Step counts, cardiorespiratory fitness, and goal setting in elementary school physical education

A national recommendation for students is to participate in moderate to vigorous physical activity (MVPA) for at least 50% of physical education class time. There is not sufficient evidence of elementary-aged children setting goals to help achieve 50% MPVA during physical education classes. This dissertation took a three-study approach to observe the physical active (PA), goal setting, and cardiorespiratory endurance of children in first to fifth grades, as well as how enjoyment affected the PA of the participants. In the pilot study, participants (first to fifth grade) wore accelerometers for 12 weeks. MVPA was tracked during a typical physical education class. Results indicated that fitness lessons having small class sizes had the greatest differences (β = 14.8%, 95% C.I. 5.7%-23.9%, p < 0.001). In study two, the participants (fourth and fifth grade) wore pedometers for 12 weeks. In study three, the participants (fourth and fifth grade) ran the PACER test three times. The control group had no mention of goals while the individual and class goals group set new goals after each data collection period. The enjoyment level of the participants was measured through the PACES questionnaire. In study two, all of the groups increased how many steps were taken during physical education class, with the control group being statistically significant. The interaction between step count and group was (F(3.59,264.10) = 2.84, p = .030, η2 p = .038). It was found that the enjoyment level did not have an effect on how many steps the students took during physical education class, (F(2,166) = 1.54, p = .218, η2 p = .019). Study three participants iv all increased the number of PACER laps run, but no groups had significant results, (F(3.99,281.60) = 1.11, p = .352, η2 p = .016) with enjoyment not effecting goal setting. In conclusion, these results show the need for physical education teachers to adjust their teaching style to allow for more opportunities to be physically active in class, thus increasing the possibility of students reaching the 50% MVPA recommendation. Further research needs to be conducted to see the true effects on goal setting in elementary-aged students.

STEP COUNTS, CARDIORESPIRATORY FITNESS, AND GOAL SETTING IN ELEMENTARY SCHOOL PHYSICAL EDUCATION by Mandy Kirkham King A dissertation submitted to the faculty of The University of Utah in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Exercise and Sports Science Department of Health, Kinesiology and Recreation The University of Utah August 2018 Copyright © Mandy Kirkham King 2018 All Rights Reserved The University of Utah Graduate School STATEMENT OF DISSERTATION APPROVAL The dissertation of Mandy Kirkham King has been approved by the following supervisory committee members: Timothy A. Brusseau and by , Chair 5/29/2018 Ryan D. Burns , Member 5/30/2018 Darla M. Castelli , Member 6/4/2018 Kristy Hilton , Member 6/13/2018 James C. Hannon , Member A. Mark Williams the Department/College/School of Date Approved Date Approved Date Approved Date Approved 6/7/2018 Date Approved , Chair/Dean of Health, Kinesiology and Recreation and by David B. Kieda, Dean of The Graduate School. ABSTRACT A national recommendation for students is to participate in moderate to vigorous physical activity (MVPA) for at least 50% of physical education class time. There is not sufficient evidence of elementary-aged children setting goals to help achieve 50% MPVA during physical education classes. This dissertation took a three-study approach to observe the physical active (PA), goal setting, and cardiorespiratory endurance of children in first to fifth grades, as well as how enjoyment affected the PA of the participants. In the pilot study, participants (first to fifth grade) wore accelerometers for 12 weeks. MVPA was tracked during a typical physical education class. Results indicated that fitness lessons having small class sizes had the greatest differences (β = 14.8%, 95% C.I. 5.7%–23.9%, p < 0.001). In study two, the participants (fourth and fifth grade) wore pedometers for 12 weeks. In study three, the participants (fourth and fifth grade) ran the PACER test three times. The control group had no mention of goals while the individual and class goals group set new goals after each data collection period. The enjoyment level of the participants was measured through the PACES questionnaire. In study two, all of the groups increased how many steps were taken during physical education class, with the control group being statistically significant. The interaction between step count and group was (F(3.59,264.10) = 2.84, p = .030, η2p = .038). It was found that the enjoyment level did not have an effect on how many steps the students took during physical education class, (F(2,166) = 1.54, p = .218, η2p = .019). Study three participants all increased the number of PACER laps run, but no groups had significant results, (F(3.99,281.60) = 1.11, p = .352, η2p = .016) with enjoyment not effecting goal setting. In conclusion, these results show the need for physical education teachers to adjust their teaching style to allow for more opportunities to be physically active in class, thus increasing the possibility of students reaching the 50% MVPA recommendation. Further research needs to be conducted to see the true effects on goal setting in elementary-aged students. iv TABLE OF CONTENTS ABSTRACT ......................................................................................................................iii LIST OF TABLES ........................................................................................................... vii LIST OF FIGURES .........................................................................................................viii ACKNOWLEDGMENTS ................................................................................................. ix Chapters 1 INTRODUCTION .......................................................................................................... 1 Statement of Problem ............................................................................................. 6 Study Purpose ......................................................................................................... 7 References .............................................................................................................. 8 2 STUDY 1: ELEMENTARY PHYSICAL EDUCATION: A FOCUS ON FITNESS ACTIVITIES AND SMALL CLASS SIZES ARE ASSOCIATED WITH HIGHER LEVELS OF PHYSICAL ACTIVITY ...................................................... 13 Abstract ................................................................................................................ Introduction ......................................................................................................... Methods ............................................................................................................... Participants .............................................................................................. Instrumentation ........................................................................................ Procedures ............................................................................................... Contextual Factors ................................................................................... Data Analysis ........................................................................................... Results ................................................................................................................. Discussion ............................................................................................................ Conclusions ......................................................................................................... References ........................................................................................................... 14 14 15 15 15 15 15 16 16 16 17 18 3 STUDY 2: EFFECT OF GOAL SETTING ON STEP COUNTS AND ENJOYMENT DURING PHYSICAL EDUCATION CLASS ................................ 19 Introduction ......................................................................................................... 19 Methods ............................................................................................................... Participants .............................................................................................. Instrumentation ........................................................................................ Procedures ............................................................................................... Data Analysis ........................................................................................... Results ................................................................................................................. Discussion ............................................................................................................ Conclusions ......................................................................................................... References ........................................................................................................... 23 23 23 24 25 26 29 35 36 4 STUDY 3: EFFECTS GOAL SETTING HAS ON CHILDREN’S CARDIORESPIRATORY FITNESS LEVELS AND ENJOYMENT ..................... 42 Introduction ......................................................................................................... Methods ............................................................................................................... Subjects .................................................................................................... Instrumentation ........................................................................................ Procedures ............................................................................................... Data Analysis ........................................................................................... Results ................................................................................................................. Discussion ............................................................................................................ Conclusions ......................................................................................................... References ........................................................................................................... vi 42 45 45 45 46 47 48 50 56 58 LIST OF TABLES Tables 2.1 Contextual factors compared to mean % of moderate-to-vigorous physical activity and percentage of students meeting 33 and 50% of moderate-to-vigorous physical activity during physical education (N = 281) ............................................. 16 2.2 Main effect parameter estimates from the multi-level general linear mixed effects model (N = 281) ............................................................................................ 16 2.3 Main effect parameter estimates from the multi-level generalized mixed effects model (logit link) ...................................................................................................... 17 3.1 Teacher assignments ................................................................................................. 24 3.2 Descriptive statistics for step counts ........................................................................ 27 3.3 Descriptive statistics for enjoyment levels ............................................................... 30 4.1 PACER laps completed across time ......................................................................... 49 4.2 Count and percentile meeting FitnessGram’s healthy fitness zone for aerobic capacity across time points ....................................................................................... 51 4.3 Descriptive statistics for enjoyment levels ............................................................... 51 4.4 Individual group, PACER goals ............................................................................... 55 LIST OF FIGURES Figures 2.1 Interaction between class size and lesson context on percent of physical education wear time in MVPA ................................................................................. 17 3.1 Step count for the three groups at three time points ................................................. 28 4.1 PACER lap count for the three groups at three time points ..................................... 49 4.2 Enjoyment levels at pre-enjoyment (Week 1) and postenjoyment (Week 15) ......... 52 ACKNOWLEDGMENTS Numerous people and schools made this dissertation possible. Thank you to the schools that allowed me to collect data. Thank you to all of the physical education teachers who helped collect data. I appreciate all of the support and guidance that my mentor, Tim Brusseau, and my committee gave me. Also, a huge thank you to my family and friends for your continued support as I was completing all of my coursework and dissertation! This task, which seemed impossible, was made achievable by your many words of encouragement and support. CHAPTER 1 INTRODUCTION Physical activity has an endless list of benefits. It can help prevent diseases, improve mood, give a natural energy boost, and help control weight (Mayo Clinic, 2016). About 35 chronic conditions can be prevented from being physically active, including cancer, metabolic syndrome, cardiovascular disease, arthritis, high blood pressure, and stroke (Booth, Roberts, & Laye, 2012; Glickman, Parker, Sim, Cook, & Miller, 2012; Koplan, Liverman, & Kraak, 2005; National Heart, Lung, and Blood Institute, 2018). Additional benefits of physical activity are that a person’s mental health and mood may improve, better sleep patterns can be attained, and bones and muscles can become stronger (Mayo Clinic, 2016; Reilly & Kelly, 2011). Adding to the list of benefits of regular physical activity is that it can also help someone’s self-esteem and social skills, which are key indicators of well-being (Biddle & Asare, 2011; Biddle & Mutrie, 2015; Ekeland, Heian, & Hagen, 2005; Landry & Driscoll, 2011). Conversely, if someone is not physically active, then they are at risk for the opposite of all of the above-stated benefits (Elmesmari, Reilly, Martin, & Paton, 2017; Oliveira, Moreira, Mota, & Santos, 2014). They could have high blood pressure, become obese and have cardiovascular disease (Cauderay & Cachat, 2015). Research shows that being physically active can help prevent obesity while high sedentary time can lead to 2 obesity (Herman, 2014; Jimenez-Pavon, 2010). Many children do not receive enough physical activity, so their psychological, social, and physical health and well-being are negatively affected (Smedegaard, Christiansen, Lund-Cramer, Bredahl, & Skovgaard, 2016). Children who did not meet the physical activity guidelines and have a significant amount of screen time have 2.52 times higher odds of being overweight or obese (Bai et al., 2016). Even though there are countless advantages of physical activity, children (and adults) are not getting as much as they need to benefit from the positive factors of physical activity (Eime, Young, Harvey, Charity, & Payne, 2013; Hills, Dengel, & Lubans, 2015). Because of the numerous benefits of exercise, the Centers for Disease Control and Prevention recommends that children should get at least 60 minutes of moderate to vigorous physical activity (MVPA) every day (CDC, 2015b). Overall, youth are not meeting this 60-minute recommendation (Hallal, Andersen, Guthold, Haskell, & Ekelund, 2012). The amount of physical activity someone receives may be a result of environmental factors, weather, grade level, individual student, location of school, socioeconomic status, and / or gender (Greenfield, Almond, Clarke, & Edwards, 2016; Tucker & Gilliland, 2007). Research also shows enjoyment affects how much children exercise. If the activity is seen as enjoyable, then it increases the likelihood of someone participating (Coulter & Woods, 2011; Fu, Burns, Brusseau, & Hannon, 2016; Gao, Zhang, & Podlog, 2013). Lewis suggests that interventions should focus on increasing the participants’ enjoyment of physical activity to see an increase in their self-reported ability to engage in physical activity (Lewis, Williams, Frayeh, & Marcus, 2016). Enjoyment is 3 one of the major determinants of whether a child participates in physical activity or not (Coulter & Woods, 2011; Fu, Burns, Brusseau, & Hannon, 2016; Gao, Zhang, & Podlog, 2013). Research shows that physical activity can have a positive effect on someone’s emotional well-being (Bailey, Hillman, Arent, & Petitpas, 2013). Schools can be a great place to help children meet the physical activity recommendation (Howe, Freedson, Alhassan, Feldman, & Osganian, 2012), as the majority of time spent outside of their home is spent in school (SHAPE America, 2013). SHAPE America and the Centers for Disease Control and Prevention have developed a program called CSPAP, Comprehensive School Physical Activity Program (CDC, 2015a; SHAPE America, 2013). CSPAP includes five different components to help children meet the national recommendation of 60 minutes of daily physical activity by suggesting different places to be physical active. The five components are physical education, physical activity before and after school, physical activity during school, staff involvement, and family and community engagement (SHAPE America, 2017). Physical education provides an optimal opportunity for children to be engaged in planned physical activity. Research shows that through a quality physical education program, children can learn skills and acquire knowledge to be physically active throughout their life (Sallis et al., 2012). The United States Department of Health and Human Services (USDHHS) recommends that students be engaged in moderate to vigorous physical activity (MVPA) for at least 50% of class time (USDHHS, 2010). The research shows that students are not getting 50% of MVPA during physical education class (Bevans, Fitspatrick, Sanches, Riley, & Forrest, 2010), but they are physically active during physical education (Brueseau & Kulinna, 2015). Students may not be as 4 active in physical education as they should be because of lack of motivation, lack of understanding the benefits of physical activity, low enjoyment levels of physical activity, or possibly because of their lifestyle choices. Hutchins (2009) found that self-efficacy and self-motivation both affected how much physical activity the participants received. One way to improve someone’s physical activity is through goal setting. A goal is defined as the object or aim of an action (Latham & Locke, 1991; Locke & Latham, 2002; Locke, Shaw, Saari, & Latham, 1981). There are many different types of goals and history shows that goal setting has been one of the most effective psychological strategies that can improve performance (Locke & Latham, 1990). The goal setting theory has been around since 1970 (Ryan, 1970). Ryan (1970) claimed goals influence subsequent action. It has been said that setting goals facilitates a behavior change because they guide individual’s attention and effort with a desire to obtain a specified level of proficiency (Locke & Latham, 2002, 2006). It has been found that someone can be more successful with obtaining their goal when they are more committed, have high self-efficacy, and perceive their goal as important (Latham & Locke, 1991; Locke & Latham, 2002; Locke & Latham, 2006). Once a goal is set, if feedback, task strategies, or rewards are given to the person trying to attain the goal, then the chance of reaching the goal may increase (Latham & Locke, 1991). Feedback, rewards, and strategy planning have been identified as behavior change techniques (BCT) (Latham & Locke, 1991; Locke & Latham, 2002, 2006). It has been found that goal-setting interventions have been successful with both males (Moy, Weston, Wilson, Hess, & Richardson, 2012), females (Sidman, Corbin, & Le Masurier, 2013), and across a range of ages (Horne, Hardman, Lowe, & Rowlands, 2009) in relation to physical activity. It has been shown that goal setting interventions can 5 last from 1 week (Gardiner, Eakin, Healy, & Owen, 2011) to longer than a year (Narayan & Mazzola, 2014). Research shows that goal setting has a positive impact on children (Dauenhauer, Keating, & Lambdin, 2016; Horne, Hardman, Lowe, & Rowlands, 2009;). Different studies have looked at the effects that goal setting has on physical activity. Burns, Brusseau, and Fu (2017) found that sixth graders increased their step count and cardiorespiratory endurance compared to sixth graders who received no goal setting during a 36-week CSPAP. There are different theories and different types of goals that research covers. One of these theories is the self-determination theory (SDT). It has been researched to see if this affects the students’ motivation to be physically active in physical education. The SDT says that if behavior is influenced by intrinsic motivation (i.e., enjoyment), then participation is more likely to continue than if extrinsic motivation is present (i.e., receiving recognition). To put it simply, SDT studies the connection between enjoyment and physical activity (Hyndman, Benson, Lester, & Telford, 2017). In some research, it was found that when students are assigned a task to work on as a team, then their physical activity increases (Deci & Ryan, 1985; Grolnick & Ryan, 1987; Prusak et al., 2004). Another theory is the achievement goal theory, which states that individuals can be in one of two dimensions: task-orientation and ego-orientation. Within these two dimensions, they can be considered to be high or low (Nicholls, 1984). Task-orientation is when someone believes their success comes from trying hard (Duda & Nicholls, 1992). Ego-orientation is when you compare your performance to someone else; for example, if you beat the opponent, then you feel you have been successful (Lochbaum & Roberts, 6 1993). One type of a goal is performance goals. Performance goals are based on your achievements and not competing against someone else (Baghurst, Tapps, & Kensinger, 2015; Weinberg & Gould, 2011). Research shows that performance goals are considered to be more effective because they are more controllable (Burton, 1989). Performance goals have also been shown to increase intrinsic motivation (Ryan, Vallerand, & Deci, 1984). The use of group goals in comparison to individual goals has been studied (Frierman & Gill, 1994; Lee, 1988; Locke, 1991). Locke and Latham (1985) found that group and individual goals can both have positive results. Research shows that setting goals can have a positive impact on the amount of physical activity that someone achieves. Koufoudakis (2016) found that goal setting had a positive effect on the participants in her study. Data were collected for 4 weeks. Week 1 and 3 were baseline, week 2 was feedback, and week 4 was goal setting. The researcher set a 10% increase in steps for the participants. It was found that boys were more active than the girls and the fourth graders took more steps than the fifth graders. Statement of Problem Even though it is suggested that children receive 60 minutes of MVPA daily, very few are reaching this recommendation (CDC, 2015b; Colley, Janssen, & Tremblay, 2012). Research shows that when people track how many steps they take, it has the potential to motivate them to be more active (Berry, Fraser, Spence, & Bengoechea, 2007). Goal setting has not been thoroughly explored to see what effect it has on improving daily MVPA for children or what effect goal setting has on children’s 7 enjoyment levels of being physically active. Nevertheless, this study will help determine if goal setting increases the number of steps children take during physical education class and well as how enjoyment affects students’ physical activity levels. Study Purpose The purpose of this study took a two-study approach to test the effects of goal setting on the participants’ physical activity, as well as if their enjoyment level plays a part into their physical activity levels. Each study had an individual goals group, class goals group, and a control group. The first study looked at the effects that goal setting had on the number of steps that the participants took during physical education class. The second study saw if goal setting affects the participants’ cardio-respiratory endurance. Participants in both studies also completed the PACES questionnaire to see how enjoyment level affected his or her physical activity. It was hypothesized that both individual and class group goals would have a positive effect on the amount of physical activity the participants achieved during physical education class in comparison to the control group. Also, the higher the participants scored themselves on the PACES questionnaire would result in higher physical activity levels. The hypothesize was found to be incorrect. 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BMC Public Health, 16, 1127. Tucker, P., & Gilliland, J. (2007). The effect of season and weather on physical activity: A systematic review. Public Health, 121, 909-922. U.S. Department of Health and Human Services. (2010). Strategies to improve the quality of physical education. Retrieved from http://www.cdc.gov/HealthyYouth. Weinberg, R. S., & Gould, D. (2011). Foundations of sport and exercise psychology. Champaign, IL: Human Kinetics. CHAPTER 2 STUDY 1: ELEMENTARY PHYSICAL EDUCATION: A FOCUS ON FITNESS ACTIVITIES AND SMALL CLASS SIZES ARE ASSOCIATED WITH HIGHER LEVELS OF PHYSICAL ACTIVITY Reprinted with permission from Kirkham-King, M., Brusseau, T. A., Hannon, J. C., Castelli, D. M., Hilton, K., Burns, R. D. (2017). Elementary Physical Education: A Focus on Fitness Activities and Smaller Class Sizes Are Associated With Higher Levels of Physical Activity. Preventive Medicine Reports, 8, 135–139. 14 Contents lists available at ScienceDirect Preventive Medicine Reports journal homepage: www.elsevier.com/locate/pmedr Elementary physical education: A focus on fitness activities and smaller class sizes are associated with higher levels of physical activity Mandy Kirkham-Kinga,⁎, Timothy A. Brusseaua, James C. Hannonb, Darla M. Castellic, Kristy Hiltond, Ryan D. Burnsa a Department of Health, Kinesiology, and Recreation, University of Utah, Salt Lake City, UT, USA College of Physical Activity and Sports Sciences, West Virginia University, Morgantown, WV, USA Department of Kinesiology and Health Education, University of Texas at Austin, Austin, TX, USA d University of Southern California, Los Angeles, CA, USA. b c ARTICLE INFO ABSTRACT Keywords: Exercise Physical education and training Adolescents Optimizing physical activity during physical education is necessary for children to achieve daily physical activity recommendations. The purpose of this study was to examine the relationship among various contextual factors with accelerometer measured physical activity during elementary physical education. Data were collected during 2015–2016 from 281 students (1st–5th grade, 137 males, 144 females) from a private school located in a metropolitan area of Utah in the U.S. Students wore accelerometers for 12 consecutive weeks at an accelerometer wear frequency of 3 days per week during physical education. A multi-level general linear mixed effects model was employed to examine the relationship among various physical education contextual factors and percent of wear time in moderate-to-vigorous physical activity (%MVPA), accounting for clustering of observations within students and the clustering of students within classrooms. Explored contextual factors included grade level, lesson context, sex, and class size. Main effects and interactions among the factors were explored in the multi-level models. A two-way interaction of lesson context and class size on %MVPA was shown to be statistically significant. The greatest differences were found to be between fitness lessons using small class sizes compared to motor skill lessons using larger class sizes (β = 14.8%, 95% C.I. 5.7%–23.9% p < 0.001). Lessons that included a focus on fitness activities with class sizes that were < 25 students associated with significantly higher %MVPA during elementary physical education. 1. Introduction There are many health benefits associated with a physically active lifestyle. Approximately 35 different chronic conditions can be prevented by being physically active, including: arthritis, cardiovascular disease, cancer, stroke, high blood pressure, metabolic syndrome, and type 2 diabetes (Centers for Disease Control and Prevention (CDC), 2015). Bones and muscles become stronger, mental health and mood can improve, as well as improved sleep patterns with elevated levels of physical activity. (Mayo Clinic, 2016). Additionally, studies have shown that a child's fitness level is associated with academic achievement (Castelli et al., 2007) and cognitive functioning (Roberts et al., 2010). Conversely, physical inactivity associates with an increased prevalence of obesity, cardiovascular disease, and high blood pressure (Cauderay and Cachat, 2015). Research has found that being physically active helps prevent obesity while higher levels of sedentary behavior can lead to obesity (Herman et al., 2014; Jimenez-Pavon et al., 2010). ⁎ Schools in the United States provide an ideal environment for students to be physical active and prevent obesity (Howe et al., 2012). School is where children spend the majority of their time outside of the home (SHAPE America, 2013). The Institutes of Medicine recommends children get 30 min of moderate-to-vigorous physical activity (MVPA) and have the opportunity to be physically active for 60 min while at school (Koplan et al., 2005). If the amount of physical activity (PA) opportunities is higher during the school day it not only helps children reach the daily recommendation of 60 min of MVPA but it may lower obesity incidence (Alexander et al., 2015). Physical education class is an optimal setting to increase the PA opportunities during the school day. Numerous sources suggest that when a high-quality physical education program is implemented, students can learn the skills, confidence, and knowledge to be physically active during school, outside of school, and throughout their life (Sallis et al., 2012; USDHHS, 2010). During physical education classes, the U.S. Department of Health and Human Services (USDHHS) recommends Corresponding author. E-mail address: [e-mail] (M. Kirkham-King). http://dx.doi.org/10.1016/j.pmedr.2017.09.007 Received 31 May 2017; Received in revised form 15 September 2017; Accepted 23 September 2017 15 M. Kirkham-King et al. that students are engaged in MVPA at least 50% of the time (USDHHS, 2010). However, there have been numerous studies done showing that students are not meeting this guideline (Bevans et al., 2010; Coe et al., 2006; Fairclough and Stratton, 2005; Levin et al., 2001; Nader and National Institute of Child Health and Human Development Study of Early Child Care and Youth Development Network, 2003; McKenzie et al., 2006; McKenzie et al., 2000; Nettlefold et al., 2011; Scruggs et al., 2003; Troiano et al., 2007; Van Beurden et al., 2003). In a review by Fairclough and Stratton (2006), it was found that on average students engage in MVPA 34.2% of physical education class time. Scruggs (2007, 2013) suggests that elementary students should be engaged in MVPA at least 33% of class time. Scruggs (2007) gives five suggestions of why the MVPA goal for elementary children should be set at 33% as opposed to 50%: 1) Elementary physical education is shorter than secondary physical education so things such as management and instruction may have a greater impact on overall activity time, 2) It is recommended that young children engage in physical activity intermittently, 3) Educational goals and public health both need to be taught as well as the importance of developing lifelong healthy habits, 4) Elementary physical education lessons are focused on the cognitive, affective and psychomotor domains and not just physical activity, 5) The “play-teach-play” approach is implemented more in elementary physical education than in secondary classes. This helps create an intermittent physical activity environment (Scruggs, 2007). The amount of MVPA students achieve during physical education can be a result of the individual student, environmental factors, socioeconomic status, grade level, location of school, and gender (Greenfield et al., 2015). Student's age, size of gym, teacher specialization, lesson type, and class size also have an effect on the amount of MVPA that is achieved (Bevans et al., 2010; Ruch et al., 2012). In a review of 44 papers that researched physical activity in physical education, Fairclough and Stratton (2005) found that regardless of the observation instrument boys and girls took part in similar amounts of physical education. Nettlefold et al. (2011) found that 1.8% of girls and 2.9% of boys achieved the physical activity guidelines. Despite these findings, no study to date has explored contextual factors related to physical activity using accelerometers over relatively long time periods. The purpose of this study was two-fold. The primary purpose was to explore what contextual factors may affect the elementary student's physical activity during education class. The explored factors included: sex of student, class size (small, large), lesson context (motor skills/ games, fitness), and grade level (1st–5th grade). For descriptive purposes, a secondary aim was to identify the percentage of participants that met the recommendations, 33% MVPA and 50% MVPA during physical education class time. 2. Methods 2.1. Participants Participants were a convenience sample of 281 school-aged children (1st–5th grade, 137 males, 144 females) from a private school located in a metropolitan area in the southwestern United States. Approximately 38% of the participants identified themselves as an ethnic minority. The parents were informed of the study in a newsletter and given the option for their child(ren) to not participate. Children were informed of the study in physical education class. Each grade level had physical education three times a week. The University Institutional Review Board and school principal approved the research design and procedures used in this study. 2.2. Instrumentation Participants wore an Actigraph GT1M (Pensacola, FL, USA) on their waist, in line with their right knee cap. The GT1M is a uniaxial accelerometer with vertical and antero-posterior vectors (Hanggi et al., 2013). The GT1M can be worn by all ages, and measures body movements at a frequency of 30 Hz (Actigraph, 2015). The epoch length (time-sampling interval) was set at 5-s. Epoch length is how often the accelerometer records the participant's physical activity (Vale et al., 2009). When higher epoch lengths are used it can result in inaccurate results because of the short-bursts of PA children typically participate in (Rowlands et al., 2006). Therefore, smaller epoch lengths can help provide more valid results (Rowlands, 2007). The GT1M has been deemed valid and reliable when compared to oxygen consumption tests (Kelly et al., 2013). Previous research has validated this instrument with this age group (Hanggi et al., 2013; Ruch et al., 2012). The cut-points for the accelerometers for this study was set to those derived from Evenson et al. (2008), which have been validated against estimated energy expenditure measured using indirect calorimetry in children (Trost et al., 2011). The cut-points were: sedentary: 0–100 Counts Per Minute (CPM), light: 101–2295 CPM, moderate: 2296–4011 CPM, and vigorous: 4012 to ∞ CPM. Because multiple students shared the same accelerometer, in most cases six students, wear time validation was calculated by using filters. Each accelerometer was linked to a respective participant using identification numbers that were taped to the surface of the device. The identification numbers were changed for separate physical education classes. The accelerometers were also color coded for each group of students to facilitate data identification. The data was downloaded according to filters that had been previously set. Filters were set according to when each participant came to physical education class. The students had physical education class three times a week, for 45 min. The filters were set to start 3 min after class started and to stop 3 min before class ends, resulting in 39 min of physical education. This was done because this time frame more accurately represents when the students were in physical education class because of transitions to and from other classes. 2.3. Procedures All children had previous experience wearing a physical activity monitor as part of their physical education program. At the beginning of the study children were reminded of the correct placement of the accelerometer (on waist above the right knee). The students kept the accelerometer on during the entire physical education class and returned it to the appropriate shoebox before they left. The children had physical education three times a week for 45-min, for a total of 135 min of physical education every week. Participants wore the accelerometer for a total of 12 weeks and most weeks they wore the accelerometers three times a week. Each week the researcher collected the accelerometers and downloaded the data. The data was downloaded using the ActiLife 6.11.5 software (Pensacola, FL). Filters were set up in the ActiLife program. These filters allowed the data to be pulled out by classroom teacher and the time the students had physical education. The researcher also recorded information on an Excel sheet to help evaluate the data. On the excel sheet the researcher recorded gender, class size (small or large), context (motor skills/games, fitness), and grade level. 2.4. Contextual factors Class size levels were determined to be small if the enrollment was < 25 students and large if the class size was 25 students or more. The physical education teacher determined if a respective lesson was motor skills/games vs. fitness, which was categorized based on the primary content/activity for a respective lesson. No physical education class was a combination of two lesson types. Although most physical education classes in the U.S. incorporates of both types of lessons, the relative time spent in each is highly variable and therefore the distribution of lesson types across the 12-week observation period in the current study was up to the discretion of the teacher. Motor skills/ 16 M. Kirkham-King et al. games consisted of practicing game specific skills (e.g., kicking, shooting, dribbling, etc.) and did not involve any direct fitness component. Fitness lessons had a direct fitness component/theme and involved activities such as distance running, sprint/interval running, circuit resistance training with the aim of improving either the cardiorespiratory endurance or muscular endurance domains of health-related fitness. Fitness testing days (e.g., one mile run/walk, Progressive Aerobic Cardiovascular Endurance Run) were also categorized as a fitness lesson. The lead author was present for all physical education classes and was in close communication with the physical education teacher. 2.5. Data analysis MVPA and step count data were screened for outliers using boxplots and z-scores (using a ± 3.0 z-score cut-point) and checked for Gaussian distributions using k-density plots. < 5% of the data were omitted because of z-scores < −3.0 z, thus missing data was assumed to have not significantly bias the results. The data analyses consisted of running three multi-level models: one using a continuous outcome and two using binary outcomes. The primary analysis consisted of employing general linear mixed effects models to examine the relationships among grade level (1st–5th), sex (girl, boy), class size (small, large), and lesson context (motor skills/games, fitness) on the percent of wear time in MVPA (%MVPA; continuous outcome) during physical education class. Random intercepts were used at the child and classroom level to adjust for clustering of observations within the data structure. Secondary categorical data analyses were then conducted. Two binary variables were created to evaluate the number of students achieving 33% MVPA and 50% MVPA. Multi-level generalized mixed effects models, with a logit link function, were then run using all of the contextual factors as predictors to determine odds of a child meeting the each respective MVPA cut-point. Again, random intercepts were used at the child and classroom level to adjust for clustering of observations within the data structure. All main effects and interactions were explored in each of the multi-level models. Referents used for all comparisons included 1st graders, males, motor skills/games, and small class sizes. Alpha level was set at priori p ≤ 0.025 to adjust for analysis on multiple dependent variables. SPSS v.23.0 (Armonk, NY, USA) was used to analyze the data. 3. Results There were a total of 175 lessons across the five grade levels over 12 weeks. Approximately 64% of the lessons were motor skills/games (112/175) and approximately 54.3% of these classes were characterized as small class sizes (95/175). There were a total of 3593 studentlevel observations across the 12-weeks. The descriptive statistics for mean %MVPA and the percent of children meeting recommendations are presented in Table 1. The main effect results from the general linear mixed effects model are presented in Table 2. Being female and being enrolled in large class sizes related to lower levels of %MVPA. Additionally, fitness lessons related to higher %MVPA compared to motor skills/games and students enrolled in the 3rd and 4th grade related to higher %MVPA compared to students enrolled in the 1st grade. When the interactions were examined for %MVPA, there was a statistically significant interaction between lesson context and class size on %MVPA (β = 14.8%, 95% C.I. 5.7%–23.9% p < 0.001). Fig. 1 visually presents the interaction between lesson context and class size on %MVPA, which yielded the largest effect across all comparisons. During fitness lessons with small class sizes is when students achieved the most MVPA compared to motor skills/games and large class sizes. The results of the generalized mixed effects models are presented in Table 3. For meeting the 33% MVPA guideline, being in a large class size related to lower odds of achievement and being enrolled in the 3rd and 4th grade related to higher odds of achievement compared to being enrolled in 1st grade. There was no lesson context main effect for 33% Table 1 Contextual factors compared to mean % moderate-to-vigorous physical activity and percentage of students meeting 33% and 50% moderate-to-vigorous physical activity during physical education (N = 281). Sex Male Female Class size Small Large Grade 1st 2nd 3rd 4th 5th Lesson Motor skills Fitness Total (N = 3593) Mean % MVPA SD % MVPA Percentage of sample meeting 33% MVPA Percentage of sample meeting 50% MVPA 1799 1794 28.7 26.9 10.3 9.5 30% 23% 4% 2% 1970 1623 30.0 25.3 10.4 8.8 35% 17% 5% 1% 867 724 747 653 602 26.9 27.9 28.6 28.9 27.9 9.7 9.6 10.1 9.9 10.7 24% 27% 29% 27% 27% 2% 2% 4% 3% 5% Context 3049 27.2 9.2 25% 1% 544 31.7 13.1 36% 13% MVPA stands for moderate-to-vigorous physical activity; SD stands for standard deviation; data were collected from the state of Utah in the U.S. during the 2015–2016 academic school year. Table 2 Main effect parameter estimates from the multi-level general linear mixed effects model (N = 281). Predictor b-Coefficient (%MVPA) 95% Confidence Interval p-Value Female Large Class 2nd grade 3rd grade 4th grade 5th grade Fitness Lesson −2.0% −4.5% 1.1% 1.3% 2.4% 1.1% 2.4% −3.3% – -0.7% −5.4%–-3.4% −0.7%–2.9% 0.4%–3.1% 0.6%–4.3% −0.6%–3.3% 1.4%–3.3% 0.002 < 0.001 0.235 0.014 0.011 0.299 < 0.001 Referents are small class sizes, males, first graders, and motor skills; bold denotes statistical significance; data were collected from the state of Utah in the U.S. during the 2015–2016 academic school year. MVPA. For meeting the 50% MVPA guideline, being female and being enrolled in a large class size related to lower odds of achievement and fitness lessons related to higher odds of achievement compared to motor skills/games. There were no grade main effects for 50% MVPA. When the interactions were examined for 33% MVPA, there was a statistically significant interaction between sex and lesson context (OR = 0.52, 95% C.I.: 0.36–0.75, p < 0.001), suggesting that girls in fitness classes having lower odds of achieving the 33% MVPA guideline. When the interactions were examined for 50% MVPA, there were no statistically significant two-way interactions. There were also no observed statistically significant three-way interactions for the categorical outcomes. 4. Discussion This study examined what contextual factors relate to the amount of physical activity students attain during traditional elementary physical education classes. It was found that students, on average, were active anywhere from 25% to 31% MVPA (see Table 1), depending on the contextual factor. These results as well as other research shows that 33% MVPA may be a more realistic goal for elementary physical education (Scruggs, 2007, 2013). When the contextual factors were examined, small class sizes that used fitness lessons related to 14.8% 17 M. Kirkham-King et al. Fig. 1. Interaction between class size and lesson context on percent of physical education wear time in MVPA. Data were collected from the state of Utah in the U.S. during the 2015–2016 academic school year. Note: Error bars are 95% Confidence Intervals; MVPA is moderate-to-vigorous physical activity; Small Class Size is defined as < 25 students and Large Class Size is defined as 25 students or more. Table 3 Main effect parameter estimates from the multi-level generalized linear mixed effects model (logit link). Outcome Predictor OR 95% Confidence Interval p-value Meeting 33% MVPA Female Large Class 2nd grade 3rd grade 4th grade 5th grade Fitness Lesson Female Large Class 2nd grade 3rd grade 4th grade 5th grade Fitness Lesson 0.68 0.28 0.94 1.75 1.80 0.92 1.24 0.52 0.35 1.25 1.53 1.48 1.24 9.97 0.47–0.99 0.21–0.39 0.59–1.49 1.11–2.75 1.15–2.81 0.57–1.45 0.97–1.58 0.30–0.89 0.18–0.65 0.58–2.70 0.75–2.17 0.80–2.00 0.56–2.65 5.97–16.64 0.044 < 0.001 0.810 0.015 0.012 0.807 0.083 0.019 < 0.001 0.566 0.119 0.053 0.555 < 0.001 Meeting 50% MVPA Referents are small class sizes, males, first graders, and motor skills; OR stands for odds ratio; MVPA stands for moderate-to-vigorous physical activity; bold denotes statistical significance; data were collected from the state of Utah in the U.S. during the 2015–2016 academic school year. higher MVPA during class time compared to large classes sizes using motor skills and games. This corresponds to approximately an increase of 6.75 min for a 45-min physical education lesson. Given the low relative distribution of students meeting 33% MVPA and 50% MVPA, corresponding to 14.85 min and 22.5 min of MVPA for a 45-min lesson, increasing MVPA by 6.75 min is a large improvement compared to motor skill/games lessons with large class sizes and, as evidenced by the results of the categorical data analysis, significantly increases the odds of a child meeting MVPA cut-points. If the lesson is fitness focused and the class size is smaller than 25 students, the %MVPA students achieve during physical education classes could increase. This finding is in agreement with Bevans et al. (2010) who reported that teacher to student ratio affects PA time. On days students participated in a fitness lesson there was a 2.4% increase in the amount of MVPA (adjusted estimate), corresponding to an approximate additional 1 min of MVPA for a 45-min lesson. When class size was under 25 students they had a 4.5% increase in MVPA (adjusted estimate), corresponding to approximately an additional 2 min of MVPA for a 45-min lesson. Although these absolute values of MVPA are difficult to compare across studies because of lesson time variability, these relative increases yield strong practical significance given the proportion of students not meeting guidelines. Most students in this sample did not meet recommended guidelines for PA during physical education. Numerous studies have found the same results that students are not meeting the national recommendation of 50% MVPA during physical education. Changing the class size so only one class of students came to physical education at a time may not be possible but it would not only result in students getting more MVPA but also help them in the classroom. As the research supports with more PA students on-task behavior improves, test scores improve, and students listen better, so academic time really is not being taken away (Castelli et al., 2007). But since this change is out of the hands of the physical educators some things that they could change is their class management strategies, amount of fitness opportunities and motivating their students. If a physical educator is focused on providing opportunities for their students to improve their motor skills than they also could incorporate fitness into their lessons. For example, if they are doing stations there could be two fitness stations mixed in with the skills stations. Or the sport and fitness stations could be combined (Konukman et al., 2009). The students could be throwing and catching a ball and after four successful throws and catches both partners could jog a lap around the gym. Instead of stationary passing with a soccer ball, the students could do give and go passes. The physical educator could also plan a separate fitness activity during the lesson. Maybe the warm-up could focus more on fitness and be done for an extended amount of time. Or at the end of the lesson there could also be a fitness component. A lot of students may not be aware of recommendation to be MVPA for 50% of class time. Providing students with a physical activity device that they can keep track of their step count and MVPA, could help them be aware of the PA levels. If students are able to check their progress during the class, this could help encourage them to work harder. Goals could be introduced to the students. These goals could be individual goals, class goals or even their grade could be based on how often they reach 50% MVPA. Limitations to this study include the use of an observational and correlational research design, therefore casual associations cannot be made linking contextual factors to physical activity behaviors. Also, data were collected from one private school located from the state of Utah in the U.S., therefore the external validity evidence for this study is limited. Also, limiting the external validity is the use of a three-day per week physical education curriculum. It is unknown how well the results would generalize to one-day per week classes or five-day per week classes. Additionally, only select contextual factors were used in the current analysis, therefore it is unknown what other contextual factors may have related to %MVPA. Other factors may include the amount of play space available, if a lesson was indoors or outdoors, experience of the physical educator, and use of a teacher-centered vs. student-centered pedagogical method. 5. Conclusions Because of longitudinal design and relative large sample, this paper gives a clear idea of how much physical activity students are receiving in elementary physical education classes and provides evidence that different contextual factors during physical education manifests different physical activity levels. Data being collected across 12 weeks and the large sample size (281 participants) aids in providing strong internal validity evidence. It was found that small class sizes (< 25 students) during fitness lessons achieved the most physical activity. These results can help physical education teachers plan their lessons differently. Despite these results, the development of motor skills should not be neglected because of its link with free-living physical activity 18 M. Kirkham-King et al. participation and health outcomes. 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CHAPTER 3 STUDY 2: EFFECT OF GOAL SETTING ON STEP COUNTS AND ENJOYMENT DURING PHYSICAL EDUCATION CLASS Introduction Children and youth ages 6 to 19 should accumulate 12,000 steps every day (Colley, Janseen, & Tremblay, 2012), or at least 60 minutes of physical activity daily (Centers for Disease Control and Prevention, 2016). Most children are not reaching the physical activity recommendation (Troiano, Berrigan et al., 2008). Schools provide an ideal environment for students to accumulate physical activity minutes as a means to prevent obesity (Howe, Freedson, Alhassan, Feldman, & Osganian, 2012). Outside of the home environment, school is where children spend the majority of their time (SHAPE America, 2013). Specifically, for the hours that children are awake, 57% of those hours are at school (Guinhouya et al., 2009), thus making schools one of the primary locations for reaching children (Koplan, Liverman, & Kraak, 2005). The Institute of Medicine (Institute of Medicine, 2013) recommends children accumulate 30 minutes of moderate to vigorous physical activity (MVPA) and have the opportunity to be physically active for 60 minutes while at school. One approach to providing opportunities for children to be physically active in schools is the Whole 20 School, Whole Community, Whole Child Model (WCSS) (Centers for Disease Control and Prevention, 2018). This collaborative approach provides supports for physical activity participation in formal educational setting, like physical education as well as engagement in play at a local park. One advantage to focusing on a quality physical education program is that it can teach a variety of skills and can increase students’ knowledge about physical activity and improve their movement proficiency (Centers for Disease Control and Prevention, 2013) through physical activity participation. The United States Department of Health and Human Services (U.S. Department and Human Services, 2010) recommends that students should be engaged in MVPA at least 50% of physical education class or 82 steps/minute (Scruggs, 2013). Research shows that 30 minutes of MVPA can be equated to 5505 steps (Burns, Brusseau, Fu, & Hannon, 2016). This recommendation can help children accumulate 60 minutes of daily MVPA (Colley et al., 2012). Physical education appears to be the best place to increase the amount of physical activity at school (Brusseau & Kulinna, 2015), as a starting place within a larger-scale model. If the amount of physical activity opportunities is increased during the school day, it not only helps children reach the daily recommendation of 60 minutes of MVPA, but it can also have multiple health benefits, such as preventing overweight and obesity (Alexander, Fusco, & Frohlich, 2015). Brusseau and Kulinna (2015) found that physical activity increased on days that students had physical education. Boys increased from 25% MVPA to 33% MVPA and girls from 31% MVPA to 46% MVPA (Brusseau & Kulinna, 2015). These percentages are converted into 1,140 more steps and 4.1 more minutes of MVPA that children achieved on days with physical education class (Brusseau & 21 Kulinna, 2015). Brusseau and Kulinna (2015) add that more emphasis needs to be placed on physical education and other physical activity segments (e.g., recess, classroom movement breaks) to increase physical activity levels. Numerous studies illustrate that children are not meeting the physical activity recommendation during physical education (Beurden et al., 2003; Bevans, Fitzpatrick, Sanchez, Riley, & Forrest, 2010; Brusseau & Kulinna, 2015; Coe, Pivarnik, Womack, Reeves, & Malina, 2006; Fairclough & Stratton, 2005; Levin, McKenzie, Hussey, Kelder, & Lytle, 2001; McKenzie, Marshall, Sallis, & Conway, 2000; McKenzie et al., 2006; Nettlefold et al., 2011; Scruggs et al., 2003; Troiano et al., 2008). Kirkham-King and colleagues (2017) found that students spent between 25% to 31% of physical education class in MVPA depending on the contextual factor of the lesson. Costa and colleagues (2017) found that 74% to 89.1% of the participants did not reach 50% MVPA during physical education classes. Targeted intervention is needed. In 2011, Brusseau and colleagues found that during physical education class the participants accumulated 49 (boys) and 46 (girls) steps/minute. In a study where the physical education lessons focused on skills such as throwing, catching, track, and field, boys accumulated 39 steps/min and girls took on average 36 steps/min (Kodish, Kulinna, Martin, Pangrazi, & Darst, 2006). Sixth graders accumulated 48 steps/min (boys) and girls 47 steps/min during physical education (Tudor-Locke, Lee, Morgan, Beighle, & Pangrazi, 2006). Brusseau (2015) found that fourth and fifth graders took on average 1,645 steps (50.8 steps/min) and girls took 1,558 steps (51.9 steps/min) in a 30-minute physical education class. In the spring when classes were outdoors, boys averaged 2,805 steps (93.5 steps/min) and girls 2,191 steps (73 steps/min) (Brusseau, 2015). 22 Goal setting may be a possible solution to increase the amount of physical activity accumulated in physical education class. Goal setting has been shown to be effective in improving dedication, commitment, and perseverance for long-term self-motivation (Silva & Weinberg, 1984). Johnson and colleagues (1997) concluded that group goals might have the most significant effect on individual sports because they increase personal goals when the performance demands are high. Streit (1996) found that two-person groups set the highest goals and six-person groups and individuals were the lowest (Streit, 1996). Recent studies have examined pedometer step count goal setting with young children (Dauenhauer, Keating, & Lambdin, 2016; Epton, Currie, & Armitage, 2017; Koufoudakis, Erwin, Beighle, & Thornton, 2016; Wilson, Sibthorp, & Brusseau, 2017). Dauenhauer and colleagues (2016) found that when goals were set, and rewards were given for reaching their goals, then physical activity increased considerably. When physical activity leaders set physical activity goals for elementary aged students, step counts and cardio-respiratory endurance increased in older children (Burns, Brusseau, & Fu, 2017). Research also shows enjoyment has been associated with someone’s decision to be physically active (Bauman et al., 2012; Teixeira, Carraça, Markland, Silva, & Ryan, 2012). Children are more likely to participate in physical activity when they find it enjoyable (Hills, Dengel, & Lubans, 2015). Chronic engagement in physical activity is also increased if the children enjoy the activity (Coulter & Woods, 2011; Fu, Burns, Brusseau, & Hannon, 2016; Fu, Gao, Hannon, Burns, & Brusseau, 2016). This current study was designed to investigate how individual goals, class goals, or no goals effect step counts and enjoyment during physical education classes. There is a 23 lack of studies comparing individual goals, class goals, and control groups (Baghurst, Tapps, & Kensinger, 2015) and a lack of studies exploring goal setting in physical education classes. It is hypothesized that setting individual and class goals will have a positive impact on the number of steps the participants take during physical education in comparison to the control group. It is also hypothesized that if step counts increase as a result of the goal setting interventions, then enjoyment will also increase. Methods Participants Participants were a convenience sample of 154 students (fourth and fifth graders, 96 males, 58 females), from a public school located in a metropolitan area in the southwestern United States. Six percent of the participants identified themselves as an ethnic minority. Parent consent was obtained before data collection. Children were informed of the study in their physical education class. The University Institutional Review Board and school principal approved the research design and procedures that were used in this study. Instrumentation Physical activity was assessed using step counts, recorded using Yamax CW-600 pedometers. Participants wore a Yamax, CW-600 Digi-Walker pedometer at waist level, on the right side, on the superior border of the iliac crest above the right knee. The Yamax Digi-Walker CW600 has a 7-day memory, tracks activity time, and has been determined to be accurate and reliable (Yamax, 2017). The Yamax-Digiwalker SW-200 (made by the same company as the CW-600) has been found to be a reliable and valid 24 instrument (Oliver, Schofield, Kolt, & Schluter, 2007). Pedometers are considered more practical because they are more affordable than accelerometers (Freedson & Miller, 2000). Children understand that when they move, they are being active, which results in taking steps (Graser, Groves, Prusak, & Pennington, 2011). Procedures Three different teachers had their students wear the pedometers. All the teachers are certified to teach physical education, have a Master’s degree, and have previous teaching experience. To eliminate teacher differences or biases, each teacher had a different group for each grade level. Teacher assignments were made according to Table 3.1. The control group had 49 participants, individual goals group had 53 participants, and the classroom goals group had 52 participants. Participants had physical education four times a week, for 45 minutes. During the study, the participants engaged in invasion game units: football, lacrosse, handball, and basketball. Each unit lasted about 4 weeks. During the baseline week, the students step counts were recorded. From the baseline step count numbers, the goals were set. The control group did not have any goals, and there was no mention of goals. After the 1st week, the 1st day the students in the individual goals group had physical education, Table 3.1 Teacher assignments Grade 4th grade Teacher 1 Class goals Teacher 2 Individual goals Teacher 3 Control group 5th grade Control group Class goals Individual goals 25 they received a paper that had their step count goal for that week. Their step count goal was a 10% increase from the previous week. The students worked towards a new goal every week. To set a new goal for the class goals group, a 10% increase was added to the total number of steps the class took the previous week. The classes step count goal was posted on the whiteboard as well as the physical education teacher informing the class of the new class goal. It was determined to have the researcher set the goal because of the age and developmental level of the participants (Koufoudakis et al., 2016). A 10% increase goal was set because increasing activity would be challenging yet achievable (Pangrazi, Beighle, & Sidman, 2002). The participants also completed the Physical Activity Children’s Enjoyment Scale (PACES) to help determine how their enjoyment level affected their physical activity. PACES is a reliable measurement tool for children’s enjoyment levels of physical activity (Moore, Yin, Duda, Gutin, & Barbeau, 2009). PACES was completed during baseline (week 1), and post (week 12). The PACES tool consists of 16 questions starting with the stem “When I am physically active …” following with a five-point Likert scale, 1 being disagree a lot and 5 being agree a lot. Data Analysis Step counts and enjoyment levels were screened for outliers using boxplots and zscores (using a ± 3.0 z-score cut-point) and checked for Gaussian distributions using histograms. No extreme outliers were found and no influential cases were identified using Cook’s distance after the primary analysis. A 2 x 3 x 3 Analysis of Variance (ANOVA) test was run to examine the effect of sex (boy, girl), group (control, individual goals, class goals), and time (week 1, week 7, week 12) on step counts taken during physical 26 education. The effect of interest was the group x time interaction, but all two-way and three-way interactions were examined. Mauchly’s test was examined for the assumption of sphericity and the Greenhouse-Geisser correction was made if the assumption of sphericity was violated. ANOVA main effect and interaction effect sizes were computed using partial eta-squared and pair-wise comparison effect sizes were computed using Cohen’s delta where d < 0.20 indicating a small effect, d = 0.50 a medium effect, and d > 0.80 a large effect (Cohen, 1988). The analysis included an alpha level of p ≤ 0.05 and was carried out using SPSS v.24.0 (Armonk, NY, USA) statistical software package. Results The step counts taken for the three groups at the different time points are presented in Table 3.2. When step counts were compared against the three different groups, the control group improved the most. Figure 3.1 shows the three groups step counts during the three time points. The individual and group goals both started out at about the same level, decreased during the midpoint, and both increased step count by the end of the study. However, the increase was not statistically significant. The class goals group took a mean of 1943.75, and SD = 586.106 steps during the baseline week, 1807.75, SD = 467.04 steps during week seven, and completed the study taking 1922.29 steps, SD = 453.98. The individual goals group started the study taking 1892.43 steps, SD = 643.35; in the middle, they took 1825.00, SD = 337.33, and finished the study taking 1976.17, SD = 430.26. The control group started low at baseline taking 1665.14 steps, SD = 506.77, increased a significant amount at the midpoint to 1886.57 steps, SD = 574.6 and finished off with a little increase taking 1902.39 steps, SD = 481.37. When the interactions were examined, there was a statistically significant 27 Table 3.2 Descriptive statistics for step counts Time Week 1 Baseline Week 7 Midpoint Week 12 Post Group Control Gender Male Female Total Mean 1722.97 1573.84 1665.14 SD 564.27 396.87 506.77 n 30 19 49 Individual goals Male Female Total 1962.86 1755.50 1892.43 588.37 737.32 643.36 35 18 53 Classroom goals Male Female Total 2016.19 1836.81 1943.75 598.36 564.60 586.11 31 21 52 Control Male Female Total 2022.77 1671.53 1886.57 622.12 420.90 574.60 30 19 49 Individual goals Male Female Total 1891.37 1695.94 1825.00 366.50 229.62 337.33 35 18 53 Classroom goals Male Female Total 2000.55 1523.14 1807.75 384.29 438.21 467.03 31 21 52 Control Male Female Total 2028.27 1703.63 1902.39 490.78 402.18 481.37 30 19 49 Individual goals Male Female Total 2086.34 1761.94 1976.17 425.80 360.66 430.26 35 18 53 Classroom goals Male Female Total 2077.00 1693.90 1922.29 420.80 409.97 453.98 31 21 52 28 Figure 3.1 Step count for the three groups at three time points. 29 interaction between group and time (F(3.59,264.10) = 2.84, p = .030, η2p = .038). The two-way interaction between gender and time was not statistically significant (F(1.78,264.10) = 2.05, p =.136, η2p = .014) and the three-way interaction among group, gender and time was also not statistically significant (F(3.57,264.10) = .516, p = .704, η2p = .007). Enjoyment was also used as an outcome variable and did not show a significant effect among the three experimental groups. The two-way interaction for group and time on enjoyment was not statistically significant (F(2,166) = 1.54, p = .218, η2p = .019). Sphericity was checked using the Mauchly’s test. It was violated for all of the effects; subsequently, we used the Greenhouse-Geisser to correct the violation. The descriptive statistics for the enjoyment levels at week 1 (pre-enjoyment) and week 12 (postbaseline) are displayed in Table 3.3. Discussion The purpose of this study was to examine the effect of individual and group goal setting on physical activity levels (step counts) and physical activity enjoyment during elementary physical education. Findings suggest that neither the individual nor class goal setting increased physical activity during physical education. Paradoxically, the control group did see an increase in physical activity. Enjoyment levels were not impacted by the goal setting intervention. The findings contradict most previous goal setting research where goal setting has had a positive impact on the participants’ physical activity behavior (Dauenhauer et al., 2016; Epton et al., 2017; Koufoudakis et al., 2016; Latham & Locke, 1991; Marcoux et al., 1999; Sallis, Mckenzie, & Alcaraz, 1997; Wilson et al., 2017). More specifically, Koufoudakis and colleagues (2016) found that goal setting during 30 Table 3.3 Descriptive statistics for enjoyment levels Time Week 1 Pre Enjoyment Week 12 Post Enjoyment Group Control Gender Male Female Total Mean 3.72 3.96 3.81 SD 1.44 1.02 1.30 n 36 21 57 Individual goals Male Female Total 4.20 4.12 4.17 .90 .57 .79 37 21 58 Classroom goals Male Female Total 4.22 4.12 4.18 .83 1.02 .90 34 23 57 Control Male Female Total 4.14 4.08 4.12 .62 .71 .65 36 21 57 Individual goals Male Female Total 4.12 4.07 4.10 .86 .63 .78 37 21 58 Classroom goals Male Female Total 4.22 4.34 4.27 .80 .57 .71 34 23 57 31 unstructured recess resulted in fourth and fifth graders increasing their percentage of time being physically active compared to a control group. Marcoux (1999) also found that goal setting was successful with fourth graders when assessing the effectiveness of a selfmanagement program. Similarly, when children set goals, had peer models, and received rewards, their physical activity increased substantially (Dauenhauer et al., 2016). Sallis (1997) found that establishing a goal led to more effort in fifth graders, which resulted in more physical activity in comparison to the control group. Burns and colleagues (2017) also found that sixth graders who set goals increased their physical activity (Burns et al., 2017). A goal setting intervention using both individual and group goals has also been successful during summer camps (Wilson et al., 2017). Epton, Curie, and Armitage (2017) found in their review of 141 studies that goal setting is an effective tool for changing behavior and is considered a fundamental component to successfully changing a behavior (Epton et al., 2017). Furthermore, they found that goal setting is particularly successful with children and in schools. There are a few studies that found a negative effect of goal setting on physical activity in younger school children. Burns (2017) found that third graders who had received a step count goal decreased their step count (-832 steps) while fourth and fifth graders saw no change in step counts. Sixth graders, however, increased their step counts. These results can be attributed to the fact that sixth graders are transferring from the concrete operational phase of cognitive development to the formal operational phase with logical thought, whereas third graders are still not able to understand abstract concepts, such as related increasing physical activity will improve their health (Burns et al., 2017). 32 The uniqueness of the current findings may be explained when considering the required curriculum, the employed goal-setting strategies, group size, age of participants, and pedometers worn by all participants. The certified teachers that were involved in this study were required to implement a curriculum focused on teaching students how to move correctly (Athlos Academies, 2017), as opposed to maximizing physical activity. The curriculum was also very teacher-centric. Lessons would often be taught using a very command style teaching lesson and have a primary focus on static skill development. The number of steps taken during physical education is directly impacted by the teacher’s instructional skills and the type of content that is delivered (Brusseau et al., 2011). Lonsdale (2013) concluded that more student-centric teaching strategies and infusing fitness into the lessons could increase moderate to vigorous physical activity. They identified specific aspects of the lessons, including activity selection and classroom management and instructional strategies, as factors that can impact physical activity. Lessons that have more of a fitness focus have also led to increased levels of physical activity in physical education classes (Kirkham-King et al., 2017). Indeed, lessons that have a fitness focus can result in 61% more moderate to vigorous physical activity (Jin, 2013; Lonsdale et al., 2013) and Brusseau (Brusseau, Hannon, & Burns, 2016) found that outdoor fitness activities resulted in higher moderate to vigorous physical activity than indoor fitness activities. Lounsbery (Lounsbery, Mckenzie, Trost, & Smith, 2011) suggested that if the curriculum is evidence-based (i.e., CATCH or SPARK), then physical activity could increase as much as 18%. Additionally, research has also found that the direct or command style instructional model tends to be less physically active when compared to the tactical games model (Smith, Savory, & Fairclough, 2015). 33 Due to the age and developmental level of the participants, the research team set each participant’s goals (Koufoudakis et al., 2016). Each week, average step count had a 10% increase added to set their new weekly goal. The participants may have considered weekly goals to be unreachable, which could efficiently attenuate effort (Epton et al., 2017). It may have been more advisable to set a daily goal of 2,000 steps, which is generally considered to be the high end of normative physical education class step counts (Bershwinger & Brusseau, 2013). Group size may have also affected how successful the group goals were. Locke and Latham (1985) found that group goal setting led to more improvement in physical activity compared to individual goals. This may be the case because when someone feels a part of a group, the performance demands are higher than when working toward an individual goal (Locke & Latham, 1985). Previous research has found that two- to threeperson groups have the most productive goal setting results when compared to larger groups (Streit, 1996). Similarly, Johnson and colleagues found that three-person groups increased their performance more than the individual goal and control groups (Johnson et al., 1997). The experimental groups in the current study had 27 and 31 participants. The weekly group goals received were very large (i.e., 190,000-200,000 steps per week). This is a very large number for anyone to break down to see how many steps they needed to personally take. Future group goal setting should be done in smaller groups, which is likely to lead to smaller and seemingly more attainable step levels. Johnson and colleagues’ (1997) group goals participants recorded their personal goal and discussed what they could individually do to reach team goal. Knowing what they were going to do 34 individually helped them comprehend that the goal was more attainable. Although contradictory to most previous goal setting research, it is possible that the participants were still in the concrete operational phase of cognitive development, (Burns et al., 2017; Hendee, 1991), which may have limited their understanding of the abstract concept of goal setting (Latham & Locke, 1991). Lytle and Achterberg (1995) suggest that the ability to understand abstract concepts is expanded when someone is in middle school. In the formal operational stage, students can formulate their own hypotheses to explain occurrences and begin to think more abstractly (Lytle & Achterberg, 1995; Michela & Contento, 1986). In the present study, the control group increased their step counts without the goal setting. Tudor-Locke (2002) and Thorup (2016) found that a pedometer, by itself, is a simple physical activity motivator. Pedometers provide instant feedback to participants so they are aware of their current step count (Thorup et al., 2016). This could have been a big enough motivator for the control group to increase their step count while the goal groups grew tired of the goal setting. Research shows that pedometers alone have been successful in increasing physical activity levels (Lubans, Morgan, & Tudor-locke, 2009). Students had access to viewing their step counts so it may have been helpful for the control group to be blinded to their step values to avoid this unintended motivation. Although, inadvertently, the current study suggests that a pedometer alone can lead to increases in physical education physical activity when compared to a pedometer with attached goal setting. It was also found that the students’ enjoyment levels did not change as a result of goal setting. The participants had a high baseline score for the enjoyment of physical activity, which likely would not have changed much due to a ceiling effect 35 (Cotter, Hermsen, Ovadia, & Vanneman, 2001). There are limitations to this study that must be considered before the results can be generalized. First, participants consisted of elementary-school-aged children from the Mountain West region of the U.S.; therefore, the external validity of the results is questionable if generalized to youth in younger (preschoolers) or older (adolescents) age groups or children from other geographical regions. Second, only step counts were monitored. The construct validity may have been stronger if accelerometers were used to assess physical activity during physical education. Third, the research design was quasiexperimental; therefore, the internal validity of the results would be stronger if a grouprandomized controlled design was employed with larger sample size. Future research should consider the size of groups, sealing the pedometers in the control group, and the curricula and teaching style as a possible research methodology to more effectively address goal-setting research questions. 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Retrieved May 20, 2018, from https://www.yamax.co.uk/digi-walkers/cw600-digi-wsalker/ CHAPTER 4 STUDY 3: EFFECTS GOAL SETTING HAS ON CHILDREN’S CARDIORESPIRATORY FITNESS LEVELS AND ENJOYMENT Introduction Evidence shows that low levels of aerobic fitness raise the risk for cardiovascular disease and decreases quality of life (Anderssen et al., 2007; Kaminsky et al., 2013). Aerobic fitness is a proxy measure of health that is a strong predictor of risk for cardiovascular disease and overall health status (Kodama et al., 2009). Aerobic fitness supports overall health and function (Garber et al., 2011). Higher levels of aerobic fitness are also beneficial to brain function, school achievement, improved memory, and cognition (Billinger, Vidoni, Morris, Thyfault, & Burns, 2017; Chaddock-Heyman, Hillman, Cohen, & Kramer, 2014). Maintaining aerobic fitness in childhood is critical to help with cognitive and physical development (Khan & Hillman, 2014). Insufficient physical activity results in a reduction of aerobic fitness levels and increased risk for disease (Kaminsky et al., 2013). Research shows that the percentage of youth reaching adequate levels of aerobic fitness has decreased from 52.4% in 2000 to 42.2% in 2012 (Gahche et al., 2014). Since 1975, youth’s aerobic performance has decreased by approximately 4% every decade 43 (Armstrong, 2013). Interventions that promote fitness have become a significant public health priority with the decline of youth’s aerobic fitness levels (Instuite of Medicine, 2012). The growing trend of inactivity in children could have an adverse effect on physical and cognitive health (Raine et al., 2013). With the decrease in aerobic fitness, schools can be an ideal environment to reverse this trend (Sanchez-Vaznaugh, Sánchez, Rosas, Baek, & Egerter, 2012). One of the main goals of physical education is to teach children and youth the skills to be live a healthy life (Metzler, McKenzie, van der Mars, Barrett-Williams, & Ellis, 2013a, 2013b). Standard three of the National Physical Education Standards is focused on helping students “achieve and maintain a health-enhancing level of physical activity and fitness” (SHAPE America, 2013). During physical education class, students engage in MVPA, which can be an essential contributor to their fitness (Lonsdale et al., 2013). Moreover, if physical education class is taught by a certified teacher, then the children’s physical fitness will increase more than if taught by a noncertified teacher (Starc & Strel, 2012). One of the most effective psychological strategies for improving performance is goal setting (Locke & Latham, 1990). Research supports that physical education is a great place to teach students self-management skills, such as self-monitoring and goal setting, that can promote aerobic fitness and physical activity (Lonsdale et al., 2013; Shilts, Horowitz, & Townsend, 2004). Goal setting is a mental management skill that has been proven to enhance motivation in a variety of settings, including children 10 years and older (Sherman, 1999). Setting goals during physical education class can help students preform better motorically and improve aerobic fitness (Baghurst, Tapps, & Kensinger, 2015). 44 Research shows that interventions can increase the rate of physical activity participation (Lonsdale et al., 2013). McDonald (2015) tested the effects that goal setting had on sixth-to-eighth-grade student’s aerobic fitness levels for 10 weeks. The study consisted of an intervention and control group. The participants completed the FitnessGram Progressive Aerobic Cardiovascular Endurance Run (PACER) test to measure their aerobic fitness. The intervention group set specific, measurable, attainable, relevant, and timely (SMART) goals, and the participants increased their number of laps from 40.6 to 45.9 where the control group decreased from 30.2 to 23.4 laps. Hill and Downing (2015) formally required middle school students to set goals as a means of increasing aerobic fitness, measured as laps on the PACER. The experimental group increased the number of completed laps; the control group also increased. In a longitudinal goal setting study (fourth to fifth grade), girls increased their mile run and sit-ups, but the amount of pull-ups, skinfold and sit-and-reach did not increase, and boys did not have statistically significant improvements in any of the five assessments (Sallis et al., 1997). McDonald and Trost (2015) have advocated that physical education focus on the importance of improving health-related fitness and the positive impact that goal setting has on impacting aerobic fitness; this topic is limited with the youth. In response to a call for action from national public health organizations, Metzler (2013b) has created a new health-oriented physical education curriculum model. Therefore, the purpose of this study was designed to investigate what effects goal setting and enjoyment has on children’s aerobic fitness during physical education class. It is hypothesized that setting individual and class goals will have a positive impact on the participant’s cardiorespiratory fitness in 45 comparison to the control group. It is also hypothesized that if goal setting has an effect on the number of PACER laps run, then enjoyment will also increase. Methods Subjects Participants were a convenience sample of 148 students (fourth and fifth graders, 91 males and 57 females), from a public school located in a metropolitan area in the southwestern United States. Six percent of the participants identified themselves as an ethnic minority. Parent consent was obtained before data collection. Children were informed of the study in their physical education class. The University Institutional Review Board and school principal approved the research design and procedures that will be used in this study. Instrumentation The participants’ fitness levels were tested using the FitnessGram’s PACER test. The PACER test is a 20-meter multistage test that measures the aerobic capacity of the participants. The participants also filled out the Physical Activity Children’s Enjoyment Scale (PACES) to help determine how enjoyment levels affected physical activity. PACES is a reliable measurement tool for children’s enjoyment levels of physical activity (Moore, Yin, Duda, Gutin, & Barbeau, 2009). PACES was completed during baseline (week 1), and post (week 15). The PACES tool consists of 16 questions starting with the stem ‘When I am physically active …’ followed with a five-point Likert scale, 1 being disagree a lot and 5 being agree a lot. 46 Procedures Three different physical education teachers had their students complete the PACER test. All of the teachers are certified to teach physical education, have Master’s degrees, and have previous experience teaching physical education. In this school setting, the students attended physical education 4 days per week for 45 minutes. The participants were divided into three groups, each teacher being assigned a different group for each grade level, to prevent biases. Teacher one had the class goals group for fourth grade and for fifth grade had the control group. Teacher two had the individual goals group for fourth grade and class goals group for fifth grade. Teacher three had the control group for fourth grade and the individual goals group for fifth grade. Over the course of the 15-week intervention, the participants completed the PACER test weeks 1, 7, and 15. During the 1st week, baseline measures of PACER test were collected for the two intervention groups that set goals. The individual group set his/her own goal. Included as part of their goal, the participants said what they could do to reach their goal. Some things the students said to achieve their goal were “pace me,” “run every day,” “go outside and play,” and “exercise at home.” Their teacher worked with them on setting achievable goals. The class goals group was told how many laps they ran as a class. As a class, they set a goal for the next time they completed the PACER. As a class, they discussed things they could do individually to increase the number of laps. During the study, the students participated in a variety of activities during their physical education classes to improve their aerobic capacity. Week 7, the individual and class goals were reevaluated and adjusted if the goal was reached or was considered unreachable by the participant and/or teacher. The same baseline assessments were 47 collected during week 15 before the PACER test. There was no mention of goals to the control group. All participants also filled out the PACES to help determine how their enjoyment level affects their aerobic fitness. PACES was completed during baseline (week 1), and post (week 15). The results from the PACES were used to see if how much a participant enjoys being physically active affects their PACER score. Data Analysis PACER laps and enjoyment levels were screened for outliers using boxplots and z-scores (using a ± 3.0 z-score cut-point) and checked for Gaussian distributions using histograms. No extreme outliers were found and no influences cases were identified using Cook’s distance after the primary analysis. A 2 x 3 x 3 Analysis of Variance ANOVA test was run to examine the effect of sex (boy, girl), group (control, individual goals, class goals), and time (week 1, week 7, week 15) on PACER laps. The effect of interest was the group x time interaction, but all two-way and three-way interactions were examined. Mauchly’s test was examined for the assumption of sphericity and the Greenhouse-Geisser correction was made if the assumption of sphericity was violated. ANOVA main effect and interaction effect sizes were computed using partial eta-squared and pair-wise comparison effect sizes were computed using Cohen’s delta where d < 0.20 indicating a small effect, d = 0.50 a medium effect, and d > 0.80 a large effect (Cohen, 1988). The analysis included an alpha level of p ≤ 0.05 and was carried out using SPSS v.24.0 (IBM Corp., Armonk, NY, USA) statistical software package. Each participants PACER score was also converted into his or her VO2peak score using the following formula (Burns et al., 2016): 48 VO2peak = (0.353 x number of PACER laps completed) – (1.121 x age of participant) + 45.619 Once each participant had a VO2peak score, the researchers looked at each score to determine if the participants were in the healthy fitness zone or needs improvement zone. The healthy fitness zone was defined if a VO2peak was above 40 and the needs improvement zone was defined if a VO2peak was below 40 (Cooper Institute, 2014). The Cooper Institute has developed healthy fitness zones for all of the FitnessGram assessments (Plowman & Meredith, 2013) to determine how many laps children should be able to complete. Results When PACER laps were compared against the three groups, no significance was found. Greenhouse-Geisser was .352. Figure 4.1 shows that all of the groups increased the numbers of laps completed, but none of the goals groups were statistically significant. Each participant in the control group increased the lap count by 6.67 laps, the individual goals group increased by 10.04 laps, and the class goals group increased by 5.74 laps. See Table 4.1 for the number of laps each group completed. The two-way interaction between PACER time (week 1, week 7, week 15) and group (control, individual goals, classroom goals) is (F(3.99,281.60) = 1.11, p = .352, η2p = .016). During the pre-PACER, 33 (21 males) participants were in the needs improvement fitness zone, 11 students from each group. For the post-PACER, this number dropped to 21 (13 boys) participants in the needs improvement zone: eight in the control group, four in the individual group, and nine in the class goals group. The study started with 19.6% of the participants in the needs improvement zone and dropped to 49 Figure 4.1 PACER lap count for the three groups at three time points. Table 4.1 PACER laps completed across time Group Control group n (=148) 46 Week 1 SD Week 7 SD Week 15 SD 29.63 17.12 33.41 18.75 36.30 19.10 Individual goals 51 27.51 14.16 32.41 17.77 37.55 20.45 Class goals group 51 27.83 14.99 28.67 14.55 33.57 15.86 50 12.5% by the end of the study. See Table 4.2 for the count and percentile of participants meeting FitnessGram’s healthy fitness zones for all time points. Enjoyment was used as an outcome variable and did not show a significant effect on the number of PACER laps the participants ran in any of the three groups. The twoway interaction for enjoyment and group was (F(2,166) = 1.54, p = .218, η2p = .019). Sphericity was checked using Mauchly’s test. It was violated for all of the effects; subsequently, we used the Greenhouse-Geisser to correct the violation. The descriptive statistics for the enjoyment levels at week 1 (pre-enjoyment) and week 15 (postbaseline) are displayed in Table 4.3. Figure 4.2 depicts the enjoyment levels at pre-enjoyment (week 1) and postbaseline (week 15). Discussion The purpose of this study was to examine the effect of individual and group goal setting on the number of PACER laps completed and physical activity enjoyment during elementary physical education. Statistically, the time main effect was significant, but there was not a group by time significant interaction. Therefore, all experimental groups increased the number of PACER laps across the three different time points; however, no specific group yielded significantly better PACER improvement scores compared to any other group. The goal setting did not impact enjoyment levels. The results from the current study have been seen in previous research. Hill and Downing (2015) found that setting goals with middle school students had a positive effect on their PACER test but the control group also increased the number of laps completed. The boys in the experimental group ran 25.76(11.46) laps for the pretest and 51 Table 4.2 Count and percentile meeting FitnessGram’s healthy fitness zone for aerobic capacity across time points Time Baseline Healthy Fitness Zone Needs Improvement 135 (80.3%) 33 (19.6%) Midpoint 140 (83.3%) 28 (16.7%) Posttest 147 (87.5%) 21 (12.5%) Table 4.3 Descriptive statistics for enjoyment levels Time Group Gender Mean SD n Week 1 Pre Enjoyment Control Male Female Total 3.72 3.96 3.81 1.44 1.02 1.30 36 21 57 Individual goals Male Female Total 4.20 4.12 4.17 .90 .57 .79 37 21 58 Classroom goals Male Female Total 4.22 4.12 4.18 .83 1.02 .90 34 23 57 Control Male Female Total 4.14 4.08 4.12 .62 .71 .65 36 21 57 Individual goals Male Female Total 4.12 4.07 4.10 .86 .63 .78 37 21 58 Classroom goals Male Female Total 4.22 4.34 4.27 .80 .57 .71 34 23 57 Week 12 Post Enjoyment 52 Figure 4.2 Enjoyment levels at pre-enjoyment (Week 1) and postenjoyment (Week 15). 53 ended the study running 28.18(13.67) laps, where the girls ran 19.32(5.80) pretest laps and 19.94(7.27) laps during the posttest. The control group boys ran 21.39(10.88) pretest laps and 24.77(13.24) posttest laps while the girls ran 17.45(7.23) pretest laps and 20.57(8.44) posttest laps. Hill and Downing (2015) also found that goal setting did not have an effect on the participants’ enjoyment. However, Sallis (1997) had mixed results in his study that bridged over 2 years (fourth to fifth grade). Initially, participants received an award if their goal was met, but rewards were eventually phased out as the participants learned to self-reward. The female participants had statistically significant results in the mile run and sit-ups. The pull-ups, sit-and-reach, and skinfold assessments were not statistically significant for girls and none of the five tests were statistically significant for boys. Additional goal setting research shows that the experimental groups were statistically significant in comparison to the control groups. In a group of sixth to eighth graders (n=228 experimental group, n=76 control group), aerobic fitness was tested using SMART goals as a goal setting intervention. The intervention group significantly increased the number of completed laps (Δ=5.3 laps) compared to a control group (Δ= 6.8 laps) (Mcdonald & Trost, 2015). Lochbaum, Stevenson, and Hilario (2009) found that performance-approach goals increased shuttle run performance for college-age men but did not have an effect on women’s shuttle run time. Gao and colleagues (2013) studied the relationship between achievement goals and cardiorespiratory fitness among middle school students. Participants ran the PACER test and completed the Achievement Goals Questionnaire and Self-Efficacy Questionnaire. It was found that self-efficacy had a significant direct 54 effect on the PACER laps after controlling for the effects of achievement goals. In the Lochbaum and Gottardy (2015) meta-analysis, it was determined that random effect model, mastery, and performance approach goals all have an impact on physical activity levels achieved. Wiersma and Sherman’s (2008) research found that physical fitness may increase enjoyment. The distinctiveness of the current findings may be warranted when considering four different details. First was the number of students who were in the Healthy Fitness Zone when the study started. The number of participants who started the study in the Needs Improvement Zone was 19.6%. This number decreased to 12.5% to finish the study (see Table 4.3). There was an improving trend from baseline to posttest in the participant’s healthy fitness zones classification, but the improvement did not differ by groups. The lower number of individuals in the needs improvement zone could also have affected the null findings because the room for improvement was already small. With all three groups having an increase in the number of laps completed, it shows that setting goals did not affect the participant's cardiorespiratory fitness. Some students increased the lap count by a few laps while others ran significantly more laps. Specific examples of how participants in the individual goals group set and achieved goals are given in Table 4.4. The class goals group all beat the goal that was set: fourth grade increased by 193 laps and fifth grade increased by 130 laps. The control group had similar results with the fourth graders increasing by 103 laps and the fifth-grade group increasing by 291 laps. Such goals may be appropriate for increasing aerobic fitness, particularly when the teacher has knowledge in developmentally appropriate health objectives (Metzler et al., 2013a). 55 Table 4.4 Individual group, PACER goals Participant Week 1 Laps 1st Goal Week 7 Laps 2nd Goal Week 15 Laps 5th grade, boy 71 108 87 108 113 5th grade, boy 6 7 10 18 19 5th grade, girl 19 20 30 31 31 5th grade, girl 43 55 41 50 49 4th grade, boy 33 39 41 45 58 4th grade, boy 24 30 32 42 37 4th grade, girl 29 50 22 68 40 4th grade, girl 36 50 25 40 54 Second was the age of the participants. With the participants being 9 to 11 years old, they are still in the concrete optional phase of cognitive development (Burns, Brusseau, & Fu, 2017; Hendee, 1991), which could have hindered their ability to understand the concept of goal setting (Locke & Latham, 1990). It has been suggested that when someone is in middle school, the ability to understand abstract concepts is increased (Lytle & Achterberg, 1995), as he or she are entering the formal operational stage. In the formal operational stage, adolescents start to think more abstractly and can formulate their own hypotheses to explain occurrences (Lytle & Achterberg, 1995; Michela & Contento, 1986). Third, all of the participants were exposed to some different physical activity opportunities that could have had an effect on their aerobic fitness. All of the participants in this study have physical education class four times a week for 45 minutes, two to three recesses every day, as well as numerous brain breaks throughout the school day. Most of 56 the participants also participate in extracurricular activities. All of these physical activity opportunities could have had an effect on why all of the groups increased the number of PACER laps they completed. Aerobic fitness can be improved by a high number of physical activity opportunities as well as the amount of times the PACER is completed. Because of this, goal setting may not have been the reason why the experimental groups increased the number of laps completed. Further study needs to be completed on the possible effects of intergrating a Health Optimizing Physical Education currciulum (Metzler et al., 2013a, 2013b), which considers physical education as part of a Comprehensive School Physical Activity Program (CSPAP). Limitations of this study must be considered before the results are generalized. First, participants were from an elementary school; therefore, the external validity of the results must be questioned if used for younger or older age children from other geographical regions. Second, the research was quasi-experimental; therefore, the internal validity of the results would be stronger if a group-randomized controlled design was employed with larger sample size. Future research should consider the current physical levels of participants as a possible research methodology to more effectively address goal-setting research questions. Conclusions All groups increased their PACER laps, and the percentage of children in the Healthy Fitness Zone classification across time, but the experimental groups did not improve significantly more than the comparison group. For future studies, it is recommended to have students at different schools as well as possibly have the control group only run the PACER during the pre- and post-weeks. These findings highlight the 57 need for additional goal setting studies, specifically in the elementary physical education setting, as well as increasing the research that studies how enjoyment affects physical activity. 58 References Anderssen, S. A., Cooper, A. R., Riddoch, C., Sardinha, L. B., Harro, M., Brage, S., & Andersen, L. B. (2007). 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