Journal of Physical Activity and Health, 2015, 12, 954 -961 http://dx.doi.org/10.1123/jpah.2013-0398 © 2015 Human Kinetics, Inc.
ORIGINAL RESEARCH
Do Perceptions of Competence Mediate The Relationship Between Fundamental Motor Skill Proficiency and Physical Activity Levels of Children in Kindergarten? Jeff R. Crane, Patti J. Naylor, Ryan Cook, and Viviene A. Temple Background: Perceptions of competence mediate the relationship between motor skill proficiency and physical activity among older children and adolescents. This study examined kindergarten children’s perceptions of physical competence as a mediator of the relationship between motor skill proficiency as a predictor variable and physical activity levels as the outcome variable; and also with physical activity as a predictor and motor skill proficiency as the outcome. Methods: Participants were 116 children (mean age = 5 years 7 months, 58% boys) from 10 schools. Motor skills were measured using the Test of Gross Motor Development-2 and physical activity was monitored through accelerometry. Perceptions of physical competence were measured using The Pictorial Scale of Perceived Competence and Social Acceptance for Young Children, and the relationships between these variables were examined using a model of mediation. Results: The direct path between object control skills and moderate-vigorous physical activity (MVPA) was significant and object control skills predicted perceived physical competence. However, perceived competence did not mediate the relationship between object control skills and MVPA. Conclusion: The significant relationship between motor proficiency and perceptions of competence did not in turn influence kindergarten children’s participation in physical activity. These findings support concepts of developmental differences in the structure of the self-perception system. Keywords: early childhood, motor development, accelerometry, perceived ability, mediation
The 2013 Active Healthy Kids Canada Report Card on Physical Activity for Children and Youth1 points to the need for most Canadian children and youth to make important changes to their physical activity patterns, including increasing active play and participation in organized sport. Knowing how to help children and youth make those important changes remains unclear. Stodden and colleagues2 created a developmental model to explain individuallevel engagement and disengagement in physical activity during early, middle, and late childhood. These authors posit that both higher levels of motor skill proficiency and perceptions of physical competence bring about a positive spiral of engagement whereas “. . . children and adolescents who perceive themselves as having low motor skill competence, and actually demonstrate low levels of motor skill competence, will be drawn into a negative spiral of disengagement”.2, p.296 Emerging evidence supports this and suggests that perceptions of physical competence may play a mediating role between motor skill proficiency and physical activity.3,4 Mediation occurs when the relationship between a predictor variable and an outcome variable is influenced by an intermediary variable, or mediator.5 Barnett and colleagues3 found that perceptions of sport competence mediated the relationship between childhood object control skills (predictor) and physical activity levels (outcome) in adolescence. Their mediation model accounted for 18% of the variance in physical activity. In a parallel study, Barnett and others found that perceptions of sport competence mediated the relationship between adolescent object control skill proficiency and engagement in moderate-vigorous physical activity (MVPA) in both directions, that is, with physical
The authors are with the School of Exercise Science, Physical and Health Education, University of Victoria, Victoria, BC, Canada. Crane (jeffrcra@ uvic.ca) is corresponding author. 954
activity as the predictor or the outcome.4 These authors also found that perceptions of sport competence mediated the relationship between locomotor skill proficiency and physical activity, but only when locomotor skill proficiency was the outcome variable. Whether perceptions of competence mediate the relationship between fundamental motor skill proficiency and participation in physical activity, or the reverse, has not been examined among young children. Separately however, the relationship between perceptions of physical competence and motor skill proficiency and the relationship between motor skill proficiency and physical activity have been examined in early childhood to some extent. Children’s beliefs about their physical competence tend to be unrealistically high during early childhood, but typically decline during the elementary school years as they begin to compare themselves with their peers and as they become more sensitive to success and failure experiences.6–8 During early childhood, the relationship between perceptions of physical competence and measured motor proficiency is generally weak to moderate in strength.9–12 It is unclear however, whether the relationship differs for type of motor skill (ie, object control and locomotor skills). Among adolescents, object control skills are more strongly related to perceptions of physical competence than locomotor skills,3 however the picture is less clear for young children. Both LeGear et al10 and Robinson12 used the Test of Gross Motor Development–213 and the Pictorial Scale of Perceived Competence and Acceptance for Young Children14 to assess the relationships between object control skills, locomotor skills, and perceptions of physical competence among 4- and 5-year-old children. LeGear and colleagues found stronger correlations between perceived competence and locomotor skills (r = .37, P < .01) than between perceived competence and object control skills (r = .14, P < .05); whereas the strength of the relationship for each type of skill with perceptions was very similar in Robinson’s study (locomotor, r = .434, P < .01; object control, r = .435, P < .01). In contrast to those 2 studies, Goodway and
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Rudisill15 did not find significant relationships between perceptions of physical competence and locomotor skills (r = .03, P = .82) or object-control skills (r = .18, P = .18) among 4-year-old children who were identified as at risk for becoming educationally disadvantaged and/or developmentally delayed. It was notable that the children’s raw object control skill scores in Goodway and Rudisill’s study were particularly low (mean object control skill scores: boys = 3.9 and girls = 2.3). This ‘floor effect’ can censor the data16 and may in part explain the lack of relationship. Significant relationships between motor skill proficiency and physical activity levels have been consistently observed among young children.17–21 Among 4-year-olds, Williams and colleagues21 found a significant relationship between motor skills scores and MVPA (r = .33) and vigorous physical activity (VPA; r = .41). Similarly, Cliff et al19 found a significant relationship between overall motor skill proficiency and VPA (r = .46) among 3- to 5-year-old boys, but not among preschool girls. However, Barnett et al17 found object control skills accounted for 32% of the controlled variance in unstructured physical activity as well as percentage of time spent in moderate to vigorous physical activities. Cliff et al19 also reported that object control skills were significantly related to the proportion of time boys spent in moderate-intensity physical activity (MPA) and in MVPA (r = .52 and r = .48, respectively). While Fisher and colleagues20 did not find any sex-based differences in the association between accelerometer measured MVPA and motor skill scores among Scottish preschoolers; these researchers did find a weak association between total motor skill score and the proportion of monitored time spent in MVPA (r = .18, P < .001) for the sample as a whole. Significant positive relationships have also been noted between accelerometer measured physical activity and more novel, and perhaps more integrated, measures of motor skill proficiency among 5-year-old preschool children in Switzerland.18 The partial correlation coefficient between MPA and time to complete an obstacle course was .15 (P = .016) and between MPA and dynamic balance assessed via walking on a balance beam was .22 (P = .001). Burgi and colleagues18 also found that higher physical activity was associated with beneficial changes in motor skills 9 months later. These authors concluded that physical activity may be facilitating motor skills development among preschool aged children. Despite some evidence and theory that suggests inflated and unrealistic perceptions of physical competence in early elementary years,8,14,15 other evidence suggests there is a relationship between actual and perceived abilities among 4- and 5-year-old children.10,12 In addition, significant relationships between physical activity levels and motor skill proficiency among young children have been shown;19–21 and this relationship is likely bidirectional.2,18 By adolescence, perceptions of physical competence are consistent predictors of physical activity levels3,22–26 and these perceptions mediate the relationship between motor skill proficiency and physical activity.3 What is unclear from the extant literature is when these perceptions begin to influence physical activity participation and when perceived competence starts to mediate the relationship. Emerging evidence suggests that among young children, actual and perceived competence are related and that motor skill proficiency is related to participation in physical activity. In keeping with these thoughts, the aim of this study was to examine whether the mediating relationship was in effect among young elementary school children. Specifically, we examined kindergarten children’s perceptions of physical competence as a mediator of the relationship between motor skill proficiency as a predictor variable and physical activity levels as the outcome variable; and also with physical activity as a predictor and motor skill proficiency as the outcome.
Methods A cross-sectional design was used to examine the relationships between motor skill proficiency, physical activity levels, and perceptions of physical competence among kindergarten children. Children were eligible to participate if they were attending kindergarten in 1 of 10 consenting schools in 2 school districts in British Columbia, Canada during the 2010–2011, 2011–2012, or 2012–2013 school years. The rate of physical health and well-being vulnerability, as measured by the Early Development Instrument (EDI)27 were 13% and 8% in the 2 school districts compared with 13.5% provincially.28 The EDI is completed by kindergarten teachers and provides a measure of school readiness. Vulnerability in the Physical Health and Well Being domain of the EDI is assessed by teachers’ perceptions of the children’s fine and gross motor development, energy level, readiness for school, washroom independence, and established handedness. Data collection from each kindergarten cohort took place between the months of December to April where the average temperatures ranged between 4°C–10°C.
Participants The University Human Research Ethics Board and the school district granted approval for this study. A 2-level consent process was implemented. Parents/guardians could consent to the at-school portion of the study that involved motor skill and perceptions of physical competence assessment. In addition, parents/guardians could allow their child to participate in the physical activity portion of the study that involved the use of accelerometry to measure levels of physical activity. Consent for the at-school portion of the study was obtained for 82% (n = 430) of eligible children. Consent to wear the accelerometer was provided for 206 of these 430 children. As accelerometer wear time did not meet the study criteria for 90 children, the final sample was n = 116 (mean age = 5 years 7 months, 58% boys). To examine the whether the 116 children were representative of the larger sample of 430, independent t tests were conducted to compare locomotor skills and object control skills raw scores as well as perceptions of physical competence raw scores. No significant differences were found between the 2 groups for locomotor raw scores F(1, 421) = 0.47, P = .496 or for object control raw scores F(1, 421) = 1.18, P = .277. Similarly, there were no statistical differences for perceptions of physical competence F(1, 425) = 0.14, P = .708.
Measures Fundamental motor skills (6 locomotor skills: run, jump, hop, slide, gallop, and leap; and 6 object control skills: throw, roll, kick, strike, catch, and dribble) were assessed using the Test of Gross Motor Development–2nd Edition [TGMD-2].13 The TGMD-2 is a criterion and norm-referenced test that is used to assess the motor skill development of children. Further, mean test-retest reliability scores for locomotor skills and object control skills have been reported as .88 and .89, respectively for children aged 3 to 5 years and .94 and .96 for children aged 6 to 8 years.13 Validity of the TGMD-2 was established based on skills selected that were deemed appropriate by content experts and results from factor analyses show the test has good construct validity. Physical activity levels were measured with the Actigraph GT1M accelerometer (ActiGraph, LLC, Fort Walton Beach, FL). The Actigraph accelerometer has been shown to be a valid indicator of energy expenditure and activity levels in children and youth.29–31
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The device is worn around the waist, positioned on the right hip above the iliac crest and is connected by an elastic strap. The biaxial accelerometer collects prefiltered data at a rate of 30 measurements per second (30Hz), which is then postfiltered into measurements known as epochs, which are then converted to a metabolic equivalent. Each accelerometer was initialized to begin recording physical activity data in 15-second epochs, which are recommended to capture the sporadic activity of children.32 Consistent with previous research33 the minimum wear time criteria to be considered a valid physical activity record was 10 hours per day for at least 4 days that included at least 3 weekdays and 1 weekend day. The Pictorial Scale of Perceived Competence and Social Acceptance for Young Children14 was used to assess perceptions of physical competence. The scale has demonstrated both acceptable reliability and validity for kindergarten children.14 The scale consists of 24 items subdivided into 4 subscales (6 statements each) that are: Cognitive Competence, Physical Competence, Peer Acceptance, and Maternal Acceptance. For the purposes of this study, only the perceptions of physical competence subscale was used. Each item in the subscale was presented in the form of bipolar statements that are accompanied by a picture for each statement; for example, 2 photos display a child climbing, which are followed by a statement describing the child’s ability (eg, ‘this girl is pretty good at climbing’ and ‘this girl isn’t very good at climbing’). The child is asked to choose which picture most closely represents them. Once the child selects a picture, a follow up question is asked to determine the degree of competence within the skill (ie, ‘Are you’; ‘really good at climbing’ or ‘pretty good’). Each item is scored on a 4-point scale, where a 4 indicates the highest degree of perceived competence and 1 the lowest. Height was determined using a SECA 214 Road Rod portable stadiometer and measured to the nearest tenth of a centimeter and weight was measured to the nearest tenth of a kilogram using a Taylor Lithium Electronic scale. Body Mass Index (BMI) was calculated using the formula weight in kilograms divided by height in meters squared34and classified using the child cut-offs from the Children’s BMI Tool for Schools provided by the Centers for Disease Control and Prevention.35
Procedures The accelerometer was placed on each child by a trained researcher on the first day of testing immediately after motor skills testing. An information package was sent home with each child to parents/ guardians requesting that the accelerometer to be worn for 7 days from when the child first woke up in the morning and throughout the day until he/she went to sleep, unless bathing or swimming. Motor skills along with height and weight were assessed during scheduled physical education classes in accordance with the testing procedure outlined in the TGMD-2 Examiner’s Manual.13 Each kindergarten class was divided into 4 small groups before entering the gymnasium with each group consisting of 3 to 5 children. Each child performed the skills at their station twice before moving onto the next station. Due to scheduling constraints (eg, physical education lessons ranged in duration from 30 to 60 minutes) data were collected by research team trained in administration of the TGMD-2 over multiple visits to each school. Consented children were digitally video-recorded performing 6 locomotor skills (run, jump, hop, slide, gallop, and leap) and 6 object control skills (throw, roll, kick, strike, catch, and dribble). Afterward, children were asked to remove their shoes and height (cm) and weight (kg) were recorded. The Pictorial Scale of Perceived Competence and
Social Acceptance for Young Children14 was administered by a trained researcher individually to each child in a quiet area following a motor skills testing session.
Data Treatment The behavioral components of object control skills and locomotor skills were scored dichotomously by the investigators from the digital video. The number of components completed correctly for each subtest (locomotor and object control skills) were summed to provide a raw score (out of 48). Interobserver reliability percent agreement was 86.3% and was established by 2 investigators who coded 15% of the digital videos. The Percent Agreement Method [Number of Agreements ÷ (Number of Agreements + Disagreements) × 100].36 Raw data from the accelerometers were downloaded using ActiLife software (Actigraph LLC) for subsequent data reduction. Kinesoft software (version 2.0.94, Kinesoft Software, New Brunswick, Canada) was used in the extraction and processing of the physical activity data. Based on comparable studies,37,38 the recorded physical activity was classified by intensity into the following categories: Light physical activity (LPA) ≥ 1.5 to < 4 METs and moderate and vigorous activity (MVPA) as ≥ 4 METs. LPA and MVPA were also summed (denoted as LMVPA) to represent overall physical activity. The items of The Pictorial Scale of Perceived Competence and Social Acceptance for Young Children assessing the physical domain were scored on a scale of 1 to 4 for each item. Scores from the physical competence questions were summed (6 items total) to provide a raw score (out of 24).
Statistical Analyses Descriptive statistics were computed for raw scores of locomotor skills, object control skills; average minutes of physical activity per day at the following intensities: LPA, MVPA, and LMVPA; and perceptions of physical competence. The distributions of these variables were checked for normality, and none of the variables showed significant skew or kurtosis. In addition, independent t tests were performed to examine if there were any significant differences in locomotor and object control skills for males and females. The relationships between physical activity, perceptions of competence, and fundamental motor skills were examined using a mediation model. Mediation occurs when the relationship between a predictor variable and outcome variable can wholly, or in part, be explained by their relationship to a third variable.5 Four criterion must be met to establish mediation: 1) the predictor variable must be significantly related to the outcome variable, 2) the predictor variable must significantly predict the mediator, 3) the mediator must be related to the outcome variable, and 4) the relationship between the predictor variable and the outcome variable should be reduced when the mediator is included in the analysis.5 Results from this process describe the direct relationship between 2 variables (predictor and outcome) as well as an indirect relationship to a third variable (mediator). The literature suggests that perceptions of physical competence may mediate the relationship between motor skill proficiency and participation in physical activity; and the reverse pathway may also exist. The literature also suggests that these relationships may differ for type of motor skill (object control and locomotor skills). Therefore, the initial analyses were linear regressions to examine the direct relationship between locomotor and object control skills and physical activity. Firstly, with object control and locomotor skills as predictors of physical activity; and subsequently with physical activity as a predictor of object control
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skills and as a predictor or locomotor skills. Independent t-tests revealed no significant differences between males and females for motor skills and therefore neither model was adjusted for sex. However, given the age range of participants, models were adjusted for age in months. As suggested by Baron and Kenny,39 mediation was tested using a series of 3 regression models. The first regression equation predicts the outcome from the predictor, the second predicts the mediator from the predictor, and the third predicts the outcome from both the predictor and the mediator. All analyses were performed using SPSS 21 for Windows.40
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Results Descriptive statistics for all variables are reported in Table 1. On average, perceptions of physical competence were generally positive, physical activity levels were quite high and motor skills levels were in the midrange; with locomotor skill proficiency scores higher than object control skill scores. The minimum of the range for mean daily MVPA displayed in Table 1 revealed that all children accumulated more than the minimum 60 minutes of MVPA per day recommended by the Canadian Physical Activity guidelines.1 Results of the first regression analysis indicated that locomotor and object control skills accounted for 7.6% of the variance in MVPA [R2 = .076, F(2, 93) = 3.786, P = .026]; however the t-statistic tests revealed that object control skills (β = .281, P = .005), but not locomotor skills (β = .054, P = .585), significantly predicted MVPA. In the second set of analyses, MVPA accounted
for 10.4% of the variance in object control skills [R2 = .104, F(2, 112) = 4.476, P = .002]; but MVPA was not a significant predictor of locomotor skills [R2 = .036, F(2, 112) = 2.114, P = .126]. The results of these preliminary analyses were used to inform the specification of 2 mediation models. In the first model, object control skills were used to predict the outcome variable (minutes of MVPA) with perceptions of physical competence as a mediator (see Figure 1). The second model consisted of the same variables as model 1; however, MVPA was used to predict object control skills with perceptions as a mediator. For the first specified model, the unstandardized regression coefficient (B) for the prediction of MVPA from object control skills was 1.332 and statistically significant t(112) = 3.337, P = .001. The second step in the analysis, predicting the mediating variable (perceptions of competence) from the predictor (object control skills), was also significant B = 0.081, t(113) = 2.050, P = .043. The third regression analysis, predicting the outcome (MVPA) from both the mediating variable (perceptions of competence) and the predictor (object control skills) was also significant R2 = .096, P = .011; however the t-statistic tests revealed that only object control skills contributed significantly to the model [B = 1.347, t(111) = 3.307, P = .001]. As perceived physical competence did not predict MVPA in this analysis [B = –0.194, t(111) = –0.207, P = .837], the hypothesized mediational pathway (Figure 1) cannot be supported. The mediation effect in the second specified model was also not supported by the statistical tests. Although the unstandardized regression coefficient for the prediction of object control skills
Table 1 Descriptive Statistics for Motor Skills, Perceived Physical Competence, BMI, and Physical Activity Variable (range/units of measure)
Mean
SD
Min
Max
Locomotor skills (0–48)
26.3
7.0
10.0
42.0
Object control skills (0–48)
20.9
6.7
9.0
38.0
Perceptions of physical competence (6–24)
18.8
3.0
10.0
24.0
Light-intensity physical activity (min/day)
221.4
27.0
96.7
289.0
Moderate-to-vigorous physical activity (min/day)
135.3
29.9
65.6
213.9
Total physical activity* (min/day)
356.8
45.4
240.0
476.4
Body mass index percentile
45.4
27.5
3.77
99.6
* Total physical activity = Light-intensity + MVPA (LMVPA). Abbreviations: MVPA, moderate-to-vigorous physical activity; LMVPA, sum of light-intensity physical activity and MVPA.
Figure 1 — Hypothesized mediational relationship between object control skills, perceived physical competence, and physical activity. JPAH Vol. 12, No. 7, 2015
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from MVPA was significant [B = 0.068, t(112) = 3.337, P = .001]; the second regression model was not significant for the prediction of perceived competence from MVPA [B = 0.003, t(112) = 0.368, P = .714]. As this finding did not support the causal order of the specified model the third regression equation was not computed.
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Discussion This study examined whether perceived physical competence mediated the relationship between fundamental motor skill proficiency and physical activity levels among children in their first year of school. Two models were used to explore mediation, but neither model supported a causal sequence. When MVPA was the outcome (Figure 1), the direct path between object control skills and MVPA was significant and object control skills also predicted perceived physical competence when adjusted for age. However, perceived competence did not mediate the relationship between object control skills and MVPA. These findings indicate that MVPA is influenced directly by object controls skills, but object control skills do not indirectly influence MVPA through children’s perceptions of their physical competence. Similarly, MVPA significantly predicted object control skills; however, perceived competence did not mediate the relationship. These results contrasts the findings with adolescence3,4 and support the concept of developmental differences in the structure of the self-perception system.8,41 Changes in the self-perception system during childhood and adolescence include increased differentiation of self-perception subdomains, strengthening of the contribution of perceptions of competence to self-esteem, and changes in the cognitive processes used to evaluate competence.8 Young children tend to have unrealistically high perceptions of competence that overestimate their abilities because they are not able to differentiate their actual and real self-concept, take the perspective of others, nor engage in social comparisons.41 As a result their perceptions tend to stay high as they do not internalize information that would suggest they are not as competent as their peers. Older children and adolescents, on the other hand, use evidence such as peer comparisons, outcomes and feedback from significant others to inform their self-perceptions.41 They are also able to distinguish between subdomains of selfconcept (eg, scholastics, athletic, peer acceptance) in terms of importance and they can have a different sense of ‘self’ in different contexts.8 These developmental changes also allow older children and adolescents to engage in self-protection strategies such as downplaying the importance of a self-perception subdomain or withdrawing from participation in that domain.42,43 As Stodden and colleagues2 explain, older children and adolescents with lower motor proficiency tend to opt out of physical activity because they have a limited repertoire of skills to participate with, they know they are less competent than their peers and they don’t want reveal their lower proficiency in public contexts. Our results indicate that kindergarten children’s participation in physical activity is not yet influenced by their perceptions of physical competence. The children’s object control skills predicted engagement in physical activity as well as their perceptions of physical competence; but perceptions did not in turn mediate the relationship between motor proficiency and physical activity. However, while the relationship between object control skills and perceived competence was not strong, it was significant. This suggests that although the children were generally inaccurate in their self-appraisals as theory indicates;8,14 they may be starting to formulate more realistic opinions of their physical competence.
The bidirectional relationship between object control skills and physical activity suggests that motor skill development is both an outcome of, and a precursor for, physical activity. From infancy and throughout the developmental years, children participate in physical activities such as pushing up, crawling, walking, and running.44 These activities contribute to overall muscular strength and endurance as well as cardiorespiratory health and fitness.44 With sufficient strength and postural control, motor skills that have a flight phase such as jumping, skipping, and hopping become more realizable.45 Furthermore, as children become more mobile they increasingly explore expanded environments. This exploration stimulates neuromotor, perceptual, and cognitive abilities, which in turn promotes motor skill development.46 The strength of this reciprocal relationship increases during development; and evidence suggests that those who become more proficient tend to demonstrate higher levels of MVPA.2,47–49 Physical activity levels in this study were high. On average, these kindergarten children accumulated 135 minutes of MVPA per day (or 18% of their day). Fifty-eight percent of the children met the Canadian guidelines of 60-minutes of MVPA per day50 every day, 92% met the guideline on the 5 weekdays, and 95% on both weekend days. These levels were much higher than previously found for preschool aged children.19,20,50,51 Previous studies of Scottish and Australian preschool children (3 to 5 years) reported daily MVPA ranging between 3% and 13% (approximately 23 minutes per day) and 50% to 90% of the day in sedentary behavior.19,20,51 The participants in this study were not preschool children; rather they were in the first year of school (ie, kindergarten). Although most children (63%) were 5 years of age, they may indeed have a different physical activity pattern than described by the majority of literature that focuses on preschool aged children.19,20,52 The Temple et al study of 3- to 5-year-old children in family child care was conducted in the same province as the current study and showed much lower levels of accelerometer measured physical activity. Children accumulated approximately 2 minutes of MVPA per hour of wear time in the Temple et al study compared with 13.5 minutes per hour of wear time in this study. Recently, Colley et al53 reported that a nationally representative sample of Canadian 5-year-old children accumulated an average of 68 minutes of MVPA per day and that 14% met the Canadian guideline of 60 minutes of MVPA per day.53 It was not reported whether the 5-year-old children in the Colley et al study were in school or in preschool; however the data highlight that the children in this study were very active compared with Canadian 5-year-olds in general. The extent to which the school versus the preschool context influences physical activity patterns of 5-year-olds is an intriguing question for future research. For school-aged children, this study revealed higher level of MVPA compared with older Canadian children in general; but levels of MVPA comparable to older children in the same province (British Columbia). For Canadian children in general, Colley et al50 found that 6- to 10-year-old children accrued 58 minutes of MVPA per day, which are less than half of the levels found in this study. Whereas in British Columbia, more than 2 hours (124 minutes) of MVPA per day have been reported for 8- to 11-year-old children.54 Nettlefold and colleagues’ findings are much higher than those reported by Colley et al for older Canadian children but are still slightly lower than those reported in the current study. Given that only 7% of Canadian children and youth are presently meeting physical activity guidelines,50 the high levels of physical activity among the kindergarten children in our study were somewhat unexpected. It is possible that the physical activity levels of participants
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in this study may be a result of location. Southern Vancouver Island in British Columbia (the location of this study) has a mild and dry climate with more sunshine than most cities in Canada and very little snow in winter.55 In general, the province has some of the lowest rates of obesity in the Canada56 and levels of MVPA that are 10% higher than the national average.57 Additional research is needed to explain whether there is something unique about the physical activity patterns of children in the first year of school or if this finding was unique to our sample. Similar to previous research with 3- to 5-year-old19 and 7- to 11-year-old children47 it appears that object control skill proficiency, but not locomotor skill proficiency is associated with higher levels of MVPA.19,47 Although there is no definitive evidence why object control skills but not locomotor skills are related to MVPA, it has been suggested that object control skills are more closely related to activities that are moderate and/or vigorous in nature (ie, basketball or soccer).47 Barnett and colleagues found that both object controls skills measured in childhood47 as those measured in adolescence3 were significantly related to adolescent physical activity levels. The similar pattern in this study suggests that the importance of object controls skills manifests at a young age. What is unclear is why and how object control skills contribute to higher physical activity levels. It is likely that detailed examination of children’s participation in physical activities is needed, including the type and intensity of activity as well as the skills used in those activities. For young children, such as in this study, asking parents to complete a detailed physical activity log to accompany the accelerometer data would go some way to unpacking this relationship. A limitation of the current study was that 2 perceptions of physical competence questions pertained to locomotor skills but none portrayed object control skills. It is possible that there may have been a stronger relationship between actual and perceived competence if the type of skill directly assessed and the type of skill the children were asked to respond to in the pictorial scale were more closely related. Future research may benefit from broadening the scope of motor skills presented to the children when examining perceptions of physical competence. Furthermore, it should be noted that perceived competence was assessed following actual measurement of motor skill proficiency, which may have influenced the children’s responses. The findings of this study should also be interpreted with an eye to the variability among the scores for specific skills of the TGMD-2. For example, the run and the slide contributed 43% of the raw locomotor subtest score; whereas, the leap and the jump combined contributed only 23%. Similarly, over 60% of the object control subtest raw score came from the strike, kick, and catch; with only 11% contributed to the roll. Finally, the loss of participants between recruitment into the larger cohort and the accelerometer cohort and the small number for whom valid accelerometer data were available resulted in a decrease in our sample. It is possible that the families that consented were more positively predisposed to physical activity than families who did not agree to this component of the study. Further, the accelerometer wear time criterion was 600 minutes of wear time for 3 week days and 1 weekend day. This resulted in 43% attrition. The most common reasons reported by parents and guardians for not meeting the wear time criterions were forgetting to wear it and discomfort. However, as previously reported, there were no significant differences found in fundamental motor skill raw scores and perceptions of physical competence among accelerometer consented participants and nonconsented accelerometer participants, which lends strength to our findings.
Conclusion The findings from this study indicate that perceived physical competence does not mediate the relationship between fundamental motor skills and physical activity among children in kindergarten. Developmentally, 5-year-old children tend to be inaccurate in their self-appraisals because of immature cognitive processes. However, our findings do show a small but significant relationship between perceptions of competence and fundamental motor skill proficiency; suggesting the emergence of more realistic assessment of performance. Although perceptions of competence were not mediating the relationship, object control skills did directly predict levels of physical activity and vice versa. The interplay between motor skills and physical activity at this age is perhaps unique, with physical activity both enabling motor skill development and being the product of enhanced motor proficiency. This differs somewhat from the relationship between object control skills and physical activity among older children and adolescents; where perceived competence mediates these relationships and children/youth are opting out of physical activity because they perceive that they lack the skills. Follow-up research is needed to identify when during the elementary school years self-perceptions of physical activity start to impact children’s physical activity choices. This study suggests that kindergarten is an ideal time to enhance both motor skill proficiency and physical activity levels, before negative self-perceptions affect children’s choices.
References 1. Active Healthy Kids Canada. Are we driving our kids to unhealthy habits? The 2013 Active Healthy Kids Canada report card on physical activity for children and youth. Toronto, ON; 2013. 2. Stodden DF, Goodway JD, Langendorfer SJ, et al. A developmental perspective on the role of motor skill competence in physical activity: an emergent relationship. Quest. 2008;60(2):290–306. doi:10.1080/0 0336297.2008.10483582 3. Barnett LM, Morgan PJ, van Beurden E, Beard JR. Perceived sport competence mediates the relationship between childhood motor skill proficiency and adolescent physical activity and fitness: a longitudinal assessment. Int J Behav Nutr Phys Act. 2008;5:1–12. PubMed doi:10.1186/1479-5868-5-40 4. Barnett LM, Morgan PJ, Van Beurden E, Ball K, Lubans DR. A reverse pathway? Actual and perceived skill proficiency and physical activity. Med Sci Sports Exerc. 2011;43(5):898–904. PubMed doi:10.1249/ MSS.0b013e3181fdfadd 5. Field A. Discovering Statistics Using IBM SPSS Statistics. 4th ed. Thousand Oaks, Ca: SAGE Publications Ltd; 2013. 6. Jacobs JE, Lanza S, Osgood DW, Eccles JS, Wigfield A. Changes in children’s self-competence and values: gender and domain differences across grades one through twelve. Child Dev. 2002;73(2):509. PubMed doi:10.1111/1467-8624.00421 7. Rodrigues LP, Saraiva L, Gabbard C. Development and construct validation of an inventory for assessing the home environment for motor development. Res Q Exerc Sport. 2005;76:140–148. PubMed doi:10.1080/02701367.2005.10599276 8. Horn T. Developmental perspectives on self-perceptions in children and adolescents. In: Weiss MR, ed. Developmental sport and exercise psychology: a lifespan perspective. Morgantown, WV: Fitness Information Technology; 2004:101–143. 9. Breslin G, Murphy M, McKee D, Delaney B, Dempster M. The effect of teachers trained in a fundamental movement skills programme on children’s self-perceptions and motor competence. Eur Phys Educ Rev. 2012;18(1):114–126. doi:10.1177/1356336X11430657
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10. LeGear M, Greyling L, Sloan E, et al. A window of opportunity? Motor skills and perceptions of competence of children in kindergarten. Int J Behav Nutr Phys Act. 2012;9:29. PubMed 11. Piek JP, Baynam GB, Barrett NC. The relationship between fine and gross motor ability, self-perceptions and self-worth in children and adolescents. Hum Mov Sci. 2006;25:65–75. PubMed doi:10.1016/j. humov.2005.10.011 12. Robinson L. The relationship between perceived physical competence and fundamental motor skills in preschool children. Child Care Health Dev. 2010;37(4):589–596. PubMed doi:10.1111/j.13652214.2010.01187.x 13. Ulrich DA. Test of Gross Motor Development (TGMD-2). 2nd ed. Austin, TX: PRO-ED, Inc.; 2000. 14. Harter S, Pike R. The pictorial scale of perceived competence and social acceptance for young children. Child Dev. 1984;55(6):1969– 1982. PubMed doi:10.2307/1129772 15. Goodway J, Rudisill ME. Perceived physical competence and actual motor skill competence of African American preschool children. Adap Phys Act Qu. 1997;14:314–326. 16. McBee M. Modeling outcomes with floor or ceiling effects: an introduction to the Tobit Model. Gift Child Q. 2010;54(4):314–320. doi:10.1177/0016986210379095 17. Barnett LM, Hinkley T, Okely AD, Salmon J. Child, family and environmental correlates of children’s motor skills proficiency. J Sci Med Sport. 2013;16(4):332–336. PubMed doi:10.1016/j.jsams.2012.08.011 18. Burgi F, Meyer U, Granacher U, et al. Relationship of physical activity with motor skills, aerobic fitness and body fat in preschool children: a cross-sectional and longitudinal study (Ballabeina). Int J Obes. 2011;35(7):937–944. PubMed doi:10.1038/ijo.2011.54 19. Cliff DP, Okely AD, Smith LM, McKeen K. Relationships between fundamental movement skills and objectively measured physical activity in preschool children. Pediatr Exerc Sci. 2009;21:436–449. PubMed 20. Fisher A, Reilly JJ, Montgomery C, et al. Fundamental movement skills and habitual physical activity in young children. Med Sci Sports Exerc. 2005;37:684–688. PubMed doi:10.1249/01. MSS.0000159138.48107.7D 21. Williams HG, Pfeiffer KA, O’Neill JR, et al. Motor skill performance and physical activity in preschool children. J Obes. 2008;16:1421– 1426. PubMed doi:10.1038/oby.2008.214 22. Sallis JF, Prochaska JJ, Taylor WC. A review of correlates of physical activity of children and adolescents. Med Sci Sports Exerc. 2000;32(5):963–975. PubMed doi:10.1097/00005768-20000500000014 23. Barnett LM, Cliff K, Morgan PJ, van Beurden E. Adolescents’ perception of the relationship between movement skills, physical activity and sport. Eur Phys Educ Rev. 2013;19(2):271–285. doi:10.1177/1356336X13486061 24. Stein C, Fisher L, Berkey C, Colditz G. Adolescent physical activity and perceived competence: does change in activity level impact self-perception? J Adolesc Health. 2007;40(5):462–468. PubMed doi:10.1016/j.jadohealth.2006.11.147 25. Kahn JA, Huang B, Gillman MW, et al. Patterns and determinants of physical activity in U.S. adolescents. J Adolesc Health. 2008;42:369– 377. PubMed doi:10.1016/j.jadohealth.2007.11.143 26. Crocker PRE, Eklund RC, Kowalski KC. Children’s physical activity and physical self-perceptions. J Sports Sci. 2000;18(6):383–394. PubMed doi:10.1080/02640410050074313 27. Kershaw P, Irwin L, Trafford K, Hertzman C. The British Columbia atlas of child development. Georgetown, ON: Human Early Learning Partnership; 2005. 28. The Human Early Learning Partnership. EDI Data tables. 2011. 29. Eston RG, Rowlands AV, Ingledew DK. Validity of heart rate, pedometry, and accelerometry for predicting the energy cost of children’s activities. J Appl Physiol. 1998;84:362–371. PubMed 30. Reilly JJ, Kelly LA, Montgomery C, et al. Validation of Actigraph accelerometer estimates of total energy expenditure in
young children. Int J Pediatr Obes. 2006;1(3):161–167. PubMed doi:10.1080/17477160600845051 31. Puyau MR, Adolph AL, Firoz AV, Butte NF. Validation and calibration of activity monitors in children. Obes Res. 2002;10(3):150–7. PubMed 32. Reilly JJ, Penpraze V, Hislop J, Davies G, Grant S, Paton JY. Objective measurement of physical activity and sedentary behaviour: review with new data. Arch Dis Child. 2008;93(6):614–619. PubMed doi:10.1136/ adc.2007.133272 33. Trost SG, McIver KL, Pate R. Conducting accelerometerbased activity assessments in field-based research. Med Sci Sports Exerc. 2005;37(11):S531–S543. PubMed doi:10.1249/01. mss.0000185657.86065.98 34. Mei Z, Grummer-Strawn LM, Pietrobelli A, Goulding A, Goran MI, Dietz WH. Validity of body mass index compared with other bodycomposition screening indexes for the assessment of body fatness in children and adolescents. Am J Clin Nutr. 2002;75(6):978–85. PubMed 35. Centers for Disease and Prevention. Children’s BMI Tool for Schools—Assessing Your Weight: Children’s BMI Tool for Schools. 2010; http://www.cdc.gov/healthyweight/assessing/bmi/childrens_ bmi/tool_for_schools.html. Accessed March, 2, 2014. 36. Baumgartner TA, Strong CH, Hensley LD. Conducting and reading research in health and human performance. New York, NY: McGraw Hill; 2002. 37. Trost SG, Loprinzi PD, Moore R, Pfeiffer KA. Comparison of accelerometer cut points for predicting activity intensity in youth. Med Sci Sports Exerc. 2011;43(7):1360–1368. PubMed doi:10.1249/ MSS.0b013e318206476e 38. Evenson KR, Catellier DJ, Gill K, Ondrak KS, McMurray RG. Calibration of two objective measures of physical activity for children. J Sports Sci. 2008;26(14):1557–1565. PubMed doi:10.1080/02640410802334196 39. Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol. 1986;54(6):1173–1182. PubMed doi:10.1037/0022-3514.51.6.1173 40. IBM SPSS Statistics [computer program]. Version 19. Somers, NY2010. 41. Harter S. The construction of the self: developmental and sociocultural foundations. 2nd ed. New York: The Guilford Press; 2012. 42. Ebbeck V, Stuart ME. Who determines what’s important? Perceptions of competence and importance as predictors of self-esteem in youth football players. Pediatr Exerc Sci. 1993;5:253–262. 43. Shapiro DR, Moffett A, Lieberman L, Drummer GM. Domain-specific ratings of importance and global self-worth of children with visual impairments. J Vis Impair Blind. 2008;102(4):232–244. 44. Strong WB, Malina RM, Blimkie CJR, et al. Evidence based physical activity for school-age youth. J Pediatr. 2005;146(6):732–737. PubMed doi:10.1016/j.jpeds.2005.01.055 45. Payne GV, Issacs LD. Human motor development. A lifespan approach. 7th ed. Boston: McGraw Hill; 2008. 46. Berger SE, Adolph KE. Learning and development in infant locomotion. Prog Brain Res. 2007;164:237–255. PubMed doi:10.1016/ S0079-6123(07)64013-8 47. Barnett LM, van Beurden E, Morgan PJ, Brooks LO, Beard JR. Childhood motor skill proficiency as a predictor of adolescent physical activity. J Adolesc Health. 2008a;44:252–259. PubMed doi:10.1016/j. jadohealth.2008.07.004 48. Okely AD, Booth ML, Patterson JW. Relationship of physical activity to fundamental movement skills among adolescents. Med Sci Sports Exerc. 2001;33(11):1899–1904. PubMed doi:10.1097/00005768200111000-00015 49. Barnett LM, van Beurden E, Morgan PJ, Brooks LO, Beard JR. Does childhood motor skill proficiency predict adolescent fitness? Med Sci Sports Exerc. 2008b;40:2137–2144. PubMed doi:10.1249/ MSS.0b013e31818160d3 50. Colley R, Garriguet D, Janssen I, Craig CL, Clarke J, Tremblay M. Physical activity of Canadian children and youth: accelerometer
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54. Nettlefold L, McKay HA, Naylor P-J, Bredin SSD, Warburton DER. The relationship between objectively measured physical activity, sedentary time, and vascular health in children. Am J Hypertens. 2012;25(8):914–919. PubMed doi:10.1038/ajh.2012.68 55. Carson V, Spence JC, Cutumisu N, Boule N, Edwards J. Seasonal variation in physical activity among preschool children in a northern canadian city. Res Q Exerc Sport. 2010;81(4):392–399. PubMed doi: 10.1080/02701367.2010.10599699 56. Statistics Canada. Health Trends—National Rates of Obesity. 2013; http://www.statcan.gc.ca/start-debut-eng.html, 2014. 57. Statistics Canada. Physical Activity During Leisure Time, 2013. 2013; www.statcan.gc.ca/pub.82-625-x/2014001/article/14024-eng.htm, 2014.
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results from the 2007-2009 Canadian health measure survey. Vol 22. Statistics Canada; 2011:1–9. 51. Reilly JJ. Low levels of objectively measured physical activity in preschoolers in child care. Med Sci Sports Exerc. 2010;42(3):502–507. PubMed doi:10.1249/MSS.0b013e3181cea100 52. Temple VA, Naylor P-J, Rhodes RE, Higgins JW. Physical activity of children in family care. Appl Physiol Nutr Metab. 2009;34:794–798. PubMed doi:10.1139/H09-061 53. Colley RC, Garriguet D, Adamo KB, Janssen I, Timmons BW, Tremblay MS. Physical activity and sedentary behavior during the early years in Canada: a cross-sectional study. Int J Behav Nutr Phys Act. 2013;10(54). PubMed
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ORIGINAL RESEARCH
Do Perceptions of Competence Mediate The Relationship Between Fundamental Motor Skill Proficiency and Physical Activity Levels of Children in Kindergarten? Jeff R. Crane, Patti J. Naylor, Ryan Cook, and Viviene A. Temple Background: Perceptions of competence mediate the relationship between motor skill proficiency and physical activity among older children and adolescents. This study examined kindergarten children’s perceptions of physical competence as a mediator of the relationship between motor skill proficiency as a predictor variable and physical activity levels as the outcome variable; and also with physical activity as a predictor and motor skill proficiency as the outcome. Methods: Participants were 116 children (mean age = 5 years 7 months, 58% boys) from 10 schools. Motor skills were measured using the Test of Gross Motor Development-2 and physical activity was monitored through accelerometry. Perceptions of physical competence were measured using The Pictorial Scale of Perceived Competence and Social Acceptance for Young Children, and the relationships between these variables were examined using a model of mediation. Results: The direct path between object control skills and moderate-vigorous physical activity (MVPA) was significant and object control skills predicted perceived physical competence. However, perceived competence did not mediate the relationship between object control skills and MVPA. Conclusion: The significant relationship between motor proficiency and perceptions of competence did not in turn influence kindergarten children’s participation in physical activity. These findings support concepts of developmental differences in the structure of the self-perception system. Keywords: early childhood, motor development, accelerometry, perceived ability, mediation
The 2013 Active Healthy Kids Canada Report Card on Physical Activity for Children and Youth1 points to the need for most Canadian children and youth to make important changes to their physical activity patterns, including increasing active play and participation in organized sport. Knowing how to help children and youth make those important changes remains unclear. Stodden and colleagues2 created a developmental model to explain individuallevel engagement and disengagement in physical activity during early, middle, and late childhood. These authors posit that both higher levels of motor skill proficiency and perceptions of physical competence bring about a positive spiral of engagement whereas “. . . children and adolescents who perceive themselves as having low motor skill competence, and actually demonstrate low levels of motor skill competence, will be drawn into a negative spiral of disengagement”.2, p.296 Emerging evidence supports this and suggests that perceptions of physical competence may play a mediating role between motor skill proficiency and physical activity.3,4 Mediation occurs when the relationship between a predictor variable and an outcome variable is influenced by an intermediary variable, or mediator.5 Barnett and colleagues3 found that perceptions of sport competence mediated the relationship between childhood object control skills (predictor) and physical activity levels (outcome) in adolescence. Their mediation model accounted for 18% of the variance in physical activity. In a parallel study, Barnett and others found that perceptions of sport competence mediated the relationship between adolescent object control skill proficiency and engagement in moderate-vigorous physical activity (MVPA) in both directions, that is, with physical
The authors are with the School of Exercise Science, Physical and Health Education, University of Victoria, Victoria, BC, Canada. Crane (jeffrcra@ uvic.ca) is corresponding author. 954
activity as the predictor or the outcome.4 These authors also found that perceptions of sport competence mediated the relationship between locomotor skill proficiency and physical activity, but only when locomotor skill proficiency was the outcome variable. Whether perceptions of competence mediate the relationship between fundamental motor skill proficiency and participation in physical activity, or the reverse, has not been examined among young children. Separately however, the relationship between perceptions of physical competence and motor skill proficiency and the relationship between motor skill proficiency and physical activity have been examined in early childhood to some extent. Children’s beliefs about their physical competence tend to be unrealistically high during early childhood, but typically decline during the elementary school years as they begin to compare themselves with their peers and as they become more sensitive to success and failure experiences.6–8 During early childhood, the relationship between perceptions of physical competence and measured motor proficiency is generally weak to moderate in strength.9–12 It is unclear however, whether the relationship differs for type of motor skill (ie, object control and locomotor skills). Among adolescents, object control skills are more strongly related to perceptions of physical competence than locomotor skills,3 however the picture is less clear for young children. Both LeGear et al10 and Robinson12 used the Test of Gross Motor Development–213 and the Pictorial Scale of Perceived Competence and Acceptance for Young Children14 to assess the relationships between object control skills, locomotor skills, and perceptions of physical competence among 4- and 5-year-old children. LeGear and colleagues found stronger correlations between perceived competence and locomotor skills (r = .37, P < .01) than between perceived competence and object control skills (r = .14, P < .05); whereas the strength of the relationship for each type of skill with perceptions was very similar in Robinson’s study (locomotor, r = .434, P < .01; object control, r = .435, P < .01). In contrast to those 2 studies, Goodway and
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Rudisill15 did not find significant relationships between perceptions of physical competence and locomotor skills (r = .03, P = .82) or object-control skills (r = .18, P = .18) among 4-year-old children who were identified as at risk for becoming educationally disadvantaged and/or developmentally delayed. It was notable that the children’s raw object control skill scores in Goodway and Rudisill’s study were particularly low (mean object control skill scores: boys = 3.9 and girls = 2.3). This ‘floor effect’ can censor the data16 and may in part explain the lack of relationship. Significant relationships between motor skill proficiency and physical activity levels have been consistently observed among young children.17–21 Among 4-year-olds, Williams and colleagues21 found a significant relationship between motor skills scores and MVPA (r = .33) and vigorous physical activity (VPA; r = .41). Similarly, Cliff et al19 found a significant relationship between overall motor skill proficiency and VPA (r = .46) among 3- to 5-year-old boys, but not among preschool girls. However, Barnett et al17 found object control skills accounted for 32% of the controlled variance in unstructured physical activity as well as percentage of time spent in moderate to vigorous physical activities. Cliff et al19 also reported that object control skills were significantly related to the proportion of time boys spent in moderate-intensity physical activity (MPA) and in MVPA (r = .52 and r = .48, respectively). While Fisher and colleagues20 did not find any sex-based differences in the association between accelerometer measured MVPA and motor skill scores among Scottish preschoolers; these researchers did find a weak association between total motor skill score and the proportion of monitored time spent in MVPA (r = .18, P < .001) for the sample as a whole. Significant positive relationships have also been noted between accelerometer measured physical activity and more novel, and perhaps more integrated, measures of motor skill proficiency among 5-year-old preschool children in Switzerland.18 The partial correlation coefficient between MPA and time to complete an obstacle course was .15 (P = .016) and between MPA and dynamic balance assessed via walking on a balance beam was .22 (P = .001). Burgi and colleagues18 also found that higher physical activity was associated with beneficial changes in motor skills 9 months later. These authors concluded that physical activity may be facilitating motor skills development among preschool aged children. Despite some evidence and theory that suggests inflated and unrealistic perceptions of physical competence in early elementary years,8,14,15 other evidence suggests there is a relationship between actual and perceived abilities among 4- and 5-year-old children.10,12 In addition, significant relationships between physical activity levels and motor skill proficiency among young children have been shown;19–21 and this relationship is likely bidirectional.2,18 By adolescence, perceptions of physical competence are consistent predictors of physical activity levels3,22–26 and these perceptions mediate the relationship between motor skill proficiency and physical activity.3 What is unclear from the extant literature is when these perceptions begin to influence physical activity participation and when perceived competence starts to mediate the relationship. Emerging evidence suggests that among young children, actual and perceived competence are related and that motor skill proficiency is related to participation in physical activity. In keeping with these thoughts, the aim of this study was to examine whether the mediating relationship was in effect among young elementary school children. Specifically, we examined kindergarten children’s perceptions of physical competence as a mediator of the relationship between motor skill proficiency as a predictor variable and physical activity levels as the outcome variable; and also with physical activity as a predictor and motor skill proficiency as the outcome.
Methods A cross-sectional design was used to examine the relationships between motor skill proficiency, physical activity levels, and perceptions of physical competence among kindergarten children. Children were eligible to participate if they were attending kindergarten in 1 of 10 consenting schools in 2 school districts in British Columbia, Canada during the 2010–2011, 2011–2012, or 2012–2013 school years. The rate of physical health and well-being vulnerability, as measured by the Early Development Instrument (EDI)27 were 13% and 8% in the 2 school districts compared with 13.5% provincially.28 The EDI is completed by kindergarten teachers and provides a measure of school readiness. Vulnerability in the Physical Health and Well Being domain of the EDI is assessed by teachers’ perceptions of the children’s fine and gross motor development, energy level, readiness for school, washroom independence, and established handedness. Data collection from each kindergarten cohort took place between the months of December to April where the average temperatures ranged between 4°C–10°C.
Participants The University Human Research Ethics Board and the school district granted approval for this study. A 2-level consent process was implemented. Parents/guardians could consent to the at-school portion of the study that involved motor skill and perceptions of physical competence assessment. In addition, parents/guardians could allow their child to participate in the physical activity portion of the study that involved the use of accelerometry to measure levels of physical activity. Consent for the at-school portion of the study was obtained for 82% (n = 430) of eligible children. Consent to wear the accelerometer was provided for 206 of these 430 children. As accelerometer wear time did not meet the study criteria for 90 children, the final sample was n = 116 (mean age = 5 years 7 months, 58% boys). To examine the whether the 116 children were representative of the larger sample of 430, independent t tests were conducted to compare locomotor skills and object control skills raw scores as well as perceptions of physical competence raw scores. No significant differences were found between the 2 groups for locomotor raw scores F(1, 421) = 0.47, P = .496 or for object control raw scores F(1, 421) = 1.18, P = .277. Similarly, there were no statistical differences for perceptions of physical competence F(1, 425) = 0.14, P = .708.
Measures Fundamental motor skills (6 locomotor skills: run, jump, hop, slide, gallop, and leap; and 6 object control skills: throw, roll, kick, strike, catch, and dribble) were assessed using the Test of Gross Motor Development–2nd Edition [TGMD-2].13 The TGMD-2 is a criterion and norm-referenced test that is used to assess the motor skill development of children. Further, mean test-retest reliability scores for locomotor skills and object control skills have been reported as .88 and .89, respectively for children aged 3 to 5 years and .94 and .96 for children aged 6 to 8 years.13 Validity of the TGMD-2 was established based on skills selected that were deemed appropriate by content experts and results from factor analyses show the test has good construct validity. Physical activity levels were measured with the Actigraph GT1M accelerometer (ActiGraph, LLC, Fort Walton Beach, FL). The Actigraph accelerometer has been shown to be a valid indicator of energy expenditure and activity levels in children and youth.29–31
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The device is worn around the waist, positioned on the right hip above the iliac crest and is connected by an elastic strap. The biaxial accelerometer collects prefiltered data at a rate of 30 measurements per second (30Hz), which is then postfiltered into measurements known as epochs, which are then converted to a metabolic equivalent. Each accelerometer was initialized to begin recording physical activity data in 15-second epochs, which are recommended to capture the sporadic activity of children.32 Consistent with previous research33 the minimum wear time criteria to be considered a valid physical activity record was 10 hours per day for at least 4 days that included at least 3 weekdays and 1 weekend day. The Pictorial Scale of Perceived Competence and Social Acceptance for Young Children14 was used to assess perceptions of physical competence. The scale has demonstrated both acceptable reliability and validity for kindergarten children.14 The scale consists of 24 items subdivided into 4 subscales (6 statements each) that are: Cognitive Competence, Physical Competence, Peer Acceptance, and Maternal Acceptance. For the purposes of this study, only the perceptions of physical competence subscale was used. Each item in the subscale was presented in the form of bipolar statements that are accompanied by a picture for each statement; for example, 2 photos display a child climbing, which are followed by a statement describing the child’s ability (eg, ‘this girl is pretty good at climbing’ and ‘this girl isn’t very good at climbing’). The child is asked to choose which picture most closely represents them. Once the child selects a picture, a follow up question is asked to determine the degree of competence within the skill (ie, ‘Are you’; ‘really good at climbing’ or ‘pretty good’). Each item is scored on a 4-point scale, where a 4 indicates the highest degree of perceived competence and 1 the lowest. Height was determined using a SECA 214 Road Rod portable stadiometer and measured to the nearest tenth of a centimeter and weight was measured to the nearest tenth of a kilogram using a Taylor Lithium Electronic scale. Body Mass Index (BMI) was calculated using the formula weight in kilograms divided by height in meters squared34and classified using the child cut-offs from the Children’s BMI Tool for Schools provided by the Centers for Disease Control and Prevention.35
Procedures The accelerometer was placed on each child by a trained researcher on the first day of testing immediately after motor skills testing. An information package was sent home with each child to parents/ guardians requesting that the accelerometer to be worn for 7 days from when the child first woke up in the morning and throughout the day until he/she went to sleep, unless bathing or swimming. Motor skills along with height and weight were assessed during scheduled physical education classes in accordance with the testing procedure outlined in the TGMD-2 Examiner’s Manual.13 Each kindergarten class was divided into 4 small groups before entering the gymnasium with each group consisting of 3 to 5 children. Each child performed the skills at their station twice before moving onto the next station. Due to scheduling constraints (eg, physical education lessons ranged in duration from 30 to 60 minutes) data were collected by research team trained in administration of the TGMD-2 over multiple visits to each school. Consented children were digitally video-recorded performing 6 locomotor skills (run, jump, hop, slide, gallop, and leap) and 6 object control skills (throw, roll, kick, strike, catch, and dribble). Afterward, children were asked to remove their shoes and height (cm) and weight (kg) were recorded. The Pictorial Scale of Perceived Competence and
Social Acceptance for Young Children14 was administered by a trained researcher individually to each child in a quiet area following a motor skills testing session.
Data Treatment The behavioral components of object control skills and locomotor skills were scored dichotomously by the investigators from the digital video. The number of components completed correctly for each subtest (locomotor and object control skills) were summed to provide a raw score (out of 48). Interobserver reliability percent agreement was 86.3% and was established by 2 investigators who coded 15% of the digital videos. The Percent Agreement Method [Number of Agreements ÷ (Number of Agreements + Disagreements) × 100].36 Raw data from the accelerometers were downloaded using ActiLife software (Actigraph LLC) for subsequent data reduction. Kinesoft software (version 2.0.94, Kinesoft Software, New Brunswick, Canada) was used in the extraction and processing of the physical activity data. Based on comparable studies,37,38 the recorded physical activity was classified by intensity into the following categories: Light physical activity (LPA) ≥ 1.5 to < 4 METs and moderate and vigorous activity (MVPA) as ≥ 4 METs. LPA and MVPA were also summed (denoted as LMVPA) to represent overall physical activity. The items of The Pictorial Scale of Perceived Competence and Social Acceptance for Young Children assessing the physical domain were scored on a scale of 1 to 4 for each item. Scores from the physical competence questions were summed (6 items total) to provide a raw score (out of 24).
Statistical Analyses Descriptive statistics were computed for raw scores of locomotor skills, object control skills; average minutes of physical activity per day at the following intensities: LPA, MVPA, and LMVPA; and perceptions of physical competence. The distributions of these variables were checked for normality, and none of the variables showed significant skew or kurtosis. In addition, independent t tests were performed to examine if there were any significant differences in locomotor and object control skills for males and females. The relationships between physical activity, perceptions of competence, and fundamental motor skills were examined using a mediation model. Mediation occurs when the relationship between a predictor variable and outcome variable can wholly, or in part, be explained by their relationship to a third variable.5 Four criterion must be met to establish mediation: 1) the predictor variable must be significantly related to the outcome variable, 2) the predictor variable must significantly predict the mediator, 3) the mediator must be related to the outcome variable, and 4) the relationship between the predictor variable and the outcome variable should be reduced when the mediator is included in the analysis.5 Results from this process describe the direct relationship between 2 variables (predictor and outcome) as well as an indirect relationship to a third variable (mediator). The literature suggests that perceptions of physical competence may mediate the relationship between motor skill proficiency and participation in physical activity; and the reverse pathway may also exist. The literature also suggests that these relationships may differ for type of motor skill (object control and locomotor skills). Therefore, the initial analyses were linear regressions to examine the direct relationship between locomotor and object control skills and physical activity. Firstly, with object control and locomotor skills as predictors of physical activity; and subsequently with physical activity as a predictor of object control
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skills and as a predictor or locomotor skills. Independent t-tests revealed no significant differences between males and females for motor skills and therefore neither model was adjusted for sex. However, given the age range of participants, models were adjusted for age in months. As suggested by Baron and Kenny,39 mediation was tested using a series of 3 regression models. The first regression equation predicts the outcome from the predictor, the second predicts the mediator from the predictor, and the third predicts the outcome from both the predictor and the mediator. All analyses were performed using SPSS 21 for Windows.40
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Results Descriptive statistics for all variables are reported in Table 1. On average, perceptions of physical competence were generally positive, physical activity levels were quite high and motor skills levels were in the midrange; with locomotor skill proficiency scores higher than object control skill scores. The minimum of the range for mean daily MVPA displayed in Table 1 revealed that all children accumulated more than the minimum 60 minutes of MVPA per day recommended by the Canadian Physical Activity guidelines.1 Results of the first regression analysis indicated that locomotor and object control skills accounted for 7.6% of the variance in MVPA [R2 = .076, F(2, 93) = 3.786, P = .026]; however the t-statistic tests revealed that object control skills (β = .281, P = .005), but not locomotor skills (β = .054, P = .585), significantly predicted MVPA. In the second set of analyses, MVPA accounted
for 10.4% of the variance in object control skills [R2 = .104, F(2, 112) = 4.476, P = .002]; but MVPA was not a significant predictor of locomotor skills [R2 = .036, F(2, 112) = 2.114, P = .126]. The results of these preliminary analyses were used to inform the specification of 2 mediation models. In the first model, object control skills were used to predict the outcome variable (minutes of MVPA) with perceptions of physical competence as a mediator (see Figure 1). The second model consisted of the same variables as model 1; however, MVPA was used to predict object control skills with perceptions as a mediator. For the first specified model, the unstandardized regression coefficient (B) for the prediction of MVPA from object control skills was 1.332 and statistically significant t(112) = 3.337, P = .001. The second step in the analysis, predicting the mediating variable (perceptions of competence) from the predictor (object control skills), was also significant B = 0.081, t(113) = 2.050, P = .043. The third regression analysis, predicting the outcome (MVPA) from both the mediating variable (perceptions of competence) and the predictor (object control skills) was also significant R2 = .096, P = .011; however the t-statistic tests revealed that only object control skills contributed significantly to the model [B = 1.347, t(111) = 3.307, P = .001]. As perceived physical competence did not predict MVPA in this analysis [B = –0.194, t(111) = –0.207, P = .837], the hypothesized mediational pathway (Figure 1) cannot be supported. The mediation effect in the second specified model was also not supported by the statistical tests. Although the unstandardized regression coefficient for the prediction of object control skills
Table 1 Descriptive Statistics for Motor Skills, Perceived Physical Competence, BMI, and Physical Activity Variable (range/units of measure)
Mean
SD
Min
Max
Locomotor skills (0–48)
26.3
7.0
10.0
42.0
Object control skills (0–48)
20.9
6.7
9.0
38.0
Perceptions of physical competence (6–24)
18.8
3.0
10.0
24.0
Light-intensity physical activity (min/day)
221.4
27.0
96.7
289.0
Moderate-to-vigorous physical activity (min/day)
135.3
29.9
65.6
213.9
Total physical activity* (min/day)
356.8
45.4
240.0
476.4
Body mass index percentile
45.4
27.5
3.77
99.6
* Total physical activity = Light-intensity + MVPA (LMVPA). Abbreviations: MVPA, moderate-to-vigorous physical activity; LMVPA, sum of light-intensity physical activity and MVPA.
Figure 1 — Hypothesized mediational relationship between object control skills, perceived physical competence, and physical activity. JPAH Vol. 12, No. 7, 2015
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from MVPA was significant [B = 0.068, t(112) = 3.337, P = .001]; the second regression model was not significant for the prediction of perceived competence from MVPA [B = 0.003, t(112) = 0.368, P = .714]. As this finding did not support the causal order of the specified model the third regression equation was not computed.
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Discussion This study examined whether perceived physical competence mediated the relationship between fundamental motor skill proficiency and physical activity levels among children in their first year of school. Two models were used to explore mediation, but neither model supported a causal sequence. When MVPA was the outcome (Figure 1), the direct path between object control skills and MVPA was significant and object control skills also predicted perceived physical competence when adjusted for age. However, perceived competence did not mediate the relationship between object control skills and MVPA. These findings indicate that MVPA is influenced directly by object controls skills, but object control skills do not indirectly influence MVPA through children’s perceptions of their physical competence. Similarly, MVPA significantly predicted object control skills; however, perceived competence did not mediate the relationship. These results contrasts the findings with adolescence3,4 and support the concept of developmental differences in the structure of the self-perception system.8,41 Changes in the self-perception system during childhood and adolescence include increased differentiation of self-perception subdomains, strengthening of the contribution of perceptions of competence to self-esteem, and changes in the cognitive processes used to evaluate competence.8 Young children tend to have unrealistically high perceptions of competence that overestimate their abilities because they are not able to differentiate their actual and real self-concept, take the perspective of others, nor engage in social comparisons.41 As a result their perceptions tend to stay high as they do not internalize information that would suggest they are not as competent as their peers. Older children and adolescents, on the other hand, use evidence such as peer comparisons, outcomes and feedback from significant others to inform their self-perceptions.41 They are also able to distinguish between subdomains of selfconcept (eg, scholastics, athletic, peer acceptance) in terms of importance and they can have a different sense of ‘self’ in different contexts.8 These developmental changes also allow older children and adolescents to engage in self-protection strategies such as downplaying the importance of a self-perception subdomain or withdrawing from participation in that domain.42,43 As Stodden and colleagues2 explain, older children and adolescents with lower motor proficiency tend to opt out of physical activity because they have a limited repertoire of skills to participate with, they know they are less competent than their peers and they don’t want reveal their lower proficiency in public contexts. Our results indicate that kindergarten children’s participation in physical activity is not yet influenced by their perceptions of physical competence. The children’s object control skills predicted engagement in physical activity as well as their perceptions of physical competence; but perceptions did not in turn mediate the relationship between motor proficiency and physical activity. However, while the relationship between object control skills and perceived competence was not strong, it was significant. This suggests that although the children were generally inaccurate in their self-appraisals as theory indicates;8,14 they may be starting to formulate more realistic opinions of their physical competence.
The bidirectional relationship between object control skills and physical activity suggests that motor skill development is both an outcome of, and a precursor for, physical activity. From infancy and throughout the developmental years, children participate in physical activities such as pushing up, crawling, walking, and running.44 These activities contribute to overall muscular strength and endurance as well as cardiorespiratory health and fitness.44 With sufficient strength and postural control, motor skills that have a flight phase such as jumping, skipping, and hopping become more realizable.45 Furthermore, as children become more mobile they increasingly explore expanded environments. This exploration stimulates neuromotor, perceptual, and cognitive abilities, which in turn promotes motor skill development.46 The strength of this reciprocal relationship increases during development; and evidence suggests that those who become more proficient tend to demonstrate higher levels of MVPA.2,47–49 Physical activity levels in this study were high. On average, these kindergarten children accumulated 135 minutes of MVPA per day (or 18% of their day). Fifty-eight percent of the children met the Canadian guidelines of 60-minutes of MVPA per day50 every day, 92% met the guideline on the 5 weekdays, and 95% on both weekend days. These levels were much higher than previously found for preschool aged children.19,20,50,51 Previous studies of Scottish and Australian preschool children (3 to 5 years) reported daily MVPA ranging between 3% and 13% (approximately 23 minutes per day) and 50% to 90% of the day in sedentary behavior.19,20,51 The participants in this study were not preschool children; rather they were in the first year of school (ie, kindergarten). Although most children (63%) were 5 years of age, they may indeed have a different physical activity pattern than described by the majority of literature that focuses on preschool aged children.19,20,52 The Temple et al study of 3- to 5-year-old children in family child care was conducted in the same province as the current study and showed much lower levels of accelerometer measured physical activity. Children accumulated approximately 2 minutes of MVPA per hour of wear time in the Temple et al study compared with 13.5 minutes per hour of wear time in this study. Recently, Colley et al53 reported that a nationally representative sample of Canadian 5-year-old children accumulated an average of 68 minutes of MVPA per day and that 14% met the Canadian guideline of 60 minutes of MVPA per day.53 It was not reported whether the 5-year-old children in the Colley et al study were in school or in preschool; however the data highlight that the children in this study were very active compared with Canadian 5-year-olds in general. The extent to which the school versus the preschool context influences physical activity patterns of 5-year-olds is an intriguing question for future research. For school-aged children, this study revealed higher level of MVPA compared with older Canadian children in general; but levels of MVPA comparable to older children in the same province (British Columbia). For Canadian children in general, Colley et al50 found that 6- to 10-year-old children accrued 58 minutes of MVPA per day, which are less than half of the levels found in this study. Whereas in British Columbia, more than 2 hours (124 minutes) of MVPA per day have been reported for 8- to 11-year-old children.54 Nettlefold and colleagues’ findings are much higher than those reported by Colley et al for older Canadian children but are still slightly lower than those reported in the current study. Given that only 7% of Canadian children and youth are presently meeting physical activity guidelines,50 the high levels of physical activity among the kindergarten children in our study were somewhat unexpected. It is possible that the physical activity levels of participants
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in this study may be a result of location. Southern Vancouver Island in British Columbia (the location of this study) has a mild and dry climate with more sunshine than most cities in Canada and very little snow in winter.55 In general, the province has some of the lowest rates of obesity in the Canada56 and levels of MVPA that are 10% higher than the national average.57 Additional research is needed to explain whether there is something unique about the physical activity patterns of children in the first year of school or if this finding was unique to our sample. Similar to previous research with 3- to 5-year-old19 and 7- to 11-year-old children47 it appears that object control skill proficiency, but not locomotor skill proficiency is associated with higher levels of MVPA.19,47 Although there is no definitive evidence why object control skills but not locomotor skills are related to MVPA, it has been suggested that object control skills are more closely related to activities that are moderate and/or vigorous in nature (ie, basketball or soccer).47 Barnett and colleagues found that both object controls skills measured in childhood47 as those measured in adolescence3 were significantly related to adolescent physical activity levels. The similar pattern in this study suggests that the importance of object controls skills manifests at a young age. What is unclear is why and how object control skills contribute to higher physical activity levels. It is likely that detailed examination of children’s participation in physical activities is needed, including the type and intensity of activity as well as the skills used in those activities. For young children, such as in this study, asking parents to complete a detailed physical activity log to accompany the accelerometer data would go some way to unpacking this relationship. A limitation of the current study was that 2 perceptions of physical competence questions pertained to locomotor skills but none portrayed object control skills. It is possible that there may have been a stronger relationship between actual and perceived competence if the type of skill directly assessed and the type of skill the children were asked to respond to in the pictorial scale were more closely related. Future research may benefit from broadening the scope of motor skills presented to the children when examining perceptions of physical competence. Furthermore, it should be noted that perceived competence was assessed following actual measurement of motor skill proficiency, which may have influenced the children’s responses. The findings of this study should also be interpreted with an eye to the variability among the scores for specific skills of the TGMD-2. For example, the run and the slide contributed 43% of the raw locomotor subtest score; whereas, the leap and the jump combined contributed only 23%. Similarly, over 60% of the object control subtest raw score came from the strike, kick, and catch; with only 11% contributed to the roll. Finally, the loss of participants between recruitment into the larger cohort and the accelerometer cohort and the small number for whom valid accelerometer data were available resulted in a decrease in our sample. It is possible that the families that consented were more positively predisposed to physical activity than families who did not agree to this component of the study. Further, the accelerometer wear time criterion was 600 minutes of wear time for 3 week days and 1 weekend day. This resulted in 43% attrition. The most common reasons reported by parents and guardians for not meeting the wear time criterions were forgetting to wear it and discomfort. However, as previously reported, there were no significant differences found in fundamental motor skill raw scores and perceptions of physical competence among accelerometer consented participants and nonconsented accelerometer participants, which lends strength to our findings.
Conclusion The findings from this study indicate that perceived physical competence does not mediate the relationship between fundamental motor skills and physical activity among children in kindergarten. Developmentally, 5-year-old children tend to be inaccurate in their self-appraisals because of immature cognitive processes. However, our findings do show a small but significant relationship between perceptions of competence and fundamental motor skill proficiency; suggesting the emergence of more realistic assessment of performance. Although perceptions of competence were not mediating the relationship, object control skills did directly predict levels of physical activity and vice versa. The interplay between motor skills and physical activity at this age is perhaps unique, with physical activity both enabling motor skill development and being the product of enhanced motor proficiency. This differs somewhat from the relationship between object control skills and physical activity among older children and adolescents; where perceived competence mediates these relationships and children/youth are opting out of physical activity because they perceive that they lack the skills. Follow-up research is needed to identify when during the elementary school years self-perceptions of physical activity start to impact children’s physical activity choices. This study suggests that kindergarten is an ideal time to enhance both motor skill proficiency and physical activity levels, before negative self-perceptions affect children’s choices.
References 1. Active Healthy Kids Canada. Are we driving our kids to unhealthy habits? The 2013 Active Healthy Kids Canada report card on physical activity for children and youth. Toronto, ON; 2013. 2. Stodden DF, Goodway JD, Langendorfer SJ, et al. A developmental perspective on the role of motor skill competence in physical activity: an emergent relationship. Quest. 2008;60(2):290–306. doi:10.1080/0 0336297.2008.10483582 3. Barnett LM, Morgan PJ, van Beurden E, Beard JR. Perceived sport competence mediates the relationship between childhood motor skill proficiency and adolescent physical activity and fitness: a longitudinal assessment. Int J Behav Nutr Phys Act. 2008;5:1–12. PubMed doi:10.1186/1479-5868-5-40 4. Barnett LM, Morgan PJ, Van Beurden E, Ball K, Lubans DR. A reverse pathway? Actual and perceived skill proficiency and physical activity. Med Sci Sports Exerc. 2011;43(5):898–904. PubMed doi:10.1249/ MSS.0b013e3181fdfadd 5. Field A. Discovering Statistics Using IBM SPSS Statistics. 4th ed. Thousand Oaks, Ca: SAGE Publications Ltd; 2013. 6. Jacobs JE, Lanza S, Osgood DW, Eccles JS, Wigfield A. Changes in children’s self-competence and values: gender and domain differences across grades one through twelve. Child Dev. 2002;73(2):509. PubMed doi:10.1111/1467-8624.00421 7. Rodrigues LP, Saraiva L, Gabbard C. Development and construct validation of an inventory for assessing the home environment for motor development. Res Q Exerc Sport. 2005;76:140–148. PubMed doi:10.1080/02701367.2005.10599276 8. Horn T. Developmental perspectives on self-perceptions in children and adolescents. In: Weiss MR, ed. Developmental sport and exercise psychology: a lifespan perspective. Morgantown, WV: Fitness Information Technology; 2004:101–143. 9. Breslin G, Murphy M, McKee D, Delaney B, Dempster M. The effect of teachers trained in a fundamental movement skills programme on children’s self-perceptions and motor competence. Eur Phys Educ Rev. 2012;18(1):114–126. doi:10.1177/1356336X11430657
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10. LeGear M, Greyling L, Sloan E, et al. A window of opportunity? Motor skills and perceptions of competence of children in kindergarten. Int J Behav Nutr Phys Act. 2012;9:29. PubMed 11. Piek JP, Baynam GB, Barrett NC. The relationship between fine and gross motor ability, self-perceptions and self-worth in children and adolescents. Hum Mov Sci. 2006;25:65–75. PubMed doi:10.1016/j. humov.2005.10.011 12. Robinson L. The relationship between perceived physical competence and fundamental motor skills in preschool children. Child Care Health Dev. 2010;37(4):589–596. PubMed doi:10.1111/j.13652214.2010.01187.x 13. Ulrich DA. Test of Gross Motor Development (TGMD-2). 2nd ed. Austin, TX: PRO-ED, Inc.; 2000. 14. Harter S, Pike R. The pictorial scale of perceived competence and social acceptance for young children. Child Dev. 1984;55(6):1969– 1982. PubMed doi:10.2307/1129772 15. Goodway J, Rudisill ME. Perceived physical competence and actual motor skill competence of African American preschool children. Adap Phys Act Qu. 1997;14:314–326. 16. McBee M. Modeling outcomes with floor or ceiling effects: an introduction to the Tobit Model. Gift Child Q. 2010;54(4):314–320. doi:10.1177/0016986210379095 17. Barnett LM, Hinkley T, Okely AD, Salmon J. Child, family and environmental correlates of children’s motor skills proficiency. J Sci Med Sport. 2013;16(4):332–336. PubMed doi:10.1016/j.jsams.2012.08.011 18. Burgi F, Meyer U, Granacher U, et al. Relationship of physical activity with motor skills, aerobic fitness and body fat in preschool children: a cross-sectional and longitudinal study (Ballabeina). Int J Obes. 2011;35(7):937–944. PubMed doi:10.1038/ijo.2011.54 19. Cliff DP, Okely AD, Smith LM, McKeen K. Relationships between fundamental movement skills and objectively measured physical activity in preschool children. Pediatr Exerc Sci. 2009;21:436–449. PubMed 20. Fisher A, Reilly JJ, Montgomery C, et al. Fundamental movement skills and habitual physical activity in young children. Med Sci Sports Exerc. 2005;37:684–688. PubMed doi:10.1249/01. MSS.0000159138.48107.7D 21. Williams HG, Pfeiffer KA, O’Neill JR, et al. Motor skill performance and physical activity in preschool children. J Obes. 2008;16:1421– 1426. PubMed doi:10.1038/oby.2008.214 22. Sallis JF, Prochaska JJ, Taylor WC. A review of correlates of physical activity of children and adolescents. Med Sci Sports Exerc. 2000;32(5):963–975. PubMed doi:10.1097/00005768-20000500000014 23. Barnett LM, Cliff K, Morgan PJ, van Beurden E. Adolescents’ perception of the relationship between movement skills, physical activity and sport. Eur Phys Educ Rev. 2013;19(2):271–285. doi:10.1177/1356336X13486061 24. Stein C, Fisher L, Berkey C, Colditz G. Adolescent physical activity and perceived competence: does change in activity level impact self-perception? J Adolesc Health. 2007;40(5):462–468. PubMed doi:10.1016/j.jadohealth.2006.11.147 25. Kahn JA, Huang B, Gillman MW, et al. Patterns and determinants of physical activity in U.S. adolescents. J Adolesc Health. 2008;42:369– 377. PubMed doi:10.1016/j.jadohealth.2007.11.143 26. Crocker PRE, Eklund RC, Kowalski KC. Children’s physical activity and physical self-perceptions. J Sports Sci. 2000;18(6):383–394. PubMed doi:10.1080/02640410050074313 27. Kershaw P, Irwin L, Trafford K, Hertzman C. The British Columbia atlas of child development. Georgetown, ON: Human Early Learning Partnership; 2005. 28. The Human Early Learning Partnership. EDI Data tables. 2011. 29. Eston RG, Rowlands AV, Ingledew DK. Validity of heart rate, pedometry, and accelerometry for predicting the energy cost of children’s activities. J Appl Physiol. 1998;84:362–371. PubMed 30. Reilly JJ, Kelly LA, Montgomery C, et al. Validation of Actigraph accelerometer estimates of total energy expenditure in
young children. Int J Pediatr Obes. 2006;1(3):161–167. PubMed doi:10.1080/17477160600845051 31. Puyau MR, Adolph AL, Firoz AV, Butte NF. Validation and calibration of activity monitors in children. Obes Res. 2002;10(3):150–7. PubMed 32. Reilly JJ, Penpraze V, Hislop J, Davies G, Grant S, Paton JY. Objective measurement of physical activity and sedentary behaviour: review with new data. Arch Dis Child. 2008;93(6):614–619. PubMed doi:10.1136/ adc.2007.133272 33. Trost SG, McIver KL, Pate R. Conducting accelerometerbased activity assessments in field-based research. Med Sci Sports Exerc. 2005;37(11):S531–S543. PubMed doi:10.1249/01. mss.0000185657.86065.98 34. Mei Z, Grummer-Strawn LM, Pietrobelli A, Goulding A, Goran MI, Dietz WH. Validity of body mass index compared with other bodycomposition screening indexes for the assessment of body fatness in children and adolescents. Am J Clin Nutr. 2002;75(6):978–85. PubMed 35. Centers for Disease and Prevention. Children’s BMI Tool for Schools—Assessing Your Weight: Children’s BMI Tool for Schools. 2010; http://www.cdc.gov/healthyweight/assessing/bmi/childrens_ bmi/tool_for_schools.html. Accessed March, 2, 2014. 36. Baumgartner TA, Strong CH, Hensley LD. Conducting and reading research in health and human performance. New York, NY: McGraw Hill; 2002. 37. Trost SG, Loprinzi PD, Moore R, Pfeiffer KA. Comparison of accelerometer cut points for predicting activity intensity in youth. Med Sci Sports Exerc. 2011;43(7):1360–1368. PubMed doi:10.1249/ MSS.0b013e318206476e 38. Evenson KR, Catellier DJ, Gill K, Ondrak KS, McMurray RG. Calibration of two objective measures of physical activity for children. J Sports Sci. 2008;26(14):1557–1565. PubMed doi:10.1080/02640410802334196 39. Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol. 1986;54(6):1173–1182. PubMed doi:10.1037/0022-3514.51.6.1173 40. IBM SPSS Statistics [computer program]. Version 19. Somers, NY2010. 41. Harter S. The construction of the self: developmental and sociocultural foundations. 2nd ed. New York: The Guilford Press; 2012. 42. Ebbeck V, Stuart ME. Who determines what’s important? Perceptions of competence and importance as predictors of self-esteem in youth football players. Pediatr Exerc Sci. 1993;5:253–262. 43. Shapiro DR, Moffett A, Lieberman L, Drummer GM. Domain-specific ratings of importance and global self-worth of children with visual impairments. J Vis Impair Blind. 2008;102(4):232–244. 44. Strong WB, Malina RM, Blimkie CJR, et al. Evidence based physical activity for school-age youth. J Pediatr. 2005;146(6):732–737. PubMed doi:10.1016/j.jpeds.2005.01.055 45. Payne GV, Issacs LD. Human motor development. A lifespan approach. 7th ed. Boston: McGraw Hill; 2008. 46. Berger SE, Adolph KE. Learning and development in infant locomotion. Prog Brain Res. 2007;164:237–255. PubMed doi:10.1016/ S0079-6123(07)64013-8 47. Barnett LM, van Beurden E, Morgan PJ, Brooks LO, Beard JR. Childhood motor skill proficiency as a predictor of adolescent physical activity. J Adolesc Health. 2008a;44:252–259. PubMed doi:10.1016/j. jadohealth.2008.07.004 48. Okely AD, Booth ML, Patterson JW. Relationship of physical activity to fundamental movement skills among adolescents. Med Sci Sports Exerc. 2001;33(11):1899–1904. PubMed doi:10.1097/00005768200111000-00015 49. Barnett LM, van Beurden E, Morgan PJ, Brooks LO, Beard JR. Does childhood motor skill proficiency predict adolescent fitness? Med Sci Sports Exerc. 2008b;40:2137–2144. PubMed doi:10.1249/ MSS.0b013e31818160d3 50. Colley R, Garriguet D, Janssen I, Craig CL, Clarke J, Tremblay M. Physical activity of Canadian children and youth: accelerometer
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54. Nettlefold L, McKay HA, Naylor P-J, Bredin SSD, Warburton DER. The relationship between objectively measured physical activity, sedentary time, and vascular health in children. Am J Hypertens. 2012;25(8):914–919. PubMed doi:10.1038/ajh.2012.68 55. Carson V, Spence JC, Cutumisu N, Boule N, Edwards J. Seasonal variation in physical activity among preschool children in a northern canadian city. Res Q Exerc Sport. 2010;81(4):392–399. PubMed doi: 10.1080/02701367.2010.10599699 56. Statistics Canada. Health Trends—National Rates of Obesity. 2013; http://www.statcan.gc.ca/start-debut-eng.html, 2014. 57. Statistics Canada. Physical Activity During Leisure Time, 2013. 2013; www.statcan.gc.ca/pub.82-625-x/2014001/article/14024-eng.htm, 2014.
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results from the 2007-2009 Canadian health measure survey. Vol 22. Statistics Canada; 2011:1–9. 51. Reilly JJ. Low levels of objectively measured physical activity in preschoolers in child care. Med Sci Sports Exerc. 2010;42(3):502–507. PubMed doi:10.1249/MSS.0b013e3181cea100 52. Temple VA, Naylor P-J, Rhodes RE, Higgins JW. Physical activity of children in family care. Appl Physiol Nutr Metab. 2009;34:794–798. PubMed doi:10.1139/H09-061 53. Colley RC, Garriguet D, Adamo KB, Janssen I, Timmons BW, Tremblay MS. Physical activity and sedentary behavior during the early years in Canada: a cross-sectional study. Int J Behav Nutr Phys Act. 2013;10(54). PubMed
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