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.

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.

Initial testing of behavioral interventions can provide valuable information about the methods of the intervention and whether it is effective. However, recommendations that provide researchers with guidance on how to best conduct pilot studies assume ideal circumstances. The mismatch between what can be realistically accomplished in a preliminary study, and what researchers expect from preliminary studies creates confusion. As a result, it is difficult for researchers to judge the quality, relevance, and potential of preliminary studies. This study suggests more research funding opportunities, clearer rules for reviewing grant applications, and more training for the people who review these applications could help improve preliminary studies and create more effective health behavior programs.

Comparison of raw accelerometry data from ActiGraph, Apple Watch, Garmin, and Fitbit using a mechanical shaker table.

The purpose of this study was to evaluate the reliability and validity of the raw accelerometry output from research-grade and consumer wearable devices compared to accelerations produced by a mechanical shaker table. Raw accelerometry data from a total of 40 devices (i.e., n = 10 ActiGraph wGT3X-BT, n = 10 Apple Watch Series 7, n = 10 Garmin Vivoactive 4S, and n = 10 Fitbit Sense) were compared to reference accelerations produced by an orbital shaker table at speeds ranging from 0.6 Hz (4.4 milligravity-mg) to 3.2 Hz (124.7mg). Two-way random effects absolute intraclass correlation coefficients (ICC) tested inter-device reliability. Pearson product moment, Lin's concordance correlation coefficient (CCC), absolute error, mean bias, and equivalence testing were calculated to assess the validity between the raw estimates from the devices and the reference metric. Estimates from Apple, ActiGraph, Garmin, and Fitbit were reliable, with ICCs = 0.99, 0.97, 0.88, and 0.88, respectively. Estimates from ActiGraph, Apple, and Fitbit devices exhibited excellent concordance with the reference CCCs = 0.88, 0.83, and 0.85, respectively, while estimates from Garmin exhibited moderate concordance CCC = 0.59 based on the mean aggregation method. ActiGraph, Apple, and Fitbit produced similar absolute errors = 16.9mg, 21.6mg, and 22.0mg, respectively, while Garmin produced higher absolute error = 32.5mg compared to the reference. ActiGraph produced the lowest mean bias 0.0mg (95%CI = -40.0, 41.0). Equivalence testing revealed raw accelerometry data from all devices were not statistically significantly within the equivalence bounds of the shaker speed. Findings from this study provide evidence that raw accelerometry data from Apple, Garmin, and Fitbit devices can be used to reliably estimate movement; however, no estimates were statistically significantly equivalent to the reference. Future studies could explore device-agnostic and harmonization methods for estimating physical activity using the raw accelerometry signals from the consumer wearables studied herein.

Screen Time, Sociodemographic Factors, and Psychological Well-Being Among Young Children.

Importance: Young children's screen time increased during the COVID-19 lockdown in 2020, but it is unknown whether their screen time returned to prepandemic levels in 2021. Knowledge of the relationship between screen time and child development and health will inform prevention and intervention targets and strategies. Objective: To evaluate screen time by family income and race and ethnicity in the prepandemic (ie, 2018, 2019) and pandemic (ie, 2020, 2021) periods and to examine the relationship between screen time and psychological well-being among young children in the US. Design, Setting, and Participants: Cross-sectional population-based web or mail survey study of 2018-2021 National Survey of Children's Health participants aged 6 months to 5 years. Exposure: Daily screen time (<1, 1, 2, 3, or ≥4 h/d) reported by participants' primary caregivers. Main outcomes and Measures: Flourishing and externalizing behaviors, as indicators of psychological well-being. All analyses were weighted, accounting for the complex survey sample design. Results: Of the 48 775 participants (50.7% female), the proportion of those with high screen time (defined as ≥1 h/d for children aged 6 months-1 year and ≥2 h/d for children aged 2-5 years) was 48.5% (95% CI, 46.3%-50.7%) in 2018, 49.2% (95% CI, 47.0%-51.5%) in 2019, 55.3% (95% CI, 53.4%-57.2%) in 2020, and 50.0% (95% CI, 48.3%-51.6%) in 2021. Among children living in poverty (federal poverty level <100%), the proportion of those with high screen time was 48.7% (95% CI, 42.8%-54.6%) in 2018, 52.0% (95% CI, 45.4%-58.6%) in 2019, 60.9% (95% CI, 55.4%-66.4%) in 2020, and 58.9% (53.7%-64.1%) in 2021. Adjusted odds ratio of flourishing was 0.66 (95% CI, 0.51-0.85), 0.81 (95% CI, 0.66-0.99), 0.68 (95% CI, 0.52-0.88), and 0.53 (95% CI, 0.42-0.69) for less than 1, 2, 3, and 4 or more hours per day vs 1 hour per day of screen time, respectively, among children aged 3 to 5 years. No association between screen time and flourishing was found among children aged 6 months to 2 years. An adjusted externalizing behavior score was higher by 0.2 points (95% CI, -0.1 to 0.5), 0.5 points (95% CI, 0.3 to 0.8), 1.3 points (95% CI, 1.0 to 1.6), and 2.1 points (95% CI, 1.7 to 2.5) for less than 1, 2, 3, and 4 or more hours per day vs 1 hour per day of screen time, respectively, among children aged 3 to 5 years. Conclusions and Relevance: In this multiyear cross-sectional study of a representative sample of young children in the US, the increased prevalence of high screen time in 2020 returned to prepandemic levels in 2021; however, it remained elevated in children living in poverty. Two hours or more of daily screen time was associated with lower psychological well-being among preschool-aged children.

Are the Risk of Generalizability Biases Generalizable? A Meta-Epidemiological Study.

Background: Preliminary studies (e.g., pilot/feasibility studies) can result in misleading evidence that an intervention is ready to be evaluated in a large-scale trial when it is not. Risk of Generalizability Biases (RGBs, a set of external validity biases) represent study features that influence estimates of effectiveness, often inflating estimates in preliminary studies which are not replicated in larger-scale trials. While RGBs have been empirically established in interventions targeting obesity, the extent to which RGBs generalize to other health areas is unknown. Understanding the relevance of RGBs across health behavior intervention research can inform organized efforts to reduce their prevalence. Purpose: The purpose of our study was to examine whether RGBs generalize outside of obesity-related interventions. Methods: A systematic review identified health behavior interventions across four behaviors unrelated to obesity that follow a similar intervention development framework of preliminary studies informing larger-scale trials (i.e., tobacco use disorder, alcohol use disorder, interpersonal violence, and behaviors related to increased sexually transmitted infections). To be included, published interventions had to be tested in a preliminary study followed by testing in a larger trial (the two studies thus comprising a study pair). We extracted health-related outcomes and coded the presence/absence of RGBs. We used meta-regression models to estimate the impact of RGBs on the change in standardized mean difference (ΔSMD) between the preliminary study and larger trial. Results: We identified sixty-nine study pairs, of which forty-seven were eligible for inclusion in the analysis (k = 156 effects), with RGBs identified for each behavior. For pairs where the RGB was present in the preliminary study but removed in the larger trial the treatment effect decreased by an average of ΔSMD=-0.38 (range - 0.69 to -0.21). This provides evidence of larger drop in effectiveness for studies containing RGBs relative to study pairs with no RGBs present (treatment effect decreased by an average of ΔSMD =-0.24, range - 0.19 to -0.27). Conclusion: RGBs may be associated with higher effect estimates across diverse areas of health intervention research. These findings suggest commonalities shared across health behavior intervention fields may facilitate introduction of RGBs within preliminary studies, rather than RGBs being isolated to a single health behavior field.

Preschoolers' Self-Regulation and Behavior Problems in the Midst of Caregiver Depression and Chaos.

OBJECTIVES: Preschoolers' self-regulation is partially developed through home and child care routines. COVID-19-related child care closures increased caregiver depressive symptoms, household chaos, and children's behavior problems. This longitudinal study examined how preschoolers' prepandemic self-regulation was related to behavior problems early in the pandemic, including buffering against the adverse effects of caregiver depressive symptoms and household chaos. METHODS: A sample of 264 caregivers of preschoolers reported on their children's self-regulation (Behavior Rating Inventory of Executive Function-Preschool Version Inhibitory Self Control Index) before the pandemic and caregiver depressive symptoms (Center for Epidemiological Studies), household chaos (Confusion, Hubbub, and Order Scale), and children's behavior problems (Behavior Rating Index for Children) during the pandemic. We used linear mixed models to examine predictors of children's behavior problems, including prepandemic self-regulation, and further examined moderation by pandemic-related caregiver depressive symptoms and household chaos. RESULTS: Children were 64% non-Hispanic White and 24% non-Hispanic Black, with mean pandemic age 5.9 years. Prepandemic self-regulation significantly predicted early pandemic behavior problems (ß = -0.38 [95% confidence interval, -0.69 to -0.07]). This association was moderated by pandemic-related caregiver depressive symptoms and household chaos; the protective association was maintained at high levels of caregiver depressive symptoms or household chaos, although the association diminished when these co-occurred. CONCLUSION: The protective association between prepandemic self-regulation and subsequent behavior problems suggests longitudinal benefits of preschoolers' inhibitory and emotional control. Despite reduced protection associated with co-occurring caregiver and household challenges, self-regulation continued to demonstrate protection against subsequent behavior problems, even in the midst of a pandemic.

Development and Calibration of a PATCH Device for Monitoring Children's Heart Rate and Acceleration.

INTRODUCTION: Current wearables that collect heart rate and acceleration were not designed for children and/or do not allow access to raw signals, making them fundamentally unverifiable. This study describes the creation and calibration of an open-source multichannel platform (PATCH) designed to measure heart rate and acceleration in children ages 3-8 years. METHODS: Children (N = 63; Mean age = 6.3) participated in a 45-minute protocol ranging in intensities from sedentary to vigorous activity. Actiheart-5 was used as a comparison measure. We calculated mean bias, mean absolute error (MAE) mean absolute percent error (MA%E), Pearson correlations and Lin's concordance correlation coefficient (CCC). RESULTS: Mean bias between PATCH and Actiheart heart rate was 2.26 BPM, MAE was 6.67 BPM and M%E was 5.99%. The correlation between PATCH and Actiheart HR was .89 and CCC was .88. For acceleration, mean bias was 1.16 mg and MAE was 12.24 mg. The correlation between PATCH and Actiheart was .96 and CCC was .95. CONCLUSIONS: The PATCH demonstrated clinically acceptable accuracies to measure heart rate and acceleration compared to a research grade device.

A comparison of perceived barriers to optimal child sleep among families with low and high income.

OBJECTIVE: Families with low-income experience suboptimal sleep compared to families with higher-income. Unique drivers likely contribute to these disparities, along with factors that universally impede sleep patterns, despite income level. To inform intervention tailoring, this mixed-methods study gathered parent's perceptions about child sleep challenges to identify similarities/differences in families with lower-income and higher-income. METHODS: Parents who experienced difficulties with their child (ages 2-4years) sleep were categorized as lower income (n = 15; $30,000 ± 17,845/year) or higher income (n = 15; $142,400 ± 61,373/year). Parents completed a survey and semistructured interview to explore barriers and facilitators for child sleep. Two coders independently evaluated transcripts for lower-income and higher-income groups using inductive analyses. Constant-comparison methods generated themes and characterized similarities/differences by income group. RESULTS: Groups were similar in themes related to diverse bedtime routines, nighttime struggles with child sleep, parent strategies to reduce night wakings, parent effort to provide a sleep-promoting environment, and presence of electronic rules. Groups differed in themes related to factors influencing routine setting (eg, lower income: external factors influencing routines; higher income: personal attributes for structure), parent appraisal of child sleep (eg, higher income: ambivalence; lower income: mostly negative appraisal), nap timing and duration (eg, lower income: longer naps), and strategy utilization and pursuit of resources (eg, higher income: more parents tried various strategies and accessed online/print resources). CONCLUSIONS: Parents experienced many similar barriers to child sleep, with a few distinct differences by income group. These findings can inform future intervention components for all families, as well as customized components to address the unique needs of families across income levels.

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.

Effects of exercise training on ANGPTL3/8 and ANGPTL4/8 and their associations with cardiometabolic traits.

Angiopoietin-like protein (ANGPTL) complexes 3/8 and 4/8 are established inhibitors of LPL and novel therapeutic targets for dyslipidemia. However, the effects of regular exercise on ANGPTL3/8 and ANGPTL4/8 are unknown. We characterized ANGPTL3/8 and ANGPTL4/8 and their relationship with in vivo measurements of lipase activities and cardiometabolic traits before and after a 5-month endurance exercise training intervention in 642 adults from the HERITAGE (HEalth, RIsk factors, exercise Training And GEnetics) Family Study. At baseline, higher levels of both ANGPTL3/8 and ANGPTL4/8 were associated with a worse lipid, lipoprotein, and cardiometabolic profile, with only ANGPTL3/8 associated with postheparin LPL and HL activities. ANGPTL3/8 significantly decreased with exercise training, which corresponded with increases in LPL activity and decreases in HL activity, plasma triglycerides, apoB, visceral fat, and fasting insulin (all P < 5.1 × 10-4). Exercise-induced changes in ANGPTL4/8 were directly correlated to concomitant changes in total cholesterol, LDL-C, apoB, and HDL-triglycerides and inversely related to change in insulin sensitivity index (all P < 7.0 × 10-4). In conclusion, exercise-induced decreases in ANGPTL3/8 and ANGPTL4/8 were related to concomitant improvements in lipase activity, lipid profile, and cardiometabolic risk factors. These findings reveal the ANGPTL3-4-8 model as a potential molecular mechanism contributing to adaptations in lipid metabolism in response to exercise training.

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.

Harnessing technology and gamification to increase adult physical activity: a cluster randomized controlled trial of the Columbia Moves pilot.

BACKGROUND: The use of health technologies and gamification to promote physical activity has increasingly been examined, representing an opportunistic method for harnessing social support inherent within existing social ties. However, these prior studies have yielded mixed findings and lacked long-term follow-up periods. Thus, a pilot cluster randomized controlled trial was conducted to gauge the feasibility and preliminary efficacy of a digital gamification-based physical activity promotion approach among teams of insufficiently active adults with existing social ties. METHODS: Teams (N = 24; 116 total participants) were randomized to either a 12-week intervention (Fitbit, step goals, app, feedback; TECH) or the same program plus gamification (TECH + Gamification). Mixed effects models were used to compare group differences in treatment adherence, and changes in social support, steps, and moderate-to-vigorous physical activity at 12 weeks and 52 weeks from baseline, adjusted for sociodemographic characteristics and team size. RESULTS: TECH had a lower mean number of days of Fitbit self-monitoring versus TECH + Gamification during the intervention (adjusted difference: -.30; 95% CI, -.54 to -.07; P = .01). Post-intervention, TECH had 47% lower odds of self-monitoring 7 days per week versus TECH + Gamification (.53; 95% CI, .31 to .89; P = .02). No differences were observed between TECH + Gamification and TECH in increases in social support (0.04; 95% CI, -.21 to .29; P = .76), ActiGraph-measured daily steps (-425; 95% CI, -1065 to 215; P = .19), or moderate-to-vigorous physical activity minutes (-3.36; 95% CI, -8.62 to 1.91; P = .21) from baseline to 12 weeks or in the regression of these improvements by 1 year (Ps > .05). Although not significant in the adjusted models (Ps > .05), clinically meaningful differences in Fitbit-measured daily steps (TECH, 7041 ± 2520; TECH + Gamification, 7988 ± 2707) and active minutes (TECH, 29.90 ± 29.76; TECH + Gamification, 36.38 ± 29.83) were found during the intervention. CONCLUSIONS: A gamified physical activity intervention targeting teams of adults with existing social ties was feasible and facilitated favorable, clinically meaningful additive physical activity effects while in place but did not drive enhanced, long-term physical activity participation. Future investigations should explore optimal team dynamics and more direct ways of leveraging social support (training teams; gamifying social support). TRIAL REGISTRATION: Clinicaltrials.gov ( NCT03509129 , April 26, 2018).

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.

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.

Exploring the Bacterial Community in Aged Fecal Sources from Dairy Cows: Impacts on Fecal Source Tracking.

(1) Background: This paper discusses the impact of agricultural activities on stream health, particularly in relation to dairy cow fecal pollution. The study explores the fecal microbiome of cattle and the potential ecological implications of aging fecal pollution on waterways. (2) Methods: The study examines changes in the bacterial community available for mobilization from in-situ decomposing cowpats and the effects of simulated rainfall. The microbiome of individual cowpats was monitored over 5.5 months. We used 16S rRNA metagenomics and machine learning software, FEAST (Fast Expectation-mAximization for microbial Source Tracking), for bacterial and fecal source assignments. (3) Results: The phyla Bacillota and Bacteroidota are dominant in the fecal microbiota of fresh cow feces but shift to Pseudomonodota, Actinomycetota, and environmental Bacteroidota in aged cowpats. Potential impacts of these bacterial community shifts on inputs to local agricultural streams are discussed in relation to water quality monitoring and aging sources of fecal contamination. We identified taxon orders that are potential indicators of fresh cattle sources (Oscillospirales and Bacteroidales) and aged sources (Peptostreptococcales-Tissierellales) in water bodies. (4) The paper highlights that bacterial metagenomic profiling can inform our understanding of the ecology of microbial communities in aquatic environments and the potential impacts of agricultural activities on ecosystem health.

Evaluation of a device-agnostic approach to predict sleep from raw accelerometry data collected by Apple Watch Series 7, Garmin Vivoactive 4, and ActiGraph GT9X Link in children with sleep disruptions.

GOAL AND AIMS: Evaluate the performance of a sleep scoring algorithm applied to raw accelerometry data collected from research-grade and consumer wearable actigraphy devices against polysomnography. FOCUS METHOD/TECHNOLOGY: Automatic sleep/wake classification using the Sadeh algorithm applied to raw accelerometry data from ActiGraph GT9X Link, Apple Watch Series 7, and Garmin Vivoactive 4. REFERENCE METHOD/TECHNOLOGY: Standard manual PSG sleep scoring. SAMPLE: Fifty children with disrupted sleep (M = 8.5 years, range = 5-12 years, 42% Black, 64% male). DESIGN: Participants underwent to single night lab polysomnography while wearing ActiGraph, Apple, and Garmin devices. CORE ANALYTICS: Discrepancy and epoch-by-epoch analyses for sleep/wake classification (devices vs. polysomnography). ADDITIONAL ANALYTICS AND EXPLORATORY ANALYSES: Equivalence testing for sleep/wake classification (research-grade actigraphy vs. commercial devices). CORE OUTCOMES: Compared to polysomnography, accuracy, sensitivity, and specificity were 85.5, 87.4, and 76.8, respectively, for Actigraph; 83.7, 85.2, and 75.8, respectively, for Garmin; and 84.6, 86.2, and 77.2, respectively, for Apple. The magnitude and trend of bias for total sleep time, sleep efficiency, sleep onset latency, and wake after sleep were similar between the research and consumer wearable devices. IMPORTANT ADDITIONAL OUTCOMES: Equivalence testing indicated that total sleep time and sleep efficiency estimates from the research and consumer wearable devices were statistically significantly equivalent. CORE CONCLUSION: This study demonstrates that raw acceleration data from consumer wearable devices has the potential to be harnessed to predict sleep in children. While further work is needed, this strategy could overcome current limitations related to proprietary algorithms for predicting sleep in consumer wearable devices.

Interpersonal and Environmental Protective Factors and Their Associations With Children's Weight Status.

Both external structure (ie, participating in extracurricular activities) and family factors (ie, parental emotional support) have separately been linked with children's physical health and well-being, however, their combined effects are less well known. The current study examined the longitudinal associations between participating in structured out-of-school activities and parent reports of warmth/emotional support with children's weight status (ie, zBMI) over time. Utilizing longitudinal data from the United States-based Early Childhood Longitudinal Study, Kindergarten Class of 2010 to 2011 (ECLS-K:2011), we employed a confirmatory factor analysis (CFA) and a latent variable cross-lagged path analysis to examine if emotional supportiveness and participation in structured activities predicted lower zBMI over the course of 1 year. The final sample included 18 135 participants. Mean age of the participants was 8.12 years (±0.38 years), and 51% of children were male. Mean zBMI was 0.54 (±1.12). Structure at baseline predicted increased zBMI in year 2 (ß = .03, P = .02) but did not predict parent emotional supportiveness at year 2 (ß = -.05, P = .09). Parent emotional supportiveness at baseline predicted greater zBMI at year 2 (ß = .02, P = <.01) but did not predict structure at year 2 (ß = .02, P = .39). zBMI at baseline did not predict structure (ß = .02, P = .25) or parent emotional supportiveness at year 2 (ß = -.01, P = .55). Our findings were inconsistent with our hypothesis with regard to directionality. Continued refinement about the role of internal structure (ie, family, and parenting practices) may inform public health prevention strategies to support the well-being of children and families.

Longitudinal associations between sleep and weight status in infants and toddlers.

BACKGROUND: The limited research assessing relationships between sleep duration and weight status in infants and toddlers relies primarily on parent-reported sleep and cross-sectional studies. OBJECTIVES: Examine whether average sleep duration and changes in sleep duration among 6-24-month-old children were associated with weight-for-length z-scores, and whether these associations varied by race/ethnicity, socioeconomic status and sex. METHODS: Data were collected when children were approximately 6, 12, 18 and 24 months old (N = 116). Sleep duration was measured using actigraphy. Weight-for-length z-scores were calculated using children's height and weight. Physical activity was assessed using accelerometry. Diet was assessed using a feeding frequency questionnaire. Demographic characteristics included sex, race/ethnicity and socioeconomic status. Separate associations of between- and within-person changes in sleep duration were estimated with weight-for-length z-score treated as the outcome variable in linear mixed model analyses. Additional models were assessed that included interactions between sleep and demographic characteristics. RESULTS: At time points where children slept longer at night compared to their own average, their weight-for-length z-score was lower. This relationship was attenuated by physical activity levels. CONCLUSIONS: Increasing sleep duration can improve weight status outcomes in very young children who have low physical activity levels.

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.

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.