Trajectory and predictors of family function in caregivers of stroke survivors: A longitudinal study of the first 6 months after stroke

Abstract

AimsThis study aimed to investigate the trajectory and predictors of family function in caregivers of stroke survivors during the first 6 months after the first episode of stroke.DesignLongitudinal study.MethodsA total of 288 primary caregivers of patients with first‐time stroke were recruited from seven tertiary hospitals in China between July 2020 and March 2021. The following characteristics were assessed by caregivers at hospitalization (T0) and at 1 month (T1), 3 months (T2) and 6 months (T3) after the stroke: family function, general self‐efficacy, social support, coping style, caregiver burden, and sociodemographic and clinical data.ResultsFamily function scores among caregivers of stroke survivors were highest in the resolve dimension and lowest in the growth and adaptation dimensions within the first 6 months. The percentages of families with low functioning were 34.7%, 33.3%, 24.8% and 17.7% at T0, T1, T2 and T3, respectively. The generalized estimating equation model revealed that family function in caregivers increased over the first 6 months (Exp(B) = 1.415–2.689, p < .05). The following factors were identified as predictors of family functioning: caregiver's age, education, residential district, self‐efficacy, social support utilization and caregiver burden.ConclusionsFamily function of caregivers of stroke survivors gradually increased during the first 6 months after stroke. However, some families demonstrated poor functioning. Caregivers' age, education, caregiver burden, self‐efficacy and social support utilization could predict family function over time.ImpactEmpirical data on family function in families of stroke survivors are important for developing psychosocial interventions that can help families adapt to stroke. This study found that families of stroke survivors were likely to be dysfunctional in the first 6 months after stroke, particularly in family growth and adaptation. Therefore, reducing caregiver burden and promoting self‐efficacy and social support utilization can help restore family functioning early after stroke.Patient or Public ContributionStroke caregivers from seven hospitals in China were involved in this study and had the right to be informed of the main findings. A few patients were informed of the research results, who contributed to the dissemination.

"Stroke Patient and Stakeholder Engagement (SPSE): Concepts, Definitions, Models, Implementation Strategies, Indicators, and Frameworks - A Systematic Scoping Review"

“…In quantitative research, stakeholders play a key role in the design and dissemination of research findings, as demonstrated by studies conducted by Zhang and Morgan (40,42). Other studies also support the engagement of stakeholders in various stages of quantitative research, including selecting research topics and titles, formulating research questions, choosing appropriate measurement tools, designing interventions, and sharing research findings (40,(42)(43)(44).…”

“…European countries, especially the United Kingdom have taken the lead in conducting SPSE studies. The increasing interest from other developed countries like the United States and China, as well as less developed countries such as Sierra Leone and Nigeria, suggests a growing interest in SPSE within the research community (4,8,34,36,37,39,40,43). Despite concerns over the cost of SPSE, many suggested principles, such as prioritizing stakeholder needs and values, and maintaining flexibility and openness, appear to be achievable for researchers irrespective of financial constraints (14,28,32).…”

Psychometric properties of the Chinese Family Assessment Instrument: evidence from mainland China

“…As such, the stability of the factor structure of the C-FAI over time was explored. It is important because the longitudinal invariant property of the C-FAI is largely neglected in previous studies using family functioning measures (e.g., Wang et al, 2021 , 2023 ; Wang X. et al, 2022 ; Zhang et al, 2023 ). Besides, apart from adopting RML estimation to address multivariate non-normality of the data, this study recruited a large sample for investigation.…”