Ettlin Dominik A, Wolf Markus, Biller-Andorno Nikola, Schneider Gerold
Digital Society Initiative (DSI), University of Zurich, Zurich, Switzerland.
Department of Reconstructive Dentistry and Gerodontology, School of Dental Medicine, University of Bern, Bern, Switzerland.
J Headache Pain. 2025 Jul 30;26(1):172. doi: 10.1186/s10194-025-02095-z.
Provision of value-based, patient-centered care requires careful appraisal of patients’ symptoms. Understanding subjective experiences, needs, and feelings is crucial for shared decision-making, especially when clinical findings differ from individual perceptions. Natural language processing (NLP) offers new ways to understand patients’ perspectives. This exploratory pilot study aimed to exemplify the use of three popular NLP methods to analyze open-ended textual self-reports from individuals experiencing orofacial pain and dysfunction for a more comprehensive understanding of their subjective symptom burdens.
This study used topic modeling, conceptual maps, and lexicon-based linguistic style analysis to analyze texts from 2,237 patients experiencing orofacial pain and/or dysfunction, who provided brief written descriptions of their chief complaints, functional limitations, and expectations.
From the aggregated text corpus of 111,923 words, unsupervised topic modeling identified 10 meaningful topics by clustering words related to prevalent complaints, constraints, and co-morbidities like tinnitus and insomnia, highlighting patients’ hopes for understanding causes and receiving a clear diagnosis. Conceptual maps of the 200 most frequent words or expressions revealed occupational limitations as significant constraints and highlighted the patients’ need for understanding causes and diagnoses. Linguistic style analyses were used to enrich the map, revealing negative emotional associations with chief complaints and the patients’ struggle to reduce uncertainty and understand their illness.
The results revealed distinct language patterns in open-ended orofacial pain reports. Chief complaints were associated with terms linked to anatomical locations and temporal patterns, functional limitations with impaired masticatory function, work-related activities and sleep disturbances, and expectations with an improved understanding of symptoms. Adding linguistic categories allowed for the validation of unsupervised methods and offered a nuanced approach to evaluate symptom burdens. NLP methods complement traditional information collection by capturing patients’ views, which are crucial for healthcare practice and shared decision-making within a biopsychosocial framework. When integrated into clinical workflows, NLP technologies might be a promising way of enhancing comprehensive symptom appraisal, benefiting both patients and clinicians alike.
The online version contains supplementary material available at 10.1186/s10194-025-02095-z.
提供基于价值的、以患者为中心的护理需要仔细评估患者的症状。理解主观体验、需求和感受对于共同决策至关重要，尤其是当临床发现与个体认知不同时。自然语言处理（NLP）为理解患者观点提供了新方法。这项探索性试点研究旨在举例说明使用三种流行的NLP方法来分析经历口面部疼痛和功能障碍的个体的开放式文本自我报告，以更全面地了解他们的主观症状负担。
本研究使用主题建模、概念图和基于词典的语言风格分析来分析来自2237名经历口面部疼痛和/或功能障碍的患者的文本，这些患者提供了关于他们主要症状、功能限制和期望的简短书面描述。
从总计111923个单词的文本语料库中，无监督主题建模通过对与常见症状、限制以及耳鸣和失眠等共病相关的单词进行聚类，识别出10个有意义的主题，突出了患者对了解病因和获得明确诊断的希望。对200个最常见的单词或表达的概念图显示职业限制是重要的限制因素，并突出了患者对了解病因和诊断的需求。语言风格分析用于丰富该图，揭示了与主要症状的负面情绪关联以及患者在减少不确定性和理解自身疾病方面的挣扎。
结果揭示了开放式口面部疼痛报告中不同的语言模式。主要症状与与解剖位置和时间模式相关的术语有关，功能限制与咀嚼功能受损、与工作相关的活动和睡眠障碍有关，期望与对症状的更好理解有关。添加语言类别有助于验证无监督方法，并提供了一种细致入微的方法来评估症状负担。NLP方法通过捕捉患者的观点来补充传统信息收集，这对于医疗保健实践和生物心理社会框架内的共同决策至关重要。当集成到临床工作流程中时，NLP技术可能是增强全面症状评估的一种有前途的方法，使患者和临床医生都受益。
在线版本包含可在10.1186/s10194-025-02095-z获取的补充材料。
