Nursing open · 2026
Digital Affective Resilience: A Cross-Sectional Observational Study of Anxiety-Related Chinese Social Media.
СтатьяНаблюдательное исследованиеНазвание и аннотация: Перевод в очереди
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Chen Jinji, Gong Jin, Wang Ziqin, Yang Lili, Yang Yuting, Xu Qiuyi, Zhang Shuyan, Tian Xiaoyan, Yan Lihui, Zhou Qi
Аннотация
BACKGROUND: Anxiety disorders, including phobias, are a growing public health concern, profoundly affecting quality of life. While existing research utilizes text-based and physiological data for detection, a multimodal, ecologically valid understanding of how anxiety is expressed and regulated in natural social contexts remains limited. Social media offers a unique setting for studying spontaneous emotional disclosure and collective coping mechanisms.
METHODS: A text-mining study was conducted on 28,349 social media comments related to phobia/anxiety from three Chinese platforms (XiaoHongShu, Zhihu, and Weibo) using convenience sampling of publicly available posts up to November 1, 2025. Social media comments related to phobia discussions were collected and analysed using the Dalian University of Technology Chinese Sentiment Vocabulary Ontology lexicon-based methods. Demographic variables were analysed using Independent Samples t-test and One-way ANOVA.
RESULTS: The most frequent emotion categories were happiness (31.6%) and surprise (15.3%), followed by fear (18.4%), sadness (14.7%), anger (12.1%), and disgust (7.9%). Gender differences based on complete-case analysis (n = 12,845) showed that female users expressed significantly more happiness- and sadness-related language than male users (p = 0.005 and p = 0.034, respectively). The sentiment classifier achieved moderate performance (F1 = 0.72).
CONCLUSION: The emotional discourse surrounding phobia on Chinese social media reflects co-occurring linguistic patterns of fear alongside happiness, surprise, sadness, anger, and low-frequency disgust, rather than fear amplification alone. These findings suggest that online communication may shape how anxiety-related emotions are collectively expressed and interpreted, although causal inferences cannot be drawn from cross-sectional text data.
IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: This study addressed the limited understanding of anxiety-related emotional expression on Chinese social media. The findings showed that anxiety discourse involved not only fear, but also supportive, empathetic, and coping-oriented emotions. These results may help nurses and mental health professionals better understand digital emotional communication, improve psychosocial support, and inform AI-assisted emotional monitoring and online mental health interventions.
REPORTING GUIDELINE: This study was reported in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) Statement for cross-sectional observational studies.
PATIENT OR PUBLIC CONTRIBUTION: No patients or members of the public were directly involved in the design, conduct, analysis, or manuscript preparation of this study. The research was based on secondary analysis of publicly available and anonymized social media data.
METHODS: A text-mining study was conducted on 28,349 social media comments related to phobia/anxiety from three Chinese platforms (XiaoHongShu, Zhihu, and Weibo) using convenience sampling of publicly available posts up to November 1, 2025. Social media comments related to phobia discussions were collected and analysed using the Dalian University of Technology Chinese Sentiment Vocabulary Ontology lexicon-based methods. Demographic variables were analysed using Independent Samples t-test and One-way ANOVA.
RESULTS: The most frequent emotion categories were happiness (31.6%) and surprise (15.3%), followed by fear (18.4%), sadness (14.7%), anger (12.1%), and disgust (7.9%). Gender differences based on complete-case analysis (n = 12,845) showed that female users expressed significantly more happiness- and sadness-related language than male users (p = 0.005 and p = 0.034, respectively). The sentiment classifier achieved moderate performance (F1 = 0.72).
CONCLUSION: The emotional discourse surrounding phobia on Chinese social media reflects co-occurring linguistic patterns of fear alongside happiness, surprise, sadness, anger, and low-frequency disgust, rather than fear amplification alone. These findings suggest that online communication may shape how anxiety-related emotions are collectively expressed and interpreted, although causal inferences cannot be drawn from cross-sectional text data.
IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: This study addressed the limited understanding of anxiety-related emotional expression on Chinese social media. The findings showed that anxiety discourse involved not only fear, but also supportive, empathetic, and coping-oriented emotions. These results may help nurses and mental health professionals better understand digital emotional communication, improve psychosocial support, and inform AI-assisted emotional monitoring and online mental health interventions.
REPORTING GUIDELINE: This study was reported in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) Statement for cross-sectional observational studies.
PATIENT OR PUBLIC CONTRIBUTION: No patients or members of the public were directly involved in the design, conduct, analysis, or manuscript preparation of this study. The research was based on secondary analysis of publicly available and anonymized social media data.