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Open Access

Peer-reviewed

Research Article

Medication self-management interventions for persons with stroke: A scoping review

  • Lauren Cadel,

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing

    Affiliations Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada, Institute for Better Health, Trillium Health Partners, Mississauga, ON, Canada

    ⨯
  • Stephanie R. Cimino,

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Writing – original draft, Writing – review & editing

    Affiliations Rehabilitation Sciences Institute, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada, St. John’s Rehab Research Program, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada

    ⨯
  • Glyneva Bradley-Ridout,

    Roles Methodology, Writing – original draft, Writing – review & editing

    Affiliation Gerstein Science Information Centre, University of Toronto, Toronto, ON, Canada

    ⨯
  • Sander L. Hitzig,

    Roles Conceptualization, Funding acquisition, Writing – review & editing

    Affiliations Rehabilitation Sciences Institute, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada, St. John’s Rehab Research Program, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada, Department of Occupational Science and Occupational Therapy, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada

    ⨯
  • Tejal Patel,

    Roles Conceptualization, Funding acquisition, Writing – review & editing

    Affiliations University of Waterloo School of Pharmacy, Kitchener, ON, Canada, Schlegel-University of Waterloo Research Institute of Aging, Waterloo, ON, Canada

    ⨯
  • Chester H. Ho,

    Roles Conceptualization, Funding acquisition, Writing – review & editing

    Affiliation Division of Physical Medicine & Rehabilitation, Department of Medicine, University of Alberta, Edmonton, AB, Canada

    ⨯
  • Tanya L. Packer,

    Roles Conceptualization, Funding acquisition, Writing – review & editing

    Affiliations Schools of Occupational Therapy and Health Administration, Dalhousie University, Halifax, NS, Canada, Department of Rehabilitation, Radboud University Medical Centre, Nijmegen, The Netherlands

    ⨯
  • Aisha K. Lofters,

    Roles Conceptualization, Funding acquisition, Writing – review & editing

    Affiliations Department of Family and Community Medicine, University of Toronto, Toronto, ON, Canada, Women’s College Research Institute, Toronto, ON, Canada

    ⨯
  • Shoshana Hahn-Goldberg,

    Roles Conceptualization, Funding acquisition, Writing – review & editing

    Affiliations Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada, OpenLab, University Health Network, Toronto, ON, Canada

    ⨯
  • Lisa M. McCarthy,

    Roles Conceptualization, Funding acquisition, Writing – review & editing

    Affiliations Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada, Institute for Better Health, Trillium Health Partners, Mississauga, ON, Canada

    ⨯
  • Sara J. T. Guilcher

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    sara.guilcher@utoronto.ca

    Affiliations Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada, Institute for Better Health, Trillium Health Partners, Mississauga, ON, Canada, Rehabilitation Sciences Institute, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada, St. John’s Rehab Research Program, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada, Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada

    ⨯

Abstract

The use of multiple medications is common following a stroke for secondary prevention and management of co-occurring chronic conditions. Given the use of multiple medications post-stroke, optimizing medication self-management for this population is important. The objective of this scoping review was to identify and summarize what has been reported in the literature on interventions related to medication self-management for adults (aged 18+) with stroke. Electronic databases (Ovid Medline, Ovid Embase, EBSCO CINAHL, Ovid PsycINFO, Web of Science) and grey literature were searched to identify relevant articles. For inclusion, articles were required to include an adult population with stroke undergoing an intervention aimed at modifying or improving medication management that incorporated a component of self-management. Two independent reviewers screened the articles for inclusion. Data were extracted and summarized using descriptive content analysis. Of the 56 articles that met the inclusion criteria, the focus of most interventions was on improvement of secondary stroke prevention through risk factor management and lifestyle modifications. The majority of studies included medication self-management as a component of a broader intervention. Most interventions used both face-to-face interactions and technology for delivery. Behavioural outcomes, specifically medication adherence, were the most commonly targeted outcomes across the interventions. However, the majority of interventions did not specifically or holistically target medication self-management. There is an opportunity to better support medication self-management post-stroke by ensuring interventions are delivered across sectors or in the community, developing an understanding of the optimal frequency and duration of delivery, and qualitatively exploring experiences with the interventions to ensure ongoing improvement.

Citation: Cadel L, Cimino SR, Bradley-Ridout G, Hitzig SL, Patel T, Ho CH, et al. (2023) Medication self-management interventions for persons with stroke: A scoping review. PLoS ONE 18(5): e0285483. https://doi.org/10.1371/journal.pone.0285483

Editor: Jonathan Bayuo, The Hong Kong Polytechnic University, HONG KONG

Received: December 14, 2022; Accepted: April 25, 2023; Published: May 18, 2023

Copyright: © 2023 Cadel et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its supporting information files (S1 Table and S2 Table).

Funding: The research was supported by the Craig H. Neilsen Foundation Psychosocial Research Studies and Demonstration Projects Grant (#855615). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Stroke is one of the leading causes of morbidity and mortality worldwide [1]. Globally in 2019, approximately 12.2 million strokes and 6.6 million stroke-related deaths occurred [1]. Common risk factors for stroke include older age, physical inactivity, consumption of alcohol, poor diet, lower socioeconomic status, and comorbidities such as hypertension, coronary heart disease, diabetes, depression, chronic pain, and atrial fibrillation [1–5]. Individuals who have experienced a stroke have a higher prevalence of comorbidities (43% - 94% of the population) than those without stroke [4, 6, 7].

Medications are commonly used for the prevention of secondary strokes (ischemic and hemorrhagic), as well as for the management of comorbidities and secondary conditions related to the stroke itself [4, 8]. Importantly, adherence to medication post-stroke is critical for minimizing the risk of recurrent strokes [9]. However, medication adherence may be a precursor to the effectiveness of these medication regimens and can be impacted by a multitude of factors, such as an individuals’ beliefs and concerns about medications, functional ability, and access to medication, including who prescribes the medication and how and where it is dispensed [10–12].

Rates of polypharmacy (use of multiple medications, often five or more) vary among adults who experienced a stroke, but have been reported to range between 26% and 75% [4, 13–15]. Despite the potential need for multiple medications to prevent secondary strokes and manage comorbidities (e.g., hypertension, coronary heart disease, diabetes, depression) and secondary conditions (e.g., chronic pain), there is also the risk of potentially inappropriate medication use (e.g., medications with high risk of adverse events) [13]. For example, Matsumoto and colleagues conducted a retrospective cohort study of 361 older adults (aged 65+) who had experienced a stroke and identified potentially inappropriate medications in 65% of patients at discharge [13]. Common potentially inappropriate medications prescribed at discharge included antipsychotics, benzodiazepines, proton pump inhibitors, and non-steroidal anti-inflammatory drugs [13]. Among individuals who have experienced a stroke, polypharmacy has been associated with reduced functional and rehabilitative outcomes [13–15].

Polypharmacy often increases the complexity of a medication regimen [16], which can impact medication-self-management. Individuals with stroke have reported challenges with their overall medication management, including understanding, medication-taking self-efficacy, and medication burden [17–20]. Medication self-management can be impacted by patient, provider, and system level factors [21], including, but not limited to, the number of medications prescribed, complexity of medication regimens, receipt of medication education/ instructions, cost, medication-related supports (e.g., pillboxes and blister packs), healthcare provider knowledge, access to interventions, and structure of the healthcare system [4, 22, 23]. Further to this, a stroke may result in residual deficits that impact an individual’s ability to self-manage their medications.

Optimal medication management, including medication self-management, following a stroke is important to reduce the risk of a recurrent stroke. For this scoping review, we define medication self-management as the range of tasks, skills, and behaviours associated with an individual’s capability, opportunity, and motivation to navigate the physical, social, and cognitive lifestyle factors, changes, and consequences inherent in taking, or choosing not to take, medications in everyday life. These tasks include having the knowledge and related confidence to deal with medical, emotional, and role management, as well as the core skills of problem-solving, decision-making, seeking formal and informal supports, self-tailoring, goal-setting, optimizing social interactions, and engaging in activities, as they relate to managing medications [24, 25].

Given the evidence demonstrating that people who experienced a stroke are prescribed inappropriate medications, along with the data showing the challenges people experience with managing their medications (knowledge, adherence, access), more work is needed to understand how to better support this population with medication self-management. Therefore, the purpose of this scoping review was to identify and summarize what was reported in the literature on interventions related to medication self-management for adults with stroke. Specific aims included identifying the content of the interventions, how the interventions were designed and delivered, the outcome measures used to evaluate the interventions, and the impact of the interventions.

Methods

We conducted this scoping review in accordance with the methodology outlined by Peters et al. [26]. The reporting guidelines for scoping reviews, Preferred Reporting Items for Systematic Reviews and Meta-Analyses–Scoping Review Extension (PRISMA-ScR), were also followed (see S1 Table) [27].

Protocol and registration

The scoping review protocol was registered on Open Science Framework (https://osf.io/89qha).

Eligibility criteria

This scoping review was our second knowledge synthesis related to medication self-management, as part of a larger research study that aims to develop and evaluate a toolkit for medication self-management for persons with spinal cord injury. The first scoping review examined literature related to medication self-management for persons with spinal cord injury [28]. Given that there was limited research within spinal cord injury, we expanded the eligible population to also include persons who have experienced stroke (neurological population that often experiences life-altering changes and significant change to medication regimen). The findings of these reviews are being presented separately based on fundamental differences noted during analysis, such as the state of the research, the content of the interventions, and the outcomes measured.

The inclusion criteria for articles for this review were: (1) an adult population (majority aged 18+) that experienced a stroke; (2) an intervention aimed at modifying or improving medication management; and (3) the intervention incorporated a component of self-management. To meet the first inclusion criteria, at least 50% of the participants had to be over the age of 18 with stroke. We limited this review to adults because the tasks and skills related to medication self-management for a youth population would likely be structured and delivered in a different manner. For the second criteria, medication management was defined as the tasks, skills, and behaviours associated with an individual’s capability, opportunity, and motivation to navigate the physical, social, and cognitive lifestyle factors, changes, and consequences inherent in taking, or choosing not to take, medications. For the third criteria, the intervention had to include a component of self-management. This was based our definition for this scoping review described above. The exclusion criteria were: (4) opinion pieces; (5) conference abstracts; (6) study protocols; or (7) the inability to access the full-text. We excluded conference abstracts and study protocols to ensure all included articles presented finalized results to fully examine their implementation characteristics and associated outcomes. We also excluded knowledge syntheses from data extraction, but reviewed their reference lists for potential articles.

Search methods

An academic health sciences librarian (GBR) developed the search strategy through frequent consultations with members of the research team (LC and SJTG). The following five electronic databases were searched on March 11th, 2022: MEDLINE (Ovid Interface), EMBASE (Ovid Interface), CINAHL Plus (EBSCOhost Interface), APA PsycINFO (Ovid Interface), and Clarivate Web of Science. A second academic librarian PRESS peer-reviewed the Ovid MEDLINE search prior to search translations [25]. The concepts of (traumatic spinal cord injury OR stroke) AND self management AND medication were combined to develop the search. Using each platforms’ command language and controlled vocabulary, the search was translated into the different databases, without limits. The full database search strategies can be found in S2 Table. Grey literature was searched on July 26, 2022. Websites and repositories (World Health Organization, Heart and Stroke Foundation, American Stroke Association, University of Toronto TSpace) were searched for relevant articles.

Selection process

We followed Bramer’s method for deduplication using EndNote X8 [29]. Articles were uploaded to a knowledge synthesis software platform, Covidence, for screening. An interrater test of the titles and abstracts of 150 articles was conducted by three screeners (LC, SRC, SJTG) to ensure good agreement and interpretation of the eligibility criteria. No revisions were made to the eligibility criteria following the interrater test as the screeners had an agreement of over 95%. The remaining titles and abstracts were independently screened by two reviewers and any disagreements that occurred were resolved through consensus. Two screeners (LC and SRC) completed an interrater test of 10 full-text articles to ensure good agreement. With 90% agreement, the remaining full-text articles were double screened by the same screeners. All disagreements were resolved through consensus. If the full-text was published in a language other than English, it was translated using Google Translate and the article was screened using the translated version.

Data charting process

A study-specific, data extraction table was developed in Microsoft Excel. The data extraction table was tested by two extractors (LC and SRC) and no revisions were made. These team members also reviewed each others’ first article extraction to ensure all data was extracted accurately and consistently. Following this review, data were independently extracted from the remaining articles by a single extractor (LC, SRC).

Data items

The data extraction process involved collating information related to the article (title, authors, year of publication, journal, funding), study description (objective, type of population, method of data collection, study design, theoretical orientation, eligibility criteria, outcomes, country, setting), intervention (description, content, frequency, duration, single or multi-component, format, tailoring, modifications, method of delivery, setting), population (sample size, age, sex, gender, ethnicity/race, income, education, marital status, household composition, employment status, comorbidities), outcomes and findings (results and key findings, conclusions). The Template for Intervention Description and Replication (TIDieR) checklist was used to inform the intervention information that was extracted [30].

Synthesis methods

Descriptive approaches were used to synthesize the extracted data. More specifically, descriptions of the study designs, countries, years of publication, intervention characteristics, and intervention outcomes are provided. To synthesize the intervention outcomes, one team member (LC) further categorized them into the following: learning outcomes (knowledge, skills, abilities, attitudes, and understanding achieved through participation in the intervention [31]), behavioural outcomes (actions that individuals consciously engaged or did not engage in [32]), or clinical outcomes (changes in health, function, or quality of life [33]). We used the TIDieR checklist to guide the presentation of the results [30]. A critical appraisal of articles was not conducted and it is not a requirement of scoping reviews [27].

Results

Study selection

The database searches identified 22,125 articles (see Fig 1). Following deduplication, 13,195 articles remained for title and abstract screening. During title and abstract screening, 13,030 articles were excluded, leaving 165 articles for the full-text screen. During full-text screening, 85 articles were excluded. Knowledge syntheses (n = 21) were reviewed for relevant articles, but not included in data extraction or analysis, resulting in 59 relevant articles. For this scoping review, we only present the results of the stroke articles, which resulted in 56 included articles.

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Fig 1. PRISMA 2020 flow diagram of included articles.

https://doi.org/10.1371/journal.pone.0285483.g001

Study characteristics

Characteristics of included articles are displayed in Table 1. The majority of the included studies used a quantitative study design (n = 53) [34–86]. There were two mixed methods studies [87, 88] and one qualitative study [89]. The most common quantitative study designs included randomized controlled trials (n = 31) and prospective studies (n = 11). Most articles (n = 53) were published after 2010 [34–61, 63–66, 68–70, 72–89], with only three being published prior [62, 67, 71]. Studies were conducted across 20 different countries, with the majority conducted in the United States (n = 14) [38, 42–45, 50, 57, 59, 67, 74, 81–83, 88] and China (n = 11) [40, 46, 73, 76–80, 84–86]. Other countries included the United Kingdom (n = 4) [63, 64, 69, 72], South Korea (n = 2) [55, 56], Australia (n = 2) [41, 65], Belgium (n = 2) [54, 75], Germany (n = 2) [49, 60], Ghana (n = 2) [68, 89], Hong Kong (n = 2) [70, 71], India (n = 2) [34, 39], Malaysia (n = 2) [35, 87], New Zealand (n = 2) [36, 61], Pakistan (n = 2) [52, 53], Austria (n = 1) [47], Denmark (n = 1) [48], France (n = 1) [37], Israel (n = 1) [62], Japan (n = 1) [66], Thailand (n = 1) [58], and Turkey (n = 1) [51].

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Table 1. Characteristics of included articles (n = 56).

https://doi.org/10.1371/journal.pone.0285483.t001

Population characteristics

The sample sizes varied, ranging from 2 participants to 5,882 participants (median = 174; IQR = 202). The majority of articles reported the sex (n = 32) [34, 38, 41, 43–49, 52, 53, 56, 57, 59, 61, 65, 66, 68–74, 77–79, 84–86, 88] or gender (n = 19) [35, 37, 39, 40, 42, 51, 54, 55, 58, 60, 62, 63, 75, 76, 80–83, 87] of participants, but no articles reported both sex and gender. Level of education was reported by 29 articles [35, 36, 39, 42, 45, 47, 50–53, 55, 58, 59, 62, 68, 70, 71, 73, 74, 76–81, 84, 87–89], with variability in how education level was collected and how the highest level of education achieved by the participant was reported. Approximately one third of included articles reported the participants’ ethnicity (n = 19) [35, 36, 42–45, 50, 59, 61–64, 69, 74, 81–83, 87, 89], marital status (n = 17) [36, 39, 50, 51, 55, 58, 69–71, 73, 74, 76, 77, 82–84, 88], and employment status (n = 17) [35, 36, 50, 51, 55, 58, 63, 68–71, 76, 82, 83, 87–89]. Income level (n = 12) [45, 46, 51, 52, 55, 58, 59, 62, 68, 73, 76, 81] and household composition (n = 10) [36, 39, 41, 42, 51, 52, 61, 62, 71, 72] were reported less frequently, in about one fifth of included articles. Comorbidities experienced by participants were reported in 27 articles [35, 37, 39, 41, 45, 47, 48, 51, 52, 54, 56–60, 62, 66, 68–70, 73, 76–78, 84, 87, 88], with hypertension, diabetes, and dyslipidemia being the most commonly reported.

Intervention characteristics

The characteristics of interventions are displayed in Table 2. The goals of the interventions were largely similar across the included studies and focused on: secondary stroke prevention through risk factor management and lifestyle modifications, improving medication-related knowledge, self-efficacy, medication adherence, and quality of life, increasing knowledge of stroke (signs, symptoms, management, risk factors), and improving care coordination and transitions. A component of medication self-management was the primary focus in 13 studies [39, 49, 52, 62–64, 66, 67, 72, 73, 78, 81, 86], with the majority (n = 43) including it as a part of a larger intervention or as an outcome measure. Two-thirds of the interventions consisted of multiple components (n = 42) [34, 35, 38–48, 51–54, 56–60, 62–65, 67–74, 77, 79, 82–85, 87, 88], while the other third were stand-alone interventions (n = 14) [36, 37, 49, 50, 55, 61, 66, 75, 76, 78, 80, 81, 86, 89]. The multicomponent interventions consisted of a combination of the following: education, counseling or coaching, workshops, text reminders, follow-up discussions, information materials, health assessments, referrals or connections to healthcare providers, support services, goal setting, and medication reviews. Just over half of the interventions (n = 33) were tailored to the participants based on their individual needs or goals [34, 37, 38, 40–50, 52–54, 56–59, 62, 63, 65, 67–69, 71, 74, 75, 80, 85, 89]. Only two articles described the modification of the intervention during the course of the study [37, 60]. One study actively modified the length of the sessions depending on the participants’ current state and level of fatigue allowing the sessions to be divided into shorter ones, as needed [37]. The other intervention planned for a possible modification before implementation and modified the intensity of their intervention schemes (module-based support program) [60].

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Table 2. Intervention characteristics aligning with the TIDieR checklist (n = 56).

https://doi.org/10.1371/journal.pone.0285483.t002

The majority of interventions were delivered by nurses (n = 15) [42, 43, 54, 61, 62, 65, 68, 70, 71, 75–77, 79, 81, 88], a multidisciplinary clinical team (n = 11) [35, 37, 40, 46, 50–53, 60, 67, 74], or pharmacists (n = 7) [34, 39, 48, 49, 66, 72, 78] and were initiated in a hospital or healthcare setting (n = 40) [34–60, 62, 68, 70, 73–77, 80, 81, 85–87], with 11 of those including a cross-sectoral or community-based component [36, 44–46, 48, 62, 73–76, 85]. Fewer interventions were delivered to individuals in the community only (n = 9). The setting was not clearly reported in 7 articles [65–67, 69, 71, 88, 89]. Seventeen interventions used only in-person methods for delivery [34, 37, 39, 49, 59–65, 67, 69, 71, 72, 81, 88] and six used only technological mechanisms for delivery [47, 52, 53, 66, 86, 89]. However, most interventions leveraged the use of both face-to-face interactions and technology for delivery (n = 33) [35, 36, 38, 40–46, 48, 50, 51, 54–58, 68, 70, 73–80, 82–85, 87]. The technological component of the interventions consisted of telephone follow-ups, coaching, interviews or hotlines, informational or motivational videos, online chats, text reminders, education, and mobile applications (e.g., mHealth apps). Most interventions were conducted on an individual basis (n = 47) [34–41, 43–45, 47–56, 60–69, 72–84, 86, 87, 89], rather than in a group setting (n = 2) [59, 71]. Seven interventions included both individual and group components [42, 46, 57, 58, 70, 85, 88]. There was significant variation in the frequency and duration of the interventions. The frequency ranged from daily to a total of two sessions and the duration ranged from 10 days to 12 months.

Intervention outcomes

Outcomes specific to each of the interventions are displayed in Table 2. The included interventions evaluated a number of different outcomes, which were categorized as behavioural outcomes [32], learning outcomes [31], and clinical outcomes [33]. Behavioural outcomes (e.g., medication adherence, compliance, or persistence, physical activity, blood pressure monitoring, nutrition) were the most commonly targeted outcomes across the interventions. Medication adherence was assessed as a primary or secondary outcome in 34 interventions. Of these 34 interventions, the majority improved medication adherence. However, no positive impacts on medication adherence were found in four studies [48, 52, 61, 66]. Learning outcomes included self-efficacy and knowledge. Knowledge was evaluated in eight interventions and demonstrated improvements related to knowledge about stroke, secondary prevention, medications, side effects, and response to side effects [34, 35, 37, 41, 45, 55, 62, 71]. Self-efficacy was assessed in six interventions [35, 42, 46, 51, 70, 87], with two-thirds (n = 4) showing improvements [35, 46, 70, 87]. The concept of self-management was evaluated using a specific self-management outcome measure for tasks, skills, or behaviours in four studies [37, 51, 70, 80], demonstrating favourable outcomes in three [37, 70, 80]. The clinical outcomes (e.g., blood pressure, low-density lipoprotein, depression/ mood, quality of life) evaluated across the included studies did not directly align with medication self-management, but may have been impacted by self-management tasks, skills, or behaviours.

Discussion

The purpose of this scoping review was to identify what was reported in the literature on interventions for medication self-management for adults who experienced a stroke. Based on the 56 included articles, we found that: (1) there were fewer interventions (n = 13) that specifically targeted a component of medication self-management; (2) the majority of interventions were initiated in-hospital or in a healthcare setting, rather than in the participants’ own community environment; (3) there is limited reporting of the ideal frequency, duration, and sustainability of the interventions to improve outcomes; and (4) interventions frequently focused on quantitative outcome measures, with limited qualitative exploration of implementation considerations and experiences.

We found that the majority of interventions did not specifically target medication self-management, but rather incorporated a small component, such as medication adherence, as part of a broader intervention focused on changing health behaviour. Importantly, medication self-management encompasses the tasks, skills, and behaviours related to one’s navigation of the physical, social, and cognitive lifestyle factors, changes, and consequences inherent in taking, or not taking, medications. Despite medication self-management including all these components, the majority of literature to date and available supports focus heavily on medication adherence. Given the wide range of challenges individuals who experienced a stroke face related to medications (e.g., medication burden, medication understanding, medication-taking self-efficacy, medication management [17–20]), it is important for interventions to focus on these areas in order to comprehensively address medication self-management. Our review identified only one study that took a more focused approach at medication self-management [62]. Specifically, this study involved a tailored and multifaceted nursing intervention that followed a structured guidebook to improve individual’s knowledge and skills with medication use and dietary habits post-stroke [62]. The intervention addressed affective (e.g., trusting environment, coping, self-esteem, self-control, self-empowerment, decision-making, self-confidence), instrumental (self-care skills, accepting health status, increasing medication self-management capability), and cognitive aspects of medication self-management (perceptions, attitudes, and beliefs of illness, self-management of medications, memory techniques, medication understanding, skills, follow-up visits and clinical tests). Significant positive effects were seen in the intervention group compared to controls for knowledge of medication shape and dosage, side effects, and response to side effects, but they were not sustained at six months. This was because the control group had increased their knowledge in these areas, eliminating the significant difference between the groups. The authors of that study suggested that the participants in the control group may have learned on their own or received education from other healthcare providers in the community. The authors also suggested that the intervention may have been more beneficial if it was delivered several months post-stroke once patients’ medication regimens were stabilized and if additional time was spent on medication self-management.

Most interventions were initiated in-hospital or in a healthcare setting (n = 40), with few initiated in the community (n = 9). Unfortunately, while in hospital, patients are often not actively involved in the management of their medication regimens and do not have a full understanding of what is involved until they are discharged and confronted with day-to-day challenges (e.g., cost, establishing routines, physically taking medications, concerns about medication use) [90, 91]. Following a stroke, the return to the individuals’ pre-hospital residence is often the goal [92]. There is evidence reported by previous research exploring discharge locations post-stroke, where home is the most common location, with rates of patients returning home ranging between 63% and 83% [93–95]. Based on the large percentage of individuals who are returning home post-stroke [93–95], it is important to have access to services and programs in the community to support medication self-management. This need was also noted by Gibson and colleagues who conducted a qualitative study with persons who experienced a stroke, caregivers, and nurses and highlighted the importance of having strategies to improve medication adherence once discharged from hospital [91]. General chronic disease self-management programs delivered in the community have shown promising outcomes for persons who experienced a stroke with improving self-efficacy, health behaviours, and quality of life [96], and can offer key learnings to apply to medication self-management programs. Furthermore, the return home for the majority of patients post-stroke emphasizes the importance of having medication self-management programs available in the community, as individuals and their caregivers learn to navigate a new norm and are responsible for most, if not all, aspects of their medication regimen.

In this scoping review we identified immense variation in the frequency (daily to total of two sessions) and duration (10 days to 12 months) of interventions related to medication self-management for those with stroke. While the variation may be attributed to a number of different factors (e.g., country, health system, funding), there is a need to better understand the optimal frequency and duration of interventions to maximize patient outcomes and experiences, while also maintaining sustainability over time. The Integrated Sustainability Framework by Shelton and colleagues presents multilevel factors (outer contextual factors, inner contextual factors, processes, intervention characteristics, and implementer characteristics) that facilitate the sustainability of interventions across settings and in different contexts [97]. These factors should be considered during the development, implementation, and adaptation of interventions, rather than once implementation has occurred. As such, when developing interventions, Shelton and colleagues recommend the use of sustainability theory as part of the planning process [97]. Overall, this scoping review identified a lack of consistency in the frequency and duration of the interventions, with limited understanding of their sustainability over time. The sustainability of interventions is critical to continually improve patient outcomes and experiences, and thus, should be considered as part of the design process.

Most studies were quantitative, with few using mixed methods or qualitative study designs. Qualitative research can supplement and provide important context to quantitative outcome measures by answering the ‘how’s’ and ‘why’s’ during development, implementation, and evaluation of interventions [98, 99]. For example, qualitative research can contribute to a better understanding of the feasibility, acceptability, and appropriateness of the intervention by allowing for a more in-depth discussion of these outcomes by those who were involved (as participants or as implementers). Understanding how participants and individuals implementing the intervention perceived it (frequency, duration, outcomes, delivery, overall experiences) can also support sustainability by identifying challenges and adapting those areas. Further to this, qualitative methods can allow researchers to explore, not only if an intervention was successful in achieving quantitative targets, but how it was successful, why it was successful, who it worked for, in what setting, and when [99]. Given the infancy of published mixed methods and qualitative research in this area, there is an opportunity to expand the collective knowledge around how individuals with stroke experience the interventions in which they participate, as well as why interventions work, for whom, when, and where.

Gaps and opportunities for future research

Based on the findings from this scoping review, key areas requiring future research include the following: (1) interventions that comprehensively address medication self-management beyond adherence; (2) interventions that are delivered across sectors or in the community in order to better address self-management, including the assessment of outcomes depending on location of delivery; (3) mixed methods studies to develop a better understanding of what frequency and duration of intervention delivery is most feasible but that will also yield the maximum benefit (through sustainability); and (4) qualitative studies to explore how individuals experience the interventions, including feedback for ongoing adaptation and improvement. While extending research in these areas, it is also important to collect and report on the cognitive level of the participants to better understand who benefits, or does not, from specific interventions.

Limitations

There are a few limitations of this scoping review to note. First, despite a comprehensive search of five electronic databases and grey literature, it is possible that relevant articles were missed because we excluded conference abstracts, opinion pieces, protocols, and articles in which we could not access the full-text. The University of Toronto is the largest academic library in Canada and has an extensive catalogue of resources [100], but there were instances where we could not access full texts from this system or from the interlibrary loan system. Second, self-management is not a well or consistently defined term. While we tried to be comprehensive in our search for self-management and self-management related tasks, skills, and behaviours, it is possible that articles were missed due to the terms searched. Similarly, in this review, we did not explore medication self-management support (from caregivers, healthcare providers, etc.) for individuals who have experienced a stroke, which is a key area of future work. Third, we did not get a professional translation of the articles published in a language other than English (n = 1), so it is possible that some details were missed or not entirely accurate during data extraction. Lastly, while not a requirement of scoping reviews, we did not conduct a critical appraisal of included articles [27].

Conclusions

This scoping review included 56 articles related to medication self-management for adults with stroke. While there were several studies that incorporated medication adherence into a larger intervention, there were few that specifically targeted medication self-management. There remains an opportunity to better support medication self-management for adults with stroke by comprehensively addressing all areas of self-management, delivering interventions across sectors or in the community to ensure individuals are in an environment where they self-manage, understanding the optimal frequency and duration of interventions while maintaining sustainability, and qualitatively exploring experiences with interventions.

Supporting information

S1 Table. Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist.

https://doi.org/10.1371/journal.pone.0285483.s001

(DOCX)

S2 Table. Full search strategies for all electronic databases.

https://doi.org/10.1371/journal.pone.0285483.s002

(DOCX)

S3 Table. List of full-text reports excluded by reason (n = 106).

https://doi.org/10.1371/journal.pone.0285483.s003

(DOCX)

Acknowledgments

We would like to thank Julia Martyniuk, a librarian at the University of Toronto, who peer reviewed the Ovid MEDLINE search strategy.

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