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.

项目概要/摘要 在美国，近 3000 万人一生中将患有饮食失调症，其中发病率最高的是 通常发生在青春期，每年造成 650 亿美元的经济损失。所有饮食中最普遍的 疾病表型是暴食症，影响 3-5% 的美国人口，预示着一系列 医学和精神后遗症，包括心脏代谢疾病和自杀率升高。社交媒体 使用在青少年中普遍存在，并与暴食症有关，但方向性和 机制仍不清楚。可能的途径包括抑郁、焦虑、网络欺凌、压力和贫困 睡觉。先前的研究大多是横断面的，不同的研究模式和关联可能有所不同。 亚人群（例如种族/民族、性别、性取向）。暴食症的预防 需要准确的预测。手机使用模式可以预测暴食症；疯狂滚动 社交媒体可以预测暴饮暴食。目前对青少年社交媒体使用的指导是有限的并且非 具体的。我们的长期目标是为青少年、家长和青少年提供社交媒体使用的精确指导。 临床医生减轻不良心理健康风险并优化福祉。我们的目标是确定 社交媒体与暴食症之间的前瞻性关联、敏感期和机制 从青春期早期到青春期晚期。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、耐受和复发）可以通过抑郁来预测暴食症， 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 社交媒体使用评估（有问题的社交媒体使用和新颖的客观手机跟踪 应用程序）以及不同国家青少年前瞻性队列中的暴食行为和失调 大脑认知发展 (ABCD) 研究 (N=11,875)，每年进行一次随访（完成 6 年）。队列 独特地在青春期之前开始，通过早期捕捉社交媒体和暴饮暴食模式的出现， 青春期中期和后期。我们将使用强大的纵向和机器学习方法来分析所有 ABCD 研究中的可用年份数据。我们的具体目标将：1）确定纵向关联， 双向关系，以及将有问题的社交媒体使用模式和狂欢联系起来的敏感窗口 饮食失调，应用交叉框架来表征种族/民族、性别、 和性取向； 2）确定有问题的社交媒体使用与暴食症之间的联系机制； 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影响程度 随着时间的推移，使用模式可以预测暴食症； 4) 将调查结果转化为指导 青少年、父母和临床医生。我们将与青年咨询委员会合作并让青少年参与， 家长和临床医生制定强有力的传播计划，为社交媒体提供精准指导 在不同的青少年人群中使用，以减轻暴食行为和失调的潜在风险。