This study protocol was developed and reported in accordance with the PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols) checklist and reporting guideline (Checklist 1) [29].

This systematic review included original, peer-reviewed studies that examined the implementation or uptake process of DHTs. These included mobile health solutions, such as smartphone apps and multimedia message services, wearable devices, and telemedicine options such as videoconferences and telemonitoring [10] for the remote management of adult patients (18 years and older) with NCDs. The NCDs included in this review were CVDs (eg, heart attacks, stroke, and heart failure), hypertension, and diabetes, as these represent highly prevalent chronic conditions globally [2]. Rural settings were defined based on the classifications or descriptions provided in the original studies. Studies were included only if they explicitly described their setting as rural, remote, nonurban, or underserved. During screening, full-text articles were carefully reviewed to ensure that the context aligned with these definitions. Studies referring to urban settings, or where the context was unclear or insufficiently described, were excluded, as it was not feasible to independently classify the setting.

Observational, experimental, qualitative, and mixed methods studies were considered if they measured, observed, or explored the implementation and uptake processes and related factors. Only articles published in the English language were included. If studies included mixed children and adult patient populations, they were considered for the review if separate findings were reported for adults. Original studies that focused on DHTs exclusively for disease screening, diagnosis, or patient education, or those conducted solely in urban settings, or without specifying the geographic area, were excluded from the study. If the studies included both urban and rural areas and presented separate results, only the findings related to rural areas were considered. No restrictions were applied to year of publication, country of publication, study setting, or adult population age. Case reports, reviews, letters to editors, and conference abstracts were not included in the review.

To identify potentially relevant articles, we searched the following bibliographic databases from inception to February 12, 2026: Medline, Embase, and CINAHL. The search strategy used three groups of keywords in the search syntax. It required at least one keyword from each group: (1) digital health–related keywords, which included terminologies that describe subsets of digital health, such as “telehealth,” “mobile health,” “digital therapeutics,” (2) NCD-related keywords, which included general terms, such as “cardiovascular disease” or “chronic diseases,” and specific conditions, such as “diabetes,” “stroke,” and “heart failure,” and (3) rural area-related, such as “rural,” “remote” or “non-urban.”

The search strategy was developed and executed by a professional librarian (EU) and customized specific search syntax based on the indexing requirements of each database, including Medline, Embase, and CINAHL. Full search strategies for all databases are provided in Multimedia Appendix 1.

Two trained researchers (SS and SA) conducted two rounds of independent screening of each article: initially by title and abstract, then by full-text review, according to the predefined inclusion and exclusion criteria. The study selection process is illustrated in the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) flow diagram. Discrepancies between the reviewers were resolved through group discussions until a consensus was reached. Covidence (Veritas Health Innovation) was used to manage the literature database.

Methodological quality was appraised using the Mixed Methods Appraisal Tool (MMAT), version 2018 [30]. The evaluation covered five study designs: qualitative research, randomized controlled trials, nonrandomized studies, quantitative descriptive studies, and mixed methods studies [30]. Two MMAT screening questions were applied to all studies: (1) whether the study had a clear research question, and (2) whether the data collected were appropriate for addressing that question [30]. After this step, design-specific criteria were applied. Consistent with MMAT guidance, we reported criterion-level ratings (ie, “Yes,” “No,” or “Can’t tell”) and summarized the proportion of criteria met within each MMAT domain (ie, each study design category).

Data were extracted using a structured form that included several categories: (1) basic information about each study, such as the title, year of publication, author’s name, study design, study participants, and country; (2) details regarding the type of DHT, the NCD condition, and the target population for the DHT; and (3) barriers and facilitators of DHT, which were identified and categorized based on the CFIR [31]. The CFIR provides a systematic way to examine what helps or hinders implementation by organizing findings into five domains: innovation, outer setting, inner setting, individuals, and implementation process [32]. The same two researchers (SS and SA) conducted independent data extraction based on the structured forms, then compared and checked for discrepancies. The complete data extraction sheet is provided in Multimedia Appendix 2

To identify barriers and facilitators influencing the implementation and uptake of DHT for remote management of NCDs in rural areas, the analysis followed the Joanna Briggs Institute methodological approach for conducting a mixed methods systematic review [33]. This review specifically used the convergent segregated approach of the Joanna Briggs Institute mixed methods systematic review methodology. Quantitative and qualitative data were simultaneously and independently analyzed, resulting in the generation of quantitative and qualitative evidence [33].

The quantitative data were synthesized using both descriptive and narrative analyses. For qualitative synthesis, we used a directed content analysis approach. Initially, we categorized the themes according to the five domains of the CFIR framework. Using an inductive method guided by the data, we then described the barriers and facilitators within each theme. Additionally, we examined links between factors across different themes.

During the final integration stage, we examined the quantitative and qualitative findings to identify convergence and divergence (ie, whether evidence from both components aligned or contradicted each other). We also explored which aspects of the qualitative evidence were addressed or overlooked in the quantitative data, and vice versa. Finally, we assessed whether qualitative evidence could elucidate why certain factors were or were not associated with DHT implementation, as indicated by the quantitative evidence.

We identified a total of 2261 records across three databases (Figure 1). After removing 770 duplicates, we screened 1491 titles and abstracts, leaving 99 records for further review. During the full-text screening, 85 records were excluded. Reasons for exclusion included publication type (eg, conference abstracts, gray literature; n=28), having irrelevant outcomes (n=28), irrelevant population (n=8), irrelevant technology (n=7), and nonempirical studies (n=8), and other reasons. A total of 14 studies were included in the final analysis.

Three main design types were used: mixed methods studies (n=7), qualitative studies (n=6), and 1 quantitative study (Table 1). Most studies were conducted in high-income countries such as the United States (n=8) and Australia (n=3). Only 1 study each originated from China, Canada, and Kenya.

The majority of studies investigated factors influencing implementation and uptake from the perspectives of patients (Table 1). Specifically, six out of 14 studies focused exclusively on patients, while four studies targeted health care providers only (physicians, nurses, and educators). In addition, three studies extended beyond patients and health care providers to include caregivers and implementation stakeholders. One study did not include study participants, consistent with its study design.

In total, we identified five categories of DHTs across the 14 selected articles (Table 1). These included four mobile apps (some of which allowed providers to communicate with patients through the app, while others did not), 4 telehealth or telemedicine platforms (primarily videoconferencing tools used for remote consultations), a smartphone-based tool, 3 remote monitoring devices, including a wearable device, and other types of DHTs. These technologies in the selected studies were primarily used for monitoring and/or managing NCD conditions in rural areas, such as stroke (n=3), diabetes (n=7), hypertension (n=3), and one unidentified CVD.

Table 2 shows that most studies lacked quantitative measurements of factors influencing DHT uptake. Even those using mixed methods approaches, the emphasis was predominantly on qualitative data, with limited use of quantitative metrics to assess barriers and facilitators. Of the 8 studies out of 14 selected, findings regarding factors in the ‘Technology/ innovation’ domain of the CFIR framework were presented using both quantitative and qualitative methodologies. The majority of selected studies investigated factors related to DHT implementation and uptake within the “Inner setting” domain of the framework, followed by the “Individuals” domain. Only a few studies delved into factors related to the “implementation process” domain of the framework, and among the 14 selected studies, only one reported facilitators within this domain.

Across study types, qualitative studies and randomized controlled trials scored highest, meeting over 70%‐80% of applicable criteria, while nonrandomized and mixed methods studies showed more limitations, with only 53%‐60% of criteria met and higher proportions of ‘No” ratings. Common factors compromising quality, particularly in quantitative studies and the quantitative components of mixed methods studies, included small sample size, unclear representativeness of the target population, insufficient detail on recruitment strategies, and lack of rationale for using mixed methods design or effective integration of both components. Figure 2 provides a visual summary of criterion-level ratings across MMAT study types, illustrating the proportion of “Yes,” “No,” and “Can’t tell” responses within each category.

Additionally, nearly half of the studies (6 out of 14) did not use a framework for designing and implementing their research, while one study used a framework solely for analysis purposes, and the remaining seven studies incorporated different frameworks into their methodologies.

Resource constraints and support within the health care environment emerged as key themes influencing the implementation and utilization of DHTs.

Within this domain, we uncovered four themes: lack of motivation and reluctance to engage, facilitators like provider monitoring, age-related differences in adoption, and clinician expertise and confidence shaping uptake.

The main barriers affecting the implementation process included a lack of systematic processes [37], insufficient time [40], and financial considerations [45]. James et al [37] reported that there were no established procedures in place to assess the benefits and risks of using the DHT device for each patient. Health care providers (ie, diabetes educators) were often challenged to decide whether a patient should use the technology, instead of using clear policies or professional guidance [37].

According to Kirkland et al [40], the top barrier was time, endorsed by 60% of clinics implementing DHT. Authors encountered difficulties in the initial stages of implementing the DHT, such as the financial impact on the rural site, the costs and benefits for patients, and the financial implications for the health care provider (ie, cardiology group) [45].

Leadership, collaboration, and tailored service delivery: effective leadership and collaboration with stakeholders, engagement of local champions, service delivery tailored to local needs, establishment of site feedback mechanisms, and evaluation of site readiness and uptake were identified as the primary facilitators of the implementation process in a single study [41].

This systematic review identified key barriers and facilitators shaping the implementation and uptake of DHTs for remote management of NCDs in rural settings. Across studies, key barriers included infrastructure and access constraints (eg, connectivity and technology availability), workforce limitations (eg, staffing shortages, workload, and limited IT expertise), and usability challenges. Facilitators included perceived benefits of DHTs, health care provider support and engagement, as well as effective teamwork and communication within clinical settings. By focusing on CVDs, hypertension, and diabetes, we aimed to provide a nuanced understanding of how these interventions function in resource-constrained environments. Applying CFIR enabled a structured organization of evidence, clarifying the practical, organizational, and contextual factors that shape success or failure.

Across studies, technical issues, such as software and hardware problems, poor navigation, and readability challenges, were common barriers to DHT uptake, alongside high costs and lack of personalized content [38,42,44,47]. These findings echo previous reviews identifying usability problems and technical complexity as major obstacles to DHT uptake more broadly [20,27]. However, unlike prior syntheses that combined rural and urban evidence [20,27], our rural-focused synthesis suggests these barriers are often amplified by limited infrastructure (eg, poor internet connectivity and limited access to devices or technology) [35,37,38,40] and constrained workforce capacity (eg, staffing shortages, turnover, and limited IT expertise) [35,37,40,44,47], which reduce the ability to provide training, troubleshooting, and sustained support.

Consistent with earlier evidence, facilitators included user-friendly design, simplified content, and the convenience of at-home use, reinforcing the importance of accessible design and perceived usefulness [35,38,39].

Patients’ limited access to internet connectivity, appropriate devices, and affordable technologies represented another major barrier [35,37,38,40]. Similar patterns have been reported in umbrella reviews, where infrastructure limitations and device availability featured prominently [20]. Yet earlier reviews rarely disaggregated findings by geography. By focusing specifically on rural contexts, our analysis highlights how these factors operate under more restrictive conditions, affecting both feasibility and sustainability.

Financial and structural barriers within the outer setting, including unsustainable funding, inadequate reimbursement models, and unreliable broadband or electricity, were also prominent [35,37,45]. Such barriers were particularly pronounced in rural settings, where infrastructure gaps, such as poor internet connectivity and unreliable electricity, remain pervasive [30,44,47]. This reflects global telehealth literature reporting similar barriers in diverse settings [27,28], but our findings emphasize that rural areas compounded inequities that elevate the risk of widening disparities if financial and infrastructural gaps remain unaddressed [48].

Resource constraints within the inner setting, limited staffing, workforce turnover, and lack of IT expertise were among the most prevalent barriers [35,37,40,47]. Although workforce limitations have been reported across urban health systems as well [49], rural environments experience more acute shortages and fewer opportunities for technical support or training [27]. Unlike complex urban systems, where challenges may relate to organizational coordination, rural challenges often seem to reflect absolute shortages in personnel or infrastructure.

The characteristics of individuals domain underscored the role of motivation, self-efficacy, and readiness for change [42]. Patterns observed in quantitative data, for example, low motivation for food logging, time limitations for self-monitoring, and forgetfulness, echoed themes in qualitative literature [38]. Age-related differences were also evident, with older adults (67‐87 y) showing minimal intention to use technology or accept support [36]. These findings mirror implementation literature emphasizing individual beliefs and self-efficacy as key determinants of uptake [32].

Provider influence further shaped uptake: in some studies, patients opted not to use DHT because their health care provider had not recommended them [46]. Conversely, provider endorsement significantly improved engagement [38]. Clinician perception similarly influenced implementation processes, with senior clinicians sometimes viewing telemedicine as redundant and time-consuming, whereas junior staff appreciated its value for support and shared decision-making [44]. These insights are consistent with wider implementation research highlighting clinician identity, perceived usefulness, and workflow compatibility as important determinants of technology uptake [50].

Process-related barriers, such as a lack of systematic procedures and insufficient time, also impeded implementation [37,40]. Meanwhile, facilitators, including strong leadership, teamwork, communication, presence of local champions, and tailored workflows, as well as periodic face-to-face interaction between providers and patients, reinforced the importance of adaptive strategies [35,38,40,41,45]. Evidence from previous reviews and qualitative studies confirms that collaboration and organizational supports are particularly critical in rural contexts where structural limitations require more compensatory mechanisms than in urban systems [51,52].

A strength of this mixed methods systematic review is the triangulation of quantitative and qualitative evidence. Although quantitative data were limited, they complemented rather than contradicted the qualitative findings. For example, quantitative correlations between perceived usefulness and DHT uptake mirrored qualitative accounts from patients and providers who valued DHT benefits. Measures such as user satisfaction, perceived ease of use, perceived usefulness, adherence by patients and providers, and consistency are well established in digital health research and are useful for future work [54-56]. These metrics are commonly used to assess the adoption and sustainability of digital health and are considered essential for evaluating user experience and long-term engagement [55,56]. Incorporating such measures alongside qualitative insights would enhance triangulation, strengthen interpretation, and provide generalizable evidence to guide implementation strategies.

Several limitations should be considered when interpreting the findings of this review. Most studies included were conducted in high-income countries, with limited representation from low- and middle-income settings, which may affect the generalizability of findings to contexts with different health system capacities, resources, and infrastructure. This distribution was not restricted by the search strategy, which did not apply limits based on country income level, but rather reflects the availability of peer-reviewed evidence in this field, highlighting a relative lack of implementation-focused DHT studies in certain settings. It is also possible that relevant evidence, particularly from underrepresented contexts, exists in the gray literature, which was beyond the scope of this review.

While the included studies captured a broad range of perspectives and technologies, variability in study contexts, interventions, and populations may limit the direct transferability of specific barriers and facilitators across settings. Nevertheless, the consistency of key themes across studies suggests that many implementation factors may be broadly applicable, although they may require adaptation to local contexts.

This review was limited to English-language publications, which may have excluded relevant studies in other languages. Additionally, we did not include gray literature or conference proceedings, which may omit recent or emerging evidence. While this approach ensured a focus on high-quality, peer-reviewed manuscripts, it may have narrowed the scope of insights.

Finally, definitions of rural settings varied across included studies and were often based on authors’ descriptions rather than standardized criteria. In many cases, studies relied on general descriptors such as “rural” or “remote” without providing explicit classification frameworks. This lack of consistency limited the ability to systematically compare or categorize rural contexts across studies and may have introduced some heterogeneity in contextual classification. However, studies were carefully screened to ensure alignment with rural or nonurban contexts.

DHTs for remote management of CVDs, hypertension, and diabetes in rural settings show promise but depend on addressing structural inequities, limited broadband, constrained workforce capacity, and fragile financing. Without targeted investments in infrastructure, reimbursement, and organizational readiness, digital tools risk entrenching rather than reducing disparities. An end-to-end approach—equity-focused design, context-responsive implementation, and sustained evaluation—can help ensure DHTs are usable, resilient, and aligned with rural health equity goals [53].