Evidence map›Paper›PMID 42434844›Full record

Observational studyNursing open2026

Digital Affective Resilience: A Cross-Sectional Observational Study of Anxiety-Related Chinese Social Media.

Jinji Chen, Jin Gong, Ziqin Wang, Lili Yang, Yuting Yang, Qiuyi Xu, Shuyan Zhang, Xiaoyan Tian, Lihui Yan, Qi Zhou

Abstract readObservational Study
In one paragraph

Observational study in Nursing open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Jinji ChenHangzhou Linping District Integrated Traditional Chinese and Western Medicine Hospital, Hangzhou, China.ORCID https://orcid.org/0009-0005-5939-2277
Jin GongHangzhou Linping District Integrated Traditional Chinese and Western Medicine Hospital, Hangzhou, China.ORCID https://orcid.org/0009-0000-6813-3350
Ziqin WangHangzhou Linping District Integrated Traditional Chinese and Western Medicine Hospital, Hangzhou, China.ORCID https://orcid.org/0009-0001-6733-182X
Lili YangSchool of Medicine, Sir Run Run Shaw Hospital of Zhejiang University, Hangzhou, China.ORCID https://orcid.org/0000-0002-4587-1438
Yuting YangSchool of Medicine, Sir Run Run Shaw Hospital of Zhejiang University, Hangzhou, China.ORCID https://orcid.org/0000-0002-9367-9942
Qiuyi XuZhejiang Shuren University Shulan International Medical College, Hangzhou, China.ORCID https://orcid.org/0009-0002-0789-5727
Shuyan ZhangThe Second Clinical College, Zhejiang Chinese Medical University, Hangzhou, China.ORCID https://orcid.org/0009-0005-7886-1083
Xiaoyan TianHangzhou Linping District Integrated Traditional Chinese and Western Medicine Hospital, Hangzhou, China.ORCID https://orcid.org/0009-0006-0875-2217
Lihui YanNursing Department, Hangzhou Linping District Integrated Traditional Chinese and Western Medicine Hospital, Hangzhou, Zhejiang, China.ORCID https://orcid.org/0009-0001-3476-4688
Qi ZhouHangzhou Linping District Integrated Traditional Chinese and Western Medicine Hospital, Hangzhou, China.ORCID https://orcid.org/0009-0009-1641-6522

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAnxiety 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.

methodsA 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.

resultsThe 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).

conclusionThe 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.

Indexed as

AnxietyResilience, PsychologicalSocial MediaAdultChinaCross-Sectional StudiesData MiningDigital MediaEmotionsFemaleHumansMaleMedia ExposurePhobic Disordersanxietyemotionshealthmediaqualitative study

Identifiers

PMID42434844
PMCPMC13355286

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.