Balancing best practice and reality in behavioral intervention development: A survey of principal investigators funded by the National Institutes of Health

Preliminary studies play a prominent role in the development of large-scale behavioral interventions. Though recommendations exist to guide the execution and interpretation of preliminary studies, these assume optimal scenarios which may clash with realities faced by researchers. The purpose of this study was to explore how principal investigators (PIs) balance expectations when conducting preliminary studies. We surveyed PIs funded by the National Institutes of Health to conduct preliminary behavioral interventions between 2000 and 2020. Four hundred thirty-one PIs (19% response rate) completed the survey (November 2021 to January 2022, 72% female, mean 21 years post-terminal degree). Most PIs were aware of translational models and believed preliminary studies should precede larger trials but also believed a single preliminary study provided sufficient evidence to scale. When asked about the relative importance of preliminary efficacy (i.e. changes in outcomes) and feasibility (i.e. recruitment, acceptance/adherence) responses varied. Preliminary studies were perceived as necessary to successfully compete for research funding, but among PIs who had peer-reviewed federal-level grants applications (n = 343 [80%]), responses varied about what should be presented to secure funding. Confusion surrounding the definition of a successful, informative preliminary study poses a significant challenge when developing behavior interventions. This may be due to a mismatch between expectations surrounding preliminary studies and the realities of the research enterprise in which they are conducted. To improve the quality of preliminary studies and advance the field of behavioral interventions, additional funding opportunities, more transparent criteria in grant reviews, and additional training for grant reviewers are suggested.

Consolidated guidance for behavioral intervention pilot and feasibility studies

BACKGROUND

In the behavioral sciences, conducting pilot and/or feasibility studies (PFS) is a key step that provides essential information used to inform the design, conduct, and implementation of a larger-scale trial. There are more than 160 published guidelines, reporting checklists, frameworks, and recommendations related to PFS. All of these publications offer some form of guidance on PFS, but many focus on one or a few topics. This makes it difficult for researchers wanting to gain a broader understanding of all the relevant and important aspects of PFS and requires them to seek out multiple sources of information, which increases the risk of missing key considerations to incorporate into their PFS. The purpose of this study was to develop a consolidated set of considerations for the design, conduct, implementation, and reporting of PFS for interventions conducted in the behavioral sciences.

METHODS

To develop this consolidation, we undertook a review of the published guidance on PFS in combination with expert consensus (via a Delphi study) from the authors who wrote such guidance to inform the identified considerations. A total of 161 PFS-related guidelines, checklists, frameworks, and recommendations were identified via a review of recently published behavioral intervention PFS and backward/forward citation tracking of a well-known PFS literature (e.g., CONSORT Ext. for PFS). Authors of all 161 PFS publications were invited to complete a three-round Delphi survey, which was used to guide the creation of a consolidated list of considerations to guide the design, conduct, and reporting of PFS conducted by researchers in the behavioral sciences.

RESULTS

A total of 496 authors were invited to take part in the three-round Delphi survey (round 1, N = 46; round 2, N = 24; round 3, N = 22). A set of twenty considerations, broadly categorized into six themes (intervention design, study design, conduct of trial, implementation of intervention, statistical analysis, and reporting) were generated from a review of the 161 PFS-related publications as well as a synthesis of feedback from the three-round Delphi process. These 20 considerations are presented alongside a supporting narrative for each consideration as well as a crosswalk of all 161 publications aligned with each consideration for further reading.

CONCLUSION

We leveraged expert opinion from researchers who have published PFS-related guidelines, checklists, frameworks, and recommendations on a wide range of topics and distilled this knowledge into a valuable and universal resource for researchers conducting PFS. Researchers may use these considerations alongside the previously published literature to guide decisions about all aspects of PFS, with the hope of creating and disseminating interventions with broad public health impact.

The Day-Level Association Between Child Care Attendance and 24-Hour Movement Behaviors in Preschool-Aged Children

BACKGROUND

Twenty-four hour movement behaviors (ie, physical activity [PA], screen time [ST], and sleep) are associated with children's health outcomes. Identifying day-level contextual factors, such as child care, that positively influence children's movement behaviors may help identify potential intervention targets, like improving access to child care programs. This study aimed to examine the between- and within-person effects of child care on preschoolers' 24-hour movement behaviors.

METHODS

Children (N = 74, 4.7 [0.9] y, 48.9% girls, 63.3% White) wore an Axivity AX3 accelerometer on their nondominant wrist 24 hours per day for 14 days to measure PA and sleep. Parents completed surveys each night about their child's ST and child care attendance that day. Linear mixed effects models predicted day-level 24-hour movement behaviors from hours spent in child care.

RESULTS

Children spent an average of 5.0 (2.9) hours per day in child care. For every additional hour of child care above their average, children had 0.3 hours (95% CI, -0.3 to -0.2) less ST that day. Between-person effects showed that compared with children who attended fewer overall hours of child care, children who attended more hours had less overall ST (B = -0.2 h; 95% CI, -0.4 to 0.0). Child care was not significantly associated with PA or sleep.

CONCLUSIONS

Child care attendance was not associated with 24-hour PA or sleep; however, it was associated with less ST. More research utilizing objective measures of ST and more robust measures of daily schedules or structure is necessary to better understand how existing infrastructure may influence preschool-aged children's 24-hour movement behaviors. In addition, future research should consider how access to child care may influence child care attendance.

Understanding Accelerated Summer Body Mass Index Gain by Tracking Changes in Children's Height, Weight, and Body Mass Index Throughout the Year

Background: Drivers of summer body mass index (BMI) gain in children remain unclear. The Circadian and Circannual Rhythm Model (CCRM) posits summer BMI gain is biologically driven, while the Structured Days Hypothesis (SDH) proposes it is driven by reduced structure. Objectives: Identify the mechanisms driving children's seasonal BMI gain through the CCRM and SDH. Methods: Children's (N = 147, mean age = 8.2 years) height and weight were measured monthly during the school year, and once in summer (July-August). BMI z-score (zBMI) was calculated using CDC growth charts. Behaviors were measured once per season. Mixed methods regression estimated monthly percent change in children's height (%HΔ), weight (%WΔ), and monthly zBMI for school year vs. summer vacation, seasonally, and during school months with no breaks vs. school months with a break ≥1 week. Results: School year vs. summer vacation analyses showed accelerations in children's %WΔ (Δ = 0.9, Standard Error (SE) = 0.1 vs. Δ = 1.4, SE = 0.1) and zBMI (Δ = -0.01, SE = 0.01 vs. Δ = 0.04, SE = 0.3) during summer vacation, but %HΔ remained relatively constant during summer vacation compared with school (Δ = 0.3, SE = 0.0 vs. Δ = 0.4, SE = 0.1). Seasonal analyses showed summer had the greatest %WΔ (Δ = 1.8, SE = 0.4) and zBMI change (Δ = 0.05, SE = 0.03) while %HΔ was relatively constant across seasons. Compared with school months without a break, months with a break showed higher %WΔ (Δ = 0.7, SE = 0.1 vs. Δ = 1.6, SE = 0.2) and zBMI change (Δ = -0.03, SE = 0.01 vs. Δ = 0.04, SE = 0.01), but %HΔ was constant (Δ = 0.4, SE = 0.0 vs. Δ = 0.3, SE = 0.1). Fluctuations in sleep timing and screen time may explain these changes. Conclusions: Evidence for both the CCRM and SDH was identified but the SDH may more fully explain BMI gain. Interventions targeting consistent sleep and reduced screen time during breaks from school may be warranted no matter the season.

A Device Agnostic Approach to Predict Children's Activity from Consumer Wearable Accelerometer Data: A Proof-of-Concept Study

INTRODUCTION

This study examined the potential of a device agnostic approach for predicting physical activity from consumer wearable accelerometry compared with a research-grade accelerometry.

METHODS

Seventy-five 5- to 12-year-olds (58% male, 63% White) participated in a 60-min protocol. Children wore wrist-placed consumer wearables (Apple Watch Series 7 and Garmin Vivoactive 4) and a research-grade device (ActiGraph GT9X) concurrently with an indirect calorimeter (COSMED K5). Activity intensities (i.e., inactive, light, moderate-to-vigorous physical activity) were estimated via indirect calorimetry (criterion), and the Hildebrand thresholds were applied to the raw accelerometer data from the consumer wearables and research-grade device. Epoch-by-epoch (e.g., weighted sensitivity, specificity) and discrepancy (e.g., mean bias, absolute error) analyses evaluated agreement between accelerometry-derived and criterion estimates. Equivalence testing evaluated the equivalence of estimates produced by the consumer wearables and ActiGraph.

RESULTS

Estimates produced by the raw accelerometry data from ActiGraph, Apple, and Garmin produced similar criterion agreement with weighted sensitivity = 68.2% (95% confidence interval (CI), 67.1%-69.3%), 73.0% (95% CI, 71.8%-74.3%), and 66.6% (95% CI, 65.7%-67.5%), respectively, and weighted specificity = 84.4% (95% CI, 83.6%-85.2%), 82.0% (95% CI, 80.6%-83.4%), and 75.3% (95% CI, 74.7%-75.9%), respectively. Apple Watch produced the lowest mean bias (inactive, -4.0 ± 4.5; light activity, 2.1 ± 4.0) and absolute error (inactive, 4.9 ± 3.4; light activity, 3.6 ± 2.7) for inactive and light physical activity minutes. For moderate-to-vigorous physical activity, ActiGraph produced the lowest mean bias (1.0 ± 2.9) and absolute error (2.8 ± 2.4). No ActiGraph and consumer wearable device estimates were statistically significantly equivalent.

CONCLUSIONS

Raw accelerometry estimated inactive and light activity from wrist-placed consumer wearables performed similarly to, if not better than, a research-grade device, when compared with indirect calorimetry. This proof-of-concept study highlights the potential of device-agnostic methods for quantifying physical activity intensity via consumer wearables.

Using the Nutrition Facts Label to Make Food Choices Is Associated with Healthier Eating among 8th and 11th-Grade Students: An Analysis of Statewide Representative Data from the 2019-2020 Texas School Physical Activity and Nutrition Survey

BACKGROUND

Nutrition labels are a tool to inform and encourage the public to make healthier food choices, but little information is available about use in multi-ethnic adolescent populations in the U.S. The purpose of this study was to examine associations between the level of nutrition label usage and healthy/unhealthy eating behaviors among a statewide representative sample of 8th and 11th-grade students in Texas.

METHODS

We analyzed cross-sectional associations between the Nutrition Facts label use and eating behaviors from a statewide sample of 8th and 11th-grade students in Texas, (n = 4730, weighted n = 710,731, mean age = 14.7 ± 1.6 years; 49% female, 51% Hispanic), who completed the 2019-2020 Texas School Physical Activity and Nutrition (TX SPAN) survey. Students self-reported their level of nutrition label usage to make food choices (5-point Likert scale from "Never" to "Always") and previous day consumption of 26 food items (13 healthy, 13 unhealthy). The 26 food items were used to calculate a Healthy Eating Index (HEI) score (0-100), a Healthy Foods Index (HFI) score (0-100), and an Unhealthy Foods Index (UFI) score (0-100). Weighted linear regression models were employed to examine the associations between self-reported use of nutrition labels to make food choices and HEI, HFI, and UFI scores. Marginal predicted means of HEI, HFI, and UFI scores were calculated post hoc from linear regression models. The odds of consuming specific individual food items for nutrition label usage were also calculated from weighted logistic regression models. All linear and logistic regression models were adjusted for grade, sex, Body Mass Index (BMI), race/ethnicity, economic disadvantage, and percentage of English language learners by school.

RESULTS

A total of 11.0% of students reported always/almost always using nutrition labels to make food choices, 27.9% reported sometimes using them, while 61.0% indicated they never/almost never used nutrition labels to make food choices. The average HEI score among students in the sample was 47.7 ± 5.9. Nutrition Facts label usage was significantly and positively associated with HEI (b = 5.79, 95%CI: 4.45, 7.12) and HFI (b = 7.28, 95%CI:4.48, 10.07), and significantly and negatively associated with UFI (b = -4.30, 95%CI: -6.25, -2.34). A dose-response relationship was observed between nutrition label usage and HEI, HFI, and UFI scores, such that the strength of these associations increased with each one-point increase in nutrition label usage. Students who reported using nutrition labels always/almost always to make food choices had significantly higher odds of consuming healthy foods including baked meat, nuts, brown bread, vegetables, whole fruit, and yogurt (ORrange = 1.31-3.07), and significantly lower odds of consuming unhealthy foods including chips, cake, candy, and soda (ORrange = 0.48-0.68) compared to students who reported never/almost never using the Nutrition Facts label.

CONCLUSIONS

Using the Nutrition Facts labels to make food choices is beneficially associated with healthy and unhealthy eating among 8th and 11th-grade students, although the proportion of students using nutrition labels to make their food choices was low. Public health efforts should be made to improve nutrition literacy and encourage nutrition label use among secondary students in the United States.

Estimating Physical Activity and Sleep using the Combination of Movement and Heart Rate: A Systematic Review and Meta-Analysis

The purpose of this meta-analysis was to quantify the difference in physical activity and sleep estimates assessed via 1) movement, 2) heart rate (HR), or 3) the combination of movement and HR (MOVE+HR) compared to criterion indicators of the outcomes. Searches in four electronic databases were executed September 21-24 of 2021. Weighted mean was calculated from standardized group-level estimates of mean percent error (MPE) and mean absolute percent error (MAPE) of the proxy signal compared to the criterion measurement method for physical activity, HR, or sleep. Standardized mean difference (SMD) effect sizes between the proxy and criterion estimates were calculated for each study across all outcomes, and meta-regression analyses were conducted. Two-One-Sided-Tests method were conducted to metaanalytically evaluate the equivalence of the proxy and criterion. Thirty-nine studies (physical activity k = 29 and sleep k = 10) were identified for data extraction. Sample size weighted means for MPE were -38.0%, 7.8%, -1.4%, and -0.6% for physical activity movement only, HR only, MOVE+HR, and sleep MOVE+HR, respectively. Sample size weighted means for MAPE were 41.4%, 32.6%, 13.3%, and 10.8% for physical activity movement only, HR only, MOVE+HR, and sleep MOVE+HR, respectively. Few estimates were statistically equivalent at a SMD of 0.8. Estimates of physical activity from MOVE+HR were not statistically significantly different from estimates based on movement or HR only. For sleep, included studies based their estimates solely on the combination of MOVE+HR, so it was impossible to determine if the combination produced significantly different estimates than either method alone.

Expert Perspectives on Pilot and Feasibility Studies: A Delphi Study and Consolidation of Considerations for Behavioral Interventions

Background

In the behavioral sciences, conducting pilot and/or feasibility studies (PFS) is a key step that provides essential information used to inform the design, conduct, and implementation of a larger-scale trial. There are more than 160 published guidelines, reporting checklists, frameworks, and recommendations related to PFS. All of these publications offer some form of guidance on PFS, but many focus on one or a few topics. This makes it difficult for researchers wanting to gain a broader understanding of all the relevant and important aspects of PFS and requires them to seek out multiple sources of information, which increases the risk of missing key considerations to incorporate into their PFS. The purpose of this study was to develop a consolidated set of considerations for the design, conduct, implementation, and reporting of PFS for interventions conducted in the behavioral sciences.

Methods

To develop this consolidation, we undertook a review of the published guidance on PFS in combination with expert consensus (via a Delphi study) from the authors who wrote such guidance to inform the identified considerations. A total of 161 PFS-related guidelines, checklists, frameworks, and recommendations were identified via a review of recently published behavioral intervention PFS and backward/forward citation tracking of well-know PFS literature (e.g., CONSORT Ext. for PFS). Authors of all 161 PFS publications were invited to complete a three-round Delphi survey, which was used to guide the creation of a consolidated list of considerations to guide the design, conduct, and reporting of PFS conducted by researchers in the behavioral sciences.

Results

A total of 496 authors were invited to take part in the Delphi survey, 50 (10.1%) of which completed all three rounds, representing 60 (37.3%) of the 161 identified PFS-related guidelines, checklists, frameworks, and recommendations. A set of twenty considerations, broadly categorized into six themes (Intervention Design, Study Design, Conduct of Trial, Implementation of Intervention, Statistical Analysis and Reporting) were generated from a review of the 161 PFS-related publications as well as a synthesis of feedback from the three-round Delphi process. These 20 considerations are presented alongside a supporting narrative for each consideration as well as a crosswalk of all 161 publications aligned with each consideration for further reading.

Conclusion

We leveraged expert opinion from researchers who have published PFS-related guidelines, checklists, frameworks, and recommendations on a wide range of topics and distilled this knowledge into a valuable and universal resource for researchers conducting PFS. Researchers may use these considerations alongside the previously published literature to guide decisions about all aspects of PFS, with the hope of creating and disseminating interventions with broad public health impact.

Are parent-reported sleep logs essential? A comparison of three approaches to guide open source accelerometry-based nocturnal sleep processing in children

We examined the comparability of children's nocturnal sleep estimates using accelerometry data, processed with and without a sleep log. In a secondary analysis, we evaluated factors associated with disagreement between processing approaches. Children (n = 722, age 5-12 years) wore a wrist-based accelerometer for 14 days during Autumn 2020, Spring 2021, and/or Summer 2021. Outcomes included sleep period, duration, wake after sleep onset (WASO), and timing (onset, midpoint, waketime). Parents completed surveys including children's nightly bed/wake time. Data were processed with parent-reported bed/wake time (sleep log), the Heuristic algorithm looking at Distribution of Change in Z-Angle (HDCZA) algorithm (no log), and an 8 p.m.-8 a.m. window (generic log) using the R-package 'GGIR' (version 2.6-4). Mean/absolute bias and limits of agreement were calculated and visualised with Bland-Altman plots. Associations between child, home, and survey characteristics and disagreement were examined with tobit regression. Just over half of nights demonstrated no difference in sleep period between sleep log and no log approaches. Among all nights, the sleep log approach produced longer sleep periods (9.3 min; absolute mean bias [AMB] = 28.0 min), shorter duration (1.4 min; AMB = 14.0 min), greater WASO (11.0 min; AMB = 15.4 min), and earlier onset (13.4 min; AMB = 17.4 min), midpoint (8.8 min; AMB = 15.3 min), and waketime (3.9 min; AMB = 14.8 min) than no log. Factors associated with discrepancies included smartphone ownership, bedroom screens, nontraditional parent work schedule, and completion on weekend/summer nights (range = 0.4-10.2 min). The generic log resulted in greater AMB among sleep outcomes. Small mean differences were observed between nights with and without a sleep log. Discrepancies existed on weekends, in summer, and for children with smartphones and screens in the bedroom.

What does it mean to use the mean? The impact of different data handling strategies on the proportion of children classified as meeting 24-hr movement guidelines and associations with overweight and obesity

Background

Despite the widespread endorsement of 24-hour movement guidelines (physical activity, sleep, screentime) for youth, no standardized processes for categorizing guideline achievement exists. The purpose of this study was to illustrate the impact of different data handling strategies on the proportion of children meeting 24-hour movement guidelines (24hrG) and associations with overweight and obesity.

Methods

A subset of 524 children (ages 5-12yrs) with complete 24-hour behavior measures on at least 10 days was used to compare the impact of data handling strategies on estimates of meeting 24hrG. Physical activity and sleep were measured via accelerometry. Screentime was measured via parent self-report. Comparison of meeting 24hrG were made using 1) average of behaviors across all days (AVG-24hr), 2) classifying each day and evaluating the percentage meeting 24hrG from 10-100% of their measured days (DAYS-24hr), and 3) the average of a random sample of 4 days across 10 iterations (RAND-24hr). A second subset of children (N=475) with height and weight data was used to explore the influence of each data handling strategy on children meeting guidelines and the odds of overweight/obesity via logistic regression.

Results

Classification for AVG-24hr resulted in 14.7% of participants meeting 24hrG. Classification for DAYS-24hr resulted in 63.5% meeting 24hrG on 10% of measured days with <1% meeting 24hrG on 100% of days. Classification for RAND-24hr resulted in 15.9% of participants meeting 24hrG. Across 10 iterations, 63.6% of participants never met 24hrG regardless of the days sampled, 3.4% always met 24hrG, with the remaining 33.0% classified as meeting 24hrG for at least one of the 10 random iterations of days. Using AVG-24hr as a strategy, meeting all three guidelines associated with lower odds of having overweight obesity (OR=0.38, p<0.05). The RAND-24hr strategy produced a range of odds from 0.27 to 0.56. Using the criteria of needing to meet 24hrG on 100% of days, meeting all three guidelines associated with the lowest odds of having overweight and obesity as well (OR=0.04, p<0.05).

Conclusions

Varying estimates of meeting the 24hrG and the odds of overweight and obesity results from different data handling strategies and days sampled.

Use of guidelines, checklists, frameworks, and recommendations in behavioral intervention preliminary studies and associations with reporting comprehensiveness: a scoping bibliometric review

BACKGROUND

Guidelines, checklists, frameworks, and recommendations (GCFRs) related to preliminary studies serve as essential resources to assist behavioral intervention researchers in reporting findings from preliminary studies, but their impact on preliminary study reporting comprehensiveness is unknown. The purpose of this study was to conduct a scoping bibliometric review of recently published preliminary behavioral-focused intervention studies to (1) examine the prevalence of GCFR usage and (2) determine the associations between GCFR usage and reporting feasibility-related characteristics.

METHODS

A systematic search was conducted for preliminary studies of behavioral-focused interventions published between 2018 and 2020. Studies were limited to the top 25 journals publishing behavioral-focused interventions, text mined to identify usage of GCFRs, and categorized as either not citing GCFRs or citing ≥ 2 GCFRs (Citers). A random sample of non-Citers was text mined to identify studies which cited other preliminary studies that cited GCFRs (Indirect Citers) and those that did not (Never Citers). The presence/absence of feasibility-related characteristics was compared between Citers, Indirect Citers, and Never Citers via univariate logistic regression.

RESULTS

Studies (n = 4143) were identified, and 1316 were text mined to identify GCFR usage (n = 167 Citers). A random sample of 200 studies not citing a GCFR were selected and categorized into Indirect Citers (n = 71) and Never Citers (n = 129). Compared to Never Citers, Citers had higher odds of reporting retention, acceptability, adverse events, compliance, cost, data collection feasibility, and treatment fidelity (ORrange = 2.62-14.15, p < 0.005). Citers also had higher odds of mentioning feasibility in purpose statements, providing progression criteria, framing feasibility as the primary outcome, and mentioning feasibility in conclusions (ORrange = 6.31-17.04, p < 0.005) and lower odds of mentioning efficacy in purpose statements, testing for efficacy, mentioning efficacy in conclusions, and suggesting future testing (ORrange = 0.13-0.54, p < 0.05). Indirect Citers had higher odds of reporting acceptability and treatment fidelity (ORrange = 2.12-2.39, p < 0.05) but lower odds of testing for efficacy (OR = 0.36, p < 0.05) compared to Never Citers.

CONCLUSION

The citation of GCFRs is associated with greater reporting of feasibility-related characteristics in preliminary studies of behavioral-focused interventions. Researchers are encouraged to use and cite literature that provides guidance on design, implementation, analysis, and reporting to improve the comprehensiveness of reporting for preliminary studies.

Observed and perceived benefits of providing physical activity opportunities in elementary schools: a qualitative study

Introduction

Schools play an important role in promoting physical activity for youth. However, school-based physical activity opportunities often compete with other academic priorities, limiting their implementation. The purpose of this study was to qualitatively explore elementary school teacher and staff perspectives on providing physical activity opportunities and how they impact students and learning.

Methods

We partnered with a school district in Texas to conduct semi-structured individual interviews. We used a purposeful sampling approach to recruit elementary teachers and staff knowledgeable about the physical activity opportunities provided at their school. Interviews included questions about participant opinions of providing physical activity opportunities and the types of opportunities provided. We analyzed data using a directed content analysis and iterative categorization approach.

Results

Fifteen participants (4 teachers, 4 physical education teachers, 3 assistant principals, and 4 principals) completed interviews from 10 elementary schools. Participants discussed observed and perceived benefits when providing physical activity opportunities, which emerged into four themes and subthemes: (1) academic benefits (learning readiness, learning engagement, and academic performance); (2) social-emotional benefits (behavior, interpersonal and social skills, and classroom culture); (3) physical benefits (brain health, skill development, physical health); and (4) instructional benefits (quality teaching time, helpful teaching tools, and teacher-student relationships).

Conclusions

Teachers and staff observed numerous benefits when students had opportunities to be physically active, including the positive impact on academic and social-emotional outcomes. Our findings highlight the alignment of physical activity with other school priorities. Physical activity programming can be used in ways to support academics, learning, behavior, and other important outcomes.

Elementary school staff perspectives on the implementation of physical activity approaches in practice: an exploratory sequential mixed methods study

Introduction

A whole-of-school approach is best to promote physical activity before, during, and after school. However, multicomponent programming is often complex and difficult to deliver in school settings. There is a need to better understand how components of a whole-of-school approach are implemented in practice. The objectives of this mixed methods study were to: (1) qualitatively explore physical activity approaches and their implementation in elementary schools, (2) quantitatively assess implementation levels, and (3) examine associations between school-level physical activity promotion and academic ratings.

Methods

We used an exploratory sequential mixed methods design. We conducted semi-structured qualitative interviews with elementary school staff from a Texas school district and used a directed content analysis to explore physical activity approaches and their implementation. Using qualitative findings, we designed a survey to quantitatively examine the implementation of physical activity approaches, which we distributed to elementary staff district wide. We used Pearson correlation coefficients to examine the association between the amount of physical activity opportunities present in individual schools and school-level academic ratings.

Results

We completed 15 interviews (7 principals/assistant principals, 4 physical educators, and 4 classroom teachers). Elementary school teachers and staff indicated PE and recess implementation was driven from the top-down by state and district policies, while implementation of classroom-based approaches, before and after school programming, and active transport were largely driven from the bottom-up by teachers and school leaders. Teachers and staff also discussed implementation challenges across approaches. Survey respondents (n = 247 from 22 schools) indicated 54.6% of schools were implementing ≥135 min/week of physical education and 72.7% were implementing 30 min/day of recess. Classroom-based approaches were less common. Twenty-four percent of schools reported accessible before school programs, 72.7% reported accessible after school programs, and 27% promoted active transport. There was a direct association between the number of physical activity opportunities provided and school-level academic ratings r(22) = 0.53, p = 0.01.

Conclusion

Schools provided physical activity opportunities consistent with a whole-of-school approach, although there was variability between schools and implementation challenges were present. Leveraging existing school assets while providing school-specific implementation strategies may be most beneficial for supporting successful physical activity promotion in elementary schools.

The mysterious case of the disappearing pilot study: a review of publication bias in preliminary behavioral interventions presented at health behavior conferences

BACKGROUND

The number of preliminary studies conducted and published has increased in recent years. However, there are likely many preliminary studies that go unpublished because preliminary studies are typically small and may not be perceived as methodologically rigorous. The extent of publication bias within preliminary studies is unknown but can prove useful to determine whether preliminary studies appearing in peer-reviewed journals are fundamentally different than those that are unpublished. The purpose of this study was to identify characteristics associated with publication in a sample of abstracts of preliminary studies of behavioral interventions presented at conferences.

METHODS

Abstract supplements from two primary outlets for behavioral intervention research (Society of Behavioral Medicine and International Society of Behavioral Nutrition and Physical Activity) were searched to identify all abstracts reporting findings of behavioral interventions from preliminary studies. Study characteristics were extracted from the abstracts including year presented, sample size, design, and statistical significance. To determine if abstracts had a matching peer-reviewed publication, a search of authors' curriculum vitae and research databases was conducted. Iterative logistic regression models were used to estimate odds of abstract publication. Authors with unpublished preliminary studies were surveyed to identify reasons for nonpublication.

RESULTS

Across conferences, a total of 18,961 abstracts were presented. Of these, 791 were preliminary behavioral interventions, of which 49% (388) were published in a peer-reviewed journal. For models with main effects only, preliminary studies with sample sizes greater than n = 24 were more likely to be published (range of odds ratios, 1.82 to 2.01). For models including interactions among study characteristics, no significant associations were found. Authors of unpublished preliminary studies indicated small sample sizes and being underpowered to detect effects as barriers to attempting publication.

CONCLUSIONS

Half of preliminary studies presented at conferences go unpublished, but published preliminary studies appearing in peer-reviewed literature are not systematically different from those that remain unpublished. Without publication, it is difficult to assess the quality of information regarding the early-stage development of interventions. This inaccessibility inhibits our ability to learn from the progression of preliminary studies.

Scientists' perception of pilot study quality was influenced by statistical significance and study design

OBJECTIVES

Preliminary studies play a key role in developing large-scale interventions but may be held to higher or lower scientific standards during the peer review process because of their preliminary study status.

STUDY DESIGN AND SETTING

Abstracts from 5 published obesity prevention preliminary studies were systematically modified to generate 16 variations of each abstract. Variations differed by 4 factors: sample size (n = 20 vs. n = 150), statistical significance (P < 0.05 vs. P > 0.05), study design (single group vs. randomized 2 groups), and preliminary study status (presence/absence of pilot language). Using an online survey, behavioral scientists were provided with a randomly selected variation of each of the 5 abstracts and blinded to the existence of other variations. Respondents rated each abstract on aspects of study quality.

RESULTS

Behavioral scientists (n = 271, 79.7% female, median age 34 years) completed 1,355 abstract ratings. Preliminary study status was not associated with perceived study quality. Statistically significant effects were rated as more scientifically significant, rigorous, innovative, clearly written, warranted further testing, and had more meaningful results. Randomized designs were rated as more rigorous, innovative, and meaningful.

CONCLUSION

Findings suggest reviewers place a greater value on statistically significant findings and randomized control design and may overlook other important study characteristics.

Feasibility indicators in obesity-related behavioral intervention preliminary studies: a historical scoping review

BACKGROUND

Behavioral interventions are often complex, operate at multiple levels, across settings, and employ a range of behavior change techniques. Collecting and reporting key indicators of initial trial and intervention feasibility is essential to decisions for progressing to larger-scale trials. The extent of reporting on feasibility indicators and how this may have changed over time is unknown. The aims of this study were to (1) conduct a historical scoping review of the reporting of feasibility indicators in behavioral pilot/feasibility studies related to obesity published through 2020, and (2) describe trends in the amount and type of feasibility indicators reported in studies published across three time periods: 1982-2006, 2011-2013, and 2018-2020.

METHODS

A search of online databases (PubMed, Embase, EBSCOhost, Web of Science) for health behavior pilot/feasibility studies related to obesity published up to 12/31/2020 was conducted and a random sample of 600 studies, 200 from each of the three timepoints (1982-2006, 2011-2013, and 2018-2020), was included in this review. The presence/absence of feasibility indicators, including recruitment, retention, participant acceptability, attendance, compliance, and fidelity, were identified/coded for each study. Univariate logistic regression models were employed to assess changes in the reporting of feasibility indicators across time.

RESULTS

A total of 16,365 unique articles were identified of which 6873 of these were reviewed to arrive at the final sample of 600 studies. For the total sample, 428 (71.3%) studies provided recruitment information, 595 (99.2%) provided retention information, 219 (36.5%) reported quantitative acceptability outcomes, 157 (26.2%) reported qualitative acceptability outcomes, 199 (33.2%) reported attendance, 187 (31.2%) reported participant compliance, 23 (3.8%) reported cost information, and 85 (14.2%) reported treatment fidelity outcomes. When compared to the Early Group (1982-2006), studies in the Late Group (2018-2020) were more likely to report recruitment information (OR=1.60, 95%CI 1.03-2.49), acceptability-related quantitative (OR=2.68, 95%CI 1.76-4.08) and qualitative (OR=2.32, 95%CI 1.48-3.65) outcomes, compliance outcomes (OR=2.29, 95%CI 1.49-3.52), and fidelity outcomes (OR=2.13, 95%CI 1.21, 3.77).

CONCLUSION

The reporting of feasibility indicators within behavioral pilot/feasibility studies has improved across time, but key aspects of feasibility, such as fidelity, are still not reported in the majority of studies. Given the importance of behavioral intervention pilot/feasibility studies in the translational science spectrum, there is a need for improving the reporting of feasibility indicators.

Influence of pilot and small trials in meta-analyses of behavioral interventions: a meta-epidemiological study

BACKGROUND

Pilot/feasibility or studies with small sample sizes may be associated with inflated effects. This study explores the vibration of effect sizes (VoE) in meta-analyses when considering different inclusion criteria based upon sample size or pilot/feasibility status.

METHODS

Searches were to identify systematic reviews that conducted meta-analyses of behavioral interventions on topics related to the prevention/treatment of childhood obesity from January 2016 to October 2019. The computed summary effect sizes (ES) were extracted from each meta-analysis. Individual studies included in the meta-analyses were classified into one of the following four categories: self-identified pilot/feasibility studies or based upon sample size but not a pilot/feasibility study (N ≤ 100, N > 100, and N > 370 the upper 75th of sample size). The VoE was defined as the absolute difference (ABS) between the re-estimations of summary ES restricted to study classifications compared to the originally reported summary ES. Concordance (kappa) of statistical significance of summary ES between the four categories of studies was assessed. Fixed and random effects models and meta-regressions were estimated. Three case studies are presented to illustrate the impact of including pilot/feasibility and N ≤ 100 studies on the estimated summary ES.

RESULTS

A total of 1602 effect sizes, representing 145 reported summary ES, were extracted from 48 meta-analyses containing 603 unique studies (avg. 22 studies per meta-analysis, range 2-108) and included 227,217 participants. Pilot/feasibility and N ≤ 100 studies comprised 22% (0-58%) and 21% (0-83%) of studies included in the meta-analyses. Meta-regression indicated the ABS between the re-estimated and original summary ES where summary ES ranged from 0.20 to 0.46 depending on the proportion of studies comprising the original ES were either mostly small (e.g., N ≤ 100) or mostly large (N > 370). Concordance was low when removing both pilot/feasibility and N ≤ 100 studies (kappa = 0.53) and restricting analyses only to the largest studies (N > 370, kappa = 0.35), with 20% and 26% of the originally reported statistically significant ES rendered non-significant. Reanalysis of the three case study meta-analyses resulted in the re-estimated ES rendered either non-significant or half of the originally reported ES.

CONCLUSIONS

When meta-analyses of behavioral interventions include a substantial proportion of both pilot/feasibility and N ≤ 100 studies, summary ES can be affected markedly and should be interpreted with caution.

Women's thoughts on receiving and sharing genetic information: Considerations for genetic counseling

Indications for genetic testing for inherited cancer syndromes are expanding both in the academic and the community setting. However, only a fraction of individuals who are candidates for testing pursue this option. Therefore, it is important to understand those factors that impact the uptake of genetic testing in individuals affected and unaffected with cancer. A successful translation of genomic risk stratification into clinical care will require that providers of this information are aware of the attitudes, perceived risks and benefits, and concerns of individuals who will be considering testing. The purpose of this study was to assess beliefs, attitudes and preferences for genetic risk information, by personal characteristics of women affected and unaffected by breast cancer enrolled in the Breast Cancer Family Registry Cohort. Data for this analysis came from eight survey questions, which asked participants (N = 9,048, 100% female) about their opinions regarding genetic information. Women reported that conveying the accuracy of the test was important and were interested in information related to personal level of risk, finding out about diseases that could be treated, and information that could be helpful to their families. Young women were most interested in how their own health needs might be impacted by genetic test results, while older women were more interested in how genetic information would benefit other members of the family. Interest in how the genetic test was performed was highest among Asian and Hispanic women. Women affected with breast cancer were more likely to report feeling sad about possibly passing down a breast cancer gene, while unaffected women were more uncertain about their future risk of cancer. The variety of informational needs identified has implications for how genetic counselors can tailor communication to individuals considering genetic testing.

Impact of Virtual vs. In-Person School on Children Meeting the 24-h Movement Guidelines during the COVID-19 Pandemic

The pandemic mitigation strategy of closing schools, while necessary, may have unintentionally impacted children's moderate-to-vigorous physical activity (MVPA), sleep, and time spent watching screens. In some locations, schools used hybrid attendance models, with some days during the week requiring in-person and others virtual attendance. This scenario offers an opportunity to evaluate the impact of attending in-person school on meeting the 24-h movement guidelines. Children (N = 690, 50% girls, K-5th) wore wrist-placed accelerometers for 14 days during October/November 2020. Parents completed daily reports on child time spent on screens and time spent on screens for school. The schools' schedule was learning for 2 days/week in-person and 3 days/week virtually. Using only weekdays (M-F), the 24-h movement behaviors were classified, and the probability of meeting all three was compared between in-person vs. virtual learning and across grades. Data for 4956 weekdays (avg. 7 d/child) were collected. In-person school was associated with a greater proportion (OR = 1.70, 95% CI: 1.33-2.18) of days that children were meeting the 24-h movement guidelines compared to virtual school across all grades. Students were more likely to meet the screen time (OR = 9.14, 95% CI: 7.05-11.83) and MVPA (OR = 1.50, 95% CI: 1.25-1.80) guidelines and less likely to meet the sleep (OR = 0.73, 95% CI: 0.62-0.86) guidelines on the in-person compared to the virtual school days. Structured environments, such as school, have a protective effect on children's movement behaviors, especially physical activity and screen time.

Changes in college students’ health behaviors and substance use after a brief wellness intervention during COVID-19

College students exhibit low levels of physical activity, high levels of sedentary behavior, poor dietary behaviors, sleep problems, high stress, and increased substance use. On-campus resources offering programs to improve college students’ health have been limited during the pandemic. The purpose of this study was to test a brief intervention to improve multiple health behaviors among United States college students. The intervention was a single arm repeated measures study conducted over 12 weeks, utilizing the Behavior Image Model. The intervention involved three components: a survey, a 25-minute wellness specialist consult with a peer health coach, and a 15-minute goal planning session. Follow-up measures were completed at 2-, 6-, and 12-weeks post session to assess changes in wellness behaviors. Linear mixed effects models for repeated measures were used to analyze the association between intervention implementation on within-subject changes in physical activity, sedentary behavior, diet, general health, emotional wellness, and substance use. A total of 121 participants enrolled in the study and 90 (74.4%) completed the health coach session (71% female). At first follow-up, statistically significant increases were observed in vigorous physical activity days/week (coef. = 0.5,95%CI: 0.2,0.9), moderate physical activity days/week (coef. = 0.7, 95%CI: 0.2,1.1), general health (coef. = 4.8,95%CI: 2.1, 7.5), and emotional wellness (coef. = 8.6,95%CI: 5.8, 11.3). Statistically significant decreases in cannabis use (coef. = -2.3,95%CI:-4.1, −0.5) and alcohol consumption (coef. = -2.5,95%CI: −3.7,-1.3) were observed. Many of these changes were sustained at second and third follow-up. This brief wellness intervention shows promise to positively influence multiple health behaviors in college students.

Bidirectional relationships of physical activity and gross motor skills before and after summer break: Application of a cross-lagged panel model

BACKGROUND

Gross motor skills are postulated to have a bidirectional relationship with physical activity (PA); however, no study has tested this relationship before and after a summer break. The purpose of this study was to examine the bidirectional relationships between school PA and gross motor skills in children before and after a summer break.

METHODS

Participants were a sample of 440 children recruited from 3 low-income schools (age = 8.9 ± 1.2 years, mean ± SD). PA was assessed as average school-day step counts using Yamax DigiWalker pedometers (Yamasa Tokei Keiki, Tokyo, Japan) worn for 5 consecutive school days. Gross motor skills were assessed using the Test for Gross Motor Development, 3rd edition. Data were collected at 2 timepoints: at the end of spring semester (T1) and at the beginning of the subsequent fall semester (T2). An age- and body mass index-adjusted cross-lagged model was employed to relate T1 school step counts with T2 gross motor skills and T1 gross motor skills with T2 school step counts.

RESULTS

T1 gross motor skills significantly predicted T2 school step counts (β = 0.24, 95 % confidence interval (95%CI): 0.08-0.40, p = 0.003); however, T1 school step counts did not predict T2 gross motor skills (β = 0.04, 95%CI: -0.06 to 0.14, p = 0.445). The model explained 35.4% and 15.9% of the variances of T2 gross motor skills and T2 school step counts, respectively. Additional analyses indicated that these relationships were driven primarily by ball skills.

CONCLUSION

The relationship between gross motor skills and school PA was not bidirectional; however, higher gross motor skills, specifically ball skills, predicted higher school PA after a 3-month summer break.

Parent and Child Perceptions of Barriers to Active School Commuting

BACKGROUND

Active commuting (AC) to and from school can contribute to physical activity, although it has recently seen a global decline. The purpose of this study was to examine the agreement between parent and child perceptions of barriers to school AC.

METHODS

Participants were parents (N = 152, M_age  = 40.6 ± 6.3 years) and elementary school children (N = 98, M_age  = 10.0 ± 1.2 years). School commute type/frequency and barriers to AC were collected via surveys. Intraclass correlation coefficients (ICCs) were used to assess relative agreement between parent and child perceptions (N = 98 dyads). Paired t tests and equivalence testing were employed to assess group-level agreement. Bland-Altman analysis was used to assess individual-level agreement. Partial correlations of AC with perceptions were also assessed.

RESULTS

All parent and child perceptions of barriers to AC to school had low agreement. Bland-Altman Plots indicated negative bias for all but 3 barrier perceptions. Paired t tests indicated significant differences between parent and child perceptions for 8 out of 15 barriers while equivalence testing deemed no parent-child perception equivalent. Partial correlations with AC frequency were significant for 7 parent perceptions and 2 child perceptions.

CONCLUSIONS

Parent and child perceptions have low agreement. Programs aimed at promoting AC to and from school should account for these discrepancies.

Adolescent Health Behaviors and Difficulty Concentrating, Remembering, and Making Decisions

The purpose of this study was to examine the associations among physical activity, dietary behaviors, and other salient health behaviors such as smoking, alcohol consumption, and sleeping with self-reported adolescent mental health on the 2017 National Youth Risk Behavior Survey (YBRS). A multistage cluster sampling procedure was employed to yield a representative sample of US adolescents. The number of sampled adolescents with usable data was 14 765. Weighted logistic regression models were employed to examine the predictive utility of independent health behaviors associating with reported mental health problems (difficulty concentrating, remembering, or making decisions), and meeting multiple health behavior criteria with reported mental health problems adjusting for age, sex, body mass index percentile, and race/ethnicity. Meeting physical activity guidelines, consuming breakfast every day, not smoking and/or consuming alcohol in the past 30 days, and sleeping at least 8 hours per night independently associated with lower odds of mental health problems (P < .01). For every one additional positive health behavior met, there were significantly lower odds of reported mental health problems (OR = 0.73, 95%CI 0.68-0.78, P < .001). Meeting salient positive health behavior criteria and meeting multiple positive health behavior criteria associated with lower odds of self-reported difficulty concentrating, remembering, or making decisions on the 2017 National YRBS.

Parent Preferences for Physical Activity in Before and After School Programs in Rural and Suburban Communities: A Discrete Choice Experiment

BACKGROUND

The purpose of this study was to examine and compare parent preferences of before and after school physical activity program components in rural and suburban elementary schools.

METHODS

A discrete choice experiment was conducted to measure parent preferences for components of before/after school programs. A total of 183 parents (age = 37.2 [8.2] y, 155 females) sampled from 15 elementary schools (K-6 grades) in the Western United States took part in the study, half of which were from a rural community (n = 93, 50.8%). Results from the discrete choice experiment were analyzed using hierarchic Bayesian methodology, which estimated utility scores and was used to calculate important scores for program components.

RESULTS

The specific goal of the before/after school program was the strongest determinant of parents' stated choice overall, followed by leaders, time of day, length, and main focus. Learning sports as the physical activity goal was the top-rated attribute. Subgroup analyses revealed discrepancies between suburban and rural parents and parents of boys and girls.

CONCLUSION

This study extends the application of discrete choice experiments to school-based programming, providing a unique way to design empirically based, stakeholder informed school programs, specifically within before and after school settings.

School-based physical activity interventions in rural and urban/suburban communities: A systematic review and meta-analysis

Disparities in physical activity and health outcomes exist between urban and rural youth. School settings can be utilized to promote physical activity in youth regardless of urban-rural status. This systematic review and meta-analysis aimed to assess and compare the effect of rural and urban/suburban school-based physical activity programs on total physical activity in youth. A search of five databases was conducted. A total of 33 studies remained after the exclusion process, 28 of which took place in urban/suburban schools and five of which took place in rural schools. The DerSimonian and Laird random effects model was employed with the estimates of heterogeneity taken from the inverse-variance fixed-effect model. For rural studies, the Hartung-Knapp-Sidak-Jonkman method was used to obtain error estimates. Results from the total sample indicated a significant but small pooled increase in daily physical activity (Hedge's g = 0.12, 95% confidence interval [CI]: 0.06-0.18), which held for interventions conducted in urban/suburban schools (Hedge's g = 0.12, 95% CI: 0.06-0.19). For rural school-based interventions, there was no significant pooled effect (Hedge's g = 0.06, 95% CI: -0.50 to 0.61). This meta-analysis provides evidence that school-based interventions can be marginally effective for increasing daily physical activity in children and adolescents; however, no effect was observed for interventions implemented in rural settings.

Rationale for the Essential Components of Physical Education

Purpose: This introductory article provides the context and rationale for conducting systematic literature reviews on each of the essential components of physical education, including policy and environment, curriculum, appropriate instruction, and student assessment. Methods: Four research teams from Doctoral Physical Education Teacher Education programs (D-PETE) conducted these systematic reviews using the PRISMA guidelines process. Results: This article explains the role of the national framework for increasing physical education and physical activity (i.e., Comprehensive School Physical Activity Program) in supporting the essential components of physical education. It also highlights the expectations for physical education and provides a brief history of these components. Lastly, this article highlights each of the articles presented in the special feature. Conclusion: Understanding the implementation of these components may be important for improving the physical education experience for all students and creating a foundation for lifelong physical activity and health.

Associations Among K-12 Student Outcomes, National Standards, and Physical Education Curricular Models: A Systematic Review

Purpose: The purpose of this article was to systematically review studies that explored associations between specific curricular models, as an essential component of physical education, and to assess how the student outcomes identified in the models aligned with the national standards. Methods: Using the PRISMA guidelines to identify, screen, determine eligibility, and include relevant ones, studies were extracted by a search of six databases using terms related to physical education-specific curricular models and student outcome measures. After screening, 23 articles met the inclusion criteria. Results: Students included in these studies ranged from 3^rd-12^th grade, although the majority of studies used students from 3^rd-8^th grade. A total of 58 associations between eight physical education curricular models and student outcomes were assessed, with 41 (70.6%) of those associations being beneficial. Student outcomes included measures of physical activity and fitness, psychosocial variables, classroom behavior, and knowledge. Aligning the national standards to these studies revealed that specific standards were underrepresented compared to others. Conclusions: Results of this systematic review suggest that there is some association between curricular models and student outcomes, although results reported for specific student populations, particularly K-2^nd grade, were lacking. Furthermore, specific student outcomes related to the national standards were underrepresented compared to others. Researchers should take a standards-based approach when deciding which student outcomes to measure and should further explore the associations between curricular models and student outcomes across grade levels.

Mothers' Diet and Family Income Predict Daughters' Healthy Eating

Introduction

Understanding the degree to which parents may influence healthy behaviors may provide opportunities to intervene among populations at increased risk of diseases, such as breast cancer. In this study, we examined the association between daughters’ healthy eating habits and family lifestyle behaviors among girls and their families by using baseline data from the LEGACY (Lessons in Epidemiology and Genetics of Adult Cancer from Youth) Girls Study. Our objective was to examine the relationship between daughters’ healthy eating and family lifestyle behaviors and to compare these associations between families with and without a history of breast cancer.

Methods

We examined demographic and lifestyle data from a cohort of 1,040 girls aged 6 to 13 years from year 1 (2011) of the LEGACY study. Half had a family history of breast cancer (BCFH). We used mixed-effects linear regression to assess the influence of the mother and father’s physical activity, family relationship scores, the mother’s diet, the family’s income, and the daughter’s sports participation, age, body mass index (BMI), and race/ethnicity on the daughter’s Healthy Eating Index (HEI) score.

Results

Daughters’ healthy eating was significantly correlated with the mother’s diet (r[668] = 0.25, P = .003) and physical activity (r[970] = 0.12, P = .002), the father’s physical activity (r[970] = 0.08, P = .01), and the family income (r[854] = 0.13, P = .006). Additionally, the mother’s diet (β coefficient = 0.71, 95% CI, 0.46–0.88, P = .005) and family income (β coefficient = 3.28, 95% CI, 0.79–5.78, P = .002) significantly predicted a daughter’s healthy eating. Analyses separated by family history status revealed differences in these associations. In families without a history of breast cancer, only the mother’s diet (β coefficient = 0.62; 95% CI, 0.29–0.95; P = .001) significantly predicted the daughter’s healthy eating. In families with a history of breast cancer, the mother’s diet (β coefficient = 0.73, 95% CI, 0.42-1.03, P = .006) and family income (β coefficient = 6.24; 95% CI, 2.68–9.80; P = .004) significantly predicted a daughter’s healthy eating.

Conclusion

A mother’s diet and family income are related to the daughter’s healthy eating habits, although differences exist among families by family history of breast cancer.

The neighbourhood social environment correlates with meeting 24-h movement behaviour recommendations in females: a cross-sectional study using the 2019 National Survey of Children's Health

The purpose of this study was to examine the association between the neighbourhood social environment and meeting recommendations for 24-h movement behaviours in youth. Participants were a sample of children and adolescents from the 2019 National Survey of Children's Health (N = 21 259; 48.2% female). Knowing where to go for help (odds ratio (OR) = 2.66, p = 0.006) and a safe school environment (OR = 1.99, p = 0.020) correlated with high probability of meeting 24-h movement behaviour recommendations in females. Novelty: The neighbourhood social environment associates with meeting 24-h movement recommendations in females.

Movement Behaviors and Perceived Loneliness and Sadness within Alaskan Adolescents

Physical activity, screen use, and sleep are behaviors that integrate across the whole day. However, the accumulative influence of meeting recommendations for these 24-h movement behaviors on the mental health of Alaskan adolescents has not been examined. The purpose of this study was to examine the associations between movement behaviors, loneliness, and sadness within Alaskan adolescents. Data were obtained from the 2019 Alaska Youth Risk Behavior Survey (YRBS). The number of adolescents participating in the 2019 Alaska YRBS was 1897. Associations between meeting recommendations for movement behaviors with loneliness and sadness were examined using weighted logistic regression models, adjusted for age, sex, race/ethnicity, and body mass index (BMI). Approximately 5.0% of the sample met recommendations for all three movement behaviors. Meeting 2 or 3 movement behavior recommendations was associated with lower odds of loneliness (odds ratio (OR) range = 0.23 to 0.44, p < 0.01). Additionally, meeting 1 to 3 movement behavior recommendations was associated with lower odds of sadness (OR range = 0.29 to 0.52, p < 0.05). Joint association analyses determined that these relationships were primarily driven by meeting the sleep recommendation for loneliness and meeting the screen use recommendation for sadness. The results support use of multiple movement-based behavior programming to attenuate feelings of loneliness and sadness within Alaskan adolescents.

Sports Participation Correlates With Academic Achievement: Results From a Large Adolescent Sample Within the 2017 U.S. National Youth Risk Behavior Survey

This study sought to examine associations between (a) sports team participation; (b) lifestyle behaviors (e.g., sleeping, alcohol, and tobacco use); and (c) dietary behaviors with self-reported academic achievement using data derived from the 2017 U.S. National Youth Risk Behavior Survey. A multistage cluster sampling procedure was employed to obtain a representative sample of U.S. adolescents from among whom the number with usable data was 14,765. We used weighted logistic regression models to examine the associations between sports participation, lifestyle behaviors, and diet with reported academic achievement (mostly A’s and B’s), adjusting for age, sex, body mass index, and race/ethnicity. After controlling for lifestyle behaviors, diet, and other potentially confounding variables, we found that adolescents participating in one or more sport teams throughout the past year also reported higher academic achievement (A’s and B’s) compared with adolescents participating in zero sports teams (odds ratio [ OR] = 1.39 to 2.40, p <  .001). This relationship was dose-dependent, as participating in multiple sports teams (i.e., > 3) showed a stronger association with academic achievement than participating on only one sports team ( p <  .001). Other independent behavioral correlates with similarly high grades included daily breakfast consumption ( OR = 1.40, p <  .001), sleeping at least eight hours per night ( OR = 1.21, p <  .001), and regular consumption of vegetables ( OR = 1.56, p <  .001) and salads ( OR = 1.30, p <  .001). We discuss the meaning and implication of these findings.

Parent Engagement and Support, Physical Activity, and Academic Performance (PESPAAP): A Proposed Theoretical Model

An emerging area of research within public health is the interaction between parents and their children for the promotion of physical activity. Higher levels of daily physical activity may not only improve physical health but also yield better academic performance by improving cognitive skills, classroom behavior, and academic achievement within the pediatric population. However, no theoretical model has yet been proposed to interrelate constructs of parental engagement and support, physical activity, and academic performance within the pediatric population. Here, we: 1) summarize salient research related to pediatric physical activity and academic performance, parents' physical activity engagement with their children, and the role of parental support in child academic performance; 2) propose a theoretical model interrelating parent physical activity engagement and support, physical activity, and academic performance (PESPAAP); 3) identify features of the proposed model that support its potential merit; and 4) provide potential future research directions and potential analyses that can be undertaken to support, modify, or disprove the proposed theoretical model. The proposed PESPAAP model provides a logically sound model that can be modified or expanded upon to improve applicability and generalizability and can be used as a framework to help align testable hypotheses for studies examining these interrelationships.

Association between Access to Electronic Devices in the Home Environment and Cardiorespiratory Fitness in Children

This study examined the association between access to electronic devices in the home and cardiorespiratory fitness in children. Participants were children aged 8⁻12 years from a local elementary school (n = 106, mean age = 9.7 + 1.1 years, male = 50). Child access to electronic devices was measured with a 37-item parent-reported questionnaire. Estimated maximal aerobic capacity (VO2 Peak) was calculated from The Progressive Aerobic Cardiovascular Endurance Run (PACER) using a validated algorithm. The association between access to electronic devices in the home and cardiorespiratory fitness was explored by employing hierarchical ridge regression, using the Ordinary Least Squares (OLS) model, controlling for the covariates of sex, age, and Body Mass Index (BMI). Controlling for sex, age, and BMI, the number of electronic items in a child's bedroom was significantly inversely related to the estimated VO2 Peak (b = -1.30 mL/kg/min, 95% C.I.: -2.46 mL/kg/min, -0.15 mL/kg/min, p = 0.028) and PACER laps (b = -3.70 laps, 95% C.I.: -6.97 laps, -0.41 laps, p = 0.028) However, the total number of electronic items in the home and total number of electronic items owned did not significantly relate to the estimated VO2 Peak (p = 0.847, 0.964) or the number of PACER laps (p = 0.847, 0.964). Child health behavior interventions focused on the home environment should devote specific attention to the bedroom as a primary locus of easily modifiable intervention.