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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.

Background 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. This study examined the association between rural children’s demographic factors and OST non-sport organized activity participation and the differences between these factors and PA. Methods During Spring 2019, children (n = 418 3rd − 6th graders, aged 8–12 years) enrolled in two rural Midwestern public schools in the United States completed the Youth Activity Profile (YAP) and supplemental National Survey of Children’s Health 2017–2018 survey questions assessing OST organized activity participation as part of the Wellscapes Project, a type 3 hybrid implementation-effectiveness community randomized trial. A subsample of 235 children (males, n = 117; females, n = 118) provided parental/guardian consent to pair YAP results with student enrollment records. Average OST moderate-to-vigorous PA (MVPA) per weekday and weekend days was estimated using an algorithm converting raw YAP scores into minutes of MVPA. Mixed models with community as a random effect examined main effects and interactions of grade, sex, and family income on OST non-sport organized activity participation and these factors and participation on MVPA. Results Most children (73.2%) participated in an OST non-sport organized activity. Males were less likely to participate in organized activities than females (OR = 0.38, 95% CI = 0.20–0.73, p = 0.004). Females and 6th graders reported lower OST MVPA on weekdays and weekends than comparison groups (p diff = -4.7 ± 2.0 minutes) and weekends (meandiff = -8.9 ± 3.8 minutes) compared with males with higher family income (p ). Conclusions Many rural children participated in OST organized activities regardless of grade and family income. However, there were inequalities in organized activity participation and OST weekday and weekend MVPA by demographic factors, including grade, sex, and family income. Designing OST organized activity settings to include PA may aid in reducing PA inequalities and promoting health equity.

ObjectivesTo examine differences in rural community children’s moderate-to-vigorous physical activity (MVPA) and participation in out-of-school activities from fall 2019 to fall 2020 and explore enacted PA opportunity modifications post initial COVID-19 disruption.DesignMixed methods study using the validated Youth Activity Profile (YAP), administrator reports and stakeholder surveys and semistructured interviews.SettingChildren and community stakeholders from one rural US Great Plains community in the state of Nebraska were recruited.ParticipantsThird through fifth graders in fall 2019 (n=144) and fall 2020 (n=174) reported MVPA and participation in out-of-school activities using the YAP. School administrators reported weekly physical education (PE) and recess minutes. Community stakeholders reported pandemic-related changes in community social structures in semistructured interviews (n=4) and surveys (n=19).ResultsAverage daily MVPA minutes increased from 2019 to 2020 (75.0 vs 81.3, SE=1.6, pConclusionsIncreased minutes of PE and recess, and decreased out-of-school activity participation may have increased children’s overall free play and MVPA during the pandemic. Free play was an important contributor to children’s PA during the pandemic and should be prioritised by educators, coaches and other leaders of child PA opportunities.Trial registration numberNCT03380143.

Despite clear evidence of the potential benefits gained by being physically active, children and adolescents (collectively youth) often fail to achieve the recommended daily 60 min of moderate-to-v...

This two-part study aimed to first evaluate the preliminary effectiveness of a brief staff training intervention to promote physical activity among children attending an after-school program, and then to determine the feasibility of delivering the training to a larger number of sites. Two Boys and Girls Club after-school sites (intervention, control) participated in study 1. Accelerometer-measured physical activity of children and directly observed staff behaviors were assessed at each site in February and May 2019. Following baseline data collection, staff at the intervention site attended a brief physical activity promotion training, which emphasized expanding the quantity and enhancing the quality of physical activity opportunities. For study 2, the training was delivered to all staff, and they completed pre- and post-training measures of self-efficacy and intention to implement strategies to promote physical activity. In study 1, children at the intervention site decreased sedentary time by 14.8 min/day, and increased light and moderate-to-vigorous physical activity by 7.8 and 7.0 min/day, respectively, relative to the control site. Instances of staff encouragement significantly increased at the intervention site. In study 2, staff reported significant improvements in self-efficacy and intention immediately following the training. These studies provide preliminary evidence that a brief staff training intervention may increase physical activity among children attending an after-school program, and that the intervention can be integrated into existing training requirements. Future research is needed to replicate these findings across a wider range of after-school programs, and to explore systematic approaches to offering sustainable physical activity training regularly at scale.

In many applications of zero-inflated models, score tests are often used to evaluate whether the population heterogeneity as implied by these models is consistent with the data. The most frequently cited justification for using score tests is that they only require estimation under the null hypothesis. Because this estimation involves specifying a plausible model consistent with the null hypothesis, the testing procedure could lead to unreliable inferences under model misspecification. In this paper, we propose a score test of homogeneity for zero-inflated models that is robust against certain model misspecifications. Due to the true model being unknown in practical settings, our proposal is developed under a general framework of mixture models for which a layer of randomness is imposed on the model to account for uncertainty in the model specification. We exemplify this approach on the class of zero-inflated Poisson models, where a random term is imposed on the Poisson mean to adjust for relevant covariates missing from the mean model or a misspecified functional form. For this example, we show through simulations that the resulting score test of zero inflation maintains its empirical size at all levels, albeit a loss of power for the well-specified non-random mean model under the null. Frequencies of health promotion activities among young Girl Scouts and dental caries indices among inner-city children are used to illustrate the robustness of the proposed testing procedure.

Background Schools provide an ideal setting for promoting healthy lifestyles in youth, but it has proven difficult to promote the adoption and implementation of evidence-based programming by school leaders. The SWITCH® (School Wellness Integration Targeting Child Health) intervention is a capacity-building process designed to help school leaders learn how to plan, implement, and sustain school wellness programs on their own. Objective The present study evaluates the transdisciplinary approaches used in establishing an integrated research-practice partnership with the state-wide 4-H/Extension network to support broader dissemination. Method The study used a mixed methods approach to evaluate the degree of engagement and motivation of 4-H leaders (N = 30) for providing ancillary support for local school wellness programming. Engagement from 4-H Staff was logged over a year-long period through tracking completion of training and ongoing engagement with aspects of SWITCH. They completed checkpoint surveys and an interview to provide perceptions of supporting school implementation of SWITCH programming. Data were analysed through Pearson bivariate correlations and constant comparative analysis. Results County-level 4-H staff demonstrated high engagement in SWITCH by attending training sessions and hosting structured checkpoint sessions with schools. Interview data revealed that 4-H Staff valued connections with schools and emphasized that training on SWITCH was consistent with their existing roles related to youth programming. Conclusions The results demonstrate the value of the sequential capacity-building process used to train 4-H Staff to facilitate school wellness programming. The transdisciplinary approaches built transferable skills and fostered relationships that directly support the broader goals of 4-H.

Numerous dietary quality indices exist to help quantify overall dietary intake and behaviors associated with positive health outcomes. Most indices focus solely on biomedical factors and nutrient or food intake, and exclude the influence of important social and environmental factors associated with dietary intake. Using the Diet Quality Index- International as one sample index to illustrate our proposed holistic conceptual framework, this critical review seeks to elucidate potential adaptations to dietary quality assessment by considering—in parallel—biomedical, environmental, and social factors. Considering these factors would add context to dietary quality assessment, influencing post-assessment recommendations for use across various populations and circumstances. Additionally, individual and population-level evidence-based practices could be informed by contextual social and environmental factors that influence dietary quality to provide more relevant, reasonable, and beneficial nutritional recommendations.

BackgroundNumerous studies have tested school-based interventions promoting healthy behaviors in youth, but few have integrated dissemination and implementation (D&I) frameworks. Using D&I frameworks can inform if and how an evidence-based intervention is implemented and maintained and provide strategies to address contextual barriers. Such application is necessary to understand how and why interventions are sustained over time. We evaluated a school wellness initiative called SWITCH® (School Wellness Integration Targeting Child Health) to (1) assess implementation outcomes of adoption, fidelity, and penetration, (2) discern implementation determinants through the Consolidated Framework for Implementation Research (CFIR), and (3) examine differences among inexperienced and experienced schools and influential factors to sustainment.MethodsA total of 52 schools from Iowa, United States enrolled in the 2019–2020 iteration of SWITCH (22 inexperienced; 30 experienced). The CFIR guided the adaptation of mixed methods data collection and analysis protocols for school settings. Specific attention was focused on (1) fidelity to core elements; (2) adoption of best practices; and (3) penetration of behavior change practices. Determinants were investigated through in-depth qualitative interviews and readiness surveys with implementation leaders. A systematic process was used to score CFIR domains (between −2 and +2) indicating positive or negative influence. Independent t-tests were conducted to capture differences between samples, followed by a cross-case analysis to compare determinants data. Inductive coding yielded themes related to sustainment of SWITCH beyond formal implementation support.ResultsExperienced schools had higher scores on fidelity/compliance (t = −1.86 p = 0.07) and adoption (t = −2.03 p = 0.04). CFIR determinants of innovation source, culture, relative priority, and leadership engagement were positive implementation determinants, whereas tension for change and networks and communications were negative determinants. Distinguishing factors between experienced and inexperienced schools were Readiness for Implementation and Self-efficacy (experienced significantly higher; p < 0.05). Strategies to enhance sustainability were increasing student awareness/advocacy, keeping it simple, and integrating into school culture.ConclusionsFindings provide specific insights related to SWITCH implementation and sustainability but more generalized insights about the type of support needed to help schools implement and sustain school wellness programming. Tailoring implementation support to both inexperienced and experienced settings will ultimately enhance dissemination and sustainability of evidence-based interventions.

OBJECTIVE This study examined the individual and combined effects of a height-adjustable desk and an online behavioral intervention on sedentary behavior and health among university employees working from home. METHODS Participants (N = 95) were randomly assigned to one of four conditions: Desk Only, Program Only, Desk + Program, or Control. Desk participants received a height-adjustable desk; program participants received a 12-week web-based intervention. Outcomes measured at baseline and post-intervention included workday sitting and cardiometabolic health outcomes. RESULTS Reductions in sitting were largest in the Desk + Program condition (-206 min/workday; d = 1.84), followed by the Desk Only condition (-122 min/workday; d = 0.98), and the Program Only condition (-96 min/workday; d = 1.13). There were no significant changes in the health outcomes assessed. CONCLUSIONS Both a height-adjustable desk and an online behavioral intervention effectively reduced occupational sitting, and a combined approach was most effective.

Background Physical activity, a high-frequency health behavior, varies by where children live, learn, and play. Children accumulate physical activity in adult-led in-school and out-of-school settings. Youth sport is a potential setting for physical activity, but there are differences in youth sport participation based on age, sex, and socioeconomic status. There is a gap in understanding demographic influences on youth sport participation and how these factors interact to influence physical activity. This study examines influences of grade, sex, and family income on youth sport participation and these factors and youth sport participation on moderate-to-vigorous physical activity of children in rural communities. Methods Children (n = 418 3rd–6th graders) living in two rural communities completed the online Youth Activity Profile as part of Wellscapes, a type 3 hybrid implementation-effectiveness community randomized trial. Mixed models with community as a random effect examined main effects and interactions of grade, sex, and family income on youth sport participation and these factors and youth sport participation on moderate-to-vigorous physical activity. Results About 80% of children engaged in youth sport, and full-pay lunch students were almost four times more likely to have youth sport participation than students with free/reduced lunch (OR = 3.91, 95% CI = 1.95, 7.8). Females and 6th graders (p p Conclusions While a fairly high percentage of children participate in youth sports, there are disparities in rural communities on youth sport participation and physical activity outcomes based on age, sex, and family income.

BackgroundPhysical activity, a high-frequency health behavior, varies by where youth live, learn, and play. Youth accumulate physical activity in adult-led in-school and out-of-school settings. Youth sport is a potential setting for physical activity, but there are differences in youth sport participation based on age, gender, and socioeconomic status. There is a gap in understanding demographic influences on youth sport participation and how these factors interact to influence physical activity. This case study examines influences of grade, gender, and family income on youth sport participation and these factors and youth sport participation on moderate-to-vigorous physical activity of youth in rural communities.MethodsYouth (n=418 3rd–6th graders) living in two rural communities completed the online Youth Activity Profile as part of Wellscapes, a type 3 hybrid implementation-effectiveness community randomized trial. Mixed models with community as a random effect examined main effects and interactions of grade, gender, and family income on youth sport participation and these factors and youth sport participation on moderate-to-vigorous physical activity. ResultsAbout 80% of youth engaged in youth sport, and full pay lunch students were almost four times more likely to have youth sport participation than students with free/reduced lunch (OR = 3.91, 95% CI = 1.95, 7.8). Females and 6th graders (p th graders, high family income had less effect on physical activity than similar 3rd-5th graders (p

Sedentary behavior negatively impacts mental health, which can decrease employee productivity. Employee mental well-being and work performance may improve with sedentary reduction interventions, especially strategies that include environmental workplace modifications and behavior-changing strategies. However, such interventions have not been examined among employees working remotely during the COVID-19 pandemic. As part of the Stand Up Kansas program, 95 sedentary university employees working from home were randomized into one of four intervention arms: height-adjustable desk provision (Desk Only), online sedentary behavior modification program (Program Only), Desk + Program, or Control. The outcomes were measured at a baseline (November 2020) and following the 12-week intervention (February 2021). Employees reported mood (positive and negative affect), stress, fatigue (duration, interference with activities and severity) and work performance (irritability, focus, work satisfaction, non-work satisfaction and productivity) were measured using established self-report instruments. The effect sizes, by comparing the Control arm to the Desk + Program arm, revealed large improvements in mood (positive affect, d = 1.106). Moderate improvements were also seen in fatigue (duration, d = −0.533, and interference with activities, d = −0.648) and several aspects of work performance (focus, d = 0.702, work satisfaction, d = 0.751, and productivity, d = 0.572). Moderate effect sizes were also seen for positive affect (d = 0.566) and fatigue severity (d = 0.577) among the Program Only arm, whereas no noteworthy effect sizes were observed among the Desk Only arm. Combining an online sedentary behavior modification program with height-adjustable desk provisions appeared to positively affect mental well-being and work performance among remote employees.

Research suggests that the dietary quality (DQ) of school lunches meeting the National School Lunch Program (NSLP) requirements may vary significantly. Possible drivers of variation include factors, such as socioeconomic status (SES) and rurality. The purpose of this cross-sectional study was to determine whether there was variation in nutrient content and DQ by SES and rurality, when analyzing middle school lunch menus meeting NSLP requirements. A random sample of 45 Kansas middle school lunch menus each were obtained from websites of randomly selected districts from low- and high-SES strata. Thirty-day menus were analyzed for nutrient content. Healthy Eating Index (HEI) 2015 scores were calculated for DQ. Rurality was determined for schools by National Center for Education Statistics (NCES) locale. There were significant differences in added sugar (p &lt, 0.001) and calcium (p = 0.001) favoring high-SES menus, and in sodium (p = 0.001) favoring low-SES menus. There were no nutrient differences by rurality. The HEI scores were not different by SES or rurality, with a mean score (SD) 61.9 (2.6) across all schools. Middle school lunch DQ in Kansas does not vary by SES or rurality. Efforts to improve DQ should focus on all foodservice operations, not specifically low-SES or rural schools.

Background School wellness programming is important for promoting healthy lifestyles and academic achievement in youth; however, research is needed on methods that can help schools implement and sustain such programs on their own. The purpose of this study was to investigate factors within and outside the school environment that influenced school capacity for implementation and potential sustainability of wellness programming. Methods As part of the School Wellness Integration Targeting Child Health (SWITCH®) intervention, elementary school wellness teams (N = 30) were guided through a capacity-building process focused on promoting the adoption of healthy lifestyle behaviors in students. Data on implementation were collected through three standardized surveys and interviews (pre-mid-post) and a post-implementation interview. Indicators of organizational capacity were assessed using the School Wellness Readiness Assessment (SWRA). Paired t-tests were run to assess changes in implementation (classroom, physical education, and lunchroom settings), capacity, and stakeholder engagement over time. One-way analysis of variance (ANOVA) tests were run to examine how implementation of best practices (low, moderate, high) explained differences in capacity gains. Qualitative data were analyzed through inductive and deductive analysis, following the Consolidated Framework for Implementation Research (CFIR). Results Paired t-tests showed non-significant increases in school and setting-specific capacity and implementation of SWITCH best practices over time, in addition to a consistent level of engagement from key stakeholders. ANOVA results revealed non-significant associations between implementation group and gains in school capacity (F [2, 24] = 1.63; p = .21), class capacity (F [2, 24]=0.20 p = .82), lunchroom capacity (F [2, 24]=0.29; p = .78), and physical education (F [2, 24]=1.45; p = .25). Qualitative data demonstrated that factors within the outer setting (i.e., engaging community partners) facilitated programming. Inner-setting factors (i.e., relationships with administration and staff) influenced implementation. Implementation process themes (e.g., planning, adaptation of resources to meet school capacity/needs, and engaging students as leaders) were cited as key facilitators. Schools discussed factors affecting sustainability, such as school culture and knowledge of school wellness policy. Conclusions The results from this implementation study document the importance of allowing schools to adapt programming to meet their local needs, and highlight the strengths of measuring multiple implementation outcomes. Increased support is needed for schools regarding the formation and improvement of wellness policies as a means to enhance sustainability over time.

Reducing sedentary behavior in the workplace has become an important public health priority, however, some employers have expressed concerns regarding the potential for reduced productivity if employees are not seated while at work. Therefore, the aim of this study was to determine the relationship between workplace sedentary behavior (sitting time) and work productivity among full-time office-based employees, and further to investigate other potential factors associated with productivity. A 19-item online self-report survey was completed by 2068 government employees in Kansas. The survey assessed workplace sedentary behavior, work productivity, job satisfaction, and fatigue. Overall, office workers reported high levels of sedentary time (mean &gt, 78%). The primary results indicated that sitting time was not significantly associated with productivity (&beta, = 0.013, p = 0.519), but job satisfaction and fatigue were positively (&beta, = 0.473, p &lt, 0.001) and negatively (&beta, = &minus, 0.047, p = 0.023) associated with productivity, respectively. Furthermore, participants with the highest level of sitting time (&gt, 91% of the time) reported lower job satisfaction and greater fatigue as compared with the lowest level of sitting time (&lt, 75% of the time). Taken together, these results offer promising support that less sitting time is associated with positive outcomes that do not seem to come at the expense of productivity.

Background: School wellness programming is important for promoting academic achievement and healthy lifestyles in youth; however, research is needed on methods that can help schools implement and sustain programs on their own. The purpose of this study was to investigate factors within and outside the school environment that impacted school capacity for implementation and potential sustainability of wellness programming. Methods: As part of the School Wellness Integration Targeting Child Health (SWITCH®) intervention, elementary school wellness teams (N=30) were guided through a capacity-building process focused on promoting the adoption of healthy lifestyle behaviors in students. Data on implementation were collected through three standardized surveys and interviews (pre-mid-post) and a post-implementation interview. Indicators of organizational capacity were assessed using the School Wellness Readiness Assessment (SWRA). Paired t-tests were run to assess changes in implementation (classroom, physical education, lunchroom settings), capacity, and stakeholder engagement over time. One-way analysis of variance (ANOVA) tests were run to examine how implementation of best practices (low, moderate, high) explained differences in capacity gains. Qualitative data were analyzed through inductive and deductive analysis, following the Consolidated Framework for Implementation Research (CFIR). Results: Paired t-tests showed non-significant increases in school and setting-specific capacity and implementation of SWITCH best practices over time, in addition to a consistent level of engagement from key stakeholders. ANOVA analyses revealed positive, non-significant variances between implementation group and gains in school capacity (F[2,24]=1.63; p=.21), class capacity (F[2,24]=0.20 p=.82), lunchroom capacity (F[2,24]=0.29; p=.78), and physical education (F[2,24]=1.45; p=.25). Qualitative data demonstrated factors within the outer setting (i.e., engaging community partners) that facilitated programming. Inner-setting factors (i.e., relationships with administration and staff) significantly affected implementation. Implementation process construct themes (e.g., planning, adaptation of resources to meet school capacity/needs, and engaging students as leaders) were cited as key facilitators. Schools discussed factors impacting sustainability, such school culture and knowledge of school wellness policy. Conclusions: Findings suggest a modest but important impact of implementation on capacity change which is the primary goal of SWITCH. The results document the importance of allowing schools to adapt programming to meet their local needs.

As technological innovations continue to be developed and introduced within healthcare, public health, and our daily lives, human beings now have access to sophisticated and powerful tools that could be used in a variety of ways to change health behaviours. Information and communications technology (ICT) features prominently among 21st century innovations, and we must consider how they may be used to help or hinder our efforts to address population health challenges. There are numerous relevant challenges that need to be addressed within healthcare, public health, and other areas relevant to population health. The Australian population is aging (increasing in both the absolute number, and also proportion of older adults), along with having greater levels of obesity, diabetes, cardiovascular diseases, cancers, and other chronic diseases that will take a large toll on Australia. There are many lifestyle determinants of chronic disease that could potentially be addressed through ICT-based intervention efforts to improve diet, physical activity, alcohol, tobacco, sleep, and sexual behaviour. Challenges also include better delivery of what innovations or interventions have been shown to work, how we can best help those who need help the most, and how to implement policy, systems, or environmental interventions that can help to make healthy behaviours more convenient, attractive, and normative. As the name suggests, ICT involves any technology that allows us to store, retrieve, manipulate, transmit, or receive information electronically in a digital form. Although such technologies may allow us to reach more people than we could without them, and to do so in more rapid manner, with better geographic reach than ever before, ICT does not automatically provide any advantage in addressing the key drivers of health behaviour. Information itself could be useful-but is almost never sufficient-to facilitate health behaviour change; rather, information must instead be placed within the context of the key drivers of behaviour change. These drivers can be described most simply as factors that enhance people's capability, opportunity, and motivation to engage in health promoting behaviour, or their obverse, behaviours that undermine health. Beyond the storage, retrieval, manipulation, transmission, or receipt of information, we must ensure that key drivers of behaviour are built into ICT approaches. Understanding, predicting, and influencing human behaviour is crucially important if we aim to address relevant population health challenges, and to achieve better health and wellness within populations. In other words, if we want to be well, we need to be "well behaved." Illustrative examples will be shared from the author's research studies, primarily focused on motivating and building the capability of adult leaders to provide better opportunities for children to be physically active, eat healthfully, and to establish health promoting habits. These studies range from interventions set in girl scouts, schools, and whole communities, with a variety of ICT approaches.

Health behaviour change programs that utilise IT-based delivery have great potential to improve health. Whilst more static Web 1.0 technologies have been somewhat effective, they often failed to promote longer-term user engagement required for greater health promotion impact. With Web 2.0 technologies, however, there is potential for greater engagement and retention, through allowing individuals to determine how information is generated, modified, and shared collaboratively. The WALK 2.0 study utilised a Web 2.0-based platform to engage participants in health behaviour change aimed at increasing physical activity levels. The program included two trials: (1) a three-arm randomised controlled trial (RCT) that compared the effectiveness of Web 2.0, Web 1.0, and paper-based logbook interventions; and (2) a real-world randomised ecological trial (RET) that compared a Web 2.0 and Web 1.0 intervention. The aim of this paper is not to focus on the research trial results per se, but rather the success factors and challenges in both the RCT and RET. Both the RCT and RET demonstrated successful outcomes, with greater improvements in physical activity for the Web 2.0 groups. A range of challenges, however, were identified in designing, implementing, and evaluating such interventions. These include IT-based intervention development within a research context, the ability to establish a self-sustaining online community, the rapid pace of change in web-based technology and implications for trial design, the selection of best outcome measures for ecological trials, and managing engagement, non-usage and study attrition in real-world trials. Future research and developments in this area must look to broader research designs that allow for the ever-changing IT-user landscape and behaviour, and greater reliance on development and testing in real-world settings.

Girl Scouts (GS) is a setting with large reach to target increased moderate-to-vigorous physical activity (MVPA) in girls. The Scouting Nutrition and Activity Program (SNAP) increased MVPA during intervention troop meetings; therefore, further examination of implementation of SNAP components is warranted to determine the processes contributing to intervention success. The purpose of this study is to examine variability in implementation of an active recreation (AR) policy into GS troop meetings. Troop leaders (n = 7) were randomized to receive SNAP, an intervention training on implementing a policy promoting AR, or a standard control. Meetings (seven meetings/troop) were observed, and girls in attendance (n = 76, 9–13 years, mean ± SD = 10.51 ± 1.19 years) wore ActiGraph GT1M accelerometers. Two observers attended each meeting and recorded start/stop points of AR time segments, as well as other tasks (i.e., opening/closing, snack, and Girl Scout curriculum [GSC]). Time-segmented accelerometer data were analyzed using Evenson cut points and paired with observation data. Researchers observed 181 segments (mean/day ± SD = 3.77 ± 1.24). Intervention troops implemented more AR segments/day (mean/day = 0.86; 95% CI = 0.62–1.09) than control troops (mean/day = 0.18; 95% CI = 0.00–0.39). A greater percentage of time (%time) was spent in MVPA during AR segments (mean = 10.99; 95% CI = 7.16–14.82) compared with GSC segments (mean = 0.73; 95% CI = 0.00–4.10), opening/closing (mean = 3.96; 95% CI = 0.54–7.38), and snack (mean = 0.74; 95% CI = 0.00–4.10) segments, and during opening/closing segments compared with GSC and snack segments. Intervention troops implemented more AR segments than control troops. Troop meeting patterns of PA were influenced by task. Adding time segments conducive to PA could increase the %time spent in MVPA during GS troop meetings.

Research into associations between lifestyle behaviours and health has largely focused on morbidity, mortality and disease prevention. Greater focus is needed to examine relationships between lifestyle behaviours and positive health outcomes such as well-being. This study aims to examine the associations between multiple lifestyle behaviours and excellent well-being. Participants (n = 6788) were adults in the member database of the 10,000 Steps Australia project who were asked to participate in an online survey in November–December 2016. Well-being (WHO-5) Smoking, dietary behaviour, alcohol consumption, physical activity, sitting time, sleep duration, and sleep quality were assessed by self-report. Logistic regression analyses were used to examine relationships between excellent well-being (top quintile) and the individual lifestyle behaviours and also a lifestyle behaviour index (the number of lower-risk behaviours performed). Lower-risk dietary behaviour (OR = 1.29, 95% CI: 1.10–1.51), physical activity (OR = 1.90, 95% CI: 1.48–2.42), sitting time (OR = 1.46, 95% CI: 1.26–1.69), sleep duration (OR = 1.52, 95% CI: 1.32–1.75) and higher sleep quality (OR = 2.98, 95% CI: 2.55–3.48) were positively associated with excellent well-being, after adjusting for socio-demographics, chronic disease, depression, anxiety and all other lifestyle behaviours. Engaging in a higher number of lower risk lifestyle behaviours was positively associated with excellent well-being. These results highlight the need for multiple lifestyle behaviour interventions to improve and maintain higher well-being.

BACKGROUND School lunches must meet National School Lunch Program (NSLP) requirements to receive reimbursement. In this study, we sought to determine whether there are significant differences in nutrient content and nutritional quality between 2 menus meeting NSLP requirements. METHODS A cross-sectional content analysis compared 6 weeks of a typical school lunch menu (TM) from an actual school district to a best practice school lunch menu (BPM) created by a registered dietitian based on Child and Adult Care Food Program (CACFP) best practices and Dietary Guidelines for Americans (DGA) healthy meal pattern recommendations. Daily nutrient content was determined using nutrient analysis software. Nutritional quality was computed using Healthy Eating Index (HEI) 2010. RESULTS For nutrients required for analysis, the BPM was lower in calories, saturated fat, and sodium and higher in protein, carbohydrate, and fiber (ps < .01). For other nutrients of concern, the BPM was higher in vitamin A, vitamin D, phosphorus, and magnesium (ps < .01). The BPM had higher HEI scores for nutritional quality (p < .001). CONCLUSIONS Results indicate the possibility for significant variation in nutritional quality of NSLP-qualifying lunches. Using CACFP best practices and DGA recommendations may significantly impact school lunch dietary quality.

Purpose: To evaluate the effectiveness of in-person versus online Girl Scout leader wellness training for implementation of wellness-promoting practices during troop meetings (phase I) and to assess training adoption and current practices across the council (phase II). Design: Pragmatic superiority trial (phase 1) followed by serial cross-sectional study (phase II). Setting: Girl Scout troop meetings in Northeast Kansas. Participants: Eighteen troop leaders from 3 counties (phase 1); 113 troop leaders from 7 counties (phase II). Intervention: Phase I: Troop leaders attended 2 wellness training sessions (first in groups, second individually), wherein leaders set wellness-promoting practice implementation goals, self-monitored progress, and received guidance and resources for implementation. Leaders received the intervention in person or online. Measures: Phase I: At baseline and postintervention, leaders completed a wellness-promoting practice implementation questionnaire assessing practices during troop meetings (max score = 11). Phase II: Leaders completed a survey about typical troop practices and interest in further training. Analysis: Phase I: Generalized linear mixed modeling. Results: Phase I: In-person training increased wellness-promoting practice implementation more than online training (in person = 2.1 ± 1.8; online = 0.2 ± 1.2; P = .022). Phase II: Fifty-six percent of leaders adopted the training. For 8 of 11 wellness categories, greater than 50% of leaders employed wellness-promoting practices. Conclusion: In-person training was superior to online training for improvements in wellness-promoting practices. Wellness training was adopted by the majority of leaders across the council.

Cardiovascular disease (CVD, i.e., disease of the heart and blood vessels) is a major cause of death globally. Current assessment tools use either clinical or non-clinical factors alone or in combination to assess CVD risk. The aim of this review was to critically appraise, compare, and summarize existing non-clinically based tools for assessing CVD risk factors in underserved young adult (18–34-year-old) populations. Two online electronic databases—PubMed and Scopus—were searched to identify existing risk assessment tools, using a combination of CVD-related keywords. The search was limited to articles available in English only and published between January 2008 and January 2019. Of the 10,383 studies initially identified, 67 were eligible. In total, 5 out of the 67 articles assessed CVD risk in underserved young adult populations. A total of 21 distinct CVD risk assessment tools were identified; six of these did not require clinical or laboratory data in their estimation (i.e., non-clinical). The main non-clinically based tools identified were the Heart Disease Fact Questionnaire, the Health Beliefs Related to CVD-Perception measure, the Healthy Eating Opinion Survey, the Perception of Risk of Heart Disease Scale, and the WHO STEPwise approach to chronic disease factor surveillance (i.e., the STEPS instrument).

Whole-of-community interventions delivered across entire geospatial areas show promise for improving population health for youth cancer prevention. The aims of this scoping review were to synthesize the whole-of-community intervention literature on six modifiable risk factors in youth for cancer prevention (alcohol use, diet, obesity, physical activity, sun exposure, tobacco use) and to develop and apply a typology describing the inclusion of fundamental control system functional characteristics. A systematic search was conducted in PubMed, Cumulative Index to Nursing and Allied Health Literature, Embase, PsycINFO, and Scopus for studies published to the end of 2019. Eligible studies included a geospatially defined whole-of-community intervention; youth 0–18 years; and at least one of the six cancer risk factor outcomes. An iterative process was undertaken to create a typology describing the functions for whole-of-community interventions guided by systems theory, and the typology was used to code the included interventions. A total of 41 interventions were included. Most interventions (43.9%) assessed multiple cancer risk factors. Few interventions provided fundamental functions necessary for community system coordination: sensor, controller, effector. Although communities are a patchwork quilt of microsystems where individuals interact in geographically bounded places nested within larger whole systems of influence, a control systems approach has not been used to frame the literature. Whole-of-community interventions can be characterized by the fundamental system functions necessary for coordinating population health improvement. Future whole-of-community intervention efforts should draw on fundamental knowledge of how systems operate and test whether adoption of the key functions is necessary for whole-of-community population health improvement.

Highlights • Data Sharing Agreements result in accessible, relevant, and timely community data. • Stakeholder data training workshops support communities in surveillance efforts. • Surveillance as standard educational practice yields local population PA estimates. • Local data can drive community decisions regarding youth PA opportunities., Accurate and effective local data collection systems are needed to inform community change on youth health behaviors such as physical activity (PA). Systematic methods are particularly important for understanding PA behaviors that may be influenced by individual, interpersonal, organizational, and regional factors. The purpose of this study was to describe a protocol for coordinating community stakeholders to implement an online youth PA surveillance instrument. The research team collaborated with local health departments (LHDs) from two rural communities to coordinate schools in implementing school-wide youth PA surveillance. A data sharing agreement was established between all partners. School administrators and teachers attended in-person training sessions for an online PA survey and how to use the data. Following the training, students were provided individualized logins to complete the survey once a semester over a two-year academic period. Across both communities, 23 teachers and administrators attended the training sessions that were facilitated by the LHDs and research team. In Year 1 (Y1), a total of 465 3rd through 6th grade students were enrolled in the participating schools (community 1 = 227; community 2 = 238). Survey response rates ranged from 86.1% to 95.4% completion, depending on the community and semester. In Year 2 (Y2), a total of 501 3rd through 6th grade students were enrolled (community 1 = 260; community 2 = 241). Response rates ranged from 86.3% to 89.6% in the fall term. A protocol for coordinating LHD and community stakeholders was an effective strategy for implementing population-level youth PA surveillance with high levels of reach.