Keith Brazendale

BACKGROUND Consumer wearables could enable continuous assessment of adolescents’ physical activity (PA) across school and summer periods, overcoming limitations of studies that rely on brief assessments at selected time points. However, little is known about whether sufficient data completeness can be maintained across school-calendar transitions or when personally owned or study-provided devices are used in the same study. OBJECTIVE This study evaluated the feasibility of collecting consumer wearable–derived PA data from middle school students across a 208-day school–summer–school transition (April 7 to October 31, 2025). METHODS A convenience sample of students in Grades 7 and 8 was recruited from Physical Education courses at one Midwestern US middle school. Participants who owned an Apple Watch used their personal device, whereas those without one were provided with a Fitbit Charge 6. The primary feasibility outcome was completeness of Fitbit moderate-to-vigorous PA (MVPA) or Apple Watch Exercise Minutes data. Completeness was summarized descriptively overall, by device group, and across school-calendar phases. Weekly PA trajectories were examined descriptively. Participants received weekly synchronization reminders via the study platform, follow-up outreach via email after prolonged interruptions, and cumulative incentives based on data completeness. RESULTS The feasibility sample included 59 participants (mean age 13.2, SD 0.6 years): 46 received a Fitbit and 13 used their own Apple Watch. Overall, 56 (94.9%) contributed at least one valid primary-outcome day. Median completeness was 42.3% (IQR 11.8%-75.0%), and 25 participants (42.4%) achieved at least 50% completeness. Median completeness was descriptively higher in the Apple Watch group than in the Fitbit group (68.3%, IQR 50.0%-86.1% vs 31.0%, IQR 8.2%-66.2%). Overall median completeness declined from 87.2% (IQR 44.7%-97.9%) at the end of the school year to 52.5% (IQR 0.0%-88.8%) during summer break and 0.0% (IQR 0.0%-61.1%) following the return to school. CONCLUSIONS Sustaining wearable-derived PA data collection among adolescents over 208 days was challenging, with fewer than half of participants achieving 50% completeness and roughly one in five achieving 90% completeness despite reminders and incentives. Participants using their own Apple Watches contributed more complete data than those provided with Fitbits, although this difference may reflect prior device familiarity, established use routines, or participation motivation. Extended adolescent PA monitoring may require simplified data transfer, rapid detection of interruptions, and adaptive support around school-calendar transitions.

Background: AI-enabled chatbots and related conversational systems can facilitate human–computer interaction through natural language, personalization, and automated support. In pediatric health promotion, these tools have the potential to provide scalable and flexible approaches to support physical activity (PA) and related lifestyle behavior change within family contexts. However, evidence regarding AI and chatbot-supported interventions for PA and obesity-related lifestyle behaviors among children and adolescents remains limited, and the extent to which these interventions involve parents, caregivers, or families has not been clearly characterized. Objective: This scoping review aimed to provide an up-to-date overview of how AI and chatbot-supported interventions are designed, delivered, and evaluated for PA and obesity-related lifestyle behaviors among children and adolescents, with attention to technology characteristics, family involvement, delivery platforms, outcomes, and research gaps. Methods: In accordance with PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guideline, 7 databases (PubMed, Web of Science, APA PsycINFO, Academic Search Complete, CINAHL Ultimate, IEEE Xplore, and Scopus) were searched through February 2026. Two reviewers independently conducted title and abstract screening, followed by full-text screening in Rayyan (Qatar Computing Research Institute). Eligible studies involved children, adolescents, or families; evaluated an AI-enabled chatbot, conversational agent, or related digital system; and addressed PA, exercise, sedentary behavior, screen time, obesity, overweight, or weight management. Diet, sleep, and other lifestyle outcomes were extracted when reported within otherwise eligible studies. Data were extracted and synthesized narratively in accordance with research objectives. Results: Of 2730 records identified, 14 studies met inclusion criteria. Most were published in 2023 or later (n=12, 85.7%) and spanned 10 countries. Mobile app delivery was most common (n=9, 64.3%). AI approaches included rule-based chatbots, hybrid personalization systems, generative AI, and single studies using recommender systems or computer vision. A total of 10 studies (71.4%) included a specific parent, caregiver, or family component. Common intervention features were personalized feedback (n=10, 71.4%), self-monitoring (n=9, 64.3%), and education (n=9, 64.3%). PA was the most common target behavior, often within broader obesity or healthy lifestyle interventions. Among 8 studies reporting direct PA or fitness outcomes, 4 showed significant improvement, 2 found no significant change, and 2 reported mixed or indirect findings. Feasibility, acceptability, usability, and engagement findings were generally favorable across studies, but cultural tailoring was reported in only one study. Conclusions: AI and chatbot-supported interventions for pediatric PA and obesity-related lifestyle behaviors represent a rapidly emerging but still early-stage field. Family involvement varies considerably across interventions and should be more clearly conceptualized and evaluated in future studies.

BACKGROUND Artificial intelligence (AI)–enabled chatbots and related conversational systems can facilitate human–computer interaction through natural language, personalization, and automated support. In pediatric health promotion, these tools have potential to provide scalable and flexible approaches to support physical activity (PA) and related lifestyle behavior change within family contexts. However, evidence specific to family-based AI and chatbot-supported interventions for children and adolescents remains limited. OBJECTIVE This scoping review aimed to provide an up-to-date overview of how family-based AI and chatbot-supported interventions are designed, delivered, and evaluated for PA and related lifestyle behaviors among children, adolescents, and families, with attention to technology characteristics, family engagement, delivery platforms, outcomes, and research gaps. METHODS In accordance with PRISMA-ScR guidelines, seven databases (PubMed, Web of Science, APA PsycINFO, Academic Search Complete, CINAHL Ultimate, IEEE Xplore, and Scopus) were searched through February, 2026. Two reviewers independently conducted title/abstract and full-text screening in Rayyan AI. Eligible studies involved children, adolescents, or families; evaluated an AI-enabled chatbot, conversational agent, or related digital system; and assessed PA, obesity, weight management, sedentary behavior, or related lifestyle outcomes. Data were extracted and synthesized narratively in accordance with research objectives. RESULTS Of 2,730 records identified, 14 studies met inclusion criteria. Most were published in 2023 or later (12/14, 85.7%) and spanned 10 countries. Mobile app delivery was most common (9/14, 64.3%). AI approaches included rule-based chatbots, hybrid personalization systems, generative AI, and single studies using recommender systems or computer vision. 10 studies (71.4%) included a specific parent, caregiver, or family component. Common intervention features were personalized feedback (10/14, 71.4%), self-monitoring (9/14, 64.3%), and education (9/14, 64.3%). PA was the most common target behavior, often within broader obesity or healthy lifestyle interventions. Among eight studies reporting direct PA or fitness outcomes, four showed significant improvement, two found no significant change, and two reported mixed or indirect findings. Feasibility, acceptability, usability, and engagement findings were generally favorable across studies, but cultural tailoring was reported in only one study. CONCLUSIONS Family-based AI and chatbot-supported interventions for pediatric PA and lifestyle behaviors represent a rapidly emerging but still early-stage field. Current evidence suggests promise for scalable and engaging support, but stronger trials, clearer reporting, culturally responsive designs, and more consistent family-centered evaluations are needed.

The objective of this systematic review is to evaluate the methodological quality of multidimensional lifestyle interventions among university students to improve nutrition and physical activity related outcomes. A critical evaluation of targeted interventions specifically for physical activity and nutrition habits in college populations was conducted for the efficacy in multifaceted behavior change. Out of the fourteen assessed trials, only five received a rating of high quality. Common issues noted included selection bias, randomization issues, loss to follow-up or attrition, and a lack of maintenance for behavior outcomes. This suggests that further research is needed to establish the longevity of behavior change related to physical activity and dietary habits among university students. Increasing self-efficacy among this cohort has the potential to contribute to management and prevention of chronic disease in late adulthood. There is a limited amount of literature exploring the long-term effects (>12 month follow-up) of a multidimensional approach for nutrition and physical activity interventions for college students. Future research efforts must be directed toward including multiple health behaviors to encompass health and wellness and establish long-term adherence to behavior change in college students.

Background : A structured day can positively impact movement behaviorsphysical activity, sedentary time, and sleep among children with cerebral palsy. This study aims to describe and examine the between- and within-person associations of movement behaviors on days with and without structured activities among children with cerebral palsy. Methods : A cross-sectional study was conducted with 17 children with cerebral palsy. Inclusion criteria were children aged 3–10 years, diagnosed with cerebral palsy, and classified as levels I to III according to the Gross Motor Function Classification System. Movement behaviors were objectively measured using accelerometers over 7 consecutive days. A daily activity log documented the structure of the children’s activities. Two-level multilevel linear mixed-effects models were fitted to analyze associations. Results : A total of 119 days were included in the analyses. Recommendations for sleep, sedentary time (ie, screen time), and physical activity were met on 30.2%, 9.2%, and 6.7% of the days, respectively. More favorable behaviors occurred on days with structured activities compared with days without. Adjusted within-person effects revealed that on days with more structured activities compared with their average days, children accumulated an additional 4.3 minutes of moderate to vigorous physical activity, took 648 more steps, and spent 24.8 fewer minutes on screen time. Conclusions : The within-person analysis highlights day-to-day patterns and provides a contextual perspective on promoting movement behaviors, regardless of the child’s level of impairment. Informing caregivers and families about the benefits of structured activities can support strategies to enhance movement behaviors in children with cerebral palsy.

The Structured Days Hypothesis suggests that the school day helps to regulate obesogenic behaviors, whereas out-of-school periods (e.g., summer) contribute to worsening obesogenic behaviors (e.g., low levels of physical activity, increased screen time, later sleep patterns, and unhealthy diet). However, little is known about how out-of-school periods impact children with intellectual and developmental disabilities who experience diagnosis-related challenges and unique family circumstances. This paper outlines a conceptual framework that proposes how out-of-school periods may be associated with obesogenic behaviors in children with intellectual and developmental disabilities, and how child- and family-level factors moderate this relationship. The hypotheses generated from the extension of the Structured Days Hypothesis to children will guide future research in this area, providing insight into who and when the risk for worsening obesogenic behavior is the greatest. This future research will provide information to help inform policies and interventions aimed at improving health outcomes and increasing access to supportive environments for this population.

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