Barriers and Enablers for Implementing Self-Management Support for Stroke Survivors: A Mixed-Methods Systematic Review

Barriers and Enablers for Implementing Self-Management Support for Stroke Survivors: A Mixed-Methods Systematic Review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Barriers and Enablers for Implementing Self-Management Support for Stroke Survivors: A Mixed-Methods Systematic Review Erika Klockar, Maya Kylén, Catharina Gustavsson, Tracy Finch, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6047723/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Stroke may pose significant challenges to individuals and healthcare systems worldwide, and there is a clear need to understand ways to provide effective self-management support. This systematic review aims to identify barriers and enablers for the implementation of self-management support for stroke survivors across various settings. Methods : We conducted a mixed-methods systematic review following PRISMA guidelines, searching CINAHL, Embase, Medline, and Scopus for studies on self-management support with long-term follow-up. The Consolidated Framework for Implementation Research (CFIR) guided our narrative synthesis. Results : After screening 7275 studies and rigorous selection criteria, 37 articles were included. The findings revealed that the implementation of self-management support interventions for stroke survivors is influenced by various enablers and barriers, including training for healthcare professionals, participant motivation, and tailored support. Notable barriers included design and compatibility issues, funding constraints, and local context challenges. Conclusions : Effective self-management interventions must be customized to meet the diverse needs of stroke survivors. Enhancing sustainability and impact requires ongoing support, such as booster sessions and community resources, along with robust evaluation methods. Developing objective measures to complement self-reported data is essential for providing reliable insights and meaningful and effective self-management support. Systematic review registration: This review is registered with the International Prospective Register of Systematic Reviews (PROSPERO), registration number CRD42024508432. Self- management stroke systematic review Consolidated Framework for Implementation Research Figures Figure 1 Figure 2 Background Every year, approximately 17 million people worldwide suffers a stroke, making stroke one of the common causes of disabilities ( 1 ) and many face challenges in managing their long-term recovery ( 2 ). This systematic literature review aimed to identify barriers and enablers in self-management support interventions that support long-term self-management after a stroke. Stroke survivors often face long-lasting physical, emotional, social, economic and cognitive consequences ( 2 ), which affects their overall quality of life and participation ( 3 ). The rehabilitation needs after stroke are often extended and complex, and there is evidence that those needs are often not being met ( 4 , 5 ). Stroke survivors may also experience lack of information, support and preparation for discharge from acute stroke care ( 6 ), despite recommendations in stroke guidelines that early supported discharge is available and consequently conducted in-home ( 7 ). To address these issues, the Action Plan for Stroke in Europe 2018–2030, states that a goal for 2030 is that after discharge, all persons with remaining disabilities after stroke should be provided with a plan for community rehabilitation and self-management support ( 2 ). This is also supported by the International Stroke Organization ( 8 ). Self-management support is often described as equipping people with the necessary skills, knowledge, and confidence in managing their health, which includes both physical and psychosocial health ( 9 , 10 ) and has been found to positively affect quality of life and self-efficacy ( 11 ). Even so, self-management support interventions vary in content from narrow focus of disease control and compliance to medical advice, to the more broader approach that includes collaboration around a person’s needs to live their lives as independent and satisfying as possible ( 12 , 13 ). Furthermore, the theoretical underpinnings of self-management support programs, the content, dose and timing of delivery show great variation ( 3 , 14 ), as well as different implementation strategies used. Despite growing recognition of self-management's importance, the factors influencing its success in the context of long-term implementation is not fully understood. To contribute to the knowledge around sustainable self-management support, this study aims to explore and synthesize barriers and enablers of long-term self-management for stroke survivors across diverse health care settings. The complexity of self-management and self-management support can make it difficult to compare studies of self-management interventions. In the present review we used the Consolidated Framework for Implementation Research (CFIR) ( 15 ), to provide a structure for understanding the multifaceted factors that influence healthcare implementation outcomes. This framework consists of five domains with related constructs and subconstructs that influence the implementation of innovations in practice (Fig. 1 ). Using CFIR, we aimed to enhance the transferability and comparability of results across the included studies to inform future intervention and implementation research. This approach provided a systematic way to categorizing and evaluating barriers and enablers across individual, organizational, and systemic levels. CFIR has been used in healthcare research to facilitate tailored interventions and improve implementation success ( 16 ). In summary, self-management support after stroke is a promising approach but the factors influencing the success of self-management support interventions can be successful in the long-term is not fully understood. Furthermore, it is necessary to consider a broad range of factors when designing and implementing self-management support programs, and how these factors affect long-term self-management for individuals with stroke which are yet to be reviewed. The overall aim of this systematic literature review was to identify barriers and enablers for implementation of self-management support interventions for people with stroke across different settings. Methods We carried out a systematic review of quantitative, qualitative, and mixed-methods studies, using narrative synthesis. This approach allowed for a comprehensive exploration and understanding of the multifaceted factors that may influence long-term self-management (measured > 6 months). A narrative synthesis method was employed to integrate evidence from multiple study designs, using the principles of The Joanna Briggs Institute guidance for mixed-methods systematic reviews ( 17 ). The 27-item Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) checklist was used for reporting the findings ( 18 ). The review was registered in PROSPERO (CRD42024508432). Eligibility criteria We used the Population, Exposure and Outcome framework (PEO) ( 19 ) to develop study eligibility criteria. Studies were eligible if they met the following criteria: Population adults (< 18 years) diagnosed with stroke and all categories of health care professionals involved in stroke care. Exposure self-management intervention in stroke care, delivered in any type of health care setting (in-hospital, community setting, in home). Outcome All outcomes reporting long-term effects of self-management interventions at least 6 months post-intervention. The time frame was determined to studies published between 2009–2024. Studies were included regardless of study design (quantitative, qualitative and mixed methods studies). Inclusion and exclusion criteria are displayed in Table 1 . Table 1 Inclusion and exclusion criteria Inclusion criteria Exclusion criteria Population Adults (< 18 years) with stroke diagnosis Health care professional in stroke care Patient populations with mixed diagnosis where the stroke population could not be separated in the results Exposure Self-management intervention in any kind of stroke care setting (in-hospital, out-hospital, community setting, in-home) Interventions that consisted of only one part of self-management (e.g., solely problem-solving), if self-management was not mentioned at all in the intervention description. Outcome All outcomes reporting long-term effects of self-management interventions at least 6 months post-intervention. None Year 2009–2024 Publications before 2009 Design Any None Language English, Swedish Non-English Publication types Full publication in peer-reviewed journal Letters, editorials, reviews, dissertations, abstracts, conference papers, protocols Search strategy and database A comprehensive search strategy was developed by the authors in collaboration with an information specialist. Following databases were searched; OVID, Medline, SCOPUS, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Web of Science. Test searches were performed to evaluate and refine the search strategy. The searches were conducted on 170222, 241022, and 270524. Search terms Boolean searches using the operators “AND” / “OR” / ”NOT” were constructed with selected search terms and combination of search terms as appropriate for each database following respective guidelines, example can be found in Additional file 1. Search results were exported to EndNote citation manager software. The total search findings were compiled, and duplicate papers were removed to generate a final list of search findings for the review. Study selection Covidence software was used to manage the data collection ( 20 ). Covidence is a web-based collaboration software platform that streamlines the production of systematic and other literature reviews. After eliminating all duplicates, titles and abstracts were screened for relevance. Most of the screening (90%) was done by the first author (EK) with a research assistant performing 10% of the screening. Full-text articles of relevant abstracts were retrieved and read in full to confirm the relevance and decide on final exclusion or inclusion by EK, MG and MK. Conceptually difficult articles were discussed with research group members (EK, MK, ME, CG). Data extraction and appraisal A purpose-designed data extraction form was developed and used jointly by the research group in Covidence to facilitate the systematically retrieval of data relevant to the aim of the study. The form included variables describing the included studies. Main findings relevant to enablers and barriers of implementation of the interventions were also extracted from the results and discussion section. We chose to include data from the discussions section as it often contained interpretations and insights from the authors that gave a rich image and multiple views on factors of importance. Initial data were extracted by EK and a research assistant, with MK and ME checking 30% of the data to verify its accuracy, introducing a layer of quality control of the process. Any discrepancies encountered during data extraction were resolved through discussions in the research group, ensuring consensus and maintaining the integrity of the data collected. The data in Covidence was finally imported into a Microsoft Excel spreadsheet. Data analysis and synthesis First, we extracted data on barriers and enablers using the expressions and terminologies from the original papers (Additional file 2 and Table 2 ). In the second step, we analysed the extracted data using narrative synthesis ( 21 ), with CFIR ( 15 ) serving as a deductive framework for the analysis. This included mapping the extracted barriers and enablers to one of the constructs or subconstructs of the CFIR framework through discussions in the research group. The discussions ensured that no barriers or enablers were forced into a construct with a poor correspondence. Following the principles of the narrative synthesis, data from constructs and subconstructs were then analyzed thematically to develop an overarching narrative in each construct and subconstruct. Quality appraisal The methodological quality of the included articles was assessed using the Mixed Methods Appraisal Tool (MMAT) ( 22 ). The appraisal tool consists of five criteria that evaluate the sampling strategy, sample representativeness, measurements, risk of nonresponse bias and appropriateness of statistical analysis. A rating of “Yes”, “No” or “Can’t tell” for each item is provided, but no overall summary rating. EK, ME and MK conducted the quality appraisal Additional file 2. Results In total, 37 articles were included in the systematic review (Figure 2). The initial search identified 7 275 articles. After the first screening, 404 articles were selected for eligibility assessment. Following a full-text review,367 articles were excluded for not meeting the inclusion criteria, resulting in a final selection of 37 articles. A full description of the included studies is in Additional file 2. Characteristics of included studies The included studies represented twelve different countries, with Australia and China being the most frequently represented, each contributing six studies. Predominantly, randomized controlled trials constituted the primary study design (n=21), while the participants mostly consisted of individuals with stroke (n=32). Sample sizes ranged from 4 to 381 participants. Patient-reported outcomes (n=30) and measurement tools (n=23) were the prevailing methods of data collection, ranging over 27 different outcome areas. The outcome assessments covered areas such as activity level, Activities of Daily Living levels, cognitive abilities, cardiovascular measurements, quality of life and self-efficacy. Quality of life was the most common measurement (n=24), followed by cardiovascular outcomes (n=15) and physical functioning (n=14). Self-efficacy was measured in 10 of the included studies, whereas self-management ability was measured in only 4 studies. Broad self-management interventions were dominating (n=17), whereas self-management of physical abilities (n=6) and self-management for secondary prevention (n=6) were equally prevalent. Most studies were conducted in-home settings (n=17). An overview of study characteristics is displayed in Additional file 2. Quality appraisal All the studies included were judged to meet sufficient quality standards based on the MMAT (22). While no specific cut-off score was applied, studies were included only if their main appraisal questions were rated as “Yes.” Studies with a “No” for key appraisal criteria were excluded. Detailed quality assessments are available in Additional file 2. Barriers and enablers for long-term self-management after stroke Barriers and enablers were identified across all domains of the CFIR and covered 26 of 39 constructs. The innovation domain had the highest frequency of covered constructs (6 out of 8 constructs covered), followed by implementation domain , individual domain , inner setting domain and the least frequency of covered constructs were seen in the outer setting domain (4 out of 10 constructs covered). The most prominent constructs are described in text with related references. For full display of included studies and the constructs and subconstructs that are related to each study see Table 2. A more detailed description of barriers and enablers are in Additional 1. Table 2. Summary of enablers and barriers for self-management support interventions CFIR domain CFIR construct CFIR subconstruct Enabler Barrier Innovation domain B. Evidence Base (23-41) C. Relative advantage (34, 38, 41-45) (41) D. Adaptability (23, 24, 31, 38, 40, 46) (25, 38) G. Design (24, 26, 28-31, 33, 34, 37-41, 43, 47-51) (24, 29, 31, 32, 35, 38, 39, 41-46, 48, 49, 52) H. Innovation cost (38) Outer setting domain A. Critical incidents (38-40) C. Local conditions (26) (25, 29, 38, 41, 42, 46) Inner setting domain A. Structural characteristics A.2. Information technology infrastructure (34) A.3. Work Infrastructure (28, 43) (46, 53) D. Culture D.2. Recipient-Centeredness (29) (25, 43, 51) D.3. Deliverer-Centeredness (34) F. Compatibility (25, 34, 36) J. Available resources J. 1. Funding (31, 38, 49) J. 3. Materials & Equipment (37, 40, 48, 54) K. Access to Knowledge & Information (23-28, 32, 36, 38, 43, 49-51) (31) Individuals domain F. Implementation Team Members (38) H. Innovation Deliverers (25, 33, 39, 41-43, 48, 51, 55, 56) (51) I. Innovation Recipients (23, 24, 28, 30, 33, 43, 44, 46, 49, 51) (23, 25, 29, 31, 36, 40, 43, 46, 47, 49, 52-55) Implementation Process domain B. Assessing needs B. 1. Innovation Deliverers (23, 24, 26, 42) (39, 53) B. 2. Innovation Recipients (24, 27, 34, 40, 54) (23, 29, 33, 40, 42, 53) C. Assessing context (24, 41) E. Tailoring Strategies (23, 31, 32, 34, 35, 38, 53) G. Doing (31) H. Reflecting & Evaluating H. 1. Implementation (28, 30, 42) H. 2. Innovation (31, 36, 38, 47) (24, 31-33, 39-41, 52, 56) I. Adapting (48) Innovation About half of the included articles based their self-management interventions on established theories, frameworks or self-management programs to guide the development or implementation of their interventions and these were viewed as enablers. Several theories recurred, such as the Self-Determination Theory (26), the Social Cognitive theory and its construct of self-efficacy (30, 39, 41). Also, the Chronic Disease Self-Management Program (CDSMP) was mentioned (25, 30, 33) as a framework to develop or guide interventions. Although, CDSMP is best classified as a self-management program rather than a theoretical framework. Additional frameworks such as Medical Research Council (MRC) Framework (36, 38) were noted in some studies for structuring the design and evaluation of interventions. Studies highlighted several ways in which the interventions aimed to improve upon existing practices, particularly in their ability to offer more comprehensive, integrated, and patient-centred care, often through longer duration (38, 42), shared-care models with broad perspectives (34, 43), to aim at enhanced self-efficacy (41), or the use of technology (45). On comparison, a barrier was seen when the new intervention was too similar to care as usual (41). Flexibility in terms of methods for delivery of the intervention to reach more participants or to adapt to various accessibility needs and learning preferences ensured broader reach and inclusivity (31). Personalization of the content was used to better address each participant’s unique challenges and strengths, potentially leading to more impactful outcomes (23). Barriers for adaptability were, for example, when sessions posed a cost for some participants (the use of a phone for participating in a session), highlighting the need for more adaptability by offering alternative delivery methods to improve access (25). Turning to design features, one key enabler was the use of an individualized approach, where participants set personal goals, created action plans, and adapted the programs based on their specific needs, preferences, and abilities (24, 33, 38, 41). Another enabler was the incorporation of telemedicine and digital platforms. These tools provided patients with access to health education, real-time monitoring, and communication with healthcare providers to extend the reach of care. This approach was particularly beneficial for individuals in remote or under-resourced areas (34, 37, 47). Multidisciplinary care was also highlighted as an important design feature, addressing a broad range of physical, psychological, and social needs (28, 31). Additionally, involvement of family and social support, continuous follow-up and peer support were noted as enablers (28, 39). Several design-related barriers limited the effectiveness and accessibility of self-management interventions, particularly challenges in delivery, population inclusion criteria, and outcome measurements. Insufficient structuring of interventions across care transitions and inadequate documentation of intervention components reduced the overall feasibility and effectiveness of the intervention in one study (24). Excessive measurement requirements, detailed diaries, or lengthy questionnaires could discourage participation and limit the quality of the data collection (29, 46). Additionally, if the intervention were delivered in short sessions, had low contact hours, or lack of ongoing input and support, intervention effectiveness was limited (48, 49). Exclusion criteria often prevented patients with greater needs to participate in interventions. Rigid timelines and fixed settings further limited flexibility, particularly for older or frail participants and those with cognitive or communication challenges (31, 45, 52). Recruitment delays and competing trials also hindered program access (42, 43). Challenges in evaluating outcomes were notable. Bias from contamination across control and intervention groups, non-blinded allocation, and recall bias complicated outcome evaluations (39, 44). Additionally, complex interventions were difficult to evaluate due to insufficient power to detect meaningful effects since they could include multiple components, varying levels of individual tailoring, multiple behavior change mechanisms, and internal and external relationships (38, 39). Outer setting The COVID-19 pandemic introduced critical barriers to the implementation of self-management studies that were conducted during the pandemic. These included shifts in delivery modes, prolonged recruitment times, and altered participant eligibility, all of which impacted study processes (38, 39). In public funded healthcare where care on all levels was free of charge and the access to rehabilitation facilities was high, participation in self-management support programs were enabled (26). However, notable barriers were also identified, including transportation challenges (25, 26, 42, 46), limited access to rehabilitation and specialized services (26, 29, 46) and inadequate integration of care (41). In addition, variability in site-specific resources and staffing further created difficulties in accessing and delivering self-management interventions (38). Inner setting Enablers among work infrastructure included having clear pathways for rehabilitation and when care was extended without interruptions (28, 43). It was beneficial to pre-schedule patient appointments before discharge to ensure that protocols for follow-up were followed which is a key component of self-management support (43). Barriers could concern organizational issues or intervention deliverers waiting for other professions to give the participants medical clearance to participate (46). Another key enabler was when integrate cultural context into self-management support design, for them to be inclusive, relevant, and effective across diverse patient groups, which in turn could enhance the intervention’s effectiveness and engagement (29, 51). Barriers included the failure to incorporate cultural context into intervention design, so that unique needs of specific populations like veterans or gender issues were overseen (25, 43). Funding barriers limited scalability and accessibility, restricting features like multilingual text messages or home-based therapy. Practical issues, such as time and travel constraints, further hinder implementation, even with financial support (31, 38, 49). Regarding materials and equipment, discomfort or refusal to use specialized devices (54), technical challenges with remote communication (48), limited access to technology and digital skills (37), and compliance issues with self-reported data collection tools were all barriers for implementation (40). These factors highlight the need for user-friendly, accessible, and reliable materials to support intervention success. Access to knowledge and information were important to consider. Comprehensive education and training for both providers and participants, along with tailored resources and ongoing support, were crucial enablers in ensuring consistent and effective implementation of interventions (24, 28, 38, 43). Individuals Those involved in delivering the intervention could be enablers for the implementation process by playing a critical role in behaviour change for the recipients, by providing accountability and dialogue (55), or motivation (41, 48). Another enabler was the role facilitators could be to the persons receiving the intervention (42). Facilitators were furthermore seen as a key component by Damush (25), where their regular phone call to the participants were much appreciated as a reminder that someone was concerned about their health. Enablers related to intervention recipients varied across studies. Participants with sedentary behaviour and low self-efficacy improved most in physical activity programs (46), while high self-efficacy and good baseline quality of life enhanced self-management outcomes, although limiting measurable gains in areas like walking (23). Interventions tailored for individuals with mild to moderate disability, or those with broad inclusion criteria addressing diverse needs, proved effective by improving functional outcomes, promoting patient engagement, and facilitating implementation through adaptability to diverse contexts (24, 49). In addition, motivation was reported as a key for engagement and adherence (43). Barriers included physical limitations like fatigue and mobility decline, particularly among older participants, and cognitive challenges such as memory impairment and low self-awareness, which hindered goal-setting (29, 52). Motivation among participants varied, with lack of interest, post-stroke adjustment stress, and loss of hope after intervention withdrawal were cited as barriers (25, 49). Practical concerns like transportation, financial costs, and in-person session burdens were significant, especially for older or remote participants (31). Implementation process Successful implementation of self-management support interventions relied heavily on comprehensive training and support for those delivering the intervention. One barrier described was that the intervention deliverers also had to conduct care as usual, and the self-management support integrated into care was not always provided to the extent originally intended (39). Another barrier was when staff perceptions of the value of the intervention was low and potentially added to workload. Healthcare professionals’ perceptions of the intervention in Brouns (51) presented potential barriers to implementation. The intervention may not have aligned with their roles, causing scepticism about its practicality. Concerns were raised about inadequate training, a lack of confidence in delivering the intervention, and its perceived complexity or additional workload. These factors contributed to low engagement and inconsistent implementation. To address these issues, the study highlights the importance of providing adequate training, streamlining the intervention to fit existing workflows, and involving professionals early in the design process to ensure relevance and practicality. Various implementation strategies were used and identified as enablers in the included studies. Stepwise approaches allowed for gradual adaptation of complex interventions into clinical practice (31). Additionally, frameworks like Template for Intervention Description and Replication (TIDier) were highlighted for their role in improving the implementation (35). The TIDieR framework is a tool designed to standardize how interventions are described, ensuring that essential details are clearly documented. The structured checklist helps researchers and practitioners outline critical aspects such as the content of the intervention, the delivery methods, the setting, and who delivered it. This clarity facilitates replication and implementation in various clinical settings, thereby enhancing the likelihood of success (34). Tailored strategies addressed both patient and provider barriers and facilitators through structured integration, stakeholder education, and support services such as helpdesks (53). To ensure fidelity to core program principles, which is key for scalability and consistency, standardized training for healthcare professionals, regular provider-researcher meetings, and systematic documentation must be implemented (38). These measures ensured that self-management support was delivered consistently across settings while allowing adaptation to individual patient needs. Tailored strategies addressed barriers and facilitators through structured integration, stakeholder education, and support services like helpdesks (53). Ensuring fidelity was key, achieved through standardized training, regular provider-researcher meetings, and systematic documentation, which supported scalability and consistency (38). Standardized delivery was also reinforced with intervention guides and workshops on program theory of the intervention (34). To sustain effects, periodic booster sessions and strategies to maintain self-efficacy post-intervention were proposed, ensuring long-term benefits for participants (23, 33). In some studies, limitations in research quality, such as the lack of qualitative and process evaluations (28, 42) and reliance on subjective outcomes (30, 48), hindered a comprehensive understanding of intervention implementation and its potential for improvement. In some studies, the lack of qualitative and process evaluations (28, 42), along with reliance on subjective outcomes (30, 48), hindered understanding and improvement of intervention implementation. Self-reported data could risk socially desirable responses, skewing results (31, 41). Many studies relied on generic outcome measures that failed to capture the nuanced impacts of self-management interventions. Additionally, the lack of sensitive measurement tools, particularly in small studies, limited the ability to generate meaningful findings (32, 33, 52). Defining and measuring self-management in a concrete way was challenging without clear outcome measures, making evaluations more difficult (39). Broad evaluations were seen as important, incorporating feedback from care professionals, patients, and caregivers to ensure diverse perspectives (31). Economic analyses could provide essential feasibility insights, while patient-relevant outcomes such as Patient-Reported Outcome Measures (PROMs) were important to capture real-world complexities and continuous improvement opportunities (38, 47). Assessing unmet needs prior to implementation could aid in refining interventions effectively (36). Discussion This study identified and synthesized barriers and enablers for implementation of long term self-management support for people with stroke across diverse settings. The review highlighted that implementing self-management interventions in clinical settings is a complex process. The long-term sustainability of these interventions depends on several critical factors. The key enablers identified included the necessity for adequate training for healthcare professionals and ongoing support for people with stroke, which are essential for effective implementation. Interventions designed to meet individual needs and satisfy diverse populations enhance relevance and engagement. In addition, individualized approaches that actively involved stroke survivors and their families in goal setting and decision-making fostered a sense of ownership, motivation, and engagement with the interventions. Partnerships between healthcare teams and patients were central to the success of these interventions. Stepwise integration into clinical workflows, supported by structured frameworks like TIDieR ( 35 ), facilitated better adaptation to local contexts, reduced resistance, and promoted smoother adoption. The main barriers noted included poor adaptation to existing practices, where interventions that did not align with current care workflows or professional roles faced significant resistance. Additionally, diverse needs among participants posed challenges for example variations in cognitive, emotional, and physical abilities of stroke survivors made it difficult to design universally effective interventions. Resource constraints, including limited funding, staffing, and institutional support, also created significant challenges to implementation and sustainability. The variation in study design and delivery The review highlights the considerable variation in the design, conceptualization and implementing self-management support programs, making direct comparisons challenging. However, the review also showed that many studies noted the possibility to tailor the intervention to the context as an enabler. While this flexibility can be considered a strength, enabling interventions to target different populations and goals, it also highlights the need for clearer theoretical grounding. Not all the included articles grounded their interventions in a theory. For the area to advance the researchers should prioritize articulating the theoretical underpinnings that inform the design of the interventions. Doing so not only ensures that interventions are evidence-based but also contributes valuable insights into understanding the mechanisms that drive change and specifically, what works, for whom, and under what circumstances. There has been research that highlights the need to develop implementation logic models, so that the implementation process can be more planned, and tailored, to achieve the desired implementation outcomes ( 57 ). There has been initiatives to define what self-management support to persons with stroke should consist of, for example Ansong ( 3 ), who identified eight essential attributes of self-management support post-discharge, including pre-discharge planning, education, goal-setting, and community reintegration. These attributes aim to enhance patient empowerment and self-efficacy, leading to improved outcomes and reduced healthcare costs. However, there are concerns regarding healthcare professionals' workload and resource constraints, making it challenging to apply this concept practically ( 3 ). For those incorporating some or all these self-management principles for specific outcome targets (blood pressure, physical ability, communication etc), it is equally important to state the theoretical underpinnings and theories of change that are used, so that self-management is just not an “add on” concept, without meaning. Morgan and colleagues ( 12 ) argue that more narrow approaches for support often involve disease control which can limit patient empowerment and reinforce a paternalistic relationship between health care professionals and the patient. In the meantime, a broader approach supports people to manage their life and situation living with one or more condition. The focus is more on ‘what matters to people and how they can be supported to shape their own lives’ ( 12 ). In our review, we observed that studies often failed to explicitly connect barriers and enablers to implementation strategies and outcomes. Thus, there is also a need to develop implementation logic models, so that the implementation process can be more planned, and tailored, to achieve the desired implementation outcomes. The importance of the individual CFIR highlights the crucial role of individuals in implementation of interventions. Many of the included studies have identified barriers like fatigue, functional limitations, and lack of transportation that hinder engagement in self-management programs. Research has shown that many individuals who could benefit from support such as those with aphasia, cognitive disabilities, severe conditions, or low health literacy are often excluded or do not participate ( 56 , 57 , 58 , 60 ). Audulv et al. ( 61 ) emphasize the need to understand the diverse strategies patients employ for self-management, which is essential for crafting comprehensive interventions targeting social, emotional, and medical support. Current self-management interventions often narrow their focus, primarily addressing secondary prevention or fall risks, but a more holistic approach that recognizes each patient's unique needs is essential ( 61 ). Self-management as an outcome measure A notable finding from this review is the limited number of studies explicitly measuring self-management. At the same time, most studies examined intervention effects on broader outcomes such as physical health improvements or secondary prevention measures (e.g., reduction in stroke recurrence). However, a few studies directly assessed participants' development of self-management skills, such as problem-solving or goal-setting. This raises an important question as to whether these interventions effectively support participants' broader and lasting self-management capacity. In studies focused on secondary prevention it was observed that many studies overlooked self-management measurement. This may not necessarily reflect the lack of interest in self-management but rather questions whether there are validated tools or frameworks explicitly designed for this purpose. For example, tools exist to measure certain components of self-management such as goal-setting ability, health literacy, or self-efficacy for managing long-term conditions, but these often assess isolated aspects. Recent research continues to highlight the challenges in defining and measuring self-management within health interventions. For example, a systematic review by Rimmer et al. ( 58 ) emphasized the need for standardized definitions and consistent outcome measures in self-management research to accurately evaluate intervention effectiveness There are examples of self-efficacy scales such as Stroke-self efficacy scale SSEQ ( 59 ) which are closely aligned with confidence to self-manage and offer a tailored measure for persons with stroke. Selecting an appropriate self-efficacy or self-management scale necessitates careful consideration of the target population, the specific aspects of self-efficacy being measured, and the tool's psychometric properties. Long-term effects We did not assess whether the included studies were successful at achieving significant changes in their primary outcomes. While success often is defined by measurable improvements in primary outcomes, valuable insights can also be drawn from studies that did not achieve significant changes. Such studies provide opportunities to explore and identify challenges in implementation, participant engagement, or contextual factors that may have influenced the impact. There is a value in understanding how intervention components, theoretical underpinnings, or delivery mechanisms might be optimized for future research. Furthermore, some studies evaluated their impact by using qualitative methods which provides a different perspective on implementation, and can provide unique understanding of the perspectives and value experienced by recipients of self-management support interventions. Many self-management intervention studies also lack follow-up which decreases the possibilities to explore the effect of self-management support over time ( 59 ). This is also stated in the Action Plan for Stroke in Europe, which calls for researchers to investigate if self-management programmes improve long term outcomes of stroke rehabilitation ( 2 ). In this review, we used the CFIR framework to identify key factors that influence the implementation of self-management interventions. The framework offered valuable insights into the complexities of implementation processes. However, the framework does not prescribe implementation strategies. Rather, it serves as a tool to understand the diverse factors that can influence implementation outcomes. The CFIR can be combined with the Expert Recommendations for Implementing Change (ERIC) strategies (( https://cfirguide.org ). ERIC assemble strategies identified by experts as effective in enhancing the adoption, implementation, and sustainability of evidence-based interventions. ERIC provides a list of discrete implementation strategies that can be selected based on the specific barriers and facilitators identified within a given implementation context. Strengths and limitations One of the strengths of this review is the inclusion of diverse studies that explored self-management interventions for people after stroke across various settings, and intervention types. This broad approach allows for a comprehensive understanding of the barriers and enablers influencing self-management interventions. We synthesized data from different contexts and thus the findings have broader applicability to a wide range of settings. We used a stepwise method and first identified barriers and enablers. The use of the CFIR framework then provided a structured and consistent approach to identifying and categorizing barriers and enablers ensuring that key factors across studies were systematically evaluated. The identification of barriers and enablers relied on the researchers’ interpretation of the findings reported in the included studies. This subjective process may introduce bias, as researchers’ understanding of self-management could shape how barriers and enablers were identified or categorized. However, we involved multiple reviewers with diverse perspectives, and we also derived themes from original studies at the first step. In addition, we discussed differences in those to agree categorizations that were less clear The lack of a unified definition of self-management in the included studies may have influenced how barriers and enablers were conceptualized and interpreted. Different studies may emphasize certain dimensions of self-management (e.g., physical, emotional, or cognitive aspects) over others, making it challenging to draw comparisons across interventions. We did not assess whether the studies included were successful in achieving their intended intervention outcomes. It is possible that those studies reporting fewer barriers, and more enablers were also more successful, which may influence the interpretation of results. Conversely, studies with significant barriers may provide valuable insights for improving future interventions, regardless of their success in achieving primary outcomes. Future research on self-management interventions The review highlighted that many self-management support interventions lack clear definitions or targeted approaches for divers populations such as stroke with specific needs, including those with mild-to-moderate disability, cognitive impairments, or frailty. Thus, future research should focus on designing interventions that are adaptable to diverse physical and cognitive abilities. In addition, understanding how barriers and enablers differ across subgroups could help to create more personalized and effective strategies. It is also important to demonstrate the importance of integrating established frameworks like CFIR, TiDIER, and logic models from the outset of implementation projects. These frameworks have been suggested to ensure interventions are well-designed, transparent, and adaptable to meet the specific needs of their contexts. However, research on the impact of these frameworks on project outcomes is still limited. Although some included studies used TiDIER, and reported that as an enabler, there was a lack of clarity in the reporting of intervention components and their mechanisms of action. Future research could add knowledge by identifying which specific components (e.g., goal setting, health literacy training, peer support) contribute most to self-management success. Many studies in the review did not measure self-management as an outcome or used fragmented tools. To address these future studies should adopt comprehensive self-management measures (e.g., goal-setting ability, health literacy, self-efficacy) to better capture intervention impact. Few studies in our review may have included process evaluations or examined the cost-effectiveness of interventions. This limits our understanding of how interventions are implemented (e.g., adherence, acceptability, contextual factors). We included studies that have measured outcomes in the long-term and research needs to continue to examine whether improvements in self-management skills are sustained over time and lead to long-term health benefits, such as reduced stroke recurrence or enhanced quality of life. In addition, there is a need for a comprehensive approach to researching self-management in stroke recovery by develop and incorporates better outcome measurement, a deeper understanding of self-management as a concept, and innovative research designs that allow for the examination of personalized implementation strategies. This would help ensure that self-management interventions are both effective and meaningfully beneficial to stroke survivors. Conclusions This review underscores the importance of personalizing self-management support to effectively address the varied cognitive, emotional, and physical needs of patients, which is key to their success. Emphasizing the critical role of ongoing support, such as booster sessions and community resources, this approach could enhance the sustainability and impact of interventions. Effective implementation also depends on robust methods of assessment. It is crucial to develop objective measures for evaluating self-management and self-efficacy to complement self-reported data, ensuring more reliable and actionable insights. By focusing on personalization of care, continuous support mechanisms, and solid evaluation methods the advance of self-management interventions can enhance, ultimately reducing health differences and improving patient outcomes across diverse settings. Abbreviations CFIR Consolidated Framework for Implementation Research ERIC Expert Recommendations for Implementing Change strategies MMAT Mixed Methods Appraisal Tool SSEQ Stroke-self efficacy scale TiDIER Template for Intervention Description and Replication Declarations Ethics approval and consent to participate Not applicable. Availability of data and materials All data generated or analyzed during this study are included in this published article [and its Additional files]. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research is funded by Dalarna University and the Swedish Research Council for Health, Working Life and Welfare (FORTE). Authors' contributions E.K. and M.E, CG, MK designed the study. E.K., M.E, CG, M.K, TF and FJ analysed the data. E.K wrote the manuscript with input from all authors. M.E oversaw overall direction and planning. Acknowledgements We are grateful for Alena Lindfors and her essential assistance in designing the search strategy and conducting the searches. We would also like to thank Maria Gidhagen for her valuable assistance during the article screening process. References Platz T. Clinical Pathways in Stroke Rehabilitation2021. Norrving B, Barrick J, Davalos A, Dichgans M, Cordonnier C, Guekht A, et al. Action Plan for Stroke in Europe 2018-2030. 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The Development of the Improving Participation after Stroke Self-Management Program (IPASS): An Exploratory Randomized Clinical Study. Top Stroke Rehabil. 2016;23(4):284-92. Wolf TJ, Spiers MJ, Doherty M, Leary EV. The effect of self-management education following mild stroke: an exploratory randomized controlled trial. Top Stroke Rehabil. 2017;24(5):345-52. Barchéus I-M, Ranner M, Månsson Lexell E, Larsson-Lund M. Occupational therapists’ experiences of using a new internet-based intervention - a focus group study. Scand J Occup Ther. 2024;31(1):2247029. Bird M-L, Mortenson WB, Eng JJ. Evaluation and facilitation of intervention fidelity in community exercise programs through an adaptation of the TIDier framework. BMC Health Serv Res. 2020;20(1):68. Forster A, Ozer S, Brindle R, Barnard L, Hardicre N, Crocker TF, et al. An intervention to support stroke survivors and their carers in the longer term: results of a cluster randomised controlled feasibility trial (LoTS2Care). Pilot and Feasibility Studies. 2023;9(1):40. Kuo YH, Chien YK, Wang WR, Chen CH, Chen LS, Liu CK. Development of a home-based telehealthcare model for improving the effectiveness of the chronic care of stroke patients. Kaohsiung J Med Sci. 2012;28(1):38-43. Markle-Reid M, Fisher K, Walker KM, Beauchamp M, Cameron JI, Dayler D, et al. The stroke transitional care intervention for older adults with stroke and multimorbidity: a multisite pragmatic randomized controlled trial. BMC Geriatr. 2023;23(1):687. Pallesen H, Pedersen SKS, Sørensen SL, Næss-Schmidt ET, Brunner I, Nielsen JF, et al. "Stroke - 65 plus. Continued active life." A randomized controlled trial of a self-management neurorehabilitation intervention for elderly people after stroke. Disabil Rehabil. 2024:1-10. Sahely A, Sintler C, Soundy A, Rosewilliam S. Feasibility of a self-management intervention to improve mobility in the community after stroke (SIMS): A mixed-methods pilot study. PLoS One. 2024;19(8):e0286611. Sit JW, Chair SY, Choi KC, Chan CW, Lee DT, Chan AW, et al. Do empowered stroke patients perform better at self-management and functional recovery after a stroke? A randomized controlled trial. Clin Interv Aging. 2016;11:1441-50. Cadilhac DA, Hoffmann S, Kilkenny M, Lindley R, Lalor E, Osborne RH, et al. A Phase II Multicentered, Single-Blind, Randomized, Controlled Trial of the Stroke Self-Management Program. Stroke. 2011;42(6):1673-9. Joubert J, Davis SM, Donnan GA, Levi C, Gonzales G, Joubert L, et al. ICARUSS: An effective model for risk factor management in stroke survivors. Int J Stroke. 2020;15(4):438-53. Vluggen T, van Haastregt JCM, Tan FE, Verbunt JA, van Heugten CM, Schols J. Effectiveness of an integrated multidisciplinary geriatric rehabilitation programme for older persons with stroke: a multicentre randomised controlled trial. BMC Geriatr. 2021;21(1):134. Wang S, Li Y, Tian J, Peng X, Yi L, Du C, et al. A randomized controlled trial of brain and heart health manager-led mHealth secondary stroke prevention. Cardiovascular Diagnosis & Therapy. 2020;10(5):1192-9. Caetano LC, Ada L, Romeu Vale S, Teixeira-Salmela LF, Scianni AA. Self-management to promote physical activity after discharge from in-patient stroke rehabilitation: a feasibility study. Top Stroke Rehabil. 2021:1-11. Kamoen O, Maqueda V, Yperzeele L, Pottel H, Cras P, Vanhooren G, et al. Stroke coach: a pilot study of a personal digital coaching program for patients after ischemic stroke. Acta Neurol Belg. 2020;120(1):91-7. Sakakibara BM, Lear SA, Barr SI, Goldsmith CH, Schneeberg A, Silverberg ND, et al. Telehealth coaching to improve self-management for secondary prevention after stroke: A randomized controlled trial of Stroke Coach. Int J Stroke. 2021:17474930211017699. Saywell NL, Vandal AC, Mudge S, Hale L, Brown P, Feigin V, et al. Telerehabilitation After Stroke Using Readily Available Technology: A Randomized Controlled Trial. Neurorehabil Neural Repair. 2021;35(1):88-97. Tan C, Qin Y, Liao C, Liu J, Peng Q, Jiang W, et al. Effect of Continuous Nursing Model Based on WeChat Public Health Education on Self-Management Level and Treatment Compliance of Stroke Patients. Iran J Public Health. 2022;51(5):1040-8. Harwood M, Weatherall M, Talemaitoga A, Barber PA, Gommans J, Taylor W, et al. Taking charge after stroke: promoting self-directed rehabilitation to improve quality of life--a randomized controlled trial. Clin Rehabil. 2012;26(6):493-501. Tielemans NS, Visser-Meily JM, Schepers VP, van de Passier PE, Port IG, Vloothuis JD, et al. Effectiveness of the Restore4Stroke self-management intervention "Plan ahead!": A randomized controlled trial in stroke patients and partners. J Rehabil Med. 2015;47(10):901-9. Brouns B, van Bodegom-Vos L, de Kloet AJ, Tamminga SJ, Volker G, Berger MAM, et al. Effect of a comprehensive eRehabilitation intervention alongside conventional stroke rehabilitation on disability and health-related quality of life: A pre-post comparison. J Rehabil Med. 2021;53(3):jrm00161. Preston E, Dean CM, Ada L, Stanton R, Brauer S, Kuys S, et al. Promoting physical activity after stroke via self-management: a feasibility study. Top Stroke Rehabil. 2017;24(5):353-60. Gauthier LV, Nichols-Larsen DS, Uswatte G, Strahl N, Simeo M, Proffitt R, et al. Video game rehabilitation for outpatient stroke (VIGoROUS): A multi-site randomized controlled trial of in-home, self-managed, upper-extremity therapy. EClinicalMedicine. 2022;43:101239. Krauss MJ, Holden BM, Somerville E, Blenden G, Bollinger RM, Barker AR, et al. Community Participation Transition After Stroke (COMPASS) Randomized Controlled Trial: Effect on Adverse Health Events. Arch Phys Med Rehabil. 2024. Smith JD, Li DH, Rafferty MR. The Implementation Research Logic Model: a method for planning, executing, reporting, and synthesizing implementation projects. Implement Sci. 2020;15(1):84. Rimmer B, Brown MC, Sotire T, Beyer F, Bolnykh I, Balla M, et al. Characteristics and Components of Self-Management Interventions for Improving Quality of Life in Cancer Survivors: A Systematic Review. Cancers (Basel). 2023;16(1). Klockar, E., Kylén, M., Gustavsson, C., Finch, T., Jones, F., & Elf, M. (2023). Self-management from the perspective of people with stroke–An interview study. Patient Education and Counseling , 112 , 107740. Kristine Stage Pedersen S, Lillelund Sorensen S, Holm Stabel H, Brunner I, Pallesen H. Effect of Self-Management Support for Elderly People Post-Stroke: A Systematic Review. Geriatrics (Basel). 2020;5(2). Audulv, Å., Ghahari, S., Kephart, G., Warner, G., & Packer, T. L. (2019). The Taxonomy of Everyday Self-management Strategies (TEDSS): A framework derived from the literature and refined using empirical data. Patient Education and Counseling , 102 (2), 367-375. Supplementary Files Additionalfile1..docx Additionalfile2.Dataextraction.docx Additionalfile3studycharacteristics.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6047723","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":453146547,"identity":"1467eabf-f6a7-4804-9019-a69e0e3a2c22","order_by":0,"name":"Erika Klockar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAiElEQVRIiWNgGAWjYDACHgbGBzykamE2IFkLmwRpWvh5Dh+reNvGYM9PtBbJ3ra0m3PbGBJnNhCrxeA8j9lt3jaGBIMDxGqxB2opBmqxtydaiwFvjxkzUAvjBmJ1MEicOZYsOeecROIMom3h70k++OFNmY09fwPR1kAtI1H9KBgFo2AUjAL8AAB1Vx7NCMlmuwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-5806-8812","institution":"Dalarna University: Hogskolan Dalarna","correspondingAuthor":true,"prefix":"","firstName":"Erika","middleName":"","lastName":"Klockar","suffix":""},{"id":453146548,"identity":"71f53533-c114-4d5b-b776-9e49d37b8eba","order_by":1,"name":"Maya Kylén","email":"","orcid":"","institution":"Kristianstad University: Hogskolan Kristianstad","correspondingAuthor":false,"prefix":"","firstName":"Maya","middleName":"","lastName":"Kylén","suffix":""},{"id":453146549,"identity":"4dc5507b-8fb9-4868-9231-bad27b846fb9","order_by":2,"name":"Catharina Gustavsson","email":"","orcid":"","institution":"Landstinget Dalarna: Region Dalarna","correspondingAuthor":false,"prefix":"","firstName":"Catharina","middleName":"","lastName":"Gustavsson","suffix":""},{"id":453146550,"identity":"a7813ead-45f8-4de4-8458-0c51c419fc06","order_by":3,"name":"Tracy Finch","email":"","orcid":"","institution":"Northumbria University","correspondingAuthor":false,"prefix":"","firstName":"Tracy","middleName":"","lastName":"Finch","suffix":""},{"id":453146551,"identity":"cfcaaff1-84fa-4a37-8358-a7cca1f8cfe1","order_by":4,"name":"Fiona Jones","email":"","orcid":"","institution":"University of London","correspondingAuthor":false,"prefix":"","firstName":"Fiona","middleName":"","lastName":"Jones","suffix":""},{"id":453146552,"identity":"9db6ffba-fff3-4840-84e3-4e4da9727770","order_by":5,"name":"Marie Elf","email":"","orcid":"","institution":"Dalarna University: Hogskolan Dalarna","correspondingAuthor":false,"prefix":"","firstName":"Marie","middleName":"","lastName":"Elf","suffix":""}],"badges":[],"createdAt":"2025-02-17 12:08:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6047723/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6047723/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82617924,"identity":"be348b55-0ef2-4c04-b1f5-c7c2036e39ca","added_by":"auto","created_at":"2025-05-13 11:54:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":121593,"visible":true,"origin":"","legend":"\u003cp\u003eConsolidated Framework for Implementation Research (CFIR) (ref). Lists of the five domains (Inner setting, outer setting, intervention characteristics, process and characteristics of individuals) and underlying constructs.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6047723/v1/e1d73cbe62c1ba5cd47681de.png"},{"id":82616854,"identity":"5eaa4ac1-c50b-402c-a549-a1309188efb0","added_by":"auto","created_at":"2025-05-13 11:46:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":77829,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePRISMA-flow chart of the process of identification, screening and selection of studies.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6047723/v1/25c298fa19bcf778de11f62c.png"},{"id":84103789,"identity":"42833c6c-9d9b-4d64-b348-fff6b35ffbb2","added_by":"auto","created_at":"2025-06-06 21:13:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1153986,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6047723/v1/e7dae5e5-3921-4dd7-b8fb-b39ee6074298.pdf"},{"id":82617925,"identity":"f43e3bab-3710-425b-84f5-29aa3796f159","added_by":"auto","created_at":"2025-05-13 11:54:40","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":23389,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1..docx","url":"https://assets-eu.researchsquare.com/files/rs-6047723/v1/97c800622b0843a014542626.docx"},{"id":82616860,"identity":"0aa691f6-a5e6-47d8-91e7-afa1947be9d8","added_by":"auto","created_at":"2025-05-13 11:46:40","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":285519,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile2.Dataextraction.docx","url":"https://assets-eu.researchsquare.com/files/rs-6047723/v1/1ad19ab5251542e80cd08153.docx"},{"id":82617926,"identity":"2f84a123-100d-47d0-b901-7e0a9211a0fd","added_by":"auto","created_at":"2025-05-13 11:54:40","extension":"xlsx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":27819,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile3studycharacteristics.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6047723/v1/beb498ef839f04934a0edd6e.xlsx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eBarriers and Enablers for Implementing Self-Management Support for Stroke Survivors: A Mixed-Methods Systematic Review\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eEvery year, approximately 17\u0026nbsp;million people worldwide suffers a stroke, making stroke one of the common causes of disabilities (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) and many face challenges in managing their long-term recovery (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). This systematic literature review aimed to identify barriers and enablers in self-management support interventions that support long-term self-management after a stroke. Stroke survivors often face long-lasting physical, emotional, social, economic and cognitive consequences (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), which affects their overall quality of life and participation (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The rehabilitation needs after stroke are often extended and complex, and there is evidence that those needs are often not being met (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Stroke survivors may also experience lack of information, support and preparation for discharge from acute stroke care (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), despite recommendations in stroke guidelines that early supported discharge is available and consequently conducted in-home (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). To address these issues, the Action Plan for Stroke in Europe 2018\u0026ndash;2030, states that a goal for 2030 is that after discharge, all persons with remaining disabilities after stroke should be provided with a plan for community rehabilitation and self-management support (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). This is also supported by the International Stroke Organization (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSelf-management support is often described as equipping people with the necessary skills, knowledge, and confidence in managing their health, which includes both physical and psychosocial health (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) and has been found to positively affect quality of life and self-efficacy (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Even so, self-management support interventions vary in content from narrow focus of disease control and compliance to medical advice, to the more broader approach that includes collaboration around a person\u0026rsquo;s needs to live their lives as independent and satisfying as possible (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Furthermore, the theoretical underpinnings of self-management support programs, the content, dose and timing of delivery show great variation (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), as well as different implementation strategies used.\u003c/p\u003e \u003cp\u003eDespite growing recognition of self-management's importance, the factors influencing its success in the context of long-term implementation is not fully understood. To contribute to the knowledge around sustainable self-management support, this study aims to explore and synthesize barriers and enablers of long-term self-management for stroke survivors across diverse health care settings.\u003c/p\u003e \u003cp\u003eThe complexity of self-management and self-management support can make it difficult to compare studies of self-management interventions. In the present review we used the Consolidated Framework for Implementation Research (CFIR) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), to provide a structure for understanding the multifaceted factors that influence healthcare implementation outcomes. This framework consists of five domains with related constructs and subconstructs that influence the implementation of innovations in practice (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eUsing CFIR, we aimed to enhance the transferability and comparability of results across the included studies to inform future intervention and implementation research. This approach provided a systematic way to categorizing and evaluating barriers and enablers across individual, organizational, and systemic levels. CFIR has been used in healthcare research to facilitate tailored interventions and improve implementation success (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn summary, self-management support after stroke is a promising approach but the factors influencing the success of self-management support interventions can be successful in the long-term is not fully understood. Furthermore, it is necessary to consider a broad range of factors when designing and implementing self-management support programs, and how these factors affect long-term self-management for individuals with stroke which are yet to be reviewed. The overall aim of this systematic literature review was to identify barriers and enablers for implementation of self-management support interventions for people with stroke across different settings.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e We carried out a systematic review of quantitative, qualitative, and mixed-methods studies, using narrative synthesis. This approach allowed for a comprehensive exploration and understanding of the multifaceted factors that may influence long-term self-management (measured\u0026thinsp;\u0026gt;\u0026thinsp;6 months). A narrative synthesis method was employed to integrate evidence from multiple study designs, using the principles of The Joanna Briggs Institute guidance for mixed-methods systematic reviews (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). The 27-item Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) checklist was used for reporting the findings (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The review was registered in PROSPERO (CRD42024508432).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEligibility criteria\u003c/h2\u003e \u003cp\u003eWe used the Population, Exposure and Outcome framework (PEO) (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) to develop study eligibility criteria. Studies were eligible if they met the following criteria:\u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePopulation\u003c/strong\u003e \u003cp\u003eadults (\u0026lt;\u0026thinsp;18 years) diagnosed with stroke and all categories of health care professionals involved in stroke care.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eExposure\u003c/strong\u003e \u003cp\u003eself-management intervention in stroke care, delivered in any type of health care setting (in-hospital, community setting, in home).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eOutcome\u003c/strong\u003e \u003cp\u003eAll outcomes reporting long-term effects of self-management interventions at least 6 months post-intervention.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eThe time frame was determined to studies published between 2009\u0026ndash;2024. Studies were included regardless of study design (quantitative, qualitative and mixed methods studies). Inclusion and exclusion criteria are displayed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInclusion and exclusion criteria\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eInclusion criteria\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eExclusion criteria\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePopulation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdults (\u0026lt;\u0026thinsp;18 years) with stroke diagnosis\u003c/p\u003e \u003cp\u003eHealth care professional in stroke care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient populations with mixed diagnosis where the stroke population could not be separated in the results\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExposure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSelf-management intervention in any kind of stroke care setting (in-hospital, out-hospital, community setting, in-home)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInterventions that consisted of only one part of self-management (e.g., solely problem-solving), if self-management was not mentioned at all in the intervention description.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOutcome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll outcomes reporting long-term effects of self-management interventions at least 6 months post-intervention.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYear\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u0026ndash;2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePublications before 2009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDesign\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAny\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLanguage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnglish, Swedish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-English\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePublication types\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFull publication in peer-reviewed journal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLetters, editorials, reviews, dissertations, abstracts, conference papers, protocols\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSearch strategy and database\u003c/h3\u003e\n\u003cp\u003eA comprehensive search strategy was developed by the authors in collaboration with an information specialist. Following databases were searched; OVID, Medline, SCOPUS, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Web of Science. Test searches were performed to evaluate and refine the search strategy. The searches were conducted on 170222, 241022, and 270524.\u003c/p\u003e\n\u003ch3\u003eSearch terms\u003c/h3\u003e\n\u003cp\u003e Boolean searches using the operators \u0026ldquo;AND\u0026rdquo; / \u0026ldquo;OR\u0026rdquo; / \u0026rdquo;NOT\u0026rdquo; were constructed with selected search terms and combination of search terms as appropriate for each database following respective guidelines, example can be found in Additional file 1.\u003c/p\u003e \u003cp\u003eSearch results were exported to EndNote citation manager software. The total search findings were compiled, and duplicate papers were removed to generate a final list of search findings for the review.\u003c/p\u003e\n\u003ch3\u003eStudy selection\u003c/h3\u003e\n\u003cp\u003eCovidence software was used to manage the data collection (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Covidence is a web-based collaboration software platform that streamlines the production of systematic and other literature reviews. After eliminating all duplicates, titles and abstracts were screened for relevance. Most of the screening (90%) was done by the first author (EK) with a research assistant performing 10% of the screening. Full-text articles of relevant abstracts were retrieved and read in full to confirm the relevance and decide on final exclusion or inclusion by EK, MG and MK. Conceptually difficult articles were discussed with research group members (EK, MK, ME, CG).\u003c/p\u003e\n\u003ch3\u003eData extraction and appraisal\u003c/h3\u003e\n\u003cp\u003eA purpose-designed data extraction form was developed and used jointly by the research group in Covidence to facilitate the systematically retrieval of data relevant to the aim of the study. The form included variables describing the included studies. Main findings relevant to enablers and barriers of implementation of the interventions were also extracted from the results and discussion section. We chose to include data from the discussions section as it often contained interpretations and insights from the authors that gave a rich image and multiple views on factors of importance.\u003c/p\u003e \u003cp\u003eInitial data were extracted by EK and a research assistant, with MK and ME checking 30% of the data to verify its accuracy, introducing a layer of quality control of the process. Any discrepancies encountered during data extraction were resolved through discussions in the research group, ensuring consensus and maintaining the integrity of the data collected. The data in Covidence was finally imported into a Microsoft Excel spreadsheet.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData analysis and synthesis\u003c/h2\u003e \u003cp\u003eFirst, we extracted data on barriers and enablers using the expressions and terminologies from the original papers (Additional file 2 and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In the second step, we analysed the extracted data using narrative synthesis (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), with CFIR (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) serving as a deductive framework for the analysis. This included mapping the extracted barriers and enablers to one of the constructs or subconstructs of the CFIR framework through discussions in the research group. The discussions ensured that no barriers or enablers were forced into a construct with a poor correspondence. Following the principles of the narrative synthesis, data from constructs and subconstructs were then analyzed thematically to develop an overarching narrative in each construct and subconstruct.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eQuality appraisal\u003c/h3\u003e\n\u003cp\u003eThe methodological quality of the included articles was assessed using the Mixed Methods Appraisal Tool (MMAT) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The appraisal tool consists of five criteria that evaluate the sampling strategy, sample representativeness, measurements, risk of nonresponse bias and appropriateness of statistical analysis. A rating of \u0026ldquo;Yes\u0026rdquo;, \u0026ldquo;No\u0026rdquo; or \u0026ldquo;Can\u0026rsquo;t tell\u0026rdquo; for each item is provided, but no overall summary rating. EK, ME and MK conducted the quality appraisal Additional file 2.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eIn total, 37 articles were included in the systematic review (Figure 2). The initial search identified 7 275 articles. After the first screening, 404 articles were selected for eligibility assessment. Following a full-text review,367 articles were excluded for not meeting the inclusion criteria, resulting in a final selection of 37 articles. A full description of the included studies is in Additional file 2.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eCharacteristics of included studies\u003c/h3\u003e\n\u003cp\u003eThe included studies represented twelve different countries, with Australia and China being the most frequently represented, each contributing six studies. Predominantly, randomized controlled trials constituted the primary study design (n=21), while the participants mostly consisted of individuals with stroke (n=32). Sample sizes ranged from 4 to 381 participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePatient-reported outcomes (n=30) and measurement tools (n=23) were the prevailing methods of data collection, ranging over 27 different outcome areas. The outcome assessments covered areas such as activity level, Activities of Daily Living levels, cognitive abilities, cardiovascular measurements, quality of life and self-efficacy. Quality of life was the most common measurement (n=24), followed by cardiovascular outcomes (n=15) and physical functioning (n=14). Self-efficacy was measured in 10 of the included studies, whereas self-management ability was measured in only 4 studies. Broad self-management interventions were dominating (n=17), whereas self-management of physical abilities (n=6) and self-management for secondary prevention (n=6) were equally prevalent. Most studies were conducted in-home settings (n=17). An overview of study characteristics is displayed in Additional file 2. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003ch3 id=\"_Toc189141633\"\u003eQuality appraisal\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003eAll the studies included were judged to meet sufficient quality standards based on the MMAT (22). \u0026nbsp;While no specific cut-off score was applied, studies were included only if their main appraisal questions were rated as \u0026ldquo;Yes.\u0026rdquo; Studies with a \u0026ldquo;No\u0026rdquo; for key appraisal criteria were excluded. Detailed quality assessments are available in Additional file 2. \u0026nbsp;\u003c/p\u003e\n\u003ch2 id=\"_Toc189141634\"\u003eBarriers and enablers for long-term self-management after stroke\u003c/h2\u003e\n\u003cp\u003eBarriers and enablers were identified across all domains of the CFIR and covered 26 of 39 constructs. The \u003cem\u003einnovation domain\u003c/em\u003e had the highest frequency of covered constructs (6 out of 8 constructs covered), followed by \u003cem\u003eimplementation domain\u003c/em\u003e, \u003cem\u003eindividual domain\u003c/em\u003e, \u003cem\u003einner setting domain\u003c/em\u003e and the least frequency of covered constructs were seen in the \u003cem\u003eouter setting domain\u003c/em\u003e (4 out of 10 constructs covered). The most prominent constructs are described in text with related references. For full display of included studies and the constructs and subconstructs that are related to each study see Table 2. A more detailed description of barriers and enablers are in Additional 1. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Summary of enablers and barriers for self-management support interventions\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCFIR domain\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCFIR construct\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCFIR subconstruct\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnabler\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBarrier\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eInnovation domain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eB. Evidence Base\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(23-41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eC. Relative advantage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(34, 38, 41-45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eD. Adaptability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(23, 24, 31, 38, 40, 46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(25, 38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eG. Design\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(24, 26, 28-31, 33, 34, 37-41, 43, 47-51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(24, 29, 31, 32, 35, 38, 39, 41-46, 48, 49, 52)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eH. Innovation cost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eOuter setting domain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eA. Critical incidents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(38-40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eC. Local conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(25, 29, 38, 41, 42, 46)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eInner setting domain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eA. Structural characteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eA.2. Information technology infrastructure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eA.3. Work Infrastructure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(28, 43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(46, 53)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eD. Culture\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eD.2. Recipient-Centeredness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(25, 43, 51)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eD.3. Deliverer-Centeredness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eF. Compatibility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(25, 34, 36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eJ. Available resources\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eJ. 1. Funding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(31, 38, 49)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eJ. 3. Materials \u0026amp; Equipment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(37, 40, 48, 54)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eK. Access to Knowledge \u0026amp; Information\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(23-28, 32, 36, 38, 43, 49-51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(31)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eIndividuals domain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eF. Implementation Team Members\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eH. Innovation Deliverers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(25, 33, 39, 41-43, 48, 51, 55, 56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(51)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eI. Innovation Recipients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(23, 24, 28, 30, 33, 43, 44, 46, 49, 51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(23, 25, 29, 31, 36, 40, 43, 46, 47, 49, 52-55)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eImplementation Process domain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eB. Assessing needs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eB. 1. Innovation Deliverers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(23, 24, 26, 42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(39, 53)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eB. 2. Innovation Recipients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(24, 27, 34, 40, 54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(23, 29, 33, 40, 42, 53)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eC. Assessing context\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(24, 41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eE. Tailoring Strategies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(23, 31, 32, 34, 35, 38, 53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eG. Doing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eH. Reflecting \u0026amp; Evaluating\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eH. 1. Implementation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(28, 30, 42)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eH. 2. Innovation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e(31, 36, 38, 47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(24, 31-33, 39-41, 52, 56)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eI. Adapting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e(48)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eInnovation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbout half of the included articles based their self-management interventions on established theories, frameworks or self-management programs to guide the development or implementation of their interventions and these were viewed as enablers. Several theories recurred, such as the Self-Determination Theory (26), the Social Cognitive theory and its construct of self-efficacy (30, 39, 41). Also, the Chronic Disease Self-Management Program (CDSMP) was mentioned (25, 30, 33) as a framework to develop or guide interventions. Although, CDSMP is best classified as a self-management program rather than a theoretical framework. Additional frameworks such as Medical Research Council (MRC) Framework (36, 38) were noted in some studies for structuring the design and evaluation of interventions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStudies highlighted several ways in which the interventions aimed to improve upon existing practices, particularly in their ability to offer more comprehensive, integrated, and patient-centred care, often through longer duration (38, 42), shared-care models with broad perspectives (34, 43), to aim at enhanced self-efficacy (41), or the use of technology (45). On\u0026nbsp;comparison, a barrier was seen when the new intervention was too similar to care as usual\u0026nbsp;(41).\u003c/p\u003e\n\u003cp\u003eFlexibility in terms of methods for delivery of the intervention to reach more participants or to adapt to various accessibility needs and learning preferences ensured broader reach and inclusivity (31). Personalization of the content was used to better address each participant\u0026rsquo;s unique challenges and strengths, potentially leading to more impactful outcomes (23). Barriers for adaptability were, for example, when sessions posed a cost for some participants (the use of a phone for participating in a session), highlighting the need for more adaptability by offering alternative delivery methods to improve access (25).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTurning to design features, one key enabler was the use of an individualized approach, where participants set personal goals, created action plans, and adapted the programs based on their specific needs, preferences, and abilities (24, 33, 38, 41). Another enabler was the incorporation of telemedicine and digital platforms. These tools provided patients with access to health education, real-time monitoring, and communication with healthcare providers to extend the reach of care. This approach was particularly beneficial for individuals in remote or under-resourced areas (34, 37, 47). Multidisciplinary care was also highlighted as an important design feature, addressing a broad range of physical, psychological, and social needs (28, 31). Additionally, involvement of family and social support, continuous follow-up and peer support were noted as enablers (28, 39).\u003c/p\u003e\n\u003cp\u003eSeveral design-related barriers limited the effectiveness and accessibility of self-management interventions, particularly challenges in delivery, population inclusion criteria, and outcome measurements. Insufficient structuring of interventions across care transitions and inadequate documentation of intervention components reduced the overall feasibility\u0026nbsp;and effectiveness of the intervention in one study (24). Excessive measurement requirements, detailed diaries, or lengthy questionnaires could discourage participation and limit the quality of the data collection (29, 46). Additionally, if the intervention were delivered in short sessions, had low contact hours, or lack of ongoing input and support, intervention effectiveness was limited (48, 49).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eExclusion criteria often prevented patients with greater needs to participate in interventions. Rigid timelines and fixed settings further limited flexibility, particularly for older or frail participants and those with cognitive or communication challenges (31, 45, 52). Recruitment delays and competing trials also hindered program access (42, 43). Challenges in evaluating outcomes were notable. Bias from contamination across control and intervention groups, non-blinded allocation, and recall bias complicated outcome evaluations (39, 44). Additionally, complex interventions were difficult to evaluate due to insufficient power to detect meaningful effects since they could include multiple components, varying levels of individual tailoring, multiple behavior change mechanisms, and internal and external relationships (38, 39).\u0026nbsp;\u003c/p\u003e\n\u003ch3 id=\"_Toc189141636\"\u003eOuter setting\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003eThe COVID-19 pandemic introduced critical barriers to the implementation of self-management studies that were conducted during the pandemic. These included shifts in delivery modes, prolonged recruitment times, and altered participant eligibility, all of which impacted study processes (38, 39).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn public funded healthcare where care on all levels was free of charge and the access to rehabilitation facilities was high, participation in self-management support programs were enabled (26). However, notable barriers were also identified, including transportation\u0026nbsp;challenges\u0026nbsp;(25, 26, 42, 46), limited access to rehabilitation and specialized services\u0026nbsp;(26, 29, 46)\u0026nbsp;and inadequate integration of care\u0026nbsp;(41). In addition, variability in site-specific resources and staffing further created difficulties in accessing and delivering self-management interventions\u0026nbsp;(38).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInner setting\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEnablers among work infrastructure included having clear pathways for rehabilitation and when care was extended without interruptions (28, 43). It was beneficial to pre-schedule patient appointments before discharge to ensure that protocols for follow-up were followed which is a key component of self-management support (43). Barriers could concern organizational issues or intervention deliverers waiting for other professions to give the participants medical clearance to participate (46).\u003c/p\u003e\n\u003cp\u003eAnother key enabler was when integrate cultural context into self-management support design, for them to be inclusive, relevant, and effective across diverse patient groups, which in turn could enhance the intervention\u0026rsquo;s effectiveness and engagement (29, 51). Barriers included the failure to incorporate cultural context into intervention design, so that unique needs of specific populations like veterans or gender issues were overseen (25, 43).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding barriers limited scalability and accessibility, restricting features like multilingual text messages or home-based therapy. Practical issues, such as time and travel constraints, further hinder implementation, even with financial support (31, 38, 49).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRegarding materials and equipment, discomfort or refusal to use specialized devices (54), technical challenges with remote communication (48), limited access to technology and digital skills (37), and compliance issues with self-reported data collection tools were all\u0026nbsp;barriers for implementation\u0026nbsp;(40). These factors highlight the need for user-friendly, accessible, and reliable materials to support intervention success.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAccess to knowledge and information were important to consider. Comprehensive education and training for both providers and participants, along with tailored resources and ongoing support, were crucial enablers in ensuring consistent and effective implementation of interventions (24, 28, 38, 43).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIndividuals\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThose involved in delivering the intervention could be enablers for the implementation process by playing a critical role in behaviour change for the recipients, by providing accountability and dialogue (55), or motivation (41, 48). Another enabler was the role facilitators could be to the persons receiving the intervention (42). Facilitators were furthermore seen as a key component by Damush (25), where their regular phone call to the participants were much appreciated as a reminder that someone was concerned about their health. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEnablers related to intervention recipients varied across studies. Participants with sedentary behaviour and low self-efficacy improved most in physical activity programs (46), while high self-efficacy and good baseline quality of life enhanced self-management outcomes, although limiting measurable gains in areas like walking (23). Interventions tailored for individuals with mild to moderate disability, or those with broad inclusion criteria addressing diverse needs, proved effective by improving functional outcomes, promoting patient engagement, and facilitating implementation through adaptability to diverse contexts (24, 49). In addition, motivation was reported as a key for engagement and adherence (43).\u003c/p\u003e\n\u003cp\u003eBarriers included physical limitations like fatigue and mobility decline, particularly among older participants, and cognitive challenges such as memory impairment and low self-awareness, which hindered goal-setting (29, 52). Motivation among participants varied, with lack of interest, post-stroke adjustment stress, and loss of hope after intervention withdrawal were cited as barriers (25, 49). Practical concerns like transportation, financial costs, and in-person session burdens were significant, especially for older or remote participants (31).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplementation process\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSuccessful implementation of self-management support interventions relied heavily on comprehensive training and support for those delivering the intervention. One barrier described was that the intervention deliverers also had to conduct care as usual, and the self-management support integrated into care was not always provided to the extent originally intended (39). Another barrier was when staff perceptions of the value of the intervention was low and potentially added to workload. Healthcare professionals\u0026rsquo; perceptions of the intervention in Brouns (51) presented potential barriers to implementation. The intervention may not have aligned with their roles, causing scepticism about its practicality. Concerns were raised about inadequate training, a lack of confidence in delivering the intervention, and its perceived complexity or additional workload. These factors contributed to low engagement and inconsistent implementation. To address these issues, the study highlights the importance of providing adequate training, streamlining the intervention to fit existing workflows, and involving professionals early in the design process to ensure relevance and practicality.\u003c/p\u003e\n\u003cp\u003eVarious implementation strategies were used and identified as enablers in the included studies. Stepwise approaches allowed for gradual adaptation of complex interventions into clinical practice (31). Additionally, frameworks like Template for Intervention Description and Replication (TIDier) were highlighted for their role in improving the implementation (35). The TIDieR framework is a tool designed to standardize how interventions are described, ensuring that essential details are clearly documented. The structured checklist helps researchers and practitioners outline critical aspects such as the content of the intervention, the delivery methods, the setting, and who delivered it. This clarity facilitates replication and implementation in various clinical settings, thereby enhancing the likelihood of success (34).\u003c/p\u003e\n\u003cp\u003eTailored strategies addressed both patient and provider barriers and facilitators through structured integration, stakeholder education, and support services such as helpdesks (53). To ensure fidelity to core program principles, which is key for scalability and consistency, standardized training for healthcare professionals, regular provider-researcher meetings, and systematic documentation must be implemented (38). These measures ensured that self-management support was delivered consistently across settings while allowing adaptation to individual patient needs. Tailored strategies addressed barriers and facilitators through structured integration, stakeholder education, and support services like helpdesks (53). Ensuring fidelity was key, achieved through standardized training, regular provider-researcher meetings, and systematic documentation, which supported scalability and consistency (38). Standardized delivery was also reinforced with intervention guides and workshops on program theory of the intervention (34). To sustain effects, periodic booster sessions and strategies to maintain self-efficacy post-intervention were proposed, ensuring long-term benefits for participants (23, 33).\u003c/p\u003e\n\u003cp\u003eIn some studies, limitations in research quality, such as the lack of qualitative and process evaluations (28, 42) and reliance on subjective outcomes (30, 48), hindered a comprehensive understanding of intervention implementation and its potential for improvement. In some studies, the lack of qualitative and process evaluations (28, 42), along with reliance on subjective outcomes (30, 48), hindered understanding and improvement of intervention implementation. Self-reported data could risk socially desirable responses, skewing results (31, 41). Many studies relied on generic outcome measures that failed to capture the nuanced impacts of self-management interventions. Additionally, the lack of sensitive measurement tools, particularly in small studies, limited the ability to generate meaningful findings (32, 33, 52). Defining and measuring self-management in a concrete way was challenging without clear outcome measures, making evaluations more difficult (39). Broad evaluations were seen as important, incorporating feedback from care professionals, patients, and caregivers to ensure diverse perspectives (31). Economic analyses could provide essential feasibility insights, while patient-relevant outcomes such as Patient-Reported Outcome Measures (PROMs) were important to capture real-world complexities and continuous improvement opportunities (38, 47). Assessing unmet needs prior to implementation could aid in refining interventions effectively (36).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study identified and synthesized barriers and enablers for implementation of long term self-management support for people with stroke across diverse settings. The review highlighted that implementing self-management interventions in clinical settings is a complex process. The long-term sustainability of these interventions depends on several critical factors. The key enablers identified included the necessity for adequate training for healthcare professionals and ongoing support for people with stroke, which are essential for effective implementation. Interventions designed to meet individual needs and satisfy diverse populations enhance relevance and engagement. In addition, individualized approaches that actively involved stroke survivors and their families in goal setting and decision-making fostered a sense of ownership, motivation, and engagement with the interventions. Partnerships between healthcare teams and patients were central to the success of these interventions. Stepwise integration into clinical workflows, supported by structured frameworks like TIDieR (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), facilitated better adaptation to local contexts, reduced resistance, and promoted smoother adoption. The main barriers noted included poor adaptation to existing practices, where interventions that did not align with current care workflows or professional roles faced significant resistance. Additionally, diverse needs among participants posed challenges for example variations in cognitive, emotional, and physical abilities of stroke survivors made it difficult to design universally effective interventions. Resource constraints, including limited funding, staffing, and institutional support, also created significant challenges to implementation and sustainability.\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eThe variation in study design and delivery\u003c/h2\u003e \u003cp\u003eThe review highlights the considerable variation in the design, conceptualization and implementing self-management support programs, making direct comparisons challenging. However, the review also showed that many studies noted the possibility to tailor the intervention to the context as an enabler. While this flexibility can be considered a strength, enabling interventions to target different populations and goals, it also highlights the need for clearer theoretical grounding. Not all the included articles grounded their interventions in a theory. For the area to advance the researchers should prioritize articulating the theoretical underpinnings that inform the design of the interventions. Doing so not only ensures that interventions are evidence-based but also contributes valuable insights into understanding the mechanisms that drive change and specifically, what works, for whom, and under what circumstances. There has been research that highlights the need to develop implementation logic models, so that the implementation process can be more planned, and tailored, to achieve the desired implementation outcomes (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere has been initiatives to define what self-management support to persons with stroke should consist of, for example Ansong (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e), who identified eight essential attributes of self-management support post-discharge, including pre-discharge planning, education, goal-setting, and community reintegration. These attributes aim to enhance patient empowerment and self-efficacy, leading to improved outcomes and reduced healthcare costs. However, there are concerns regarding healthcare professionals' workload and resource constraints, making it challenging to apply this concept practically (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor those incorporating some or all these self-management principles for specific outcome targets (blood pressure, physical ability, communication etc), it is equally important to state the theoretical underpinnings and theories of change that are used, so that self-management is just not an \u0026ldquo;add on\u0026rdquo; concept, without meaning. Morgan and colleagues (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) argue that more narrow approaches for support often involve disease control which can limit patient empowerment and reinforce a paternalistic relationship between health care professionals and the patient. In the meantime, a broader approach supports people to manage their life and situation living with one or more condition. The focus is more on \u0026lsquo;what matters to people and how they can be supported to shape their own lives\u0026rsquo; (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e In our review, we observed that studies often failed to explicitly connect barriers and enablers to implementation strategies and outcomes. Thus, there is also a need to develop implementation logic models, so that the implementation process can be more planned, and tailored, to achieve the desired implementation outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eThe importance of the individual\u003c/h2\u003e \u003cp\u003eCFIR highlights the crucial role of individuals in implementation of interventions. Many of the included studies have identified barriers like fatigue, functional limitations, and lack of transportation that hinder engagement in self-management programs. Research has shown that many individuals who could benefit from support such as those with aphasia, cognitive disabilities, severe conditions, or low health literacy are often excluded or do not participate (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). Audulv et al. (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e) emphasize the need to understand the diverse strategies patients employ for self-management, which is essential for crafting comprehensive interventions targeting social, emotional, and medical support. Current self-management interventions often narrow their focus, primarily addressing secondary prevention or fall risks, but a more holistic approach that recognizes each patient's unique needs is essential (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eSelf-management as an outcome measure\u003c/h2\u003e \u003cp\u003eA notable finding from this review is the limited number of studies explicitly measuring self-management. At the same time, most studies examined intervention effects on broader outcomes such as physical health improvements or secondary prevention measures (e.g., reduction in stroke recurrence). However, a few studies directly assessed participants' development of self-management skills, such as problem-solving or goal-setting. This raises an important question as to whether these interventions effectively support participants' broader and lasting self-management capacity. In studies focused on secondary prevention it was observed that many studies overlooked self-management measurement. This may not necessarily reflect the lack of interest in self-management but rather questions whether there are validated tools or frameworks explicitly designed for this purpose. For example, tools exist to measure certain components of self-management such as goal-setting ability, health literacy, or self-efficacy for managing long-term conditions, but these often assess isolated aspects. Recent research continues to highlight the challenges in defining and measuring self-management within health interventions. For example, a systematic review by Rimmer et al. (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e) emphasized the need for standardized definitions and consistent outcome measures in self-management research to accurately evaluate intervention effectiveness\u003c/p\u003e \u003cp\u003eThere are examples of self-efficacy scales such as Stroke-self efficacy scale SSEQ (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e) which are closely aligned with confidence to self-manage and offer a tailored measure for persons with stroke. Selecting an appropriate self-efficacy or self-management scale necessitates careful consideration of the target population, the specific aspects of self-efficacy being measured, and the tool's psychometric properties.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eLong-term effects\u003c/h2\u003e \u003cp\u003eWe did not assess whether the included studies were successful at achieving significant changes in their primary outcomes. While success often is defined by measurable improvements in primary outcomes, valuable insights can also be drawn from studies that did not achieve significant changes. Such studies provide opportunities to explore and identify challenges in implementation, participant engagement, or contextual factors that may have influenced the impact. There is a value in understanding how intervention components, theoretical underpinnings, or delivery mechanisms might be optimized for future research. Furthermore, some studies evaluated their impact by using qualitative methods which provides a different perspective on implementation, and can provide unique understanding of the perspectives and value experienced by recipients of self-management support interventions. Many self-management intervention studies also lack follow-up which decreases the possibilities to explore the effect of self-management support over time (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). This is also stated in the Action Plan for Stroke in Europe, which calls for researchers to investigate if self-management programmes improve long term outcomes of stroke rehabilitation (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e In this review, we used the CFIR framework to identify key factors that influence the implementation of self-management interventions. The framework offered valuable insights into the complexities of implementation processes. However, the framework does not prescribe implementation strategies. Rather, it serves as a tool to understand the diverse factors that can influence implementation outcomes. The CFIR can be combined with the Expert Recommendations for Implementing Change (ERIC) strategies ((\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cfirguide.org\u003c/span\u003e\u003cspan address=\"https://cfirguide.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). ERIC assemble strategies identified by experts as effective in enhancing the adoption, implementation, and sustainability of evidence-based interventions. ERIC provides a list of discrete implementation strategies that can be selected based on the specific barriers and facilitators identified within a given implementation context.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eOne of the strengths of this review is the inclusion of diverse studies that explored self-management interventions for people after stroke across various settings, and intervention types. This broad approach allows for a comprehensive understanding of the barriers and enablers influencing self-management interventions. We synthesized data from different contexts and thus the findings have broader applicability to a wide range of settings. We used a stepwise method and first identified barriers and enablers. The use of the CFIR framework then provided a structured and consistent approach to identifying and categorizing barriers and enablers ensuring that key factors across studies were systematically evaluated.\u003c/p\u003e \u003cp\u003eThe identification of barriers and enablers relied on the researchers\u0026rsquo; interpretation of the findings reported in the included studies. This subjective process may introduce bias, as researchers\u0026rsquo; understanding of self-management could shape how barriers and enablers were identified or categorized. However, we involved multiple reviewers with diverse perspectives, and we also derived themes from original studies at the first step. In addition, we discussed differences in those to agree categorizations that were less clear\u003c/p\u003e \u003cp\u003eThe lack of a unified definition of self-management in the included studies may have influenced how barriers and enablers were conceptualized and interpreted. Different studies may emphasize certain dimensions of self-management (e.g., physical, emotional, or cognitive aspects) over others, making it challenging to draw comparisons across interventions.\u003c/p\u003e \u003cp\u003eWe did not assess whether the studies included were successful in achieving their intended intervention outcomes. It is possible that those studies reporting fewer barriers, and more enablers were also more successful, which may influence the interpretation of results. Conversely, studies with significant barriers may provide valuable insights for improving future interventions, regardless of their success in achieving primary outcomes.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eFuture research on self-management interventions\u003c/h2\u003e \u003cp\u003eThe review highlighted that many self-management support interventions lack clear definitions or targeted approaches for divers populations such as stroke with specific needs, including those with mild-to-moderate disability, cognitive impairments, or frailty. Thus, future research should focus on designing interventions that are adaptable to diverse physical and cognitive abilities. In addition, understanding how barriers and enablers differ across subgroups could help to create more personalized and effective strategies. It is also important to demonstrate the importance of integrating established frameworks like CFIR, TiDIER, and logic models from the outset of implementation projects. These frameworks have been suggested to ensure interventions are well-designed, transparent, and adaptable to meet the specific needs of their contexts. However, research on the impact of these frameworks on project outcomes is still limited. Although some included studies used TiDIER, and reported that as an enabler, there was a lack of clarity in the reporting of intervention components and their mechanisms of action. Future research could add knowledge by identifying which specific components (e.g., goal setting, health literacy training, peer support) contribute most to self-management success.\u003c/p\u003e \u003cp\u003eMany studies in the review did not measure self-management as an outcome or used fragmented tools. To address these future studies should adopt comprehensive self-management measures (e.g., goal-setting ability, health literacy, self-efficacy) to better capture intervention impact.\u003c/p\u003e \u003cp\u003eFew studies in our review may have included process evaluations or examined the cost-effectiveness of interventions. This limits our understanding of how interventions are implemented (e.g., adherence, acceptability, contextual factors).\u003c/p\u003e \u003cp\u003eWe included studies that have measured outcomes in the long-term and research needs to continue to examine whether improvements in self-management skills are sustained over time and lead to long-term health benefits, such as reduced stroke recurrence or enhanced quality of life.\u003c/p\u003e \u003cp\u003eIn addition, there is a need for a comprehensive approach to researching self-management in stroke recovery by develop and incorporates better outcome measurement, a deeper understanding of self-management as a concept, and innovative research designs that allow for the examination of personalized implementation strategies. This would help ensure that self-management interventions are both effective and meaningfully beneficial to stroke survivors.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis review underscores the importance of personalizing self-management support to effectively address the varied cognitive, emotional, and physical needs of patients, which is key to their success. Emphasizing the critical role of ongoing support, such as booster sessions and community resources, this approach could enhance the sustainability and impact of interventions.\u003c/p\u003e \u003cp\u003eEffective implementation also depends on robust methods of assessment. It is crucial to develop objective measures for evaluating self-management and self-efficacy to complement self-reported data, ensuring more reliable and actionable insights.\u003c/p\u003e \u003cp\u003eBy focusing on personalization of care, continuous support mechanisms, and solid evaluation methods the advance of self-management interventions can enhance, ultimately reducing health differences and improving patient outcomes across diverse settings.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCFIR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConsolidated Framework for Implementation Research\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eERIC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eExpert Recommendations for Implementing Change strategies\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMMAT\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMixed Methods Appraisal Tool\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSSEQ\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStroke-self efficacy scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eTiDIER\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTemplate for Intervention Description and Replication\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this published article [and its Additional files]. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research is funded by Dalarna University and the Swedish Research Council for Health, Working Life and Welfare (FORTE). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors' contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eE.K. and M.E, CG, MK designed the study. \u0026nbsp;E.K., M.E, CG, M.K, TF and FJ analysed the data. E.K wrote the manuscript with input from all authors. M.E oversaw overall direction and planning.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful for Alena Lindfors and her essential assistance in designing the search strategy and conducting the searches. We would also like to thank Maria Gidhagen for her valuable assistance during the article screening process.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePlatz T. Clinical Pathways in Stroke Rehabilitation2021.\u003c/li\u003e\n\u003cli\u003eNorrving B, Barrick J, Davalos A, Dichgans M, Cordonnier C, Guekht A, et al. Action Plan for Stroke in Europe 2018-2030. Eur Stroke J. 2018;3(4):309-36.\u003c/li\u003e\n\u003cli\u003eAnsong R, Gazarian P. Healthcare self‐management support of stroke patients after discharge: A conceptual analysis using Rodger\u0026apos;s evolutionary approach. J Adv Nurs. 2024.\u003c/li\u003e\n\u003cli\u003eTing C, Bo Z, Yan D, Jing-Chun F, Liansheng Z, Fujian S. Long-term unmet needs after stroke: systematic review of evidence from survey studies. BMJ Open. 2019;9(5):e028137.\u003c/li\u003e\n\u003cli\u003eLin B-L, Mei Y-X, Wang W-N, Wang S-S, Li Y-S, Xu M-Y, et al. Unmet care needs of community-dwelling stroke survivors: a systematic review of quantitative studies. BMJ Open. 2021;11(4):e045560.\u003c/li\u003e\n\u003cli\u003eLindblom S, Flink M, Sj\u0026ouml;strand C, Laska A-C, Von Koch L, Ytterberg C. Perceived Quality of Care Transitions between Hospital and the Home in People with Stroke. J Am Med Dir Assoc. 2020;21(12):1885-92.\u003c/li\u003e\n\u003cli\u003eLanghorne P, Baylan S. Early supported discharge services for people with acute stroke. Cochrane Database Syst Rev. 2017;2017.\u003c/li\u003e\n\u003cli\u003eFeigin VL, Owolabi MO, Feigin VL, Abd-Allah F, Akinyemi RO, Bhattacharjee NV, et al. 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American Journal Of Translational Research. 2021;13(4):3147-55.\u003c/li\u003e\n\u003cli\u003eKam Yuet Wong F, Wang SL, Ng SSM, Lee PH, Wong AKC, Li H, et al. Effects of a transitional home-based care program for stroke survivors in Harbin, China: a randomized controlled trial. Age Ageing. 2022;51(2):02.\u003c/li\u003e\n\u003cli\u003eMinshall C, Castle DJ, Thompson DR, Pascoe M, Cameron J, McCabe M, et al. A psychosocial intervention for stroke survivors and carers: 12-month outcomes of a randomized controlled trial. Top Stroke Rehabil. 2020;27(8):563-76.\u003c/li\u003e\n\u003cli\u003eNg SSW, Chan DYL, Chan MKL, Chow KKY. Long-term efficacy of occupational lifestyle redesign programme for strokes. Hong Kong Journal of Occupational Therapy. 2013;23(2):46-53.\u003c/li\u003e\n\u003cli\u003eVluggen TPMM, van Haastregt JCM, Verbunt JA, van Heugten CM, Schols J. Feasibility of an integrated multidisciplinary geriatric rehabilitation programme for older stroke patients: a process evaluation. BMC Neurol. 2020;20(1):219.\u003c/li\u003e\n\u003cli\u003eWolf TJ, Baum CM, Lee D, Hammel J. The Development of the Improving Participation after Stroke Self-Management Program (IPASS): An Exploratory Randomized Clinical Study. Top Stroke Rehabil. 2016;23(4):284-92.\u003c/li\u003e\n\u003cli\u003eWolf TJ, Spiers MJ, Doherty M, Leary EV. The effect of self-management education following mild stroke: an exploratory randomized controlled trial. Top Stroke Rehabil. 2017;24(5):345-52.\u003c/li\u003e\n\u003cli\u003eBarch\u0026eacute;us I-M, Ranner M, M\u0026aring;nsson Lexell E, Larsson-Lund M. Occupational therapists\u0026rsquo; experiences of using a new internet-based intervention - a focus group study. Scand J Occup Ther. 2024;31(1):2247029.\u003c/li\u003e\n\u003cli\u003eBird M-L, Mortenson WB, Eng JJ. Evaluation and facilitation of intervention fidelity in community exercise programs through an adaptation of the TIDier framework. BMC Health Serv Res. 2020;20(1):68.\u003c/li\u003e\n\u003cli\u003eForster A, Ozer S, Brindle R, Barnard L, Hardicre N, Crocker TF, et al. An intervention to support stroke survivors and their carers in the longer term: results of a cluster randomised controlled feasibility trial (LoTS2Care). Pilot and Feasibility Studies. 2023;9(1):40.\u003c/li\u003e\n\u003cli\u003eKuo YH, Chien YK, Wang WR, Chen CH, Chen LS, Liu CK. Development of a home-based telehealthcare model for improving the effectiveness of the chronic care of stroke patients. Kaohsiung J Med Sci. 2012;28(1):38-43.\u003c/li\u003e\n\u003cli\u003eMarkle-Reid M, Fisher K, Walker KM, Beauchamp M, Cameron JI, Dayler D, et al. The stroke transitional care intervention for older adults with stroke and multimorbidity: a multisite pragmatic randomized controlled trial. BMC Geriatr. 2023;23(1):687.\u003c/li\u003e\n\u003cli\u003ePallesen H, Pedersen SKS, S\u0026oslash;rensen SL, N\u0026aelig;ss-Schmidt ET, Brunner I, Nielsen JF, et al. \u0026quot;Stroke - 65 plus. Continued active life.\u0026quot; A randomized controlled trial of a self-management neurorehabilitation intervention for elderly people after stroke. Disabil Rehabil. 2024:1-10.\u003c/li\u003e\n\u003cli\u003eSahely A, Sintler C, Soundy A, Rosewilliam S. Feasibility of a self-management intervention to improve mobility in the community after stroke (SIMS): A mixed-methods pilot study. PLoS One. 2024;19(8):e0286611.\u003c/li\u003e\n\u003cli\u003eSit JW, Chair SY, Choi KC, Chan CW, Lee DT, Chan AW, et al. Do empowered stroke patients perform better at self-management and functional recovery after a stroke? A randomized controlled trial. Clin Interv Aging. 2016;11:1441-50.\u003c/li\u003e\n\u003cli\u003eCadilhac DA, Hoffmann S, Kilkenny M, Lindley R, Lalor E, Osborne RH, et al. A Phase II Multicentered, Single-Blind, Randomized, Controlled Trial of the Stroke Self-Management Program. Stroke. 2011;42(6):1673-9.\u003c/li\u003e\n\u003cli\u003eJoubert J, Davis SM, Donnan GA, Levi C, Gonzales G, Joubert L, et al. ICARUSS: An effective model for risk factor management in stroke survivors. Int J Stroke. 2020;15(4):438-53.\u003c/li\u003e\n\u003cli\u003eVluggen T, van Haastregt JCM, Tan FE, Verbunt JA, van Heugten CM, Schols J. Effectiveness of an integrated multidisciplinary geriatric rehabilitation programme for older persons with stroke: a multicentre randomised controlled trial. BMC Geriatr. 2021;21(1):134.\u003c/li\u003e\n\u003cli\u003eWang S, Li Y, Tian J, Peng X, Yi L, Du C, et al. A randomized controlled trial of brain and heart health manager-led mHealth secondary stroke prevention. Cardiovascular Diagnosis \u0026amp; Therapy. 2020;10(5):1192-9.\u003c/li\u003e\n\u003cli\u003eCaetano LC, Ada L, Romeu Vale S, Teixeira-Salmela LF, Scianni AA. Self-management to promote physical activity after discharge from in-patient stroke rehabilitation: a feasibility study. Top Stroke Rehabil. 2021:1-11.\u003c/li\u003e\n\u003cli\u003eKamoen O, Maqueda V, Yperzeele L, Pottel H, Cras P, Vanhooren G, et al. Stroke coach: a pilot study of a personal digital coaching program for patients after ischemic stroke. Acta Neurol Belg. 2020;120(1):91-7.\u003c/li\u003e\n\u003cli\u003eSakakibara BM, Lear SA, Barr SI, Goldsmith CH, Schneeberg A, Silverberg ND, et al. Telehealth coaching to improve self-management for secondary prevention after stroke: A randomized controlled trial of Stroke Coach. Int J Stroke. 2021:17474930211017699.\u003c/li\u003e\n\u003cli\u003eSaywell NL, Vandal AC, Mudge S, Hale L, Brown P, Feigin V, et al. Telerehabilitation After Stroke Using Readily Available Technology: A Randomized Controlled Trial. Neurorehabil Neural Repair. 2021;35(1):88-97.\u003c/li\u003e\n\u003cli\u003eTan C, Qin Y, Liao C, Liu J, Peng Q, Jiang W, et al. Effect of Continuous Nursing Model Based on WeChat Public Health Education on Self-Management Level and Treatment Compliance of Stroke Patients. Iran J Public Health. 2022;51(5):1040-8.\u003c/li\u003e\n\u003cli\u003eHarwood M, Weatherall M, Talemaitoga A, Barber PA, Gommans J, Taylor W, et al. Taking charge after stroke: promoting self-directed rehabilitation to improve quality of life--a randomized controlled trial. Clin Rehabil. 2012;26(6):493-501.\u003c/li\u003e\n\u003cli\u003eTielemans NS, Visser-Meily JM, Schepers VP, van de Passier PE, Port IG, Vloothuis JD, et al. Effectiveness of the Restore4Stroke self-management intervention \u0026quot;Plan ahead!\u0026quot;: A randomized controlled trial in stroke patients and partners. J Rehabil Med. 2015;47(10):901-9.\u003c/li\u003e\n\u003cli\u003eBrouns B, van Bodegom-Vos L, de Kloet AJ, Tamminga SJ, Volker G, Berger MAM, et al. Effect of a comprehensive eRehabilitation intervention alongside conventional stroke rehabilitation on disability and health-related quality of life: A pre-post comparison. J Rehabil Med. 2021;53(3):jrm00161.\u003c/li\u003e\n\u003cli\u003ePreston E, Dean CM, Ada L, Stanton R, Brauer S, Kuys S, et al. Promoting physical activity after stroke via self-management: a feasibility study. Top Stroke Rehabil. 2017;24(5):353-60.\u003c/li\u003e\n\u003cli\u003eGauthier LV, Nichols-Larsen DS, Uswatte G, Strahl N, Simeo M, Proffitt R, et al. Video game rehabilitation for outpatient stroke (VIGoROUS): A multi-site randomized controlled trial of in-home, self-managed, upper-extremity therapy. EClinicalMedicine. 2022;43:101239.\u003c/li\u003e\n\u003cli\u003eKrauss MJ, Holden BM, Somerville E, Blenden G, Bollinger RM, Barker AR, et al. Community Participation Transition After Stroke (COMPASS) Randomized Controlled Trial: Effect on Adverse Health Events. Arch Phys Med Rehabil. 2024.\u003c/li\u003e\n\u003cli\u003eSmith JD, Li DH, Rafferty MR. The Implementation Research Logic Model: a method for planning, executing, reporting, and synthesizing implementation projects. Implement Sci. 2020;15(1):84.\u003c/li\u003e\n\u003cli\u003eRimmer B, Brown MC, Sotire T, Beyer F, Bolnykh I, Balla M, et al. Characteristics and Components of Self-Management Interventions for Improving Quality of Life in Cancer Survivors: A Systematic Review. Cancers (Basel). 2023;16(1).\u003c/li\u003e\n\u003cli\u003eKlockar, E., Kyl\u0026eacute;n, M., Gustavsson, C., Finch, T., Jones, F., \u0026amp; Elf, M. (2023). Self-management from the perspective of people with stroke\u0026ndash;An interview study. \u003cem\u003ePatient Education and Counseling\u003c/em\u003e, \u003cem\u003e112\u003c/em\u003e, 107740.\u003c/li\u003e\n\u003cli\u003eKristine Stage Pedersen S, Lillelund Sorensen S, Holm Stabel H, Brunner I, Pallesen H. Effect of Self-Management Support for Elderly People Post-Stroke: A Systematic Review. Geriatrics (Basel). 2020;5(2). \u003c/li\u003e\n\u003cli\u003eAudulv, \u0026Aring;., Ghahari, S., Kephart, G., Warner, G., \u0026amp; Packer, T. L. (2019). The Taxonomy of Everyday Self-management Strategies (TEDSS): A framework derived from the literature and refined using empirical data. \u003cem\u003ePatient Education and Counseling\u003c/em\u003e, \u003cem\u003e102\u003c/em\u003e(2), 367-375.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Self- management, stroke, systematic review, Consolidated Framework for Implementation Research ","lastPublishedDoi":"10.21203/rs.3.rs-6047723/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6047723/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Stroke may pose significant challenges to individuals and healthcare systems worldwide, and there is a clear need to understand ways to provide effective self-management support. This systematic review aims to identify barriers and enablers for the implementation of self-management support for stroke survivors across various settings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: We conducted a mixed-methods systematic review following PRISMA guidelines, searching CINAHL, Embase, Medline, and Scopus for studies on self-management support with long-term follow-up. The Consolidated Framework for Implementation Research (CFIR) guided our narrative synthesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: After screening 7275 studies and rigorous selection criteria, 37 articles were included. The findings revealed that the implementation of self-management support interventions for stroke survivors is influenced by various enablers and barriers, including training for healthcare professionals, participant motivation, and tailored support. Notable barriers included design and compatibility issues, funding constraints, and local context challenges.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: Effective self-management interventions must be customized to meet the diverse needs of stroke survivors. Enhancing sustainability and impact requires ongoing support, such as booster sessions and community resources, along with robust evaluation methods. Developing objective measures to complement self-reported data is essential for providing reliable insights and meaningful and effective self-management support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSystematic review registration:\u003c/strong\u003e This review is registered with the International Prospective Register of Systematic Reviews (PROSPERO), registration number CRD42024508432.\u003c/p\u003e","manuscriptTitle":"Barriers and Enablers for Implementing Self-Management Support for Stroke Survivors: A Mixed-Methods Systematic Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-13 11:46:35","doi":"10.21203/rs.3.rs-6047723/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"52abd0a0-b2a5-4a36-80d7-29c117525b7f","owner":[],"postedDate":"May 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-06T21:05:02+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-13 11:46:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6047723","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6047723","identity":"rs-6047723","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}