Self-management in adult patients after stroke –⁠ a review of self-management programs

Overview

Aim: The aim of the literature review was to identify existing self-management programs for adults after stroke and to describe their key characteristics, including program content, implementation methods, and tools used to evaluate results. The research question formulated according to the Participants–Phenomenon of Interest–Context (P-PI-Co) framework was: What self-management programs are intended for patients after stroke? Materials and methods: The literature review was based on a narrative synthesis of quantitative studies, which were identified through searches in the APA PsycINFO, Cinahl, Medline, ProQuest Central, SocINDEX and Web of Science databases between April and May 2025. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) methodological recommendations were used in the preparation of this review study. A total of 912 studies were identified, of which 10 were included in the review: eight randomized controlled trials, one quasi-experimental study, and one interventional cohort study. To assess the quality of the included studies, risk of bias assessment tools were used –⁠ RoB 2 for randomized studies and ROBINS-I for non-randomized studies. Results: The analysis identified 10 quantitative studies focusing on self-management programs for adults after stroke. These programs were designed with regard to the specific needs and settings of these patients. Seven programs were evaluated as effective or promising, particularly in terms of improving self-efficacy, quality of life, and selected clinical outcomes. Conclusion: Self-management programs can be an effective tool for supporting adults after stroke. These programs have the potential to improve coping with the consequences of stroke, overall health, and the patients‘ quality of life.

Keywords:

stroke – rehabilitation – community health services – self-management

This is an unauthorised machine translation into English made using the DeepL Translate Pro translator. The editors do not guarantee that the content of the article corresponds fully to the original language version

 

Introduction

Stroke is one of the leading causes of death and disability worldwide. According to 2021 data from the Global Burden of Disease Study 2021, stroke was the third leading cause of death, following ischemic heart disease and COVID-19, and caused 7.3 million deaths worldwide [1]. In the same year, 11.9 million new cases of stroke were diagnosed, and 93.8 million people were living with its consequences [1]. The economic burden of stroke is also significant—global costs were estimated at $891 billion in 2017 [2]. Projections from the World Stroke Organization indicate that stroke mortality is expected to increase by 50% between 2020 and 2050. At the same time, a 30% increase in the number of disability-adjusted life years (DALYs) is projected [3]. With the growing number of stroke survivors, the European Stroke Action Plan (ESAP) 2018–2030 emphasizes the need to offer all patients discharged from the hospital effective support in the area of self-management (SM) to cope with the long-term consequences of the disease [4].

Self-management is an active approach in which patients learn how to function as well as possible despite the physical and psychological limitations caused by the disease [5]. The goal of SM is to improve quality of life, reduce the risk of complications, and minimize the need for acute medical care. The forms and scope of SM support may vary depending on professional recommendations, individual preferences, the experiences of patients and their families, and the organization of care and rehabilitation at a specific healthcare facility [6]. In the literature focused on chronic diseases, SM traditionally focuses on improving patients’ ability to manage symptoms and daily limitations associated with chronic conditions such as diabetes or arthritis. Although the positive effects of SM on health behaviors are well documented, systematic research into these approaches for individuals with long-term disabilities following a stroke has only recently begun.

Among the best-known and most recognized programs is the Chronic Disease Self-Management Program (CDSMP), which has repeatedly demonstrated improvements in physical and emotional health, self-efficacy, and quality of life, while also contributing to reduced healthcare utilization among the chronically ill [7].

Education in the context of MS develops patients’ practical skills for symptom management and decision-making, and includes medical MS (treatment adherence, symptom management, medication, physical activity), role-based MS (adaptation of lifestyle and social interactions), and emotional MS (coping with the emotional impact of the disease and planning adaptive strategies). The programs utilize behavioral and cognitive techniques, such as problem-solving, goal-setting and action planning, motivational interviewing, cognitive restructuring, and training in social and communication skills. The goal is to develop the patient’s ability to solve problems, make decisions, seek out resources, build a collaborative relationship with healthcare providers, and implement decisions [8].

SM programs for adult patients after stroke are primarily based on Bandura’s social-cognitive theory [9] and promote active patient involvement, self-efficacy, and a proactive approach to rehabilitation and managing daily life after stroke. Understanding the effectiveness of these programs in adult stroke patients is essential for optimizing follow-up care and improving patients’ quality of life. Current evidence, including randomized controlled trials (RCTs) and qualitative studies, suggests that SM programs improve motor and cognitive abilities, self-efficacy, symptom management, and adaptation to life roles, while also promoting long-term patient participation in rehabilitation and reducing the risk of relapse or complications.

In our review, we focused exclusively on SM programs designed for adults after stroke, which reflect the specific needs of this population. The aim of the review is to identify existing SM programs and their effectiveness and to describe their key characteristics, including content, implementation methods, and the effectiveness indicators used.

 

Data Set and Methodology

Methodology

The systematic review was conducted in accordance with the methodological guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) [10] (Fig. 1). The review was conducted according to the following steps:

1. formulation of the research question;

2. establishing criteria for study inclusion;

3. development and implementation of a search strategy;

4.
selection of relevant studies/assessment of risk of bias;

5. data extraction;

6. Analysis and presentation of results.

Formulation of the research question

Based on the defined objectives of the systematic review, the following research questions were formulated:

1.
What rehabilitation programs have been developed and implemented for adults after stroke as part of follow-up care?

2.
What is the effectiveness of these programs in improving post-stroke follow-up care outcomes?

3.
What are the key characteristics of these SM programs for adults, including content, implementation methods, and the effectiveness indicators used?

 

Inclusion and exclusion criteria for studies

The Participants–Phenomenon of Interest–Context (P-PI-Co) mnemonic framework was used to identify relevant criteria.

    Participants: The target population consisted of adult patients who had experienced a stroke of any type or severity and who had undergone any form of intervention promoting self-management at any time following the stroke. Studies involving individuals under the age of 18 or studies that used self-management exclusively for stroke prevention were excluded from the review.

    Phenomenon of Interest: Studies utilizing SM strategies individually or in a group setting were included. Studies focused exclusively on psychosocial and/or behavioral interventions without targeting SM-related behaviors were not included.

    Context: Studies conducted in the context of follow-up care—in the long-term period following a stroke or in the chronic phase—were included.

    Study Design: No restrictions were imposed regarding the type of quantitative study design. The search included peer-reviewed quantitative studies in English that met the specified criteria and were published between 2015 and 2025. Qualitative studies, grey literature, including dissertations, study protocols, discussion papers, reviews, editorials, conference abstracts, books, reports, and expert opinions were not included.

 

Search strategy

The following keywords and combinations thereof were used to search for studies: (stroke OR cerebrovascular accident OR cerebrovascular disease OR ischemic stroke OR hemorrhagic stroke OR CVA OR hemiplegia OR acquired brain injury OR cerebral stroke) AND (self-management program OR recovery self-management OR self-management support OR rehabilitation self-management OR post-stroke self-management) AND (long-term OR stroke care OR post-stroke care OR community health services).

The literature search was conducted between April and May 2025 and covered the period from 2015 to April 2025. For the purpose of study selection, inclusion and exclusion criteria were established, relevant search terms were identified, and the following databases were selected: Medline (OvidSP), Cinahl Plus with Full Text (EBSCOhost), APA PsycINFO (EBSCOhost), SocINDEX with Full Text (EBSCOhost), Web of Science Core Collection (Clarivate Analytics), and ProQuest Central (ProQuest). The search terms were adapted for each database and pertained to adult patients after stroke and stroke management programs in follow-up care. The terms were applied to article titles, abstracts, and keywords and supplemented with MeSH medical terms. Term combinations were performed using the Boolean operators “AND” and “OR.” The search was limited to the English language and a specified time period.

Data were systematically extracted by two independent researchers (R.B., E.G.) in accordance with the PRISMA diagram (Fig. 1).

Assessment of risk of bias

To assess the effectiveness of rehabilitation programs for adults after stroke, studies evaluated a wide range of clinical and functional domains using standardized measurement tools. An overview of the most frequently assessed domains and corresponding tools is provided in Table 1 [7,11–19]. Some instruments were repeated across programs, suggesting consensus regarding key aspects of SM following stroke. Differences lie in the methodology and risk of bias in the studies, which directly influence the strength of the evidence regarding their effectiveness. Eight studies had an RCT design, and two studies were non-randomized (non-RCT). The risk of bias assessment showed that five studies (50%) were classified as having some concern, three studies (30%) as having a low risk of bias, and two non-randomized studies (20%) as having a serious risk of bias. No critical risk of bias was identified in any of the included studies (Tables 2, 3). Risk of bias assessments were conducted using the standardized Cochrane ROB 2 [20] tool for RCTs and the ROBINS-I [21] tool for non-RCTs.

The assessment, evaluation of risk of bias, and data extraction were performed by two researchers (R.B., E.G.), with the full texts of selected sources analyzed for final inclusion in the review. After the search was completed, quantitative studies published in English were included in the analysis. Descriptive data were extracted from each study, including: author/year/country; program name; study objective; study design; target group of the SM program; key interventions and duration of the SM program; number and age of participants at the time of the study; details of data collection and evaluation of SM program outcomes, including evaluation tools.

 

Results

A total of 912 studies were identified. A total of 10 quantitative research studies focusing on SM programs for adults after stroke and published between 2016 and 2024 were included in the literature review (Table 4), of which eight studies had an RCT design. In addition, one quasi-experimental study and one intervention cohort study were identified. In all studies, sampling was conducted using purposive sampling. The studies originated from China (n = 3), the United States (n = 3), the United Kingdom (n = 2), Belgium (n = 1), and Italy (n = 1). Across the analyzed studies, the age range of participants ranged from 18 to 95 years. The average age of participants in the studies ranged from 60 to 70 years. The number of program participants ranged from 24 (iSMART [14]) to 1,040 (IPCAS [17]). The total number of participants across the 10 programs was 2,552. We analyzed a total of 10 studies focusing on SM programs for adults after stroke.

 

Theoretical foundations

A common feature of the analyzed programs is an emphasis on multidisciplinary teams and a focus on improving quality of life. Self-efficacy assessment was a key element in most of these SM programs (Table 4). The Stroke Self-Efficacy Questionnaire (SSEQ) is widely used in these studies to assess self-efficacy in patients after a stroke. An interesting finding regarding the analyzed SM programs for adults is the repeated use of the principles and structure of the program commonly known as the Chronic Disease Self-Management Program (CDSMP). This globally recognized framework served as the basis or source of inspiration for the LAY [11], SUCCEED [18], and IPASS [7] programs. Bandura’s theory of self-efficacy and outcome expectations (as a key component of the social-cognitive framework [self-efficacy theory]) [9] formed the basis for programs such as SESSMP [15], COMBO-KEY [16], and iSMART [14]. In addition, the COMBO-KEY program [16] utilized principles of individual health coaching and support. The COM-B model was used in the IPCAS program [17], specifically as “My Life After Stroke” (MLAS), which is based on specific philosophies and theories, including the narrative approach, social learning theory, and cognitive-behavioral theory. An adaptation of the Person-Environment-Occupational Performance (PEOP) model was used in the IPASS [7] and iSMART [14] programs.

 

Form of Intervention Delivery and Staffing

The format of intervention delivery varied across programs. Most programs combine modal approaches, such as individual sessions, group sessions, and digital/telephone support. Support materials used within the interventions included workbooks, manuals, and digital platforms, which typically reinforce learning and skill retention (Table 4).

Teams include various healthcare professionals (nurses, physicians, therapists/occupational therapists, speech-language pathologists, physical therapists), community workers, as well as trained volunteers or peer facilitators, reflecting an effort to provide broader, community-based support. Most of these programs include an educational component that teaches patients about their condition, risk factors, and self-management strategies. Training in skills to address common problems and challenges associated with life after a stroke is a key component of self-management programs for adults.

 

Program Success and Community Utilization

The LAY program [11] has been shown to be effective in improving self-efficacy, mental health, and ADL. SM BRIDGES [12] improved self-efficacy and functional capacity, although the differences were not statistically significant. STROKE COACH [13] showed promising results in reducing stroke recurrence and improving adherence and quality of life in stroke patients. The iSMART program [14] is feasible and can improve self-efficacy in the area of stroke management. SESSMP [15] led to improvements in self-efficacy, outcome expectations, and satisfaction with behavior implementation in the area of stroke management. COMBO-KEY [16] demonstrated efficacy—it improved self-efficacy, satisfaction with behavior, health-related quality of life (HRQoL), and reintegration. IPCAS [17] showed no measurable effect; a primary care model with a broad target population is likely ineffective. SUCCEED [18] did not improve blood pressure control compared to usual care in a disadvantaged population. IPASS [7] showed promising results in improving self-efficacy and coping with the consequences of stroke. PCSMEI [19] led to higher levels of self-efficacy and greater independence in ADLs, as well as lower rehospitalization rates compared to the control group. An analysis of the studies confirms that programs supporting individuals after stroke are successfully implemented in community settings.

The LAY [11], COMBO-KEY [16], SESSMP [15], PCSMEI [19], IPASS [7], STROKE COACH [13], and iSMART [14] programs were evaluated as effective or promising in terms of improving self-efficacy, quality of life, or clinical outcomes. In contrast, the IPCAS [17], SUCCEED [18], and, to some extent, SM BRIDGES [12] programs were ineffective or showed no statistically significant improvement compared to standard care (Table 5).

 

Context and Focus of the Studies

There are differences in the composition of CHW programs for adults depending on the type of disease. Our aim was to focus exclusively on patients after stroke, on the program’s placement within the healthcare system, and on the level of involvement of healthcare professionals.

CHW programs for adults after stroke use multimodal strategies to support patients in managing their chronic condition. They focused on the comprehensive management of the health, emotional, and social aspects of life. A central element was the promotion of self-efficacy (empowerment), which leads to improved participation in daily activities and an overall increase in quality of life. Within the programs, patients acquired practical skills through problem-solving in groups as well as during individual sessions.

Digital platforms and remote interventions are increasingly coming to the forefront. Within SM programs, the web platforms beroertecoach.be and STROKE COACH [13], as well as the CommCare mobile app for systemic support in the SUCCEED program [18]. These systems and other programs utilized various forms of remote communication, including video conferencing for group and individual sessions (iSMART [14]) and regular telephone follow-ups for aftercare (PCSMEI [19]). Regular content was delivered via SMS messages (iSMART [14]). Videos or DVDs featuring the stories of other patients were used to model successful coping and share experiences (COMBO-KEY [16], SESSMP [15], PCSMEI [19]).

A key and recurring intervention was the setting of individual goals with the help of trained professionals. Based on these goals, a specific action plan was created to achieve them, which allowed the patient to take active control of their life.

Workbooks and manuals, tools that served as practical guides for managing one’s own problems, also provided space for recording personal goals and reflecting on progress made (SESSMP [15], BRIDGES [12]). They provided support and included stories, activities, ideas, and solutions from others who had themselves experienced a stroke (BRIDGES [12]). These materials often contained detailed “step-by-step” instructions for practicing self-management skills (COMBO-KEY [16]). Manuals included topics covered in group sessions and forms for action plans (LAY [11]). Interactive discussions took place, focusing on knowledge, goals, and fears; identifying barriers; evaluating achieved goals; discussing plan implementation; sharing experiences; providing encouragement; and practicing practical skills.

Discussion

There is a great need to develop programs that support the goal of helping individuals lead healthy and active lives and fully participate in society after a stroke. This review was conducted to present the latest evidence on the existence of stroke rehabilitation programs for adults focused on stroke survivors. The goal of CHM is not merely to manage symptoms, but to learn to live with a chronic illness—that is, to function as well as possible given the challenges life presents, to achieve the things we want to do, and to find joy in life. A healthy life in the context of chronic illness means seeking physical and mental balance and the ability to adapt to these challenges [5]. A common element in the majority of studies was the promotion of self-management and self-efficacy. All programs sought to actively involve patients in managing their health after a stroke. Self-efficacy was the most frequently measured domain, along with quality of life. The most commonly used questionnaire, the SSEQ, was developed by Jones F., Partridge C., and Reid F. in 2008 [22]. The SSEQ questionnaire has been culturally adapted and validated in many countries, e.g., in Arabic [23], Romanian [24], and Swedish versions [25]. While a systematic review [26] states that SM programs for adults after stroke contribute to improved quality of life and self-efficacy, a more recent systematic review [27] reached different conclusions—these programs do not significantly improve self-efficacy and have only a small effect on quality of life. This may be due to limitations, including the heterogeneity of the interventions, outcome measures, target behaviors, time since stroke onset, and methods and timing of outcome measurement, as well as the number of studies analyzed, which differed between these two reviews. Review [26] included 14 studies with a total of 1,863 participants; review [27] included 44 RCTs with 5,931 participants. The LAY [11], SUCCEED [18], and IPASS [7] studies used the CDSMP framework as a basis or source of inspiration for their SM programs designed for post-CMP patients, which systematically incorporates self-efficacy theory. It was developed at Stanford University by Lorig et al. [28]. The CDSMP program aims to improve self-management behaviors for chronic diseases, enhance self-efficacy, and improve health-related outcomes in people with chronic diseases [29].

Self-management programs for adults after stroke have been implemented in community settings, either partially or fully. This aligns with findings suggesting that community settings may be more suitable for facilitating self-care strategies [26,30,31]. Self-efficacy in participation is significantly associated with the level of participation among community-dwelling patients who have experienced mild or moderate stroke. Rehabilitation programs may be more effective if they include participation-focused strategies aimed at enhancing self-efficacy, which can facilitate recovery and reintegration into society [32]. In our review, the COMBO-KEY program [16] listed social reintegration as a secondary outcome, and the study authors described improvements in this area. In contrast, IPCAS [17] mentions participation as a primary outcome in its objectives, yet its abstract does not include a positive conclusion regarding improvements in social participation or reintegration. Within 4 years of the onset of CMP, more than 30% of CMP survivors report persistent limitations in participation (e.g., difficulties with autonomy, engaging in social roles, or fulfilling them) [33]. Further high-quality research is needed that focuses primarily on social participation [34].

Technology plays a key and increasingly important role in supporting home -⁠ and community-based rehabilitation following stroke [35] and for patients with multiple comorbidities [36]. Digital literacy is clearly linked to the effective use of information and communication technologies, which have been shown to promote the physical and mental well-being of older adults [37]. The authors of this review state that further assessments and studies of digital literacy among older adults, which overcome the limitations of existing measurement methods, would allow for better allocation of support and resources to meet the diverse healthcare needs of this growing but vulnerable population group. According to systematic reviews [38] and [39], text messages were effective, even as a low-cost solution; these results directly support and complement our findings regarding their use and potential in self-management programs for individuals after a stroke. Seven self-management programs for adults after a stroke are generally effective and applicable. Much depends on the study design, the comprehensiveness of the programs, and the professionals involved in the program. Furthermore, the significant role of peers with experience of stroke was described, particularly in the subsequent recovery phase; our findings are consistent with the review [40]. The average age of participants in SM programs was 60–70 years; it is evident that the SM programs we analyzed do not emphasize age distribution when applying SM programs for adults. Although it is clear that the incidence of stroke among young adults is on the rise [41], it appears that SM programs for adults have been generalized to the general population, rather than taking into account the age and needs of younger adults after a stroke, who have different needs due to their age [42]. An individualized approach is essential if we are to achieve the best possible outcomes.

Self-management programs for adults have employed SM strategies for managing stroke, including lifestyle (physical activity and exercise), social support (support from family and caregivers), communication (communication and coordination among all team members, including the patient, are considered absolutely essential), knowledge and information (recommended information on available community resources and patient education), and goal-setting strategies currently recommended by clinical guidelines for post-CMP rehabilitation [33]—this finding correlates with the results of the review [40]. SM programs for adults after stroke included in our review show considerable variability in terms of effectiveness, duration, type of interventions, patient participation rates, and number of participants.

The effectiveness of SM programs for adults depends on patient participation. The SUCCEED study [18] faced low participation in the SM component (CDSMP), with only 14.5% of participants receiving the full intended dose of the intervention. However, individuals with a higher number of clinic and home visits, moderate disability, and later enrollment in the study (i.e., after incentives and transportation began to be offered) participated in more CDSMP sessions. Conversely, participants with higher chaos scores participated in fewer CDSMP sessions. These findings suggest that addressing key social determinants of health, such as transportation and financial barriers, can significantly increase participation in SM programs. This supports the finding that offering incentives, including financial rewards, significantly increases willingness to participate in SM programs for adults [43].

To ensure more stable results that persist even after the intervention ends, it is essential to test and investigate the optimal duration and frequency of program use in the future. This will allow for a better understanding of how to sustain the achieved improvements in the long term, rather than only during the active intervention period.

The success of SM programs for adults lies primarily in the active engagement of stroke survivors, leading to targeted and structured changes in behavior and thinking, and in the application of knowledge and skills, rather than merely in the passive transfer of information.

Based on the results of this review, we recommend exploring the potential and cost-effectiveness of digital SM programs for adults by comparing them with face-to-face interventions.

In order to effectively compare the results of SM programs for adults across studies, standardizing measurement outcomes is a priority. Only in this way can we arrive at robust, generalizable evidence for clinical practice.

 

Limitations

The main limitation of this review stems from the chosen method of data synthesis. Due to significant methodological heterogeneity among the primary studies, a meta-analysis was not conducted. Key components and theoretical mechanisms of SM programs for adults were identified through narrative analysis (Table 4).

Limitations encountered in the programs included high staff turnover, which complicated and increased the costs of necessary training. Other limitations in study design included short participant follow-up periods, small sample sizes, and the fact that participants were sometimes recruited from only one institution, which limited the generalizability of the results.

 

Conclusion

In our review of SM programs for adult patients after stroke, we concluded that improving the quality of life for stroke patients is possible primarily through an individualized approach, targeted patient support, multidisciplinary team collaboration, and an effective combination of various approaches and interventions. The analyzed SM programs included a range of elements and strategies aimed at supporting patients in managing the long-term consequences of stroke and facilitating their active participation in home, work, and community life. An analysis of 10 selected self-management programs for adults revealed an effort to address the complex and long-term needs of the post-stroke population. A key finding is the dominant role of self-efficacy theory as the theoretical foundation of most successful interventions, underscoring the importance of strengthening patients’ belief in their own abilities. Programs often share common effective components, such as education, goal setting, action planning, and problem-solving; however, their specific implementation, delivery methods (ranging from in-person meetings to modern digital platforms), and intensity vary considerably. The rise of digital and technology-enhanced programs offers promising opportunities to improve the accessibility, scalability, and personalization of care, but requires careful consideration of the challenges associated with the digital divide and the need to preserve the human element of support. Future research should focus on the long-term effectiveness and sustainability of interventions.

 

Funding

This article did not receive any specific funding from any funding agency, commercial, or nonprofit sector.

 

Author contributions

Study design and concept, data analysis and interpretation (E.G. and R.B.), manuscript preparation and final revision of the article (R.B.), critical review of the manuscript (E.G. and R.B.).

 

Conflict of Interest

The authors declare that they have no conflict of interest regarding the subject of the study.

 

	Self-efficacy	Quality of life	Functional status, ADL	Participation, Reintegration	Impact of stroke	Mental status	Clinical indicators
LAY [11]	SSEQ	SF-12/SF-6D	MBI			GDS
BRIDGES [12]	SSEQ	SF-12/SF-6D	NEADL			HADS
STROKE COACH [13]		EQ-5D-5L	mRS				SCORE
iSMART [14]	PS-SES, PROMIS-SE
SESSMP [15]	SSEQ
COMBO-KEY [16]	SSEQ	SSQOL		RNLI
IPCAS [17]		EQ-5D-5L			SIS
SUCCEED [18]		SF-12/SF-6D				PHQ-9	SBP, Non-HDL, HbA1c, CRP, IPAQ
IPASS [7]		WHOQOL-BREF		CPI, RNL	SIS
PCSMEI [19]	SSEQ		MBI

Table 1. Overview of the most frequently assessed domains and tools used in SM programs following CMP.

ADL –⁠ activities of daily living; CPI –⁠ community participation indicators; EQ-5D-5L –⁠ EuroQol-5 Dimension; GDS –⁠ Geriatric Depression Scale; HADS –⁠ Hospital Anxiety and Depression Scale; IPAQ –⁠ International Physical Activity Questionnaire; MBI –⁠ Modified Barthel Index; mRS –⁠ Modified Rankin Scale; NEADL –⁠ Nottingham Extended Activities of Daily Living Scale; PHQ-9 –⁠ Patient Health Questionnaire-9; PROMIS-SE –⁠ Patient-Reported Outcomes Measurement Information System's Self-Efficacy; PS-SES –⁠ Participation Strategies Self-Efficacy Scale; RNL –⁠ Reintegration to normal living; RNLI –⁠ Reintegration to Normal Living Index; SF-12/SF-6D –⁠ Short-Form Health Survey; SBP –⁠ systolic blood pressure; SCORE –⁠ Systematic Coronary Risk Evaluation; SIS –⁠ Stroke Impact Scale; SM –⁠ self-management; SSEQ –⁠ Stroke Self-Efficacy Questionnaire; SSQOL –⁠ Stroke Specific Quality of Life Scale; WHOQOL-BREF –⁠ WHO Quality of Life Scale

 

Author, year, country	1. Bias due to the randomization process	2. Bias due to deviations from the intended interventions	3. Bias due to missing outcome data	4. Bias due to outcome measurement	5. Bias due to selection of the reported result	Overall risk of bias
Jones et al., 2016, UK, BRIDGES [12]	low risk of bias	low risk of bias	low risk of bias	low risk of bias	low risk of bias	low risk of bias
Li et al., 2024, US, ISMART [14]	some concerns	some concerns	some concerns	low risk of bias	low risk of bias	some concerns
Lo et al., 2018, China, SESSMP [15]	low risk of bias	low risk of bias	low risk of bias	low risk of bias	low risk of bias	low risk of bias
Lo et al., 2023, Hong Kong COMBO-KEY [16]	low risk of bias	low risk of bias	low risk of bias	low risk of bias	low risk of bias	low risk of bias
Mullis et al., 2024, UK, IPCAS [17]	low risk of bias	some concerns	some concerns	low risk of bias	low risk of bias	some concerns
Towfighi et al., 2021, US, SUCCEED [18]	low risk of bias	some concerns	low risk of bias	low risk of bias	low risk of bias	some concerns
Wolf et al., 2016, US, IPASS [7]	low risk of bias	some concerns	some concerns	low risk of bias	low risk of bias	some concerns
Chen et al., 2018, China, PSCMEI [19]	low risk of bias	some concerns	low risk of bias	low risk of bias	low risk of bias	some concerns

Table 2. Overview of Risk of Bias (ROB) 2.

 

Author, year, country, program	1. Bias due to confounding factors	2. Bias due to participant selection	3. Bias due to classification of interventions	4. Bias due to deviations from intended interventions	5. Bias due to missing outcome data	6. Bias due to outcome measurement	7. Bias due to selection of the reported outcome	Overall risk of bias
Messina et al., 2020 Italy, LAY [11]	serious risk of bias	serious risk of bias	low risk of bias.	some concerns	some concerns	low risk of bias	low risk of bias	serious risk of bias
Kamoen et al., 2020, Belgium, STROKE COACH [13]	serious risk of bias	serious risk of bias.	low risk of bias	some concerns	some concerns	some concerns	low risk of bias	serious risk of bias

Table 3. Overview of the ROBIN-1 risk of bias.

 

Author (year, country)	Program name	Study type	Target group (number, age)	Program objective	Duration and form of intervention	Key interventions	Results and tools
Messina et al. (2020, Italy) [11]	LAY	Quasi-experimental	185 patients after stroke, 18+, mean age of the experimental group 69.3 years	to increase self-efficacy and improve quality of life after stroke	6 group + 2 individual sessions	manuals, action plans, fall prevention	SSEQ, SPPB, MBI, SF-12, GDS
Jones et al. (2016, UK) [12]	BRIDGES SMP	Cluster-RCT	78 patients after stroke, mean age of the intervention group 61.8 years	support for individual self-management	12 weeks, individual sessions	7 principles of self-management, workbook	SAQOL, NEADL, SSEQ, HADS, SF-12
Kamoen et al. (2020, Belgium) [13]	STROKE COACH	Cohort intervention	147 patients after ischemic stroke, mean age 66.6 years	improve control of risk factors	1 educational session + 4 video calls	coach and digital platform	SCORE, mRS, EQ-5D-5L
Li et al. (2024, USA) [14]	iSMART	pilot RCT	24 patients, mean age 59 years	self-management support, increased self-efficacy	12 weeks, video + SMS	psychoeducation, coaching, reports	PS-SES, PROMIS-SE, FIM, AIM, IAM
Lo et al. (2018, China) [15]	SESSMP	RCT	128 patients, mean age 67.5 years	effect of self-efficacy on recovery	4 weeks (in-person visits, group sessions, phone calls)	peer models, videos, workbook	SSEQ, SSMOES, SSBPS
Lo et al. (2023, China) [16]	COMBO-KEY	RCT	134 patients, mean age 64.1 years	promotion of self-efficacy and self-management behaviors	8 weeks, in-person visits + phone calls	coaching, videos, workbook	SSEQ, SSBPS, SSQOL, RNLI
Mullis et al. (2024, UK) [17]	IPCAS	Cluster-RCT	1,040 patients, mean age 70.6 years	improvement in primary care following stroke	12 months	MLAS program, structured review	SIS 3.0, SIS-SF, EQ-5D-5L, ICECAP-A, SSSMQ HLQ
Towfighi et al. (2021, USA) [18]	SUCCEED	RCT	487 patients, mean age 57.1 years	risk factor control	12 months, various types of visits	CDSMP, mobile app, BP measurement	SBP, Non-HDL, HbA1c, BMI, IPAQ, PACIC, CAHPS, PHQ-9, SF-6D
Wolf et al. (2016, USA) [7]	IPASS	RCT	185 patients, average age of the intervention group 57 years	increase participation and self-efficacy	12 sessions (small groups)	IPASS model, problem-solving	SBT, BDAE, BNT, CDSES, PS-SES, CPI, ACS, WHOQOL-BREF
Chen et al. (2018, China) [19]	PCSMEI	RCT	144 patients, mean age 65.9 years	improve ADL and reduce rehospitalization	6 weeks, individual + 1 group session + phone calls	empowerment model, DVD, discussion	SSEQ, BI, rehospitalization

Table 4. Overview of self-management programs.

ACS –⁠ Activity Card Sort; ADL –⁠ activities of daily living; AIM –⁠ Acceptability of Intervention Measure; BI –⁠ Barthel Index; BDAE –⁠ Boston Diagnostic Aphasia Exam; BMI –⁠ body mass index; BNT –⁠ 15-item Short Form Boston Naming Test; CAHPS –⁠ Consumer Assessment of Healthcare Providers and Systems; CDSES –⁠ Chronic Disease Self-Efficacy Scale; CDSMP –⁠ Stanford Chronic Disease Self-Management Program; CPI –⁠ community participation indicators; EQ-5D-5L –⁠ EuroQol-5D; FIM –⁠ Feasibility of Intervention Measure; GDS –⁠ Geriatric Depression Scale; HADS –⁠ Hospital Anxiety and Depression Scale; HLQ –⁠ Health Literacy Questionnaire; IAM –⁠ Intervention Appropriateness Measure; ICECAP-A –⁠ ICEpop CAPability measure for Adults; IPAQ –⁠ International Physical Activity Questionnaire; IPASS –⁠ Improving Participation after Stroke Self-Management Program; MBI –⁠ Modified Barthel Index; MLAS –⁠ My Life After Stroke; mRS –⁠ Modified Rankin Scale; NEADL –⁠ Nottingham Extended Activities of Daily Living Scale; PACIC –⁠ Patient Assessment of Chronic Illness Care; PHQ-9 –⁠ Patient Health Questionnaire-9; PROMIS-SE –⁠ Patient-Reported Outcomes Measurement Information System's Self-Efficacy; PS-SES –⁠ Participation Strategies Self-Efficacy Scale; RCT –⁠ randomized controlled trial; RNLI –⁠ Reintegration to Normal Living Index; SAQOL –⁠ Stroke and Aphasia Quality of Life Scale; SBP –⁠ systolic blood pressure; SBT –⁠ Short Blessed Test; SCORE –⁠ Systematic Coronary Risk Evaluation; SF-6D –⁠ Short Form 6 Dimension; SF-12 –⁠ Short-Form Health Survey; SIS –⁠ Stroke Impact Scale; SIS-SF –⁠ Stroke Impact Scale –⁠ Short Form; SPPB –⁠ Short Physical Performance Battery; SSBPS –⁠ Stroke Self-management Behaviors Performance Scale; SSEQ –⁠ Stroke Self-Efficacy Questionnaire; SSMOES –⁠ Stroke Self-Management Outcome Expectation Scale; SSQOL –⁠ Stroke Specific Quality of Life Scale; SSSMQ –⁠ Southampton Stroke Self-Management Questionnaire; BP –⁠ blood pressure; WHOQOL-BREF –⁠ WHO Quality of Life Scale

 

Author (year, country)	Program title	Study results
Messina et al. (2020, Italy) [11]	LAY	The intervention was effective in improving self-efficacy, mental health, and activities of daily living. Improvement in self-efficacy (SSEQ): The total SSEQ score in the intervention group increased by 7.79 points from baseline to discharge (p = 0.001). An initial improvement in SSEQ self-management was observed in the intervention group during hospitalization. Among patients with higher education (more than 13 years of schooling), SSEQ activity scores were significantly higher in the intervention group compared to the control group. Improvement in mental health (SF-12 MCS): The Mental Component Summary (SF-12 MCS) score increased by 7.4 points from baseline to discharge. The intervention group showed an upward trend over time. Improvement in Activities of Daily Living (MBI): MBI scores increased significantly by 49.5 points from baseline to discharge (p < 0.001). The intervention group had a significantly higher average MBI score than the control group (by 7.9 points; p = 0.048). Among participants with higher education, the MBI score was 17.3 points higher in the intervention group than in the control group (p = 0.005). The intervention group was 8.9 times more likely to consult a general practitioner after discharge and 2.9 times more likely to exercise regularly than the control group.
Jones et al. (2016, UK) [12]	BRIDGES SMP	No significant difference was found in any of the outcomes, but measurements of functional capacity and self-efficacy showed a response to the intervention. Self-efficacy (SSEQ): Improvement of 1.11 points after 6 weeks and 2.20 points after 12 weeks compared to the control group. Functional capacity (NEADL): An average difference of 3.77 points after 6 weeks and 2.89 points after 12 weeks in favor of the intervention group.
Kamoen et al. (2020, Belgium) [13]	STROKE COACH	STROKE COACH showed promising results in reducing stroke recurrence and improving adherence and quality of life in patients after a stroke. Reduction in SCORE (Systematic COronary Risk Evaluation: High and Low cardiovascular Risk Charts) scores: By 3.2 points in the intervention group (p < 0.001). However, the comparison between the control and intervention groups was not statistically significant (p = 0.55). Improvement in quality of life (EQ-5D-5L): In the intervention group, from 68.4 to 77.6 (p < 0.001). High adherence to therapy: 96% in the intervention group. The program showed promising results in reducing the rate of stroke recurrence, with only 5% of patients in the intervention group suffering a new stroke during the 6-month follow-up period.
Li et al. (2024, USA) [14]	iSMART	iSMART is feasible and can improve self-efficacy in the area of SM. Improvement in self-efficacy: The iSMART group showed moderate to large effects in improving self-efficacy in managing emotions (r = 0.494), symptoms (r = 0.514), daily activities (r = 0.593), and treatment and medication (r = 0.870). In contrast, the control group showed negligible to small effects in the decline of self-efficacy in these areas. Use of participation strategies: The iSMART group demonstrated moderate to large effects in increasing the use of participation strategies for coping at home (r = 0.554), work (r = 0.633), the community (r = 0.673), and communication activities (r = 0.476). In contrast, the control group showed small to large effects in the decrease in the use of these strategies. Feasibility, acceptability, and appropriateness: The mean scores for FIM (4.11, SD 0.61), AIM (4.44, SD 0.73), and IAM (4.36, SD 0.70) indicate high feasibility, acceptability, and appropriateness of the iSMART intervention.
Lo et al. (2018, China) [15]	SESSMP	Improvements in self-efficacy, outcome expectations, and satisfaction with SM behavior implementation. Self-efficacy (SSEQ): The intervention group showed a significant improvement compared to the control group (B = 7.50, 95% CI: 2.55–12.45; p < 0.01). Outcome Expectancy (SSMOES): The intervention group showed a significant improvement compared to the control group (B = 9.74, 95% CI: 5.47–14.01; p < 0.01). Satisfaction (SSBPS): The intervention group showed a significant improvement compared to the control group (B = 8.63, 95% CI: 3.38–13.87; p < 0.01). Similar results were obtained after 8 weeks of follow-up in the per-protocol population: improvement in self-efficacy B = 9.30 (2.22–16.38; p = 0.01), outcome expectancy B = 11.34 (5.98–16.70; p < 0.01), and satisfaction B = 7.71 (0.56–14.86; p = 0.04).
Lo et al. (2023, China) [16]	COMBO-KEY	COMBO-KEY demonstrated efficacy—it improved self-efficacy, satisfaction with behavior, HRQoL, and reintegration. Total Self-Efficacy Score (SSEQ): Participants in the intervention group showed significantly better results after 8 weeks of follow-up compared to baseline (B = 7.80, 95% CI: 0.87–14.73; p = 0.027). Total Behavior Satisfaction Score (SSBPS): Participants in the intervention group showed a significantly greater improvement after 8 weeks of follow-up compared to baseline (B = 6.40, 95% CI: 0.40–12.41; p = 0.037). Health-Related Quality of Life (SSQOL): Participants in the intervention group showed a significantly greater improvement after 8 weeks of follow-up compared to baseline (B = 9.69, 95% CI: 1.32–18.06; p = 0.023). Reintegration (RNLI): Participants in the intervention group showed a significantly greater improvement after 8 weeks of follow-up compared to baseline (B = 12.89, 95% CI: 6.18–19.60; p < 0.001).
Mullis et al. (2024, UK) [17]	IPCAS	IPCAS showed no measurable effect; a broadly targeted primary care model is likely ineffective. After 12 months, the intervention group showed an improvement in emotional outcomes of 0.64 (97.5% CI: –1.7 to +2.8) and an increase in participation outcomes of 1.3 (97.5% CI: –2.0 to +4.6) compared to the control group. No effect of the intervention was demonstrated on the short form of the Stroke Impact Scale, quality of life (EQ-5D-5L), well-being (ICECAP-A), SSSMQ, or health literacy (HLQ).
Towfighi et al. (2021, USA) [18]	SUCCEED	SUCCEED did not improve blood pressure control compared to standard care in a disadvantaged population. Systolic blood pressure improved in both groups (from a mean of 143 mmHg to 133 mmHg in the intervention group and from 146 mmHg to 137 mmHg in the standard care group), yet the differences between the groups were not statistically significant −3.3 mmHg (95% CI: −14.9 to +8.8 mmHg; p = 0.57). Improvements were observed only in salt intake (p = 0.004) and CRP levels (p = 0.003), but not in the other secondary outcomes monitored.
Wolf et al. (2016, USA) [7]	IPASS	IPASS showed promising results in improving self-efficacy and coping with the consequences of stroke. There was a significant short-term increase in health-related self-efficacy both within the group and between groups in managing chronic diseases, which persisted during follow-up (the average effect size was 0.46), indicating a moderate effect overall. Furthermore, a significant short-term increase in self-efficacy regarding participation was found (with an overall moderate effect size of 0.55).
Chen et al. (2018, China) [19]	PCSMEI	PCSMEI led to higher levels of self-efficacy and greater independence in ADLs, as well as a lower rate of rehospitalization compared to the control group. Improvement in self-efficacy: Patients in the intervention group (IG) showed significantly higher levels of self-efficacy at discharge (p = 0.014), 1 month after discharge (p = 0.008), and 3 months after discharge (p = 0.023), with significant differences in change between the IG and the control group (CG): At discharge (T1): (B = 3.644, 95% CI: 0.728–6.560), 1 month after discharge (T2): (B = 4.968, 95% CI: 1.322–8.613), 3 months after discharge (T3): (B = 4.252, 95% CI: 0.576–7.928) Improvement in self-reliance (BI): A significant difference in the change in BI between the IG and CG 3 months after discharge (T3) (B = 5.175, 95% CI: 0.131–10.219; p = 0.044). Lower rehospitalization rate: The rehospitalization rate in the IG was lower than in the CG after 1 month (2.8% vs. 5.6%) and after 3 months (6.9% vs. 18.1%). This lower rehospitalization rate in the IG was clinically significant. However, the difference was not statistically significant after 3 months (B = −0.094, 95% CI: −0.192 to 0.004; p = 0.061).

Table 5. Results of self-management programs.

AIM –⁠ Acceptability of Intervention Measure; BI –⁠ Barthel Index; CI –⁠ confidence interval; EQ-5D-5L –⁠ EuroQol-5 Dimension, five-level questionnaire; FIM –⁠ Feasibility of Intervention Measure; IAM –⁠ Intervention Appropriateness Measure; MBI –⁠ Modified Barthel Index; MCS –⁠ Mental Component Summary; NEADL –⁠ Nottingham Extended Activities of Daily Living Scale; SCORE –⁠ Coronary Risk Evaluation; SD –⁠ standard deviation; SF-12 –⁠ Short-Form Health Survey; SM –⁠ self-management; SSBPS –⁠ Stroke Self-management Behaviors Performance Scale; SSEQ –⁠ Stroke Self-Efficacy Questionnaire; SSMOES –⁠ Stroke Self-Management Outcome Expectation Scale