Evidence map›Paper›PMID 37274271›Full record

ArticleFrontiers in oncology2023

Construction of the structural equation model of stigma, self-disclosure, social support, and quality of life of breast cancer patients after surgery-a multicenter study.

Liuxiu Bu, Xisui Chen, Shaoyan Zheng, Guanhua Fan

Abstract read
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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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

10 citing papers in PubMed.

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  6. Nurse-led support impact via a mobile app for breast cancer patients after surgery: a quasi-experimental study (step 2).Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024
    Article
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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

4 authors.

Liuxiu BuShantou University Medical College, Shantou, China.
Xisui ChenDepartment of Nursing, First Affiliated Hospital of Shantou University Medical College, Shantou, China.
Shaoyan ZhengShantou University Medical College, Shantou, China.
Guanhua FanShantou University Medical College, Shantou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Stigma is common in patients with breast cancer after surgery, which has a negative impact on the quality of life (QOL). This study aimed to investigate the QOL of breast cancer patients after surgery and to analyze the multiple chains mediating effects of self-disclosure and social support between stigma and QOL. Methods: A total 292 patients of breast cancer patients after operation were recruited in this study. A questionnaire survey was conducted using the general information questionnaire, the consumer experiences of stigma questionnaire (CESQ), the distress disclosure index(DDI), the perceived social support scale(PSSS), and the functional assessment of cancer therapy-breast(FACT-B). Path analysis was conducted to test the hypothesized serial multiple mediation model. Results: The total scores of stigma, self-disclosure, social support and QOL were 15 (10 ~ 22), 39 (31 ~ 46), 58 (50 ~ 67) and 88 (74 ~ 104) respectively. QOL of breast cancer patients after the operation was negatively correlated with stigma (p < 0.01), and positively correlated with self-disclosure and social support (p < 0.01). Self-disclosure and social support played a complete mediating effect between stigma and QOL, and the total mediating effect value was 85. 87%. Conclusions: Self-disclosure and social support play a complete intermediary role between stigma and QOL. In order to improve the quality of life of patients, medical staff should pay attention to the assessment of stigma, encourage patients to express their emotions, and encourage their families and friends to respond to their expression and needs of patients.

Indexed as

breast cancerquality of lifeself-disclosuresocial supportstigmastructural equation model

Identifiers

PMID37274271
PMCPMC10233134

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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.