David. A. Dzewaltowski

Out-of-school time (OST) organized group youth activities (e.g., afterschool programs, clubs) can reduce health inequalities by increasing physical activity (PA). However, unlike youth sport, PA is not the primary focus of many organized activities, and little is known about rural children’s non-sport organized activity participation. This study examined sociodemographic characteristics associated with OST non-sport organized activity participation and PA among children living in rural U.S. Midwest communities. During Spring 2019, children (n = 418 3^rd–6^th graders) attending school in two rural communities completed a PA surveillance instrument as part of Wellscapes, a community randomized trial. Caregivers of a subsample of children (n = 235) consented to pair their child’s survey results with student enrollment records. Mixed models with community as a random effect examined main and interaction effects of grade, sex, and family income on OST non-sport organized activity participation and these sociodemographic characteristics and organized activity participation on OST moderate-to-vigorous PA (MVPA) per weekday and weekend day. Most children (73.2%) participated in an OST non-sport organized activity. Males were less likely to participate than females (OR = 0.38, 95% CI = 0.20–0.73, p = 0.004). Females and 6^th graders reported lower OST MVPA on weekdays and weekends than comparison groups (p < 0.001). Males with lower family income accumulated significantly fewer minutes of MVPA on weekdays (mean_diff= -4.7 ± 2.0 minutes) and weekends (mean_diff= -8.9 ± 3.8 minutes) compared with males with higher family income (p < 0.05). Many rural children participated in OST organized activities regardless of grade and family income. However, there were disparities in organized activity participation and OST PA outcomes based on sociodemographic factors, including grade, sex, and family income. Designing OST organized activity settings to be more accessible and include opportunities for PA may help ensure children can achieve optimal health.

Background: Adult-led organized settings for children (eg, classrooms) provide opportunities for physical activity (PA). The structure of setting time may influence inequalities (ie, unequalness) in the distribution of PA. This study examined differences in PA inequality by setting and time-segment purpose in time-segmented organized group settings for children. Methods: PA and setting meetings were assessed using accelerometer and video observation data from school, before-/after-school, and youth club groups (n = 30) for third- through sixth-grade children (n = 699) in 2 rural US communities. Meetings (n = 130) were time-segmented into smaller units (sessions; n = 835). Each session was assigned a purpose code (eg, PA). Accelerometer data were paired with the meetings and sessions, and the Gini coefficient quantified inequality in activity counts and moderate to vigorous PA minutes for each segment. Beta generalized estimating equations examined differences in PA inequality by setting and session purpose. Results: Activity count inequality was lowest (P < .05) during youth club meetings (Gini = 0.17, 95% CI, 0.14–0.20), and inequality in moderate to vigorous PA minutes was greatest (P < .01) during school (Gini = 0.34, 95% CI, 0.30–0.38). Organized PA sessions (Gini = 0.20, 95% CI, 0.17–0.23) had lower activity count inequality (P < .0001) than academic (Gini = 0.30, 95% CI, 0.27–0.34), enrichment (Gini = 0.31, 95% CI, 0.27–0.36), and nonactive recreation (Gini = 0.30, 95% CI, 0.25–0.34) sessions. Inequality in moderate to vigorous PA minutes was lower (P < .05) in organized PA (Gini = 0.26, 95% CI, 0.20–0.32) and free play (Gini = 0.28, 95% CI, 0.19–0.39) than other sessions. Conclusions: PA inequality differed by setting time structure, with lower inequality during organized PA sessions. The Gini coefficient can illuminate PA inequalities in organized settings and may inform population PA improvement efforts in rural communities.

Background: Community-based coalitions are a common strategy for community engagement efforts targeting the improvement of a variety of population health outcomes. The typical processes that coalitions follow to organize efforts include steps that are sequential, slow, and time intensive. These processes also limit local decision-making to the selection of evidence-based policies or programs. Methods: We present a process control theory-based Community Action Process, Investigate-Design-Practice-Reflect (IDPR), where community hubs (i.e., coalitions) organize agile efforts in a non-sequential, rapid, and efficient manner to harness local assets and data to make decisions regarding the provision and production of population health services. Using qualitative methods, we illustrate and analyze the use of IDPR in a one community case study as part of Wellscapes, a Type 3-hybrid implementation-effectiveness community randomized controlled trial to improve children’s population health physical activity. Results: We found community members followed the IDPR Community Action Process to rapidly design, organize, deliver, and receive feedback on a community-based, children’s population physical activity prototype, an afterschool Play-in-the-Park opportunity for all children. Discussion: Following IDPR afforded the community coalition timely learning through feedback within a process that coordinated decisions regarding what community services met community needs (provision decisions) and how to organize the production of the population health services (production decisions).

Background: Locomotor and object control skills are considered essential skills for children to learn due to their potential impact in aiding in future health-enhancing physical activity. Evidence indicates that out-of-school time programs (OST) can provide meaningful movement opportunities for children. It has been found that leaders of OST programs are not equipped with the proper training to improve children’s motor skills. The purpose of this study was to gather expert consensus on the essential motor skills that should be practiced and evidence-based activities that should be integrated during OST programming. Methods: A three-round Delphi method was used to establish expert consensus on essential motor skills that children (5–10 years of age) should practice and evidence-based activities that should be integrated during OST programming to enhance child motor skill development. Results: Seven experts completed three rounds, and consensus was established (>70% agreement). Five essential motor skills were identified: overhand throwing, kicking, catching, jumping, and striking. Six evidence-based activities were agreed upon: team sport play, racket sports, swimming, resistance training, jogging/walking, and game-based approaches. Conclusion: Results from this study provide specific motor skills and evidence-based activities that program leaders could integrate during OST programming to enhance child motor skill development.

Purpose: Youth sport (YS) is a community system for promoting children's physical activity (PA). Studies have examined mean PA during YS practices, but few have examined inequalities in the distribution of PA among children during practice time. This study examined PA inequality in time-segmented YS practices and differences in inequality by time segment characteristics. Methods: Children's PA and YS practices were examined using accelerometer and video observation data from a sample of YS teams (n = 36 teams, n = 101 practices) for third- through sixth-grade children (n = 392), approximately eight to 12 years old, in two rural U.S. communities. Practices were time-segmented into smaller units (episodes; n = 991). Episodes were assigned codes for purpose (e.g. warm-up), member arrangement (e.g. whole group), and setting demand (i.e. fosters participation, creates exclusion). Group accelerometer data were paired with episodes, and the Gini coefficient quantified inequality in activity counts and minutes of moderate-to-vigorous PA (MVPA). Beta generalized estimating equations examined the influence of episode structure on PA inequality. Results: Warm-up (Gini = 0.22), fitness (Gini = 0.24), and sport skill (Gini = 0.24) episodes had significantly lower inequality (p < .05) in activity counts than other purpose types. Management (Gini = 0.32) and strategy (Gini = 0.40) episodes had significantly greater inequality (p < .05) in MVPA minutes than other purpose types. Episodes fostering participation (Gini = 0.32) had significantly lower activity count inequality (p < .05) than episodes creating exclusion (Gini = 0.35). Conclusion: PA inequality among children during YS varied by practice structure. Metrics such as the Gini coefficient can illuminate inequalities in PA and may be useful for guiding efforts to improve population PA in children. Trial Registration: This study is registered at www.clinicaltrials.gov (Identifier: NCT03380143).

Background: Approaches to prevent and manage diabetes at a community population level are hindered because current strategies are not aligned with the structure and function of a community system. We describe a community-driven process based on local data and rapid prototyping as an alternative approach to create diabetes prevention and care management solutions appropriate for each community. We report on the process and provide baseline data for a 3-year case study initiative to improve diabetes outcomes in two rural Nebraska communities. Methods: We developed an iterative design process based on the assumption that decentralized decision-making using local data feedback and monitoring will lead to the innovation of local sustainable solutions. Coalitions act as community innovation hubs and meet monthly to work through a facilitated design process. Six core diabetes measures will be tracked over the course of the project using the electronic health record from community clinics as a proxy for the entire community. Results: Baseline data indicate two-thirds of the population in both communities are at risk for prediabetes based on age and body mass index. However, only a fraction (35% and 12%) of those at risk have been screened. This information led both coalitions to focus on improving screening rates in their communities. Discussion: In order to move a complex system towards an optimal state (e.g., improved diabetes outcomes), stakeholders must have access to continuous feedback of accurate, pertinent information in order to make informed decisions. Conventional approaches of implementing evidence-based interventions do not facilitate this process.

"Data Coaching: A Strategy to Address Youth Physical Behavior, Motor Competence, and Out-of-School Time Leader Evidence-Based Practices" published on 12 Dec 2023 by Human Kinetics.

Background: To address low state physical education (PE) quantity and quality law implementation in elementary schools, the New York City Department of Education (NYCDOE) delivered a multilevel intervention (PE Works; 2015-2019), which included a district-led audit of school PE-law implementation, feedback, and coaching with principals. Using the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) implementation science framework, we assessed the primary multilevel drivers of success for this approach in increasing adherence to PE quantity and quality law. Methods: We conducted in-depth, semi-structured interviews with district-level personnel (n=17), elementary school administrators (n=18), and PE teachers (n=6) in 2020-21. Results: Interview results suggested several key RE-AIM drivers of successful PE law implementation. Reach: Ensure higher-need schools receive the necessary initial support to improve PE and later focus on lower-need schools. Effectiveness: Provide support tailored to school needs, not penalties, to improve PE. Adoption: Increase the priority of PE at both district and school levels (e.g., audit and feedback, themselves, appear to elevate PE’s priority). Streamline data collection and feedback reports; collecting/reporting too much information is burdensome and leads to lack of focus. Involve qualified (i.e., skilled in both school administration and PE programming/pedagogy) district-level personnel to work collaboratively with schools. Implementation: Build strong, trusting district-school relationships. Maintenance: Provide ongoing district-level support to schools and involve parents to advocate for quality PE. Conclusions: PE audits, feedback, and coaching (PEAFC) can guide schools in establishing long-term plans for successfully implementing PE-related law. Future research should examine the impact of PEAFC elsewhere (e.g., secondary schools, other districts).

Background: Communities are wellness landscapes of geospatially and temporally bound settings where children spend their time. Improving population physical activity (PA) requires investigating available community settings for children, such as classrooms and sport teams, and the dynamic social interactions producing PA. This protocol describes a multiscale community wellness landscape monitoring and feedback system of adult-led organized group settings and PA outcomes for children. Methods: The data system assessed organized groups for third- through sixth-grade children in 2 rural communities within seasons (fall 2018–2019). Within each season, groups were identified, sampled, and recruited. Sampled group meetings were assessed for children’s PA (accelerometry) and meeting routines (video observation). A data processing protocol time-segmented data into meetings and meeting routines into smaller units (sessions). A purpose code was assigned to each meeting (eg, classroom, sport) and session (eg, academic, PA). Group accelerometer data were paired with the coded segments. Multiscale metrics (season, meeting, and session) were generated and provided to the communities in tailored reports. Results: A total of 94 groups were recruited, and 73 groups with 1302 participants were included in the data system. Data were collected from 213 meetings and 844 sessions. Most participants (83.1%) consented to link their accelerometer data with demographic data from school enrollment records. Conclusions: The community data system identified available organized group settings for children and collected video and PA data from these settings. Incorporating setting data into local data systems provides detailed accounts of whole-of-community PA social systems to inform population health improvement efforts.