Exploring the effectiveness of a school-based physical activity policy in British Columbia, Canada: a mixed-methods observational study

Exploring the effectiveness of a school-based physical activity policy in British Columbia,... Abstract The Daily Physical Activity (DPA) policy in British Columbia requires elementary schools to help students achieve 30 min of physical activity during instructional and noninstructional time on school days. The purpose of this study was to determine how elementary teachers implement the DPA policy, and examine differences in children’s light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA) at school, based on how the teacher implemented the DPA policy during the school day (provision of DPA during instructional time or only noninstructional time). In this observational mixed-methods study, 12 teachers were interviewed on their implementation approaches. Teachers provided DPA opportunities during instructional time (i.e., prescriptive implementers, n = 9) or relied on students to be active during noninstructional times (i.e., nonprescriptive, n = 3). Next, 10 students from each interviewed teacher’s classroom were randomly selected to wear accelerometers for one school week. Hierarchical linear modeling was used to examine the contribution of teacher’s implementation strategy on student’s activity levels. t-Tests examined differences in students’ activity levels between implementation groups. Teacher’s DPA implementation strategy accounted for a significant proportion of variance in student’s activity throughout the school day (p’s < .05). The prescriptive group (n = 88) was more active (LPA and MVPA) and spent a greater proportion of their school days in MVPA during instructional time than the nonprescriptive group (n = 23). Heterogeneity in policy implementation creates variations in policy effectiveness. Students provided with opportunities to be active during instructional time may accumulate more MVPA compared with those who are not given these opportunities. Registration: Not applicable. Implications Practice: Providing additional opportunities for children to be active during classroom time may help children to meet their daily physical activity requirements. Policy: Policymakers should strengthen the Daily Physical Activity (DPA) policy statement to include specific requirements for implementation, including the requirement to deliver DPA during instructional time, and improve monitoring procedures of adherence. Research: Additional research is needed to examine the effectiveness of the DPA policy on children’s PA outcomes in BC, with specific focus on the impact of teacher DPA implementation method. BACKGROUND Physical activity (PA) is essential to the physiological and psychosocial health and development of children [1, 2]. As such, authoritative national and international organizations provide guidelines recommending minimum levels of PA required to achieve optimal benefits [3–6]. In Canada, it is recommended that children participate in a minimum of 60 min of moderate-to-vigorous physical activity (MVPA) every day [7]; however, the majority of children are failing to meet these guidelines [8]. Physical inactivity in childhood is a risk factor for being overweight or obese [9], which can persist into adulthood [10]. Public health–governing bodies have prioritized initiatives to help combat physical inactivity and obesity amongst children [3, 11, 12], often targeting schools as an environment through which to deliver PA initiatives [13, 14]. Policy is a potentially effective tool to change practices in schools to support PA of children on a more permanent basis [15, 16], and governments within Canada, as well as the UK and the USA, have introduced school policies to promote PA in children. A review by Lagarde and LeBlanc [13] identified that some PA policies have the potential to increase children’s PA, such as improving the quality and variety of physical education (PE) and requiring mandatory qualifications for PE teachers and adequate facilities. In 2008, the Ministry of Education in British Columbia (BC), Canada mandated a Daily Physical Activity (DPA) policy, requiring elementary schools to help students in grades kindergarten to seven achieve at least 30 min of PA between the instructional (within-class) and noninstructional (lunch and recess) school time [17]. Similar policies have been mandated in Ontario [18] and Alberta [19]. The impact of school-based PA policies is rarely evaluated [20]; however, some research has examined the impact of Ontario’s DPA policy on student PA. Hobin et al. [21] examined school-level characteristics associated with student self-reported PA in Ontario and found that student PA was associated with the frequency of PE per week but not the schools’ chosen DPA implementation model (i.e., DPA only on days without PE, in addition to daily PE, or as part of daily PE). Stone et al. [22] used accelerometers and classroom schedules to compare total PA and sustained bouts of MVPA with the frequency of DPA schedule. They found that less than half of the students received DPA every day and no child engaged in sustained MVPA for 20 min as required by Ontario’s DPA guidelines. However, children who were offered DPA every day were significantly more active than those who did not receive DPA. In a large cross-sectional study of more than 2,000 elementary students in Ontario, Leatherdale et al. [23] found that 80 per cent of their included schools were actively implementing the DPA policy; however, this school indicator was not significantly associated with a student classified as being moderately active. In British Columbia, the impact of the DPA policy on student PA levels has not yet been examined [24, 25]. The effectiveness of school-based PA policies at the student-level depends on their implementation at the school- and classroom-level [26], and thus, it is important to examine and link implementation processes to impacts/outcomes. Unfortunately, the policy does not mandate how schools or teachers must implement DPA during the school day [17]. As a result, teachers’ DPA implementation approach may vary and have a heterogeneous effect on student’s PA levels. Mâsse et al. [26] examined teachers’ DPA implementation styles in BC and identified that teachers approach implementation either prescriptively or nonprescriptively. Prescriptive approaches required all students to participate by scheduling more PA opportunities during instructional hours, including more PE classes, activity breaks, and embedding PA within curriculum subjects. Nonprescriptive styles provided more opportunities for PA, often during noninstructional time, but did not require students to participate (e.g., intramural programs, running/walking clubs, and open access to facilities). The present study was part of a two-phased study in British Columbia. In the first phase of this study [25], we explored the barriers and facilitators influencing the implementation of the DPA policy in a small sample of elementary school teachers and compared factors according to how teachers implemented the policy during the instructional school day. Currently, it is unknown how different implementation approaches affect students’ achievement of the DPA policy requirements [26]. Understanding the extent of these differences, if any, would provide policy makers with evidence on how to improve and strengthen policy guidelines and could inform future implementation practices. The aim of this follow-up study was to explore the differences in children’s PA according to how the teacher implemented the DPA policy during the school day (provision of DPA during instructional time or only noninstructional time). PURPOSE This study had two primary research objectives. The first objective was to describe how teachers implemented the DPA policy during instructional versus noninstructional school time. The second objective was to examine whether students were meeting DPA guidelines and to examine whether teachers’ DPA implementation approach affected their student’s PA during the school day. To examine when PA was occurring, we also examined student’s activity on the different parts of school day (instructional vs. noninstructional time). Although the DPA policy does not specify PA intensity requirements, the overall purpose of the school policy is to help students achieve half of the Canadian PA guidelines of 60 min of MVPA per day while at school [17]. Given that PA in the moderate-to-vigorous intensity levels help children achieve optimal health, this study compares MVPA levels of students at school as a marker for meeting DPA requirements. Based on the available research examining DPA effectiveness in Ontario [21–23], it was hypothesized that (1) children at school would not meet the DPA policy requirements of 30 min of MVPA during the school day. To examine whether teacher’s DPA implementation approach affected MVPA, it was hypothesized that (2a) teacher implementation approach would account for a significant amount of variance in their student’s MVPA during the school day. Next, it was hypothesized that (2b) children in prescriptive DPA classes would accumulate more MVPA during the entire school day than children in nonprescriptive classes. Since it is possible that DPA implementation may result in PA that is of a lower intensity than moderate-to-vigorous, light physical activity (LPA) was also examined. It was hypothesized that teacher’s DPA implementation approach would account for a significant amount of variance in their student’s (3a) total LPA, and that children in prescriptive DPA classes would accumulate (3b) more LPA during the entire school day than children in nonprescriptive classes. To determine when total MVPA minutes occurred during the school day, we examined the differences in time spent in MVPA during instructional and noninstructional time. It was hypothesized that (4a) implementation strategy would account for a significant amount of variance in MVPA during instructional time, and (4b) the prescriptive group would accumulate more instructional MVPA minutes than the nonprescriptive group. For noninstructional time, it was hypothesized that there would be no differences between the groups, since both groups of children were left to use this time as they chose. METHODS Overall design This observational study was part of a larger research project using multiple data collection methods that explored the implementation and effectiveness of the DPA policy in BC. This paper examines the differences in children’s PA at school during different DPA delivery methods. Teacher interviews were conducted to explore how teachers implement the DPA policy during the instructional and noninstructional school day. Following teacher interviews, a random sample of children from each class wore an accelerometer to objectively measure PA at school for one school week (5 days). The STROBE checklist for observational studies [27] guided reporting of this study (Supplementary Material). Sample selection and recruitment Recruitment of schools and teachers has been described elsewhere [25]. Briefly, one school district from British Columbia was approached and provided ethical approval to participate in this study. Principals from 13 public elementary schools (42% response rate) provided approval for their school to participate. Grades 4, 5, and 6 teachers from these schools were eligible to participate if they had at least 1 year of experience teaching at an elementary school level and were currently teaching in the 2015–2016 academic year. Thirty-three (of 40) teachers from 11 of these schools (83% response rate) provided written consent to participate in a short survey and potentially participate in an interview. The short survey consisted of two questions relating to the teacher’s DPA implementation approach: (i) What is the most common implementation strategy you use to implement DPA in your classroom (i.e., in addition to daily PE class, as part of daily PE class, only on days with no PE class, I don’t implement DPA (the students are active as recess and/or lunch), none of the above/other) and (ii) explain in detail how you implement DPA during the school day (open-ended question). The survey was used as a device solely to assist in selecting teachers to interview and we aimed to recruit teachers who differed in how they implemented DPA during the instructional and noninstructional school days. The interviews were used to clarify whether DPA was provided during the instructional or noninstructional school days (not always evident based on survey responses) and understand how each teacher delivered DPA during these times. In total, 12 teachers (4 males, 8 females) from 10 schools were chosen for the interview (Mage = 45.83, SD = 9.90) with teaching experience varying from 5 to 34 years (M = 16.25, SD = 9.50). Of those teachers who were interviewed, one teacher taught grade 4, three teachers taught grade 4/5, two teachers taught grade 5, four teachers taught grade 5/6, and two teachers taught grade 6. Nine teachers reported providing additional opportunities for students to be active during instructional time (herein referred to as prescriptive approaches), whereas three teachers relied on students being active during noninstructional lunch and recess breaks (herein referred to as nonprescriptive approaches). Regarding school characteristics, school size was based on total school enrollment number, and Statistics Canada 2016 census profile results (http://www12.statcan.gc.ca/census-recensement/index-eng.cfm?HPA=1) were used to determine median total income of households in 2015 and population density per square kilometer by each school’s postal code. The average school size for prescriptive and nonprescriptive schools was 361 and 401, respectively. The median total income of households in the corresponding regional district (for which each school was located) was $71,127. The average median total income for prescriptive schools was $83,833 and $78,496 for the nonprescriptive schools. The average population density per square kilometer for prescriptive and nonprescriptive schools was 1484.1 and 1368.7, respectively. All students from each interviewed teachers’ classroom were eligible and invited to participate unless they provided a reason why they must not engage in PA (i.e., injury, pre-existing condition) or were absent on recruitment day (n = 20). In total, 326 of 350 (93.1%) students were willing and eligible to participate, 4 children were ineligible, and 20 children (5.7%) refused to participate. From those students who wanted to participate and were present, random sampling, stratified for sex, was used to recruit 10 children (5 males, 5 females) within each class. Informed written parent consent and child assent was obtained for each student. Data collection Interviews Semistructured interviews were conducted with 12 teachers between February and April 2016. Interviews consisted of open-ended questions relating to the following: (i) DPA implementation approaches and (ii) factors (i.e., barriers and facilitators) influencing implementation of DPA (analysis of implementation factors presented in Weatherson et al. [25]). The present manuscript reports on teachers’ responses about their implementation approaches. The interview consisted of four questions regarding teachers DPA implementation approaches, including the following: (i) How is the DPA policy implemented at your school? Does your school provide any guidelines on how to do so? (ii) How do you implement the DPA policy in your classroom? (iii) What is your most common strategy to implement DPA in your classroom? (iv) Why do you choose some activities over others? Verbal consent was obtained from each participant to audio-record the interview and participants received a monetary reimbursement ($40) for their participation. Physical activity Accelerometer data collection occurred from March to June 2016. Students were assigned a numbered accelerometer to wear for the entire school day for five consecutive school days. Students were instructed to wear the accelerometers around the waist with the unit placed on the right hip and reminded to participate in their typical activities at recess and lunch break. For those students not randomly selected to participate, they were given a low-cost pedometer during the data collection period, with similar instructions. To increase wear compliance, children (participants and nonparticipants) were provided with a PA device log whereby they were given a sticker to record their wear of their device (upon returning their respective device to the teacher at the end of each day). At the end of the week, each student was awarded with a pedometer to keep if they wore their respective device for the entire data collection period. Classroom teachers were reminded to teach as they would on any normal school day (i.e., keeping with their DPA implementation approach) and were provided with a blank time table in which to log and record the times at which recess, lunch, and PE occurred, as well as when DPA was implemented (if applicable). Measures Implementation approach Digital recordings were transcribed verbatim directly into NVivo qualitative data analysis software [28] and interview transcripts were checked for accuracy by the interviewer. Responses to the interview questions were summarized descriptively. In addition, the time tables were collected at the end of the week and used to confirm that each teacher held to their reported implementation approach during accelerometer data collection (i.e., did not change as a result of being observed): the prescriptive teachers recorded a DPA block during regular instructional time, whereas the nonprescriptive teachers did not have these blocks recorded (only lunch and recess breaks). Objective physical activity The ActiGraph wGT3X-BT accelerometer (ActiGraphTM, LCC, Fort Walton Beach, FL, USA) was used to measure children’s movement at school. The ActiGraph wGT3X-BT accelerometer has been validated by indirect calorimetry in youth [29]. ActiLife software version 6.13.2 [30] (ActiGraph, Pensacola, Florida) was used to download raw acceleration data (Axis 1) into activity counts summed at 15 s epoch lengths. A valid day was defined as a ratio of school time, with children required to wear the accelerometer for at least 80 per cent of the school day [31]. Each student needed at least 3 valid wear days to be included in the analysis. Further details for accelerometer data processing and cleaning are available in Supplementary Material. Accelerometer data were analyzed using Evenson et al. [32] 15 s count cut-points for children: 26–573 (LPA) and ≥574 (MVPA). The classroom time table was used to categorize (i) total school day, (ii) noninstructional time (recess and lunch break), and (iii) instructional time. All school days were 360 min (from 8:30 am to 2:30 pm). Amount of noninstructional time ranged from 40 to 51 min per day across schools (M = 45.63, SD = 3.50). An independent-samples t-test indicated that there was a significant difference in noninstructional minutes per day between groups such that the prescriptive group received fewer minutes of recess/lunch break per day (M = 44.72, SD = 3.05) than the nonprescriptive group (M = 49.17, SD = 2.82); t(109) = −6.34, p < .001. To statistically control for this, all statistical tests compared percent proportion of instructional or noninstructional school time spent in LPA and MVPA (not mean minutes). Statistical analyses Descriptive analyses were run using SPSS (Version 24) [33]. Assumptions were examined and managed according to recommendations by Field [34] and Tabacknick and Fidell [35]. Group means are presented to determine whether students met the DPA policy guidelines (hypothesis 1). Hierarchical linear models (HLMs) were run using HLM7 software [36] to examine the contribution of teacher’s implementation strategy (teacher-level predictor) on student’s activity levels (student-level outcome; hypotheses 2–4). Age and sex (student-level variables) were added into the model as covariates given past research demonstrating their influence on students’ activity levels [37]. Intraclass correlation coefficients (ICCs) were calculated to examine the proportion of variance in students’ activity that was attributable to teacher-level factors and to student-level factors. Chi-square difference tests (χ2) were run to examine whether adding implementation strategy significantly improved the model compared with the null model. The total amount of variance accounted for by teacher’s implementation strategy in students’ PA was calculated by multiplying the amount of variance at the teacher-level accounted for by implementation and the amount of variance that the teacher-level accounted for in the PA outcomes. Finally, follow-up between-subjects t-tests were run to examine differences in students’ activity levels between prescriptive and nonprescriptive implementation groups (hypotheses 2–4). Differences between estimates were considered statistically significant at p < .05. RESULTS Implementation approaches In the interviews, each teacher reported that their respective school did not provide guidelines as to how they were to implement DPA during the instructional and noninstructional school day and thus each teacher had the autonomy to implement the policy as they saw fit. Within the prescriptive group, most teachers reported offering indoor and outdoor activities that were structured/organized (e.g., stretching, running laps, exercise circuits, games/sports, and aerobic or dance videos) and few offered unstructured (e.g., free time play). Some of these teachers offered a combination of these activities. Most of the activities were provided as breaks from teaching; however, two teachers embedded activity into curriculum material (academic lessons). The amount of time allotted to these activities was typically 15 min, although a few teachers provided multiple breaks per day. Two teachers tried to schedule an extra PE class per week if the gym was available. Five of the prescriptive teachers scheduled DPA into their time table at the same time each day while the rest offered PA during curriculum transitions or when the students became restless. Five of the teachers using a prescriptive style offered PA opportunities to their students only on days with no PE, whereas the other four offered opportunities in addition to PE class; however, the number of scheduled PE classes ranged from 1 to 4 per week. The teachers who used a prescriptive approach reported doing so because they did not believe that children were active on their recess and lunch breaks. They believed that providing opportunities during instructional time helped them to be confident that children would meet the guidelines. The teachers who used a nonprescriptive approach did not provide any opportunities for children to be active during instructional time (beyond scheduled PE class) because they believed that their students were active on their own volition during recess and lunch, and this time (approximately 60 min) was sufficient for them to meet the DPA guidelines. One nonprescriptive teacher also emphasized that students have the option to participate in extracurricular sports. Given our small sample and the variety of activities used by teachers to meet the DPA guidelines in this study (especially within the prescriptive group), the only characteristic across our sample that allowed us to broadly group our teachers was whether they provided PA opportunities during the instructional or noninstructional school day, and thus, the classification names derived from Mâsse et al. [26] were deemed appropriate. The two groups were confirmed through the classroom time tables provided by teachers during accelerometer data collection, with prescriptive teachers writing DPA down in their time table. Participant demographics At recruitment, 119 children (60 males, 59 females), aged 9–12 years (Mage = 10.50, SD = 0.97) provided consent and wore accelerometers for 1 week at school. In total, 111 students (56 females, 55 males) were included in the analyses. Participant demographics by implementation group and total sample are displayed in Table 1. A chi-square test showed no significant difference in sex between implementation approach group (p = .51). An independent-samples t-test showed a significant difference in mean age between groups such that the nonprescriptive group was older (Mage = 11.39, SD = 0.58) than the prescriptive group (Mage = 10.17, SD = 0.84; t(93) = −6.50, p < .001). Table 1 Student demographics Prescriptive (n = 88) Nonprescriptive (n = 23) Total (n = 111) Sex, % Female 48.9 (43) 56.5 (13) 50.5 (56) Male 51.1 (45) 43.5 (10) 49.5 (55) Age (years), % 9 18.2 (16) 0.0 (0) 14.4 (16) 10 36.4 (32) 4.3 (1) 29.7 (33) 11 22.7 (20) 52.3 (12) 28.8 (32) 12 4.5 (4) 43.5 (10) 12.6 (14) missing 18.2 (16) 0.0 (0) 14.4(16) Grade, % 4 15.9 (14) 0.0 (0) 12.6 (14) 4/5 22.7 (20) 0.0 (0) 18.0 (20) 5 38.6 (34) 0.0 (0) 30.6 (34) 5/6 22.7 (20) 30.4 (7) 24.3 (27) 6 0.0 (0) 69.6 (16) 14.5 (16) Prescriptive (n = 88) Nonprescriptive (n = 23) Total (n = 111) Sex, % Female 48.9 (43) 56.5 (13) 50.5 (56) Male 51.1 (45) 43.5 (10) 49.5 (55) Age (years), % 9 18.2 (16) 0.0 (0) 14.4 (16) 10 36.4 (32) 4.3 (1) 29.7 (33) 11 22.7 (20) 52.3 (12) 28.8 (32) 12 4.5 (4) 43.5 (10) 12.6 (14) missing 18.2 (16) 0.0 (0) 14.4(16) Grade, % 4 15.9 (14) 0.0 (0) 12.6 (14) 4/5 22.7 (20) 0.0 (0) 18.0 (20) 5 38.6 (34) 0.0 (0) 30.6 (34) 5/6 22.7 (20) 30.4 (7) 24.3 (27) 6 0.0 (0) 69.6 (16) 14.5 (16) View Large Table 1 Student demographics Prescriptive (n = 88) Nonprescriptive (n = 23) Total (n = 111) Sex, % Female 48.9 (43) 56.5 (13) 50.5 (56) Male 51.1 (45) 43.5 (10) 49.5 (55) Age (years), % 9 18.2 (16) 0.0 (0) 14.4 (16) 10 36.4 (32) 4.3 (1) 29.7 (33) 11 22.7 (20) 52.3 (12) 28.8 (32) 12 4.5 (4) 43.5 (10) 12.6 (14) missing 18.2 (16) 0.0 (0) 14.4(16) Grade, % 4 15.9 (14) 0.0 (0) 12.6 (14) 4/5 22.7 (20) 0.0 (0) 18.0 (20) 5 38.6 (34) 0.0 (0) 30.6 (34) 5/6 22.7 (20) 30.4 (7) 24.3 (27) 6 0.0 (0) 69.6 (16) 14.5 (16) Prescriptive (n = 88) Nonprescriptive (n = 23) Total (n = 111) Sex, % Female 48.9 (43) 56.5 (13) 50.5 (56) Male 51.1 (45) 43.5 (10) 49.5 (55) Age (years), % 9 18.2 (16) 0.0 (0) 14.4 (16) 10 36.4 (32) 4.3 (1) 29.7 (33) 11 22.7 (20) 52.3 (12) 28.8 (32) 12 4.5 (4) 43.5 (10) 12.6 (14) missing 18.2 (16) 0.0 (0) 14.4(16) Grade, % 4 15.9 (14) 0.0 (0) 12.6 (14) 4/5 22.7 (20) 0.0 (0) 18.0 (20) 5 38.6 (34) 0.0 (0) 30.6 (34) 5/6 22.7 (20) 30.4 (7) 24.3 (27) 6 0.0 (0) 69.6 (16) 14.5 (16) View Large Fulfillment of DPA guidelines (hypothesis 1) Table 2 displays the average minutes and percent proportions of LPA and MVPA accumulated during the total, noninstructional, and instructional school day across the total sample, as well as for each implementation group. In support of hypothesis 1, children in the total sample did not meet the DPA guidelines of 30 min of MVPA on DPA days (∼29.7 min MVPA). However, children in the prescriptive group met the DPA guidelines (32.2 min MVPA). Table 2 Mean minutes and proportion of instructional, noninstructional and total SB, LPA, and MVPA by implementation approach group and total sample Prescriptive (n = 88) Nonprescriptive (n = 23) Total (n = 111) Mean minutes (SD) Proportion (SD)a Mean minutes (SD) Proportion (SD) Mean minutes (SD) Proportion (SD) Instructional LPA 94.99 (20.66) 30.1 (6.6) 76.94 (24.21) 24.8 (7.9) 91.25 (22.55) 29.0 (7.16) MVPA 19.03 (6.06) 6.0 (1.9)** 10.77 (4.98) 3.5 (1.6)** 17.32 (6.74) 5.5 (2.11) Noninstructional LPA 19.05 (4.10) 42.5 (8.0) 24.35 (6.12) 49.4 (11.6) 20.15 (5.04) 43.9 (9.3) MVPA 13.19 (6.58) 29.7 (15.3)* 9.37 (4.69) 19.0 (9.3)* 12.40 (6.41) 27.5 (14.9) Total LPA 114.04 (22.12) 23.8 (5.1)** 101.29 (27.99) 19.4 (5.9)** 111.40 (23.88) 22.9 (5.52) MVPA 32.22 (10.9) 5.1 (1.6)** 20.14 (8.43) 2.9 (1.3)** 29.72 (11.51) 4.64 (1.77) Meeting DPA? Yes X No X X Prescriptive (n = 88) Nonprescriptive (n = 23) Total (n = 111) Mean minutes (SD) Proportion (SD)a Mean minutes (SD) Proportion (SD) Mean minutes (SD) Proportion (SD) Instructional LPA 94.99 (20.66) 30.1 (6.6) 76.94 (24.21) 24.8 (7.9) 91.25 (22.55) 29.0 (7.16) MVPA 19.03 (6.06) 6.0 (1.9)** 10.77 (4.98) 3.5 (1.6)** 17.32 (6.74) 5.5 (2.11) Noninstructional LPA 19.05 (4.10) 42.5 (8.0) 24.35 (6.12) 49.4 (11.6) 20.15 (5.04) 43.9 (9.3) MVPA 13.19 (6.58) 29.7 (15.3)* 9.37 (4.69) 19.0 (9.3)* 12.40 (6.41) 27.5 (14.9) Total LPA 114.04 (22.12) 23.8 (5.1)** 101.29 (27.99) 19.4 (5.9)** 111.40 (23.88) 22.9 (5.52) MVPA 32.22 (10.9) 5.1 (1.6)** 20.14 (8.43) 2.9 (1.3)** 29.72 (11.51) 4.64 (1.77) Meeting DPA? Yes X No X X Noninstructional time includes recess and lunch breaks. LPA light physical activity; MVPA moderate-to-vigorous physical activity; DPA Daily Physical Activity. aIn this table, proportion means the percentage of the designated time spent in each outcome variable. For example, the prescriptive group spent 23.8% of their total school days in LPA, which resulted in a mean of 114.0 min. Independent-sample t-tests were used to determine significant proportional differences between groups with *p < .01; **p < .001. View Large Table 2 Mean minutes and proportion of instructional, noninstructional and total SB, LPA, and MVPA by implementation approach group and total sample Prescriptive (n = 88) Nonprescriptive (n = 23) Total (n = 111) Mean minutes (SD) Proportion (SD)a Mean minutes (SD) Proportion (SD) Mean minutes (SD) Proportion (SD) Instructional LPA 94.99 (20.66) 30.1 (6.6) 76.94 (24.21) 24.8 (7.9) 91.25 (22.55) 29.0 (7.16) MVPA 19.03 (6.06) 6.0 (1.9)** 10.77 (4.98) 3.5 (1.6)** 17.32 (6.74) 5.5 (2.11) Noninstructional LPA 19.05 (4.10) 42.5 (8.0) 24.35 (6.12) 49.4 (11.6) 20.15 (5.04) 43.9 (9.3) MVPA 13.19 (6.58) 29.7 (15.3)* 9.37 (4.69) 19.0 (9.3)* 12.40 (6.41) 27.5 (14.9) Total LPA 114.04 (22.12) 23.8 (5.1)** 101.29 (27.99) 19.4 (5.9)** 111.40 (23.88) 22.9 (5.52) MVPA 32.22 (10.9) 5.1 (1.6)** 20.14 (8.43) 2.9 (1.3)** 29.72 (11.51) 4.64 (1.77) Meeting DPA? Yes X No X X Prescriptive (n = 88) Nonprescriptive (n = 23) Total (n = 111) Mean minutes (SD) Proportion (SD)a Mean minutes (SD) Proportion (SD) Mean minutes (SD) Proportion (SD) Instructional LPA 94.99 (20.66) 30.1 (6.6) 76.94 (24.21) 24.8 (7.9) 91.25 (22.55) 29.0 (7.16) MVPA 19.03 (6.06) 6.0 (1.9)** 10.77 (4.98) 3.5 (1.6)** 17.32 (6.74) 5.5 (2.11) Noninstructional LPA 19.05 (4.10) 42.5 (8.0) 24.35 (6.12) 49.4 (11.6) 20.15 (5.04) 43.9 (9.3) MVPA 13.19 (6.58) 29.7 (15.3)* 9.37 (4.69) 19.0 (9.3)* 12.40 (6.41) 27.5 (14.9) Total LPA 114.04 (22.12) 23.8 (5.1)** 101.29 (27.99) 19.4 (5.9)** 111.40 (23.88) 22.9 (5.52) MVPA 32.22 (10.9) 5.1 (1.6)** 20.14 (8.43) 2.9 (1.3)** 29.72 (11.51) 4.64 (1.77) Meeting DPA? Yes X No X X Noninstructional time includes recess and lunch breaks. LPA light physical activity; MVPA moderate-to-vigorous physical activity; DPA Daily Physical Activity. aIn this table, proportion means the percentage of the designated time spent in each outcome variable. For example, the prescriptive group spent 23.8% of their total school days in LPA, which resulted in a mean of 114.0 min. Independent-sample t-tests were used to determine significant proportional differences between groups with *p < .01; **p < .001. View Large Impact of teachers’ implementation strategy on student’s activity (hypotheses 2–3) Regarding hypothesis 2a, teacher-level factors accounted for a large proportion of the variance in student’s MVPA during the school day (ICC = 0.4375). After controlling for age (p = .832) and sex (p < .001) at the student-level, teacher’s implementation strategy was a significant predictor of student’s MVPA (t = 4.239, p < .01) and significantly improved the model (χ2 difference = 61.80, df = 3, p < .001). Implementation strategy accounted for 57.14 per cent of the teacher-level variance and 25 per cent of the total variance in student’s MVPA. Regarding hypothesis 2b, follow-up t-tests revealed that the prescriptive group spent a greater percent proportion of their school days in MVPA (M = 5.1, SD = 1.6) compared with the nonprescriptive group (M = 2.9, SD = 1.3; t(109) = 5.95, p < .001, g = 1.39). Regarding hypothesis 3a, teacher-level factors accounted for a small proportion of the variance in student’s LPA during the school day (ICC = 0.1877). Teacher’s implementation strategy significantly improved the prediction of student’s LPA (t = 2.18, p < .05; χ2 difference = 32.78, df = 3, p < .001) after controlling for age (p = .17) and sex (p < .05). Implementation strategy accounted for 69.09 per cent of the teacher-level variance and 12.96 per cent of the total variance in student’s LPA. The prescriptive group spent a greater percent proportion of their school days in LPA (M = 23.8, SD = 5.1) compared with the nonprescriptive group (M = 19.4, SD = 5.9; t(109) = 3.60, p < .001, g = 0.84). Impact of teachers’ implementation strategy on MVPA during instructional and noninstructional time (hypothesis 4) Teacher-level factors accounted for a small proportion of the variance in student’s MVPA during instructional time (ICC = 0.2820). After controlling for age (p = .32) and sex (p < .01), teacher’s implementation strategy was a significant predictor of student’s MVPA during instructional time (t = 4.05, p < .001) and significantly improved the model (χ2 difference = 57.94, df = 3, p < .001). Teachers’ implementation strategy accounted for 36.36 per cent of the teacher-level variance and 10.3 per cent of the total variance in student’s MVPA during instructional time. The prescriptive group spent a greater percent proportion in MVPA during instructional time (M = 6.0, SD = 1.9) than the nonprescriptive group (M = 3.5, SD = 1.6; t(109) = 5.91, p < .001, g = 1.38). Teacher-level factors accounted for a small proportion of the variance in student’s MVPA during noninstructional time (ICC = 0.0865). After controlling for age (p = .58) and sex (p < .01), teacher’s implementation strategy was a significant predictor of student’s MVPA during noninstructional time (t = 2.57, p < .01), but did not significantly improve the model (χ2 difference = 3.83, df = 3, p = .28). Implementation strategy accounted for 69.19 per cent of the teacher-level variance and 5.98 per cent of the total variance in student’s MVPA during noninstructional time. Compared with the nonprescriptive group (M = 19.0, SD = 9.3), the prescriptive group spent a greater percent proportion in MVPA during noninstructional time (M = 29.7, SD = 15.3; t(109) = 3.19, p < .01, g = 0.74). DISCUSSION The implementation of school-based PA policies, which govern the amount of PA children obtain while at school, is a recommended public health strategy to support the development of PA behaviors in school-aged children. This study aimed to measure the impact of teacher’s DPA policy implementation approach on children’s LPA and MVPA while at school. The findings from this study demonstrate that heterogeneity in policy implementation can create variations in policy effectiveness. Overall, teacher’s DPA implementation strategy accounted for a significant and large proportion of variance in student’s activity throughout the school day, and the prescriptive group was more active (LPA and MVPA) than the nonprescriptive group. Furthermore, implementation strategy significantly predicted and accounted for a moderate proportion of variance in student’s MVPA during instructional time. Implementation strategy was also a significant predictor of MVPA during noninstructional time; however, it accounted for a small proportion of variance and it did not significantly improve the model. These findings underscore the impact of prescriptive approaches to DPA implementation on students’ MVPA specifically during instructional time. Although it may not guarantee that students meet policy recommendations, teachers who provide additional opportunities for students to be active during instructional time (i.e., beyond non-instructional breaks) may help students to accumulate more LPA and MVPA. Importantly, children who were provided with DPA opportunities during instructional time were more active during this time and were not less active during noninstructional time, resulting in more total MVPA accumulated during the school day. Continued efforts to increase children’s PA during the instructional school day are warranted for improving total daily PA levels in youth. It may seem intuitive that more opportunities for PA during instructional time equate to more PA overall. However, teachers using a prescriptive approach to DPA implementation offered a variety of activities, and it is possible that some of these activities may have provided a greater contribution to students’ daily MVPA than others. For example, teachers who provided active breaks (e.g., running laps) may have elicited more vigorous PA than teachers who incorporated PA into academic lessons. As currently phrased, the DPA policy guidelines allow for either of these PA approaches; however, it may be more beneficial for teachers to deliver active breaks as part of their existing practice to meet policy requirements. Extensive research, particularly in the USA, has examined the impact of these strategies on students’ PA at school. For example, students who receive short (10 min) activity breaks were more likely to obtain 30 min/day of MVPA during school [38]. Although the integration of PA into academic content is a more recent school-based PA intervention, this strategy has also shown promise at improving MVPA levels of children [39–41]. There are numerous factors that can influence the implementation and effectiveness of PA policies and programs in schools [42–44]. For example, a systematic review by Naylor et al. [45] examining the barriers to the implementation of school-based PA models identified common barriers, including a lack of time (competing instructional requirements, teacher overload), quality/availability of resources, supportive school climate (administrative support), availability of training, and teacher self-efficacy to deliver such programs. Understanding the barriers that influence teachers’ implementation of the DPA policy during instructional time is essential in providing context to these findings and developing effective strategies to overcome them (data presented in Weatherson et al. [25]). For example, teachers in this study lacked the knowledge on what or when constitutes appropriate delivery and fulfillment of the DPA policy guidelines. As a result, the teachers with a nonprescriptive approach believed that noninstructional breaks at recess and lunch provide sufficient time for students to achieve these guidelines. This belief may reflect the underlying motive of teachers who hold a nonprescriptive implementation approach. Although there were only three nonprescriptive teachers in this study, teachers who were interviewed reported that many of their colleagues took this approach to DPA implementation [25]. One potential intervention approach could be to modify these teachers’ perceptions that all children are active during recess and lunch breaks [46, 47] and educate them on the advantage of strategies that incorporate PA during class time (e.g., improvements in academic achievement) [48, 49]. Teachers in the prescriptive group tended to teach younger grades than the nonprescriptive teachers; thus, students in the prescriptive group were younger. Although age was included as a covariate in the analyses, it was not a significant predictor nor did it account for a significant proportion of variance in students’ activity. Since children become less active as they get older [50–52], the prescriptive group being younger may have accounted for some of the observed differences in MVPA. Additionally, both the prescriptive and the nonprescriptive teachers reported that it was more difficult to incorporate PA in classes with older children due to differences in curriculum demands and students’ lack of interest [25]. Strategies to enhance guideline adherence in higher grades may include teacher education on the benefits of PA on children’s learning and academic outcomes and training/workshops on how to engage and motivate older students in age-appropriate activities. Alternatively, policy guidelines may need to be modified to account for the decline in PA as children age. It may be necessary to mandate that DPA occurs during instructional time (similar to Ontario). Similar to other Canadian DPA policies that have had little to no impact on children’s PA levels [24], neither the total sample nor the nonprescriptive implementation group met the DPA guidelines of 30 min of MVPA. Furthermore, the children in this study were less physically active than other BC students. For example, Nettlefold and colleagues [46] measured PA in a group of 380 children (8–11 years) in another region of BC and found that male and female children spent 64 and 53 min of the school day, respectively, in MVPA. One explanation for these observed differences is that the former study was conducted closer to when the DPA policy was first mandated and it is possible that school-level priority of the policy has diminished over time. As time passes, ongoing evaluation of PA policies is imperative to maintain policy support, ensure accountability of stakeholders, inform future policy development (or refinement), and warrant ongoing implementation [11, 53]. STRENGTHS AND LIMITATIONS This study is novel in that it is the first study to explore the student-level effectiveness of the DPA policy in BC. The major strength of this study was the mixed methods design which simultaneously measured and linked PA outcomes to policy implementation approach. Another strength was the use of HLM analyses to account for the nested data. Although the size of the two implementation groups were unequal, heterogeneity of the variance was not violated. This along with a sample size that was smaller than recommended for HLM [54], due to the number of available accelerometers, could have reduced statistical power. Despite these potential limitations, we were still able to detect significant main effects. The use of observational methods is useful to evaluate applicability of policy in real-world settings; however, this design limits the interpretation of findings to relationships and we cannot say that DPA implementation caused one group to have higher PA levels compared with the other group. Relatedly, a primary challenge of observational designs is the issue of confounding. There are other student-level (e.g., weight status, participation in team sports) and school-level (e.g., school SES, use of PA as a reward vs. a punishment, established community partners) factors shown to influence children’s PA levels that were not accounted for in this study [23, 55]. The main strategy that drove sampling for this study was the purposeful sampling of elementary teachers. Although this sampling method provides diversity for qualitative purposes, it might not provide an adequate sample for quantitative inference or statistical analyses. Additionally, it was difficult to recruit teachers who took a nonprescriptive approach, which resulted in unequal group sizes and ages. It could be that teachers taking this approach did not want to participate in the study for appearing they were not following the policy. To account for this limitation, we used adjusted t-tests and controlled for sex and age wherever appropriate. IMPLICATIONS The purpose of any school-based PA policy is to help all students become more physically active; however, the enactment of a policy will not ensure its full implementation [56]. The findings from this study have several implications for policy and practice. In the area of policy, it is recommended that governing bodies strengthen PA policy guidelines by specifying types of PA required and implementation procedures needed to meet these aims. Based on their study investigating adoption and implementation of U.S. state-level PA policies during school, Carlson et al. [16] conclude that clear policy language and accountability is needed for schools to provide sufficient opportunities for PA. They provide several recommendations for policy makers to ensure the implementation necessary to have a significant impact on youth PA, including using stronger and more specific languages, such as MVPA rather than PA, including evaluation components to measure impact of school PA policies, and employing monitoring systems to track implementation of these policies. According to Olstad et al. [24], flexible delivery models, where teachers have autonomy in determining the PA delivery format, are common to Canadian DPA policies but can also hinder policy implementation and effectiveness. Integrating DPA into the instructional school day may be a necessary step to remedy inconsistent implementation practices and ensure that all children have equal opportunities for PA at school. PA policies can be an effective strategy to increase PA in children at school, given that they influence school practices to provide additional opportunities for PA across the whole school day [57]. As this study suggests, additional opportunities during instructional time, including PA breaks and active lessons, represent potential methods to increase children’s PA at school. Other interventions have improved children’s PA during instructional time by scheduling sufficient time for PE [56, 58], improving the quality of PE instruction using standardized curricula [59] and PE specialists [58]. Noninstructional time also provides another important opportunity for regular PA at school, during recess, and before- and after-school. For recess, schools that provide adult supervision [58, 60], access to game equipment [61, 62], and playground markings [63] have more physically active children. Encouraging active travel to- and from-school [64] and providing intramural/interscholastic PA programs [21] are other methods to enhance children’s PA during the school day. Overall, evidence suggests that schools that adopt a whole-school approach and implement multiple strategies have the greatest impact on students’ PA [42, 58]. Although a comprehensive, whole-school approach is warranted, policy makers must recognize that there are a myriad of multilevel factors, beyond policy elements, that interact to influence both the implementation of PA approaches and children’s’ PA behaviors at school. These factors include the school environment and organizational characteristics, teacher and classroom-related factors, attributes of students and their families, and characteristics of the PA approach itself [42]. Governing bodies and school districts must help foster an environment that is conducive to teachers’ provision of PA opportunities and students engagement in these opportunities. Although school administrators can support teachers in their efforts by promoting active classroom breaks/lessons during class time, it is recommended that provinces and districts provide and fund mandatory and ongoing teacher training, education, and resources for PA policy implementation. SUPPLEMENTARY MATERIAL Supplementary material is available at Translational Behavioral Medicine online. Acknowledgments We would like to thank the school district and teachers for their time and responses provided in the interviews and facilitating data collection in their classrooms. We thank all the students who were involved in the study. The first author received funding from the Canadian Institutes of Health Research—Canada Graduate Scholarship to conduct this research and the project was funded by a Michael Smith Foundation for Health Research grant (No. 5917) to the third author. Compliance with Ethical Standards Primary Data: We can confirm that this work is original, that the findings have not been previously published, and that the manuscript is not under consideration for publication elsewhere. The authors have full control of all primary data, which we allow the journal to review upon request. Authors’ Contributions: K.W. conceptualized the study, and M.J. provided intellectual input into the methodological design. K.W. collected the data, and K.W. and S.L. analyzed the data and drafted the manuscript. All authors reviewed and approved the final manuscript. Conflict of Interest: None declared. Ethical Approval: All procedures performed in this study involving human participants were in accordance with the 1964 Helsinki declaration and its later amendments or comparable ethical standards and ethical approval was obtained from the Canadian University’s Behavioral Research Ethics Board for research involving humans (no. 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The relationship between school physical activity policy and objectively measured physical activity of elementary school students: a multilevel model analysis . Arch Public Health . 2014 ; 72 ( 1 ): 20 . Google Scholar CrossRef Search ADS PubMed © Society of Behavioral Medicine 2018. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Translational Behavioral Medicine Oxford University Press

Exploring the effectiveness of a school-based physical activity policy in British Columbia, Canada: a mixed-methods observational study

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Abstract

Abstract The Daily Physical Activity (DPA) policy in British Columbia requires elementary schools to help students achieve 30 min of physical activity during instructional and noninstructional time on school days. The purpose of this study was to determine how elementary teachers implement the DPA policy, and examine differences in children’s light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA) at school, based on how the teacher implemented the DPA policy during the school day (provision of DPA during instructional time or only noninstructional time). In this observational mixed-methods study, 12 teachers were interviewed on their implementation approaches. Teachers provided DPA opportunities during instructional time (i.e., prescriptive implementers, n = 9) or relied on students to be active during noninstructional times (i.e., nonprescriptive, n = 3). Next, 10 students from each interviewed teacher’s classroom were randomly selected to wear accelerometers for one school week. Hierarchical linear modeling was used to examine the contribution of teacher’s implementation strategy on student’s activity levels. t-Tests examined differences in students’ activity levels between implementation groups. Teacher’s DPA implementation strategy accounted for a significant proportion of variance in student’s activity throughout the school day (p’s < .05). The prescriptive group (n = 88) was more active (LPA and MVPA) and spent a greater proportion of their school days in MVPA during instructional time than the nonprescriptive group (n = 23). Heterogeneity in policy implementation creates variations in policy effectiveness. Students provided with opportunities to be active during instructional time may accumulate more MVPA compared with those who are not given these opportunities. Registration: Not applicable. Implications Practice: Providing additional opportunities for children to be active during classroom time may help children to meet their daily physical activity requirements. Policy: Policymakers should strengthen the Daily Physical Activity (DPA) policy statement to include specific requirements for implementation, including the requirement to deliver DPA during instructional time, and improve monitoring procedures of adherence. Research: Additional research is needed to examine the effectiveness of the DPA policy on children’s PA outcomes in BC, with specific focus on the impact of teacher DPA implementation method. BACKGROUND Physical activity (PA) is essential to the physiological and psychosocial health and development of children [1, 2]. As such, authoritative national and international organizations provide guidelines recommending minimum levels of PA required to achieve optimal benefits [3–6]. In Canada, it is recommended that children participate in a minimum of 60 min of moderate-to-vigorous physical activity (MVPA) every day [7]; however, the majority of children are failing to meet these guidelines [8]. Physical inactivity in childhood is a risk factor for being overweight or obese [9], which can persist into adulthood [10]. Public health–governing bodies have prioritized initiatives to help combat physical inactivity and obesity amongst children [3, 11, 12], often targeting schools as an environment through which to deliver PA initiatives [13, 14]. Policy is a potentially effective tool to change practices in schools to support PA of children on a more permanent basis [15, 16], and governments within Canada, as well as the UK and the USA, have introduced school policies to promote PA in children. A review by Lagarde and LeBlanc [13] identified that some PA policies have the potential to increase children’s PA, such as improving the quality and variety of physical education (PE) and requiring mandatory qualifications for PE teachers and adequate facilities. In 2008, the Ministry of Education in British Columbia (BC), Canada mandated a Daily Physical Activity (DPA) policy, requiring elementary schools to help students in grades kindergarten to seven achieve at least 30 min of PA between the instructional (within-class) and noninstructional (lunch and recess) school time [17]. Similar policies have been mandated in Ontario [18] and Alberta [19]. The impact of school-based PA policies is rarely evaluated [20]; however, some research has examined the impact of Ontario’s DPA policy on student PA. Hobin et al. [21] examined school-level characteristics associated with student self-reported PA in Ontario and found that student PA was associated with the frequency of PE per week but not the schools’ chosen DPA implementation model (i.e., DPA only on days without PE, in addition to daily PE, or as part of daily PE). Stone et al. [22] used accelerometers and classroom schedules to compare total PA and sustained bouts of MVPA with the frequency of DPA schedule. They found that less than half of the students received DPA every day and no child engaged in sustained MVPA for 20 min as required by Ontario’s DPA guidelines. However, children who were offered DPA every day were significantly more active than those who did not receive DPA. In a large cross-sectional study of more than 2,000 elementary students in Ontario, Leatherdale et al. [23] found that 80 per cent of their included schools were actively implementing the DPA policy; however, this school indicator was not significantly associated with a student classified as being moderately active. In British Columbia, the impact of the DPA policy on student PA levels has not yet been examined [24, 25]. The effectiveness of school-based PA policies at the student-level depends on their implementation at the school- and classroom-level [26], and thus, it is important to examine and link implementation processes to impacts/outcomes. Unfortunately, the policy does not mandate how schools or teachers must implement DPA during the school day [17]. As a result, teachers’ DPA implementation approach may vary and have a heterogeneous effect on student’s PA levels. Mâsse et al. [26] examined teachers’ DPA implementation styles in BC and identified that teachers approach implementation either prescriptively or nonprescriptively. Prescriptive approaches required all students to participate by scheduling more PA opportunities during instructional hours, including more PE classes, activity breaks, and embedding PA within curriculum subjects. Nonprescriptive styles provided more opportunities for PA, often during noninstructional time, but did not require students to participate (e.g., intramural programs, running/walking clubs, and open access to facilities). The present study was part of a two-phased study in British Columbia. In the first phase of this study [25], we explored the barriers and facilitators influencing the implementation of the DPA policy in a small sample of elementary school teachers and compared factors according to how teachers implemented the policy during the instructional school day. Currently, it is unknown how different implementation approaches affect students’ achievement of the DPA policy requirements [26]. Understanding the extent of these differences, if any, would provide policy makers with evidence on how to improve and strengthen policy guidelines and could inform future implementation practices. The aim of this follow-up study was to explore the differences in children’s PA according to how the teacher implemented the DPA policy during the school day (provision of DPA during instructional time or only noninstructional time). PURPOSE This study had two primary research objectives. The first objective was to describe how teachers implemented the DPA policy during instructional versus noninstructional school time. The second objective was to examine whether students were meeting DPA guidelines and to examine whether teachers’ DPA implementation approach affected their student’s PA during the school day. To examine when PA was occurring, we also examined student’s activity on the different parts of school day (instructional vs. noninstructional time). Although the DPA policy does not specify PA intensity requirements, the overall purpose of the school policy is to help students achieve half of the Canadian PA guidelines of 60 min of MVPA per day while at school [17]. Given that PA in the moderate-to-vigorous intensity levels help children achieve optimal health, this study compares MVPA levels of students at school as a marker for meeting DPA requirements. Based on the available research examining DPA effectiveness in Ontario [21–23], it was hypothesized that (1) children at school would not meet the DPA policy requirements of 30 min of MVPA during the school day. To examine whether teacher’s DPA implementation approach affected MVPA, it was hypothesized that (2a) teacher implementation approach would account for a significant amount of variance in their student’s MVPA during the school day. Next, it was hypothesized that (2b) children in prescriptive DPA classes would accumulate more MVPA during the entire school day than children in nonprescriptive classes. Since it is possible that DPA implementation may result in PA that is of a lower intensity than moderate-to-vigorous, light physical activity (LPA) was also examined. It was hypothesized that teacher’s DPA implementation approach would account for a significant amount of variance in their student’s (3a) total LPA, and that children in prescriptive DPA classes would accumulate (3b) more LPA during the entire school day than children in nonprescriptive classes. To determine when total MVPA minutes occurred during the school day, we examined the differences in time spent in MVPA during instructional and noninstructional time. It was hypothesized that (4a) implementation strategy would account for a significant amount of variance in MVPA during instructional time, and (4b) the prescriptive group would accumulate more instructional MVPA minutes than the nonprescriptive group. For noninstructional time, it was hypothesized that there would be no differences between the groups, since both groups of children were left to use this time as they chose. METHODS Overall design This observational study was part of a larger research project using multiple data collection methods that explored the implementation and effectiveness of the DPA policy in BC. This paper examines the differences in children’s PA at school during different DPA delivery methods. Teacher interviews were conducted to explore how teachers implement the DPA policy during the instructional and noninstructional school day. Following teacher interviews, a random sample of children from each class wore an accelerometer to objectively measure PA at school for one school week (5 days). The STROBE checklist for observational studies [27] guided reporting of this study (Supplementary Material). Sample selection and recruitment Recruitment of schools and teachers has been described elsewhere [25]. Briefly, one school district from British Columbia was approached and provided ethical approval to participate in this study. Principals from 13 public elementary schools (42% response rate) provided approval for their school to participate. Grades 4, 5, and 6 teachers from these schools were eligible to participate if they had at least 1 year of experience teaching at an elementary school level and were currently teaching in the 2015–2016 academic year. Thirty-three (of 40) teachers from 11 of these schools (83% response rate) provided written consent to participate in a short survey and potentially participate in an interview. The short survey consisted of two questions relating to the teacher’s DPA implementation approach: (i) What is the most common implementation strategy you use to implement DPA in your classroom (i.e., in addition to daily PE class, as part of daily PE class, only on days with no PE class, I don’t implement DPA (the students are active as recess and/or lunch), none of the above/other) and (ii) explain in detail how you implement DPA during the school day (open-ended question). The survey was used as a device solely to assist in selecting teachers to interview and we aimed to recruit teachers who differed in how they implemented DPA during the instructional and noninstructional school days. The interviews were used to clarify whether DPA was provided during the instructional or noninstructional school days (not always evident based on survey responses) and understand how each teacher delivered DPA during these times. In total, 12 teachers (4 males, 8 females) from 10 schools were chosen for the interview (Mage = 45.83, SD = 9.90) with teaching experience varying from 5 to 34 years (M = 16.25, SD = 9.50). Of those teachers who were interviewed, one teacher taught grade 4, three teachers taught grade 4/5, two teachers taught grade 5, four teachers taught grade 5/6, and two teachers taught grade 6. Nine teachers reported providing additional opportunities for students to be active during instructional time (herein referred to as prescriptive approaches), whereas three teachers relied on students being active during noninstructional lunch and recess breaks (herein referred to as nonprescriptive approaches). Regarding school characteristics, school size was based on total school enrollment number, and Statistics Canada 2016 census profile results (http://www12.statcan.gc.ca/census-recensement/index-eng.cfm?HPA=1) were used to determine median total income of households in 2015 and population density per square kilometer by each school’s postal code. The average school size for prescriptive and nonprescriptive schools was 361 and 401, respectively. The median total income of households in the corresponding regional district (for which each school was located) was $71,127. The average median total income for prescriptive schools was $83,833 and $78,496 for the nonprescriptive schools. The average population density per square kilometer for prescriptive and nonprescriptive schools was 1484.1 and 1368.7, respectively. All students from each interviewed teachers’ classroom were eligible and invited to participate unless they provided a reason why they must not engage in PA (i.e., injury, pre-existing condition) or were absent on recruitment day (n = 20). In total, 326 of 350 (93.1%) students were willing and eligible to participate, 4 children were ineligible, and 20 children (5.7%) refused to participate. From those students who wanted to participate and were present, random sampling, stratified for sex, was used to recruit 10 children (5 males, 5 females) within each class. Informed written parent consent and child assent was obtained for each student. Data collection Interviews Semistructured interviews were conducted with 12 teachers between February and April 2016. Interviews consisted of open-ended questions relating to the following: (i) DPA implementation approaches and (ii) factors (i.e., barriers and facilitators) influencing implementation of DPA (analysis of implementation factors presented in Weatherson et al. [25]). The present manuscript reports on teachers’ responses about their implementation approaches. The interview consisted of four questions regarding teachers DPA implementation approaches, including the following: (i) How is the DPA policy implemented at your school? Does your school provide any guidelines on how to do so? (ii) How do you implement the DPA policy in your classroom? (iii) What is your most common strategy to implement DPA in your classroom? (iv) Why do you choose some activities over others? Verbal consent was obtained from each participant to audio-record the interview and participants received a monetary reimbursement ($40) for their participation. Physical activity Accelerometer data collection occurred from March to June 2016. Students were assigned a numbered accelerometer to wear for the entire school day for five consecutive school days. Students were instructed to wear the accelerometers around the waist with the unit placed on the right hip and reminded to participate in their typical activities at recess and lunch break. For those students not randomly selected to participate, they were given a low-cost pedometer during the data collection period, with similar instructions. To increase wear compliance, children (participants and nonparticipants) were provided with a PA device log whereby they were given a sticker to record their wear of their device (upon returning their respective device to the teacher at the end of each day). At the end of the week, each student was awarded with a pedometer to keep if they wore their respective device for the entire data collection period. Classroom teachers were reminded to teach as they would on any normal school day (i.e., keeping with their DPA implementation approach) and were provided with a blank time table in which to log and record the times at which recess, lunch, and PE occurred, as well as when DPA was implemented (if applicable). Measures Implementation approach Digital recordings were transcribed verbatim directly into NVivo qualitative data analysis software [28] and interview transcripts were checked for accuracy by the interviewer. Responses to the interview questions were summarized descriptively. In addition, the time tables were collected at the end of the week and used to confirm that each teacher held to their reported implementation approach during accelerometer data collection (i.e., did not change as a result of being observed): the prescriptive teachers recorded a DPA block during regular instructional time, whereas the nonprescriptive teachers did not have these blocks recorded (only lunch and recess breaks). Objective physical activity The ActiGraph wGT3X-BT accelerometer (ActiGraphTM, LCC, Fort Walton Beach, FL, USA) was used to measure children’s movement at school. The ActiGraph wGT3X-BT accelerometer has been validated by indirect calorimetry in youth [29]. ActiLife software version 6.13.2 [30] (ActiGraph, Pensacola, Florida) was used to download raw acceleration data (Axis 1) into activity counts summed at 15 s epoch lengths. A valid day was defined as a ratio of school time, with children required to wear the accelerometer for at least 80 per cent of the school day [31]. Each student needed at least 3 valid wear days to be included in the analysis. Further details for accelerometer data processing and cleaning are available in Supplementary Material. Accelerometer data were analyzed using Evenson et al. [32] 15 s count cut-points for children: 26–573 (LPA) and ≥574 (MVPA). The classroom time table was used to categorize (i) total school day, (ii) noninstructional time (recess and lunch break), and (iii) instructional time. All school days were 360 min (from 8:30 am to 2:30 pm). Amount of noninstructional time ranged from 40 to 51 min per day across schools (M = 45.63, SD = 3.50). An independent-samples t-test indicated that there was a significant difference in noninstructional minutes per day between groups such that the prescriptive group received fewer minutes of recess/lunch break per day (M = 44.72, SD = 3.05) than the nonprescriptive group (M = 49.17, SD = 2.82); t(109) = −6.34, p < .001. To statistically control for this, all statistical tests compared percent proportion of instructional or noninstructional school time spent in LPA and MVPA (not mean minutes). Statistical analyses Descriptive analyses were run using SPSS (Version 24) [33]. Assumptions were examined and managed according to recommendations by Field [34] and Tabacknick and Fidell [35]. Group means are presented to determine whether students met the DPA policy guidelines (hypothesis 1). Hierarchical linear models (HLMs) were run using HLM7 software [36] to examine the contribution of teacher’s implementation strategy (teacher-level predictor) on student’s activity levels (student-level outcome; hypotheses 2–4). Age and sex (student-level variables) were added into the model as covariates given past research demonstrating their influence on students’ activity levels [37]. Intraclass correlation coefficients (ICCs) were calculated to examine the proportion of variance in students’ activity that was attributable to teacher-level factors and to student-level factors. Chi-square difference tests (χ2) were run to examine whether adding implementation strategy significantly improved the model compared with the null model. The total amount of variance accounted for by teacher’s implementation strategy in students’ PA was calculated by multiplying the amount of variance at the teacher-level accounted for by implementation and the amount of variance that the teacher-level accounted for in the PA outcomes. Finally, follow-up between-subjects t-tests were run to examine differences in students’ activity levels between prescriptive and nonprescriptive implementation groups (hypotheses 2–4). Differences between estimates were considered statistically significant at p < .05. RESULTS Implementation approaches In the interviews, each teacher reported that their respective school did not provide guidelines as to how they were to implement DPA during the instructional and noninstructional school day and thus each teacher had the autonomy to implement the policy as they saw fit. Within the prescriptive group, most teachers reported offering indoor and outdoor activities that were structured/organized (e.g., stretching, running laps, exercise circuits, games/sports, and aerobic or dance videos) and few offered unstructured (e.g., free time play). Some of these teachers offered a combination of these activities. Most of the activities were provided as breaks from teaching; however, two teachers embedded activity into curriculum material (academic lessons). The amount of time allotted to these activities was typically 15 min, although a few teachers provided multiple breaks per day. Two teachers tried to schedule an extra PE class per week if the gym was available. Five of the prescriptive teachers scheduled DPA into their time table at the same time each day while the rest offered PA during curriculum transitions or when the students became restless. Five of the teachers using a prescriptive style offered PA opportunities to their students only on days with no PE, whereas the other four offered opportunities in addition to PE class; however, the number of scheduled PE classes ranged from 1 to 4 per week. The teachers who used a prescriptive approach reported doing so because they did not believe that children were active on their recess and lunch breaks. They believed that providing opportunities during instructional time helped them to be confident that children would meet the guidelines. The teachers who used a nonprescriptive approach did not provide any opportunities for children to be active during instructional time (beyond scheduled PE class) because they believed that their students were active on their own volition during recess and lunch, and this time (approximately 60 min) was sufficient for them to meet the DPA guidelines. One nonprescriptive teacher also emphasized that students have the option to participate in extracurricular sports. Given our small sample and the variety of activities used by teachers to meet the DPA guidelines in this study (especially within the prescriptive group), the only characteristic across our sample that allowed us to broadly group our teachers was whether they provided PA opportunities during the instructional or noninstructional school day, and thus, the classification names derived from Mâsse et al. [26] were deemed appropriate. The two groups were confirmed through the classroom time tables provided by teachers during accelerometer data collection, with prescriptive teachers writing DPA down in their time table. Participant demographics At recruitment, 119 children (60 males, 59 females), aged 9–12 years (Mage = 10.50, SD = 0.97) provided consent and wore accelerometers for 1 week at school. In total, 111 students (56 females, 55 males) were included in the analyses. Participant demographics by implementation group and total sample are displayed in Table 1. A chi-square test showed no significant difference in sex between implementation approach group (p = .51). An independent-samples t-test showed a significant difference in mean age between groups such that the nonprescriptive group was older (Mage = 11.39, SD = 0.58) than the prescriptive group (Mage = 10.17, SD = 0.84; t(93) = −6.50, p < .001). Table 1 Student demographics Prescriptive (n = 88) Nonprescriptive (n = 23) Total (n = 111) Sex, % Female 48.9 (43) 56.5 (13) 50.5 (56) Male 51.1 (45) 43.5 (10) 49.5 (55) Age (years), % 9 18.2 (16) 0.0 (0) 14.4 (16) 10 36.4 (32) 4.3 (1) 29.7 (33) 11 22.7 (20) 52.3 (12) 28.8 (32) 12 4.5 (4) 43.5 (10) 12.6 (14) missing 18.2 (16) 0.0 (0) 14.4(16) Grade, % 4 15.9 (14) 0.0 (0) 12.6 (14) 4/5 22.7 (20) 0.0 (0) 18.0 (20) 5 38.6 (34) 0.0 (0) 30.6 (34) 5/6 22.7 (20) 30.4 (7) 24.3 (27) 6 0.0 (0) 69.6 (16) 14.5 (16) Prescriptive (n = 88) Nonprescriptive (n = 23) Total (n = 111) Sex, % Female 48.9 (43) 56.5 (13) 50.5 (56) Male 51.1 (45) 43.5 (10) 49.5 (55) Age (years), % 9 18.2 (16) 0.0 (0) 14.4 (16) 10 36.4 (32) 4.3 (1) 29.7 (33) 11 22.7 (20) 52.3 (12) 28.8 (32) 12 4.5 (4) 43.5 (10) 12.6 (14) missing 18.2 (16) 0.0 (0) 14.4(16) Grade, % 4 15.9 (14) 0.0 (0) 12.6 (14) 4/5 22.7 (20) 0.0 (0) 18.0 (20) 5 38.6 (34) 0.0 (0) 30.6 (34) 5/6 22.7 (20) 30.4 (7) 24.3 (27) 6 0.0 (0) 69.6 (16) 14.5 (16) View Large Table 1 Student demographics Prescriptive (n = 88) Nonprescriptive (n = 23) Total (n = 111) Sex, % Female 48.9 (43) 56.5 (13) 50.5 (56) Male 51.1 (45) 43.5 (10) 49.5 (55) Age (years), % 9 18.2 (16) 0.0 (0) 14.4 (16) 10 36.4 (32) 4.3 (1) 29.7 (33) 11 22.7 (20) 52.3 (12) 28.8 (32) 12 4.5 (4) 43.5 (10) 12.6 (14) missing 18.2 (16) 0.0 (0) 14.4(16) Grade, % 4 15.9 (14) 0.0 (0) 12.6 (14) 4/5 22.7 (20) 0.0 (0) 18.0 (20) 5 38.6 (34) 0.0 (0) 30.6 (34) 5/6 22.7 (20) 30.4 (7) 24.3 (27) 6 0.0 (0) 69.6 (16) 14.5 (16) Prescriptive (n = 88) Nonprescriptive (n = 23) Total (n = 111) Sex, % Female 48.9 (43) 56.5 (13) 50.5 (56) Male 51.1 (45) 43.5 (10) 49.5 (55) Age (years), % 9 18.2 (16) 0.0 (0) 14.4 (16) 10 36.4 (32) 4.3 (1) 29.7 (33) 11 22.7 (20) 52.3 (12) 28.8 (32) 12 4.5 (4) 43.5 (10) 12.6 (14) missing 18.2 (16) 0.0 (0) 14.4(16) Grade, % 4 15.9 (14) 0.0 (0) 12.6 (14) 4/5 22.7 (20) 0.0 (0) 18.0 (20) 5 38.6 (34) 0.0 (0) 30.6 (34) 5/6 22.7 (20) 30.4 (7) 24.3 (27) 6 0.0 (0) 69.6 (16) 14.5 (16) View Large Fulfillment of DPA guidelines (hypothesis 1) Table 2 displays the average minutes and percent proportions of LPA and MVPA accumulated during the total, noninstructional, and instructional school day across the total sample, as well as for each implementation group. In support of hypothesis 1, children in the total sample did not meet the DPA guidelines of 30 min of MVPA on DPA days (∼29.7 min MVPA). However, children in the prescriptive group met the DPA guidelines (32.2 min MVPA). Table 2 Mean minutes and proportion of instructional, noninstructional and total SB, LPA, and MVPA by implementation approach group and total sample Prescriptive (n = 88) Nonprescriptive (n = 23) Total (n = 111) Mean minutes (SD) Proportion (SD)a Mean minutes (SD) Proportion (SD) Mean minutes (SD) Proportion (SD) Instructional LPA 94.99 (20.66) 30.1 (6.6) 76.94 (24.21) 24.8 (7.9) 91.25 (22.55) 29.0 (7.16) MVPA 19.03 (6.06) 6.0 (1.9)** 10.77 (4.98) 3.5 (1.6)** 17.32 (6.74) 5.5 (2.11) Noninstructional LPA 19.05 (4.10) 42.5 (8.0) 24.35 (6.12) 49.4 (11.6) 20.15 (5.04) 43.9 (9.3) MVPA 13.19 (6.58) 29.7 (15.3)* 9.37 (4.69) 19.0 (9.3)* 12.40 (6.41) 27.5 (14.9) Total LPA 114.04 (22.12) 23.8 (5.1)** 101.29 (27.99) 19.4 (5.9)** 111.40 (23.88) 22.9 (5.52) MVPA 32.22 (10.9) 5.1 (1.6)** 20.14 (8.43) 2.9 (1.3)** 29.72 (11.51) 4.64 (1.77) Meeting DPA? Yes X No X X Prescriptive (n = 88) Nonprescriptive (n = 23) Total (n = 111) Mean minutes (SD) Proportion (SD)a Mean minutes (SD) Proportion (SD) Mean minutes (SD) Proportion (SD) Instructional LPA 94.99 (20.66) 30.1 (6.6) 76.94 (24.21) 24.8 (7.9) 91.25 (22.55) 29.0 (7.16) MVPA 19.03 (6.06) 6.0 (1.9)** 10.77 (4.98) 3.5 (1.6)** 17.32 (6.74) 5.5 (2.11) Noninstructional LPA 19.05 (4.10) 42.5 (8.0) 24.35 (6.12) 49.4 (11.6) 20.15 (5.04) 43.9 (9.3) MVPA 13.19 (6.58) 29.7 (15.3)* 9.37 (4.69) 19.0 (9.3)* 12.40 (6.41) 27.5 (14.9) Total LPA 114.04 (22.12) 23.8 (5.1)** 101.29 (27.99) 19.4 (5.9)** 111.40 (23.88) 22.9 (5.52) MVPA 32.22 (10.9) 5.1 (1.6)** 20.14 (8.43) 2.9 (1.3)** 29.72 (11.51) 4.64 (1.77) Meeting DPA? Yes X No X X Noninstructional time includes recess and lunch breaks. LPA light physical activity; MVPA moderate-to-vigorous physical activity; DPA Daily Physical Activity. aIn this table, proportion means the percentage of the designated time spent in each outcome variable. For example, the prescriptive group spent 23.8% of their total school days in LPA, which resulted in a mean of 114.0 min. Independent-sample t-tests were used to determine significant proportional differences between groups with *p < .01; **p < .001. View Large Table 2 Mean minutes and proportion of instructional, noninstructional and total SB, LPA, and MVPA by implementation approach group and total sample Prescriptive (n = 88) Nonprescriptive (n = 23) Total (n = 111) Mean minutes (SD) Proportion (SD)a Mean minutes (SD) Proportion (SD) Mean minutes (SD) Proportion (SD) Instructional LPA 94.99 (20.66) 30.1 (6.6) 76.94 (24.21) 24.8 (7.9) 91.25 (22.55) 29.0 (7.16) MVPA 19.03 (6.06) 6.0 (1.9)** 10.77 (4.98) 3.5 (1.6)** 17.32 (6.74) 5.5 (2.11) Noninstructional LPA 19.05 (4.10) 42.5 (8.0) 24.35 (6.12) 49.4 (11.6) 20.15 (5.04) 43.9 (9.3) MVPA 13.19 (6.58) 29.7 (15.3)* 9.37 (4.69) 19.0 (9.3)* 12.40 (6.41) 27.5 (14.9) Total LPA 114.04 (22.12) 23.8 (5.1)** 101.29 (27.99) 19.4 (5.9)** 111.40 (23.88) 22.9 (5.52) MVPA 32.22 (10.9) 5.1 (1.6)** 20.14 (8.43) 2.9 (1.3)** 29.72 (11.51) 4.64 (1.77) Meeting DPA? Yes X No X X Prescriptive (n = 88) Nonprescriptive (n = 23) Total (n = 111) Mean minutes (SD) Proportion (SD)a Mean minutes (SD) Proportion (SD) Mean minutes (SD) Proportion (SD) Instructional LPA 94.99 (20.66) 30.1 (6.6) 76.94 (24.21) 24.8 (7.9) 91.25 (22.55) 29.0 (7.16) MVPA 19.03 (6.06) 6.0 (1.9)** 10.77 (4.98) 3.5 (1.6)** 17.32 (6.74) 5.5 (2.11) Noninstructional LPA 19.05 (4.10) 42.5 (8.0) 24.35 (6.12) 49.4 (11.6) 20.15 (5.04) 43.9 (9.3) MVPA 13.19 (6.58) 29.7 (15.3)* 9.37 (4.69) 19.0 (9.3)* 12.40 (6.41) 27.5 (14.9) Total LPA 114.04 (22.12) 23.8 (5.1)** 101.29 (27.99) 19.4 (5.9)** 111.40 (23.88) 22.9 (5.52) MVPA 32.22 (10.9) 5.1 (1.6)** 20.14 (8.43) 2.9 (1.3)** 29.72 (11.51) 4.64 (1.77) Meeting DPA? Yes X No X X Noninstructional time includes recess and lunch breaks. LPA light physical activity; MVPA moderate-to-vigorous physical activity; DPA Daily Physical Activity. aIn this table, proportion means the percentage of the designated time spent in each outcome variable. For example, the prescriptive group spent 23.8% of their total school days in LPA, which resulted in a mean of 114.0 min. Independent-sample t-tests were used to determine significant proportional differences between groups with *p < .01; **p < .001. View Large Impact of teachers’ implementation strategy on student’s activity (hypotheses 2–3) Regarding hypothesis 2a, teacher-level factors accounted for a large proportion of the variance in student’s MVPA during the school day (ICC = 0.4375). After controlling for age (p = .832) and sex (p < .001) at the student-level, teacher’s implementation strategy was a significant predictor of student’s MVPA (t = 4.239, p < .01) and significantly improved the model (χ2 difference = 61.80, df = 3, p < .001). Implementation strategy accounted for 57.14 per cent of the teacher-level variance and 25 per cent of the total variance in student’s MVPA. Regarding hypothesis 2b, follow-up t-tests revealed that the prescriptive group spent a greater percent proportion of their school days in MVPA (M = 5.1, SD = 1.6) compared with the nonprescriptive group (M = 2.9, SD = 1.3; t(109) = 5.95, p < .001, g = 1.39). Regarding hypothesis 3a, teacher-level factors accounted for a small proportion of the variance in student’s LPA during the school day (ICC = 0.1877). Teacher’s implementation strategy significantly improved the prediction of student’s LPA (t = 2.18, p < .05; χ2 difference = 32.78, df = 3, p < .001) after controlling for age (p = .17) and sex (p < .05). Implementation strategy accounted for 69.09 per cent of the teacher-level variance and 12.96 per cent of the total variance in student’s LPA. The prescriptive group spent a greater percent proportion of their school days in LPA (M = 23.8, SD = 5.1) compared with the nonprescriptive group (M = 19.4, SD = 5.9; t(109) = 3.60, p < .001, g = 0.84). Impact of teachers’ implementation strategy on MVPA during instructional and noninstructional time (hypothesis 4) Teacher-level factors accounted for a small proportion of the variance in student’s MVPA during instructional time (ICC = 0.2820). After controlling for age (p = .32) and sex (p < .01), teacher’s implementation strategy was a significant predictor of student’s MVPA during instructional time (t = 4.05, p < .001) and significantly improved the model (χ2 difference = 57.94, df = 3, p < .001). Teachers’ implementation strategy accounted for 36.36 per cent of the teacher-level variance and 10.3 per cent of the total variance in student’s MVPA during instructional time. The prescriptive group spent a greater percent proportion in MVPA during instructional time (M = 6.0, SD = 1.9) than the nonprescriptive group (M = 3.5, SD = 1.6; t(109) = 5.91, p < .001, g = 1.38). Teacher-level factors accounted for a small proportion of the variance in student’s MVPA during noninstructional time (ICC = 0.0865). After controlling for age (p = .58) and sex (p < .01), teacher’s implementation strategy was a significant predictor of student’s MVPA during noninstructional time (t = 2.57, p < .01), but did not significantly improve the model (χ2 difference = 3.83, df = 3, p = .28). Implementation strategy accounted for 69.19 per cent of the teacher-level variance and 5.98 per cent of the total variance in student’s MVPA during noninstructional time. Compared with the nonprescriptive group (M = 19.0, SD = 9.3), the prescriptive group spent a greater percent proportion in MVPA during noninstructional time (M = 29.7, SD = 15.3; t(109) = 3.19, p < .01, g = 0.74). DISCUSSION The implementation of school-based PA policies, which govern the amount of PA children obtain while at school, is a recommended public health strategy to support the development of PA behaviors in school-aged children. This study aimed to measure the impact of teacher’s DPA policy implementation approach on children’s LPA and MVPA while at school. The findings from this study demonstrate that heterogeneity in policy implementation can create variations in policy effectiveness. Overall, teacher’s DPA implementation strategy accounted for a significant and large proportion of variance in student’s activity throughout the school day, and the prescriptive group was more active (LPA and MVPA) than the nonprescriptive group. Furthermore, implementation strategy significantly predicted and accounted for a moderate proportion of variance in student’s MVPA during instructional time. Implementation strategy was also a significant predictor of MVPA during noninstructional time; however, it accounted for a small proportion of variance and it did not significantly improve the model. These findings underscore the impact of prescriptive approaches to DPA implementation on students’ MVPA specifically during instructional time. Although it may not guarantee that students meet policy recommendations, teachers who provide additional opportunities for students to be active during instructional time (i.e., beyond non-instructional breaks) may help students to accumulate more LPA and MVPA. Importantly, children who were provided with DPA opportunities during instructional time were more active during this time and were not less active during noninstructional time, resulting in more total MVPA accumulated during the school day. Continued efforts to increase children’s PA during the instructional school day are warranted for improving total daily PA levels in youth. It may seem intuitive that more opportunities for PA during instructional time equate to more PA overall. However, teachers using a prescriptive approach to DPA implementation offered a variety of activities, and it is possible that some of these activities may have provided a greater contribution to students’ daily MVPA than others. For example, teachers who provided active breaks (e.g., running laps) may have elicited more vigorous PA than teachers who incorporated PA into academic lessons. As currently phrased, the DPA policy guidelines allow for either of these PA approaches; however, it may be more beneficial for teachers to deliver active breaks as part of their existing practice to meet policy requirements. Extensive research, particularly in the USA, has examined the impact of these strategies on students’ PA at school. For example, students who receive short (10 min) activity breaks were more likely to obtain 30 min/day of MVPA during school [38]. Although the integration of PA into academic content is a more recent school-based PA intervention, this strategy has also shown promise at improving MVPA levels of children [39–41]. There are numerous factors that can influence the implementation and effectiveness of PA policies and programs in schools [42–44]. For example, a systematic review by Naylor et al. [45] examining the barriers to the implementation of school-based PA models identified common barriers, including a lack of time (competing instructional requirements, teacher overload), quality/availability of resources, supportive school climate (administrative support), availability of training, and teacher self-efficacy to deliver such programs. Understanding the barriers that influence teachers’ implementation of the DPA policy during instructional time is essential in providing context to these findings and developing effective strategies to overcome them (data presented in Weatherson et al. [25]). For example, teachers in this study lacked the knowledge on what or when constitutes appropriate delivery and fulfillment of the DPA policy guidelines. As a result, the teachers with a nonprescriptive approach believed that noninstructional breaks at recess and lunch provide sufficient time for students to achieve these guidelines. This belief may reflect the underlying motive of teachers who hold a nonprescriptive implementation approach. Although there were only three nonprescriptive teachers in this study, teachers who were interviewed reported that many of their colleagues took this approach to DPA implementation [25]. One potential intervention approach could be to modify these teachers’ perceptions that all children are active during recess and lunch breaks [46, 47] and educate them on the advantage of strategies that incorporate PA during class time (e.g., improvements in academic achievement) [48, 49]. Teachers in the prescriptive group tended to teach younger grades than the nonprescriptive teachers; thus, students in the prescriptive group were younger. Although age was included as a covariate in the analyses, it was not a significant predictor nor did it account for a significant proportion of variance in students’ activity. Since children become less active as they get older [50–52], the prescriptive group being younger may have accounted for some of the observed differences in MVPA. Additionally, both the prescriptive and the nonprescriptive teachers reported that it was more difficult to incorporate PA in classes with older children due to differences in curriculum demands and students’ lack of interest [25]. Strategies to enhance guideline adherence in higher grades may include teacher education on the benefits of PA on children’s learning and academic outcomes and training/workshops on how to engage and motivate older students in age-appropriate activities. Alternatively, policy guidelines may need to be modified to account for the decline in PA as children age. It may be necessary to mandate that DPA occurs during instructional time (similar to Ontario). Similar to other Canadian DPA policies that have had little to no impact on children’s PA levels [24], neither the total sample nor the nonprescriptive implementation group met the DPA guidelines of 30 min of MVPA. Furthermore, the children in this study were less physically active than other BC students. For example, Nettlefold and colleagues [46] measured PA in a group of 380 children (8–11 years) in another region of BC and found that male and female children spent 64 and 53 min of the school day, respectively, in MVPA. One explanation for these observed differences is that the former study was conducted closer to when the DPA policy was first mandated and it is possible that school-level priority of the policy has diminished over time. As time passes, ongoing evaluation of PA policies is imperative to maintain policy support, ensure accountability of stakeholders, inform future policy development (or refinement), and warrant ongoing implementation [11, 53]. STRENGTHS AND LIMITATIONS This study is novel in that it is the first study to explore the student-level effectiveness of the DPA policy in BC. The major strength of this study was the mixed methods design which simultaneously measured and linked PA outcomes to policy implementation approach. Another strength was the use of HLM analyses to account for the nested data. Although the size of the two implementation groups were unequal, heterogeneity of the variance was not violated. This along with a sample size that was smaller than recommended for HLM [54], due to the number of available accelerometers, could have reduced statistical power. Despite these potential limitations, we were still able to detect significant main effects. The use of observational methods is useful to evaluate applicability of policy in real-world settings; however, this design limits the interpretation of findings to relationships and we cannot say that DPA implementation caused one group to have higher PA levels compared with the other group. Relatedly, a primary challenge of observational designs is the issue of confounding. There are other student-level (e.g., weight status, participation in team sports) and school-level (e.g., school SES, use of PA as a reward vs. a punishment, established community partners) factors shown to influence children’s PA levels that were not accounted for in this study [23, 55]. The main strategy that drove sampling for this study was the purposeful sampling of elementary teachers. Although this sampling method provides diversity for qualitative purposes, it might not provide an adequate sample for quantitative inference or statistical analyses. Additionally, it was difficult to recruit teachers who took a nonprescriptive approach, which resulted in unequal group sizes and ages. It could be that teachers taking this approach did not want to participate in the study for appearing they were not following the policy. To account for this limitation, we used adjusted t-tests and controlled for sex and age wherever appropriate. IMPLICATIONS The purpose of any school-based PA policy is to help all students become more physically active; however, the enactment of a policy will not ensure its full implementation [56]. The findings from this study have several implications for policy and practice. In the area of policy, it is recommended that governing bodies strengthen PA policy guidelines by specifying types of PA required and implementation procedures needed to meet these aims. Based on their study investigating adoption and implementation of U.S. state-level PA policies during school, Carlson et al. [16] conclude that clear policy language and accountability is needed for schools to provide sufficient opportunities for PA. They provide several recommendations for policy makers to ensure the implementation necessary to have a significant impact on youth PA, including using stronger and more specific languages, such as MVPA rather than PA, including evaluation components to measure impact of school PA policies, and employing monitoring systems to track implementation of these policies. According to Olstad et al. [24], flexible delivery models, where teachers have autonomy in determining the PA delivery format, are common to Canadian DPA policies but can also hinder policy implementation and effectiveness. Integrating DPA into the instructional school day may be a necessary step to remedy inconsistent implementation practices and ensure that all children have equal opportunities for PA at school. PA policies can be an effective strategy to increase PA in children at school, given that they influence school practices to provide additional opportunities for PA across the whole school day [57]. As this study suggests, additional opportunities during instructional time, including PA breaks and active lessons, represent potential methods to increase children’s PA at school. Other interventions have improved children’s PA during instructional time by scheduling sufficient time for PE [56, 58], improving the quality of PE instruction using standardized curricula [59] and PE specialists [58]. Noninstructional time also provides another important opportunity for regular PA at school, during recess, and before- and after-school. For recess, schools that provide adult supervision [58, 60], access to game equipment [61, 62], and playground markings [63] have more physically active children. Encouraging active travel to- and from-school [64] and providing intramural/interscholastic PA programs [21] are other methods to enhance children’s PA during the school day. Overall, evidence suggests that schools that adopt a whole-school approach and implement multiple strategies have the greatest impact on students’ PA [42, 58]. Although a comprehensive, whole-school approach is warranted, policy makers must recognize that there are a myriad of multilevel factors, beyond policy elements, that interact to influence both the implementation of PA approaches and children’s’ PA behaviors at school. These factors include the school environment and organizational characteristics, teacher and classroom-related factors, attributes of students and their families, and characteristics of the PA approach itself [42]. Governing bodies and school districts must help foster an environment that is conducive to teachers’ provision of PA opportunities and students engagement in these opportunities. Although school administrators can support teachers in their efforts by promoting active classroom breaks/lessons during class time, it is recommended that provinces and districts provide and fund mandatory and ongoing teacher training, education, and resources for PA policy implementation. SUPPLEMENTARY MATERIAL Supplementary material is available at Translational Behavioral Medicine online. Acknowledgments We would like to thank the school district and teachers for their time and responses provided in the interviews and facilitating data collection in their classrooms. We thank all the students who were involved in the study. The first author received funding from the Canadian Institutes of Health Research—Canada Graduate Scholarship to conduct this research and the project was funded by a Michael Smith Foundation for Health Research grant (No. 5917) to the third author. Compliance with Ethical Standards Primary Data: We can confirm that this work is original, that the findings have not been previously published, and that the manuscript is not under consideration for publication elsewhere. The authors have full control of all primary data, which we allow the journal to review upon request. Authors’ Contributions: K.W. conceptualized the study, and M.J. provided intellectual input into the methodological design. K.W. collected the data, and K.W. and S.L. analyzed the data and drafted the manuscript. All authors reviewed and approved the final manuscript. Conflict of Interest: None declared. Ethical Approval: All procedures performed in this study involving human participants were in accordance with the 1964 Helsinki declaration and its later amendments or comparable ethical standards and ethical approval was obtained from the Canadian University’s Behavioral Research Ethics Board for research involving humans (no. 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The relationship between school physical activity policy and objectively measured physical activity of elementary school students: a multilevel model analysis . Arch Public Health . 2014 ; 72 ( 1 ): 20 . Google Scholar CrossRef Search ADS PubMed © Society of Behavioral Medicine 2018. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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Translational Behavioral MedicineOxford University Press

Published: May 24, 2018

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