Linguistic markers for identifying post-traumatic stress disorder and associated symptoms: a systematic literature review.

IF 4.6 2区 医学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Robin Quillivic, Yann Auxéméry, Frédérique Gayraud, Jacques Dayan, Salma Mesmoudi
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引用次数: 0

Abstract

Objectives: Diagnosing post-traumatic stress disorder (PTSD) remains a challenge due to symptom variability and comorbidities. Linguistic analysis offers an innovative approach to identify PTSD symptoms and severity. This systematic review aimed at identifying linguistic features associated with PTSD, assessing the quality and limitations of existing studies, summarizing the predictive performance of identified models, and describing the clinical utility of these models.

Materials: A comprehensive search was conducted across multiple databases, resulting in the identification of 593 articles. After screening and eligibility assessment, 58 studies were included.

Methods: Data extraction focused on study characteristics, methodology, and performance metrics. We assessed the risk of bias using the PROBAST and conducted both a narrative synthesis and a meta-analysis.

Results: Linguistic features such as pronoun use, emotional valence, cognitive processing words, narrative length, discourse disorganization, temporal orientation, specific lexical fields (death, anxiety, sensory-perception details), and disfluencies were commonly investigated. The meta-analysis revealed a pooled area under the curve of 0.81, indicating the high performance of classification models. However, significant publication bias and heterogeneity were noted. Only 8 studies were rated with a low risk of bias, highlighting common issues such as inadequate control groups, unvalidated linguistic tools, unvalidated diagnosis tools, and low rigor in statistical analysis.

Discussion and conclusions: Linguistic markers showed potential for enhancing PTSD diagnoses, but the contemporary research was limited by methodological inconsistencies and biases. Future research should focus on standardized tools, symptom-focused studies, and interdisciplinary collaboration to improve the robustness and clinical applicability of findings.

识别创伤后应激障碍及其相关症状的语言标记:系统的文献回顾。
目的:由于症状变异性和合并症,诊断创伤后应激障碍(PTSD)仍然是一个挑战。语言分析提供了一种识别创伤后应激障碍症状和严重程度的创新方法。本系统综述旨在识别与PTSD相关的语言特征,评估现有研究的质量和局限性,总结已识别模型的预测性能,并描述这些模型的临床应用。资料:在多个数据库中进行了全面的检索,最终确定了593篇文章。经过筛选和资格评估,纳入了58项研究。方法:数据提取侧重于研究特征、方法学和绩效指标。我们使用PROBAST评估偏倚风险,并进行了叙述综合和荟萃分析。结果:语言特征如代词使用、情绪效价、认知加工词、叙述长度、话语混乱、时间取向、特定词汇场(死亡、焦虑、感觉-知觉细节)和不流畅性被普遍调查。meta分析显示,曲线下的池面积为0.81,表明分类模型的性能较高。然而,我们注意到显著的发表偏倚和异质性。只有8项研究被评为低偏倚风险,突出了常见的问题,如对照组不足、未经验证的语言工具、未经验证的诊断工具和统计分析的低严谨性。讨论与结论:语言标记显示了增强PTSD诊断的潜力,但当代研究受到方法不一致和偏见的限制。未来的研究应侧重于标准化工具、以症状为重点的研究和跨学科合作,以提高研究结果的稳健性和临床适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of the American Medical Informatics Association
Journal of the American Medical Informatics Association 医学-计算机:跨学科应用
CiteScore
14.50
自引率
7.80%
发文量
230
审稿时长
3-8 weeks
期刊介绍: JAMIA is AMIA''s premier peer-reviewed journal for biomedical and health informatics. Covering the full spectrum of activities in the field, JAMIA includes informatics articles in the areas of clinical care, clinical research, translational science, implementation science, imaging, education, consumer health, public health, and policy. JAMIA''s articles describe innovative informatics research and systems that help to advance biomedical science and to promote health. Case reports, perspectives and reviews also help readers stay connected with the most important informatics developments in implementation, policy and education.
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