Profiling family resilience in chronic obstructive pulmonary disease: a network analysis approach to identifying intervention targets.
9 affiliations
- 1Department of Respiratory and Critical Care Medicine, The Fourth Central Hospital Affiliated to Tianjin Medical University, Tianjin, China.
- 2Department of Ophthalmology, Peking University People's Hospital, Beijing, China.
- 3Beijing Key Laboratory of Ocular Disease and Optometry Science, Peking University People's Hospital, Beijing, China.
- 4School of Nursing, Capital Medical University, Beijing, China.
- 5Department of Nursing, Tianjin Eye Hospital, Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin Eye Institute, Clinical College of Ophthalmology, Tianjin Medical University, Tianjin, China.
- 6State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
- 7Department of Respiratory and Critical Care, Tianjin First Central Hospital, Tianjin, China.
- 8Tianjin Medical University General Hospital, Tianjin, China, Tianjin, China.
- 9School of Nursing, Tianjin Medical University, Tianjin, China.
Abstract
Aim
This study aimed to explore the status of and the factors influencing family resilience among patients with chronic obstructive pulmonary disease (COPD) and caregivers and to construct a related structural model and system of influencing factors for family resilience based on network analysis methods. Furthermore, the study aimed to identify the core variables in the network, explore the interaction mechanisms and pathways of different variables, and provide an intervention basis and direction for the improvement of resilience in COPD families.Design
The study employed a cross-sectional survey design.Methods
A total of 221 COPD patient-caregiver dyads were recruited using convenience sampling from April 2023 to November 2024 at two hospitals in Tianjin, China. SPSS 26.0 was used to perform descriptive statistics, univariate analysis, correlation analysis, and multivariate analysis. R 4.2.1 was used to construct the network of family resilience dimensions, the item network, and the network models of family resilience and its influencing factors among COPD patients and caregivers.Results
Family communication and problem-solving exhibited the highest centrality in the family resilience network, showing the strongest correlation with caregivers' ability to maintain a positive outlook. In addition, significant patient-caregiver correlations were identified in the dimensions of family communication and problem-solving. In the item network of family communication and problem-solving among COPD patients and caregivers, the node FCPS19 (We discuss problems and feel good about the solutions") exhibited the highest centrality, while the strongest correlation was observed between FCPS19 and FCPS20("We discuss things until we reach a resolution"). A statistically significant difference in the strength of the node FCPS8 ("We can ask for clarification if we do not understand each other") was observed between COPD patients and caregivers. In the network of family resilience and its influencing factors among COPD patients and caregivers, family communication and problem-solving exhibited the highest centrality. The strongest correlation was observed between the family concern of caregivers and the family communication and problem-solving of patients. A statistically significant difference in the strength of family communication and problem-solving was observed between spousal caregivers and offspring caregivers.Conclusion
Interventions focused on improving family communication and problem-solving methods can enhance family resilience among patients and caregivers, especially offspring caregivers. Both patients and caregivers prefer to discuss problems with family members to find satisfactory solutions. Compared to patients, caregivers require more explanations from family members when they do not understand something. Nurses should encourage other family members to care more for caregivers, monitor changes in family communication and problem-solving between patients and caregivers, and explore their potential connections.
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BibTeX
@article{peng2026profiling,
title = {{Profiling family resilience in chronic obstructive pulmonary disease: a network analysis approach to identifying intervention targets.}},
author = {Qiufeng Peng and Nan Zhang and Jia Liu and Zheng Tian and Yong Liu and Yimiao Li and Xi Yu and Yuan Liu and Jingchun He and Lan Wang},
journal = {Frontiers in psychology},
year = {2026},
month = oct,
doi = {10.3389/fpsyg.2026.1932841},
url = {https://europepmc.org/article/MED/42903133},
note = {CC BY},
}
RIS
TY - JOUR
TI - Profiling family resilience in chronic obstructive pulmonary disease: a network analysis approach to identifying intervention targets.
AU - Qiufeng Peng
AU - Nan Zhang
AU - Jia Liu
AU - Zheng Tian
AU - Yong Liu
AU - Yimiao Li
AU - Xi Yu
AU - Yuan Liu
AU - Jingchun He
AU - Lan Wang
PY - 2026
DA - 2026/10/06
JO - Frontiers in psychology
DO - 10.3389/fpsyg.2026.1932841
UR - https://europepmc.org/article/MED/42903133
AB - Aim This study aimed to explore the status of and the factors influencing family resilience among patients with chronic obstructive pulmonary disease (COPD) and caregivers and to construct a related structural model and system of influencing factors for family resilience based on network analysis methods. Furthermore, the study aimed to identify the core variables in the network, explore the interaction mechanisms and pathways of different variables, and provide an intervention basis and direction for the improvement of resilience in COPD families.Design The study employed a cross-sectional survey design.Methods A total of 221 COPD patient-caregiver dyads were recruited using convenience sampling from April 2023 to November 2024 at two hospitals in Tianjin, China. SPSS 26.0 was used to perform descriptive statistics, univariate analysis, correlation analysis, and multivariate analysis. R 4.2.1 was used to construct the network of family resilience dimensions, the item network, and the network models of family resilience and its influencing factors among COPD patients and caregivers.Results Family communication and problem-solving exhibited the highest centrality in the family resilience network, showing the strongest correlation with caregivers' ability to maintain a positive outlook. In addition, significant patient-caregiver correlations were identified in the dimensions of family communication and problem-solving. In the item network of family communication and problem-solving among COPD patients and caregivers, the node FCPS19 (We discuss problems and feel good about the solutions") exhibited the highest centrality, while the strongest correlation was observed between FCPS19 and FCPS20("We discuss things until we reach a resolution"). A statistically significant difference in the strength of the node FCPS8 ("We can ask for clarification if we do not understand each other") was observed between COPD patients and caregivers. In the network of family resilience and its influencing factors among COPD patients and caregivers, family communication and problem-solving exhibited the highest centrality. The strongest correlation was observed between the family concern of caregivers and the family communication and problem-solving of patients. A statistically significant difference in the strength of family communication and problem-solving was observed between spousal caregivers and offspring caregivers.Conclusion Interventions focused on improving family communication and problem-solving methods can enhance family resilience among patients and caregivers, especially offspring caregivers. Both patients and caregivers prefer to discuss problems with family members to find satisfactory solutions. Compared to patients, caregivers require more explanations from family members when they do not understand something. Nurses should encourage other family members to care more for caregivers, monitor changes in family communication and problem-solving between patients and caregivers, and explore their potential connections.
SN - 1664-1078
ER -