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Active Smarter Kids (ASK): Rationale and design of a cluster-randomized controlled trial investigating… Resaland, Geir K; Moe, Vegard F; Aadland, Eivind; Steene-Johannessen, Jostein; Glosvik, Øyvind; Andersen, John R; Kvalheim, Olav M; McKay, Heather A; Anderssen, Sigmund A Jul 28, 2015

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RESEARCH ARTICLE Open AccessActive Smarter Kids (ASK): Rationale and designof a cluster-randomized controlled trial investigatingthe effects of daily physical activity on children’sacademic performance and risk factors fornon-communicable diseasesGeir K Resaland1*, Vegard Fusche Moe1, Eivind Aadland1, Jostein Steene-Johannessen1, Øyvind Glosvik1,John R Andersen2,3, Olav M Kvalheim2,4, Heather A McKay5, Sigmund A Anderssen1,6 and on behalf of the ASKstudy groupAbstractBackground: Evidence is emerging from school-based studies that physical activity might favorably affect children’sacademic performance. However, there is a need for high-quality studies to support this. Therefore, the mainobjective of the Active Smarter Kids (ASK) study is to investigate the effect of daily physical activity on children’sacademic performance. Because of the complexity of the relation between physical activity and academicperformance it is important to identify mediating and moderating variables such as cognitive function, fitness,adiposity, motor skills and quality of life (QoL). Further, there are global concerns regarding the high prevalence oflifestyle-related non-communicable diseases (NCDs). The best means to address this challenge could be through primaryprevention. Physical activity is known to play a key role in preventing a host of NCDs. Therefore, we investigated as asecondary objective the effect of the intervention on risk factors related to NCDs. The purpose of this paper is to describethe design of the ASK study, the ASK intervention as well as the scope and details of the methods we adopted to evaluatethe effect of the ASK intervention on 5th grade children.Methods & design: The ASK study is a cluster randomized controlled trial that includes 1145 fifth graders (aged10 years) from 57 schools (28 intervention schools; 29 control schools) in Sogn and Fjordane County, Norway. Thisrepresents 95.3 % of total possible recruitment. Children in all 57 participating schools took part in a curriculum-prescribed physical activity intervention (90 min/week of physical education (PE) and 45 min/week physical activity, intotal; 135 min/week). In addition, children from intervention schools also participated in the ASK intervention model(165 min/week), i.e. a total of 300 min/week of physical activity/PE. The ASK study was implemented over 7 months,from November 2014 to June 2015. We assessed academic performance in reading, numeracy and English usingNorwegian National tests delivered by The Norwegian Directorate for Education and Training. We assessed physicalactivity objectively at baseline, midpoint and at the end of the intervention. All other variables were measured atbaseline and post-intervention. In addition, we used qualitative methodologies to obtain an in-depth understanding ofchildren’s embodied experiences and pedagogical processes taking place during the intervention.(Continued on next page)* Correspondence: geirkr@hisf.no1Faculty of Teacher Education and Sports, Sogn og Fjordane UniversityCollege, Sogndal, NorwayFull list of author information is available at the end of the article© 2015 Resaland et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution License(http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium,provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Resaland et al. BMC Public Health  (2015) 15:709 DOI 10.1186/s12889-015-2049-y(Continued from previous page)Discussion: If successful, ASK could provide strong evidence of a relation between physical activity and academicperformance that could potentially inform the process of learning in elementary schools. Schools might also beidentified as effective settings for large scale public health initiatives for the prevention of NCDs.Trial registration: Clinicaltrials.gov ID nr: NCT02132494. Date of registration, 6th of May, 2014.Keywords: Cluster-randomized trial, Children, Academic performance, Cognitive functions, Executive functions,Non-communicable diseases, Physical activity, Sedentary behavior, Cardiorespiratory fitness, Quality of lifeBackground and objectivesThe relation between physical activity and academic per-formance has received widespread attention owing tothe increasing pressure on schools and teachers to pro-vide children with a range of physical and intellectualcapabilities. Physical activity might affect children’s aca-demic performance [1] and cognitive function [2]. Theschool setting is the cornerstone of societies globally.Schools reach a diverse group of children from an earlyage, and provide a learning environment that can exertan influence on children across a long period of time.Therefore, schools provide potentially useful settings toimplement strategies designed to increase children’sphysical activity [3, 4].Over the last decade, there has been a considerable in-crease in both the number and quality of school-basedstudies. However, as school based interventions are diffi-cult to implement, many have not assessed academic per-formance or cognition with validated tests, others havelacked a theoretical framework or were not randomized,some were of short duration, delivered a small “dose” ofphysical activity, had a small sample size or involved pro-motion of physical activity by non-experts. Also, it shouldbe noted that relatively few studies have measured physicalactivity objectively [1]. Hence, there is a need for high-quality studies that address these limitations.Further, there are global concerns regarding the highprevalence of lifestyle-related non-communicable dis-eases (NCDs) [5]. The prevalence of NCDs, such as type2 diabetes, is increasing worldwide, and they affectpeople of all ages, including children [6]. The ultimatecosts are a decreasing quality of life and escalatinghealthcare expenditures [7]. Physical activity is known toeffectively prevent a host of NCDs [8], thus providing animportant target for primary prevention.Our primary objective is to investigate the effect of aone year school-based physical activity intervention(Active Smarter Kids; ASK) on academic performanceon a sample of 10-year-old boys and girls attendingelementary school in Norway. Due to the complex rela-tion between physical activity and academic perform-ance, we identified possible mediating and moderatingvariables (cognitive function, physical fitness, adiposity,motor skills and quality of life (QoL)).Our secondary objective is to investigate the effect ofASK on modifiable lifestyle-related risk factors related toNCDs, such as physical activity and sedentary behavior,cardiorespiratory fitness, muscle strength, motor skills,adiposity, dyslipidemia and blood pressure.Methods/DesignA. Study design, study population and inclusion criteriaThe ASK study is a seven months cluster-randomized par-allel group controlled trial, with random allocation at theschool level with a 1:1 ratio. All children are in fifth-grade(10-year-olds) from the Sogn and Fjordane County, situ-ated in thewestern part of Norway. Inclusion criteria werethat schools should have at least seven children in fifth-grade; that children were healthy (with no serious orchronic illnesses) and able to participate in daily physicalactivity and physical education (PE). Participants had to beable to complete standard academic performance tests(our primary outcome).Sixty schools, encompassing 1202 fifth-grade children,fulfilled the inclusion criteria, and agreed to participate.This represented 86.2 % of the population of 10-year-olds in the county, and 95.2 % of total possible recruit-ment. We randomized 30 schools for the intervention(I-schools) and 30 schools for the control (C-schools)arm. A neutral third party (Centre for Clinical Research,Haukeland University Hospital, Norway) performed therandomization. After randomization, three schools (twoI-schools and one C-school) from the same municipalitydeclined to participate. In total, 1145 (97.4 %) of 1175children from 57 schools (28 I-schools and 29 C-schools) agreed to participate in the study.B. The ASK intervention (dose, intensity, teacher trainingand following up)DoseThe ASK intervention consists of three components (intotal 165 min/week). In order to optimize adherence,these were established as part of the mandatory schoolcurriculum for all children attending I-schools:1) ASK physically active educational lessons (3 ×30 min each week); Academic lessons in three core sub-jects, Norwegian, mathematics and English carried outResaland et al. BMC Public Health  (2015) 15:709 Page 2 of 10in the school playground. 2) ASK physical activity breaksduring classroom lessons (5 min × 5 days each week). 3)ASK physical activity homework prepared by the teachers(10 min daily; 5 × 10 min each week).As a part of the mandatory school curriculum inNorway, children from both the I-schools and C-schoolsparticipated in curriculum-prescribed 90 min/week of PEand 45 min/week of physical activity, in total; 135 min/week. Therefore, the children from the I-schools per-formed 300 min/week of physical activity/PE, while thechildren from the C-schools performed 135 min/week ofphysical activity/PE. However, it was specified to the C-school that they could carry out the amount of physicalactivity/PE that they would have done regardless of theASK study.IntensityThe three physical activity components in the ASK inter-vention were planned so that activities were varied andenjoyable for the children. We emphasized to the ASK-teachers that all activities should include all children, espe-cially those who were not particularly fit or enthusiasticabout physical activity. Special attention was given to cre-ating an encouraging and motivating atmosphere duringlessons, in order to support positive feelings and attitudestowards physical activity. Approximately 25 % of dailyphysical activity in the ASK intervention was intended tobe of vigorous intensity. This was defined as “childrenwould be sweating and out of breath”. The vigorous activ-ity component was achieved by selecting a variety of highintensity activities such as running, relay racing, obstaclecourses and various forms of active play.Fifty-nine ASK teachers led the physical activity com-ponent in the 28 I-schools. These ASK teachers areclassroom teachers assigned by the school principal toteach 5th grade in the I-schools (independently of theASK study). To ensure that teachers were empowered,supported and qualified to deliver the ASK physical ac-tivity intervention to their students, we conducted threecomprehensive instructional seminars (April, June andSeptember 2014) for the I-schools teachers. Further, weprovided two regional refresher sessions during theintervention period (December 2014 and February 2015)to encourage teachers to share experiences and solvechallenges together with each other and the researchteam. Finally, we provided teachers in I-schools withemail- and telephone-support. We also provided a pass-word protected ASK homepage (http://www.askstudy.no)that supplied teachers in I-schools with information, vid-eos and physical activity lessons.C. Theoretical frameworkThe ASK study is embedded in a socio-ecological con-ceptual framework that focuses on positive physicalactivity behaviors [9]. In brief, the socio-ecological modelacknowledges the role of proximal (e.g. individual andsocial) and more distal (e.g. school physical environ-ment, school policy) determinants of health behaviorchange as necessary to achieve sustained positive healthbehaviors. To address individual and social determi-nants we adopted specific theoretical frameworks in-cluding Harter’s Competence Motivation Theory [10],Achievement goal theory [11] and Ryan & Deci’s self-determination theory [12]. In line with these theoriesthe ASK intervention emphasizes creating autonomysupporting and mastery oriented teacher-student inter-action in order to enhance students’ physical activitybehavior by positively influencing their perception ofcompetence, self-efficacy, and intrinsic motivation forphysical activity.D. Outcome measuresAll participating children were tested at baseline andpost intervention. The exception was physical activitywhich was assessed at baseline, at the midpoint of theintervention period and at post intervention. We de-scribe each variable assessed in the following sections.Academic performance (primary outcome)Academic performance in 1) reading, 2) numeracy, and3) English was measured using specific standardizedNorwegian National tests designed and administrated byThe Norwegian Directorate for Education and Training(NDET) [13]. The three different tests were administeredon three different days, both at the baseline and postintervention test. Tests are extensively verified for valid-ity and reliability by NDET and are aligned with compe-tencies demanded from all schools by the nationalcurriculum. For ASK, we analyzed reading, numeracyand English individually and as a composite score.Cognitive function/Executive functionsWe assessed the three core executive functions identifiedby Miyake et al. (2000) [14], i.e. inhibition, cognitiveflexibility and working memory using four pen andpaper tests. The tests were administered in a quiet roomat the children’s school. All tests required 15–20 min tocomplete. 1) To assess inhibition we used Golden’s ver-sion of the Stroop test [15, 16]. 2) To assess cognitiveflexibility we used two tests, one verbal (Verbal fluency)and one nonverbal test (The Trail Making Test) [17]. 3)To assess working memory we used a digit span testwith digits both forward and backward (WechslerIntelligence Scale for Children, 4th ed; WISC-IV) [16].Physical activity and sedentary behaviorPhysical activity was measured by triaxial accelerometry(ActiGraph GT3X+, LLC, Pensacola, Florida, USA).Resaland et al. BMC Public Health  (2015) 15:709 Page 3 of 10ActiGraph accelerometry uses the most widely appliedinstrument for objective assessment of physical activityand has been extensively tested for validity and reliabilityin children [18]. Children were instructed to wear theaccelerometer on the right hip over seven consecutivedays at all times, except during water activities or whilesleeping. A wear-time of ≥ 480 min/day was applied as acriterion for a valid day. Periods of ≥ 20 min of zerocounts are defined as non-wear time [19]. The numberof ‘valid days’ vary depending on the analyses performed.Outcomes for physical activity levels are total physicalactivity level (counts/min), sedentary behavior (min/dayand percentage of valid wear time), light physical activity,moderate physical activity, moderate to vigorous physicalactivity and vigorous physical activity (min/day), usingpreviously applied and established cut points [20, 21]. Allanalyses were based on accumulation of data over 10 sepochs.Cardiorespiratory fitnessCardiorespiratory fitness was measured with an intermit-tent practicable running field test (the Andersen-test[22]) that has demonstrated reliability and validity forour target age group [23]. The Andersen-test was ad-ministered as per standard procedures. The childrenwere tested indoors on a wooden or rubber floor ingroups of 10–20 children. The test required 10 min toperform. Children ran from one end line to another(20 m apart) in an intermittent to-and-fro movement,with 15-s work periods and 15-s breaks (standing still).We recorded the distance covered as the outcome foranalysis.Muscle strengthMuscle strength (i.e., endurance, isometric and explosivestrength) was measured using reliable and validated se-lected tests from the Eurofit test battery [24]: 1) Upperlimb strength – handgrip strength using a hand dyna-mometer (Baseline® Hydraulic Hand Dynamometer,Elmsford, NY, USA); 2) Explosive strength in the lowerbody, standing broad jump. Muscle strength tests wererecorded both individually and as a composite score foranalyses.Motor skillsMotor skills were measured using a battery of threetests: 1) Catching with one hand and throwing at a walltarget constitute the aiming and catching subgroup ofthe movement-ABC-2; 2) Throwing at a wall target; 3)Ten times 5 m sprint. Tests 1) and 2) are from theMovement Assessment Battery for Children 2 (Move-ment ABC-2), age band 3 (11–16 years) [25], and test 3)is from Eurofit test battery [24]. Reliability and validityof these tests are well documented [26–29]. TheMovement ABC-2 demonstrated good concurrent andconvergent validity [30, 31]. We recorded motor skillstests both individually and as a composite score foranalyses.Anthropometry and maturityBody mass (weight; 0.1 kg) was measured using an elec-tronic scale (Seca 899, SECA GmbH, Hamburg, Germany)with children wearing light clothing. Stature (height;0.1 cm) was measured with a portable Seca 217 (SECAGmbH, Hamburg, Germany). The child was asked to faceforward, with shoes removed. We calculated body massindex (kg · m−2) as weight (kg) divided by the heightsquared (m2).Waist circumference was measured with a Seca 201(SECA GmbH, Hamburg, Germany) ergonomic circum-ference measuring tape. The measure was taken two cmover the level of the umbilicus (0.5 cm) with the child’sabdomen relaxed at the end of a gentle expiration. Thechild stood with arms hanging slightly away from thebody. We collected two measurements from each child.If the difference between measures was a greater thanone cm, we obtained a third measurement; the mean oftwo closest measurements are used for analyses.Body fat was measured using four skinfold thicknesssites (biceps, triceps, subscapular, and suprailiac) on theleft side of the body using a Harpenden skinfold caliper(Bull; British Indicators Ltd., West Sussex, England) asper the criteria described by Lohmann et al. [32]. TheHarpenden skinfold caliper has been tested for validityand reliability in children [33]. All measurements wereconducted in a private room. The caliper was placedaround the skinfold one cm below and to the left wherethe skin was held between thumb and forefinger. Wecollected two measurements at each site (in sequence).If the difference between measures was a greater thantwo mm, we obtained a third measurement; the mean ofthe two closest measurements are used for analyses. Theskinfold calipers was calibrated each time they weremoved between measurement sites.Children self-assessed their pubertal stage as per theTanner method [34] using a scale of color images pro-posed by Carel and Leger [35]. Children were givenstandardized series of images with explanatory text. Weused a scale based on pictures of pubic hair for bothsexes and of breast and genital development for girlsand boys, respectively. We created a relaxed atmos-phere for this assessment and the researcher was of thesame sex as the child. In a private room, children wereasked to read the brief descriptions for each stage, andinstructed to put a checkmark in the box below the pic-ture that best represented their stage of developmentfor each component.Resaland et al. BMC Public Health  (2015) 15:709 Page 4 of 10Blood pressureSystolic and diastolic blood pressure (BP) was measuredusing the Omron HBP-1300 automated BP monitor(Omron Healthcare, Inc, Vernon Hills, IL, US). The deviceis validated as per the AAMI protocol using the ANSI/AAMI/ISO standard (Omron, 2015) [36]. Children restedquietly for ten minutes in a sitting position with no dis-tractions before BP was measured. During measurement,each child sat in a quiet room; BP was measured on theupper right arm using an appropriate sized cuff. We tookfour measurements, with a one-minute interval. We usedthe mean of the last three measurements for analyses. If adifference > five mmHg between measurements wasfound, we obtained one extra measurement, in which casethe mean of the last four are used.Blood samples (factors impacting risk of metabolic disease)After an overnight fast, between 08:00 a.m. and10:00 a.m., a nurse or phlebotomist collected an intra-venous blood sample from each child’s antecubital vein.Serum was obtained according to a standardized proto-col consisting of the following steps: 1) Blood plasmawas collected in 5 ml tubes with gel (Vakuette® SerumGel with activator, G456073). 2) Tubes were carefullyturned upside-down five times and placed vertically forcoagulation. 3) After 30 minutes the sample was centri-fuged at 2000 G for 10 minutes. Serum was then visuallyinspected for residues and centrifugation was repeated ifresidue was present. 4) The serum tube was kept in re-frigerator at 4 °C before pipetting 0,5 ml into cryo tubes.5) The cryo tubes were then stored at -80 °C prior tobiochemistry analyses.Serum samples were analyzed for constituents relatedto traditional risk factors for NCDs, such as insulin, glu-cose and the standard lipid panel (triglycerides, totalcholesterol, high density lipoprotein cholesterol (HDL)and low density lipoprotein cholesterol (LDL)) usingstandard laboratory methods. Baseline and post inter-vention samples were analyzed at the same time in onebatch at an ISO certificated laboratory.Analyses of low molecular weight metabolites andlipoprotein distribution was performed for serum samplesusing proton nuclear magnetic resonance (1H-NMR)spectroscopy. The proton NMR profiles of low molecularmetabolites (fatty acids and amino acids) were obtained byusing a standard experimental set-up [37]. For lipoproteinswe made a minor modification to the experimental proto-col used by Mihaleva et. a.l (2014) [38]. Lipoprotein fea-tures such as subclass concentrations for HDL, LDL etc.and average particle size of each main class were derivedfrom the NMR profiles. Fatty acid analysis was performedaccording to the following protocol: 200 µL serum sampleis weighed into 10 mL glass tubes and water evaporatedunder nitrogen, followed by adding 150 µL internalstandard (triheptadecanoin, 0.4855 mg/mL). After evap-orating the solvent the samples are derivatized to fattyacid methyl esters (FAME) by direct esterification inmethanolic HCl at 90 °C for 2 h under nitrogen atmos-phere [39]. FAMEs will be extracted and analyzed bygas chromatography as described in Gudbrandsen et al.[40]. The samples are run in a randomized sequenceand the FAME reference mixture GLC-461 (Nu-ChekPrep, Elysian, MN, USA) will be analyzed as every 10thsample. Chromatographic areas are corrected by empir-ical response factors calculated from the GLC-461 mix-ture. The amounts of FAs are thereafter quantified bymeans of the internal standard. The total amounts ofFAs in each serum sample are converted to amounts inμg per g sample by dividing with the sample weights.Questionnaires: children, parents/guardians, teachersChildrenMode of transport to school, levels of leisure time physicalactivity, sedentary behavior and psycho-social and envir-onmental correlates of physical activity were assessed witha questionnaire developed for youths also used in a largenational representative surveillance study of physical activ-ity among Norwegian children and youth [41, 42].Children’s QoL was assessed by self-report using theKidscreen-27 questionnaire [43], which consists of 27items covering the following five QoL dimensions: 1)physical well-being (5 items); 2) psychological well-being(7 items); 3) parents/guardians relations & autonomy (7items) 4) social support & peers (4 items); and 5) schoolenvironment (5 items). The Kidscreen-27 questionnairewas developed simultaneously in several European coun-tries, and has been validated in Norwegian children aged10 [44] and 8–18 [45] In order to assess well-being atschool and predictors for this, we also used the teacherand classmate support scale [46].Physical activity preferences were assessed with aquestionnaire created by the ASK group. The childrenrated their preferences for each of 28 different activitieson a scale from one to ten.Parents/guardiansWe obtained self-reported height and weight from par-ents/guardians. We assessed physical activity habits,physical activity in leisure time and everyday living witha questionnaire developed for adults [42]. This question-naire also assessed background variables (ethnic back-ground, income, education and job description), as wellas psychological, social and environmental determinantsof physical activity.TeachersTo assess behavioral self-regulation of children from I-schools, we used 10 items from the Child Behavior RatingResaland et al. BMC Public Health  (2015) 15:709 Page 5 of 10Scale (CBRS) [47]. The original CBRS was designed toevaluate a child’s task behavior and social behavior withpeers and adults [48]. More recent studies have identifieda 10-item factor that describes child behavioral self-regulation in a classroom setting [49]. Teachers wereasked to rate children’s practical behavior on a five pointLikert scale ranging from 1 (never) to 5 (always) to indi-cate how frequently a given behavior occurs. The CBRS isa reliable and valid tool that has been used in multiplestudies in Western countries [50, 51]. After the inter-vention period, the teachers from the I-schools wereasked to provide a self-report survey evaluation of theASK intervention.Qualitative study of embodied experiences andpedagogical processesWe investigated the embodied experiences and interper-sonal relationships of teaching and learning in physicalactivity from the perspectives of children, teachers andparents/guardians using qualitative methodologies. Thepurpose was to obtain an in-depth understanding ofpedagogical processes taking place in the ASK study.More specifically, we identified purposive sample of clas-ses from two I-schools and two C-schools. The samplecriteria emphasized variation in school location, schooland class size, teachers’ education and experience withPE and physical activity, and the schools’ overall focuson physical activity. In total 100 children with parents’/guardians’ approval and seven teachers provided in-formed written consent to participate. All children par-ticipated in a drawing and writing task and one groupinterview. The students were also observed by the re-searcher during one PE lesson. This data, together withteachers’ description of their students in PE lessons,were used to choose children to further in-depth studies.We conducted in-depth interviews and field observa-tions including short video recordings with 32 children.Teachers were interviewed (individually and in groups)and observed; we also interviewed two groups of par-ents. We deem insight attained using multiple methodsand perspectives to be essential in research with chil-dren, as adult researchers may have difficulty interpret-ing a child’s perspective [52, 53]. Further, a deeperunderstanding of childrens’, teachers’, and parents’/guardians’ perspectives enriched and gave a nuanced pic-ture of processes leading to certain outcomes from themain trail. Data (i.e., transcripts of interviews, fieldnotes, drawings and writings, pictures and video record-ings) were structured and explored using the softwareprogram Nvivo 10 (QSR International Pty Ltd 2015). De-veloping in-depth knowledge is an iterative processwhere preliminary interpretations of the empirical ma-terial are brought together with discussions on theoret-ical significance in increasing detail.We consider empirical data as a construct created in aspecific cultural and historical context, influenced by theinterplay between the researcher and the participant,and the researcher’s theoretical underpinning. Empiricaldata are used as “a critical dialogue partner” and as aninspiration to challenge and rethink established taken-for-granted assumptions and theories [54]. Thus ourapproach differed from a more conventional approachwhere empirical data are seen as separate from theory,but are used to guide and validate theory development. Bythese means we aim to interpret the children’s embodiedexperiences and pedagogical practices during the ASKintervention as an interactive whole where researchers’pre-understanding, alternative theoretical input, and em-pirical data constitute the dialogue setting [54].We further created a reflexive account on children’sembodied experiences and pedagogical practices duringthe ASK intervention. Thus, the qualitative approachthus shed light on «what’s going on» in schools duringthe intervention period: How do children interact witheach other and the teachers within the schools duringthe intervention, and, in particular, how is it to be achild in an I-school? In addition, this gives us a basis todiscuss the teaching and learning processes, the possiblebenefits and pitfalls in the intervention, as well as toevaluate whether the intervention and the ASK study asa whole might serve as tools towards creating an im-proved atmosphere for learning in the schools in thefuture.E. AdherenceRegarding adherence to the intervention program,school administrators at the 57 schools recorded everychild’s absence from school. Administrators also re-corded children’s injuries and the names of children whodid not participate in physical activity lessons.We assessed the extent to which the intervention wasimplemented (dose), the quality of the implementation(fidelity), as well as feasibility as perceived by teachersand others.ASK teachers at the 28 I-schools completed a reporteach week that described activities performed throughoutthe school day, the intensity of the activities (on a 1 to 3scale) and the number of minutes allocated to physicalactivity/PE in each ASK session. All 29 C-schools, at theend of the school year, completed a report that describesthe activities that were performed and the estimated timeallocated to physical activity/PE during the school year(minutes/week).F. Statistical considerations/Statistical methodsRandomization procedureThe randomization procedure is explained in section 2a.Resaland et al. BMC Public Health  (2015) 15:709 Page 6 of 10BlindingBlinding of children and schools was not possible due tothe nature of the experiment. However, only the projectmanagement group has formal knowledge of group as-signment. The data manager and statisticians are blindedto group allocation until analyses are conducted.Power calculations/Sample size and powerThe ASK study was designed to detect an effect size(Cohen’s D) of 0.35 between two groups for change inacademic performance. Sample size calculations wereperformed using standard formulas, given ɑ = 0.05, 1-β = 90 %, group ratio 1:1 and correlation of repeatedmeasurements = 0.7, leading to a naive n = 103 childrenin each group. Due to the cluster-randomized controlledtrial (RCT) design, the sample size was corrected forthe design effect using formula 1; Design Effect = 1 +[(CV2 + 1)*n – 1]* (ICC), where CV = coefficient of vari-ation for n, n = number of children within each cluster,and ICC = intraclass correlation coefficient. Thus, after ac-counting for school clusters, we required a sample size of468 children in each arm (INT; CON). This is based onan ICC = 0.15, n = 16.2 after accounting for 20 % attritionat the subject level, and CV = 0.72 (design effect correc-tion factor = 4.54). The assumed ICC is a conservative es-timate compared to the expected ICC of 0.03 to 0.07,which lay the foundation for the sample size of the A+PAAC study [55]. For secondary outcomes we assume anICC of 0.05 to 0.10 [56]. Accepting the assumptionsabove, the target sample size allowed us to detect a signifi-cant difference between the groups for variables reachingan effect size of 0.24 (ICC = 0.05) to 0.30 (ICC = 0.10)or higher.Plan for analysisOur main analysis in order to assess the effectiveness ofthe ASK intervention are based on and intention to treatanalysis [57, 58]. We also acknowledge the importanceof conducting per-protocol analyses to determine efficacybased on schools that showed fidelity to the model andperformed the physical activity intervention as intended[59]. Therefore, we conducted secondary analyses of chil-dren who participated in ≥80 % of the physical activity-based intervention and schools which delivered ≥80 % ofthe physical activity-based intervention as we deem thisacceptable adherence to the intervention itself.We describe missing data using appropriate flowcharts [60] that also allowed for investigation of missingdata mechanisms and assumptions that underpin statis-tical analyses. Missing data was imputed from all avail-able relevant variables by means of multiple imputationusing a Markov Chain Monte Carlo procedure with 20iterations, with an assumption that data are missing atrandom. We performed sensitivity analyses to evaluatethe stability of results under various assumptions ofmissing data.We used a mixed-effects model to test the between-group difference (intervention vs. control) for the mainoutcome (academic performance), controlling for base-line values and including school as a random effect. Theper-protocol analysis was adjusted for differences be-tween groups as appropriate.We conducted our analyses using the newest availableversion of IBM SPSS (IBM SPSS Statistics for Windows,Armonk, NY: IBM Corp., USA). A two-sided p-value ≤0.05 were considered statistically significant.We conducted defined moderator-mediator analyses apriori to evaluate characteristics of children and path-ways that could influence the effect of the interventionon academic performance. We identified potential mod-erators that include both characteristics of the childrenand baseline values for specific secondary outcomes. Weincluded change in executive function, motor skills, phys-ical activity, physical fitness, adiposity and other risk fac-tors for lifestyle-related non-communicable diseases inmediation-analyses. We used a similar strategy to evaluatemoderators and mediators of secondary outcomes. As apart of the investigation of possible moderators of the ef-fects evaluated, we conducted subgroup-analyses definingsubgroups by quintiles or quintile split and testing group*-subgroup interaction terms. For mediation analyses weused structural equation modeling. We also used multi-variate linear regression and exploratory analyses [61, 62]to evaluate associations between secondary outcomes andacademic performance, and to explore associations amongindependent variables.G. Recruitment and anchoringImplementation research suggests that to successfullyimplement a large scale study within the school system,researchers must engage partners early and stakeholdersshould be active participants in design, implementationand dissemination of the ‘innovation’ [63]. Importantly,school-based models will be more likely to be sustainedif they are anchored and supported by policy within theschool system [64]. We carried out a four-stage plan toachieve this.First, the study was accepted by “The forum for develop-ment in kindergartens and schools in Sogn and FjordaneCounty”. This educational forum was established in 1997in Sogn and Fjordane County as an arena to discuss,translate and integrate educational policies regardingschool quality and school development. The forum in-cludes professional executives of the most important edu-cational authorities and organizations in the Sogn andFjordane, and it is highly respected by school administra-tors and teachers in the county. Second, through the “Theforum for development in kindergartens and schools inResaland et al. BMC Public Health  (2015) 15:709 Page 7 of 10Sogn and Fjordane County” we obtained access to a seriesof already established meeting venues for all county schoolleaders and principals, who accepted the study at the op-erations level. Third, parents/guardians were invited tomeet with us at individual schools, where we provided adescription of the study (oral and written), including ouraims and any possible hazards, discomfort, or inconveni-ence. We also clearly described the measurement protocoland procedures and addressed any questions. We empha-sized that children were free to withdraw from the studyor from any measurements at any time, without providingan explanation. Fourth, we carried out an extensive an-choring process with the ASK teachers in the I-schools.H. Ethical perspectivesProcedures and methods used in the ASK study conformto the ethical guidelines defined by the World MedicalAssociation’s Declaration of Helsinki and its subsequentrevisions [65]. The study protocol was approved by TheRegional Committee for Medical Research Ethics. TheASK study adopted a population-based approach that fo-cuses on- and treats all children equally and considerately.We obtained written consent from each child’s parent/guardian prior to all testing. Reporting are anonymousand it is not be possible to identify individual participantsin any published materials.DiscussionThe school setting offers a unique opportunity for struc-tured physical activity for children; it may well be theideal environment for population-based physical activityinterventions. Most children and adolescents, aged six to16, spend most of their day in school. No other institutionhas possibly as much influence on children during the firsttwo decades of their lives [66]. Further, schools might bethe only means in diverse and pluralistic societies to reacha large number of children from all socio-economic back-grounds, irrespective of their parents/guardians’ behaviorand attitude towards physical activity. As the physicalactivity is mandatory in the 28 I-schools in the ASKstudy, all children were involved in a physical activityintervention, and not only the motivated children. Add-itionally, the school offers a safe environment and facil-ities in an arena designed for learning. This creates anoptimal context to support increased physical activitylevels of children.A comprehensively designed and appropriately pow-ered RCT of elementary school-based physical activitywith a long enough intervention and an adequate dosedelivered by trained teachers in order to enhance phys-ical activity of students would provide Level I evidenceto support the effectiveness of such models. High re-cruitment levels and carefully selected and implementedmeasures (such as objectively measured physical activity)also enhance the quality of the ASK study. The trial isimportant for a number of reasons and may have an im-pact in a number of ways. First, if the physical activityintervention positively influences academic performance,this could in turn influence how the school communitydesigns and implements children’s learning processesand related school curriculum and policies. Second,schools could be considered key sites for preventive pub-lic health initiatives that are adaptable, feasible and em-bedded within school culture. Academic performanceand public health initiatives are interrelated. It is clearthat if schools are to play a role in the prevention ofNCDs and other public health problems in the future,the approach to achieving this must be anchored and ac-cepted among the larger school community (parents,teachers, administrators). For schools to adopt this roleand redefine themselves, the pathway to this is likelythrough enhanced academic performance through phys-ical activity.Importantly, if classroom teachers receive comprehen-sive education beyond qualification, the ASK model canbe inexpensively disseminated to schools. In nationaland international contexts, the ASK study has the poten-tial to extend current evidence and inform the politicaland scientific debate as to whether embedding physicalactivity into school culture is an effective next step to-ward meeting both educational and health goals.AbbreviationsASK: Active smarter kids; BMI: Body mass index; Cm: Centimeter; CBRS: Childbehavior rating scale; CV: Coefficient of variation; HDL: High densitylipoprotein cholesterol; ICC: Intraclass correlation coefficient; kg: Kilogram;LDL: Low density lipoprotein cholesterol; Movement ABC-2: MovementAssessment battery for children 2; NCDs: Non-communicable diseases;PE: Physical education; QoL: Quality of live; RCT: Randomized controlled trial;I-schools: The intervention group; C-schools: The control group.Competing interestsThe authors declare that they have no competing interests.Authors’ contributionsGKR and SAA conceived the study, and will act as guarantors of the paper.GKR, VFM, ØG, JRA, OMK, JSJ, HM and SAA designed the study and obtainedfinancial support. All authors participated in the writing of the paper andapproved the final version.Authors’ informationThe ASK study group:1. Mette Stavnsbo1, mette.stavnsbo@hisf.no, Ph.D. student2. Turid Skrede1, turid.skrede@hisf.no, Ph.D. student3. Katrine N Aadland1, katrine.Nyvoll.Aadland@hisf.no, Ph.D. student4. Laura Suominen1, laura.Suominen@hisf.no, Ph.D. student5. Gunn Engelsrud1,4, gunn.engelsrud@nih.no, Senior investigator6. Yngvar Ommundsen4, yngvar.ommundsen@nih.no, Senior investigator7. Ulf Ekelund4, ulf.ekelund@nih.no, Senior investigator8. Lars B Andersen4, lboandersen@health.sdu.dk, Senior investigator9. Ingar Holme4, i.m.k.holme@nih.no, Statistical investigator10. Willem van Mechelen5, w.vanmechelen@vumc.nl, Scientific advisory board11. Susi Kriemler6, susi.kriemler@ifspm.uzh.ch, Scientific advisory board12. Age K Smilde7, a.k.smilde@uva.nl, Scientific advisory board13. Svein Mjøs,3, svein.Mjos@kj.uib.no, Chemical analysis investigator14. Tarja AR Kvalheim2, tarja.kvalheim@gmail.com, Metabolomics investigator15. Tone F Bathen8, tone.f.bathen@ntnu.no, Metabolomics investigatorResaland et al. BMC Public Health  (2015) 15:709 Page 8 of 1016. Aud M Øien9, aud.Marie.Oien@hisf.no, Qualitative investigator17. Inger J Solheim9, inger.johanne.solheim@hisf.no, Qualitative investigator18 Einar Ylvisåker1, einar.ylvisaker@hisf.no, Physical activity investigator19. Øystein Lerum1, oystein.Lerum@hisf.no, Research assistants20. Stian Gjørøy1, stian.Gjoroy@hisf.no, Research assistants21. Frode O Haara1, frode.olav.haara@hisf.no, Academic performance investigator22. Tom R Kongelf1, tom.rune.kongelf@hisf.no, Academic performance investigator23. Erik Kyrkjebø1, erik.Kyrkjebo@hisf.no, Administration responsible24. Kolbjørn Brønnick10,11, bronnick@gmail.com, Cognitionperformance investigator25. Hege Kristiansen2, hegekr@gmail.com, Medical responsible1Sogn og Fjordane University College, Faculty of Teacher Education andSports, Sogndal, Norway.2Førde Central Hospital, Centre of Health Research, Førde, Norway.3University of Bergen, Department of Chemistry, Bergen, Norway.4Norwegian School of Sport Sciences, Department of Sports Medicine,Oslo, Norway.5VU University, Department of Public and Occupational Health, EMGO+Institute for Health and Care Research, VU University Medical Center,Amsterdam, The Netherlands.6University of Basel, Swiss Tropical and Public Health Institute, Basel,Switzerland.7University of Amsterdam, Swammerdam Institute for Life Sciences,Amsterdam, The Netherlands.8NTNU, Dept. of Circulation and Medical Imaging (ISB), Faculty of medicine,Trondheim, Norway.9Sogn og Fjordane University College, Faculty of Social Sciences, Sogndal,Norway.10University of Stavanger, The National Centre for Reading Education andResearch, Stavanger, Norway.11Stavanger University Hospital, Regional Centre for Clinical Research inPsychosis, Division of Psychiatry, Stavanger, Norway.AcknowledgementsThis study was supported by The Research Council of Norway, The Sogn ogFjordane University College, The Norwegian schools of Sports Science.Main funding sourcesThe Research Council of Norway (ID number 221047/F40) and Sogn ogFjordane University College.Author details1Faculty of Teacher Education and Sports, Sogn og Fjordane UniversityCollege, Sogndal, Norway. 2Faculty of Health Studies, Sogn og FjordaneUniversity College, Førde, Norway. 3Centre of Health Research, Førde CentralHospital, Førde, Norway. 4Department of Chemistry, University of Bergen,Bergen, Norway. 5Department of Family Practice, Faculty of Medicine, TheUniversity of British Columbia, Vancouver, Canada. 6Department of SportsMedicine, Norwegian School of Sport Sciences, Oslo, Norway.Received: 23 June 2015 Accepted: 10 July 2015References1. Singh A, Uijtdewilligen L, Twisk JW, van Mechelen W, Chinapaw MJ. Physicalactivity and performance at school: a systematic review of the literatureincluding a methodological quality assessment. Arch Pediatr Adolesc Med.2012;166(1):49–55.2. Hillman CH, Kamijo K, Scudder M. A review of chronic and acute physicalactivity participation on neuroelectric measures of brain health andcognition during childhood. Prev Med. 2011;52(Suppl 1):21–8.3. Pate RR, Davis MG, Robinson TN, Stone EJ, McKenzie TL, American HeartAssociation Council on Nutrition PA, Metabolism, Council on CardiovascularDisease in the Y, Council on Cardiovascular N: Promoting physical activity inchildren and youth: a leadership role for schools: a scientific statement fromthe American Heart Association Council on Nutrition, Physical Activity, andMetabolism (Physical Activity Committee) In Collaboration With theCouncils on Cardiovascular Disease In the Young and CardiovascularNursing. Circulation. 2006;114(11):1214–24.4. Naylor PJ, McKay HA. Prevention in the first place: schools a setting foraction on physical inactivity. Br J Sports Med. 2009;43(1):10–3.5. Lee IM, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT. Effect ofphysical inactivity on major non-communicable diseases worldwide: ananalysis of burden of disease and life expectancy. Lancet.2012;380(9838):219–29.6. World Health Organization. Prevention and control of noncommunicablediseases: implementation of the global strategy. Geneva: WHO; 2008.7. Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, Amann M,Anderson HR, Andrews KG, Aryee M, et al. A comparative risk assessment ofburden of disease and injury attributable to 67 risk factors and risk factorclusters in 21 regions, 1990-2010: a systematic analysis for the GlobalBurden of Disease Study 2010. Lancet. 2012;380(9859):2224–60.8. World Health Organization: http://www.euro.who.int/en/what-we-do/health-topics/disease-prevention/physical-activity/facts-and-figures/10-key-facts-on-physical-activity-in-the-who-european-region. In.: WHO; 2011.9. McLeroy KR, Bibeau D, Steckler A, Glanz K. An ecological perspective onhealth promotion programs. Health Educ Q. 1988;15(4):351–77.10. Harter S. Effectance motivation reconsidered: toward a developmentalmodel. Hum Dev. 1978;21:34–64.11. Nicholls JG. The competitive ethos and democratic education. Cambridge,Mass: Harvard University Press; 1989.12. Ryan RM. Overview of self-determination theory. An organismic dialecticalperspective. Rochester NY: The University of Rochester Press; 2002.13. The Norwegian Directorate for Education and Training. Information aboutnational tests. http://www.udir.no/PageFiles/82639/Foreldrebrosjyre_Nasjonaleprover_2014_engelsk.pdf.14. Miyake A, Friedman NP, Emerson MJ, Witzki AH, Howerter A, Wager TD. Theunity and diversity of executive functions and their contributions tocomplex "frontal lobe" tasks: A latent variable analysis. Cogn Psychol.2000;41(1):49–100.15. Golden CJ. Stroop Color and Word Test. Chicago: Stoelting; 1978.16. Lezak MD, Howieson DB, Bigler ED, Tranel D. NeuropsychologicalAssessment. USA: OUP; 2012.17. Spreen O, Strauss E. A compendium of neuropsychological tests. 2nd ed.New York: Oxford University Press; 1998.18. Brage S, Wedderkopp N, Franks PW, Andersen LB, Froberg K. Reexaminationof validity and reliability of the CSA monitor in walking and running.Med Sci Sports Exerc. 2003;35(8):1447–54.19. Esliger DW, Copeland JL, Barnes JD, Tremblay MS. Standardizing andOptimizing the Use of Accelerometer Data for Free-Living Physical ActivityMonitoring. J Phys Act & Health. 2005;2(3):366.20. Evenson KR, Catellier DJ, Gill K, Ondrak KS, McMurray RG. Calibration of twoobjective measures of physical activity for children. J Sport Sci.2008;26(14):1557–65.21. Trost SG, Loprinzi PD, Moore R, Pfeiffer KA. Comparison of AccelerometerCut Points for Predicting Activity Intensity in Youth. Med Sci Sports Exerc.2011;43(7):1360–8.22. Andersen LB, Andersen TE, Andersen E, Anderssen SA. An intermittentrunning test to estimate maximal oxygen uptake: the Andersen test.J Sports Med Phys Fitness. 2008;48(4):434–7.23. Aadland E, Terum T, Mamen A, Andersen LB, Resaland GK. The Andersenaerobic fitness test: reliability and validity in 10-year-old children. Plos One.2014;9(10):e110492–2.24. COE. Eurofit: handbook for the Eurofit test on physical fitness. Strasbourg:Council of Europe. 1993.25. Henderson SE, Sugden DA, Barnett A. The Movement Assessment Batteryfor Children 2. London: Pearson Assessment; 2007.26. Kemper HC, Van Mechelen W. Physical fitness testing of children: AEuropean perspective. Pediatr Exerc Sci. 1996;8:201–14.27. Schulz J, Henderson SE, Sugden DA, Barnett AL. Structural validity of theMovement ABC-2 test: Factor structure comparisons across three agegroups. Res Dev Disabil. 2011;32(4):1361–9.28. Wuang Y-P, Su J-H, Su C-Y. Reliability and responsiveness of the MovementAssessment Battery for Children. Second Edition Test in children withdevelopmental coordination disorder. Dev Med Child Neurol. 2012;54(2):160–5.29. Wagner MO, Kastner J, Petermann F, Bös K. Factorial validity of theMovement Assessment Battery for Children-2 (age band 2). Res Dev Disabil.2011;32(2):674–80.30. van Waelvelde H, Peersman W, Lenoir M, Engelsman BCMS. The reliability ofthe Movement Assessment Battery for Children for preschool children withResaland et al. BMC Public Health  (2015) 15:709 Page 9 of 10mild to moderate motor impairment.Clin Rehabil. 2007;21(5):465–70.31. Croce RV, Horvat M, McCarthy E. Reliability and concurrent validity of themovement assessment battery for children. Percept Mot Skills. 2001;93(1):275.32. Lohman TG, Roche AFM, Martorell R. Anthropometric standardizationreference manual. Illinois: Champaign, IL: Human Kinetics Books; 1991.33. Yeung DC, Hui SS. Validity and reliability of skinfold measurement inassessing body fatness of Chinese children. Asia Pac J Clin Nutr.2010;19(3):350–7.34. Tanner JM. Growth at Adolescence. Oxford, United Kingdom: Blackwell;1962.35. Carel JC, Leger J. Precocious puberty. New Engl J Med. 2008;358(22):2366–77.36. A clinical evaluation report of professional blood pressure monitorHBP-1300. http://www.omron-healthcare.com/eu/en/our-products/blood-pressure-monitoring/hbp-1300.37. Soininen P, Kangas AJ, Würtz P, Tukiainen T, Tynkkynen T, Laatikainen R,Järvelin M-R, Kähönen M, Lehtimäki T, Viikari J, et al. High-throughput serumNMR metabonomics for cost-effective holistic studies on systemicmetabolism. Analyst. 2009;134(9):1781–5.38. Mihaleva VV, van Schalkwijk DB, de Graaf AA, van Duynhoven J, van DorstenFA, Vervoort J, Smilde A, Westerhuis JA, Jacobs DM. A systematic approachto obtain validated partial least square models for predicting lipoproteinsubclasses from serum NMR spectra. Anal Chem. 2014;86(1):543–50.39. Meier S, Mjos SA, Joensen H, Grahl-Nielsen O: Validation of a one-stepextraction/methylation method for determination of fatty acids andcholesterol in marine tissues. Journal of Chromatography 2006, 1104: 291-298.40. Gudbrandsen OA, Kodama Y, Mjos SA, Zhao C-M, Johannessen H, BrattbakkH-R et al: Effects of duodenal switch alone or in combination with sleevegastrectomy on body weight and lipid metabolism in rats. Nutrition &Diabetes 2014, 4, e124.41. Ostergaard L, Kolle E, Steene-Johannessen J, Anderssen SA, Andersen LB.Cross sectional analysis of the association between mode of schooltransportation and physical fitness in children and adolescents. Int J BehavNutr Phys Act. 2013;10:91–1.42. The Norwegian Directorate of Health. Physical activity among 6, 9 and 16year olds. Results from surveillance in 2011. IS-2002, 06/2012. Oslo43. Ravens-Sieberer U, Auquier P, Erhart M, Gosch A, Rajmil L, Bruil J, Power M,Duer W, Cloetta B, Czemy L, et al. The KIDSCREEN-27 quality of life measurefor children and adolescents: psychometric results from a cross-culturalsurvey in 13 European countries. Qual Life Res. 2007;16(8):1347–56.44. Andersen JR, Natvig GK, Haraldstad K, Skrede T, Aadland E, Resaland GK. Isthe Kidscreen-27 a valid measure of health-related quality of life in 10-year-old Norwegian children? Peer J PrePrints. 2015;3:e1383. https://dx.doi.org/10.7287/peerj.preprints.1134v1.45. Haraldstad K, Christophersen KA, Eide H, Nativg GK, Helseth S. Health relatedquality of life in children and adolescents: reliability and validity of theNorwegian version of KIDSCREEN-52 questionnaire, a cross sectional study.Int J Nurs Stud. 2011;48(5):573–81.46. Torsheim T, Wold B, Samdal O. The teacher and classmate support scale:factor structure, test retest reability and validity in samples of 13–15 yearold adolecents. Sch Psychol Int. 2000;21:195–212.47. Bronson MB, Goodson BD, Layzer JI, Love JM. Child Behavior Rating Scale.Cambridge: MA: Abt Associates; 1990.48. Bronson MB, Tivnan T, Seppanen PS. Relations between teacher andclassroom activity variables and the classroom behaviors of prekindergartenchildren in Chapter 1 funded programs. J Appl Dev Psychol. 1995;16(2):253–82.49. Matthews JS, Ponitz CC, Morrison FJ. Early gender differences in self-regulation and academic achievement. J Educ Psychol. 2009;101(3):689–704.50. von Suchodoletz A, Gestsdottir S, Wanless SB, McClelland MM, Birgisdottir F,Gunzenhauser C, Ragnarsdottir H. Behavioral self-regulation and relations toemergent academic skills among children in Germany and Iceland. EarlyChild Res Q. 2013;28(1):62–73.51. Lim SM, Rodger S, Brown T. Validation of child behavior rating scale inSingapore (Part 1): Rasch analysis. Hong Kong J Occup Ther. 2010;20(2):52–62.52. Christensen P. Childhood and the cultural constitution of vulnerable bodies.In: Prout A, Campling J, editors. The body, childhood and society.Houndmills: Macmillan Press Ltd.; 2000.53. Christensen P, Prout A. Working with ethical symmetry in social researchwith children. Childhood. 2002;9(4):477–97.54. Alvesson M, Kärreman D. Qualitative Research and Theory Development.London: SAGE Publications; 2011.55. Donnelly JE, Greene JL, Gibson CA, Sullivan DK, Hansen DM, Hillman CH,et al. Physical activity and academic achievement across the curriculum(A + PAAC): rationale and design of a 3-year, cluster-randomized trial. BMCPublic Health. 2013;13:307–7.56. Kriemler S, Zahner L, Schindler C, Meyer U, Hartmann T, Hebestreit H,Brunner-La Rocca HP, van Mechelen W, Puder JJ. Effect of school basedphysical activity programme (KISS) on fitness and adiposity in primaryschool children: cluster randomised controlled trial. Br Med J. 2010;340:c785.57. Hollis S, Campbell F. What is meant by intention to treat analysis? Survey ofpublished randomised controlled trials. Br Med J. 1999;319(7211):670–4.58. Polit DF, Gillespie BM. Intention-to-treat in randomized controlled trials:recommendations for a total trial strategy. Res Nurs Health. 2010;33(4):355–68.59. Donnelly JE, Greene JL, Gibson CA, Smith BK, Washburn RA, Sullivan DK,DuBose K, Mayo MS, Schmelzle KH, Ryan JJ et al. Physical Activity Across theCurriculum (PAAC): A randomized controlled trial to promote physicalactivity and diminish overweight and obesity in elementary school children.Prev Med. 2009;49(4):336–41.60. Campbell MK, Piaggio G, Elbourne DR, Altman DG, Grp C. Consort 2010statement: extension to cluster randomised trials. Br Med J. 2012;345:e5661.61. Rajalahti T, Arneberg R, Berven FS, Myhr KM, Ulvik RJ, Kvalheim OM.Biomarker discovery in mass spectral profiles by means of selectivity ratioplot. Chemometr Intell Lab Syst. 2009;95(1):35–48.62. Rajalahti T, Kvalheim OM. Multivariate data analysis in pharmaceutics: atutorial review. Int J Pharm. 2011;417(1–2):280–90.63. Durlak JA, DuPre EP. Implementation matters: a review of research on theinfluence of implementation on program outcomes and the factorsaffecting implementation. Am J Community Psychol. 2008;41(3–4):327–50.64. McKay HA, Macdonald HM, Nettlefold L, Masse LC, Day M, Naylor P-J. ActionSchools! BC implementation: from efficacy to effectiveness to scale-up. Br JSports Med. 2015;49(4):210–8.65. WMA. Ethical principles for medical research involving human subjects.Helsinki: World Medical Association General Assembly. 1964.66. Story M, Nanney MS, Schwartz MB. Schools and obesity prevention: creatingschool environments and policies to promote healthy eating and physicalactivity. Milbank Q. 2009;87(1):71–100.Submit your next manuscript to BioMed Centraland take full advantage of: • Convenient online submission• Thorough peer review• No space constraints or color figure charges• Immediate publication on acceptance• Inclusion in PubMed, CAS, Scopus and Google Scholar• Research which is freely available for redistributionSubmit your manuscript at www.biomedcentral.com/submitResaland et al. BMC Public Health  (2015) 15:709 Page 10 of 10


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