Purpose: Most children and adolescents do not meet leisure screen time recommendations. Observational studies suggest excessive screen time may be related to increased risk of depressive and anxiety symptoms. This systematic review synthesizes experimental evidence on the effects of behavioral interventions to reduce leisure screen time on depressive and anxiety symptoms in youth.

Methods: Four bibliographic databases (PubMed/MEDLINE, PsycINFO, Embase, Web of Science: Core Collection) were searched for peer-reviewed manuscripts published between 1981 and November 2023. Two reviewers screened titles/abstracts and full text records using Covidence. Randomized intervention trials that (1) addressed leisure screen time as either a primary or secondary behavioral target, (2) reported on depressive and/or anxiety symptoms as a primary or secondary outcome, and (3) included participants aged 3 to <18 years were included. A narrative synthesis of eligible studies was conducted.

Results/findings: 15,529 titles/abstracts and 243 full text records were screened. Thirteen intervention studies from eight countries met eligibility criteria. One included participants in early childhood, four during mid/late childhood, and eight during adolescence. Most (n=11) interventions targeted multiple health behaviors in addition to leisure screen time, including physical activity, dietary intake, and substance use. Seven interventions reported total leisure screen time, while six interventions reported specific types of screen time (television, videogames, computer/internet use, and social media use). Seven studies reported depressive symptoms only, one reported anxiety symptoms only, and five reported both. Six of the interventions resulted in reductions in screen time; five in specific types of screen time (one during early childhood, four during adolescence). Only three studies reported reductions in depressive and/or anxiety symptoms along with reduced leisure screen time. Of the seven interventions that did not significantly reduce leisure screen time, two reported reductions in depressive and/or anxiety symptoms, possibly due to other intervention components.

Conclusions: About half of the interventions reviewed reduced leisure screen time, but only a quarter also reduced depressive and/or anxiety symptoms. While interventions to reduce leisure screen time may have promise for also reducing depressive and/or anxiety symptoms, additional research into the active intervention components and mediating processes are needed to improve emotional health in youth.

Purpose: Overall, 24.7% of adults and 33.2% of children in the East Riding of Yorkshire are classified as ‘inactive’ by engaging in less than 30 minutes of physical activity (PA) per day (Sport England, 2023). Systematic reviews into green exercise (GE) highlight the positive impact on health and wellbeing for both adults (Coventry et al., 2021) and children (Mnich et al., 2019). The aim of the ‘Green2Gold’ project was to create and pilot a new GE intervention in the East Riding of Yorkshire and gain preliminary insights into the benefits of engagement for local families.

Methods: The researchers worked in partnership with The British Olympic Association to create ‘Team GB Family Activity Trails’ in two locations based on an ongoing systematic review into outdoor community-based PA interventions. Walking formed the basis of the project, as an accessible mode of PA displaying various physical and mental wellbeing benefits (Hanson & Jones, 2015). Signposts were installed along the routes containing co-designed activities linked to Olympic sports and other PA challenges. Each signpost contained a unique QR code to take users to further PA and education opportunities on the project’s website. Various community guided walks were delivered to engage local families with the trails and obtain survey feedback regarding activity enjoyment, mood, and motivators and barriers to participation. IBM SPSS v29 was used to analyse quantitative feedback via response frequencies and cross-tabulations. Thematic analysis was used to assess qualitative feedback (Braun & Clarke, 2006).

Results: Over 200 trail users were sampled. Feedback indicates a high level of enjoyment and potential intention to re-engage in trails from both adults (<90%) and children (<80%). Each element of the trail was rated highly by adults and children (<4.3/5). Short-term improvements in mood were also reported by participants of all ages. Cross-tabulations highlighted differences in the types of activities enjoyed, and motivators and barriers to participation, by gender and trail location.

Conclusions: The study provides preliminary evidence to support ‘Activity Trails’, endorsed by an Olympic Association, as a free and simple self-directed activity for creating positive effects on mental wellbeing and PA intention at a community level.

Purpose: To determine the feasibility of high intensity interval training (HIIT) activities and a brief cognitive assessment in adolescents and determine the preliminary efficacy of HIIT activities, with moderate or high cognitive demand, on adolescents’ acute cognitive performance.
Methods: This was a within-subject, crossover design with conditions completed between 7 to 14 days apart. We recruited 7th/8th graders (ages 11-14) from two physical education classes at one middle school. HIIT activities were from the Burn2Learn intervention and were 4 minutes in duration, The moderate cognitive demand HIIT session used simple exercises (e.g. push-ups, sprints) and the high cognitive demand HIIT session used exercises with greater cognitive demand (e.g., following commands to spring in compass directions). For fidelity, students wore accelerometers during the sessions. Before and after each condition, students completed four brief cognitive tests from the Mobile Monitoring of Cognitive Change app to assess processing speed (Color Speed), spatial working memory (Dot Memory), and response inhibition (Go/No-Go).
Results: A total of 25 adolescents were included in the analyses. The mean age was 13.0 years (SD 0.8), 39% female, and 39% classified as overweight or obese. There were no differences in hip-worn accelerometer-measured activity between genders, obesity status, or between HIIT conditions. The re-test reliabilities of the cognitive assessment ranged from .69 to .88. There were significant time-by-condition interaction effects for spatial working memory (Dot Memory) (p=.015) and processing speed (Color Speed) (p=.026). Spatial working memory (Dot Memory) worsened following the high cognitive demand HIIT (sum error distance of 18.2 pre to 28.5 post), while it improved following the moderate cognitive demand HIIT (20.6 to 18.1). Processing speed (Color Speed) reaction time improved more following the moderate cognitive demand HIIT (765.7 ms to 555.6 ms) compared to the high cognitive demand HIIT (716.9 ms to 703.8 ms).
Conclusions: We found greater improvements in spatial working memory and processing speed following a moderate cognitive demand HIIT compared to high cognitive demand HIIT in adolescents. The HIIT exercises were feasible for delivery during middle school physical education lessons in 7th and 8th-grade students of varying physical activity participation and obesity status.

Purpose: Associations between physical activity (PA), sedentary behavior (SB), and psychopathology among adolescents are documented; however, literature has been limited by methodological and measurement issues. The current study examines bidirectional associations within a longitudinal study between objectively measured PA, SB, and adolescent reported internalizing and externalizing psychopathology symptoms.

Methods: 215 adolescents (ages 14-18) wore ActiGraph devices to measure PA and SB continuously for two weeks at each annual timepoint for four years. At each collection, participants completed the Youth Self Report (YSR) to measure internalizing and externalizing symptoms. Random intercept cross-lagged panel models (RI-CLPMs) were run for average moderate to vigorous physical activity (MVPA), MVPA variability, and average SB (i.e., three RI-CLPMs with internalizing problems, externalizing problems, and the respective activity level variable). Maternal education, income-to-needs ratio, age, and sex were included as control variables and were estimated as predictors of the random intercepts of activity level (i.e. MVPA variability, MVPA average, SB average), internalizing problems, and externalizing problems.

Results: Within the average MVPA model, average MVPA was not associated with subsequent decreases in externalizing and internalizing problems. Additionally, externalizing and internalizing problems were not associated with subsequent decreases in average MVPA. Within the MVPA variability model, higher MVPA variability at each timepoint was associated with subsequent increases in internalizing problems (β=0.070, SE=0.028, p = .011). However, MVPA variability was not associated with subsequent increases in externalizing problems. Furthermore, externalizing and internalizing problems were not associated with subsequent increases in MVPA variability. Within the average SB model, internalizing problems at each time point were associated with subsequent increases in SB (β=3.223, S.E.= 1.638, p=.049). However, externalizing problems was not associated with subsequent increases in SB. Moreover, average SB was not associated with subsequent increases in internalizing and externalizing problems.

Conclusions: Results suggest that consistent engagement in MVPA (less day-to-day MVPA variability) is potentially more important than daily MVPA amount (average MVPA) in reducing internalizing problems. Given the relationships between internalizing problems, MVPA variability, and average SB, findings should inform prevention and intervention programs for adolescents to improve concurrent and long-term activity level, activity consistency, and psychopathology.

Purpose: Adolescence is a vulnerable period when, amid increased reward sensitivity and continued maturation of self-regulatory processes, adolescents gain more opportunities for decision-making around eating. Adolescent eating behaviors can have consequences for later diet and associated health risks, emphasizing the importance of evaluating contributing and potentially modifiable factors. Executive control (EC), a set of brain-based abilities for directing attention and behavior, may impact adolescent eating, but research examining these associations has been mixed with notable methodological limitations. The current study examines longitudinal associations between adolescent EC, as measured by neuropsychological tasks, and adolescent eating behaviors a year later, as assessed through 24-hour dietary recall.

Methods: 190 adolescents (ages 14-18, M = 15.37) residing in a small Midwestern city in Nebraska, USA, completed EC tasks and dietary measures. At Time 1 (T1), EC was assessed with performance-based tasks, including the Nebraska Barnyard task, an adaptation of the Noisy Book task (Hughes et al., 1998), the Go/No-Go task as adapted from Bezdjian and colleagues (2009), and the Shape School-Switching Condition (Espy, 1997; Espy et al., 2006). At T1, diet was assessed by three daily dietary recalls using the Automated Self-Administered 24-hour Dietary Assessment Tool (ASA24-2016; Subar et al., 2012). EC and dietary recalls were repeated approximately a year later at Time 2 (T2). Structural equation modeling was used with ASA data. EC was modeled as a latent variable with performance-based tasks as indicators. Maximum likelihood with robust standard errors (MLR) was utilized. Model fit indices suggested good fit to the data, CFI = 1.00, RMSEA = .000.

Results: Better EC performance at T1 predicted greater fruit and vegetable intake (F/V) at T2 (β= .324, S.E.= .121, p= .008) with small-to-medium effects, controlling for T1 F/V consumption, maternal education, income-to-needs, age, and sex. T1 EC performance was a stronger predictor of F/V consumption at T2 than T1 F/V intake (β= .309, S.E.= .087, p < .001).

Conclusions: ASA findings suggest EC may be an important intervention target to improve adolescent dietary quality, including F/V intake.

Purpose: Adolescents with intellectual disabilities (ID) have 1.8 times the risk of overweight/obesity (OW/OB) compared to those without disabilities due to a myriad of social, behavioral, and health-related risk factors. This study reports the associations between diet quality, energy intake, and weight in this population.
Methods: This is a secondary analysis of baseline data from a clinical weight loss trial conducted in adolescents and young adults with ID and OW/OB. Dietary intake was assessed with 3-day image assisted food records which were used to calculate energy intake (kcals/day) and diet quality scores using the Healthy Eating Index 2015 (HEI-2015), which measures adherence to USDA dietary guidelines with max score 100 indicating perfect adherence. Overweight and obesity were determined using CDC guidelines for BMI z-score for those age ≤19. Associations between HEI-2015 scores, energy intake, and BMI z-scores were examined with Spearman and Pearson analyses. Subgroup analyses by diagnosis (Down syndrome (DS), autism, and other) were conducted with ANOVA and Kruskall-Wallis tests.
Results/findings: Participants were 13-19 years of age (n=88) with average BMI z-score of 1.93 ± 0.54. Average energy intake was 1965.4 ± 584 kcals/day and average HEI-2015 was 50.8 ± 9.4. Total energy intake was inversely associated with HEI-2015 (-0.26, p=0.016) but BMI z-score was not associated with energy intake or HEI-2015 (r=0.13, p=0.24 and r=-0.007, p=.95, respectively). Diet quality of those with autism (49.2 ± 9.5) had a significant inverse association with energy intake (-0.35; p= 0.03) and was lower than diet quality of those with DS (53.1 ± 8.7, p=0.09).
Conclusions: In conclusion, neither the diet quality nor energy intake was associated with OW/OB. However, energy intake was inversely associated with diet quality scores, indicating that higher energy intake is related to worse diet quality; the strongest association was among those with autism. Future studies should include those with normal weight to better elucidate the relationship of diet quality and energy intake with BMI in this population. Other factors including lack of physical activity, weight inducing medications, sedentary behavior and screen time may contribute to weight outcomes in this population and deserve further exploration.