Background: Head and neck cancers (H&NCs) constitute a significant part of all cancer cases. H&NC patients experience unintentional weight loss, poor nutritional status, or speech disorders. Medical interventions affect appearance and interfere with patients’ self-perception of their bodies. Psychological consultations are not affordable due to limited time. Methods: We used NLP to analyze the basic emotion intensity, sentiment about one’s body, characteristic vocabulary, and potential areas of difficulty in free notes. The emotion intensity research uses the extended NAWL dictionary developed using word embedding. The sentiment analysis used a hybrid approach: a sentiment dictionary and a deep recursive network. The part-of-speech tagging and domain rules defined by a psycho-oncologist determine the distinct language traits. Potential areas of difficulty were analyzed using the dictionaries method with word polarity to define a given area and the presentation of a note using bag-of-words. Here, we applied the LSA method using SVD to reduce dimensionality. A total of 50 cancer patients requiring enteral nutrition participated in the study. Results: The results confirmed the complexity of emotions in patients with H&NC in relation to their body image. A negative attitude towards body image was detected in most of the patients. The method presented in the study appeared to be effective in assessing body image perception disturbances, but it cannot be used as the sole indicator of body image perception issues. Limitations: The main problem in the research was the fairly wide age range of participants, which explains the potential diversity of vocabulary. Conclusions: The combination of the attributes of a patient’s condition, possible to determine using the method for a specific patient, can indicate the direction of support for the patient, relatives, direct medical personnel, and psycho-oncologists.
背景：头颈部癌症在所有癌症病例中占有重要比例。头颈癌患者常出现非自愿性体重减轻、营养状况不佳或言语障碍。医疗干预会影响患者外貌，并干扰其身体自我认知。由于时间有限，心理咨询往往难以实现。方法：本研究采用自然语言处理技术，分析自由笔记中的基本情绪强度、身体意象情感倾向、特征性词汇及潜在困难领域。情绪强度分析采用基于词嵌入技术扩展的NAWL词典；情感分析采用混合方法：结合情感词典与深度递归网络；词性标注及心理肿瘤学家定义的领域规则用于确定独特的语言特征；潜在困难领域分析采用词典法，通过词汇极性界定特定领域，并运用词袋模型呈现笔记内容，此处应用潜在语义分析中的奇异值分解法进行降维处理。研究共纳入50名需要肠内营养的癌症患者。结果：研究结果证实头颈癌患者身体意象相关情绪的复杂性，多数患者表现出对身体意象的消极态度。本研究提出的方法在评估身体意象感知障碍方面显示有效性，但不能作为身体意象感知问题的唯一指标。局限性：研究主要问题在于参与者年龄跨度较大，这解释了词汇使用的潜在多样性。结论：结合患者病况特征（可通过本方法针对特定患者确定），能为患者、家属、直接医疗人员及心理肿瘤学家指明支持方向。
肿瘤(癌症)患者之家