Journal Logo

EPIDEMIOLOGY

Physical Activity and Skills Intervention

SCORES Cluster Randomized Controlled Trial

COHEN, KRISTEN E.1; MORGAN, PHILIP J.1; PLOTNIKOFF, RONALD C.1; CALLISTER, ROBIN2; LUBANS, DAVID R.1

Author Information
Medicine & Science in Sports & Exercise: April 2015 - Volume 47 - Issue 4 - p 765-774
doi: 10.1249/MSS.0000000000000452
  • Free

Abstract

Physical inactivity has been described as a global pandemic (18). Global estimates suggest that 80% of young people are not participating in adequate amounts of moderate-to-vigorous physical activity (MVPA) to acquire the associated physical, social, cognitive, and psychological benefits (18). Schools have been identified as important settings for the promotion of physical activity (PA) among children (8) because they have the necessary resources and they provide access to populations at risk of being physically inactive, such as those from low socioeconomic backgrounds (13,20).

Numerous school-based interventions have been evaluated, and evidence suggests that multicomponent interventions are more effective than curriculum-only approaches (22). Although strong evidence exists for the effectiveness of school-based PA interventions (1,5), studies rarely report their effect on fundamental movement skill (FMS) competency. This is a notable exclusion because evidence suggests that competency in a range of FMS may serve as protective factor against the decline in PA typically observed during adolescence (4).

FMS are considered the building blocks for movement, and the primary school years are the optimal stage of life to develop proficiency (17). For most, FMS competency does not occur naturally and is more likely to be achieved through quality instruction and active play experiences (17). FMS can be categorized into locomotor (e.g., run, hop, jump, leap), object control (e.g., throw, catch, kick, strike), and stability (e.g., static balance) skills (17). Strong evidence exists for a positive association between FMS and PA, and FMS and cardiorespiratory fitness in children, and an inverse association between skill level and weight status in children (27). Although the health benefits gained from developing FMS competency in children is clear (27), competency among children is low (15,19).

Socioenvironmental factors (e.g., reduced access to PA facilities and resources, working parents, and unsafe neighborhoods) (12,43) and ineffective school-based strategies, including poor-quality physical education (PE) (11), may explain the low PA levels and poor FMS competency among children living in low socioeconomic communities. These findings highlight the need to evaluate school-based approaches to promote PA among those at most risk of being physically inactive (e.g., those from low socioeconomic backgrounds). The aim of the current study was to evaluate the effects of the Supporting Children’s Outcomes using Rewards, Exercise, and Skills (SCORES) program (28), a 12-month school-based cluster randomized controlled trial (RCT) designed to increase PA and improve FMS competency among children attending primary schools in low-income communities. This study reports the midprogram (6 months) and posttest (12 months, study’s primary time point) intervention effects.

METHODS

Study Design and Participants

The ethics approval for this study was obtained from the human research ethics committees of the University of Newcastle, Australia, and the New South Wales Department of Education and Communities. School principals, teachers, parents, and study participants provided a written informed consent. The design and methods of the SCORES cluster RCT have been reported in detail elsewhere (28). The design, conduct, and reporting of this cluster RCT adhered to the Consolidated Standards of Reporting Trials guidelines for group trials (7). Baseline assessments were conducted in February through March 2012, midprogram (6 months after baseline) assessments were conducted in August through September 2012, and immediate posttest (12 months after baseline, study’s primary time point) assessments were completed in February through March 2013.

The intervention was designed for children from schools located in low-income communities, and the Socio-Economic Indexes for Areas (SEIFA) index of relative socioeconomic disadvantage (2) was used to identify eligible primary schools. The SEIFA index (scale 1 = lowest, to 10 = highest) summarizes the characteristics of people and households within an area and was developed using the following data: employment, education, financial well-being, housing stress, overcrowding, home ownership, family support, family breakdown, family type, lack of wealth (no car or telephone), low income, indigenous status, and foreign birth (2). Sixteen government primary schools located within a 30-km radius from the University of Newcastle with a SEIFA index ≤5 (lowest 50%) were invited to participate in the study, and eight schools (25 classes) consented to participate (50% consent rate). All students in grades 3 and 4 (stage 2, age 7–10 yr) at the study schools were invited to participate in the program. From the 592 eligible children at the eight schools, 460 children consented to participate (78% consent rate).

Sample Size Calculation and Randomization

Power calculations were conducted to determine the sample size required to detect changes in the three primary outcomes (i.e., PA, FMS, and cardiorespiratory fitness) at the posttest (12 months after baseline, study’s primary time point) assessments. All calculations assumed baseline–posttest correlation scores of 0.80 and were based on 80% power with alpha levels set at P < 0.05. Using the SD (SD, 33) and intraclass correlation coefficient (ICC, 0.05) values from the Kinder-Sportstudie (KISS) (23), it was calculated that a study sample of 440, with eight clusters (i.e., schools) of 55 students, would provide adequate power to detect an achievable between-group difference of 11 min·d−1 of MVPA (23). On the basis of data from the Action Schools BC! (SD, 13) (35) and the KISS (ICC, 0.03) (23) studies, a sample of 440 would also provide adequate power to detect a between-group difference of four laps on the multistage fitness test (i.e., cardiorespiratory fitness outcome). In the absence of existing ICC values for FMS outcomes, an ICC estimate of 0.05 and an SD of 15 units (42) indicated that the study would be adequately powered to detect a between-group difference of 5 units on the Test of Gross Motor Development 2 (TGMD-2).

After baseline assessments, the eight schools were match-paired (i.e., four pairs of schools) on the basis of their size and socioeconomic position (based on the postcode of school). These pair-matched schools were then randomized to control or intervention conditions by an independent researcher using a computer-based random number-producing algorithm. The schools were allocated to either the SCORES intervention or control group for the duration of the study. Assessors were blinded to treatment allocation at baseline but not at follow-up assessments.

Intervention

SCORES was a 12-month multicomponent PA and FMS intervention for primary schools in low-income communities. A detailed description of the SCORES intervention has been reported previously (28). Briefly, the socioecological model (30) provided a framework for the intervention components. The SCORES intervention was implemented in three phases. Phase 1 (implemented from April 2012) focused on teacher professional learning, student leadership workshops, and PA promotion tasks to achieve awards. Students who completed five tasks achieved a SCORES Yellow Leader award, those who completed 10 tasks achieved a SCORES Red Leader award, and those who completed 15 tasks achieved a SCORES Blue Leader award. Examples of tasks included acting as equipment monitor, organizing games during recess and lunch, and writing a PA promotion article for the school newsletter. Equipment was also provided to the school during this phase, and the school committee was established. In phase 2 (implemented from July 2012), intervention schools were encouraged to implement six PA policies to support the promotion of PA and FMS competency within the school. A member of the research team met with the principal at the intervention schools to explain the policies. The member of the research team then conducted a meeting with all staff members to explain the policies and provide strategies for implementation of the policies. In addition, the research team used a range of strategies targeting the home environment (newsletters, parent evening, and FMS homework) to engage parents and encourage them to support their children’s PA. Phase 3 (implemented from October 2012) addressed strategies to improve school–community links (e.g., inviting local sporting organizations to assist with school sport programs).

The control schools were asked to follow their usual PE and school sport programs. The New South Wales Department of Education and Communities requires by policy that all schools provide students with 120 min·wk−1 of planned PA. In government primary schools, sports programs are similar among schools. All schools in the study did not have PE specialists. Alternatively, PE and school sports were taught by the generalist classroom teacher. To assist in recruitment of schools and prevent resentful demoralization or compensatory rivalry (34), the control schools were provided with equipment packs and a condensed version of the program after the posttest (12 months) assessments.

Assessments and Measures

Data collection was conducted in the study schools by trained research assistants. For consistency and accuracy, a protocol manual, which included specific instructions for conducting all assessments, was developed and used by research assistants to standardize procedures and for quality assurance. The same research assistants were used across all three time points. Assessors were blind to treatment allocation at baseline but not at follow-up assessments.

Primary Outcome Measures

PA

PA was assessed using triaxial ActiGraph GT3X+ accelerometers (ActiGraph, LLC, Fort Walton Beach, FL). Accelerometers were worn by participants during waking hours for seven consecutive days, except while bathing and swimming. Trained research assistants, following standardized accelerometer protocols (41), fitted the monitors and explained the monitoring procedures to students. MeterPlus version 4.3 software (Santech Inc., San Diego, CA) was used to analyze accelerometer data. Data were collected and stored in 10-s epochs with a frequency of 30 Hz. Valid wear time for total PA was defined as a minimum of three weekdays and a weekend day with at least 8 h (480 min·d−1) of total wear time recorded. Valid wear time for within-school and after-school PA was defined as a minimum of three weekdays with at least 8 h (480 min·d−1) of total wear time recorded. The within-school period was defined as the period from when school started for each participant (ranged from 9:00 to 9:15 a.m.) to the time when school ended for each participant (3:00 p.m. for all participants). The after-school period was defined as the period from when school ended for each participant (3.00 p. m. for all participants) to 6.00 p.m. Valid wear time for weekend PA was defined as a minimum of one weekend day with at least 8 h (480 min·d−1) of total wear time recorded. Nonwear time was defined as strings of consecutive zeroes equating to 20 min (6,38). The mean activity counts per minute (cpm) were calculated; activity thresholds were used to calculate time spent sedentary (≤25 counts) and in light (26–573 counts), moderate (574–1002 counts), and vigorous (≥1003 counts) activity, and minutes and percentage spent in each activity intensity (16).

FMS

FMS competency was assessed using the TGMD-2 (42), which has established validity and reliability in children (42). The TGMD-2 includes six locomotor (i.e., run, gallop, hop, leap, horizontal jump, and slide) and six object control (i.e., striking a stationary ball, stationary dribble, kick, catch, overhand throw, and underhand roll) skills. Participants performed each skill twice, and skills were videotaped for assessment. Each skill includes several behavioral components. If the participant performed a behavioral component correctly, they received a score of 1; if they performed it incorrectly, they received a 0. This procedure was completed for each of the two trials, and scores were summed to obtain a total raw skill score. The raw skill scores were then added to obtain a raw locomotor subtest score and a raw object control subtest score. The raw locomotor subtest score and the raw object control subtest score were then added to obtain a raw overall FMS score (42). Interrater reliability (98% agreement rate) and intrarater reliability (97%–99% agreement rate) were established using precoded videotapes before movement skills were assessed by three assessors. Kappa values were also calculated to take into account agreement beyond chance. These were 0.97 (95% confidence interval (CI), 0.96–0.98) for interrater reliability and ranged from 0.94 (95% CI, 0.91–0.97) to 0.98 (95% CI, 0.97–0.99) for intrarater reliability.

Cardiorespiratory fitness

Cardiorespiratory fitness was assessed using the 20-m multistage fitness test (24). Participants were required to run back and forth between two lines over a 20-m distance within a set time limit. Running speed started at 8.5 km·h−1 and increased by 0.5 km·h−1 each minute using the multistage test cadence compact disc. Participants were instructed to run in a straight line and to place one foot over the 20-m line before the next beep. The test was completed when a participant failed to reach the line for two consecutive shuttles. Scores were recorded as the level and shuttle reached, which was converted to the number of 20-m laps completed to provide a continuous variable for analysis.

Height and Weight

Height was recorded to the nearest 0.1 cm using a portable stadiometer (model no. PE087; Mentone Educational Centre, Australia). Weight was measured in light clothing without shoes using a portable digital scale (model no. UC-321PC; A&D Company Ltd, Tokyo Japan) to the nearest 0.1 kg. Body mass index (BMI) was calculated using the standard equation weight (kg)/height squared (m2), and BMI z-scores were calculated using the “LMS” method (10).

Demographic Measures

Participating children completed a questionnaire to obtain demographic information including sex, age, language spoken at home, Aboriginal or Torres Strait Islander decent, ethnicity, and suburb. The suburb of the child’s residence was used to determine their socioeconomic status (SES) using the SEIFA index of relative socioeconomic disadvantage (2).

Process Evaluation

A detailed process evaluation was conducted and included 1) teacher and student attendance at workshops (i.e., percentage attendance), 2) student leadership accreditation (i.e., number of students who completed the workshop and satisfied the accreditation guidelines), 3) teacher satisfaction with professional learning workshops (using workshop evaluation questionnaires at the end of phase 1), 4) parental involvement determined using a process evaluation questionnaire completed by parents (e.g., reading newsletters and completion of home-based FMS tasks) and attendance at the parent evening, 5) teacher, student, and parent satisfaction with all intervention components (using process evaluation questionnaires at the completion of the study), 6) compliance with PA policies determined through interviews with school principals (one interview at each of the four intervention schools was conducted, which lasted 1 h on average), and 6) PE intervention fidelity determined using the SCORES lesson observation checklist. The checklist assessed teachers’ adherence to the recommended PE lesson structure and included the following components with a “yes” (= 1) or “no” (= 0) response: 1) introduction, wherein i) the teacher reviews previous lesson and ii) the teacher explains lesson focus; 2) warm-up, wherein i) lesson involves general movement-based warm-up and ii) warm-up includes dynamic and/or static stretching; 3) skill development, wherein i) a teacher or student demonstrates the skill, ii) lesson involves skill exploration, and iii) lesson involves guided discovery; 4) skill application, wherein i) lesson involves modified games and ii) lesson involves full-sided games; and 5) closure, wherein i) lesson includes cooldown, ii) the teacher uses questioning to check for student understanding, and iii) the teacher reinforces key skill components, and if the teacher was using the SCORES teaching resource. At the intervention schools, stage 2 teachers’ PE lessons were observed three times by a member of the research team. The results of the observations were provided to the teachers immediately after each observation.

Statistical Analyses

All analyses were performed using IBM SPSS Statistics for Windows version 20 (2011 SPSS Inc., IBM Corp., Armonk, NY), and statistical significance was set at P < 0.05. Data were assessed for normality of distribution and transformed where necessary. Differences between groups at baseline for those who did not complete follow-up assessments were examined using independent-sample t-tests and chi-square (χ2) tests for categorical variables. Statistical analyses followed the intention-to-treat principle and were conducted using linear mixed models, which have the advantage of being robust to the biases of missing data (29). Mixed models were used to assess all outcomes for the effect of treatment (intervention or control), time (treated as categorical with levels baseline, 6 months, and 12 months), and the group–time interaction, these three terms forming the base model. Sex, age, BMI z-score, SES, and ethnicity were included as fixed factors, and school class was included as a random effect. School class was the smallest cluster in the sampling design; therefore, it was introduced as a random effect (23). Intraclass correlation was calculated to compare the variation between school classes as a fraction of the total variance.

RESULTS

Twenty-five classes in eight schools including 460 children (199 children in the intervention group and 261 in control group) entered the study (Fig. 1). Table 1 shows the baseline characteristics by treatment group. Tables 2 and 3 describe results for primary outcomes at baseline, midprogram (6 months), and at posttest (12 months). Children with baseline assessment but no posttest assessment did not differ from the remaining children in terms of sex (χ2 (1) = 3.09, P = 0.079), age (t (246) = 1.49, P = 0.137), PA (t (246) = 0.08, P = 0.939), object control skills (t (452) = −0.82, P = 0.410), or cardiorespiratory fitness (t (435) = −0.86, P = 0.392). However, children who did not complete the posttest assessment had lower locomotor skill competency (mean (SD), 23.8 (5.7) vs 26.0 (5.7); t (426) = −3.06, P = 0.002) compared with those who completed the posttest assessments.

TABLE 1
TABLE 1:
Characteristics of study sample.
TABLE 2
TABLE 2:
Changes in primary outcomes measures and group differences at midprogram (6-months).
TABLE 3
TABLE 3:
Changes in primary outcome measures and group differences at posttest (12 months).
FIGURE 1
FIGURE 1:
Study design and flow of participants through the study with primary outcome measures.aChildren either arrived late at school or left school early on the assessment day; bchildren were absent on the assessment day; cchildren left the school; dchildren withdrew from the program.

Primary outcomes at midprogram (6 months after baseline)

Table 2 shows the results of the primary outcomes at baseline and midprogram as well as the adjusted differences at midprogram. There were no statistically significant group–time interactions for PA, FMS, or cardiorespiratory fitness at midprogram.

Primary outcomes at posttest (12 months after baseline, study’s primary time point)

Table 3 shows the results of the primary outcomes at baseline and posttest as well as the adjusted differences at posttest (12 months minus baseline). There was a statistically significant group–time interaction in favor of the intervention group for daily MVPA minutes (P = 0.008), corresponding to a difference of 13 min·d−1 of MVPA. There was also a statistically significant group–time interaction in favor of the intervention group for daily after-school MVPA minutes (P = 0.028) and daily weekend MVPA minutes (P = 0.034).The changes in total PA (P = 0.054), MVPA percentage (P = 0.051), and within-school MVPA (P = 0.182) from baseline to posttest showed trends in favor of the intervention group. There was a statistically significant group–time interaction for overall FMS, with children in the intervention group scoring significantly higher (P = 0.045) than those in the control group. Changes in locomotor and object control skills were in favor of the intervention group, but there were no statistically significant group–time interactions. The intervention resulted in a significant group–time interaction for children’s cardiorespiratory fitness (P = 0.003), corresponding to an additional five laps on the 20-m multistage fitness test.

Process outcomes

Nine of 13 (69.2%) stage 2 (grade 3 and 4) teachers at the intervention schools (these teachers were the specific target of the intervention) attended the full-day professional learning workshop, and 50 of 57 (87.7%) teachers at the intervention schools (all teachers in the school) attended the whole-school professional learning workshop (a member of the research team met with those teachers who were unable to attend the full-day workshop and explained the intervention strategies and components). Overall, stage 2 teachers were satisfied with the professional learning workshop; they found the workshop enjoyable (mean (SD), 4.9 (0.3); rating scale, 1 = strongly disagree, to 5 = strongly agree) and provided them with useful information about effective teaching of FMS (mean (SD), 4.8 (0.4); rating scale, 1 = strongly disagree, to 5 = strongly agree). Similarly, teachers were satisfied with the whole-school professional learning workshop, reporting that the workshop was enjoyable (mean (SD), 4.7 (0.5); rating scale, 1 = strongly disagree, to 5 = strongly agree) and provided useful information about effective teaching of FMS (mean (SD), 4.6 (0.7); rating scale, 1 = strongly disagree, to 5 = strongly agree). A total of 177 children attended the student leadership workshop (88.5%). Of the 177 children, 145 (81.9%) achieved the SCORES Yellow Leader award, 105 children achieved the SCORES Red Leader award (59.3%), and 73 children achieved the SCORES Blue Leader award (41.2%). Overall, children were satisfied with the program (mean (SD), 2.7 (0.6); rating scale, 1 = not really, to 3 = a lot). Parents reported that, on average, their child completed FMS homework once per week (mean (SD), 3.6 (1.8); rating scale, 1 = never, to 5 = greater than once per week). Parents reported that the newsletters provided them with useful information about the promotion of PA in children (mean (SD), 3.8 (0.7); rating scale, 1 = strongly disagree, to 5 = strongly agree). In total, 140 parents attended the parent evenings. Seventy-five percent of the intervention schools complied with policy 1 (functioning school PA committee), all intervention schools complied with policy 2 (all students must participate in at least 120 min of timetabled PE and school sport per week), 25% of intervention schools complied with policy 3 (50% of PE and school sport time must be devoted to MVPA. The intervention schools were provided with a class set of pedometers. Teachers were encouraged to use the pedometers to measure their students’ MVPA during PE and school sport. If the students were achieving 75–85 steps per minute in the lesson, it was deemed to be equivalent to 50% MVPA (39)), 25% of intervention schools complied with policy 4 (annual reporting of students’ FMS and fitness levels), 75% of intervention schools complied with policy 5 (promotion of active playgrounds), and 25% of intervention schools complied with policy 6 (involve family members/carers in school-based PA). Each of the four intervention schools had four visits from community sporting organizations, and 58.7% of children reported that they had joined a local sporting club. On average, stage 2 teachers at the intervention schools adhered to 62.9% of the recommended PE lesson structure at observation 1, 70.5% at observation 2, and 79.0% at observation 3. No injuries or adverse effects were reported during implementation of the intervention components or assessments.

DISCUSSION

The SCORES school-based multicomponent PA and FMS intervention resulted in significant group–time interactions for daily MVPA, overall FMS competency, and cardiorespiratory fitness among children attending primary schools in low-income communities. Results from the SCORES intervention add to the body of evidence for the effectiveness of multicomponent school-based interventions.

Although no significant group–time interactions were observed at midprogram, there was a significant increase in MVPA among those in the intervention group. The increase in PA observed at midprogram could be attributed to a seasonal effect. In Australia, children participate in more extracurricular sport during the winter months (3), thus increasing PA during this time. At posttest, the control group’s PA significantly decreased whereas the intervention group maintained their PA. A significant group–time interaction was observed at posttest, indicating that the SCORES intervention was protective against declines in children’s PA. After completion of the intervention, the adjusted difference between intervention and control schools was 13 min·d−1 of MVPA. This finding is comparable with the intervention effect observed in the KISS study (23) (11 min·d−1). The KISS study involved the addition of daily PE lessons delivered by specialists, which may not be feasible in many schools because of the pressures of a crowded curriculum and the cost of employing specialists (33). In contrast, the SCORES intervention was able to achieve an intervention effect for children’s daily MVPA without increasing the time allocated to PE or school sport or taking time away from other subjects, which is important for possible future adoption in schools. The SCORES intervention effects add to the body of evidence identified in a recent systematic review (31), which found that, on average, PA interventions for children achieve only small improvements in the time spent in MVPA. Although levels of MVPA significantly declined among participants in the control group, activity levels were maintained in the intervention group. This finding is of considerable importance because it indicates that the intervention was protective against the decline in PA that is often observed in late childhood and early adolescence. Lopes et al. (26) demonstrated a similar PA maintenance effect over time and suggested that increasing movement skills was the primary mechanism responsible for this result.

The intervention effect on MVPA observed in the current study may be attributed to the greater quality of PE and school sport delivered in the intervention schools, which were key intervention targets. The professional development provided to teachers focused on improving the quality of PE lessons, which included appropriate FMS instruction and high levels of active learning time (i.e., the proportion of PE lesson time students spend in MVPA). A recent systematic review identified that school-based interventions can increase the proportion of time students spend in MVPA during PE lessons (25). Effective intervention strategies identified in the review included teacher professional development focusing on class organization, management, and instruction (25), all of which were key areas for professional development and lesson observations in the SCORES intervention (28). This suggestion is further supported by the high adherence to the recommended PE lesson structure observed in the intervention school teachers, which improved over the intervention period.

The SCORES intervention resulted in a significant group–time interaction for after-school and weekend MVPA. This is a notable finding, as the after-school period in particular is considered the critical window of opportunity for young people to be physically active. Children have more discretion over how they spend their time after school and on weekends. The maintenance of MVPA during these periods indicates that the intervention was successful in preventing children from selecting sedentary recreational activities. Although the within-school MVPA group–time interactions were not significant, participants in the intervention group were spending 4 min more in MVPA compared with those in the control group.

Improvements in FMS competency were observed in both the intervention and control groups at midprogram and posttest; however, improvements were greater in the intervention group. The increase observed in both groups is likely due to maturation and natural development that occur during childhood. Findings from the current study are consistent with a recent systematic review (32), which concluded that enhanced PE programs that use PE specialists or provide professional development for teachers can increase the rate of skill development in children. The review also highlighted the benefit of student-centered approaches to FMS teaching (9,21), particularly approaches that adopted a mastery climate, focusing on success, optimal challenge, and autonomy. Aligning with recommendations from this review, the SCORES intervention used professional development and mastery climate approaches.

Although there was significant group–time interaction for overall FMS at posttest, the midprogram effect was not statistically significant. Movement skill acquisition is a developmental process, over time, involving a large degree of variability in movement patterns. With quality learning opportunities, individuals progress through stages from rudimentary to more advanced movement skill patterns with improved performance and consistency. The lack of significant effects for FMS at midprogram could be attributed to the quality of instruction by the teachers not being adequate to result in improvements in the children’s skills above and beyond natural development. Improvements in the quality of PE lessons, as per the lesson observations, were seen after the midpoint of the intervention. The lack of significant effects at midprogram, but significant effects found at posttest, supports the notion that it takes time, practice, and quality feedback from qualified personnel to increase the rate of skill development. It is possible that the nonsignificant midprogram findings were due to the combined MVPA/skill development aim for PE. Although teachers were provided with strategies to maximize both opportunities for skill development and PA, in the early stages of the intervention, teachers may have found it challenging to achieve both outcomes. On the basis of the process evaluation data, teachers improved their lesson quality over time and demonstrated a capacity to adhere to the desired SCORES lesson structure as the intervention progressed.

As expected with maturation, cardiorespiratory fitness increased in both the intervention and control groups at midprogram. However, by posttest, the significant increase in cardiorespiratory fitness was sustained only in the intervention group. The SCORES intervention was found to have significant group–time interaction for cardiorespiratory fitness, equivalent to five additional laps on the multistage fitness test. This finding is substantial, considering the low levels of fitness observed among young people and the decline in cardiorespiratory performance over recent decades (40). Other high-quality school-based interventions have also reported improvements in cardiorespiratory fitness (14,22,36). Interestingly, many of these trials have used PE specialists to deliver their programs, which have sometimes included daily PA sessions. Alternatively, SCORES achieved improvements in cardiorespiratory fitness, with the generalist classroom teacher delivering the program and without additional sessions per week. It is plausible to suggest that the SCORES intervention strategies targeting PA within and beyond the school day (e.g., lunch and recess organized games, FMS homework, 50% of PE and sport time devoted to MVPA) over an extended period contributed to improvements in cardiorespiratory fitness.

Interestingly, none of the intervention effects for the primary outcomes were significant at midprogram. Overall, there was good compliance to the intervention strategies; however, the lack of findings at midprogram may be due to the intervention components taking time to become adopted and implemented. Furthermore, the lack of significant findings at midprogram may be due to the intervention being delivered in a three-phase approach, meaning that not all components were used in the first 6 months. Phase 1 involving the teacher professional development, student leadership, provision of equipment, and establishment of a school committee was implemented before the 6-month assessments. Although teachers reported that they found the workshops to be useful for effective PE teaching strategies, improvement in the quality of their PE lessons, as per the lesson observations, were seen after the midpoint of the intervention. There was good attendance at the student leadership workshop; however, schools commented that it took some time to implement the student leadership tasks and award system, which may have contributed to less PA opportunity in the first period of the intervention. Phases 2 and 3 involved school PA promotion policies, strategies to target the home environment and improve school–community links, all of which were implemented during and after the 6-month assessments. Parent engagement and community link strategies seemed to be successful, with good compliance and satisfaction as demonstrated in the process evaluation measures. Adherence to school PA policies ranged. School principals commented that low adherence to some policies (e.g., FMS reporting) was due to adoption and implementation of these policies being more appropriate and practical at the start of the school year rather than halfway through as designed in the intervention.

The positive results in the current study were found in a population subgroup (i.e., low socioeconomic background) at elevated risk of the consequences of physical inactivity. The primary school years are the optimal time for developing children’s PA behaviors and FMS (17). PE is a vital medium for providing developmental opportunities, and the quality of instruction is one of the most influential factors in children’s development (17). Current issues (e.g., inadequate teacher training, crowded curriculum) (33) within the primary school PE learning context need to be addressed, so that children can receive continual progressive quality instruction. Adopting successful evidenced-based approaches may assist in improving the currently low levels of primary school-age children’s PA, FMS, and cardiorespiratory fitness (20), especially in those who are at most risk (i.e., those with low socioeconomic backgrounds), and the dire state of Australian primary school PE (11). Promotion of positive health-related behaviors and outcomes (i.e., PA, FMS, and cardiorespiratory fitness) in early life is important and is expected to have long-term benefits. Using the established personnel and resources in the school setting, combined with effective evidence-based strategies, such as SCORES, may be a practical method of early PA intervention.

Strengths and limitations

The strengths of this study include the cluster RCT design, comprehensive multicomponent intervention, objective measures of PA, FMS, and cardiorespiratory fitness, adjustment of all analyses for confounders, and high level of participant retention for FMS (81.1%) and cardiorespiratory fitness (84.7%). However, there are some limitations that should be noted. First, despite implementing a range of strategies (e.g., text messages and prizes) to improve accelerometer monitoring compliance, only a small number of participants provided usable accelerometer data at baseline (54.3%) and posttest (30.0%). Although accelerometers are considered to be the optimal method for assessing change in PA, compliance to monitoring protocols is often poor, particularly among children of low socioeconomic status (37). Children who are socially disadvantaged or who live in disadvantaged areas are significantly less likely to provide reliable accelerometer data (37). Studies that measure only weekday or school time (i.e., 9:00 a.m. to 3:00 p.m. Monday to Friday or break time) PA tend to achieve higher rates of compliance. This was observed in the current study, with higher baseline (70.7%) and posttest (46.3%) weekday compliance. Often, higher school time compliance is attributed to teachers being responsible for children, putting accelerometers on at the start of the school day and collecting the monitors at the end of the day, thus reducing the challenges of poor compliance outside the school setting. Alternatively, wrist-worn accelerometers may be more acceptable for young people, resulting in higher rates of compliance. Finally, lack of a long-term follow-up is an additional study limitation.

CONCLUSIONS

The SCORES intervention resulted in significant group–time interactions for children’s daily MVPA minutes, overall FMS competency, and cardiorespiratory fitness. The findings demonstrate the potential for multicomponent school-based interventions to promote PA, movement skill competency, and fitness in children attending primary schools in low-income communities.

The authors are grateful for the support and cooperation of the participating schools and students. The authors would also like to thank Tara Finn, Lee Upton, Jordan Smith, Mark Babic, Sarah Costigan, and Deborah Dewar for their assistance in data collection.

This project was funded by the Hunter Medical Research Institute, Australia.The Supporting Children’s Outcomes using Rewards, Exercise, and Skills project and K. E. C. are funded by a grant from the Hunter Medical Research Institute, Australia. R. C. P. is supported by a Senior Research Fellowship Salary Award from the National Health and Medical Research Council, Australia.

The Australian New Zealand Clinical Trials Registry number for this study is ACTRN12611001080910.

There are no conflicts of interest.

The results of the present study do not constitute endorsement by the American College of Sports Medicine.

REFERENCES

1. Aburto NJ, Fulton JE, Safdie M, Duque T, Bonvecchio A, Rivera JA. Effect of a school-based intervention on physical activity: cluster-randomized trial. Med Sci Sports Exerc. 2011; 43 (10): 1898–906.
2. Australian Bureau of Statistics. Socio-economic Indexes for Areas (SEIFA) Australia: Postal Areas, Index of Relative Socio-economic Advantage and Disadvantage. Canberra (Australia): Australian Bureau of Statistics; 2011. pp. 1–81.
3. Australian Bureau of Statistics. Children’s Participation in Cultural and Leisure Activities, Australia. Catalogue Number 4901.0. Canberra (Australia): Australian Bureau of Statistics; 2012.
4. 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. 2009; 44 (3): 252–9.
5. Bugge A, El-Naaman B, Dencker M, et al. Effects of a three-year intervention: the Copenhagen School Child Intervention Study. Med Sci Sports Exerc. 2012; 44 (7): 1310–7.
6. Cain KL, Sallis JF, Conway TL, Van Dyck D, Calhoon L. Using accelerometers in youth physical activity studies: a review of methods. J Phys Activity Health. 2013; 10 (3): 437–50.
7. Campbell MK, Elbourne DR, Altman DG. CONSORT statement: extension to cluster randomised trials. BMJ. 2004; 328 (7441): 702–8.
8. Centers for Disease Control and Prevention. School health guidelines to promote healthy eating and physical activity. MMWR Recomm Rep. 2011; 60 (5): 1–76.
9. Cliff D, Wilson A, Okely A, Mickle K, Steele J. Feasibility of SHARK : a physical activity skill-development program for overweight and obese children. J Sci Med Sport. 2007; 10 (4): 263–7.
10. Cole TJ. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ. 2000; 320 (7244): 1240.
11. Crawford D. Future of Sport in Australia. Canberra (Australia): Commonwealth of Australia; 2009. pp. 1–147.
12. de Vet E, de Ridder DTD, de Wit JBF. Environmental correlates of physical activity and dietary behaviours among young people: a systematic review of reviews. Obes Rev. 2011; 12 (5): e130–42.
13. Department of Health and Ageing. 2007 Australian National Children’s Nutrition and Physical Activity Survey—Main Findings. Australian Capital Territory (Australia): Commonwealth of Australia; 2008. pp. 1–44.
14. Eather N, Morgan PJ, Lubans DR. Improving the fitness and physical activity levels of primary school children: results of the Fit-4-Fun group randomized controlled trial. Prev Med. 2013; 56 (1): 12–9.
15. Erwin HE, Castelli DM. National physical education standards: a summary of student performance and its correlates. Res Q Exerc Sport. 2008; 79 (4): 495–505.
16. 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): 1557–65.
17. Gallahue DL, Ozmun JC. Understanding Motor Development: Infants, Children, Adolescents, Adults. 6th ed. Boston (MA): McGraw-Hill; 2006. p. 512.
18. Hallal PC, Andersen LB, Bull FC, Guthold R, Haskell W, Ekelund U. Global physical activity levels: surveillance progress, pitfalls, and prospects. Lancet. 2012; 380: 247–57.
19. Hardy LL, Barnett L, Espinel P, Okely AD. Thirteen-year trends in child and adolescent fundamental movement skills: 1997–2010. Med Sci Sports Exerc. 2013; 45 (10): 1965–70.
20. Hardy LL, King L, Espinel P, Cosgrove C, Bauman A. NSW Schools Physical Activity and Nutrition Survey (SPANS) 2010: Full Report. Sydney (Australia): NSW Ministry of Health; 2010. pp. 1–387.
21. Kalaja SP, Jaakkola TT, Liukkonen JO, Digelidis N. Development of junior high school students’ fundamental movement skills and physical activity in a naturalistic physical education setting. Phys Educ Sport Pedagogy. 2012; 17 (4): 411–28.
22. Kriemler S, Meyer U, Martin E, van Sluijs EMF, Andersen LB, Martin BW. Effect of school-based interventions on physical activity and fitness in children and adolescents: a review of reviews and systematic update. Br J Sports Med. 2011; 45 (11): 923–30.
23. Kriemler S, Zahner L, Schindler C, et al. Effect of school based physical activity programme (KISS) on fitness and adiposity in primary schoolchildren: cluster randomised controlled trial. BMJ. 2010; 340: c785.
24. Leger L, Lambert JA. A maximal multistage 20 m shuttle run test to predict VO2 max. Eur J Appl Physiol. 1982; 49: 1–12.
25. Lonsdale C, Rosenkranz RR, Peralta LR, Bennie A, Fahey P, Lubans DR. A systematic review and meta-analysis of interventions designed to increase moderate-to-vigorous physical activity in school physical education lessons. Prev Med. 2012; 53: 152–61.
26. Lopes VP, Rodrigues LP, Maia JAR, Malina RM. Motor coordination as predictor of physical activity in childhood. Scand J Med Sci Sports. 2011; 21 (5): 663–9.
27. Lubans DR, Morgan PJ, Cliff DP, Barnett LM, Okely AD. Fundamental movement skills in children and adolescents: review of associated health benefits. Sports Med. 2010; 40 (12): 1019–35.
28. Lubans DR, Morgan PJ, Weaver K, et al. Rationale and study protocol for the supporting children’s outcomes using rewards, exercise and skills (SCORES) group randomized controlled trial: A physical activity and fundamental movement skills intervention for primary schools in low-income communities. BMC Public Health. 2012; 12 (1): 427–38.
29. Mallinckrodt CH, Watkin JG, Molenberghs G, Carroll RJ. Choice of the primary analysis in longitudinal clinical trials. Pharm Stat. 2004; 3 (3): 161–9.
30. McLeroy KR, Bibeau D, Steckler A, Glanz K. An ecological perspective on health promotion programs. Heath Educ Q. 1988; 15 (4): 351–77.
31. Metcalf B, Henley W, Wilkin T. Effectiveness of intervention on physical activity of children: systematic review and meta-analysis of controlled trials with objectively measured outcomes (EarlyBird 54). BMJ. 2012; 345: e5888.
32. Morgan PJ, Barnett LM, Cliff DP, et al. Fundamental movement skill interventions in youth: a systematic review and meta-analysis. Pediatrics. 2013; 132 (5): e1361–83.
33. Morgan PJ, Hansen V. Classroom teachers’ perceptions of the impact of barriers to teaching physical education on the quality of physical education programs. Res Q Exerc Sport. 2008; 79 (4): 506–16.
34. Murray DM. Design and Analysis of Group-Randomized Trials. New York (NY): Oxford University Press; 1998. pp. 1–467.
35. Reed KE, Warburton DE, Macdonald HM, Naylor P, McKay HA. Action Schools! BC: A school-based physical activity intervention designed to decrease cardiovascular disease risk factors in children. Prev Med. 2008; 46 (6): 525–31.
36. Resaland GK, Anderssen SA, Holme IM, Mamen A, Andersen LB. Effects of a 2-year school-based daily physical activity intervention on cardiovascular disease risk factors: the Sogndal school-intervention study. Scand J Med Sci Sports. 2011; 21 (6): e122–31.
37. Rich C, Cortina-Borja M, Dezateux C, et al. Predictors of non-response in a UK-wide cohort study of children’s accelerometer-determined physical activity using postal methods. BMJ Open. 2013; 3 (3): e002290–2300.
38. Salmon J, Arundell L, Hume C, et al. A cluster-randomized controlled trial to reduce sedentary behavior and promote physical activity and health of 8–9 year olds: the Transform-Us! study. BMC Public Health. 2011; 11: 759.
39. Scruggs PW. Pedometer steps/min in physical education: does the pedometer matter? J Sci Med Sport. 2013; 16 (1): 36–9.
40. Tomkinson GR, Olds TS. Secular changes in pediatric aerobic fitness test performance: the global picture. Med Sport Sci. 2007; 50: 46–66.
41. Trost SG, McIver KL, Pate RR. Conducting accelerometer-based activity assessments in field-based research. Med Sci Sports Exerc. 2005; 37 (11 Suppl): S531–43.
42. Ulrich DA. Test of Gross Motor Development Examiner’s Manual. 2nd ed. Austin (TX): PRO-ED; 2000. p. 60.
43. Van Der Horst K, Paw MJCA, Twisk JWR, Van Mechelen W. A brief review on correlates of physical activity and sedentariness in youth. Med Sci Sports Exerc. 2007; 39 (8): 1241–50.
Keywords:

LOW INCOME; CHILDREN; PRIMARY SCHOOL; CARDIORESPIRATORY FITNESS; FUNDAMENTAL MOVEMENT SKILLS; SOCIOECOLOGICAL

© 2015 American College of Sports Medicine