GRAPHICAL ABSTRACT

INTRODUCTION

Hypertension is a global issue, with an estimated 918 million individuals affected worldwide in 2000—a number anticipated to rise to 1.56 billion by 2025 [1,2]. Population growth and aging are the primary factors contributing to the increasing prevalence of hypertension. In low-income and middle-income nations, this rise may also be attributed to a widespread distribution of elevated blood pressure [3]. Empirical research consistently shows that high blood pressure is not only a risk factor but also a primary contributor to various cardiac, cerebral, and vascular conditions, including stroke, coronary heart disease, heart failure, atrial fibrillation, peripheral artery disease, cognitive impairment, and dementia [4]. Management of hypertension typically begins with healthy lifestyle interventions such as reducing salt and alcohol intake, increasing consumption of fruits and vegetables, weight loss, regular physical activity, and avoiding smoking. When lifestyle modifications prove ineffective, antihypertensive medication therapy is a viable approach to controlling blood pressure [5]. However, adherence to antihypertensive medication remains a significant challenge; many patients discontinue their medications within the first few months without informing their doctor [6]. A meta-analysis found that an estimated 45.2% of patients were non-adherent, and 83.7% had uncontrolled blood pressure [7].

Multiple barriers may impede a patient’s adherence to a treatment regimen [8]. To enhance adherence, interventions must incorporate components that effectively overcome these barriers [9]. According to the Medical Research Council (MRC)’s framework, systematically developing complex interventions using theory is recommended, as this approach is more likely to improve efficacy [10]. Applying theory in intervention development can help challenge researchers’ preconceptions about intervention effectiveness [11]. Integrating a theoretical framework into intervention design enables researchers to identify practical components and assess their applicability across different contexts [12,13]. Evidence suggests that theory-based programs are superior to non-theory interventions in influencing behavior [14,15].

The systematic review conducted by Holmes et al. [16] revealed that theory-guided interventions to improve adherence can encourage sustainable behavioral changes in clinical settings. This review primarily used self-report questionnaires to measure treatment adherence, with social cognitive theory (SCT) accounting for half of the theories applied. In contrast, Conn et al. [17] found that the most widely used theories and models were SCT, motivational interviewing (MI), and the health belief model (HBM). SCT emphasizes the relationship among 3 key components—personal, environmental, and behavioral—and their role in modifying behavior [18]. MI facilitates behavior change through a patient-directed approach, assisting clients in exploring and resolving ambivalence. Fundamentally, MI is characterized not by its techniques but by its style, which fosters strong human relationships [19]. The HBM centers on 4 primary cognitive constructs: perceived susceptibility to disease, perceived severity of disease, perceived benefits of behavior modification, and perceived barriers to action [20].

Most patients with hypertension receive treatment in primary healthcare and community pharmacy settings. Therefore, primary care represents an optimal environment for interventions designed to enhance medication adherence. To date, no reviews have specifically examined the application of theory in developing interventions for improving medication adherence in primary care hypertension patients. To address this gap in the literature, the primary objective of this systematic review is to provide a comprehensive description of interventions that utilize health behavioral models/theories to enhance medication adherence among individuals diagnosed with hypertension in primary healthcare and community settings. Additionally, this review examines whether delivering a theory-based intervention significantly improves medication adherence.

METHODS

This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [21].

Search Method

Two reviewers, TY and AWW, searched the PubMed and Scopus databases for relevant literature in October 2023. The search was restricted to full text articles published within the last 10 years. A literature search was conducted using keywords based on the population, intervention, comparison, and outcome (PICO) framework [22]. The population term was “hypertension,” the intervention term was “theory” (including its synonyms), and the outcome terms were “medication adherence” and “medication compliance.” Boolean operators “AND” and “OR” were used to facilitate the search. Additionally, a combination of keywords was used in the title, abstract, full text, and Medical Subject Headings (MeSH). Reference lists of the identified publications were also examined for additional relevant studies.

Eligibility Criteria

The literature search applied the following inclusion criteria: (1) full text papers employing a randomized controlled trial (RCT) design, (2) publications written in English, (3) explicit statement of the theoretical framework underpinning the intervention, (4) focus on adult patients diagnosed with hypertension, and (5) research conducted in primary healthcare and community settings.

Data Extraction

The search results were imported into the Rayyan website to facilitate screening and removal of duplicate titles [23]. Two reviewers, TY and AWW, independently screened the titles and abstracts. The full texts of potentially relevant studies were then evaluated separately. Data extraction was performed by these reviewers, and relevant information from the included studies was recorded in an Excel spreadsheet. The data extraction file included categories such as author, year of publication, country of origin, number of participants, study subjects or setting, inclusion and exclusion criteria, intervention modality and strategy, presence of a control group, the profession of the interventionist, theories used, duration of follow-up, techniques for measuring adherence, and the extent of change observed in medication adherence. Any disagreements in data extraction were resolved through discussion among 4 reviewers: TY, AWW, SAK, and NMY.

Quality Assessment

The risk of bias in each included study was independently assessed by 4 reviewers (TY, AWW, SAK, and NMY) using the Joanna Briggs Institute (JBI) critical appraisal tool for RCTs [24]. Disagreements were resolved through discussion. The JBI checklist evaluates aspects such as randomization, concealed allocation, baseline comparability between treatment and control groups, blinding, potential bias due to dropout, reliability of outcome measurements, and appropriateness of statistical analysis. In this review, studies were categorized as high quality if they scored above 70%, medium quality if between 50% and 70%, and low quality if below 50% [25].

Ethics Statement

This study is a systematic review that utilized data extracted from published articles; therefore, institutional review board approval was not required.

RESULTS

Study Selection

A total of 446 publications were identified, with 402 articles undergoing screening. Following title and abstract screening, 56 full text articles were assessed for inclusion. Figure 1 presents a PRISMA diagram of the search procedure for this review. Ultimately, 10 studies were included: 9 RCTs and 1 pilot RCT.

Study Characteristics

A total of 3485 individuals participated across the 10 studies, with sample sizes ranging from 42 to 1186. The interventions were conducted in various countries, including China [26], Chile [27], Iran [28,29], Palestine [30], Spain [31], Taiwan [32], and the United States (n=3) [33-35], which had the highest number of interventions. Nine studies were conducted in primary healthcare clinics, while 1 was carried out in a community pharmacy.

Five studies focused on primary hypertension patients [26,27,29,30,32], 2 studies on patients with hypertension who had uncontrolled blood pressure [33,34], 1 study on older men with hypertension [28], 1 study on patients with both hypertension and diabetes mellitus [35], and 1 study on patients with hypertension, asthma, or chronic obstructive pulmonary disease [31]. The number of intervention sessions varied from 1 to 15, and follow-up durations ranged from 3 months to 12 months. Table 1 details the study characteristics, theoretical frameworks, intervention strategies, and methods used to measure medication adherence.

Theoretical Frameworks of the Studies

The theories employed in the selected articles include the predisposing, reinforcing, and enabling constructs in educational diagnosis and evaluation (PRECEDE) model [29], SCT [27,28,32], the transtheoretical model (TTM) [33,34], MI [30], and information-motivations-behavioral (IMB) skills models [35]. Two studies integrated theoretical frameworks by combining MI with SCT [26] and using a combination of TTM, MI, and HBM [31]. Table 2 summarizes the newly identified theories used to enhance medication adherence.

Intervention Techniques and Approaches

The studies employed various methods, including mobile apps/mobile health [29,35] telephone counseling [33,34], text messages [27], face-to-face [26,30,31], and a combination of face-to-face with web-based [32] or phone calls [28]. In 5 trials, nurses were responsible for implementing the intervention [26-28,30,32]. Only 1 study [31] used pharmacists to deliver the intervention.

Medication Adherence Measurements

The studies used various self-report questionnaires to assess medication adherence. The instruments included the Hill Bone Compliance to High Blood Pressure Scale (HBCHBPS) [29], the Hypertension Self-Care Activity Level Effects Scale (H-SCALE) questionnaire [32], the Treatment Adherence Questionnaire of Patients with Hypertension (TAQPH) [26], the Morisky-Green-Levine Medication Adherence Questionnaire (MGLMAQ) [27,31,33,34], the 8-item Morisky Medication Adherence Scale (MMAS-8) [30,35], and the hypertension self-efficacy scale [28]. Six studies [26,27,29-32,35] documented a significant improvement in medication adherence during the intervention.

Risk of Bias of the Selected Studies

The potential for bias is summarized in Table 3. The risk of bias was categorized as high in 5 studies [26,27,32,33,35], moderate in 4 studies [29-31,34], and low in 1 study [28]. Six studies lacked information on the blinding of personnel delivering the treatment, and 3 did not provide any details regarding blinding. Additionally, 5 studies were assessed as having a high risk of allocation concealment, while the remaining studies did not report details on allocation concealment.

DISCUSSION

The primary aim of this study was to provide a thorough overview of interventions that combine health behavioral models/theories to improve medication adherence among individuals diagnosed with hypertension in primary healthcare and community settings. Only ten RCTs employing health behavioral theory as the foundation for their interventions were identified. This number is relatively small compared to the multitude of interventions implemented to enhance medication adherence in patients with hypertension, suggesting that some studies may incorporate behavioral theory without explicitly acknowledging it in their published articles.

During the review, we paid close attention to factors that influence the proper development of an intervention. Each intervention stage was carefully examined and linked to the corresponding theoretical framework. As Michie et al. [36] note, using an explicit theory does not guarantee the intervention’s success. However, theory remains a crucial component of rigorous and systematic intervention development, which can impact effectiveness [37]. It is important to emphasize that the use of theory in intervention design is largely conceptual; therefore, more empirical research is needed to determine whether proper application of theory leads to more successful treatments. All ten interventions focused on medication adherence but were grounded in various psychological theories. Selecting a single theory from the extensive range available can be challenging, as the choice is often influenced by experience, personal preference, or current trends [36]. When choosing a theory, a well-defined justification is essential. In 7 out of 10 studies, the rationale for theory selection was not explicitly explained, although it was evident that the authors had carefully considered their choice. Selecting the most suitable theory may be difficult when individual theories fail to encompass all factors that influence the target behavior [38].

The first theory we will discuss is Bandura’s SCT. Three articles used SCT as a single framework [27,28,32], and 1 combined SCT with MI [26]. SCT explains human cognition and behavior through a reciprocal model in which personal, behavioral, and environmental factors mutually influence one another [39]. The theory posits that for behavior change to occur, individuals must understand health risks and benefits, and it emphasizes the critical role of “self-efficacy”—an individual’s belief in their ability to perform a task [40]. In this review, 2 studies focused on self-efficacy as a key factor in improving self-management [28,32]. However, another study employing SCT did not clarify whether all constructs were used or only a subset [26,27]. Despite the varied application of SCT constructs, medication adherence improved in 3 out of 4 studies. For example, as described in 1 publication [32], researchers changed self-efficacy by utilizing educational videos that emphasized lifestyle modifications tailored to patients’ needs, complications from uncontrolled blood pressure, daily blood pressure monitoring, and telephone follow-up. This intervention empowered patients to manage their condition more effectively, thereby enhancing medication adherence. These findings suggest that SCT may be associated with improved medication adherence in patients with hypertension. SCT has also been applied to increase medication adherence in patients with diabetes [40], depression [41,42], coronary heart disease [42], and stroke [43].

The next theory discussed is the TTM. TTM posits a dynamic and adaptive process that precedes genuine behavior change, serving as a guide to meet patients’ varying needs during different phases. The model comprises 4 components: stages of change, change processes, decisional balance, and self-efficacy. The stages of change categorize an individual’s readiness into 5 phases: pre-contemplation, contemplation, preparation, action, and maintenance [44]. Existing literature suggests that TTM can help individuals with conditions such as depression [45] and hyperlipidemia [46] adhere to their treatment. In this review, the authors employed this framework to develop interventions to improve medication adherence [33,34]. Researchers used TTM stages to assess readiness for adherence in patients with hypertension and to tailor telephonic counseling accordingly. For example, 1 study defined the stages as follows: pre-contemplation (no intention to adhere within 6 months), contemplation (intending to adhere within 1 to 6 months), preparation (intending to adhere within 1 month), action (adherence for less than 6 months), and maintenance (adherence for 6 months or more) [33]. Another study integrated TTM as part of a multifaceted intervention to assess patients’ readiness to change after identifying barriers to medication adherence [31]. This effective TTM model significantly enhanced medication adherence, in contrast to the findings of 2 previous studies [33,34]. The discrepancy may be due to high baseline adherence in those earlier studies, leaving little room for improvement during follow-up.

MI is a technique designed to help individuals express and address their ambivalence about behavior while fostering intrinsic motivation to find personalized solutions [47]. MI incorporates principles and techniques from multiple theoretical frameworks, emphasizing a patient-centered approach, enhancing patient self-efficacy, and focusing on the patient’s readiness to change [48]. Three articles in this review incorporated MI into the counseling process for patients with hypertension [26,30,31]. MI strategies involve building a partnership with the patient, weighing the advantages and disadvantages of specific health behaviors, collaboratively identifying and addressing barriers, and fostering motivation and confidence for change. Researchers effectively implement MI strategy through several phases: assessing patient motivation and confidence in disease management, understanding the patients’ problems, correlating adherence with treatment goals, and establishing a collaborative contract with the patient to facilitate agreed-upon modifications. Afterward, the patient’s progress is discussed. Enhanced patient motivation and confidence following MI sessions augment medication adherence. In all 3 studies employing MI [26,30,31], medication adherence improved, consistent with other systematic reviews indicating that MI can enhance medication adherence in chronic conditions [49].

In addition to TTM and MI, the HBM was employed in 1 study [31]. As a foundational theory in behavior research [50], HBM was used to design strategies addressing the perceptual barriers encountered by patients with hypertension. For example, the intervention aimed to enhance the perceived benefits of medication adherence while mitigating concerns about potential side effects by explaining their likelihood and outlining management strategies. This comprehensive intervention improved medication adherence.

The PRECEDE model is part of the “predisposing, reinforcing, and enabling constructs in educational diagnosis and evaluation—policy, regulatory, and organizational constructs in educational and environmental development” (PRECEDE-PROCEED) model, which provides a comprehensive framework for planning, conducting, and evaluating health promotion programs [51]. Green and Kreuter [52] initially developed the PRECEDE component for health diagnosis and educational needs, later incorporating the PROCEED component to include policy, regulation, organization, and environmental factors. Although the model is primarily designed for developing interventions, many researchers use it as a theoretical framework similar to SCT [38]. One study in this review employed the PRECEDE model to develop an educational package for improving medication adherence, delivered via a smartphone application [29]. The model was operationalized through a questionnaire assessing predisposing, enabling, and reinforcing factors—such as knowledge, attitude, and self-efficacy. This intervention successfully improved medication adherence among patients with hypertension. The PRECEDE model has also been effective in health education for patients with diabetes [53,54] and obesity management in adolescent females [55].

Fisher and Fisher [56] developed the IMB skills model in 1992. This behavior-specific theory asserts that for a behavior to be performed, an individual must possess the necessary information, motivation, and behavioral skills. According to the IMB model, medication adherence is determined by the extent to which an individual is informed about their regimen, is motivated to adhere, and has the required skills to do so in various situations [57]. In 1 reviewed article [35], a behavioral skills intervention was used to develop patients’ medication-taking habits—a strategy that was rarely found in other interventions. The IMB model has been effective in enhancing medication adherence in human immunodeficiency virus (HIV) and diabetes management [57,58]. In this review, improved adherence in interventions for patients with hypertension may be attributed to the researchers’ effective application of the IMB construct, which incorporated all its essential elements.

Another critical issue in medication adherence research is the variability and comparability of adherence measurement instruments. Assessing adherence remains challenging, with some authors suggesting that combining at least 2 methodologies is ideal [59]. However, most studies in this review used a single adherence measurement technique. The wide range of instruments employed underscores the lack of academic consensus on the optimal tools for assessing adherence. While patient self-reporting is the simplest approach for identifying non-compliant patients in clinical settings, it may overestimate adherence compared to more objective measures such as electronic drug trackers or pharmacy claims data [60]. In this review, 4 studies used the MGLMAQ questionnaire and 2 employed the MMAS-8. A systematic review of adherence questionnaires for hypertension patients found that no single questionnaire emerged as the gold standard, although the HBCHBPS, MGLMAQ, and MMAS-8 were among the most extensively validated [61].

One limitation of this review is the lack of blinding in some studies, which may introduce bias. Additionally, most investigations were conducted at single centers, limiting the generalizability of the results. The reliance on self-reported measurements to assess adherence may have resulted in either overestimation or underestimation; thus, combining subjective and objective evaluations is advisable to reduce bias. Another limitation is that the search was restricted to only 2 databases, potentially missing other relevant studies. Furthermore, the review was limited to articles published in English.

CONCLUSION

Research studies employing theoretical frameworks often fail to explain the rationale behind selecting a particular theory and its underlying mechanisms. Although not all studies in this review employed a complete theoretical framework, the majority indicate that utilizing theory can enhance medication adherence.

Notes

Conflict of Interest

The authors have no conflicts of interest associated with the material presented in this paper.

Funding

None.

Acknowledgements

None.

Author Contributions

Conceptualization: Yulianti T, Yasin NM, Widayanti AW, Kristina SA. Data curation: Yulianti T, Widayanti AW. Funding acquisition: None. Methodology: Yulianti T, Yasin NM, Widayanti AW, Kristina SA. Writing – original draft: Yulianti T, Yasin NM, Widayanti AW, Kristina SA. Writing – reviewing & editing: Yulianti T, Yasin NM, Widayanti AW, Kristina SA.

Figure. 1.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart of the systematic screening process. SR, systematic review; RCT, randomized controlled trial.

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