Telerehabilitation for Family Caregivers of Stroke Survivors: A Systematic Review and Meta-Analysis

Sun, Wen-Jing; Song, Yuan-Yuan; Wang, Cong; Jiang, Yan; Cui, Wen-Yao; Liu, Wen-Jie; Liu, Yan

doi:https://doi.org/10.1155/2023/3450312

Journal of Nursing Management

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Abstract Introduction Materials and Methods Results Discussion Conclusion Data Availability Conflicts of Interest Acknowledgments Supplementary Materials References Copyright Related Articles

Review Article | Open Access

Volume 2023 | Article ID 3450312 | https://doi.org/10.1155/2023/3450312

Telerehabilitation for Family Caregivers of Stroke Survivors: A Systematic Review and Meta-Analysis

Wen-Jing Sun,^1,2Yuan-Yuan Song,^2,3Cong Wang,^2,4Yan Jiang ,^2,4Wen-Yao Cui,¹Wen-Jie Liu,¹and Yan Liu¹

Academic Editor: Nabeel Al-Yateem

Received14 Mar 2023

Revised25 May 2023

Accepted01 Jun 2023

Published14 Jun 2023

Abstract

Aim. This systematic review aimed at evaluating the effectiveness of telerehabilitation on family caregivers of stroke survivors. Background. After discharge from the hospital, family caregivers of stroke survivors faced physical and psychological stress. Telerehabilitation seems crucial for family caregivers. However, the impact of telerehabilitation on family caregivers’ health outcomes remains to be studied. Evaluation. Six databases (PubMed, Embase, Cochrane Library, Web of Science, CINAHL, and PsycINFO) were searched up to June 16^th, 2022, without language restrictions. The Revised Cochrane Risk-of-bias Tool for Randomized Trials was used to assess the quality of included studies. The GRADEpro (Grading of Recommendations Assessment, Development, and Evaluation Profile) tools were applied to assess the synthesized evidence quality. The subgroup analysis was performed according to the intervention formats. Statistical analysis was conducted using Review Manager 5.3, and the publication bias was calculated by Stata 14.0. Key Issue(s). A total of 16 studies containing 992 caregivers were pooled in this systematic review. Telerehabilitation significantly improved the caregiver burden (SMD = −0.18, 95% CI = −0.35∼−0.02, , moderate-quality evidence), knowledge (SMD = 0.75, 95% CI = 0.03∼1.47, , very low-quality evidence), and competence (SMD = 1.35, 95% CI = 0.82∼1.88, , very low-quality evidence) but not depression (SMD = −0.04, 95% CI = −0.3∼0.21, , moderate-quality evidence), anxiety (MD = 0.68, 95% CI = −0.68∼2.04, , low-quality evidence), and self-efficacy (SMD = −0.30, 95% CI = −1.22∼0.61, , very low-quality evidence) in family caregivers of stroke survivors. The subgroup analysis demonstrated that multi-form telerehabilitation (SMD = 1.86, 95% CI = 1.32∼2.40, ) was significantly effective in improving caregiving competence. Conclusion. Telerehabilitation can effectively reduce the caregiver burden as well as improve the knowledge and competence of stroke caregivers. Implications for Nursing Management. The emergence of telerehabilitation can help relieve caregivers’ stress and provide a new form for nursing managers to make discharge plans for stroke.

1. Introduction

Stroke remains the second-leading cause of death and the third-leading cause of death and disability combined worldwide [1]. It is estimated that the total global direct and indirect costs of stroke are $891 ($746∼1077) billion, accounting for 1.12% of the global gross domestic product [2]. Almost 70%–80% of stroke survivors have complications such as cognitive impairment, motor dysfunction, and swallowing dysfunction [3]. In addition, 25%–50% of stroke survivors become partially or entirely dependent on others in activities of daily living [4]. According to a recent systematic review, the average medical cost of a stroke family is about 5,798.15 to 140,048 euros [5]. A series of stroke complications, massive demand for rehabilitation, and heavy economic pressure may overwhelm stroke survivors and family caregivers.

After discharge from the hospital, family caregivers such as parents, spouses, children, and siblings provide informal and unpaid care for stroke survivors. The lack of professional guidance and reasonable rehabilitation plans often lead to poor knowledge, belief, and behavior for caregivers and poor home rehabilitation effects for stroke survivors [6]. According to a survey, 82% of family caregivers provided stroke care for more than 8 hours a day [7]. This challenging care may bring adverse outcomes to family caregivers’ physical and mental health. A longitudinal study in Singapore showed that the health status of stroke caregivers gradually declined within 12 months after patients suffered a stroke [8]. Approximately 21.4% (95% [Confidence Interval, CI]: 11.6%∼35.9%) of family caregivers experienced anxiety symptoms, while 40.2% (95% CI: 30.1%∼51.1%) experienced depression symptoms during the period of caring for stroke survivors [9]. The vast majority of family caregivers felt lifestyle changes and faced varying degrees of caregiving burden [7]. To solve these problems, routine rehabilitation is carried out for stroke caregivers including on-site and face-to-face guidance such as outpatient follow-up, home visits, etc. [10]. Routine rehabilitation could help doctors comprehensively evaluate patients through visual touch and listening. However, according to a survey, stroke caregivers need to spend $1,167 on healthcare services, resulting in an increase of $726 in total home care costs. [11]. In addition, routine rehabilitation makes it difficult for nurses to effectively supervise the rehabilitation effects, resulting in discontinuity of care and adverse effects on stroke survivors and caregivers.

Therefore, the implementation of remote interventions may help satisfy the needs of family caregivers, providing them with stroke-related knowledge and skills to adapt to life and role changes. Telerehabilitation uses information and communication technology (telephone, mail, and video conferencing) and computer science technology (applets, websites, and mobile applications) to provide services remotely [12]. According to a practice guideline published by American Congress of Rehabilitation Medicine Stroke International Special Interest Group, telerehabilitation could benefit family caregivers in several ways, including (1) reduction of direct and indirect costs: despite the high costs of placing network devices at home, telerehabilitation reduces outpatient and round-trip costs; (2) breaking geographical restrictions: it provides more opportunities for patients in rural and remote areas and improves the accessibility of medical services; (3) providing prompt diagnosis and quick response: experts can use communication technology to achieve timely consultation and treatment; (4) reduction in the spread of infectious diseases such as COVID-19 [13].

Despite the various advantages of telerehabilitation, current research focuses too much on patient health outcomes, resulting in caregivers often being neglected. Multiple systematic reviews have demonstrated the effectiveness of telerehabilitation in enhancing patients’ motor function, generic quality of life, and activities of daily living [14, 15]. However, the vulnerability and sensitivity of stroke caregivers still deserve attention. There have been randomized controlled trials (RCTs) comparing the differences between telerehabilitation and routine rehabilitation for stroke caregivers [16–18]. Conflicting evidence on caregiver health outcomes has led to a lack of consistent findings and difficulties for healthcare practitioners to make appropriate judgments [19, 20]. Therefore, this study evaluated and synthesized evidence to explore the effectiveness of telerehabilitation on the health outcomes of stroke caregivers.

2. Materials and Methods

This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 checklist and was registered in PROSPERO (https://www.crd.york.ac.uk/prospero/) with a registration number of CRD42022358364.

2.1. Search Strategy

Six databases were comprehensively searched, including PubMed, Embase, Cochrane Library, Web of Science, CINAHL, and PsycINFO. Databases were searched up to June 16^th, 2022, without any language restrictions. The search strategy was designed based on the PICOS framework (e.g., P: stroke, family caregiver, informal caregiver, and carer). Free terms were employed to supplement the MeSH terms. The references of the included studies were manually searched to identify any additional studies. The complete list of search strategies is listed in Supplementary Table 1.

2.2. Eligibility Criteria

The inclusion criteria were as follows: (1) stroke survivors aged ≥18 years; (2) family caregivers such as parents, spouses, children, and siblings provided home care for stroke survivors; (3) telerehabilitation was applied to family caregivers of stroke survivors to provide them with caregiving skills or improve their health outcomes; (4) the interventions may include videoconferencing, telephone sessions, applets, virtual reality, etc., and the routine rehabilitation in the control group may include on-site and face-to-face rehabilitation; (5) outcomes reported caregiver burden, competence, knowledge, depression, anxiety, or self-efficacy; (6) RCTs. The exclusion criteria were as follows: (1) conference abstracts and posters; (2) protocols did not report results; (3) family caregivers received both telerehabilitation and on-site rehabilitation.

2.3. Study Selection and Data Extraction

Firstly, two reviewers used EndNote X9 to screen the searched records back-to-back and compared the records to reach an agreement. Any disagreements were resolved by a third reviewer. Secondly, two reviewers completed the data extraction independently. The extracted contents included author, year, country, sample size, age of patients, age of caregivers, interventions, intervention format, intervention duration, and outcomes. Lastly, the extracted results were cross-checked by two reviewers to determine the final results. Caregiver burden was identified as the primary outcome, while caregiving competence, knowledge, depression, anxiety, and self-efficacy were identified as secondary outcomes. The definition and evaluation methods of each outcome were elaborated in the previous protocol [21].

2.4. Quality Assessment

Two reviewers utilized the Revised Cochrane Risk-of-Bias Tool for Randomized Trials (ROB 2) to assess the quality of the included studies from five domains, including the randomization process, deviations from the intended interventions, missing outcome data, measurement of the outcome, and selection of the reported results. Overall bias was calculated according to the algorithm provided by the Cochrane Collaboration [22]. All disagreements were resolved by an expert in evidence-based medicine.

2.5. Data Synthesis and Analysis

Review Manager 5.3 was used to conduct the systematic review and meta-analysis. Since all outcomes in this study were continuous variables, the mean difference (MD) or standardized mean difference (SMD) with 95% CI was used to calculate the effects according to whether the same scale was employed. Data available from the included studies were processed to estimate missing values. The value less than 0.05 was considered statistically significant. The I² statistic was used to measure the heterogeneity of the included studies. The fixed effects model was utilized only if I² ≤ 50% with ; otherwise, the random effects model was utilized. The subgroup analysis was used to compare different intervention formats (single-form telerehabilitation and multiform telerehabilitation). The sensitivity analysis was conducted to test the robustness of results by changing effects model. The single-form telerehabilitation was defined as the use of only one remote intervention for stroke caregivers, while multiform telerehabilitation used two or more remote interventions for stroke caregivers, including network, videoconferencing, telephone sessions, applets, virtual reality, etc. The GRADEpro (Grading of Recommendations Assessment, Development, and Evaluation Profile) Guideline Development Tool (GDT) was applied to assess the quality of synthesized evidence. When at least ten studies reported the same outcome, the publication bias was evaluated using Stata 14.0. Egger’s test with considered the presence of publication bias.

3. Results

3.1. Search Results and Selection

There were 11,851 identified via six databases. No additional records were identified by manual search. After duplicated records were removed, 7081 records were sought for retrieval. Later, 6966 unrelated records, 36 records without caregiver outcomes, 27 protocols without results, 23 records did not receive telerehabilitation, 9 records received mixed interventions, and 4 non-RCTs were excluded. According to the eligibility criteria, three three-arm studies [16, 18, 23] and three four-arm studies [24–26] removed redundant arms. A total of 16 RCTs were pooled in this systematic review finally. The flow diagram of study selection is shown in Figure 1.

3.2. Study Characteristics

The characteristics of the included studies are described in Table 1. A total of 16 RCTs containing 992 caregivers were pooled in this systematic review. The included studies were published between 2007 and 2021 in America (n = 5), China (n = 3), Korea (n = 2), Australia (n = 2), Netherlands (n = 2), New Zealand (n = 1), and Malaysia (n = 1). One article was published in Korean [16], one in Chinese [20], and the others in English. Although one study was a study protocol registered in the United States National Library of Medicine, it reported detailed results and was therefore included in this systematic review [24]. The intervention formats of telerehabilitation varied among all the studies. The main intervention formats included web-based software, websites, e-mail, DVD, telephone sessions, video conferencing, and applets. Six studies used multiple intervention formats of telerehabilitation [17, 19, 20, 26, 27, 32], while the rest used only one intervention format [10, 16, 18, 23–25, 28–31].

3.3. Quality Assessment

According to ROB 2, the quality assessment of each study is displayed in Supplementary Figure 1. Of the 16 RCTs, 2 studies (12.5%) were at a low risk, 4 studies (25%) were at a high risk, and the rest (62.5%) remained some concerns. The summary evidence of a bias risk for each outcome is detailed in Supplementary Table 2. The GRADEpro GDT determined the moderate quality of synthesized evidence on caregiver burden and depression symptoms. Synthesized evidence of anxiety was rated as low quality. The evidence of caregiving knowledge, competence, and self-efficacy was rated as very low quality. Studies with a risk of bias and a small sample size were the main factors affecting the evaluation results.

3.4. Meta-Analysis of the Outcomes

3.4.1. Caregiver Burden

Twelve studies applied four scales (Caregiver Burden Index, Expanded Caregiver Burden Index, Zarit Burden Interview, and the Zarit Burden Interview-Short Form) to assess caregiver burden. Among these studies, one study treated caregiver stress as a classified variable, with 20.5% of caregivers in the intervention group and 34.8% of caregivers in the control group at a high-stress level [10]. Finally, 11 studies were enrolled in the meta-analysis. The fixed-effects model in Figure 2(a) shows that the caregiver burden is significantly lower in the telerehabilitation group than in the routine rehabilitation group (SMD = −0.18, 95% CI = −0.35∼−0.02, , I² = 36%). Sensitivity analysis showed that the results were not significant after changing into the random effects model (SMD = −0.16, 95% CI = −0.38∼0.06, , I² = 36%). The subgroup analysis in Supplementary Figure 2a shows that compared with routine rehabilitation, single-form telerehabilitation yields lower caregiver burden (SMD = −0.35, 95% CI = −0.58∼−0.12, , I² = 0%). There was no statistical difference between multiform telerehabilitation and routine rehabilitation in improving caregiver burden (SMD = 0.04, 95% CI = −0.34∼0.42, I² = 58%). Egger’s test observed no publication bias ().

(a)

(b)

(c)

(d)

(e)

(f)

3.4.2. Depression

Eight studies applied four scales (Center for Epidemiologic Studies Depression Scale, 10-item Center for Epidemiological Studies for Depression Scale, Hospital Anxiety and Depression Scale, and Patient Health Questionnaire-9) to assess depression symptoms. Because I² < 50% with , the random-effects model was used for a conservative estimate of pooled data. The meta-analysis in Figure 2(b) shows that the telerehabilitation group has no significant effect on depression symptoms to the routine rehabilitation group (SMD = −0.04, 95% CI = −0.3∼0.21, , I² = 45%). Sensitivity analysis showed that the result was stable. The subgroup analysis in Supplementary Figure 2b shows that compared with routine rehabilitation, neither single-form rehabilitation (SMD = −0.26, 95% CI = −0.63∼0.12, , I² = 50%) nor multiform rehabilitation was significant in improving depression symptoms (SMD = 0.20, 95% CI = −0.08∼0.47, , I² = 0%).

3.4.3. Anxiety

Three studies applied the Hospital Anxiety and Depression Scale to assess anxiety symptoms. Thus, MD was used to calculate the effect size. The fixed-effects model in Figure 2(c) shows that the telerehabilitation group has no significant effect on anxiety symptoms to the routine rehabilitation group (MD = 0.68, 95% CI = −0.68∼2.04, , I² = 0%).

3.4.4. Caregiving Knowledge

Three studies applied different scales (Kong’s Caregiving Knowledge Scale, Knowledge of Stroke Questionnaire, and Comprehensive Competence Assessment Questionnaire for Stroke Caregivers) to assess caregiving knowledge. The random-effects model in Figure 2(d) shows that the caregiving knowledge in the telerehabilitation group is significantly higher than in the routine rehabilitation group (SMD = 0.75, 95% CI = 0.03∼1.47, , I² = 79%). The high heterogeneity may result from different measurement tools.

3.4.5. Caregiving Competence

Three studies applied different scales (Six-item Care Giving Mastery Scale, Caregiving Competence Scale, and Comprehensive Competence Assessment Questionnaire for Stroke Caregivers) to assess the competence of family caregivers. The random-effects model in Figure 2(e) shows that the caregiving competence in the telerehabilitation group is significantly higher than that in the routine rehabilitation group (SMD = 1.35, 95% CI = 0.82∼1.88, , I² = 65%). Different measurement tools may be one of the potential sources of high heterogeneity.

3.4.6. Self-Efficacy

Four studies applied three scales (Self-efficacy Scale, Caregiving Self-efficacy Score, and General Self-efficacy Scale) to assess anxiety symptoms. The random-effects model in Figure 2(f) shows that the telerehabilitation group has no significant effect on self-efficacy to the routine rehabilitation group (SMD = −0.30, 95% CI = −1.22∼0.61, , I² = 89%). The high heterogeneity may result from different measurement tools.

4. Discussion

Previous studies paid more attention to the effects of telerehabilitation on stroke survivors. This is the first systematic review and meta-analysis focused on the impact of telerehabilitation on the health outcomes of stroke caregivers. Although some published systematic reviews attempted to compare the outcomes of stroke caregivers receiving telerehabilitation, they only performed descriptive analyses without further meta-analysis [33, 34]. This study pooled 16 studies and found that 3/4 of the studies implement telerehabilitation through websites and software, which demonstrated that more and more medical institutions tend to cooperate with Internet companies to build new platforms to realize medical modernization and intelligence. Stroke patients and caregivers can enjoy high-quality medical and nursing services without leaving home. Only RCTs were included in this study to ensure study quality and accuracy. However, 87.5% of the RCTs had some risk of bias due to poor design and missing data. The total sample size of the studies reporting anxiety, knowledge, competence, and self-efficacy was insufficient, resulting in an inferior quality of synthesized evidence for the four outcomes. Although the quality evaluation was rigorous, this study yielded some surprising results.

Moderate-quality evidence indicated that telerehabilitation can ease the burden and reduce the strain on stroke caregivers. A previous systematic review found that the caregiver strain index of stroke caregivers was comparable, which was consistent with the results of this study [34]. A qualitative study found that caregivers of stroke survivors were experiencing a stressful period [35]. New responsibilities leave family caregivers feeling resentful and guilty of self-sacrifice. Meanwhile, outpatient follow-up is stressful for stroke caregivers due to scheduling, transportation, and expenses. Telerehabilitation improved the feasibility and acceptability of the interventions. In Lelaurin’s study, 80% of stroke caregivers considered telerehabilitation very or even extremely useful [26]. However, the majority of caregivers receiving telerehabilitation interventions have a high level of education. For caregivers with low education levels and poor network resources, receiving telerehabilitation makes them feel burdensome instead. This problem is also a major problem that needs to be overcome when implementing telerehabilitation.

Very low-quality evidence suggested that family caregivers have a substantial demand for caregiving knowledge and skills, which can be solved by telerehabilitation. An evidence-based guideline for stroke caregivers recommended websites as critical platforms to provide caregivers with information about stroke treatment and prognosis (level 3) [36]. Zhao’s study suggested that the low competence of stroke caregivers is due to a lack of knowledge and skills [20]. Almost all 16 RCTs in this study mentioned the importance of improving the knowledge and skills of stroke caregivers, but only four assessed the results specifically. Thus, it is necessary to assess the knowledge and skills of stroke caregivers in various ways. After all, the knowledge and skills of caregivers directly affect the effects of home rehabilitation in patients with stroke.

Multiform telerehabilitation can improve caregiving competence. However, the effects of multiform telerehabilitation on depression were not significantly different from those of routine rehabilitation. Multiform telerehabilitation mainly provides interventions through at least two media to ensure patients and caregivers master knowledge and skills. This phenomenon indicates that multiform telerehabilitation has higher requirements for network equipment configuration than single-form telerehabilitation and routine rehabilitation. Unfortunately, no RCT has yet proven the hypothesis that multiform telerehabilitation may cause a waste of resources and increase the economic burden. In addition, more RCTs with direct and indirect comparisons between multiform telerehabilitation and single-form telerehabilitation are needed. In the near future, a network meta-analysis of multiform telerehabilitation, single-form telerehabilitation, and routine rehabilitation may be necessary.

The emotional state of stroke caregivers deserves attention, but it is often ignored. The current study cannot demonstrate the effectiveness of telerehabilitation in improving anxiety, depression, and self-efficacy. This finding did not mean that telerehabilitation cannot affect caregivers’ emotions. Due to the inconsistent duration of intervention, caregivers’ anxiety, depression, and self-efficacy may require long-term observation. Besides, limited studies also lead to nonstatistically significant differences. At present, telerehabilitation mainly provides caregiving knowledge and skills to help stroke survivors get better care and indirectly relieve the anxiety and depression of family caregivers. There is a lack of direct telerehabilitation interventions for caregivers’ anxiety and depression symptoms. Healthcare providers should pay close attention to the psychological and emotional changes of stroke caregivers for a long time and take timely treatment measures.

The prospect of telerehabilitation for family caregivers of stroke survivors is broad and promising. Nevertheless, some challenges come along (1) the education level and digital literacy of stroke caregivers need to be taken into account while implementing telerehabilitation; (2) healthcare facilities need to complete the mechanism of telerehabilitation supervision to ensure the safety and effectiveness; (3) remote consultation and therapies need to be provided based on caregivers’ physical and psychological stress. Most of the family caregivers in this study were aged between 25 and 84, indicating that the design of telerehabilitation should be more accessible and meet the personalized needs of different age groups.

Several limitations should be acknowledged in this systematic review. Firstly, most of the telerehabilitation programs were offered to stroke survivors and their family caregivers simultaneously, leading to the possibility of some interaction effects. Secondly, although we used SMD to combine the effect size, different measurement tools may bring potential heterogeneity. Finally, due to limited studies, subgroup analysis and sensitivity analysis were only performed in caregiver burden and depression. Thus, more high-quality RCTs should be carried out to support our results.

5. Conclusion

Providing telerehabilitation for family caregivers of stroke survivors can improve caregiver burden, knowledge, and competence. Multiform telerehabilitation plays a positive role in improving caregiving competence. High-quality studies and individualized telerehabilitation are needed to be tailed for family caregivers of stroke survivors.

6. Implications for Nursing Management

After stroke survivors are discharged from the hospital, their family caregivers typically take on the main caregiving role. Sudden caregiving task makes stroke caregivers more vulnerable to physical and mental stress, which is often neglected by medical staff. The emergence of telerehabilitation can help relieve caregivers' stress and improve their adverse outcomes. In addition, telerehabilitation provides a new form for nursing managers to make discharge plans for stroke.

Data Availability

The data supporting this study are from previously reported studies and datasets, which have already been cited.

Conflicts of Interest

The authors declare no conflicts of interest.

Acknowledgments

The authors thank the Evidence-Based Nursing Center of West China Hospital, Sichuan University, for their cooperation in completing this meta-analysis. This work was supported by the CAMS Innovation Fund for Medical Sciences (CIFMS) (no. 2021-I2M-C&T-A-023) and the 2021 Research Project of Chinese Nursing Association (no. ZHKYQ202101).

Supplementary Materials

Supplementary Table. 1. Search strategy. Supplementary Figure 1. Risk of bias graph. Supplementary Figure 2. Subgroup analysis. Supplementary Table. 2. Overall evidence quality of each outcome. (Supplementary Materials)

References

Gbd 2019 Stroke Collaborators, “Global, regional, and national burden of stroke and its risk factors, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019,” The Lancet Neurology, vol. 20, pp. 795–820, 2021.
View at: Publisher Site | Google Scholar
M. O. Owolabi, A. G. Thrift, A. Mahal et al., “Primary stroke prevention worldwide: translating evidence into action,” The Lancet Public Health, vol. 7, pp. e74–e85, 2022.
View at: Publisher Site | Google Scholar
D. Cao, X. Zhang, M. Liu et al., “Efficacy and safety of manual acupuncture for the treatment of upper limb motor dysfunction after stroke: protocol for a systematic review and meta-analysis,” PLoS One, vol. 16, no. 11, Article ID e0258921, 2021.
View at: Publisher Site | Google Scholar
H. G. Ugur and B. Erci, “The effect of home care for stroke patients and education of caregivers on the caregiver burden and quality of life,” Acta Clinica Croatica, vol. 58, pp. 321–332, 2019.
View at: Publisher Site | Google Scholar
J. Lucas-Noll, J. L. Clua-Espuny, M. Lleixà-Fortuño et al., “The costs associated with stroke care continuum: a systematic review,” Health Econ Rev, vol. 13, p. 32, 2023.
View at: Publisher Site | Google Scholar
S. Lin, C. Wang, Q. Wang et al., “The experience of stroke survivors and caregivers during hospital-to-home transitional care: a qualitative longitudinal study,” International Journal of Nursing Studies, vol. 130, Article ID 104213, 2022.
View at: Publisher Site | Google Scholar
Y. Han, Y. Liu, X. Zhang, W. Tam, J. Mao, and V. Lopez, “Chinese family caregivers of stroke survivors: determinants of caregiving burden within the first six months,” Journal of Clinical Nursing, vol. 26, pp. 4558–4566, 2017.
View at: Publisher Site | Google Scholar
W. F. W. Chong, L. H. Ng, R. M.-H. Ho et al., “Stroke rehabilitation use and caregiver psychosocial health profiles in Singapore: a latent profile transition analysis,” Journal of the American Medical Directors Association, vol. 22, pp. 2350–2357.e2, 2021.
View at: Publisher Site | Google Scholar
A. Z. Loh, J. S. Tan, M. W. Zhang, and R. C. Ho, “The global prevalence of anxiety and depressive symptoms among caregivers of stroke survivors,” Journal of the American Medical Directors Association, vol. 18, pp. 111–116, 2017.
View at: Publisher Site | Google Scholar
N. S. Redzuan, J. P. Engkasan, M. Mazlan, and S. J. F. Abdullah, “Effectiveness of a video-based therapy program at home after acute stroke: a randomized controlled trial,” Archives of Physical Medicine and Rehabilitation, vol. 93, pp. 2177–2183, 2012.
View at: Publisher Site | Google Scholar
B. Johnston, L. Wheeler, J. Deuser, and K. H. Sousa, “Outcomes of the kaiser permanente tele-home health research Project,” Archives of Family Medicine, vol. 9, pp. 40–45, 2000.
View at: Publisher Site | Google Scholar
K. E. Laver, Z. Adey-Wakeling, M. Crotty, N. A. Lannin, S. George, and C. Sherrington, “Telerehabilitation services for stroke,” Cochrane Database of Systematic Reviews, vol. 1, Article ID CD010255, 2020.
View at: Publisher Site | Google Scholar
E. Kringle, M. Trammell, and E. D. Brown, “American congress of rehabilitation medicine (ACRM) stroke international special interest group,” Archives of Physical Medicine and Rehabilitation, vol. 0003-9993, no. 23, 2023.
View at: Publisher Site | Google Scholar
J. Chen, W. Jin, X.-X. Zhang, W. Xu, X.-N. Liu, and C.-C. Ren, “Telerehabilitation approaches for stroke patients: systematic review and meta-analysis of randomized controlled trials,” Journal of Stroke and Cerebrovascular Diseases, vol. 24, pp. 2660–2668, 2015.
View at: Publisher Site | Google Scholar
B. León-Salas, Y. González-Hernández, D. Infante-Ventura et al., “Telemedicine for neurological diseases: a systematic review and meta-analysis,” European Journal of Neurology, vol. 30, pp. 241–254, 2023.
View at: Publisher Site | Google Scholar
C. G. Kim and H. A. Park, “Development and evaluation of a web-based education program to prevent secondary stroke,” c, vol. 41, pp. 47–60, 2011.
View at: Publisher Site | Google Scholar
L. L. Pierce, V. L. Steiner, S. A. Khuder, A. L. Govoni, and L. J. Horn, “The effect of a web-based stroke intervention on carers’ well-being and survivors’ use of healthcare services,” Disability & Rehabilitation: An International, Multidisciplinary Journal, vol. 31, pp. 1676–1684, 2009.
View at: Publisher Site | Google Scholar
M. V. Radomski, Impact of post-discharge Habit Training of Self Care Skills on independence, Caregiver burden, and Development of Automaticity for Survivors of Recent Stroke, University of Minnesota, Minneapolis, MN, USA, 2007.
M. Berg, M. P. Crotty, E. Liu, M. Killington, G. P. Kwakkel, and E. van Wegen, “Early supported discharge by caregiver-mediated exercises and e-health support after stroke: a proof-of-concept trial,” Stroke, vol. 47, pp. 1885–1892, 2016.
View at: Publisher Site | Google Scholar
Y. Zhao, X. Xie, J. Li, G. Li, L. Feng, and X. Kong, “Application of Internet combined with IMB model in nursing care of main caregivers of ischemic stroke patients,” Chinese Nursing Research, vol. 35, pp. 4114–4118, 2021.
View at: Publisher Site | Google Scholar
W. Sun, Y. Song, C. Wang et al., “Telerehabilitation programs for family caregivers of stroke survivors: a systematic review and meta-analysis,” 2022, https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=358364.
View at: Google Scholar
Cochrane Scientific Committee, “Risk of bias tools-current version of RoB 2,” 2019, https://www.riskofbias.info/welcome/rob-2-0-tool/current-version-of-rob-2.
View at: Google Scholar
A. T. Woodward, M. C. Fritz, A. K. Hughes et al., “Effect of transitional care stroke case management interventions on caregiver outcomes: the MISTT randomized trial,” Social Work in Health Care, pp. 1–14, 2021.
View at: Publisher Site | Google Scholar
Blanton, “Evaluation of a CarePartner-integrated telehealth rehabilitation program for persons with stroke,” 2016, https://clinicaltrials.gov/show/NCT02703532.
View at: Google Scholar
M. Harwood, M. Weatherall, A. Talemaitoga et al., “Taking charge after stroke: promoting self-directed rehabilitation to improve quality of life-a randomized controlled trial,” Clinical Rehabilitation, vol. 26, pp. 493–501, 2012.
View at: Publisher Site | Google Scholar
J. H. LeLaurin, I. M. Freytes, K. E. Findley et al., “Feasibility and acceptability of a telephone and web-based stroke caregiver intervention: a pilot randomized controlled trial of the RESCUE intervention,” Clinical Rehabilitation, vol. 35, pp. 253–265, 2021.
View at: Publisher Site | Google Scholar
S. Eames, T. Hoffmann, L. Worrall, S. Read, and A. Wong, “Randomised controlled trial of an education and support package for stroke patients and their carers,” BMJ Open, vol. 3, 2013.
View at: Publisher Site | Google Scholar
J.-I. Kim, S. Lee, and J.-H. Kim, “Effects of a web-based stroke education program on recurrence prevention behaviors among stroke patients: a pilot study,” Health Education Research, vol. 28, pp. 488–501, 2013.
View at: Publisher Site | Google Scholar
J. Chen, W. Jin, W. S. Dong et al., “Effects of home-based telesupervising rehabilitation on physical function for stroke survivors with hemiplegia A randomized controlled trial,” American Journal of Physical Medicine and Rehabilitation, vol. 96, pp. 152–160, 2017.
View at: Publisher Site | Google Scholar
H. Y. Cheng, S. Y. Chair, and J. P. C. Chau, “Effectiveness of a strength-oriented psychoeducation on caregiving competence, problem-solving abilities, psychosocial outcomes and physical health among family caregiver of stroke survivors: a randomised controlled trial,” International Journal of Nursing Studies, vol. 87, pp. 84–93, 2018.
View at: Publisher Site | Google Scholar
J. A. Kootker, C. M. van Heugten, B. Kral, S. M. C. Rasquin, A. C. Geurts, and L. Fasotti, “Caregivers’ effects of augmented cognitive-behavioural therapy for post-stroke depressive symptoms in patients: secondary analyses to a randomized controlled trial,” Clinical Rehabilitation, vol. 33, pp. 1056–1065, 2019.
View at: Publisher Site | Google Scholar
J. D. M. Vloothuis, M. Mulder, R. H. M. Nijland et al., “Caregiver-mediated exercises with e-health support for early supported discharge after stroke (CARE4STROKE): a randomized controlled trial,” PLoS One, vol. 14, 2019.
View at: Publisher Site | Google Scholar
F. S. Sarfo, U. Ulasavets, O. K. Opare-Sem, and B. Ovbiagele, “Tele-rehabilitation after stroke: an updated systematic review of the literature,” Journal of Stroke and Cerebrovascular Diseases, vol. 27, pp. 2306–2318, 2018.
View at: Publisher Site | Google Scholar
H. Tchero, M. Tabue Teguo, A. Lannuzel, and E. Rusch, “Telerehabilitation for stroke survivors: systematic review and meta-analysis,” Journal of Medical Internet Research, vol. 20, Article ID e10867, 2018.
View at: Publisher Site | Google Scholar
J. Luker, C. Murray, E. Lynch, S. Bernhardsson, M. Shannon, and J. Bernhardt, “Carers’ experiences, needs, and preferences during inpatient stroke rehabilitation: a systematic review of qualitative studies,” Archives of Physical Medicine and Rehabilitation, vol. 98, pp. 1852–1862.e13, 2017.
View at: Publisher Site | Google Scholar
C. van Heugten, A. Visser-Meily, M. Post, and E. Lindeman, “Care for carers of stroke patients: evidence-based clinical practice guidelines,” Journal of Rehabilitation Medicine, vol. 38, pp. 153–158, 2006.
View at: Publisher Site | Google Scholar

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Copyright © 2023 Wen-Jing Sun et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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