Developing a daily life measure of depression for persons with aphasia and examining its relation with communicative confidence

失语症是一种多模态的语言障碍，通常在左脑卒中后获得。失语症（PWAs）患者中风后抑郁的发生率是一般中风人群的两倍。中风后抑郁与语言和认知能力下降以及整体生活质量下降有关。然而，由于缺乏有效的评估工具，pwa通常被排除在脑卒中后抑郁的研究之外。更重要的是，对PWAs抑郁症的研究仅使用每周回顾性测量来评估抑郁症，从而忽略了情绪的日常变化。一种评估抑郁症动态性质的创新方法是生态瞬时评估（EMA）。EMAs涉及在现实世界环境中随时间实时重复采样数据。电子信号简短，从而最大限度地减少了响应负担，通常使用超过85%的美国人拥有的移动电话收集。EMAs在生态学上是有效的，但由于其语言干扰而未在pwa中使用。本研究的目的是使用以用户为中心的设计来创建和验证失语友好型抑郁症EMA，并调查其与沟通信心的关系（N = 95）。在失语症的情况下仍有信心与人交流，这是对整体生活质量的有力预测。该研究的目的1将采用以用户为中心的设计，包括pwa、他们的照顾者和语言病理学家来设计和构建简短（~小于60秒）的EMA抑郁症测量。EMA测量的有效性将使用收敛效度方法建立，并使用已建立的pwa抑郁量表作为其验证器。目标2将使用基于智能手机的身体活动测量（即步数）来确定EMA对抑郁症评估的有效性。无论是在神经健康的个体还是中风患者中，体力活动的减少都与抑郁症有着密切的联系。目的3将研究抑郁与沟通信心之间的关系，并测试EMA测量比回顾性每周抑郁测量的增量有效性。还将建立EMA的可用性和可行性。最后，探索性目标将确定基于智能手机的身体活动与沟通信心之间的关系。拟议的职业发展奖项旨在为Ashaie博士提供培训活动，以增加他在以下方面的知识：(1)精神病理学，特别是抑郁症；(2)以用户为中心的设计；(3)EMA方法；(4)分析基于智能手机的传感器数据。培训目标将通过指导培训、正式课程、研讨会和讲习班来实现。他的跨学科指导团队由抑郁症和跨诊断研究（Shankman博士）、以用户为中心的设计（Reddy博士）、设计抑郁症评估（Griffith博士）、统计（Siddique博士）和分析被动智能手机传感器数据（Jayaraman博士）等领域的顶尖专家组成。K23将使阿沙伊博士能够提交R01，并成为美国国立卫生研究院资助的独立科学家，他在抑郁症评估方面的工作可以带来更好的抑郁症管理，并最终改善PWA的生活质量。

Aphasia is a multi-modality disturbance of language that is often acquired after a left hemisphere stroke. Post-stroke depression is two times higher in persons with aphasia (PWAs) than in the general stroke population. Post-stroke depression is associated with worse language and cognitive performance and overall decreased quality of life. However, PWAs are typically excluded from studies of post-stroke depression due to a lack of valid assessment tools. More importantly, studies of depression in PWAs only assess depression using weekly retrospective measures thus ignoring the day-to-day variability in mood. An innovative approach to assessing the dynamic nature of depression is ecological momentary assessment (EMA). EMAs involve repeated sampling of data over time in the real-time in real-world environments. EMAs are brief thus minimizing response burden and are typically collected using mobile phones which are owned by more than 85% of Americans. EMAs are ecologically valid but have not been used in PWAs due to their language disturbances. A goal of this study is to use user-centered design to create and validate an aphasia-friendly EMA of depression and investigate its association with communicative confidence (N = 95). Having the confidence to communicate despite aphasia is a robust predictor of overall quality of life. Aim 1 of the study will adapt a user-centered design by involving PWAs, their caregivers, and speech-language pathologists to design and construct brief (~less than 60s) EMA measure of depression. Validity of the EMA measure will be established using a convergent validity approach and use as its validator an established depression scale for PWAs. Aim 2 will establish the validity of the EMA assessment of depression using a smartphone-based measure of physical activity (i.e., step count). Reduced physical activity is a robust correlate of depression in both neurologically healthy individuals and those with stroke. Aim 3 will investigate the relationship between depression and communicative confidence and test the incremental validity of the EMA measure over the retrospective weekly measure of depression. Usability and feasibility of the EMA will also be established. Lastly, an exploratory aim will determine the association between smartphone-based physical activity and communicative confidence. The proposed career development award aims to provide Dr. Ashaie with training activities that will increase his knowledge of (1) psychopathology especially depression, (2) user-centered design, (3) EMA methods, and (4) analyzing smartphone-based sensor data. The training goals will be accomplished through mentored training, formal coursework, and seminars and workshops. His interdisciplinary mentorship team consists of leading experts in depression and transdiagnostic research (Dr. Shankman), user-centered design (Dr. Reddy), designing depression assessments (Dr. Griffith), statistics (Dr. Siddique), and analyzing passive smartphone-based sensor data (Dr. Jayaraman). The K23 will enable Dr. Ashaie to submit an R01 and become an NIH-funded independent scientist whose work in depression assessment can lead to better depression management and ultimately improve PWA’s quality of life.