Web-Based Graphic Representation of the Life Course of Mental Health: Cross-Sectional Study Across the Spectrum of Mood, Anxiety, Eating, and Substance Use Disorders
Web-Based Graphic Representation of the Life Course of Mental Health: Cross-Sectional Study Across the Spectrum of Mood, Anxiety, Eating, and Substance Use Disorders
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DOI：
10.2196/16919
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发表时间：
2020-01-28
影响因子：
5.2
通讯作者：
Khalsa, Sahib S.
中科院分区：
文献类型：
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作者：
Aupperle, Robin Leora;Paulus, Martin P.;Khalsa, Sahib S.
背景：尽管患者病史对于精神健康评估、诊断和预后至关重要，但缺乏衡量与精神障碍相关的时间依赖因素的标准化工具。先前的研究已证明被称为生命图表的图形表示法在描绘精神疾病病程复杂性方面的潜在用途。然而，这些评估的实施受到以下因素的限制：仅专注于特定的精神疾病（如双相情感障碍）以及缺乏用于数据收集和可视化的直观图形界面。
目的：本研究旨在开发和测试塔尔萨生命图表（TLC）作为一种基于网络的结构化方法的实用性，用于获取并以图形方式表示与一系列精神障碍相关的心理社会和精神健康事件的历史信息。
方法：塔尔萨1000研究中的499名参与者在基线时完成了TLC访谈，塔尔萨1000是一项针对患有抑郁、焦虑、物质使用或进食障碍的个体以及健康对照者（HCs）的纵向研究。所有数据均以电子方式输入，并使用谷歌可视化应用程序编程接口开发了一个单页的电子交互式图形表示。对于8个不同的生命阶段（每个阶段约5 - 10年），TLC评估了以下因素：上学情况、爱好、工作、社会支持、物质使用、精神健康治疗、家庭结构变化、负面和正面事件，以及与阶段和事件相关的情绪评分。我们使用广义线性混合模型（GLMMs）来评估每个领域随时间以及按性别、年龄和诊断的变化轨迹，并使用案例和基于网络的交互式图表来可视化数据。
结果：GLMM分析揭示了所有领域的阶段和诊断的主效应或交互效应。在情绪评分以及负面事件与正面事件数量方面发现了阶段与诊断的交互作用（所有P值（P <.05））。（最后一个括号里的内容似乎不完整，可能影响对整体结果的准确理解）
Background: Although patient history is essential for informing mental health assessment, diagnosis, and prognosis, there is a dearth of standardized instruments measuring time-dependent factors relevant to psychiatric disorders. Previous research has demonstrated the potential utility of graphical representations, termed life charts, for depicting the complexity of the course of mental illness. However, the implementation of these assessments is limited by the exclusive focus on specific mental illnesses (ie, bipolar disorder) and the lack of intuitive graphical interfaces for data collection and visualization.Objective: This study aimed to develop and test the utility of the Tulsa Life Chart (TLC) as a Web-based, structured approach for obtaining and graphically representing historical information on psychosocial and mental health events relevant across a spectrum of psychiatric disorders.Methods: The TLC interview was completed at baseline by 499 participants of the Tulsa 1000, a longitudinal study of individuals with depressive, anxiety, substance use, or eating disorders and healthy comparisons (HCs). All data were entered electronically, and a 1-page electronic and interactive graphical representation was developed using the Google Visualization Application Programming Interface. For 8 distinct life epochs (periods of approximately 5-10 years), the TLC assessed the following factors: school attendance, hobbies, jobs, social support, substance use, mental health treatment, family structure changes, negative and positive events, and epoch and event-related mood ratings. We used generalized linear mixed models (GLMMs) to evaluate trajectories of each domain over time and by sex, age, and diagnosis, using case examples and Web-based interactive graphs to visualize data.Results: GLMM analyses revealed main or interaction effects of epoch and diagnosis for all domains Epoch by diagnosis interactions were identified for mood ratings and the number of negative-versus-positive events (all P values (P