Evidence map›Paper›PMID 40438684›Full record

ArticleFrontiers in oncology2025

Hematological cancer patients' social support, coping strategies, anxiety, depression and posttraumatic growth: a structural equation model.

Taoyun Liang, Ling Mao, Xinwen Du, Fengjiao Chen

Abstract read
In one paragraph

Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

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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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Self-management engagement in adults with hematologic cancers: a meta-synthesis of qualitative studies.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Pooled it
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Taoyun LiangWest China Hospital, Sichuan University, Chengdu, China.
Ling MaoWest China Hospital, Sichuan University, Chengdu, China.
Xinwen DuWest China Hospital, Sichuan University, Chengdu, China.
Fengjiao ChenWest China Hospital, Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Posttraumatic growth (PTG), defined as positive psychological changes following traumatic events, has been observed in some hematological cancer patients during their disease course. These changes, encompassing shifts in life perspective, interpersonal relationships, and self-perception, are critical for psychological recovery. However, the interplay of social support, coping strategies, anxiety, and depression in shaping PTG remains unclear. Therefore, the aim of this study was to explore these associations in hematological cancer patients using a hypothetical model. Methods: From August 2019 to May 2021, a cross-sectional survey was conducted with 474 hospitalized patients with hematological cancer at West China Hospital, Sichuan University, China (a tertiary hospital). The Social Support Rating Scale, Medical Coping Modes Questionnaire, Hospital Anxiety and Depression Scale, and Posttraumatic Growth Inventory were used for data collection. Correlation and regression analyses were performed using SPSS 26.0, a structural equation model was constructed using AMOS 24.0 software, and the confidence interval of the mediating effect was calculated using the bias-corrected bootstrap method. Results: Social support was positively associated with PTG in hematological cancer patients ( Conclusion: These findings provide a basis for further research on PTG in cancer patients, particularly with respect to coping strategies in various dimensions. Enhancing social support and addressing maladaptive coping may promote PTG. Tailored interventions targeting depression management and culturally sensitive support systems are recommended to enhance PTG.

Indexed as

anxietycoping skillsdepressionhematologic neoplasmsposttraumatic growthsocial support

Identifiers

PMID40438684
PMCPMC12116656

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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.