Social Media Signals for Post-traumatic Stress and Anxiety in Crisis-Inflicted Communities

受危机影响的社区中创伤后压力和焦虑的社交媒体信号

基本信息

批准号：
9319296
负责人：
Munmun De Choudhury
金额：
$ 28.53万
依托单位：
GEORGIA INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-09-15 至 2019-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9319296
关键词：
Acute Adjustment Disorders Affect Affective Algorithms Anxiety Anxiety Disorders Archives Area Arousal Attention Behavior Behavioral Cognitive Collaborations Communities Complement Cues Custom Data Detection Diagnosis Diagnostic Disasters Distress Early Diagnosis Early Intervention Emotional Event Exhibits Exposure to Face Faculty Feeling Fright General Population Goals Government Grief reaction Health Health Professional Health Resources Health behavior Human Impairment Institutes Intervention Investigation Knowledge Laboratory Study Language Lead Life Linguistics Link Longitudinal Studies Measures Memory Mental Depression Mental Health Mental Health Services Mental disorders Metadata Methods Modeling Mood Disorders Moods Nature Occupational Outcome Pattern Pharmaceutical Preparations Physiological Policies Population Post-Traumatic Stress Disorders Predisposition Prevention strategy Principal Investigator Process Property Psychologist Psychology Public Health Reaction Recovery Recurrence Rehabilitation therapy Reporting Research Risk Risk Factors Role Sampling Schools Signal Transduction Social Network Social support Source Stress Structure Surveys Survivors Symptoms Syndrome Techniques Technology Texas Text Textiles Thinking Time Trauma Universities Variant Work Writing austin behavior measurement behavioral health behavioral study biological adaptation to stress brief intervention cognitive performance data mining design disaster survivor effective intervention empowered experience help-seeking behavior high risk population instrument interactive computing intervention program lens novel phrases physical conditioning post-traumatic stress prevention service programs psychologic public health relevance response sensor social social capital social media social networking website social stigma stress disorder stress related disorder stressor success symptom treatment symptomatology technology development tool traumatic event

项目摘要

DESCRIPTION (provided by applicant): Millions of people undergo traumatic experiences annually. While acute distress is a normative response to trauma, a small percent of the people who have undergone traumatic experiences continue to exhibit severe stress reactions long after the trauma. The posttraumatic reactions may include intrusive memories, hypervig- ilant arousal, impaired concentration, depression, emotional detachment from others, and disengagement from aspects of life that provide meaning and self-fulfillment. In functional assessments these recurrent reactions seriously impair intrapersonal, interpersonal, and occupational functioning. Despite these ramifications, post-traumatic stress disorders are under-reported, and in many cases go completely undetected. Barriers to help-seeking include: lack of knowledge about predisposition symptoms, the unavailability of appropriate remedial/prevention services, the fear of the social stigma of mental illness, lack of social support, or assumptions that the mood changes are a part of the overwhelming nature of post-crisis life. In recent times, many crisis rehabilitation efforts have recognized these challenges, and have incorporated access to mental health services in their intervention and support programs. However, treatment efforts, that typically comprise medication, therapy, or both, are more successful with early intervention; in fact, the likelihood of achieving full recovery decline as the illness lengthens. Social media such as Twitter and Facebook are increasingly serving an important role in crisis situations: aggregating and disseminating information, while providing opportunities for reflection and discussion of collective grief and trauma. These platforms thus provide an opportunity to investigate if post-traumatic stress and anxiety can be detected on a macro scale by studying the affective responses of crisis-inflicted populations. Due to social media's archival record, reactions to societal crisis and traumatic happenings can be tracked longitudinally. We propose to mine behavioral data from these platforms to better understand the range of responses of people to crises. By applying state-of-the-art techniques from text and social network analytics, we will go be- yond population-level estimates of crisis behavior, to gauge the social, psychological, emotional, and linguistic attributes of specific crisis-laden communities, and the relationship of these behavioral attributes to key mental and public health outcomes in a crisis context. Specifically, we will accomplish the following research aims: 1. Design data mining techniques that can intelligently filter social media posts for crisis-relevant content, incorporating statistical correction methods that can extract population representative samples. 2. Use linguistic signals and social network metadata to identify key communities in the crisis-laden population. 3. Develop behavioral measures from the activities of these communities that reflect the extent of their risk to stress disorders from the crisis situation. Ths will include measures that automatically expand and refine existing technologies to match community-specific language and dialects, which can vary dramatically in social media writing, as well as factor in the unique context of crisis events. 4. Perform a longitudinal study of the behavior of crisis-embroiled communities, identifying the factors that indicate especially high-ris groups. If successful, this research will (a) bring to the fore variables related to the exacerbaton of (or even predisposition to) PTSD, (b) enable new mechanisms to identify at-risk communities in a near real-time fashion, and (c) lend a complementary perspective on current research around trauma diagnosis, which relies typically on laboratory studies and surveys. On a practical note, a potential link between behavior manifested in social media in the context of a crisis, and anxiety and post-traumatic stress symptomatology can also augment traditional efforts in providing valuable interventions as a part of disaster response. This work is a close collaboration with computational linguist and faculty of School of Interactive Computing at Georgia Institute of Technology, Dr. Jacob Eisenstein, who is an expert in the discovery of social relationships latent in linguistic data, and Dr. James Pennebaker, a social psychologist and faculty in the Department of Psychology at the University of Texas, Austin, whose expertise is in the area of psychological interpretation of language cues.

描述（由申请人提供）：每年有数百万人经历创伤经历。虽然急性痛苦是对创伤的正常反应，但一小部分经历过创伤经历的人在创伤后很长时间内仍表现出严重的应激反应。创伤后反应可能包括侵入性记忆、过度警觉、注意力不集中、抑郁、与他人情感疏离，以及脱离生活中提供意义和自我实现的方面。在功能评估中，这些反复出现的反应严重损害了人际功能、人际功能和职业功能。尽管存在这些影响，但创伤后应激障碍的报道仍然不足，而且在许多情况下完全未被发现。寻求帮助的障碍包括：缺乏对易感症状的了解，无法获得适当的治疗/预防服务，担心精神疾病的社会耻辱，缺乏社会支持，或认为情绪变化是压倒性症状的一部分危机后生活的本质。近年来，许多危机康复工作已经认识到这些挑战，并将心理健康服务纳入其干预和支持计划。然而，治疗工作（通常包括药物、疗法或两者兼而有之）通过早期干预会更成功；事实上，随着病情的延长，完全康复的可能性会下降。 Twitter 和 Facebook 等社交媒体在危机局势中发挥着越来越重要的作用：聚合和传播信息，同时提供反思和讨论集体悲伤和创伤的机会。因此，这些平台提供了一个机会，通过研究遭受危机的人群的情感反应来调查是否可以在宏观范围内检测创伤后压力和焦虑。由于社交媒体的档案记录，可以纵向追踪对社会危机和创伤事件的反应。我们建议从这些平台挖掘行为数据，以更好地了解人们对危机的反应范围。通过应用来自文本和社交网络分析的最先进技术，我们将超越对危机行为的人口水平估计，来衡量特定危机社区的社会、心理、情感和语言属性，以及危机背景下这些行为属性与关键心理和公共卫生结果的关系。具体来说，我们将实现以下研究目标： 1. 设计数据挖掘技术，可以智能过滤社交媒体帖子中与危机相关的内容，并结合可以提取人群代表性样本的统计校正方法。 2. 使用语言信号和社交网络元数据来识别危机重重的人群中的关键社区。 3. 根据这些社区的活动制定行为衡量标准，反映他们在危机情况下遭受应激障碍的风险程度。这将包括自动扩展和完善现有技术的措施，以匹配社区特定的语言和方言，这些语言和方言在社交媒体写作中可能存在巨大差异，并考虑到危机事件的独特背景。 4. 对陷入危机的社区的行为进行纵向研究，找出表明高风险群体的因素。如果成功，这项研究将（a）突出与 PTSD 恶化（甚至倾向）相关的变量，（b）启用新机制以近乎实时的方式识别高危社区，以及（c））为当前围绕创伤诊断的研究提供了补充视角，这些研究通常依赖于实验室研究和调查。实际上，危机背景下社交媒体上表现的行为与焦虑和创伤后应激症状之间的潜在联系也可以增强传统的努力，提供有价值的干预措施作为灾难应对的一部分。这项工作是与乔治亚理工学院交互计算学院计算语言学家、发现语言数据中潜在社会关系的专家 Jacob Eisenstein 博士和社会学家 James Pennebaker 博士密切合作的结果。德克萨斯大学奥斯汀分校心理学系的心理学家和教师，其专业领域是语言线索的心理解释领域。