Public Perspectives on Palliative and Hospice Care: Social Media Content Analysis Using Topic Modeling and Multiclass Sentiment Analysis.

IF 6 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Aeri Kim, Kyungmi Woo
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引用次数: 0

Abstract

Background: Palliative care enhances dignity and quality of life for patients with serious illnesses by managing distressing symptoms and supporting families. However, inadequate awareness and misconceptions often hinder patients and their families from accessing these services. Understanding of public perspectives on palliative and hospice care can facilitate the development of targeted educational resources and awareness campaigns. As social media becomes an important source of health information, analyzing such publicly available web-based sources can yield valuable insights into perceptions of palliative and hospice care.

Objective: This study analyzed public perspectives posted on a popular social media platform in South Korea to understand perceptions, challenges, needs, and sentiments related to palliative and hospice care.

Methods: Data were collected from Naver Knowledge iN, a popular web-based public forum in South Korea, encompassing 34,501 texts posted between 2002 and 2024. After applying inclusion and exclusion criteria, 9072 relevant perspectives were analyzed. Contextualized topic modeling was used to identify themes, and the optimal model was selected based on coherence, diversity scores, and expert feedback. In addition, multiclass sentiment analysis using a fine-tuned Korean bidirectional encoder representations from transformers (KoBERT) model classified sentiments into 6 categories. The multiclass sentiment model's performance was evaluated using accuracy, precision, recall, and F1-score.

Results: Social media discussions on palliative and hospice care have increased steadily over time. Topic modeling identified 9 themes, with "ethical and legal concerns" and "medical care in hospitals" peaking in recent years, suggesting growing public interest in these areas. "Emotional and psychological support" emerged as the predominant theme, reflecting a significant need for psychosocial assistance among patients and their families. Sentiment analysis revealed that "sadness," "anxiety," and "neutral" were common emotions across many topics. Notably, themes such as "emotional and psychological support," "disease treatment outcomes and prognosis," "medical care in hospitals," "financial issues," and "symptom management" were predominantly associated with "sadness," while "administrative and volunteer services," "ethical and legal concerns," and "nutrition management" were more closely linked with "anxiety."

Conclusions: This study highlights public concerns about palliative and hospice care in South Korea, including ethical dilemmas, caregiving burden, and emotional distress. Findings underscore the need for communication strategies that address informational, emotional, and psychological needs. Culturally sensitive, interactive communication tools, such as artificial intelligence-powered chatbots and public education campaigns, may help dispel misconceptions and promote timely, informed decisions about palliative and hospice care.

公众对缓和与安宁疗护的看法:使用主题模型与多阶层情绪分析的社交媒体内容分析。
背景:姑息治疗通过控制痛苦症状和支持家庭来提高重症患者的尊严和生活质量。然而,认识不足和误解往往阻碍患者及其家属获得这些服务。了解公众对姑息治疗和临终关怀的看法,有助于开发有针对性的教育资源和宣传活动。随着社交媒体成为健康信息的重要来源,分析这些公开的基于网络的资源可以对姑息治疗和临终关怀的看法产生有价值的见解。目的:本研究分析了在韩国一个流行的社交媒体平台上发布的公众观点,以了解与姑息治疗和临终关怀相关的认知、挑战、需求和情绪。方法:数据收集自Naver Knowledge iN,这是韩国一个流行的网络公共论坛,包括2002年至2024年间发布的34,501篇文章。应用纳入和排除标准,对9072个相关视角进行分析。采用情境化主题模型对主题进行识别,并基于连贯性、多样性评分和专家反馈选择最优模型。此外,使用经过微调的韩国双向编码器转换器表示(KoBERT)模型的多类情感分析将情感分为6类。多类情绪模型的性能评估使用准确性,精度,召回率和f1得分。结果:随着时间的推移,社交媒体上关于姑息治疗和临终关怀的讨论稳步增加。主题模型确定了9个主题,其中“道德和法律问题”和“医院医疗”近年来达到顶峰,表明公众对这些领域的兴趣日益浓厚。“情感和心理支持”成为主要主题,反映了患者及其家属对心理社会援助的巨大需求。情绪分析显示,“悲伤”、“焦虑”和“中性”是许多话题中常见的情绪。值得注意的是,诸如“情感和心理支持”、“疾病治疗结果和预后”、“医院医疗”、“财务问题”和“症状管理”等主题主要与“悲伤”相关,而“行政和志愿服务”、“道德和法律问题”和“营养管理”与“焦虑”更密切相关。结论:本研究突出了公众对韩国姑息治疗和临终关怀的关注,包括伦理困境、护理负担和情绪困扰。研究结果强调了沟通策略对信息、情感和心理需求的需求。具有文化敏感性的互动沟通工具,如人工智能驱动的聊天机器人和公共教育活动,可能有助于消除误解,促进有关姑息治疗和临终关怀的及时、明智的决定。
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来源期刊
CiteScore
14.40
自引率
5.40%
发文量
654
审稿时长
1 months
期刊介绍: The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades. As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor. Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.
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