seconds; n—number; t = t-value; * p ≤ 0.05; # practical significance small effect d = ≥0.2; ## practical significance medium effect d = ≥0.5; ### practical significance large effect, d = ≥0.8.
Table
Table 4. Effect of the intervention program on the experimental- and control group regarding the anthropometric measurements and physical fitness tests.
Table 4. Effect of the intervention program on the experimental- and control group regarding the anthropometric measurements and physical fitness tests.
VariabledfMean2F-Valuep-Value
Anthropometry
Height (cm)
Interaction effect15,412,709.9947,751.24≤0.001 *
Time effect184.9674.77≤0.001 *
Time × Group effect11.931.700.195
Group effect1830.837.330.008 *
Weight (kg)
Interaction effect1522,763.201197.359≤0.001 *
Time effect181.8120.61≤0.001 *
Time × Group effect15.731.450.232
Group effect142.550.0970.755
BMI
Interaction effect196,723.641697.21≤0.001 *
Time effect10.340.1780.674
Time × Group effect13.491.8530.176
Group effect138.700.6790.412
Body fat %
Interaction effect1153,667.081182.04≤0.001 *
Time effect1498.0146.07≤0.001 *
Time × Group effect182.607.6410.007 *
Group effect164.5700.4970.482
Physical Fitness
Stork Balance (sec)
Interaction effect1338,076.531081.20≤0.001 *
Time effect113,157.58151.67≤0.001 *
Time × Group effect17719.5688.98≤0.001 *
Group effect18119.9925.97≤0.001 *
Plate Tapping (sec)
Interaction effect149,027.799459.45≤0.001 *
Time effect18.929.760.002 *
Time × Group effect176.7683.97≤0.001 *
Group effect1151.6729.26≤0.001 *
Sit-and-Reach (cm)
Interaction effect1157,355.181636.97≤0.001 *
Time effect169.853.6400.059
Time × Group effect19.950.5180.473
Group effect11804.1818.77≤0.001 *
Standing Long Jump (cm)
Interaction effect14,804,888.096095.46≤0.001 *
Time effect13.640.1260.723
Time × Group effect1930.6432.190≤0.001 *
Group effect13248.374.1210.045
Sit-ups (n)
Interaction effect181,331.871917.066≤0.001 *
Time effect198.226.4100.013 *
Time × Group effect1287.0818.733≤0.001 *
Group effect1535.9012.6320.001 *
10 × 5 m Shuttle Run (sec)
Interaction effect1105,944.7613,932.109≤0.001 *
Time effect114.238.370.005 *
Time × Group effect1102.4660.22≤0.001 *
Group effect165.488.6110.004 *
20 m Shuttle Run (n)
Interaction effect1141,989.26415.955≤0.001 *
Time effect11165.3560.47≤0.001 *
Time × Group effect11568.7181.403≤0.001 *
Group effect176.100.2230.638
df—degrees of freedom; cm—centimeters; kg—kilogram; %—percentage; sec—seconds; n—number; p—Greenhouse–Geisser; p ≤ 0.05 *.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Bonnema, J.; Coetzee, D.; Lennox, A. Effect of a Three-Month HOPSports Brain Breaks® Intervention Program on the Physical Fitness Levels of Grade 6-Learners in South Africa. Int. J. Environ. Res. Public Health 2022, 19, 11236. https://doi.org/10.3390/ijerph191811236

AMA Style

Bonnema J, Coetzee D, Lennox A. Effect of a Three-Month HOPSports Brain Breaks® Intervention Program on the Physical Fitness Levels of Grade 6-Learners in South Africa. International Journal of Environmental Research and Public Health. 2022; 19(18):11236. https://doi.org/10.3390/ijerph191811236

Chicago/Turabian Style

Bonnema, Jacqueline, Dané Coetzee, and Anita Lennox. 2022. "Effect of a Three-Month HOPSports Brain Breaks® Intervention Program on the Physical Fitness Levels of Grade 6-Learners in South Africa" International Journal of Environmental Research and Public Health 19, no. 18: 11236. https://doi.org/10.3390/ijerph191811236

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

Article Metrics

Back to TopTop