Purpose Cannabis legalization in the U.S. has introduced an ongoing public health challenge. Among adults, cannabis legalization is associated with increased cannabis use and shifting attitudes toward cannabis use. These expectancies, or personal beliefs about the outcomes of a behavior, are both positive (e.g., increased relaxation) and negative (e.g., cognitive impairment). With rapid shifts in state-level cannabis legislation, the associations of these policies with adolescent cannabis expectancies are unknown. Methods We conducted a cross-sectional analysis of the Adolescent Brain Cognitive Development Study from the Year 2 follow-up (2018-2020, average age: 12 years) via Poisson analysis to investigate the association between state-level cannabis legalization and positive and negative cannabis expectancies via the Marijuana Effect Expectancy Questionnaire-Brief, controlling for sociodemographic covariates. Results A total of 8356 participants lived in states with no (NCL, 34%), medical (MCL, 39%), or recreational (RCL, 27%) cannabis legalization in place. Compared to NCL states, participants from both MCL (ARR=1.09, 95%CI: 1.07-1.11, p<0.001) and RCL (ARR=1.08, 95%CI: 1.06-1.11, p<0.001) states were more likely to report positive cannabis expectancies. Those from MCL states were less likely to report negative cannabis expectancies (ARR=0.98, 95%CI: 0.97-0.99, p=0.017). Discussion These findings indicate that early adolescents from states with medical and recreational cannabis legalization may have higher positive cannabis expectancies compared to those from states with no cannabis legalization. Our results may have important implications for public health officials, policymakers, and clinicians working to help adolescents understand the effects of cannabis use.

Introduction Adolescence is a critical period during which exposures to cardiovascular disease risk factors and related pathophysiologic changes begin. Yet neighborhood-level factors shaping cardiovascular health from adolescence onward remain understudied. The American Heart Association’s Life’s Essential 8 (LE8) is a composite cardiovascular health score, encompassing diet, physical activity, body mass index, blood pressure, and other factors. Area Deprivation Index (ADI), Social Vulnerability Index (SVI), and Childhood Opportunity Index (COI) estimate neighborhood disadvantage. This study examines associations between neighborhood disadvantage and LE8 cardiovascular risk factors in early adolescents. Methods We analyzed data from the Adolescent Brain Cognitive Development (ABCD) Study, including 8,160 early adolescents with behavioral subcomponent scores and 1,125 with overall LE8 and health factors subcomponent scores. Neighborhood disadvantage indices (ADI, SVI, COI) were derived from geospatial data. Multivariable linear regression models assessed associations between ADI, SVI, and COI at baseline (2016–2018) and LE8 scores at Year 2 (2018–2020) and Year 3 (2019–2021), adjusted for age, sex, and race/ethnicity. Results Higher neighborhood disadvantage was associated with lower (less healthy) LE8 cardiovascular health scores in early adolescents, driven mainly by behavioral factors. Overall LE8 scores were 9.45 points lower for the most deprived ADI quintile (95% CI: -11.86, -7.05; p<0.001), 6.95 points lower for the most vulnerable SVI quintile (95% CI: -9.09, -4.82; p<0.001), and 8.45 points lower for the lowest opportunity COI quintile (95% CI: -10.77, -6.12; p<0.001). Conclusion Higher neighborhood deprivation was associated with poorer LE8 cardiovascular health scores in early adolescence.

This cross-sectional study uses passive smartphone sensing data to characterize school night smartphone use by app category among adolescents and to examine sociodemographic correlates of nighttime use in a national sample.

INTRODUCTION:Adolescence is a critical period of ongoing cognitive and behavioral development. Problematic social media use is a potentially important factor that shapes cognitive development during this period. This study examined the associations between problematic social media use trajectories and cognitive performance. METHODS:A total of 4,809 adolescents (mean age = 12 years, 48.9% female, 73.6% White) from the Adolescent Brain Cognitive Development Study were assessed from Year 2 (2018-2020) to Year 4 (2020-2022). Group-based trajectory modeling estimated patterns of problematic social media use in adolescents aged 10-16 years. Cognition was assessed at Year 4 (aged 12-16 years) using 5 of the 7 subtests of the NIH Toolbox Cognition Battery. Multiple linear regression models estimated the associations between problematic social media use trajectories and cognitive performance, adjusting for demographics, cognitive scores, mental health symptoms, and study site. RESULTS:Three problematic social media use trajectories were identified: no/low increasing, low-to-moderate, and moderate-to-high trajectories. Adolescents in the low-to-moderate trajectory demonstrated lower scores on the Picture Sequence Memory Test (β [standardized beta]= -0.10, 95% CI= -0.16, -0.03, p=0.003) and Picture Vocabulary Test (β= -0.11, 95% CI= -0.16, -0.07, p<0.001) than those in the no/low increasing trajectory. Adolescents in the moderate-to-high trajectory demonstrated lower scores on the Picture Sequence Memory Test (β= -0.24, 95% CI= -0.35, -0.13, p<0.001) and Picture Vocabulary Test (β= -0.17, 95% CI= -0.25, -0.09, p<0.001). CONCLUSIONS:Increasing trajectories of problematic social media use were associated with lower cognitive performance in the memory and language domains, highlighting the importance of developing effective interventions to address problematic social media use behaviors and support cognitive development.

STUDY OBJECTIVES:To evaluate associations between age and objectively measured sleep in women. METHODS:We analyzed ~3.8 million nights' data from 192 500 female Galaxy Smartwatch users aged 20-65 years (United States, South Korea, Germany, France, and the UK) with ≥7 nights' sleep data during March 2024. We evaluated associations between age and total sleep period duration (TSPD), total sleep time (TST), and wakefulness after sleep onset (WASO; log-transformed) using linear mixed models, adjusting for repeated user measures, country, body mass index, weekday/weekend night, and daily activity time. Reference group was age 20-24 years. Separate models were run for a comparison group of men. RESULTS:In women WASO increased notably at midlife; average increases of +5 mins (+15%) for 50-54 years, +9 minutes (+25%) for 55-59 years, and + 11 minutes (+32%) for 60-64 years vs. reference group (corresponding increases in men were + 3 minutes [+9%], +6 minutes [+16%], and + 9 minutes [+27%]). Compared with the reference group, age differences in TSPD and TST were ≤ 5 minutes less and ≤ 17 minutes less, respectively. Effects of age on TST and WASO were similar across Western countries; in South Korea, TSPD and TST were shorter across all ages, while increases in WASO were apparent from early adulthood. CONCLUSIONS:A pronounced increase in WASO was seen in women at midlife. Women in this stage of life could benefit from early identification and tailored interventions to improve their sleep as part of overall health counselling.

PURPOSE:To determine associations between media parenting practices and cyberbullying in a national cohort of early adolescents. METHODS:We analyzed cross-sectional data from the Adolescent Brain Cognitive Development Study (N = 9,686; 48.2% female, 44.7% non-White), Year 3 (2019-2022, 11-15 years). Media parenting practices were assessed for the following: screen time modeling, mealtime screen use, bedroom screen use, screen use for behavior management, monitoring screen time, and limiting screen time. Logistic regression models were used to determine associations between media parenting practices and cyberbullying victimization and perpetration, adjusting for sociodemographic characteristics. RESULTS:Parental allowance of mealtime screen use (adjusted odds ratio [AOR] 1.14), bedroom screen use (AOR 1.31), and screen use for behavior management (AOR 1.18) were associated with higher odds of cyberbullying victimization. Greater allowance of bedroom screen use was associated with higher odds of cyberbullying perpetration (AOR 1.44). Greater restriction of screen time (AOR 0.80) was associated with lower odds of cyberbullying victimization. Daily active screen time partially mediated these associations. DISCUSSION:Media parenting practices had stronger associations with cyberbullying victimization compared to perpetration. The significant mediation effect of active screen time indicates the importance of the amount of time on screens, which likely enables greater exposure to cyberbullying behaviors. Based on current pediatrics guidelines, parents may consider discussing how to safely navigate digital media and promote positive, respectful digital environments to minimize cyberbullying exposure behaviors. Our findings reinforce elements of the American Academy of Pediatrics' family media plan, including considering limiting bedroom, mealtime, and general screen use.

Abstract Introduction REM sleep is critical for health and cognitive functioning. Recent studies have identified electrophysiological REM burst events (REM bursts) in theta (4-8Hz) and alpha (8-16Hz) frequency bands associated with cognitive performance, suggesting REM bursts as neural markers of cognitive processes. Still, intra-individual characteristics of REM bursts are unknown. Here, we conducted an in-depth analysis of REM burst events across the night and examined their intra-subject reliability across four nights of sleep. Methods 86 healthy young adults (67F; 18-35 years) slept in-lab for four nights with polysomnography. A validated REM burst detection algorithm was used to identify EEG theta and alpha bursts. Using linear mixed models, we examined burst features (count, power, duration, density) across four quartiles of sleep and relations between time in REM and bursts in each night. We also calculated intraclass correlation coefficients (ICCs) for burst features and REM minutes across four nights of sleep per subject. Results Both REM theta and alpha burst count increased across each quartile, but burst power decreased over the night. Alpha burst density was lowest during quartile 1 compared with the rest of the night. Theta burst duration increased from quartile 1 and 2 to 3 and 4, while alpha burst duration did not vary. REM minutes positively predicted count and density measures, but negatively predicted power and duration measures. Exclusively in quartiles 1 and 2, REM minutes positively predicted alpha burst density and negatively predicted alpha burst power, indicating potential change in REM physiology from early to late night. Intraclass correlations from alpha and theta bursts showed that power and duration are highly reliable within-subject (ICC≈0.9), while counts, density, and REM minutes are moderately reliable (ICC≈0.5), showing similar levels of reliability levels as non-REM sleep spindles. Conclusion REM bursts were shorter, higher in power, and negatively correlated with the amount of REM sleep in the first half of night, while density increased across the night. We also identified burst features as trait-like, with intra-individual reliability comparable to existing spindles results. These results may provide foundational knowledge for studying REM bursts as neural markers of REM functions. Support (if any) RF1AG061355 (Baker/Mednick). K08HD107161 (Simon).

Abstract Introduction Nighttime wakefulness is common among postmenopausal women with vasomotor symptoms (VMS). Elinzanetant has previously shown improvements in patient-reported sleep outcomes in this population. The Phase II NIRVANA trial was the first to evaluate elinzanetant’s effect on wakefulness after sleep onset (WASO) using both objective (polysomnography [PSG], Sleepiz One+) and subjective (Sleep Diary) measures. This post hoc analysis compared changes in WASO with elinzanetant across all three modalities. Methods NIRVANA randomized 110 postmenopausal women with PSG-confirmed WASO ≥30 minutes and ≥20 moderate-to-severe VMS/week to elinzanetant 120 mg (n=55) or placebo (n=55) once daily for 12 weeks. Sleep disturbances were assessed using in-lab PSG and patient-reported Sleep Diary for all participants, and with the contactless home-monitoring device Sleepiz One+ in a subset (elinzanetant: n=33, placebo: n=33). PSG assessments occurred at baseline, week 4, and week 12 (two consecutive nights/timepoint). Sleepiz One+ and diary data were collected nightly. WASO values were analyzed on the original scale for consistency in presentation across measures. A post hoc random coefficient model estimated overall treatment effects over 12 weeks for each modality. Results Elinzanetant demonstrated numerical reductions in WASO versus placebo across all assessment modalities. PSG: Baseline mean (standard deviation [SD]) WASO was 74.7 (34.8) minutes for elinzanetant and 82.8 (34.4) minutes for placebo. Overall treatment effect favored elinzanetant (least squares [LS] mean difference: -10.1 minutes; unadjusted 95% confidence interval [CI]: -18.5, -1.6). Sleepiz One+: Baseline mean (SD) WASO was 77.7 (52.6) minutes for elinzanetant and 61.7 (27.6) minutes for placebo. Overall treatment effect favored elinzanetant (LS mean difference: -17.7 minutes; unadjusted 95% CI: -27.1, -8.2). Sleep Diary: Baseline mean (SD) WASO was 42.4 (25.7) minutes for elinzanetant and 45.5 (25.6) minutes for placebo. Overall treatment effect favored elinzanetant (LS mean difference: -8.1 minutes; unadjusted 95% CI: -14.2, -1.9). Conclusion Greater reductions in WASO were observed with elinzanetant versus placebo across all modalities, consistent with previously reported improvements in sleep disturbances from the OASIS trials. While exploratory in nature, these findings support elinzanetant’s potential use in improving sleep disturbances in menopausal women with VMS. Support (if any) Sponsored by Bayer. Medical writing assistance (Highfield, Oxford, UK) funded by Bayer.

BACKGROUND:Given concerns that screen time may impact dietary habits, this study investigated the association between screen time and dietary intake among adolescents in the United States. METHODS:We analyzed a prospective cohort (N = 6485, 47.3% female, age: 12 ± 0.7 years) from the Adolescent Brain Cognitive Development (ABCD) Study, using data from Year 2 (2018-2020) and Year 3 (2019-2021). Multinomial logistic regression models estimated the associations between participant-reported screen time (watching television shows and videos, playing video games, socializing, browsing the internet, and total screen time (hours/day)) and parent/participant-reported intake of various food/nutrient categories 1 year later (Year 3). We adjusted for age, sex, race and ethnicity, household income, parent education, average daily kilocalorie intake, respective food or nutrient, and study site (Year 2). RESULTS:Each additional hour of most screen time modalities was prospectively associated with higher odds of consuming fewer fruits, vegetables, whole grains, legumes, fiber, and dairy, and higher glycemic index, and higher odds of consuming more added sugars and a higher polyunsaturated fats ratio 1 year later. CONCLUSION:These findings highlight the need for parental guidance and clinical interventions to support screen time habits and promote healthy dietary choices among adolescents. IMPACT:This study examines the association between contemporary screen time modalities and dietary intake 1 year later in a demographically diverse U.S. sample of early adolescents. Most screen time modalities, such as total screen time and watching television shows and videos, were prospectively associated with higher odds of consuming fewer fruits, vegetables, whole grains, legumes, and fiber 1 year later. Greater total screen time and time spent socializing were prospectively associated with higher odds of a higher polyunsaturated fats ratio 1 year later.

PURPOSE:This study examined the associations between social media use trajectories and eating disorder symptoms across early adolescence. METHODS:Data from 10,735 United States adolescents (48.9% female, mean baseline age 10 ± 0.7 years) participating in the Adolescent Brain Cognitive Development Study were analyzed. Adolescents self-reported social media use (average daily hours) from baseline (2016-2018) through Year 4 (2020-2022). Parent-reported eating disorder symptoms (experienced by adolescents) were assessed at baseline and Year 4: binge-eating symptoms, self-worth tied to weight, inappropriate compensatory behaviors to prevent weight gain, worry about weight gain, and any eating disorder symptom. Group-based trajectory modeling identified social media trajectories from baseline to Year 4. Logistic regression models estimated associations between social media use trajectories and eating disorder symptoms at Year 4, adjusting for covariates, including baseline eating disorder symptoms. RESULTS:Three social media use trajectories emerged: (1) no/very low use, (2) moderate, gradual increasing, and (3) rapid increasing. Compared with those in the no/very low use trajectory, adolescents in the moderate, gradual increasing, and rapid increasing trajectories had significantly higher odds of experiencing most eating disorder symptoms. CONCLUSIONS:Adolescents with increasing social media use were more likely to experience a range of eating disorder symptoms.

Sleep plays a foundational role in adolescent development, supporting emotional regulation, cognition and brain maturation. However, adolescents today face increasing challenges to healthy sleep partly due to widespread social media use and heightened reward sensitivity. While each factor has been studied independently, less is known about how they interact, especially whether brain activation shapes how social media influences sleep. We examined prospective associations between self-reported sleep duration, social media use and brain activation in 1985 adolescents (mean age, Year 2 = 11.91 years) from the Adolescent Brain Cognitive Development (ABCD) Study. Sleep duration was measured via the Munich Chronotype Questionnaire; social media use via the Youth Screen Time Survey and brain activity using fMRI during the Monetary Incentive Delay task. We tested three sets of prospective models to examine how sleep, social media use, executive control and reward-related brain activation influence each other over two years, controlling sociodemographics. Greater social media use at Year 2 predicted shorter sleep duration at Year 4, particularly among adolescents with lower activation in the nucleus accumbens, cingulate gyrus, insula and putamen. Shorter sleep also predicted increased social media use two years later, with effects moderated by activation in the insula and middle frontal gyrus. Longer sleep at Year 2 predicted higher caudate activation at Year 4. Brain activation in reward and executive control-related regions moderated associations between sleep and social media use, suggesting that lower neural engagement may reflect increased susceptibility to the sleep-disrupting effects of social media.

Abstract Introduction Sleep in aging is characterized by decreased sleep quantity and quality, further amplified in clinical populations, such as Parkinson’s disease (PD) and people living with HIV (PLWH). Wearables such as actigraphy and commercial devices are increasingly deployed in remote sleep monitoring, yet validation of these technologies primarily reflects young healthy adults under laboratory conditions. Whether these devices align to daily sleep diaries – a standard measurement in the field – in older adults and clinical populations has not been adequately examined. Methods Adults ≥ 50 years were recruited into three groups: healthy controls (n=33), PD (n=21), PLWH (n=21). Participants completed 7-14 consecutive nights of at-home sleep monitoring, as part of an ongoing observational study, wearing an Axivity AX3 wrist actigraphy, Oura ring (generation 3 model), and completing daily electronic sleep diaries. Total sleep time (TST), sleep efficiency (SE), and wake after sleep onset (WASO) were derived for each night using the GGIR R package for actigraphy and default software for the ring. These metrics were compared across devices and diaries using night-by-night Spearman correlations and Bland-Altman analyses to calculate limits of agreement (LOA). Results Correlations between the two devices and sleep diaries were high for TST (ρ=0.64-0.74) and lower for SE (ρ=0.29-0.47) and WASO (ρ=0.27-0.45). Bland-Altman analyses revealed the ring reported lower TST compared to actigraphy with a mean difference of −12.6 minutes (95% LOAs -134.0, 108.8). The ring detected lower SE than actigraphy (mean -9.1%, 95% LOAs -26.3, 8.0). Both devices reported lower TST (actigraphy: -28.0 min 95% LOAs -179.9, 123.8; ring: -35.8 min 95% LOAs -183.0, 111.4) and SE (actigraphy: -4.1% 95% LOAs -28.6, 20.3; ring: -12.8% 95% LOAs -33.9, 8.3) compared to self-report. PD participants were biased towards longer actigraphy TST relative to ring TST. Conclusion Devices agreed moderately for TST and differed most in SE estimates across cohorts. Both devices can be used for scalable, remote sleep monitoring in real world cohorts. Future studies should compare devices with polysomnography in aging clinical populations. Support (if any) R01AG081144

Objectives Few studies have examined sleep health among African adolescents. We aimed to understand sleep health among Ugandan secondary school students. Methods We collected quantitative data in two schools through a survey with items on sleep health and insomnia (using the Cleveland Adolescent Sleepiness Questionnaire, Munich Chronotype Questionnaire and Insomnia Severity Index [ISI]) and mental health with the UNICEF Measuring Mental Health Among Adolescents and Young People at the Population Level (MMAPP) tool. We used regression models to assess characteristics associated with ISI score, and of sleep health with depression and anxiety. We conducted focus group discussions and in-depth interviews with students, parents, teachers, and officials. Quantitative and qualitative analyses were guided by the social ecological model of sleep health. Results The 358 participants generally reported poor sleep health (assessed by satisfaction, alertness, timing, efficiency and duration), especially among boarding students. The median sleep duration was 5.1 hours (interquartile range 4.2-6.2). Overall, 36 (10.1%) participants screened positive for moderate/severe insomnia (ISI ≥15), with higher prevalence among females than males (12.7% vs. 6.2%; p = .05). Qualitative interviews highlighted that individual (knowledge and attitudes), social-cultural (religious beliefs, family dynamics, academic demands, peer pressure), environmental (school and home conditions, technological influences), and societal factors (national school schedule guidelines) influenced sleep patterns. Depression and anxiety were associated with multiple dimensions of poor sleep health. Conclusions Ugandan adolescents face substantial sleep challenges, which are associated with poor mental health. Evidence-based interventions should be adapted for specific social-ecological contexts to improve sleep and mental health in this population.

Importance:Given shared processes in attentional control, impulsivity, and reward sensitivity, problematic social media use (PSMU) may be associated with attention-deficit/hyperactivity disorder (ADHD) symptoms. Yet most evidence has been from cross-sectional studies; multiyear prospective, within-person studies on an association of PSMU with ADHD symptoms are lacking. Objectives:To estimate bidirectional, within-person associations between PSMU and ADHD symptoms across 5 annual assessments, and to test variation by sex. Design, Setting, and Participants:This prospective cohort study used data from 5 annual assessments (year 2 [2017-2019] through year 6 [2021-2023]) of the Adolescent Brain Cognitive Development Study, a population-based cohort that enrolled youths aged 9 to 10 years from 21 US sites in year 1 (2016-2018). Participants had data on ADHD symptoms or PSMU at 1 or more waves between year 2 and year 6. Data analysis was performed between July and September 2025. Exposure:Youth-reported PSMU measured using the Social Media Addiction Questionnaire. Main Outcomes and Measures:Parent-reported ADHD symptoms (measured using the ADHD Problems subscale of the Child Behavior Checklist) at each wave. Random-intercept cross-lagged panel models were used to separate stable between-person differences from within-person variation and to estimate concurrent and lagged within-person associations between PSMU and ADHD symptoms across waves. Results:The analytic sample consisted of 11 286 youths with a mean (SD) age at year 2 of 12.1 (0.67) years; 5918 (52.4%) were male. At the within-person level, years in which youths reported higher-than-usual PSMU were followed by elevations in parent-reported ADHD symptoms (year 4 to year 5: β  = 0.08 [95% CI, 0.03-0.12], P < .001; year 5 to year 6: β = 0.08 [95% CI, 0.03-0.13], P = .001). ADHD symptoms were also associated with higher PSMU from year 4 to year 5 (β = 0.04 [95% CI, 0.01-0.07]; P = .02). Tests of moderation indicated that the prospective association between PSMU and ADHD symptoms was higher in magnitude for males than for females (change in χ216 = 31.7; P = .01). Conclusions and Relevance:This cohort study of US youths found that year-to-year elevations in self-reported PSMU were directly associated with ADHD symptoms during mid-adolescence, particularly among males; reverse associations of ADHD symptoms with later PSMU were small in magnitude and sporadic. Screening for hard-to-control social media use, time spent on social media, and attention to sex-specific patterns may be warranted, although the population-based associations may be small.

Objective:Despite increasing social media use among adolescents, few studies have investigated social media use patterns associated with the Social Media Addiction Questionnaire Scale. Social media addiction (SMA) is characterized in terms of social media platforms, engagement patterns, and account settings. Method:Cross-sectional data on youth 10 to 13 years of age from the Adolescent Brain Cognitive Development℠ Study (n = 5,639) were used. The majority of the sample were female, White, and from families living above poverty. SMA was assessed via an adapted scale. Regression models assessed links between SMA and hours spent per day on social media, most-used platform, public and secret accounts, and follower and following counts. Results:SMA was higher among youth whose most-used platforms were TikTok (b = 1.52, 95% CI = 1.12, 1.93), Instagram (b = 0.92, 95% CI = 0.51, 1.34), and Snapchat (b = 0.60, 95% CI = 0.16, 1.03). Those with a public account (b = 0.85, 95% CI = 0.56, 1.13), a secret account (b = 2.27, 95% CI = 1.65, 2.89), or reporting more social media hours (b = 0.66, 95% CI = 0.61, 0.71) had higher SMA scores. Weak interactions between social media hours and platforms were observed. Conclusion:Higher SMA scores were most associated with TikTok, Instagram, and Snapchat use as well as using a public account, a secret account, and spending more time on social media. The relationship between social media hours and SMA confirms previous findings. This is the first study to investigate the relationship between account settings and SMA.

Abstract Introduction Sleep disturbances are common among midlife women. Wearables offer a novel, scalable approach to study sleep globally. Using Samsung Galaxy Watch data, we examined associations of age, weekdays/weekends, physical activity, and country with sleep parameters in an international cohort of women. Methods We analyzed sleep data from 192,500 women (aged 20–65 years) from France, Germany, South Korea, the UK, and the US (n=38,500/country). Sleep parameters included total sleep period duration (TSPD), total sleep time (TST), and wake after sleep onset (WASO; log-transformed). Linear mixed models assessed associations with age, weekdays/weekends, physical activity, and country (reference: US). An exploratory model included age-by-country interactions. Results Mean (standard deviation) values were: TSPD 439.4 (92.0) minutes, TST 391.2 (81.9) minutes, and WASO 48.3 (33.5) minutes. Age distributions were comparable across countries, with ~1/3 of women aged ≥50 years. Weekend nights were associated with ~24 minutes longer TSPD (+5.4%). Age and physical activity effects were small (±5 minutes). Women in South Korea had the shortest TSPD, averaging 27 minutes less (−6.2%) than US women. TST declined with age, with women aged ≥50 sleeping 13–17 minutes less (−3.3% to −4.4%) than those aged 20–24. Weekend nights were associated with ~21 minutes longer TST (+5.3%) than weeknights. Activity-related differences were small (< 3 minutes; < 1%). Women in South Korea averaged a 25-minute shorter TST (−6.3%) versus US women. WASO increased with age; women aged ≥50 had 5–11 minutes more wakefulness (+15–32%) than those aged 20–24. Effects were small for weekend (+2 minutes; +5.4%), activity (< 1 minutes; −1.1% to −2.5%) and country (UK: +1.5 minutes; South Korea: −1 minute versus US). Age-related WASO increases were consistent across countries, except South Korea where interaction effects were greater. Conclusion Results demonstrated country-specific differences in TST and TSPD and age-related effects on TST and WASO, with differences evident in women aged ≥50, consistent with the menopausal transition. Smartwatch data provides large-scale sleep research potential to understand unique factors influencing sleep in women. Support (if any) Sponsored by Bayer and Samsung Electronics America. Medical writing assistance (Highfield, Oxford, UK) funded by Bayer.

OBJECTIVE:Given the increasing prevalence of cyberbullying in the digital era, this study evaluated whether cyberbullying trajectories were prospectively associated with academic outcomes among early adolescents. METHODS:We analyzed a prospective cohort (N = 10,003, 48.4% female) from the Adolescent Brain Cognitive Development Study. Group-based trajectory modeling estimated patterns of adolescent-reported cyberbullying victimization from Year 2 (2018-2020; mean age: 12.1 years, SD = 0.8) to Year 4 (2020-2022). Parent-reported academic outcomes, assessed at Year 5 (2021-2023), included their children's grades from the past year and the number of excused and unexcused absences, assessed separately, in the past four weeks and 12 months. Ordinal logistic regression models estimated the associations between the cyberbullying trajectories and academic outcomes, adjusting for sex, race, ethnicity, Year 2 age, household income, parent education, attention-deficit/hyperactivity symptoms, depressive symptoms, academic outcome measures, total screen time, individualized education plans, cyberbullying perpetration, traditional bullying, chronic conditions, smartphone ownership, and study site. RESULTS:Two cyberbullying trajectories emerged: 1) no or very low (94.9%), and 2) increasing cyberbullying (5.1%). Compared to adolescents in the no or very low cyberbullying trajectory, those in the increasing cyberbullying trajectory had higher odds of lower grades (AOR: 1.40, 95% CI: 1.11, 1.76) and more unexcused absences in the past four weeks (AOR: 1.45, 95% CI: 1.01, 2.08). Cyberbullying was associated with additional academic outcomes. CONCLUSION:Cyberbullying trajectories were linked to poorer academic performance and greater excused and unexcused school absences. These findings underscore the importance of developing targeted strategies to prevent and protect against cyberbullying victimization.

To investigate sex differences in prospective associations between eating disorder (ED) symptoms and changes in body mass index (BMI) percentile in early adolescence. This prospective study used survey data from 7111 participants aged 10–12 years at Year 1 from the Adolescent Brain Cognitive Development (ABCD) Study—a diverse, national sample of adolescents from 21 sites across the United States (US). Multivariable linear regression models were used to assess the prospective associations between ED symptoms at Year 1 and BMI percentile at Year 2, adjusting for covariates and BMI percentile at Year 1. Effect moderation was explored in sex-stratified models. Sex modified the relationship between ED symptoms and changes in BMI percentile. Having binge eating symptoms (B = 3.65, 95

BACKGROUND AND OBJECTIVES:Social media exposure may influence early nicotine experimentation, a behavior linked to later nicotine dependence and health risks. Few studies have examined the role of smoking expectancies (i.e., beliefs about the anticipated positive or negative effects of nicotine) as a pathway underlying this association, especially in early adolescence. The objective of this study is to examine the prospective association between social media use and nicotine experimentation in early adolescence, and whether smoking expectancies mediate this relationship. METHODS:Using longitudinal data from the Adolescent Brain Cognitive Development Study (N = 8292; mean age 12.0 years at Year 2; 2018-2020), we estimated associations between social media time (Year 2) and nicotine experimentation (Year 4), adjusting for confounders and testing positive and negative smoking expectancies (Year 3) as mediators using generalized structural equation modeling. RESULTS:Social media time at Year 2 was associated with nicotine experimentation at Year 4. Positive smoking expectancies (but not negative expectancies) were associated with nicotine experimentation. Positive smoking expectancies mediated 5.97% (95% CI: 1.27%-10.67%, p = .013) of the social media-nicotine experimentation association. DISCUSSION AND CONCLUSIONS:Early social media exposure may be associated with favorable beliefs about nicotine, increasing adolescents' risk of experimentation. Regulatory policies, clinical screening, and prevention programs could mitigate early nicotine use. Future research should explore how these relationships evolve across adolescence. SCIENTIFIC SIGNIFICANCE:This study advances understanding of how social media use contributes to early nicotine experimentation in adolescents by identifying positive smoking expectancies as a potential pathway.