ArticleWorld journal of psychiatry2024
Emotional differences based on comments on doctor-patient disputes with varying levels of severity.
Article in World journal of psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- Patient influencing doctor-patient dispute trials: evidence from China.Frontiers in psychology · 2026Article
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6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe risks associated with negative doctor-patient relationships have seriously hindered the healthy development of medical and healthcare and aroused widespread concern in society. The number of public comments on doctor-patient relationship risk events reflects the degree to which the public pays attention to such events.
aimTo explore public emotional differences, the intensity of comments, and the positions represented at different levels of doctor-patient disputes.
methodsThirty incidents of doctor-patient disputes were collected from Weibo and TikTok, and 3655 related comments were extracted. The number of comment sentiment words was extracted, and the comment sentiment value was calculated. The Kruskal-Wallis
resultsThe study results showed that public comments on media reports of doctor-patient disputes at all levels are mainly dominated by "good" and "disgust" emotional states. There was a significant difference in the comment scores and the number of partial emotion words between comments on varying levels of severity of doctor-patient disputes. The comment score was positively correlated with the number of emotion words related to positive, good, and happy) and negatively correlated with the number of emotion words related to negative, anger, disgust, fear, and sadness.
conclusionThe number of emotion words related to negative, anger, disgust, fear, and sadness directly influences comment scores, and the severity of the incident level indirectly influences comment scores.
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