Association of nurse-mother partnerships with parenting stress and family resilience among South Korean mothers of children with congenital heart disease

Purpose: Advances in the management of congenital heart disease (CHD) have significantly decreased mortality rates, indicating a need for continuous care as a chronic condition throughout the child's lifespan. This study examined the association of nurse-mother partnerships with parenting stress and family resilience among South Korean mothers of children with CHD. Design and methods: This descriptive study involved 93 mothers of children aged six years or younger with CHD admitted to a hospital. Data were collected from September to November 2020 and analyzed using SPSS/WIN (version 29.0) for t-tests, analyses of variance, Pearson's correlation coefficient, and multiple regression analyses. Results: The means and standard deviations of the nurse-mother partnership, parenting stress, and family resilience were 4.13 +/- 0.47, 76.98 +/- 16.6, and 56.54 +/- 7.86 points, respectively. Parenting stress increased as the number of hospitalizations and surgeries increased and with complex types of CHD. Nurse-mother partnerships were stronger with longer hospital stays. Family resilience was higher with younger children, fewer rehospitalizations, and shorter hospital stays. A positive correlation was found between nurse-mother partnerships and family resilience, and a negative correlation between parenting stress and family resilience. Factors influencing parenting stress included family resilience, rehospitalizations, and complex types of CHD, and those affecting family resilience were nurse-mother partnerships, parenting stress, and the child's age. Conclusion: Nurse-mother partnerships significantly affect family resilience. Practical implications: Enhancing nurse-mother partnerships can improve family resilience, which in turn can reduce parenting stress, thus offering guidance for future nursing interventions. (c) 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.