Diabetes distress (DD) is a common psychological response to the challenges of self-managing type 2 diabetes (T2D) characterized by feeling overwhelmed, frustrated, guilty, or hopeless [1-4]. DD affects a substantial proportion of adults living with the condition, with prevalence estimates ranging from 36% [1] to nearly 70% over time [5], depending on the measures used and populations studied. These emotional difficulties can undermine a patient’s motivation and confidence to engage in adequate self-management, often worsening glycemic control [6-8], which amplifies the risk of serious diabetes-related complications [9] and places greater burden on health care systems [10-13]. Although it can co-occur with depression, DD is a separate construct and more directly associated with self-management behaviors and glycemic outcomes [6,14-17]. Given its prevalence, impact, and distinct profile, providing effective, tailored support for DD is essential.

Psychological and behavioral interventions have shown promise in reducing DD, and in some cases, improving related outcomes, such as anxiety, depressive symptoms, self-efficacy, and self-management behaviors [18-24]. While much evidence focuses on traditional delivery modes, digital health interventions (DHIs), including apps, websites, telehealth platforms, remote monitoring tools, and wearables, are promoted as scalable and cost-effective solutions that can extend access to care [25]. These interventions are increasingly used to support the self-management and well-being of people with chronic conditions, including T2D [26-37]. In T2D, DHIs have been found to improve glycemic control [36], and in some instances, reduce medication use and the number of outpatient appointments [38]. Emerging evidence also suggests that artificial intelligence–enabled conversational agents or chatbots may facilitate diabetes self-management by providing personalized guidance, psychoeducation, and emotional support [39-42], although research in this area remains at an early stage.

Despite growing interest in digital approaches, only a handful of systematic reviews have explored digital or technology-based interventions targeting DD or similar outcomes [31-33,43]. These reviews suggest that DHIs may produce modest improvements in DD, but the evidence base remains heterogeneous, with considerable variations in intervention types, delivery formats, and outcome measures. Reviews have also highlighted inconsistent reporting of intervention components and limited use of theoretical frameworks, making it difficult to determine why some interventions appear more effective than others.

Behavior change techniques (BCTs) are considered the active components of behavioral interventions, representing the replicable elements that alter causal processes underlying behavior change (eg, beliefs, self-regulation, and motivation) [44,45]. As such, they are recognized as key mechanisms through which interventions, including DHIs, achieve effects on behavior and health outcomes [46-48]. In addition to BCTs, DHI may incorporate therapeutic components, such as cognitive-behavioral strategies, mindfulness, or psychoeducation [32,49-51]. However, existing studies often provide limited detail on how these elements are integrated within digital interventions targeting DD or how combinations of techniques may influence engagement and outcomes [31].

Important questions also remain regarding the accessibility and real-world relevance of DHIs, particularly for underserved populations who may face barriers to digital participation, including people facing socioeconomic disadvantage, ethnic and racial minority groups, individuals living in rural or remote areas, people with disabilities, and those with limited digital literacy or access to technology [52]. These groups may bear a disproportionate burden of DD [53-58]; yet, they are often underrepresented in digital health research and intervention development [59-61]. If underserved groups are not adequately considered during design, evaluation, and implementation, DHIs may fail to address their needs or risk exacerbating existing health inequalities.

Qualitative research has begun to explore how people with T2D perceive and engage with relevant digital tools and interventions, including barriers and facilitators to access and use [27,55,56,62-65]. For example, Turnbull et al [56] have shown that factors, such as limited digital skills, financial costs, and lack of access to technology, can create barriers to using digital health tools for diabetes self-management, particularly among socially disadvantaged groups. Other work has highlighted that individuals experiencing DD may feel digitally alienated or prefer human interaction over technology-based support, which can influence engagement with DHIs [65]. However, these insights have not yet been synthesized alongside evidence on intervention design, therapeutic components, and outcomes.

Given the diversity and heterogeneity of existing evidence, a mixed methods scoping review is needed to provide a broad, exploratory mapping of DHIs for DD (eg, the different types of interventions, their content, and how they are designed, structured, and delivered), identify their active components, including therapeutic strategies and BCTs (eg, the specific mechanisms or strategies embedded in interventions that are theorized to produce changes in self-management, emotional well-being, or related behaviors), and examine how diverse populations experience and engage with these interventions (eg, how users interact with, adhere to, perceive, and respond to interventions, including factors that support or hinder engagement). Particular attention will be paid to how issues of equity and inclusion are addressed across the literature, both in research practices and in the design and delivery of DHIs.

A preliminary search carried out on February 7, 2025 identified several relevant systematic reviews [18,19,31,33], but no reviews synthesizing qualitative and mixed methods evidence relating to intervention design and delivery, therapeutic content and behavior change strategies, user experience and engagement, or equity-related considerations in DHIs for DD, confirming the novelty and appropriateness of this work.

This review aims to map and characterize DHIs targeting DD in adults with T2D, with special attention to how equity and inclusion are considered.

The specific objectives of the review are as follows:

This review and its inclusion criteria will be guided by the population-concept-context framework [68].

This review will include primary research studies with qualitative, quantitative, or mixed methods designs. Eligible sources include randomized controlled trials, quasi-experimental studies, cohort studies, cross-sectional studies, qualitative research, and mixed methods evaluations.

Gray literature sources, such as reports from public health organizations or nongovernmental organizations, doctoral theses and dissertations, implementation case studies, and conference abstracts (where sufficient data are reported), will also be included.

Systematic reviews, scoping reviews, protocols, editorials, opinion pieces, and purely theoretical papers will be excluded.

No restrictions will be placed on publication language at the point of search. Studies published from 1998 onward will be included to reflect the emergence of digital health technologies.

Table 1 presents the criteria that will be used during the screening phases to determine the potential eligibility of studies.

Following the completion of the multiphase search strategy outlined previously, all retrieved search results will be imported into Covidence (a Cochrane technology platform designed and recommended for management of reviews) for deduplication and screening. Screening will be performed in two sequential stages: (1) title and abstract screening and (2) full-text screening.

Prior to formal screening, a sample of 25 titles and abstracts will be selected for pilot testing. Two reviewers will independently screen this sample using the predefined eligibility criteria and a shared definitions guide. The team will meet to check discrepancies and clarify any ambiguous inclusion criteria. Refinements to the screening guide will be made if needed.

Screening will commence only after a minimum absolute inter-rater agreement of 75% is achieved across the team, in order to ensure consistency in decision-making and interpretation of eligibility criteria.

All remaining titles and abstracts will be screened independently by at least 2 reviewers. Records will be assessed for their potential relevance based on the inclusion criteria, and irrelevant studies will be excluded at this stage. Reviewers will be blinded to each other’s decisions to minimize bias. Discrepancies will be resolved through consensus or by involving a third reviewer.

Full-text articles of all studies deemed potentially eligible will be retrieved and reviewed in detail by a minimum of 2 reviewers. Each study will be evaluated independently against all inclusion criteria. As before, discrepancies will be resolved through discussion or by involving a third reviewer.

An audit trail of the selection process will be maintained throughout, and the final report will include a PRISMA flow diagram. Separate appendices will include sources with full bibliographic details and excluded full-text sources with justifications for exclusion.

Data extraction will be guided by a standardized form, which will be piloted on 5 studies by the review team to check inter-rater reliability, relevance, and completeness of the fields. Following this pilot, the project’s patient and public involvement (PPI) panel, consisting of a diverse group of people with lived experiences of T2D, will be consulted to provide feedback on the form, including suggestions for additional fields or refinements that better reflect the experiences and priorities of adults with T2D. Modifications will be made based on both pilot testing and PPI input to ensure clarity, efficiency, and relevance before proceeding to full extraction. Modifications will be made based on both pilot testing and PPI input to ensure clarity, efficiency, and relevance before proceeding to full extraction.

The form will capture bibliographical and methodological detail (eg, author, publication year, title, source of publication, country, study design, recruitment methods, and setting), participant demographics (eg, age, gender, ethnicity, language, socioeconomic status, education level, duration of diabetes, treatment type, and proxies for digital exclusion), DHI features (eg, name and version, focus, format, content, delivery mode, timing, duration, frequency, accessibility, etc), therapeutic strategies and BCTs, DD measures and findings, and user experience and engagement data.

Data extraction will then be completed by at least 1 reviewer, with 1 or more reviewers independently verifying the accuracy of the data extraction for a random sample of a minimum of 25% of included studies. Discrepancies will be resolved through discussion, or if necessary, by consulting a third reviewer.

Data from all included studies will be synthesized descriptively to provide a comprehensive overview of DHIs for DD in adults with T2D.

To address the overarching research questions, quantitative, qualitative, and intervention-level findings will be integrated using a convergent approach suitable for mixed methods scoping reviews. For each included study and intervention, a standardized summary sheet will be created containing key quantitative findings, including changes in DD outcomes and engagement metrics, qualitative findings, such as participants’ experiences, perceived barriers, and facilitators, and intervention-level characteristics encompassing focus, content, delivery mode, duration, human or peer support, and equity-focused adaptations. These summary sheets will also capture the presence and frequency of BCTs according to level 1 categories of the BCT ontology and the use of specific therapeutic strategies (eg, cognitive-behavioral therapy, motivational interviewing, mindfulness, and problem-solving therapy), alongside any equity-relevant participant characteristics identified through the PROGRESS-Plus framework.

The summary sheets will be compared side by side and integrated into a master matrix, with rows representing studies or interventions and columns representing quantitative outcomes, qualitative themes, BCT and therapeutic content, participant characteristics, and user engagement patterns. NVivo (Lumivero) will facilitate the coding of qualitative data and enable cross-domain queries, while Excel will be used to summarize frequencies, trends, and patterns across studies. Integration will focus on identifying convergence, divergence, and gaps across different data types. Convergence will be defined as multiple strands supporting similar patterns or findings, divergence as conflicting or inconsistent evidence, and gaps as areas where evidence is limited or absent.

Following integration, a conceptual framework will be developed to depict potential links between intervention design features, equity dimensions, user experience and engagement, and patterns of DD outcomes. This framework will serve as a tool to understand how different digital health interventions may work for diverse populations in varying contexts. The integrated findings and conceptual framework will then inform the derivation of equity-sensitive guiding principles, which will be used to generate practical recommendations for the design, delivery, and evaluation of future interventions for DD.

Finally, the review will identify evidence gaps across quantitative, qualitative, and intervention-level domains, including underreported outcomes, limited equity analysis, or incomplete reporting of engagement or intervention features. These identified gaps will highlight priorities for future research and guide the refinement of intervention development.

As this is a scoping review, a formal quality appraisal is not standard practice and will not be undertaken.

This review does not require ethical approval as it involves the secondary analysis of publicly available data.

There is growing evidence that DHIs can help support emotional well-being and reduce DD [32,37,43], which is a known psychosocial risk factor for poor self-management and adverse health outcomes among people living with T2D [2,6]. Their flexibility and scalability make them particularly well suited for use in health care settings, such as primary care, community clinics, and outpatient services, where resources are often stretched and patient needs varied.

This review focuses on both who current DHIs for DD reach and how they are designed, in order to assess whether they address the needs of underserved populations, such as ethnic minority communities, socioeconomically disadvantaged groups, and others at risk of digital exclusion. In doing so, the review will identify DHI features, user experiences, and engagement patterns that could inform the design and delivery of more equitable interventions. For example, the review will examine whether people with lived experience were involved in the development process; whether content was adapted for cultural or linguistic relevance; whether accessibility features were incorporated to accommodate physical, sensory, or neurodiverse needs; whether digital devices, internet access, or technical support were provided; and whether tailored outreach or engagement strategies were employed to engage diverse populations.

The findings will also highlight trends and gaps in equity-related research practices. This includes examining participant recruitment strategies and whether eligibility criteria unintentionally exclude specific groups. The review will also assess the reporting of demographic characteristics, such as age, ethnicity, socioeconomic status, and other equity-relevant variables, and evaluate whether subgroup analyses were conducted to explore differences in outcomes across populations. These insights will provide guidance for more inclusive research efforts and help ensure that underserved populations are adequately represented in future studies.

The findings of this review, together with the findings of a qualitative study conducted in parallel, are expected to contribute to a set of practical, equity-sensitive design and delivery principles to guide the codevelopment of a digital intervention for managing DD in T2D, targeted at underserved communities in England [78]. Moreover, this intervention is being developed specifically for delivery in NHS primary care, the first point of contact in the UK health care system encompassing general practices and other community-based services, and aims to improve access to psychosocial support while alleviating pressure on frontline services.

The findings from the scoping review will be disseminated through multiple channels to maximize their relevance, reach, and impact, including peer-reviewed journal publications, conference presentations (eg, in digital health, primary care, and implementation science), and briefings and workshops for digital health developers, NHS stakeholders, and community organizations.

In addition, plain language summaries and visual infographics will be developed in partnership with the PPI panel members to make sure that the findings are accessible and relevant to service users, patient groups, and community stakeholders. This will help ensure that the voices and needs of people with T2D, especially those from underserved communities, remain central to the design and delivery of future interventions.

This protocol outlines a mixed methods scoping review led by a multidisciplinary team of academic, clinical, and lived experience experts, which ensures that the review is informed by the real-world needs of people with T2D and remains relevant to both research and practice. Furthermore, the review proposed here adopts an equity-focused stance, aiming to understand whether, and how, the needs of underserved communities, including those at risk of digital exclusion, have been considered in the design and delivery of DHIs for DD. In parallel, the review seeks to examine equity-related research practices across the available literature to determine whether studies have adequately included underserved populations and reported relevant outcomes. In addition, by drawing on a wide range of study designs and sources, and including research from varied settings and populations, the review is set to capture a more complete picture of DHI-related design features, user experience, and engagement, and factors across diverse contexts. However, while patterns and trends that appear to support engagement or positive user experience may be identified, the nature of this review does not allow firm or causal conclusions about what works or the factors driving DHIs’ effectiveness in improving DD. Anticipated heterogeneity in intervention types and outcomes may further limit direct comparability between studies. In addition, because study quality will not be formally assessed, the review is limited to mapping and describing the available evidence rather than evaluating the robustness of the findings.

Digital interventions aimed at alleviating DD are gaining attention as promising approaches to support the emotional well-being of people with T2D. However, little is known about whether and how they address the needs of groups who could benefit most but are paradoxically at greatest risk of exclusion. This scoping literature review will map the existing evidence on the design and content of DHIs, including active components, user experience and engagement, and impact on DD, as well as how equity considerations are reported across studies. The findings will help guide the development of more inclusive, user-centered, and equitable interventions and promote better research practices to ensure that underserved populations are adequately represented, supporting both accessibility and meaningful engagement.