Evidence map›Paper›PMID 38303971›Full record

ArticleDigital health

"No man is an island": How Chinese netizens use deliberate metaphors to provide "depression sufferers" with social support.

Youping Jing, Guiying Jiang

Open access · goldAbstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.5field-weighted citation impact, top 19% of its field
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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. Constructing RhetoricalInquiry : a journal of medical care organization, provision and financing
    Article
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

2 authors at 1 institution in 1 country.

Youping JingCollege of Foreign Languages and Cultures, Xiamen University, Xiamen, Fujian, China.ORCID https://orcid.org/0000-0002-0699-7361
Guiying JiangCollege of Foreign Languages and Cultures, Xiamen University, Xiamen, Fujian, China.
Xiamen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Online social support provides a way to positively influence depression sufferers. In the present study, we aim to analyze how social support in Chinese online depression communities is communicated through the lens of deliberate metaphor theory (DMT) to deepen the understanding of the under-researched complicated, emotionally laden, and culture-related concepts of this experience. Methods: We collected data (n = 3546 comments) from the Warm Supporting section of the Depression Super Topic, a major Chinese online depression community on Weibo. The data were analyzed using a metaphorical analysis with the Metaphor Identification Procedure Vrije Universiteit and a thematic analysis. Results: Our findings identify two themes: deliberate metaphors (DMs) of depression and DMs of social environment for depression sufferers. The former conceptualizes future expectations without depression (as Conclusions: The findings suggest that DMs as important online social support resources, helping to express empathy and normalize depression with more common-sense, and non-judgmental concepts. Additionally, in DMs, Chinese netizens navigate the intricate intersection of medical and moral perspectives on depression and its recovery, leveraging both aspects to offer comprehensive social support. "Confucian-based" elements are embedded in culture-related social support expressions in DMs. In practice, our findings contribute to tailored and appropriate health interventions for depression.

Indexed as

Chinese netizensDeliberate metaphordepressiononline social support

Identifiers

PMID38303971
PMCPMC10832413
OpenAlexW4391443841

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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 OpenQuestion graph.