Developmental trajectory of family resilience and its predictors in preterm infants discharged from NICU based on growth mixed model:A longitudinal study
Objective To explore the developmental trajectory categories and predictors of family resilience(FRAS)in preterm infants discharged from the NICU and to provide a reference basis for developing subsequent precision nursing intervention programs.Methods A total of 161 preterm infants were admitted to the NICU of The First Maternity and Infant Hospital of Tongji University,and the primary caregivers of the parents of the preterm infants who had been cured and dis-charged from November 2022 to August 2023 were selected as the study subjects,and the FRAS levels of the preterm infants were measured at four-time nodes,namely,one week after discharge from the NICU(T0),at corrected one-month-old(T1),at corrected three-month-old(T2)and corrected six-month-old(T3),and the levels of FRAS were analyzed by the GMM(Growth Mixed Model).GMM to identify potential trajectory categories and analyze their predictors using multivariate Logistic re-gression.Results A total of three NICU discharge preterm infant FRAS trajectories were identified in this study,namely,the"high family resilience stabilization group"(6.2％),"moderate family resilience increase group"(6.8％),and"low family resilience persistence group"(87.0％).Logistic regression showed that parenting competence,social support,and family caring were predictors of FRAS developmental trajectory categories in preterm infants discharged from the NICU(P＜0.05).Conclusion Correcting for the heterogeneity in the developmental trajectories of FRAS in families of preterm infants dis-charged from the NICU within six months of age,there are three different developmental trajectories.Most families of preterm infants with a low level of FRAS onset did not improve after discharge,and they are the population that researchers should focus on and prioritize interventions.Care managers should give precise and targeted care intervention programs based on their predictive factors with limited healthcare resources to improve the intervention's effectiveness and optimize the use of resources.Then,to enhance intervention outcomes and optimize resource utilization.
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