Evidence map›Paper›PMID 41491948›Full record

ArticleBMC public health2026

Family resilience and its related factors among parents of children with congenital heart disease in China: a latent profile analysis.

Jingran Yang, Fang Ma, Yu Wang, Qinglan Li, Ruijie YangLan, Min Zhou, Yimei Zhang, Yangjuan Bai, Qiulan Hu, Wei Wei

Abstract read
In one paragraph

Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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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

2 citing papers in PubMed.

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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

10 authors.

Jingran YangDepartment of Nursing, The First Affiliated Hospital of Kunming Medical University, 295 Xichang Road, Wuhua District, Kunming, 650032, China.
Fang MaDepartment of Nursing, The First Affiliated Hospital of Kunming Medical University, 295 Xichang Road, Wuhua District, Kunming, 650032, China. rebeccamalei@126.com.
Yu WangDepartment of Nursing, The First Affiliated Hospital of Kunming Medical University, 295 Xichang Road, Wuhua District, Kunming, 650032, China.
Qinglan LiDepartment of Nursing, The First Affiliated Hospital of Kunming Medical University, 295 Xichang Road, Wuhua District, Kunming, 650032, China.
Ruijie YangLanDepartment of Nursing, The First Affiliated Hospital of Kunming Medical University, 295 Xichang Road, Wuhua District, Kunming, 650032, China.
Min ZhouDepartment of Nursing, The First Affiliated Hospital of Kunming Medical University, 295 Xichang Road, Wuhua District, Kunming, 650032, China.
Yimei ZhangDepartment of Nursing, The First Affiliated Hospital of Kunming Medical University, 295 Xichang Road, Wuhua District, Kunming, 650032, China.
Yangjuan BaiCardiology Department, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Qiulan HuIntensive Care Unit in Geriatric Department, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Wei WeiDigestive Surgery Department, The First Affiliated Hospital of Kunming Medical University, Kunming, China.

Funding

the Medical High-Level Talent Training Program of Yunnan Provincial Health Commission L-2024013the National Natural Science Foundation of China 72364022
6 · The paper itself

Abstract

backgroundParents of children with congenital heart disease (CHD) face chronic stress impairing family functioning and well-being. As a key protective factor, family resilience aids their adaptation. However, existing research predominantly measures general family resilience, neglecting heterogeneous resilience patterns and subgroup profiles. Our study uses person-centered Latent Profile Analysis (LPA) to identify latent family resilience classes in Chinese culture to provide tailored support.

methodsThis study adopted a cross-sectional survey design. From October 2024 to July 2025, convenience sampling was used to recruit 426 eligible parents of children with CHD from two tertiary hospitals in Yunnan Province, China. Data were collected using the General Information Questionnaire, Family Hardiness Index (FHI), Simplified Coping Style Questionnaire (SCSQ), and Social Support Rating Scale (SSRS). LPA was applied to classify the family resilience levels of these parents. Subsequently, univariate and multivariate ordinal logistic regression analyses were conducted to explore the factors associated with different latent classes of family resilience.

resultsA total of 400 valid questionnaires were collected, with an effective response rate of 93.9%. The mean total score for family resilience in parents of children with CHD was 58.13 ± 5.79, suggesting a moderate overall level of family resilience in this group. The family resilience of parents of children with CHD was classified into three latent profiles: “High family resilience responsibility-anchored type” (N = 51), “Low family resilience challenge-vulnerable type” (N = 25), and “Moderate family resilience balanced-stable type” (N = 324). Univariate analysis identified significant differences (all P < 0.05) in the following factors: the number of the child’s cardiac diagnoses, place of residence, parental education, coping styles, family monthly income, and social support. Logistic regression revealed that coping styles, family monthly income, and social support were predictors of family resilience latent classes in CHD children’s parents.

conclusionsParents of children with CHD demonstrate heterogeneity in family resilience. Healthcare professionals should pay attention to the family resilience differences among parents of children with CHD and implement targeted intervention measures based on the characteristics of different subgroups, thereby enhancing parents’ family resilience and further promoting family well-being.

Indexed as

Heart Defects, CongenitalParentsResilience, PsychologicalAdaptation, PsychologicalAdultChildChild, PreschoolChinaCoping SkillsCross-Sectional StudiesFemaleHumansLatent Class AnalysisMaleSocial SupportSurveys and QuestionnairesCongenital heart diseaseFamily resilienceLatent profile analysisParentsRelated factors

Identifiers

PMID41491948
PMCPMC12870328

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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.