Investigating relationships between problematic social media use and binge-eating disorder to inform precision guidance for adolescents

调查有问题的社交媒体使用与暴食症之间的关系，为青少年提供精准指导

• 批准号: 10815182
• 负责人: Jason M Nagata
• 金额: $ 53.96万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10815182
• 关键词: 10 year old; 18 year old; Academy; Adolescence; Adolescent; Adolescent Medicine; Adult; Affect; Age; American; Anxiety; Automobile Driving; Behavior; Binge Eating; Binge eating disorder; Brain; Cardiometabolic Disease; Cellular Phone; Conflict (Psychology); Data; Data Reporting; Development; Eating Behavior; Eating Disorders; Ethnic Origin; Focus Groups; Gender; Goals; Guidelines; Health; Heterogeneity; Individual; Interview; Link; Measures; Mediating; Medical; Mental Depression; Mental Health; Mood Disorders; Parents; Pathway interactions; Patient Self-Report; Pattern; Pediatrics; Personal Satisfaction; Phenotype; Population; Press Releases; Prevention; Professional Organizations; Prospective cohort; Questionnaires; Race; Relapse; Reporting; Research; Risk; Schedule; Schizophrenia; Sex Orientation; Sexual and Gender Minorities; Societies; Stress; Subgroup; Telephone; Time; Translating; Youth; addiction; adolescent health; clinical application; cognitive development; cohort; cyberbullying; economic cost; machine learning algorithm; machine learning method; minority children; novel; pediatrician; poor sleep; prevent; prospective; response; screening; social media; suicidal

PROJECT SUMMARY / ABSTRACT Nearly 30 million individuals in the US will suffer from an eating disorder in their lifetime, with onset most commonly in adolescence and with $65 billion in yearly economic costs. The most prevalent of all eating disorder phenotypes is binge-eating disorder, which affects 3-5% of the US population and portends an array of medical and psychiatric sequelae, including cardiometabolic disease and elevated suicidality. Social media use is ubiquitous among adolescents and implicated in binge-eating disorder, but the directionality and mechanisms remain unclear. Possible pathways include depression, anxiety, cyberbullying, stress, and poor sleep. Prior studies have been mostly cross-sectional, and patterns and associations may differ for diverse subpopulations (e.g., race/ethnicity, gender, sexual orientation). The prevention of binge-eating disorder requires accurate prediction. Mobile phone use patterns could predict binge-eating disorder; binge-scrolling social media could predict binge eating. Current guidance for adolescent social media use is limited and non- specific. Our long-term goal is to inform precision guidance for social media use for adolescents, parents, and clinicians to mitigate adverse mental health risks and optimize wellbeing. Our objective is to identify prospective associations, sensitive periods, and mechanisms between social media and binge-eating disorder from early to late adolescence. Our central hypothesis is that problematic social media behavior patterns (e.g., addiction, conflict, overuse, tolerance, and relapse) can predict binge-eating disorder through depression, anxiety, cyberbullying, stress, and poor sleep. To achieve our objective, we will leverage comprehensive assessments of social media use (problematic social media use and a novel objective mobile phone tracking app) and binge-eating behaviors and disorder among a diverse national prospective cohort in the Adolescent Brain Cognitive Development (ABCD) Study (N=11,875), followed annually (6 years completed). The cohort uniquely starts prior to adolescence to capture onset of social media and binge-eating patterns through early, mid, and late-adolescence. We will use robust longitudinal and machine learning methods to analyze all available years of data in the ABCD Study. Our specific aims will: 1) determine longitudinal associations, bidirectional relationships, and sensitive windows linking problematic social media use patterns and binge- eating disorder, applying an intersectional framework to characterize heterogeneity by race/ethnicity, gender, and sexual orientation; 2) identify mechanisms linking problematic social media use with binge-eating disorder; 3) use machine learning algorithms applied to mobile phone data to determine the extent to which social media use patterns over time can predict binge-eating disorder; and 4) translate findings to inform guidance for adolescents, parents, and clinicians. We will partner with a Youth Advisory Board and engage adolescents, parents, and clinicians to develop a robust dissemination plan to inform precision guidance for social media use among diverse adolescent populations to mitigate potential risks from binge-eating behaviors and disorder.

项目摘要 /摘要 在美国，近3000万人将遭受一生的饮食失调症，发病大部分 通常在青春期，每年经济成本为650亿美元。所有饮食中最普遍的 障碍表型是暴饮暴食障碍，影响美国人口的3-5％，并预示着阵列 医学和精神后遗症，包括心脏代谢性疾病和自杀性升高。社交媒体 在青少年中使用无处不在，与暴饮暴食有关，但方向性和 机制仍然不清楚。可能的途径包括抑郁，焦虑，网络欺凌，压力和差 睡觉。先前的研究主要是横截面，模式和关联可能会有所不同 亚群（例如种族/种族，性别，性取向）。预防暴饮暴食 需要准确的预测。手机使用模式可以预测暴饮暴食障碍；暴饮暴食 社交媒体可以预测暴饮暴食。当前有关青少年社交媒体使用的指南是有限的，非 具体的。我们的长期目标是为青少年，父母和 临床医生减轻不良心理健康风险并优化健康。我们的目标是确定 社交媒体与暴饮暴食障碍之间的潜在关联，敏感时期和机制 从早期到晚期。我们的中心假设是有问题的社交媒体行为模式（例如， 成瘾，冲突，过度使用，宽容和复发）可以通过抑郁症来预测暴饮暴食的疾病， 焦虑，网络欺凌，压力和睡眠不佳。为了实现我们的目标，我们将利用全面的 社交媒体使用的评估（有问题的社交媒体使用和新颖的客观手机跟踪 APP）以及青少年多元化的国家潜在队列中的暴饮暴食行为和混乱 脑认知发展（ABCD）研究（n = 11,875），每年遵循（已完成6年）。队列 独特开始在青春期之前开始，以捕获社交媒体的发作和早期的暴饮暴食模式， 中期和青春期。我们将使用强大的纵向和机器学习方法来分析所有 ABCD研究中可用的数据。我们的具体目标将：1）确定纵向关联， 双向关系和敏感的窗户连接有问题的社交媒体使用模式和暴饮暴食 - 饮食失调，应用相交框架以表征种族/种族，性别， 和性取向； 2）确定将有问题的社交媒体使用与暴饮暴食障碍联系起来的机制； 3）使用应用于手机数据的机器学习算法来确定社交媒体的程度 随着时间的流逝，使用模式可以预测暴饮暴食障碍； 4）翻译发现以告知指导 青少年，父母和临床医生。我们将与青年顾问委员会合作，并与青少年互动， 父母和临床医生制定强大的传播计划，以为社交媒体提供精确指南 在不同的青少年种群中使用，以减轻暴饮暴食和混乱的潜在风险。