Evidence map›Paper›PMID 41063107›Full record

ArticleBMC nursing2025

Primary caregiver-reported family resilience in children with cancer in central China: a latent profile analysis.

Bowen Li, Dan Shu, Shiguang Pang, Li Wang, Lixiu Wang, Xuelin Yin, Jingtian Xing, Huijing Zou, Bing Xiang Yang, Qian Liu

Abstract read
In one paragraph

Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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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

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

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4 · The record

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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.

Bowen Li *Center for Wise Information Technology of Mental Health Nursing Research, School of Nursing, Wuhan University, Wuhan, Hubei province, 430071, China.
Dan Shu *Center for Wise Information Technology of Mental Health Nursing Research, School of Nursing, Wuhan University, Wuhan, Hubei province, 430071, China.
Shiguang Pang *Center for Wise Information Technology of Mental Health Nursing Research, School of Nursing, Wuhan University, Wuhan, Hubei province, 430071, China.
Li WangCenter for Wise Information Technology of Mental Health Nursing Research, School of Nursing, Wuhan University, Wuhan, Hubei province, 430071, China.
Lixiu WangCenter for Wise Information Technology of Mental Health Nursing Research, School of Nursing, Wuhan University, Wuhan, Hubei province, 430071, China.
Xuelin YinSchool of Nursing, Wuhan University, Wuhan, Hubei Province, 430071, China.
Jingtian XingSchool of Public Health, Wuhan University, Wuhan, Hubei Province, 430071, China.
Huijing ZouCenter for Wise Information Technology of Mental Health Nursing Research, School of Nursing, Wuhan University, Wuhan, Hubei province, 430071, China.
Bing Xiang YangCenter for Wise Information Technology of Mental Health Nursing Research, School of Nursing, Wuhan University, Wuhan, Hubei province, 430071, China.
Qian LiuCenter for Wise Information Technology of Mental Health Nursing Research, School of Nursing, Wuhan University, Wuhan, Hubei province, 430071, China. hopeliuqian@whu.edu.cn.

Funding

the National Natural Science Foundation of China No. 82103025
6 · The paper itself

Abstract

backgroundChildhood cancer can disrupt family functioning, increase caregiver psychological distress, and impair caregiver quality of life. While family resilience is crucial for adaptation, most research has focused on individual-level factors, neglecting heterogeneity and multilevel influences on family resilience.

methodsGuided by the Social Ecological Model (SEM), this cross-sectional observational study used latent profile analysis (LPA) to identify distinct profiles of family resilience among caregivers of children with cancer and to explore factors associated with these profiles. Between July 2022 and March 2024, 292 caregivers were recruited. Family resilience was measured using the Family Resilience Assessment Scale. LPA was employed to identify resilience profiles, and binary logistic regression was used to explore influencing factors.

resultsTwo latent profiles were identified: the Low Resources-Low Positivity profile (86%) and the High Internal Resilience profile (14%). The Low Resource-Low Positivity profile demonstrated generally lower scores, especially in utilizing social and economic resources and maintaining a positive outlook. The High Internal Resilience profile showed higher scores across all family resilience dimensions, particularly in communication/problem solving, positive outlook, and meaning-making, while the use of external social and economic resources remained relatively lower. Univariate analysis showed significant differences between profiles in residence, number of siblings, caregiver education, individual resilience, social support, caregivers' physical and psychological well-being and child communication (caregiver-reported). Binary logistic regression identified having more than one child (OR = 3.184, 95% CI: 1.437 ~ 7.057, P = 0.004) and higher individual resilience (OR = 1.095, 95% CI: 1.028 ~ 1.165, P = 0.005) as significant predictors of High Internal Resilience profile.

conclusionThis study identified two distinct family resilience profiles among caregivers of children with cancer. Limited use of social and economic resources was common, while caregiver resilience and having multiple children predicted higher family resilience. Interventions should enhance caregiver coping capacity, support one-child families through peer and family programs, and improve access to social support, flexible employment, and affordable care to strengthen family resilience. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Family caregiversFamily resilienceLatent profile analysisPediatric cancerSocial ecological model

Identifiers

PMID41063107
PMCPMC12505539

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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.