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Background The PROMIS ® Early Childhood Physical Activity (PROMIS EC PA) scale is a recently developed PROMIS Early Childhood measure to assess PA among children aged 1–5 years. The purpose of this study was to examine test-retest reliability and convergent validity of the PROMIS EC PA scale among toddlers. Method An ancillary study was conducted in the toddler-mother dyad sample of the Child and Mother Physical Activity Study. Mothers completed the 7-item PROMIS EC PA scale twice: during a study visit (test) and on the last day when their child’s wore an ActiGraph accelerometer on the hip for 7 days (retest). The PROMIS EC PA summed score was calculated by totaling scores from items 1–5. Test-retest reliability was assessed using intraclass correlation coefficient (ICC) for test and retest PROMIS EC PA. Convergent validity was assessed using rank correlation coefficients (rho) between PROMIS EC PA scores and accelerometer-measured moderate- and vigorous-intensity PA (MVPA). Results Among 74 participants (56% female; 19 ± 4 months of mean age with range of 12–30 months), average accelerometer-measured MVPA was 76 ± 24 min/day. The median number of days between PROMIS EC PA test and retest was 8 days (IQR = 6 to 8), with an average PROMIS EC PA summed score of 11.0 ± 3.5 at test and 10.5 ± 3.4 at retest. ICC for the test-retest PROMIS EC PA summed scores was 0.72 (95% CI = 0.59–0.82). The rank correlation between the PROMIS EC PA summed score and accelerometer-measured MVPA was 0.13 (95% CI=-0.10 to 0.35; p  = 0.28). Conclusion In a sample of children aged 12–30 months, test-retest reliability for the PROMIS EC PA scale was moderate and its convergent validity against accelerometer-measured MVPA was poor. Prior to a widespread use of the PROMIS EC PA scale in large-scale research and clinical practice, the tool should be further refined and validated to elucidate how young children’s lived PA experience as measured in the PROMIS EC PA scale is relevant to their health and wellbeing outcomes.

Background Excessive screen time ( ≥ 2 h per day) is associated with childhood overweight and obesity, physical inactivity, increased sedentary time, unfavorable dietary behaviors, and disrupted sleep. Previous reviews suggest intervening on screen time is associated with reductions in screen time and improvements in other obesogenic behaviors. However, it is unclear what study characteristics and behavior change techniques are potential mechanisms underlying the effectiveness of behavioral interventions. The purpose of this meta-analysis was to identify the behavior change techniques and study characteristics associated with effectiveness in behavioral interventions to reduce children’s (0–18 years) screen time. Methods A literature search of four databases (Ebscohost, Web of Science, EMBASE, and PubMed) was executed between January and February 2020 and updated during July 2021. Behavioral interventions targeting reductions in children’s (0–18 years) screen time were included. Information on study characteristics (e.g., sample size, duration) and behavior change techniques (e.g., information, goal-setting) were extracted. Data on randomization, allocation concealment, and blinding was extracted and used to assess risk of bias. Meta-regressions were used to explore whether intervention effectiveness was associated with the presence of behavior change techniques and study characteristics. Results The search identified 15,529 articles, of which 10,714 were screened for relevancy and 680 were retained for full-text screening. Of these, 204 studies provided quantitative data in the meta-analysis. The overall summary of random effects showed a small, beneficial impact of screen time interventions compared to controls (SDM = 0.116, 95CI 0.08 to 0.15). Inclusion of the Goals, Feedback, and Planning behavioral techniques were associated with a positive impact on intervention effectiveness (SDM = 0.145, 95CI 0.11 to 0.18). Interventions with smaller sample sizes ( n  < 95) delivered over short durations (< 52 weeks) were associated with larger effects compared to studies with larger sample sizes delivered over longer durations. In the presence of the Goals, Feedback, and Planning behavioral techniques, intervention effectiveness diminished as sample size increased. Conclusions Both intervention content and context are important to consider when designing interventions to reduce children’s screen time. As interventions are scaled, determining the active ingredients to optimize interventions along the translational continuum will be crucial to maximize reductions in children’s screen time.

Purpose The Structured Days Hypothesis (SDH) posits that children’s behaviors associated with obesity – such as physical activity – are more favorable on days that contain more ‘structure’ (i.e., a pre-planned, segmented, and adult-supervised environment) such as school weekdays, compared to days with less structure, such as weekend days. The purpose of this study was to compare children’s moderate-to-vigorous physical activity (MVPA) levels on weekdays versus weekend days using a large, multi-country, accelerometer-measured physical activity dataset. Methods Data were received from the International Children’s Accelerometer Database (ICAD) July 2019. The ICAD inclusion criteria for a valid day of wear, only non-intervention data (e.g., baseline intervention data), children with at least 1 weekday and 1 weekend day, and ICAD studies with data collected exclusively during school months, were included for analyses. Mixed effects models accounting for the nested nature of the data (i.e., days within children) assessed MVPA minutes per day (min/day MVPA) differences between weekdays and weekend days by region/country, adjusted for age, sex, and total wear time. Separate meta-analytical models explored differences by age and country/region for sex and child weight-status. Results/findings Valid data from 15 studies representing 5794 children (61% female, 10.7 ± 2.1 yrs., 24% with overweight/obesity) and 35,263 days of valid accelerometer data from 5 distinct countries/regions were used. Boys and girls accumulated 12.6 min/day (95% CI: 9.0, 16.2) and 9.4 min/day (95% CI: 7.2, 11.6) more MVPA on weekdays versus weekend days, respectively. Children from mainland Europe had the largest differences (17.1 min/day more MVPA on weekdays versus weekend days, 95% CI: 15.3, 19.0) compared to the other countries/regions. Children who were classified as overweight/obese or normal weight/underweight accumulated 9.5 min/day (95% CI: 6.9, 12.2) and 10.9 min/day (95% CI: 8.3, 13.5) of additional MVPA on weekdays versus weekend days, respectively. Conclusions Children from multiple countries/regions accumulated significantly more MVPA on weekdays versus weekend days during school months. This finding aligns with the SDH and warrants future intervention studies to prioritize less-structured days, such as weekend days, and to consider providing opportunities for all children to access additional opportunities to be active.

Background Careful consideration and planning are required to establish “sufficient” evidence to ensure an investment in a larger, more well-powered behavioral intervention trial is worthwhile. In the behavioral sciences, this process typically occurs where smaller-scale studies inform larger-scale trials. Believing that one can do the same things and expect the same outcomes in a larger-scale trial that were done in a smaller-scale preliminary study (i.e., pilot/feasibility) is wishful thinking, yet common practice. Starting small makes sense, but small studies come with big decisions that can influence the usefulness of the evidence designed to inform decisions about moving forward with a larger-scale trial. The purpose of this commentary is to discuss what may constitute sufficient evidence for moving forward to a definitive trial. The discussion focuses on challenges often encountered when conducting pilot/feasibility studies, referred to as common (mis)steps, that can lead to inflated estimates of both feasibility and efficacy, and how the intentional design and execution of one or more, often small, pilot/feasibility studies can play a central role in developing an intervention that scales beyond a highly localized context. Main body Establishing sufficient evidence to support larger-scale, definitive trials, from smaller studies, is complicated. For any given behavioral intervention, the type and amount of evidence necessary to be deemed sufficient is inherently variable and can range anywhere from qualitative interviews of individuals representative of the target population to a small-scale randomized trial that mimics the anticipated larger-scale trial. Major challenges and common (mis)steps in the execution of pilot/feasibility studies discussed are those focused on selecting the right sample size, issues with scaling, adaptations and their influence on the preliminary feasibility and efficacy estimates observed, as well as the growing pains of progressing from small to large samples. Finally, funding and resource constraints for conducting informative pilot/feasibility study(ies) are discussed. Conclusion Sufficient evidence to scale will always remain in the eye of the beholder. An understanding of how to design informative small pilot/feasibility studies can assist in speeding up incremental science (where everything needs to be piloted) while slowing down premature scale-up (where any evidence is sufficient for scaling).

Background Children’s BMI gain accelerates during summer. The Structured Days Hypothesis posits that the lack of the school day during summer vacation negatively impacts children’s obesogenic behaviors (i.e., physical activity, screen time, diet, sleep). This natural experiment examined the impact of summer vacation on children’s obesogenic behaviors and body mass index (BMI). Methods Elementary-aged children ( n  = 285, 5-12 years, 48.7% male, 57.4% African American) attending a year-round ( n  = 97) and two match-paired traditional schools ( n  = 188) in the United States participated in this study. Rather than taking a long break from school during the summer like traditional schools, year-round schools take shorter and more frequent breaks from school. This difference in school calendars allowed for obesogenic behaviors to be collected during three conditions: Condition 1) all children attend school, Condition 2) year-round children attend school while traditional children were on summer vacation, and Condition 3) summer vacation for all children. Changes in BMI z-score were collected for the corresponding school years and summers. Multi-level mixed effects regressions estimated obesogenic behaviors and monthly zBMI changes. It was hypothesized that children would experience unhealthy changes in obesogenic behaviors when entering summer vacation because the absence of the school day (i.e., Condition 1 vs. 2 for traditional school children and 2 vs. 3 for year-round school children). Results From Condition 1 to 2 traditional school children experienced greater unhealthy changes in daily minutes sedentary (∆ = 24.2, 95CI = 10.2, 38.2), screen time minutes (∆ = 33.7, 95CI = 17.2, 50.3), sleep midpoint time (∆ = 73:43, 95CI = 65:33, 81:53), and sleep efficiency percentage (−∆ = 0.7, 95CI = -1.1, − 0.3) when compared to year-round school children. Alternatively, from Condition 2 to 3 year-round school children experienced greater unhealthy changes in daily minutes sedentary (∆ = 54.5, 95CI = 38.0, 70.9), light physical activity minutes (∆ = − 42.2, 95CI = -56.2, − 28.3) MVPA minutes (∆ = − 11.4, 95CI = -3.7, − 19.1), screen time minutes (∆ = 46.5, 95CI = 30.0, 63.0), and sleep midpoint time (∆ = 95:54, 95CI = 85:26, 106:22) when compared to traditional school children. Monthly zBMI gain accelerated during summer for traditional (∆ = 0.033 95CI = 0.019, 0.047) but not year-round school children (∆ = 0.004, 95CI = -0.014, 0.023). Conclusions This study suggests that the lack of the school day during summer vacation negatively impacts sedentary behaviors, sleep timing, and screen time. Changes in sedentary behaviors, screen time, and sleep midpoint may contribute to accelerated summer BMI gain. Providing structured programming during summer vacation may positively impact these behaviors, and in turn, mitigate accelerated summer BMI gain. Trial registration ClinicalTrials.gov Identifier: NCT03397940 . Registered January 12th 2018.

Background To examine the efficacy of providing free summer day camp (SDC) to children from low-income families on changes in physical activity, time spent sedentary, and screentime. Methods Across three summers (2021–2023), we randomized 422 children (8.2 ± 1.5yrs, 48% female, 51% Black, 69% at or below 200% Federal Poverty Level, 30% food insecure) from seven elementary schools to one of two conditions: summer as usual (control, n  = 199) or free SDC for 8-10wks (intervention, n  = 223). Accelerometry measured activity (moderate-to-vigorous PA [MVPA] and time spent sedentary) and parent daily report of screentime were measured using a 14-day in April/May (school) and July (summer). Intent-to-treat analysis examined changes in behaviors between school and summer. Exposure models examined differences in behaviors during summer on days when children attended vs. did not attend a SDC in both intervention and control children. Results Intent-to-treat models indicated in the summer children in the intervention group accumulated + 15.0 min/day (95CI 12.0 to 18.0) more MVPA and spent − 29.7 min/day (-37.7 to -21.8) less time sedentary and − 14.1 min/day (-23.9 to -4.3) on screens, compared to children in the control group. Exposure models indicated, on days children attended SDCs, they accumulated more MVPA (+ 26.1 min/day, 22.5 to 29.7), and spent less time sedentary (-63.5 min/day, -72.9 to -54.1) and on screens (-9.5 min/day, -20.1 to 1.2), compared to days when children did not attend SDC. Conclusions Policies targeting upstream structural factors, such as universal access to existing community SDCs during summer, could lead to improvements in health behaviors among children from low-income households. Clinical trials.Gov NCT04072549

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).

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.

Purpose During summer vacation, many children in households with low income lose access to federally-funded, healthful school meals. Summer day camps (SDCs) provide access to healthful meals and a structured environment; yet low-income families often cannot afford SDCs which may influence food/beverage consumption. This study examined the impact of receiving a free SDC versus experiencing summer as usual (SAU) on dietary intake during summer among children from low-income families. Methods Parent-child dyads ( N  = 422; child age: 8.2 ± 1.5 yrs; 48% female; 51% Black) were recruited over 3 years (2021–2023) from schools serving families with low-income. Children were randomized to receive 8–10 weeks of free SDC (intervention) or SAU (control). Parents completed daily diaries for 14 days during school (April/May) and summer (July) which captured child consumption of healthful (e.g., fruit, vegetables, milk) and unhealthful (e.g., soda, fast food, snacks/chips) foods/beverages. Mixed-effects intent-to-treat (ITT) models examined the odds of consuming different foods/beverages during summer, controlling for school year consumption, in the SDC group compared to SAU. Secondary as-treated analyses examined the impact of attending structured summer programming versus not attending on the odds of consuming different food/beverages, regardless of randomization. Results A total of 2,931 daily diaries were completed for intervention ( n  = 232) and control ( n  = 201) children. ITT analyses showed the SDC group had decreased odds of consuming frozen desserts (OR 0.68, 95%CI 0.49–0.94), compared to SAU, during summer weekdays. No other differences were observed. As-treated analyses showed children had increased odds of consuming fruit (1.77, 1.30–2.41), milk (1.97, 1.44–2.69), and chips/snacks (1.49, 1.17–1.90), and decreased odds of consuming soda (0.53, 0.34–0.84), fast food (0.57, 0.45–0.73), and frozen desserts (0.58, 0.45–0.74) on weekdays when they attended structured summer programming, compared to days they did not attend. Conclusions Providing free SDC alone did not promote more healthful food/beverage consumption during summer vacation compared to SAU. However, on days children attended a structured program, children experienced more dietary benefits compared to days they did not. Thus, structured environments may positively impact children’s diet during summer; yet, identifying strategies to address barriers beyond cost to improve attendance and enrollment may enhance the impact of summer programming.

Background Risks for chronic health problems are embedded in preschoolers’ dietary and physical activity habits. Childcare centers are a potential venue to establish healthy habits. We hypothesized that health-promoting center plus parent interventions would improve preschoolers’ dietary and physical activity outcomes, including body weight, over control. Methods We made local modifications to the 30-week Food Friends ® curriculum to develop a center intervention, Creating Healthy Habits Among Maryland Preschoolers (CHAMP), and a parent website (CHAMP+), aligned with the CHAMP intervention. The CHAMP intervention included a manual, web-based lessons plans, handouts, resources, and program materials implemented by CHAMP-trained staff. We evaluated effectiveness in a 3-arm cluster randomized controlled trial. Childcare centers serving low-income communities were recruited (2017–2020) from 10 counties and randomized to center (CHAMP), center plus parent (CHAMP+), or Control arms. Willingness-to-try-new-food, fruit and vegetable (FV) preference, motor competence (Test of Gross Motor Development-2), moderate-vigorous-physical-activity (MVPA, 7-day accelerometry), and anthropometry (BMI z-scores) were measured at baseline/endline (6 months post-baseline) by assessors masked to intervention status. Linear mixed models examined differences in changes among arms. Center baseline nutrition/physical activity environmental quality (Environment and Policy Assessment and Observation) was examined as moderating intervention effects. Results Fifty-six centers were randomized (CHAMP = 21, CHAMP+ = 20, Control = 20); 855 children. Centers were diverse by location, race, and income; children were mean age 48.44 (SD 7.50) months, 54% male; 26% experienced overweight/obesity. Analyses adjusted for baseline differences in child age, race, and ethnicity. The intervention improved motor competence (gross motor quotient: pooled CHAMP/CHAMP+ vs. Control 5.67 [95% CI: 0.60, 10.75]; locomotor score: pooled CHAMP/CHAMP+ vs. Control 1.74 [95% CI: 0.43, 3.05]) and reduced BMIz (pooled CHAMP/CHAMP+ vs. Control (-0.08 [95% CI: -0.15, 0.00]); with no intervention effects on willingness-to-try-new-foods, FV preference, or MVPA and no impact enhancement by the parent intervention (CHAMP+). Moderation analyses showed stronger increases in willingness-to-try-new-foods and MVPA in centers with higher quality nutrition/physical activity environments. Conclusions Childcare center interventions can improve motor competence and reduce BMIz among preschoolers. Higher quality nutrition/physical activity environment can increase the impact of interventions on children’s dietary behaviors and physical activity, contributing to healthy habits. Trial registration NCT03111264.