Aupperle Robin Leora, Paulus Martin P, Kuplicki Rayus, Touthang James, Victor Teresa, Yeh Hung-Wen, Khalsa Sahib S
Laureate Institute for Brain Research, Tulsa, OK, United States.
Oxley College of Health Sciences, The University of Tulsa, Tulsa, OK, United States.
JMIR Ment Health. 2020 Jan 28;7(1):e16919. doi: 10.2196/16919.
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.
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.
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.
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 <.001), with all psychiatric groups reporting worse mood and greater negative-versus-positive events than HCs. These differences were most robust at different epochs, depending on diagnosis. There were also diagnosis and epoch main effects for substance use, mental health treatment received, social support, and hobbies (P<.001). User experience ratings (each on a 1-5 scale) revealed that participants found the TLC pleasant to complete (mean 3.07, SD 1.26) and useful for understanding their mental health (mean 3.07, SD 1.26), and that they were likely to recommend it to others (mean 3.42, SD 0.85).
The TLC provides a structured, Web-based transdiagnostic assessment of psychosocial history relevant for the diagnosis and treatment of psychiatric disorders. Interactive, 1-page graphical representations of the TLC allow for the efficient communication of historical life information that would be useful for clinicians, patients, and family members.
尽管患者病史对于心理健康评估、诊断和预后至关重要,但缺乏标准化工具来衡量与精神障碍相关的时间依赖性因素。先前的研究表明,一种称为生活图表的图形表示法在描绘精神疾病病程的复杂性方面具有潜在用途。然而,这些评估的实施受到仅关注特定精神疾病(即双相情感障碍)以及缺乏用于数据收集和可视化的直观图形界面的限制。
本研究旨在开发并测试塔尔萨生活图表(TLC)作为一种基于网络的结构化方法的实用性,以获取并以图形方式呈现与一系列精神障碍相关的心理社会和心理健康事件的历史信息。
TLC访谈在基线时由塔尔萨1000研究的499名参与者完成,该研究是一项针对患有抑郁、焦虑、物质使用或饮食失调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录入,并使用谷歌可视化应用程序编程接口开发了一份1页的电子交互式图形表示。对于8个不同的生活时期(约5 - 10年的时间段),TLC评估了以下因素:上学情况、爱好、工作、社会支持、物质使用、心理健康治疗、家庭结构变化、负面和正面事件以及与时期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、年龄和诊断的轨迹,并使用案例示例和基于网络的交互式图表来可视化数据。
GLMM分析揭示了所有领域中时期和诊断的主要或交互作用。在情绪评分以及负面与正面事件数量方面发现了时期与诊断的交互作用(所有P值<.001),所有精神疾病组报告的情绪比HCs更差,负面与正面事件更多。这些差异在不同时期最为明显,具体取决于诊断。在物质使用、接受的心理健康治疗、社会支持和爱好方面也存在诊断和时期的主要影响(P<.001)。用户体验评分(每项评分为1 - 5分)显示,参与者发现完成TLC很愉快(平均3.07,标准差1.26),并且对理解自己的心理健康很有用(平均3.07,标准差1.26),而且他们很可能会向他人推荐它(平均3.42,标准差0.85)。
TLC提供了一种结构化的、基于网络的跨诊断心理社会病史评估,与精神障碍的诊断和治疗相关。TLC的交互式1页图形表示能够有效地传达历史生活信息,这对临床医生、患者和家庭成员都很有用。