Factors influencing the caregiver burden on primary family caregivers of stroke survivors: a scoping review

Abstract

Background

Stroke is a leading cerebrovascular disease characterized by high incidence and significant disability rates. Following the acute phase, most stroke survivors require prolonged home-based rehabilitation and care, a responsibility predominantly undertaken by primary family caregivers. The sustained demands of caregiving often impose considerable physical, psychological, and social burdens on these individuals.

Objective

This review aims to systematically identify and synthesize the factors influencing the caregiving burden among primary family caregivers of stroke survivors.

Methods

This scoping review followed the Joanna Briggs Institute’s methodological framework. A comprehensive literature search was conducted in the following databases: Web of Science, PubMed, CINAHL, Cochrane Library, Embase, CNKI, CBM, Wanfang Date, and VIP. The search included articles published from inception until October 24, 2025. All study designs reporting on factors influencing the caregiving burden of primary family caregivers of stroke survivors were eligible for inclusion.

Results

A total of 2005 records were identified, of which 35 articles met the inclusion criteria. The included studies comprised 30 cross-sectional studies (85.71%), four prospective cohort studies (11.43%), and one mixed-methods study (2.86%). Most of the included studies were from Asian countries, including China (n = 28), South Korea (n = 2), Poland (n = 2), Greece (n = 1), India (n = 1), and Thailand (n = 1). Eleven studies (31.4%) reported incidence data, but substantial heterogeneity precluded direct quantitative synthesis. A total of 65 influencing factors were identified and grouped into three categories: caregiver-related factors, patient-related factors, and family and social support factors. The most frequently reported factors included caregiver age (n = 19), average daily caregiving hours (n = 19), patient activities of daily living (n = 19), caregiver - patient relationship (n = 16), and caregiver education level (n = 16).

Conclusion

The caregiving burden among primary family caregivers of stroke survivors is influenced by a wide range of factors. To reconcile inconsistent or contradictory findings, further research using standardized assessment tools and methodologies is warranted.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11136-026-04236-6.

Introduction

Stroke is the second leading cause of death and the third leading cause of disability worldwide, with a growing epidemiological burden [1]. According to the 2019 Global Burden of Disease study, approximately 12.2 million new stroke cases occur annually [2]. Although the age-standardized incidence of stroke has declined from 1990 to 2019, the absolute number of stroke cases continues to rise, largely due to factors such as population aging [3]. Projections indicate that by 2050, the global number of stroke cases will reach 21.43 million, with approximately 159.31 million stroke survivors worldwide [4]. An estimated 70% – 80% of stroke survivors experience varying degrees of physical impairment, cognitive deficits, or dysphagia, which significantly reduces their ability to perform activities of daily living [5]. A systematic review [6] highlighted that due to limb dysfunction, stroke survivors often require long-term basic support from family caregivers to maintain activities of daily living. This caregiving demands substantial time and energy, often at the expense of the caregivers’ social lives and work. Such sustained pressure frequently results in a high care burden, particularly for the primary family caregiver. As noted by R. Evans et al. [7], Primary family caregivers score higher in caregiver burden inventories compared to other caregivers. In this review, a “family caregiver” is defined as a family member or relative providing unpaid care [8], while the “primary family caregiver” is the individual bearing the core responsibility for daily care [9]. This study specifically focuses on the latter group.

Caregiving burden is defined as the multidimensional adverse effects - encompassing psychological, physical, and social domains - experienced by family caregivers as a result of providing long-term assistance, comfort, and support to disabled older adults [10]. Prolonged exposure to a high level of caregiver burden negatively impacts not only the quality of care provided but also significantly compromises the health status of the primary family caregivers, thereby diminishing their health-related quality of life (HRQoL) [11]. HRQoL is a multidimensional construct encompassing an individual’s perception of physical and mental health, social relationships, and the supportive environment [12]. Serap et al. [13] found that the level of care burden was inversely correlated with scores on the caregiver quality of life scale. Long-term caregiving can induce physical fatigue, chronic pain, and weakened immunity. This state of high burden substantially affects caregivers’ mental health, contributing to depression, excessive worry, and anxiety [14–16].

The severity of caregiver burden is influenced by multiple factors. Patient-related factors, such as the severity of neurological deficits, the degree of dependence in activities of daily living, and a high number of post-stroke complications, significantly increase the physical fatigue and psychological pressure on primary family caregivers [17–19]. On the other hand, caregiver-related factors are also critical [20–21]. Female gender, older age, and poor baseline health status of the caregiver are all established predictors of a higher burden. Identifying these influencing factors is essential for developing interventions to alleviate the care burden and promote the physical and mental health of primary family caregivers. For instance, Lu et al. [22] demonstrated that enhancing resilience and reducing negative coping styles can effectively mitigate burden and improve quality of life. Furthermore, facilitating access to community resources and providing psychoeducational support can reduce burden levels and lead to better health outcomes [23].

While numerous studies have explored factors associated with caregiver burden, no research has systematically examined the determinants of this burden specifically for primary family caregivers of stroke survivors. Although Yue et al. [24] Conducted a systematic review in 2022 on factors influencing the caregiver burden among stroke survivors caregivers in China; their study did not focus on primary family caregivers and was geographically limited to China, which may not fully capture the influencing factors relevant to this specific group. Therefore, this scoping review aims to systematically identify and analyze the factors affecting the care burden of primary family caregivers of stroke survivors in the existing literature. It also summarizes the reported incidence of care burden and the current application of assessment tools within this population. The goal is to advance research on care burden management, enhance the precision of interventions, and ultimately improve the physical and mental health and quality of life of primary family caregivers.

Scoping review research questions

The review seeks to answer the following questions:

1. What is the current state of the literature on the caregiving burden among primary family caregivers of stroke survivors?

2. What factors influence the caregiving burden of primary family caregivers of stroke survivors?

3. What assessment tools are currently used to evaluate the caregiving burden in primary family caregivers of stroke survivors?

Methods

This scoping review was conducted following the Joanna Briggs Institute (JBI) methodological framework for scoping reviews and reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist (Supplementary Material 1). The review protocol was registered with the Open Science Framework (https://osf.io/3yb57/overview).

Search strategy

A systematic literature search was conducted in PubMed, Web of Science, CINAHL, the Cochrane Library, Embase, CNKI, CBM, Wanfang, and VIP from their inception until October 24, 2025. The search strategy combined subject headings with free-text keywords and was adapted to the specific syntax of each database. The detailed search strategies are provided in Supplementary Material 2.

Eligibility criteria

In accordance with the JBI-recommended PCC (Population, Concept, Context) framework, the inclusion and exclusion criteria for this review were developed. The specific criteria are presented in Table 1.

Table 1.

Inclusion and exclusion criteria

PCC framework	Inclusion criteria	Exclusion criteria
Participants	• The study participants were primary family caregivers of stroke survivors, including spouses, adult children, parents, and other relatives, as well as friends who assumed the primary caregiving role.	• Non-primary family caregivers (e.g., professional caregivers, volunteers, institutional caregivers)
Concept	• Studies have focused on caregiver burden and its influencing factors • Including psychological burden, emotional stress, quality of life, social support, care time, economic status and other influencing factors	• Only the effects of intervention measures on caregivers were discussed, and the influencing factors of burden were not analyzed •The study did not explicitly focus on caregiver burden
Context	• Studies for all countries and regions (high, middle, and low-income countries) • All genders, races, and cultural backgrounds •There was no restriction on the time of literature publication	• Non-chinese and English literature • Conference abstracts, review articles, reviews, non-empirical studies

Source of evidence selection

All retrieved records were imported into NoteExpress [25] (version 4.3.0; Aegean Software Corp., Beijing, China), a reference management tool used for de-duplication and screening preparation, and duplicates were initially removed using its built-in deduplication function. Two reviewers (Li ZJ and Wu XQ) independently screened the titles and abstracts against the inclusion and exclusion criteria. Potentially eligible articles underwent full-text review and cross-verification. Any discrepancies were resolved through discussion or, if necessary, by consultation with a third reviewer (Li XC). During full-text assessment, the reference lists of included articles were also examined to identify additional relevant literature. For publications whose full text was unavailable, corresponding authors were contacted to request complete data. Throughout the screening process, reasons for exclusion were systematically documented. In line with the PRISMA-ScR guidelines, which do not require formal quality assessment for scoping reviews [26], no quality appraisal or risk-of-bias analysis was conducted on the included studies.

Data extraction and analysis

Two reviewers (Li ZJ and Wu XQ) independently extracted data using a standardized Excel form, which included the following items: author, publication year, national income level (classified according to the World Bank 2024 standards [27]), study design, types of stroke included, study population, assessment tools, incidence (if reported), and associated factors. Any discrepancies in data extraction were resolved through consensus or, when necessary, by a third reviewer (Li XC).

Results

A total of 2004 records were retrieved from the nine databases, and one additional article was identified via citation searching, resulting in 2005 records for screening. After deduplication and eligibility assessment, 35 articles were finally included. The detailed screening process is illustrated in Fig. 1, which adheres to the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines.

Fig. 1.

Preferred reporting items for systematic reviews and meta-analyses extension for scoping review (PRISMA-ScR) flow diagram

Characteristics of included studies

Of the 35 included articles, the publication years were from 2005 to 2025. Of the 35 evidence sources, 30 were cross-sectional studies (85.71%), 4 were prospective cohort studies (11.43%), and 1 was a mixed study (2.86%). The sample size ranged from 56 to 1133, with a total of 6795 patients. Twenty-three articles reported the score of caregiving burden (65.7%), and 11 articles reported the incidence of caregiving burden (31.4%). Detailed literature characteristics are shown in Table 2.

Table 2.

Basic characteristics of the included literature (n = 35)

Author (Publication year)	Country	Income level	The types of stroke included	Research subjects	Research type	Tools for assessment	Sample size	Total burden score/incidence rate
Wang et al. 2025[28]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	ZBI	240	30.43 ± 13.33/-
Xu et al. 2025[29]	China	Middle to high	Hemorrhagic	Primary family caregiver	Cross-sectional	ZBI	220	32.52 ± 8.11/4.09%*, 72.73%**, 23.18%***
Duan et al. 2025[30]	China	Middle to high	Mixed	Primary family caregiver	Mixed-method	ZBI-12	238	-/38.4%
Rys et al. 2025[31]	Poland	High	Ischemic	Primary family caregiver	Cross-sectional	CBS	110	2.39 ± 0.74/32.7%*, 40.0%**, 27.3%***
Xu et al. 2024[32]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	ZBI	462	–
Kwon et al. 2023[17]	Korea	High	Mixed	Primary family caregiver	Prospective cohort	CBI	1 133	14.8 ± 12.8/-
Kavga et al. 2022[33]	Greece	High	Mixed	Primary family caregiver	Cross-sectional	G-BCOS	109	48.3 ± 13.3/-
Kumar et al. 2022[18]	India	Middle to high	Mixed	Primary family caregiver	Prospective cohort	OCBS	251	–
Boonsin et al. 2021[34]	Thailand	Middle to high	Mixed	Primary family caregiver	Cross-sectional	ZBI	200	29.9 ± 12.50/-
Wu et al. 2020[35]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	CBI	342	–
Wang et al. 2019[36]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	ZBI	100	52.8 ± 6.3/13.0%*, 68.0%**, 19%**
Han et al. 2018[37]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	CBI	202	50.17 ± 9.75/5.94%*, 80.20%**, 13.86%***
Hu et al. 2018[38]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	ZBI	120	33.56 ± 15.43/44.8%*, 27.8%**, 6.9%***
Zhang et al. 2018[39]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	CRA	154	3.38 ± 0.44/-
Chang et al. 2018[40]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	CBI	105	40.50 ± 6.96/-
Dou et al. 2018[41]	China	Middle to high	Ischemic	Primary family caregiver	Cross-sectional	ZBI	271	–
Lan et al. 2017[42]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	–	160	–
Yan et al. 2017[43]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	CBI	211	57.37 ± 10.15/-
Li et al. 2017[44]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	ZBI	234	–
Han et al. 2017[45]	China	Middle to high	Mixed	Primary family caregiver	Prospective longitudinal	CSI	164	7.35 ± 2.9/-
Fu et al. 2016[46]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	–	100	–
Zhang et al. 2016[47]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	CBI	167	-/4.79%*, 82.60%**, 12.61%***
Mei et al. 2015[48]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	ZBI	110	38.43 ± 14.22/50.5%*, 35.2%**, 7.6%***
Jaracz et al. 2015[49]	Poland	High	Mixed	Primary family caregiver	Prospective cohort	CBS	88	2.04 ± 0.64/-
Zhang et al. 2014[50]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	ZBI	155	-/63.9%
Su et al. 2012[51]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	ZBI	198	55.72 ± 19.01/-
Liu et al. 2012[52]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	FBS	108	1.002 ± 0.461/-
Qi et al. 2011[53]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	ZBI	156	57.55 ± 14.39/-
Liu et al. 2011[54]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	CSI	96	7.9 ± 2.9/53.1%
Zhang et al. 2009[55]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	CBI	56	1.55 ± 0.35/-
He et al. 2009[56]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	–	100	–
Zhao 2008[57]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	–	101	–
Zhang et al. 2007[58]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	BCOS	108	48.83 ± 8.05/-
Yang et al. 2005[59]	China	Middle to high	Mixed	Primary family caregiver	Cross-sectional	Self-made scale	79	66.56 ± 15.49/57.88%
Choi et al. 2005[60]	Korea	High	Ischemic	Primary family caregiver	Cross-sectional	SCQ	147	2.3 ± 0.6/-

ZBI, Zarit Burden Interview; ZBI-12, Zarit Burden Interview-12; CBS, Caregiver Burden Scale; CBI, Caregiver Burden Inventory; G-BCOS, Bakas Caregiving Outcomes Scale - Greek version; OCBS, Oberst Caregiving Burden Scale; CRA, Caregiver Reaction Assessment scale; CSI, Caregiver Strain Index; FBS, Family Burden Scale of Disease; BCOS, Bakas caregiving outcome scale; SCQ, Sense of Competence Questionnaire; “-”, Not mentioned; “*”, A modest burden; “**”, Moderate burden; “***”, Severe burden

Explanations

Mixed means that studies included both ischemic and hemorrhagic strokes.

Incidence rate

Among the 35 included studies, eleven studies^{[29–31,36−38,47–48,50,54,59]} reported the incidence of caregiver burden among primary family caregivers of stroke survivors. The reported incidence ranged from 4.09% to 50.5% for mild burden, 27.8% to 82.6% for moderate burden, and 6.9% to 27.3% for severe burden. Individual studies by Duan et al. [30], Zhang et al. [50], Liu et al. [54], and Yang et al.^{[59 ]}reported overall incidence rates of 38.4%, 63.9%, 53.1%, and 57.88%, respectively. These findings indicate a generally high burden of care among primary family caregivers of stroke survivors, with moderate burden being particularly prominent. Ten of these eleven studies were conducted in China, and one was from Poland, which reflects, to some extent, a current lack of research on caregiver burden in this population across diverse cultural and regional contexts.

Influencing factors

This study identified 65 influencing factors, which could be divided into 3 first-level categories (care-related factors, patient-related factors, and family and social support factors) and 14 s-level dimensions, as shown in Table 3.

Table 3.

Factors influencing

First class classification	Secondary dimension	Quantity	Influencing factors
Caregiver-related factors	Demographic characteristics	7	Age, gender, education level, occupation status, economic status, marital status, religious belief
	Health condition	4	Chronic diseases, self-rated health status, good sleep, and physical discomfort
	Psychological and emotional state	6	Self-compassion, depression, affective disorder, anxiety, depression, mental state
	Caring behavior and burden	7	Average daily care time, total care time, care tasks, work time, care time of other caregivers, whether there are other caregivers, coping behavior
	Cognition and Knowledge	3	Mastery of disease knowledge, whether to accept professional training, self-efficacy
Patient-related factors	Subjective feelings	4	Caregivers’ overall quality of life, caregivers’ willingness, stress perception ability, positive feelings
	Demographic characteristics	3	Age, gender, and education level
	Disease condition	7	Stroke duration, stroke frequency, stroke type, suffering from other chronic diseases, depression, anxiety and mental state
	Functional status	7	Barthel Index, mRS Score, NIHSS score, FMA score, cognitive function, number of dysfunction, muscle strength
	Complications	3	Whether there were falls, pressure sores above the second stage, and aphasia
	Behavior and lifestyle	3	Drinking, rehabilitation exercise times per week, and feeding patterns
Family and social support factors	Family structure and relationships	4	Relationship with the patient, closeness to the patient, whether living with the patient, health level of other family members
	State of the economy	4	Insurance type, medical payment method, monthly medical expenses, family economic level
	Social resources	3	Residence, hospitalization times, and social support level

mRS, Modified Rankin Scale; NIHSS, National Institutes of Health Stroke Scale; FMA, Fugl‑Meyer Assessment

Caregiver related factors

Demographic characteristics

Regarding demographic characteristics, several studies have explored the association between different variables and caregiving burden. The data showed that age (19/35, 54%), gender (15/35, 42%), education level (16/35, 45%), occupation (12/35, 34%), economic status (3/35, 8%), marital status (11/35, 31%), religious belief (3/35, 8%) and other factors were included in the analysis.

Regarding age, among the 19 studies that assessed caregiver age, three studies [29, 36, 49] identified age ≥ 60 years as being associated with higher burden levels (3/19, 15%), whereas one study [18] reported age ≤ 60 years as a contributing factor (1/19, 5%). Another study [54] used a threshold of ≤ 45 years (1/19, 5%), and two studies [43, 53] did not specify a clear age cutoff (2/19, 10%).

Regarding gender, four of the 15 studies that examined this factor [33, 40, 54, 60] reported that female caregivers tended to experience a higher burden (4/15, 26%). As for education, among the 16 studies that assessed caregiver education level, four studies [35, 39, 42, 58] found that caregivers with a junior high school education or below reported greater burden (4/16, 25%), while one study [32]indicated that a bachelor’s degree or above was associated with increased burden (1/16, 6%).

Regarding occupational status, three of the 12 studies that examined this factor [39, 53, 60] found that being retired or unemployed was associated with higher burden (3/12, 25.0%), while one study [33] suggested that employed caregivers might receive greater social support (1/12, 8.3%). Other demographic factors, including lower economic status [31, 44] (2 of 3 studies, 66%), marital status [51] (1 of 10 studies, 10%), and religious belief [59] (1 of 3 studies, 33%), were also reported as potential influencing factors.

Health condition

In terms of health status, the main factors included chronic diseases (3/35, 8%), self-rated health status (7/35, 20%), good sleep (1/35, 2%), and physical discomfort (1/35, 2%).

Among the 3 studies that examined chronic diseases in caregivers, two [42, 58] studies observed that caregivers with chronic diseases were the influencing factors of care burden (2/3, 66%). When caregivers evaluate their own health status as poor or very poor [28, 30, 32, 58], the burden of care will also increase (4 of 7 studies, 57%). The physical discomfort of caregivers was also an influencing factor [35, 45] (1 of 1 study, 100%).

Psychological and emotional state

The main symptoms included self-compassion (1/35, 2%), depression (1/35, 2%), affective disorder (1/35, 2%), anxiety (6/35, 17%), depression (5/35, 14%), and mental state (1/35, 2%).

The only included study [28] assessing self‑compassion reported a negative correlation between caregivers’ total self‑compassion score and their caregiving burden score (1/1, 100%). One [31] study pointed out that emotional disorder of caregivers was the influencing factor of care burden. The conclusions on the correlation between depression, anxiety, and depression and the occurrence of care burden were consistent. Studies showed that caregivers were depressed [31](1/1, 100%), anxious [18, 36, 38, 48–49, 60] (6/6, 100%) and depressed [36–37, 47, 49, 60] (5/5, 100%) were the aggravating factors of care burden. The worse the mental state of the caregivers, the higher the burden of care [31] (1/1, 100%). Note: Denominators indicate the number of studies assessing each specific factor.

Caring behavior and burden

They mainly included average daily care time (19/35, 54%), total care time (10/35, 28%), care tasks (2/35, 5%), caregivers’ working time (1/35, 2%), care time of other caregivers (1/35, 2%), and whether there were other caregivers (9/35, 2%). 25%), and coping behaviors (2/35, 5%).

Research on caregiving time can be divided into two categories: Average daily care time and total care time. For average daily care time, among the 19 studies that assessed this factor, two studies [54, 59] considered average daily care time ≥ 4 h as the influencing factor of care burden (2/19, 10%), and five studies [18, 34, 42, 49, 57] found that average daily care time ≥ 6 h may be a factor (5/19, 26%). However, seven [29, 32, 35–37, 58, 60] studies used the average daily care time ≥ 8 h as the threshold (7/19, 36%), and 3 [33, 51, 53] studies did not give specific research threshold (3/19, 15%). For the total care time, among the 10 studies that assessed this factor, two [31, 34] studies pointed out that the total care time > 3 months was the influencing factor of care burden (3/10, 30%), and the other five [29–30, 51, 53, 60] studies did not give a specific demarcation value (5/10, 50%).

The two studies [42, 58] that examined the number of care tasks both found that having ≥ 10 care tasks can significantly increase the burden of care (2/2, 100%). The single study [48] that assessed external working hours suggested that caregivers‘ time spent working outside the home may also be an influencing factor (1/1, 100%). Additionally, one study [46] found that the care time contributed by other caregivers was an influencing factor (1/1, 100%).

Among the 9 studies that assessed the availability of shared care, three [39, 50, 55] found that whether there were other caregivers to share the tasks had an impact on the care burden (3/9, 33%). Furthermore, both studies [31, 49] that examined coping style reported that a negative coping style was an influencing factor for care burden (2/2, 100%).

Cognition and knowledge

Caregiver-related health and competency factors were also examined. These included knowledge about stroke (1/35, 2.9%), whether they had received professional training (2/35, 5.7%), and self-efficacy (3/35, 8.6%).

Findings indicated that the single study [42] assessing stroke-related knowledge reported that caregivers with sufficient knowledge experienced lower levels of burden (1/1, 100%). Of the two studies examining professional rehabilitation training, one [39] found that caregivers who had received such training experienced a lower burden (1/2, 50%). Additionally, all three studies [34, 38, 58] that assessed self-efficacy consistently reported a significant negative correlation between caregivers’ self-efficacy and caregiving burden (3/3, 100%).

Subjective feelings

The following factors were also examined: caregivers’ overall quality of life (1/35, 2.9%), willingness to provide care (2/35, 5.7%), perceived stress (1/35, 2.9%), and positive caregiving appraisals (2/35, 5.7%).

One study [31] suggested that lower overall quality of life may contribute to greater caregiver burden (1/1, 100%). Regarding willingness, two studies [48, 58] reported that feeling obligated to provide care was associated with higher burden levels (2/2, 100%). Similarly, higher perceived stress was linked to increased burden in one study [31] (1/1, 100%). In contrast, positive feelings toward caregiving were consistently identified as protective factors in two studies [43, 45] (2/2, 100%). Note: Denominators indicate the number of studies assessing each specific factor.

Patient-related factors

Demographic characteristics

Regarding patient-related demographic factors, age (6/35, 17%), gender (6/35, 17%), and education level (1/35, 2%) were reported.

Of the 6 studies that assessed patient age, two [31, 52] suggested that older patient age was associated with higher caregiver burden (2/6, 33%). No other patient demographic characteristics showed statistically significant associations with burden levels.

Disease condition

The following clinical factors were examined: stroke duration (2/35, 5%), stroke frequency (2/35, 5%), stroke type (2/35, 5%), comorbidities (4/35, 11%), depression (6/35, 17%), anxiety (1/35, 2%), and mental status (2/35, 5%).

Of the 2 studies assessing stroke duration, one [54] reported that a longer duration, especially when accompanied by more severe complications, was associated with increased caregiver burden (1/2, 50%). Regarding patient comorbidities, one [59] of the 4 studies examining this factor found that the presence of comorbidities may be a risk factor for caregiver burden (1/4, 25%). Patient psychological factors were strongly associated with burden. All 5 studies [17, 41, 43–44, 49] assessing depression reported it was significantly associated with higher burden levels (5/5, 100%). Similarly, the single study [47] examining anxiety (1/1, 100%) and the single study [35] assessing general mental status (1/1, 100%) also reported significant associations with higher burden.

Functional status

The assessed functional measures included: Barthel Index (BI) for activities of daily living (19/35, 54%), mRS (2/35, 5%), NIHSS (5/35, 14%), FMA (2/35, 5%), cognitive function (4/35, 11%), number of functional impairments (1/35, 2%), and muscle strength (1/35, 2%).

Of the 19 studies that assessed patient functional status using the BI, seventeen studies [28, 30, 32, 34–35, 38, 43, 46, 48, 50–51, 53, 57] demonstrated a significant inverse correlation between BI scores and caregiver burden, indicating that greater functional dependence (lower BI scores) was associated with higher burden levels (17/19, 89%). Both studies assessing mRS [17, 31] identified scores ≥ 3 as predictive of increased burden (2/2, 100%).

Regarding NIHSS scores, three [17, 36, 47] of the 5 studies that evaluated this measure found that mild-to-moderate neurological impairment was associated with caregiver burden (3/5, 60%), whereas one study [37] reported severe impairment as a predictor (1/5, 20%). For motor function, both studies that employed the FMA [17, 58] showed consistent associations with burden (2/2, 100%). In terms of cognitive function, three of the four studies examining this domain [35, 38, 53] indicated that poorer cognitive performance was correlated with higher caregiver burden (3/4, 75%). The only study assessing muscle strength [41] suggested that reduced strength may contribute to burden (1/1, 100%).

Complications

Factors such as history of falls (1/35, 2%), pressure ulcers (stage ≥ 2) (1/35, 2%), and aphasia (1/35, 2%) were also examined.

No significant association was observed between caregiver burden and the occurrence of falls or pressure ulcers. In contrast, one study [17] reported that aphasia was associated with higher caregiver burden (1/1, 100%).

Behavior and lifestyle

Including whether drinking (1/35, 2%), feeding patterns (2/35, 5%), and the number of rehabilitation exercises per week (1/35, 2%).

The single study [44] assessing patient drinking history reported that it may be a risk factor for care burden (1/1, 100%). Of the 3 studies examining feeding patterns, two [36–37] indicated that this factor influenced care burden (2/3, 66%).

Family and social support factors

Family structure and relationships

These included the relationship with the patient (16/35, 45%), closeness to the patient (1/35, 2%), whether living with the patient (3/35, 8%), and the health level of other family members (1/35, 2%).

Regarding the relationship between primary caregivers and patients, of the 16 studies that assessed this factor, four [35, 39, 49, 60] found that a spousal relationship was an influencing factor for care burden (4/16, 25%). Another [18] reported that a daughter-in-law relationship was associated with the occurrence of burden (1/16, 6%), while a further two studies [51, 53] considered the caregiver-patient relationship to be influential but did not specify the type of relationship (2/16, 18%).

Additionally, the single study [30] that examined the health of other family members indicated that poor health among other family members may increase the caregiver burden (1/1, 100%).

State of the economy

Insurance type (1/35, 2%), medical payment method (2/35, 5%), monthly medical expenses (1/35, 2%), and family economic level (11/35, 31%) were examined.

Of the 2 studies assessing payment methods, one [59] suggested that out-of-pocket payment for medical expenses was associated with higher caregiver burden (1/2, 50%). Regarding expense levels, the single study [52] examining this factor identified monthly medical expenses exceeding 4,000 Chinese yuan as a contributing factor (1/1, 100%). In terms of income, one [33] of the 11 studies assessing family income reported that an average annual income below €10,000 was linked to increased burden (1/11, 9%). Four other studies [30, 42, 47, 58] in this group reported that lower family income was associated with burden but did not specify a clear income threshold (4/11, 36%).

Social resources

The place of residence (2/35, 5.7%), frequency of hospitalizations (2/35, 5.7%), and level of social support (12/35, 34.3%) were examined.

Of the 2 studies assessing caregiver residence, one [52] reported that primary caregivers residing in urban areas tended to experience lower levels of caregiving burden (1/2, 50%). A consistent finding across the 2 studies [55–56] that assessed hospitalization frequency was that a higher frequency was associated with increased burden (2/2, 100%). Furthermore, regarding social support, 9 [29, 33, 38, 42–43, 45, 52, 57, 59] of the 12 studies examining this factor indicated that greater social support was associated with reduced burden among primary caregivers (9/12, 58%).

Assessment tools

A total of 14 distinct assessment tools were employed across the 35 studies. Table 4 provides detailed characteristics of these caregiver burden instruments. Among the most frequently used scales were the ZBI, CBS, CBI, and CSI, all of which demonstrated good reliability.This review identified considerable heterogeneity in the dimensions, number of items, scoring systems, and focus of the assessment tools utilized. For instance, the ZBI emphasizes a comprehensive evaluation of emotional, psychological, relational, and overall burden, whereas the CBS primarily addresses objective burden related to economic and time-related life interference. While this heterogeneity reflects the multidimensional nature of caregiver burden, it also hinders direct comparison and synthesis of findings across studies, underscoring the lack of a standardized assessment consensus in this research domain.

Table 4.

Assessment tools

Name of assessment tool	Country	Author	Scoring system	Dimension number/dimension name	Number of items	Reliability and validity
Zarit burden interview(Chinese version)	China	Wang et al.[61]	Likert 5	2 / personal burden, Burden of responsibility, 3/ independent entries	22	Cronbach’s α 0.870; -
Zarit burden interview-12	Canada	Bédard et al.[62]	Likert 5	2 / Personal Strain, Role Strain	12	Cronbach’s α 0.830; -
Caregiver burden scale	Sweden	Gerritsen et al.[63]	Likert 5	2 / Relationship, Personal Consequences	13	Cronbach’s α 0.840; -
Caregiver burden inventory	Canada	Novak et al.[64]	Likert 5	5 / time-dependence burden, developmental Burden, physical burden, Social burden, Emotional burden	24	Cronbach’s α 0.920; -
Oberst caregiving burden scale	America	Oberst et al.[65]	Likert 5	2 / Time, Difficulty	15	Cronbach’s α 0.900; -
Bakas caregiving outcomes scale(Greek version)	Greece	Govina et al.[66]	Likert 7	3 / Physical health, social functioning, and subjective well-being	15	Cronbach’s α 0.830; -
Zarit burden interview(Thai version)	Thailand	Toonsiri et al.[67]	Likert 5	4 / personal strain, privacy conflict, guilt, and attitude of uncertainty	22	Cronbach’s α 0.820; -
Caregiver burden inventory(Chinese version)	China	Yue et al.[68]	Likert 5	5 / time-dependence burden, developmental Burden, physical burden, Social burden, Emotional burden	24	Cronbach’s α 0.920; Test-retest reliability 0.93; -
Caregiver reaction assessment scale	America	Given et al.[69]	Likert 5	5 / Disrupted Schedule, Financial Problems, Lack of Family Support, Health Problems, Caregiver’s Self-Esteem	24	Cronbach’s α 0.732; -
Caregiver Strain Index(Chinese version)	China	Chan et al.[70]	-	3 / social stress, economy stress, psychological stress	13	Cronbach’s α 0.800; -
Family burden scale of disease	India	Pai et al.[71]	Likert 3	6 / family economic burden, family daily life, family leisure and entertainment activities, family relationships, physical health of family members, and mental health of family members	24	Cronbach’s α 0.823; -
Bakas caregiving outcome scale	America	Bakas et al.[72]	Likert 7	4 / Social functioning status, emotional health, physical health, economics	15	Cronbach’s α 0.900; -
Self-designed questionnaire	China	Yang et al.[59]	Likert 5	4 / Physical, mental, social, economic	23	Cronbach’s α 0.840; Content validity 0.94
Sense of competence questionnaire	Netherlands	Scholte et al.[73]	-	3 / Consequences, Satisfaction, Competence	27	Cronbach’s α 0.830; Test-retest reliability 0.93; -

The content is (Note: "-", Not mentioned)

Discussion

This scoping review systematically examined the incidence, influencing factors, and assessment tools related to caregiving burden among primary family caregivers of stroke survivors. The findings revealed heterogeneity in reported incidence rates of caregiver burden. Influencing factors were identified across caregiver-related, patient-related, and family/social support domains, while multiple assessment tools were employed across studies. However, a notable limitation is the geographic imbalance of the included studies, with 28 of the 35 conducted in China. Consequently, the current evidence predominantly reflects the specific socio-cultural norms, family structures, and healthcare systems of China, which may limit the generalizability of the identified factors. Thus, the findings should be interpreted with caution.

Caregiver burden, as a multidimensional negative experience, is influenced by multiple factors and is significantly associated with psychological issues and diminished HRQoL among primary family caregivers. The review indicated that the age of primary family caregivers age—whether ≥ 60 years or ≤ 60 years—may influence burden levels, a finding consistent with previous research by Onyia et al. [74] and Cook et al. [75]. Although several studies support the role of age, the precise relationship remains unclear, and further evidence is needed to clarify its impact.

The gender of primary family caregivers was also identified as a significant factor, aligning with results from large-scale surveys on dementia caregivers. One study [76] reported that female caregivers experienced significantly higher burden levels than males, potentially due to gender-related role conflicts and time allocation differences. Similarly, Lindt et al. [77] observed that women are more likely to experience time-related pressure and emotional exhaustion during the caregiving process, resulting in a diminished quality of life. Regarding education level, most studies in this review suggested that primary family caregivers with a junior high school education or below were at higher risk of experiencing burden.

Due to limited health literacy and disease management skills, primary family caregivers with lower education levels often struggle to comprehend patients’ conditions, treatment regimens, and key care requirements. This can lead to misconceptions and practical errors, thereby increasing both psychological distress and caregiving workload [78]. Similarly, unemployed individuals exhibited significantly higher levels of caregiver burden, depression, and anxiety compared to their employed counterparts, reflecting their potentially poorer health-related quality of life. A cross-sectional study of elderly caregivers in Malaysia confirmed a significant association between unemployment and higher burden levels [79].

The presence of chronic illnesses in caregivers was also identified as a contributing factor. Chronic conditions may reduce physical capacity and energy reserves, making daily care activities more exhausting and stressful—a finding consistent with existing systematic reviews [80]. Furthermore, multiple studies [28, 30, 32, 58] indicated that primary family caregivers’ self-rated health is a predictor of subjective burden. Agyemang et al. [80] similarly, it was concluded that poorer self-rated health was associated with higher burden, depression, anxiety, and other adverse psychological outcomes.

Anxiety and depression are highly prevalent among caregivers and demonstrate a significant positive correlation with burden severity. Previous studies [81–82] reported that approximately 43% of primary family caregivers experience moderate anxiety and over 31% exhibit depressive symptoms, highlighting how emotional distress intensifies perceived caregiving burden.

Both average daily care hours and total duration of care were identified as significant contributors to caregiver burden. A systematic review [83] concluded that longer daily care hours are associated with higher burden levels—a finding consistent with the present review. Prolonged, high-intensity care increases physical exhaustion and emotional strain, leaving primary family caregivers with limited time for rest and self-care. Furthermore, the total duration of caregiving can also encroach upon time allocated for social activities, leisure, and even career development, which consequently exacerbates psychological stress and progressively diminishes the quality of life for primary family caregivers [84].

The availability of shared caregiving support from other family members or friends significantly.

alleviates the burden on primary family caregivers. Alshammari et al. [85] noted that sharing responsibilities reduces daily care time and physical demands on individual caregivers, thereby creating opportunities for recovery and social engagement.

Seventeen studies^{[28,30–32,34−35,38,43,46,48,50–51,53−57]} identified impaired activities of ADL as a key predictor of primary family caregivers burden. Patients’ functional limitations not only increase primary family caregivers’ actual caregiving time but also exacerbate burden by intensifying patients’ behavioral issues and primary family caregivers’ emotional distress. Hess et al. [86] reported that each 10-point decrease in ADL scores corresponded to a 3–4 point increase in ZBI scores.The NIHSS score was also associated with caregiver burden, with higher scores indicating greater stroke severity. A latent profile analysis by Lin et al. [87] revealed that patients with elevated NIHSS scores exhibited greater dependency in daily activities.

Studies have indicated that primary family caregivers who are spouses of the care recipients tend to bear a higher caregiver burden than those in other types of relationships. In a Dutch elderly sample, Oldenkamp et al. [88] observed that spouses reported greater subjective burden, which was closely linked to care recipients’ functional decline.

Nearly half of the included studies indicated that lower family income and diminished social support were associated with increased burden—a finding consistent with previous research demonstrating significant negative correlations between these factors and caregiver burden [83, 89].

Implications

In light of the multiple modifiable factors identified—such as average daily care hours and patient functional ability—the healthcare and social service systems should establish early screening and assessment mechanisms for primary family caregivers of stroke survivors. Interventions should be precisely targeted, for instance, providing respite care, skills training, and psychological support specifically to caregivers who are older, dedicate extensive hours to care, or have compromised personal health. Furthermore, strengthening connections to community resources can enhance caregivers’ social support and economic circumstances. These combined measures are essential for care burden and preventing the decline in health-related quality of life.

Strengths and limitations

This scoping review provides a systematic and comprehensive synthesis of the current status, assessment tools, and influencing factors of caregiving burden among primary family caregivers of stroke survivors. However, several limitations should be considered. First, the literature search was restricted to Chinese and English publications, which may introduce language bias. The geographical distribution of included studies is highly concentrated, predominantly from China, which may limit the generalizability of the findings to other cultural and healthcare contexts. Second, unpublished and grey literature were excluded, which may have led to selection bias. Furthermore, in the discussion, due to space constraints and the uneven distribution of available evidence, only the more frequently studied factors were examined in depth, which may affect the comprehensiveness and representativeness of the conclusions. Future research could broaden the scope of literature retrieval and conduct more in-depth analyses of the full range of influencing factors.

Conclusion

The incidence of caregiving burden among primary family caregivers of stroke survivors is relatively high, though reported rates vary across studies, likely due to differences in assessment tools, study designs, and sample characteristics. While a wide range of factors influencing caregiver burden have been identified, current evidence remains inconsistent across many of these factors, and most research has been conducted in Chinese populations. Future studies should expand the evidence base across diverse cultural settings. Numerous tools are currently available to assess caregiver burden in this population, providing diverse options for quantification; however, this variability hinders direct comparison of findings across studies. Future research should aim to promote the standardization of assessment tools and further explore the underlying mechanisms of caregiving burden.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

CNKI

China national knowledge infrastructure

VIP

Weipu Chinese journal service platform

CBM

China biomedical literature database

Author contributions

The conceptualization and design of this study were completed by Yang Hongwei and Ruan Lingmei. Material preparation, data extraction, and analysis were carried out by Li Zhongjian, Wu Xiaoqian, Zeng Mingyue, Li Xuechun, and other contributors. The initial draft of the manuscript was written by Yang Hongwei, and the manuscript was reviewed by Wang Juan, Ji Hui, and An Yaqiong. All authors have read and approved the final version of the paper.

Funding

This study was supported by the Panzhihua Key Laboratory of Characteristic Biopharmaceuticals and the Sichuan Province BIM+ Application and Intelligent Visualization Engineering Technology Research Center, with grant numbers TSSWYY-202506​and 25BIMYX0006, respectively.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. E-mail: 1911813548@qq.com.

Declarations

Ethics approval and consent to participate

The present study is a scoping review, therefore ethics approval and consent to participate are not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.