The learning experiences at Jump Start Academy are designed to help our students grow both in and out of the classroom. Founded in 2014, Jump Start Academy is located in Marietta and reflects the vibrant energy of the area. With 100 students and a staff of 16, we are here to help our students make an impact on the world. Are you ready for your child to reach his/her potential? Join us!We are currently empowering children at our Karve Road, Pimple Saudagar, Nyati County, Magarpatta, Baner and Pashan centers as well as at Koramangala in Bangalore. We are redefining education through our varied, well-designed, innovative programs.To create our future leaders, we are looking to partner with passionate individuals who believe in spreading goodness and making a difference in every child’s life; one life at a time.We at Jumpstart International Preschool strive to make the first five crucial years of a child’s life which defines the future years as enriching as possible. We focus on the holistic growth and development of children.The 6-month effects of the Jump Start interventions showed no difference in physical activity between children in the intervention and control centres. At this initial time point, this is due to low levels of implementation among intervention centres. This reinforces the importance of supporting centres to achieve high levels of fidelity and overcome barriers to implementation. It can take time in these settings for changes to be embedded into everyday routines and ongoing professional development is critical given the dynamic nature of these environments in these communities. Cornelius M, Carrie Armel K, Hoffman K, et al. Increasing energy- and greenhouse gas-saving behaviors among adolescents: a school-based cluster-randomized controlled trial. Energy Efficiency. 2014;7:217–42. Early childhood education and care (childcare) settings are important for promoting physical activity, especially in low-income communities. Most early childhood curriculum standards and frameworks mandate the provision of physical activity opportunities for children whilst attending childcare settings . Several systematic reviews have been inconclusive in showing that childcare-based interventions are efficacious in increasing physical activity levels among children while at childcare [6, 7]. This may be due to poor study quality, and low levels of implementation fidelity, especially when interventions are being implemented by childcare staff. This latter point may be due to staff not receiving an adequate “dose” of professional development to successfully integrate and sustain change into their daily routines [8, 9]. These reviews also show that there is less evidence in low-income communities; only six studies were reported and only one of these found a significant effect . Further, this effect was from a short-term intervention (3 months duration). There are very few studies in these communities with follow-ups longer than 12 months. Other evidence gaps identified were reporting intervention results for sub-groups such as boys and girls and overweight/obese and healthy weight children.
Wick K, Leeger-Aschmann CS, Monn ND. Interventions to promote fundamental movement skills in childcare and kindergarten: a systematic review and meta-analysis. Sports Med. 2017;47(10):2045–68.Sample size and power estimates were based on the formula proposed by Murray  to adjust for a clustered (nested) cohort design. Based on the changes observed in our pilot studies for accelerometer-based physical activity, we estimated the minimum acceptable difference between groups to be 45 mins/day of total physical activity (LMVPA) at the 18-month time point which translated to an effect size (Cohen’s d) of 0.4 . For a two-tailed alpha = 0.05 and an intraclass correlation (ICC) of 0.01–0.05 our proposed sample size of 608 participants (304 per group) provided approximately 86% power to detect an intervention effect of 0.4 or greater for the ICC range proposed.
The Jump Home component was not well supported by centres. Parents did not always receive the information on the specific activities covered by the educators each week. This resulted in poor adherence. Only a very small number of parents (16 in total) completed the checklists to indicate how often they completed any of the ‘homework’ activities with their child. As a result, evaluation of the home intervention component was not able to be completed.For many centres allocated to the control group, they continued to implement the Munch & Move program . Munch & Move is an initiative of the NSW Government and provided, from 2010 to 2015, free face-to-face training for one staff member on promoting healthy eating, active play and fundamental movement skills and reducing screen time in their centre. From 2016, Munch and Move offered online professional learning and support through health promotion officers from the local area health service. In this study, we sent regular emails to staff in control centres encouraging them to take up the online Munch & Move training and to contact the Department of Health if they required any resources. A truncated version of the Jump Start intervention was offered to staff at the end of the full intervention period (18-months).
Data supporting the results reported in this article are stored at the University of Wollongong. These data are available upon request by contacting the first author.Centres were eligible to participate in the study if they were located in an area with a SEIFA index of relative socioeconomic disadvantage of less than or equal to 5 (lowest 50%) and had a minimum enrolment of five eligible consenting children. Recruitment of centres occurred from January 2015 to June 2015.After six-months the Jump Start intervention had no effect on physical activity levels during ECEC. This was largely due to low levels of implementation. Increasing fidelity may result in higher levels of physical activity when outcomes are assessed at 18-months. Hardy LL, King L, Kelly B, et al. Munch and move: evaluation of a preschool healthy eating and movement skill program. Int J Behav Nutr Phys Act. 2010;7(1):80–90.Analyses were conducted using STATA (Version 15, StataCorp LCC, College Station TX) following the procedures as outlined in Murray . Summary statistics were created for the variables of interest (child sex, BMI, and activity level) and accelerometer wear time. T-tests or chi-square tests were used to determine if students who provided data at 6-month follow-up differed to those that only provided baseline data on the following characteristics: sex, baseline age, weight status and physical activity level. Significance levels were set at p ≤ 0.05. As there was a large amount of missing data at baseline (due mostly to monitors not worn outside of child care attendace) and the focus of the intervention was on promoting physical activity during childcare hours, a decision was made to only assess physical activity during childcare hours for the 6-month follow-up data collection. The primary outcome remained the same (time spent in LMVPA) but was operationalised as minutes per hour (mins/hr) during childcare to allow for different operating hours of centres and child time of attendance, which was determined from the attendance logbook kept by each centre.This study was funded by the National Health & Medical Research Council of Australia (APP1062433). Anthony Okely was supported by a National Heart Foundation of Australia Career Development Fellowship. DPC was supported by an Australian Research Council Discovery Early Career Researcher Award (DE140101588). TH was supported by a National Health and Medical Research Council Early Career Fellowship (APP1070571).
fect among overweight/obese children in the control group compared with the intervention group for mins/hr. of physical activity (2.35mins/hr., [0.28 to 4.43], p = 0.036).It was challenging collecting adequate accelerometry data outside childcare (i.e., the home environment). For this reason, we decided after baseline assessments to only focus on collecting accelerometry data during childcare hours for the 6-month follow-up.Carson V, Lee E-Y, Hewitt L, et al. Systematic review of the relationships between physical activity and health indicators in the early years (0-4 years). BMC Public Health. 2017;17(5):854.Sutherland R, Campbell E, Lubans DR, et al. Mid-intervention effects of the ‘physical activity 4 everyone’ school-based intervention to prevent the decline in adolescent physical activity levels: a cluster randomised trial. Br J Sports Med. 2016;50:488–95.Levels of implementation varied considerably across the 22 intervention centres. For the four components of the intervention that were able to be monitored (Jump In, Jump Out, Jump Up, and Jump Through – see Table 1 for details), implementation ranged from 0 to 100% for all components except Jump In, which ranged from 0 to 90%. The mean levels of implementation were highest for the Jump Through (72%) and Jump Up (64%) components, respectively, and lowest for the Jump In (38%) and Jump Out (45%) components. Median levels were higher for each component except Jump Up and were reported due to the high level of variability within centres: Jump Through (100%) and Jump Up (50%) Jump In (40%) and Jump Out (50%).The seven centres that were classified as having a high level of implementation during the first 6 months of the intervention, were characterised as having a large number of staff trained in the Jump Start program. As such, the responsibility for implementation was shared among staff and not the responsibility of only one or two staff members. These centres also had strong “hands-on” support for Jump Start from their Director. This leadership from the Director allowed the program to be successfully integrated into the daily routine, and gave it a higher priority among staff than in those centres with less support from the Director. Norton K, Whittingham N, Carter L, et al. Measurement techniques in anthropometry. In: Norton K, Olds T, editors. Anthropometrica. Sydney: University of New South Wales Press; 1996. p. 25–75. As child sex, age and weight status are common moderators of physical activity interventions , sub-group analyses were performed comparing boys and girls, children’s baseline BMI (categorised into two groups: ‘underweight/healthy weight’ and ‘overweight/obese’ based on the IOTF cut-points ), and age (categorised based on a median split). We included moderator interaction terms in the above GLMM separately for all potential moderators and presented the results by mediator subgroup if the test for three-way interaction term (group x time x moderator) was significant at the non-conservative 20% threshold .These findings are similar to those reported in other interventions in childcare settings in low-SES communities. Of the six studies identified in a 2016 systematic review on the effectiveness of childcare-based interventions in increasing physical activity, five reported small and non-significant effects on physical activity . Another large-scale study involving a similar number of centres and children from a range of SES backgrounds also reported no intervention effects for children from low-SES pre-schools . Despite the challenges in conducting interventions in these settings, the preliminary results from this intervention may be interpreted as somewhat disappointing, although it may be too early to arrive at this conclusion. More work is needed to better understand how to effectively promote physical activity in childcare centres in low-SES communities.
Tremblay MS, Chaput J-P, Adamo KB, et al. Canadian 24-hour movement guidelines for the early years (0–4 years): an integration of physical activity, sedentary behaviour, and sleep. BMC Public Health. 2017;17(5):874. Moher D, Hopewell S, Schulz KF, et al. CONSORT 2010 explanation and elaboration: updated guidelines for reporting parallel group randomised trials. BMJ. 2010;340:c869. Matthews CE, Hagströmer M, Pober DM, et al. Best practices for using physical activity monitors in population-based research. Med Sci Sports Exerc. 2012;44(1S):S68–76. For the comparison centres, the mean score out of 12 for implementation of the Munch & Move program was 6.86 (SD 1.59). Ten of the centres were categorised as low levels of implementation, five as average, and six as high implementers. Intervention fidelity was assessed by trained research assistants on one occasion over a one-day period using a study-specific direct observation instrument . The instrument recorded start and finish times for each Jump Start component (see Table 1), the number of children (3–5 year-olds) involved in each component, adherence to the structured lesson plans (where appropriate), description of activities, use of equipment and resources, staff behaviours, and additional comments (e.g., weather and environmental changes).Observation data were presented as a percentage of intended components completed (see Table 1 for components). Each component was evenly weighted out of 25%. Zero was given if no Jump Ups were observed, 12.5% if only one Jump Up was observed and 25% was if ≥2 Jump Ups were observed. A similar scoring system was utilised for the Jump Out and Jump Through components. For the Jump In component, the structured lessons comprised four components and these were scored based on their relative importance to provide a total score of 100, which was then standardised to a score out of 25%.
This paper reports the 6-month results from a multi-component intervention conducted in childcare centres located in low socioeconomic areas in New South Wales, Australia. At 6-months (one-third of the way through the intervention), there were no differences between intervention and control centres on the physical activity or sedentary outcomes. Across the entire sample, children increased their time spent in physical activity by about 1.5mins per hour over the 6-month period, which over a typical 7–10 h day in childcare would result in between 10 and 15mins more physical activity. However, there were no significant differences in physical activity between children in the intervention and control centres.Yildirim M, van Stralen MM, Chinapaw MJ. For whom and under what circumstances do school-based energy balance behavior interventions work? Systematic review on moderators. Int J Pediatr Obes. 2011;6:e46–57.
An important point to note is that because the levels of physical activity were already high in the intervention centres, any intervention that might replace some unstructured time outdoors with a structured activity (like the Jump In component that focused on developing gross motor skill competency) may likely result in an initial decline in children’s activity levels until the staff become confident in being able to implement the sessions with high levels of fidelity. As we did not assess gross motor skills at 6-month follow-up, it is not possible to determine if these skills improved more in the intervention centres. This is something that will be assessed at 18-month follow-up.
Physical activity was measured using Actigraph accelerometer models GT1M, GT3X+ and GT3X models which display high levels of agreement . Minutes per hour spent in total physical activity (a combination of light-, moderate-, and vigorous-intensity physical activity; LMVPA) while at the childcare centre was the primary outcome. Other physical activity outcomes included minutes per hour spent sedentary and in moderate- to vigorous-intensity physical activity (MVPA). Children were asked to wear an accelerometer for 1 week during waking hours, except during water-based activities. Collected accelerometer data were integrated into 15 s epochs during data reduction. After screening for non-wear periods (≥20 min of consecutive ‘0’ counts), participant data were considered valid at each time point if they accumulated ≥3 h of valid wear time during childcare centre hours on ≥1 childcare day. These criteria were chosen because: i) 3 h represented 40–43% of a typical childcare day (7.0–7.5 h), and ii) this study was a group RCT and, as such, the aim was to represent total physical activity at the centre level from individual child samples. Therefore, less stringent inclusion criteria (e.g., ≥ 1 day) were acceptable because these errors may not bias centre-level estimates, and loss of precision may be overcome by increasing sample size . Epochs recording ≥200 counts/15 s were classified as LMVPA  and epochs ≥420 counts/15 s and ≤ 25 counts/15 s during childcare hours were classified as MVPA and sedentary behavior, respectively [21, 22].Stanley RM, Jones RA, Cliff DP, et al. Increasing physical activity among young children from disadvantaged communities: study protocol of a group randomised controlled effectiveness trial. BMC Public Health. 2016;16(1):1095. De Craemer M, De Decker E, Verloigne M, et al. The effect of a kindergarten-based family-involved intervention on objectively measured physical activity in Belgian preschool boys and girls of high and low SES: the ToyBox-study. Int J Behav Nutr Phys Act. 2014;11:38. Given the lack of evidence on efficacious interventions in childcare settings in low-income communities, the primary aim of this study was to test an 18-month multi-component, multi-setting intervention for promoting physical activity among pre-school-aged children in these settings. As intervention effects may be moderated by a child’s sex, age, initial physical activity level and adiposity, a secondary aim was to test if the intervention results differed between boys and girls, younger and older and overweight and non-overweight children, and children who were adequately or inadequately active. Sub-group analyses for sex, age, baseline physical activity level and baseline body mass index (BMI) were also reported. This paper reports the 6-month results from this study.The Jump Start intervention comprised five components as described in Table 1. These were designed to complement one another and provide multiple opportunities to integrate physical activity into the daily routine of the centre. The intervention was based on Bandura’s Social Cognitive Theory (SCT) and focused on the personal, behavioural and environmental factors that influence physical activity participation in childcare settings. The intervention was developed using the “working backwards” process developed by Robinson and reported in previous interventions [14, 15]. The explicit links to the Australian ECEC sector’s framework and curricula (National Quality Standard and Early Years Learning Framework) [5, 16] were made.
and were not likely to be enrolled in primary school the following year. All parents/caregivers of eligible children received a participant information sheet and a link to an online recruitment video designed to simplify the explanation of the study. All staff working with 3-year-olds in the ECEC centres were also invited to participate in the study.
Strooband KFB, Stanley R, Okely AD, et al. Support to enhance level of implementation in physical activity interventions: an observational study. Australas J Early Childhood. 2018;43(1):25–33.Pate RR, O’Neill JR, Brown WH, et al. Prevalence of compliance with a new physical activity guideline for preschool-age children. Child Obes. 2015;11(4):415–20. Okely AD, Ghersi D, Hesketh KD, et al. A collaborative approach to adopting/adapting guidelines-the Australian 24-hour movement guidelines for the early years (birth to 5 years): an integration of physical activity, sedentary behavior, and sleep. BMC Public Health. 2017;17(5):869. We also explored potential moderators of intervention effects to determine if the intervention worked for some sub-groups. There were no sub-group effects for age or sex however a significant intervention effect was found among overweight and obese children in this study, with those in the control group participating in around 2.4 mins/hr. more physical activity than those in the intervention group. Over the course of a typical day at childcare (8 h) this translates to about 19mins/day which is around 10% of the daily amount recommended in the Australian Guidelines (180mins/day) . Given children in Australia attend childcare an average of 3 days per week this difference is small and greater amounts of physical activity may be needed to prevent unhealthy weight gain among overweight and obese children. The possible explanations for this are not clear given there were no differences between groups for physical activity. It may be that the overweight and obese children in the control centres participated in more physical activity outside of their time at childcare, but this was not measured at follow-up.
Data were collected by trained research assistants blinded to group allocation. Baseline data were collected from February–June 2015, and 6-month follow-up data collected from the same cohort of children from August–December 2015. Only physical activity data were collected 6-months into the trial. Although this was an 18-month intervention, we chose to collect and report data at 6-months as we believed it would provide a long enough intervention period to avoid any novelty effects (overcome threats to internal validity of the study) and was potentially long enough to have an identifiable effect on the primary outcomes. That is, we wanted to determine if intervention effects could be seen as early as 6 months after baseline. To ensure all data collectors remained blinded during the assessment periods, they conducted assessments either in the intervention or control centres only. Staff were asked not to discuss group allocation with data collectors. In addition, the objectively assessed primary outcome measure was selected to minimise the potential for bias.
Janssen X, Cliff DP, Reilly JJ, et al. Predictive validity and classification accuracy of ActiGraph energy expenditure equations and cut-points in young children. PLoS One. 2013;8(11):e79124.Australian Bureau of Statistics. Socio-economic indexes for areas (SEIFA), Australia 2011— index of relative disadvantage. Canberra: Australian Bureau of Statistics; 2013.
With smaller group sizes and structured routines, our Teachers can focus on enhancing your child’s learning and self-confidence. Students build social-emotional skills and slowly gain confidence in a small classroom setting before transitioning into formal schooling with larger class sizes.