Social Media Intervention for OnLinE Victimized Youth

这项研究的目标是评估通过社会干预提供的自动干预的可行性 基于媒体的聊天机器人，以减少在初级保健中发现的在线受害，防止抑郁和自杀 亚综合征抑郁症状青少年的思想与行为(STB) 关注黑人、性少数和性别少数(SGM)青年的需要。在线受害(OV)(即， 在网络空间中造成伤害的贬损言论、符号、图像或行为)在社会上频繁发生 媒体，并与抑郁和自杀意念直接相关，这反过来又与近期自杀有关 风险。OV在青春期达到顶峰，在少数族裔青少年中特别流行；超过一半的黑人 青少年经历了一种基于种族的在线受害形式，包括贬低或排斥，以及SGM青少年 体验OV的比例是非SGM年轻人的三倍。对OV的早期发现和干预具有潜力 改善青春期的健康，防止长期的负面影响。初级保健提供者(PCP) 认识到OV在他们的患者中很常见，但实际障碍限制了他们的反应能力。 聊天机器人是一种软件程序，它使用人工智能来模拟通过文本、语音和 或视频，并可以部署在社交媒体、短信上，也可以基于网络。一个响应OV的聊天机器人 在初级保健中被确定可以扩大初级保健医生的能力，通过自动干预来帮助患有OV的青年。 我们建议开发和评估Smiley，这是一种部署在社交媒体上的聊天机器人交付的干预工具 会减少OV频率和痛苦强度(与抑郁严重程度和自杀有关的因素 在初发症状为亚综合征抑郁症状的网络受害青少年中 关心。为了向干预措施的发展提供信息，我们将应用实施综合框架 研究(CFIR)进行定性访谈，以确定对 聊天机器人提供了对在线受害的干预。然后我们将使用以人为中心的设计方法来 开发、评估和迭代Smiley。然后，我们将进行一项随机试验，比较微笑和简短的 对新近受害的亚综合征抑郁青少年的心理教育干预。一起， 这些目标将提供关于一种新型聊天机器人干预的数据，这种干预可能有望填补 为遭受网络伤害的青少年提供服务，并有意义地推进预防自杀 脆弱的年轻人。我们的目标是开发一种对小规模青年来说可接受和可行的干预措施， 特别是黑人和SGM青年，他们特别容易经历网络受害，因此 解决这些青年健康差距的一个根源。

The objective of this research is to evaluate the feasibility of an automated intervention delivered via a social media-based chatbot to reduce online victimization detected in primary care and prevent depression and suicidal thoughts and behaviors (STBs) among adolescents with subsyndromal depressive symptoms, with special attention to the needs of Black and sexual and gender minority (SGM) youth. Online victimization (OV) (i.e., disparaging remarks, symbols, images, or behaviors that inflict harm in online spaces) frequently occurs on social media, and is directly linked to depression and suicidal ideation, which in turn associate with near-term suicide risk. OV peaks during adolescence and it is especially prevalent among minority adolescents; over half of Black youth experience a form of race-based online victimization involving derogation or exclusion, and SGM youth experience OV at three times the rate of non-SGM youth. Early detection and intervention on OV has potential to improve health during adolescence and prevent longer-term negative effects. Primary care providers (PCPs) recognize that OV is common among their patients, but practical barriers inhibit their capacity for response. Chatbots are software programs that use artificial intelligence to simulate conversation with a user via text, voice, or video, and can be deployed on social media, SMS, or can be web-based. A chatbot that responds to OV identified in primary care could extend PCPs’ capacity to help youth with OV through an automated intervention. We propose to develop and evaluate SMILEY, a chatbot-delivered intervention deployed on social media that will reduce OV frequency and intensity of distress (factors associated with depressive severity and suicidal ideation) among online-victimized adolescents with subsyndromal depressive symptoms identified in primary care. To inform intervention development, we will apply the Consolidated Framework for Implementation Research (CFIR) to the conduct of qualitative interviews to identify perceptions and preferences regarding a chatbot-delivered intervention for online victimization. We will then use human-centered design methods to develop, evaluate, and iterate SMILEY. We will then conduct a randomized trial comparing SMILEY vs. a brief psychoeducational intervention among recently victimized adolescents with subsyndromal depression. Together, these aims will provide data regarding a novel chatbot intervention that may hold promise to fill a critical gap in services for adolescents experiencing online victimization and meaningfully advance suicide prevention for vulnerable youth. We aim to develop an intervention that is acceptable and feasible for minoritized youth, specifically Black and SGM youth, who are especially vulnerable to experience online victimization, thus addressing a source of health disparities in these youth.