Vizer Lisa, Pierce Jennifer, Ji Yinyao, Bucher Meredith A, Liu Mochuan, Ungar Lyle, Giorgi Salvatore, Xing Zhaopeng, House Stacey L, Beaudoin Francesca L, Stevens Jennifer S, Neylan Thomas C, Clifford Gari D, Jovanovic Tanja, Linnstaedt Sarah D, Zeng Donglin, Germine Laura T, Bollen Kenneth A, Rauch Scott L, Haran John P, Storrow Alan B, Lewandowski Christopher, Musey Paul I, Hendry Phyllis L, Sheikh Sophia, Jones Christopher W, Punches Brittany E, Hudak Lauren A, Pascual Jose L, Seamon Mark J, Harris Erica, Pearson Claire, Peak David A, Merchant Roland C, Domeier Robert M, O'Neil Brian J, Sergot Paulina, Sanchez Leon D, Bruce Steven E, Harte Steven E, Kessler Ronald C, Koenen Karestan C, McLean Samuel A, An Xinming
Department of Medicine, Division of General Medicine and Clinical Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27559 USA.
Department of Anesthesiology, University of Michigan, Ann Arbor, MI 48109 USA.
NPP Digit Psychiatry Neurosci. 2025;3(1):8. doi: 10.1038/s44277-025-00028-x. Epub 2025 May 20.
Language features may reflect underlying cognitive and emotional processes following a traumatic event that portend clinical outcomes. The authors sought to determine whether language features from usual smartphone use were markers associated with concurrent posttraumatic symptoms and worsening or improving posttraumatic symptoms over time following a traumatic exposure. This investigation was a secondary analysis of the Advancing Understanding of RecOvery afteR traumA study, a longitudinal study of traumatic outcomes among survivors recruited from 33 emergency departments across the United States. Adverse posttraumatic sequelae were assessed over the six months following the initial traumatic exposure. Language features were extracted from usual smartphone use in a specialized app. Bivariate linear mixed models were used to identify and validate language features that are markers associated with posttraumatic symptoms. Participants were 1744 trauma survivors, with a mean age of 39 [SD = 13] years old, and 56% were female. Fourteen language features were associated with severity level of posttraumatic symptoms at specific timepoints (cross-sectional markers) and five features were associated with change in severity level of posttraumatic symptoms (longitudinal markers). References to the body and health or illness were predictive of worsening pain, somatic, and thinking/concentration/fatigue symptom severity over time. An increase in references to others was associated with improvement in somatic symptom severity over time and increases in expressions of causation or cognitive processes were associated with improvement in pain symptom severity over time. Language features derived from usual smartphone use can convey important information about health, functioning, and recovery following a traumatic event. Clinicians might utilize such information to determine who may experience a high symptom burden or risk of worsening posttraumatic symptoms.
语言特征可能反映创伤事件后潜在的认知和情感过程，而这些过程预示着临床结果。作者试图确定日常智能手机使用中的语言特征是否是与创伤后症状并发以及创伤暴露后随着时间推移创伤后症状恶化或改善相关的标志物。这项调查是对“创伤后恢复的深入理解”研究的二次分析，该研究是一项纵向研究，研究对象是从美国33个急诊科招募的创伤幸存者的创伤结局。在首次创伤暴露后的六个月内评估创伤后不良后遗症。语言特征是从一个专门应用程序中日常智能手机使用情况中提取的。使用双变量线性混合模型来识别和验证作为创伤后症状标志物的语言特征。参与者为1744名创伤幸存者，平均年龄39岁[标准差=13]，56%为女性。14种语言特征与特定时间点创伤后症状的严重程度相关（横断面标志物），5种特征与创伤后症状严重程度的变化相关（纵向标志物）。对身体以及健康或疾病的提及预示着随着时间推移疼痛、躯体症状以及思维/注意力/疲劳症状严重程度会加重。对他人提及的增加与随着时间推移躯体症状严重程度的改善相关，因果关系或认知过程表达的增加与随着时间推移疼痛症状严重程度的改善相关。日常智能手机使用产生的语言特征可以传达有关创伤事件后健康、功能和恢复的重要信息。临床医生可以利用这些信息来确定谁可能经历高症状负担或创伤后症状恶化的风险。
