{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T11:59:03Z","timestamp":1785239943905,"version":"3.55.0"},"reference-count":56,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T00:00:00Z","timestamp":1783728000000},"content-version":"vor","delay-in-days":10,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Nursing Open"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Anxiety disorders, including phobias, are a growing public health concern, profoundly affecting quality of life. While existing research utilizes text\u2010based 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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A text\u2010mining 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\u2010based methods. Demographic variables were analysed using Independent Samples t\u2010test and One\u2010way ANOVA.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      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\u2010case analysis (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200912,845) showed that female users expressed significantly more happiness\u2010 and sadness\u2010related language than male users (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.005 and\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.034, respectively). The sentiment classifier achieved moderate performance (F1\u2009=\u20090.72).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The emotional discourse surrounding phobia on Chinese social media reflects co\u2010occurring linguistic patterns of fear alongside happiness, surprise, sadness, anger, and low\u2010frequency disgust, rather than fear amplification alone. These findings suggest that online communication may shape how anxiety\u2010related emotions are collectively expressed and interpreted, although causal inferences cannot be drawn from cross\u2010sectional text data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Implications for the Profession and\/or Patient Care<\/jats:title>\n                    <jats:p>This study addressed the limited understanding of anxiety\u2010related emotional expression on Chinese social media. The findings showed that anxiety discourse involved not only fear, but also supportive, empathetic, and coping\u2010oriented emotions. These results may help nurses and mental health professionals better understand digital emotional communication, improve psychosocial support, and inform AI\u2010assisted emotional monitoring and online mental health interventions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Reporting Guideline<\/jats:title>\n                    <jats:p>This study was reported in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) Statement for cross\u2010sectional observational studies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Patient or Public Contribution<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/nop2.70691","type":"journal-article","created":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T10:12:22Z","timestamp":1783764742000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Digital Affective Resilience: A Cross\u2010Sectional Observational Study of Anxiety\u2010Related Chinese Social Media"],"prefix":"10.1002","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-5939-2277","authenticated-orcid":false,"given":"Jinji","family":"Chen","sequence":"first","affiliation":[{"name":"Hangzhou Linping District Integrated Traditional Chinese and Western Medicine Hospital  Hangzhou 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