Association between family support and 6-months functional recovery in acute ischemic stroke patients: a prospective cohort study

Aims: Stroke is a leading cause of disability and death worldwide, with family support playing a pivotal role in the recovery process. This study aimed to evaluate the association between family support levels and the short-term functional prognosis of patients with acute ischemic stroke.

Materials and methods: A total of 124 patients admitted to the Department of Neurology at Second People’s Hospital of Neijiang were included, with an average age of 68 years. Family support was assessed by the Family Support Questionnaire (FSQ) and the Family APGAR Questionnaire. The primary outcome was functional independence, defined as a Modified Rankin Scale (mRS) score of 0–2, assessed 6 months after discharge. Secondary outcomes included lifestyle behaviors and medication adherence. Multivariate logistic and linear regression were used to analyze the association between family support and functional independence.

Results: Compared to patients with FSQ of 0–5, FSQ of 10–15 were significantly associated with greater functional independence (OR: 1.666, 95% CI 1.236–2.214, P = 0.005) and mRS changes between baseline and follow-up at 6-months (β = −1.001, 95% CI −1.418 to −0.584, P < 0.001). However, the APGAR score was not significantly associated with functional recovery (P > 0.05). Lifestyle improvements were noted post-stroke, but no significant differences were observed among different family support levels (P > 0.05). Higher FSQ scores and APGAR scores were associated with better medication adherence (P < 0.001).

Conclusion: The study concludes family support is positively associated with functional recovery and medication adherence, further studies are needed to clarify whether improved medication adherence mediates this association.

Introduction

Stroke remains a global public health challenge, causing a substantial burden on socioeconomic development and human health (1–4). As the second leading cause of death worldwide, stroke-related mortality has exhibited significant growth over the past three decades (1, 2). Notably, ischemic stroke dominates among stroke subtypes, with both its incidence and disability rates demonstrating persistent upward trends (5). While thrombolysis and thrombectomy therapies have proven effective for acute ischemic stroke, limitations in treatment time windows and healthcare accessibility result in fewer than 1% of patients receiving timely intervention, with over half of survivors developing severe functional impairments (6–10). Against the backdrop of population aging-marked by multi-organ functional decline and comorbidities in elderly patients-post-stroke recovery becomes increasingly challenging (11), adding to the socioeconomic burden that needs to be addressed.

Families, as foundational societal units, play an irreplaceable role in stroke rehabilitation (12). Family support encompasses material assistance, emotional care, financial aid, and social resource coordination (13). By addressing daily living needs, enhancing treatment adherence, and facilitating rehabilitation exercises, such support positively impacts post-stroke recovery and stroke recurrence prevention (14, 15). However, the benefits of family support for the recovery of stroke patients are still in dispute. Some studies found that family support may be related to the psychological recovery of stroke patients, but not to their physical wellbeing (16, 17). This may be related to patients having received good rehabilitation treatment during their hospital stay. In fact, patients’ income and economic level are independent factors affecting the recovery of stroke patients, which may influence access to medical resources (18, 19). In resource-poor areas, family support is particularly important in the rehabilitation of stroke patients (20). Nevertheless, chronic diseases may diminish the family support available to patients, thereby compromising their recovery (21). Therefore, whether family support for stroke patients in resource-poor areas has a positive effect on their recovery is still unknown.

Since post-stroke dysfunction is the leading cause of disability in China (22, 23), rehabilitation interventions are necessary. Functional recovery refers to the degree of recovery of body structure and function to the pre-stroke state, which mainly occurs in the first 6 months after stroke, especially in the first 3 months (24–26). However, in China, due to the imperfection of primary healthcare institutions and high hospitalization costs, the rehabilitation of stroke patients primarily takes place at home (27, 28). Therefore, it is necessary to evaluate the short-term functional recovery of patients with acute ischemic stroke with different family support levels, and understand the prognosis of short-term functional recovery of patients with acute ischemic stroke with different family support levels. This study aims to clarify how distinct family support level influence short-term functional prognoses in acute ischemic stroke patients, thereby providing a theoretical basis for home-based rehabilitation strategies.

Population and study design

Our study initially screened 280 patients with ischemic stroke admitted to the Department of Neurology at the Second People’s Hospital of Neijiang from May 1, 2019, to September 30, 2019. According to the guidelines (29), acute ischemic stroke was defined as: (1) acute onset; (2) presence of focal neurological deficits (e.g., unilateral facial or limb weakness or numbness, aphasia, etc.); (3) identification of a responsible lesion on CT/MRI or persistence of symptoms/signs for >24 h; (4) exclusion of non-vascular etiologies; and (5) exclusion of intracerebral hemorrhage on imaging. Among all patients, we excluded patients (1) with severe organ failure (n = 13), aphasia [Boston Diagnostic Aphasia Battery grade 0–2 (30), n = 25], psychiatric disorders (n = 34), or malignancies (n = 6); (2) lacked full cognitive capacity or refused to sign the informed consent form (n = 73); (3) who were lost to follow-up (n = 5). Finally, 124 patients with acute ischemic stroke were included in the study (Figure 1). This study was supported by the China National Stroke Screening Survey (CNSSS). It was approved by the Medical Ethics Committee of the Second People’s Hospital of Neijiang, with approval number 2018073. All participants and their proxies provided written informed consent.

FIGURE 1

Figure 1. Study flow chat.

Prior to the implementation of the study, all data collectors underwent standardized training, which included structured questionnaire interviews, standardized blood pressure measurement, and standardized laboratory testing procedures. Only those who passed the assessment were permitted to participate in the study. An independent quality control group was established during the study to dynamically monitor the entire data collection process, including questionnaire completion, physical examination, and laboratory testing. Participants were admitted within 72 h of symptom onset and all baseline data were collected within 48 h of hospital admission. Data management was conducted using a dual-independent data entry system. After data entry, consistency checks were performed. Any discrepancies in the data entries were corrected after dual verification with the original paper records.

Family support assessment

Family support was assessed using the Family Support Questionnaire (FSQ) and the Family Adaptation, Partnership, Growth, Affection and Resolve (APGAR) Questionnaire. The FSQ is an appropriate instrument for assessing family support in the Chinese population and has been validated in previous study (Cronbach’s α = 0.85) (31), with reference to the Family Support Scale (Perceived Social Support from Family Scale, PSS-Fa) designed by Procidano and Heller in the United States in 1983 (32–34). The FSQ captures tangible supportive behaviors (emotion, finance, daily affairs, or health) directly relevant to post-stroke recovery (35). The total score ranges from 0 to 15 points, based on the scores, family behavioral support is categorized into three levels: low level (0–5 points), medium level (6–10 points), and high level (11–15 points).

The Family APGAR Questionnaire was developed by American scholar Smilkstein in 1978 (36). The APGAR Questionnaire has been validated and shown to be appropriate for use in the Chinese population, a survey conducted among 2,635 Chinese individuals demonstrated that the APGAR Questionnaire has good internal consistency in the Chinese population (Cronbach’s α = 0.94) (37). The Family APGAR Questionnaire captures the close relationships between the respondents and other family members, it is widely used in stroke recovery (38, 39). The total score ranges from 0 to 10 points. Based on the scores, family function is categorized into three levels: severe dysfunction (0–3 points), moderate dysfunction (4–6 points), and good function (7–10 points), which correspond to low, medium, and high levels of family care and support, respectively.

Outcome assessment

The primary outcome was assessed using the internationally recommended scale for functional evaluation of acute ischemic stroke (Chinese version), namely the Modified Rankin Scale (mRS) (40–42). Previously, several studies in China used mRS to assess the functional status of stroke patients (42–44). The mRS score ranges from 0 to 6, divided into seven levels. Based on previous studies, we defined scores of 0–2 as functional independence and scores of 3–6 as functional dependence (45, 46). We evaluated the mRS scores of participants both at admission and 6 months after discharge. Additionally, we calculated the difference between the mRS score at 6 months after discharge and the admission score, denoted as ΔmRS.

Secondary outcomes included changes in lifestyle behaviors (alcohol consumption, smoking, exercise, and healthy diet score) and medication adherence at follow-up, which are key modifiable risk factors in clinical guidelines. Alcohol consumption, smoking status and physical activity were assessed with standardized instruments that have been validated (47–50). The healthy diet score (51) was assessed by seven components, details of which can be referred to in previous studies. Medication adherence was evaluated using the Brief Medication Questionnaire (BMQ) (52), which includes necessity beliefs and concern beliefs. The difference between these two beliefs constitutes the final score. The BMQ has been validated in the Chinese population and has demonstrated good validity and reliability (Cronbach’s α = 0.759) (53).

Covariates assessment

The following covariates were assessed: age (years), sex (male/female), educational status (years of schooling: <6, 6–9, >9), alcohol status (current, former/never), smoking status (current, former/never), physical activity (whether meeting the guideline recommendations) (54), hypertension (yes/no), diabetes (yes/no), hyperlipidemia (yes/no), and National Institutes of Health Stroke Scale (NIHSS) score. The above information was obtained from patient self-reports or electronic medical records during hospitalization.

Statistical analysis

Continuous data are presented as mean and standard deviation. Categorical data are described using frequencies and percentages. For functional recovery, univariate and multivariate logistic regression analyses were built. With low family support participants as the reference group, the multivariate logistic regression analysis was adjusted for all the covariates mentioned above and baseline mRS scores. Additionally, changes in mRS scores were assessed using univariate and multivariate linear regression, with the same adjustments as in the multivariate logistic regression. For secondary outcomes, ANOVA analysis and chi-square tests were used according to the data types. Statistical significance was defined as a p-value < 0.05 for two-tailed tests. All analyses were performed using SPSS version 27.0 (IBM Corp., Armonk, NY, USA).

Results

Baseline characteristics

A total of 124 participants were included in this study (age: 68.44 ± 11.27 years, male: 71 [57.26%]) with follow-up of 6 months. At baseline, there were no significant differences among participants with different levels of FSQ and APGAR score in terms of age, gender ratio, smoking and alcohol history, hypertension, hyperglycemia, hyperlipidemia, and mRS scores (Table 1).

TABLE 1

Table 1. Participants characteristics at baseline.

Association between FSQ scores and mRS scores

In the unadjusted model (Figure 2), compared with low-support patients, those with high support exhibited a 52% relative increase in the odds of functional independence (OR = 1.666, 95% CI 1.236–2.214, P = 0.010). Additionally, each one-point increase in the FSQ score was associated with a 6.8% increase in the odds of functional independence (OR = 1.068, 95% CI 1.008–1.116, P < 0.001). In the fully adjusted logistic regression (Figure 2), participants with high FSQ score level had an odds ratio (OR) of 1.517 (95% CI 1.224–1.895, P = 0.005), and each one-point increase was associated with an OR of 1.061 (95% CI 1.004–1.129, P < 0.001).

FIGURE 2

Figure 2. Association between family support level and functional independence. (A) Unadjusted model; (B) fully-adjusted models. Fully-adjusted models were adjusted for age, sex, educational status, alcohol status, smoking status, physical activity, hypertension, diabetes, hyperlipidemia, and NIHSS score.

In the fully adjusted linear regression (Table 2), in the high FSQ score group, mRS scores decreased (β = −1.001, 95% CI −1.418 to −0.584, P < 0.001) compared to low FSQ score group and each one-point increase in FSQ score was associated with a mean decrease in mRS scores of 0.127 (β = −0.127, 95% CI −0.179 to −0.075, P < 0.001). Thus, higher FSQ score was linked to greater functional independence in post-stroke patients.

TABLE 2

Table 2. Association between family support level and ΔmRS score.

Association between APGAR scores and mRS scores

In the unadjusted model (Figure 2), compared to low score groups, high APGAR score group were associated with greater functional independence (OR = 1.475, 95% CI 1.137–1.875, P = 0.027). For each one-point increase in APGAR scores, the odds of functional independence increased by 5.6% (OR = 1.056, 95% CI 1.008–1.132, P = 0.006). However, in the fully adjusted logistic regression (Figure 2), APGAR score level was not significantly associated with functional independence (P > 0.05).

In the fully adjusted linear regression (Table 2), there was no association between APGAR score group and mRS scores decreased. While each one-point increase in APGAR score was associated with a mean decrease in mRS scores of 0.073 (β = −0.073, 95% CI −0.138 to −0.007, P = 0.030). Although APGAR categorical variable was no longer significantly associated with functional independence after multivariable adjustment, each unit increase in its continuous score remained associated with measurable improvement in mRS.

Association between lifestyle behaviors and medication adherence

Compared to the baseline, the overall proportion of current smokers (27.42% vs. 12.10%) and drinkers (20.97% vs. 5.65%) among participants was reduced after 6 months, while the healthy diet score (2.44 ± 1.18 vs. 3.91 ± 0.71) and proportion of exercising (6.45% vs. 20.97%) increased. However, there were no significant differences in smoking, drinking, exercise, and healthy diet scores among the groups with different levels of FSQ and APGAR scores (Table 3). In terms of medication adherence (Table 3), a higher level of FSQ score (low vs. medium vs. High: 3.24 ± 1.48 vs. 3.73 ± 1.03 vs. 5.40 ± 1.01, P < 0.001) and APGAR score (low vs. medium vs. high: 4.30 ± 1.16 vs. 4.33 ± 1.51 vs. 4.76 ± 1.47, P = 0.039) were associated with higher medication adherence. Collectively, higher levels of FSQ and APGAR scores were statistically associated with better medication adherence but not with short-term lifestyle change.

TABLE 3

Table 3. Analyses to lifestyle and medication adherence after 6 months.

Discussion

In this study, 124 patients with acute ischemic stroke were included, with an average age of 68 years, mainly distributed in the age group of 60–69 years, which is consistent with the age characteristics of the stroke registry data in China (55). High level of family support (FSQ 11–15 points) showed 1.52-fold higher odds of functional independence and each one-point increase in the FSQ was associated with a 0.127-point decrease in the mRS score, extending previous reports that robust family support improves functional recovery after stroke by quantifying the dose–response relationship. In contrast, APGAR score levels were no longer associated with functional independence after multivariable adjustment. Regardless of whether assessed by FSQ or APGAR score, higher family support was associated with better medication adherence. It should be noted that, although we found that the overall lifestyle improved after stroke compared with before, no significant differences were found between different levels of family support. In summary, this study further highlights the importance of family support for post-stroke functional recovery.

Family support refers to the psychological, social, and behavioral support provided by family members to patients. It has a positive impact on patients’ prognosis, including depression, anxiety, relationship satisfaction, disability, and mortality after illness (56, 57). The Family Support Questionnaire (FSQ) score is mainly used to assess the degree of family support perceived by individuals, quantifying the level of support provided by family members in terms of emotion, finance, daily affairs, or health (35). High levels of family support may be associated with improved patient prognosis. For example, a study in Iran targeting the elderly in rural communities showed that high level of family support were significantly associated with increased activities of daily living among the elderly (58). Additionally, a cross-sectional study demonstrated a positive correlation between high levels of family support and self-efficacy in stroke patients (29). However, an Indonesian tuberculosis cohort found no association between family support and anti-tuberculosis medication adherence (59).

The APGAR score primarily focuses on family function (60). Previous studies showed that lower APGAR score may be an important factor in the occurrence of post-stroke fatigue and lower health beliefs among stroke patients (61, 62). Additionally, the APGAR score was not significantly correlated with patient gender, age, marital status, education level, or socioeconomic status (63). In this study, after fully adjusting the model, the APGAR score was not associated with functional recovery of patients with acute ischemic stroke, which may suggest that family support assessed by FSQ score may play a more important role in the functional recovery of stroke patients and further studies are needed to explore the underlying reasons.

Due to the long recovery time for stroke patients, high hospitalization costs and lack of medical resources, most stroke patients in China only conduct rehabilitation exercise at home after discharge (28, 64, 65). Therefore, functional recovery supported by the family is particularly important for stroke patients in China. Our study clarified the positive impact of family support level on the recovery of patients with acute ischemic stroke, offering a new perspective for improving stroke functional recovery in areas with limited medical resources. This may be related to better family support increasing patients’ health beliefs, self-efficacy, emotional improvement, and medication adherence. Although our study found that lifestyle behaviors were similar in different levels of FSQ and APGAR scores at both baseline and the 6-months follow-up, this may be due to the short follow-up period, which led to insufficient observation.

The study has several limitations. First, the observational, non-randomized design precludes causal inference; all reported associations should be interpreted as correlational. Second, neither patients nor outcome assessors were blinded to the support-level grouping, introducing potential assessor bias in the 6-months mRS evaluation and response bias in self-reported questionnaires. Third, the evaluation of family support and medication adherence relied entirely on patient self-report, which is susceptible to recall and social-desirability bias. Fourth, the single-center design and relatively small sample (n = 124) limit external validity and the ability to detect small effect sizes, especially in the lifestyle subgroup analyses. Fifth, the 6-months follow-up, while sufficient for functional outcomes, may be too short to observe the full trajectory of medication adherence or lifestyle change, and longer-term assessments are warranted. Finally, the study did not record the exact relationship between the patient and the family member providing support; thus, we could not examine whether relationship type influences the level of family support. Future studies need to be large-scale and have longer follow-up periods to clarify the impact of family support level on the prognosis of stroke patients.

Conclusion

The level of family support is positively correlated with functional recovery, and improvement of medication adherence may be a potential mechanism. Our study suggests that family support needs to be assessed among stroke patients after discharge. Enhancing family support may be an essential pathway to improve functional recovery of stroke patients in limited medical resources areas. Future research should investigate the association between family support levels and lifestyle improvements with larger samples and longer follow-up periods.

Data availability statement

The original contributions presented in this study are included in this article/supplementary material, further inquiries can be directed to the corresponding author.

Ethics statement

The studies involving humans were approved by the Medical Ethics Committee of the Second People’s Hospital of Neijiang, with approval number 2018073. The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participants’ legal guardians/next of kin.

Author contributions

MZ: Conceptualization, Data curation, Investigation, Methodology, Writing – original draft, Writing – review & editing. YZ: Data curation, Methodology, Software, Writing – original draft, Writing – review & editing. YJ: Data curation, Investigation, Methodology, Software, Writing – review & editing. YY: Investigation, Methodology, Validation, Writing – review & editing. YC: Data curation, Investigation, Methodology, Writing – review & editing. DL: Data curation, Investigation, Writing – review & editing. YgZ: Formal analysis, Software, Validation, Writing – review & editing. YL: Data curation, Investigation, Methodology, Writing – review & editing. QZ: Resources, Software, Writing – review & editing. JH: Conceptualization, Investigation, Supervision, Writing – review & editing. XL: Conceptualization, Project administration, Supervision, Visualization, Writing – review & editing.

Funding

The author(s) declare financial support was received for the research and/or publication of this article. This work was supported financially by grants from 2022 Neijiang City Key Science and Technology Project Plan (Social Development Category, No. 34), Noncommunicable Chronic Diseases-National Science and Technology Major Project (Nos. 2023ZD0506101 and 2023ZD0506100), Sichuan Science and Technology Program (Nos. 2024NSFSC0661, 2024NSFSC1534, and 24ZDYF0065), Sichuan Provincial Health Commission (Nos. 2023-103 and 2024-102), 135 Project for Disciplines of Excellence-Clinical Research Incubation Project and Artificial Intelligence (Nos. 2023HXFH002 and 0040206107081), and Postdoctor Research Fund of West China Hospital, Sichuan University (No. 2024HXBH067), CDHT Health Bureau (Nos. 2024004 and 2024005).

Acknowledgments

We appreciate the participants for their participation and contribution to this research.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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