Effectiveness of digital health interventions in influencing the primary prevention of non-communicable diseases: protocol for an umbrella review

Abstract

Introduction

Non-communicable diseases (NCDs) currently contribute to over 50% of the global disease burden. Digital tools bear the potential to mitigate the risk of NCDs by facilitating personalised, preventive healthcare. It is therefore pertinent to examine the specific components that contribute to the success or constrain the impact of digital health interventions (DHIs), with particular attention to the sustainability of their long-term effects. Additionally, it is important to provide an up-to-date perspective on emerging interventions and technologies that have not yet been comprehensively addressed in the literature. This protocol defines the methodology for an umbrella review to synthesise the available high-quality evidence from systematic reviews and meta-analyses regarding effectiveness of DHIs in influencing the primary prevention of NCDs.

Methods and analysis

Using a rigorous search strategy, the subsequent databases will be searched in December 2025: MEDLINE, Web of Science, CINAHL, Embase, Scopus and Epistemonikos. Following the Joanna Briggs Institute (JBI) methodology, the selected literature will be screened based on predefined inclusion criteria. This includes systematic reviews and meta-analyses published within the last 5 years, without restrictions on country or language, that evaluate the effectiveness of any DHI aimed at the primary prevention of NCDs. Suitable full-text articles will be extracted by four researchers and independently assessed for methodological quality by two researchers using the AMSTAR-2 (A Measurement Tool to Assess Systematic Reviews) tool. The results will be presented in a summary table aligned with the review question and subquestions, accompanied by a narrative synthesis that explores the findings and their relevance to the research aims.

Ethics and dissemination

Ethical approval is not required as no primary data will be collected. The findings of this umbrella review will be published in a peer-reviewed journal and presented at academic conferences.

PROSPERO registration number

CRD420251139744.

STRENGTHS AND LIMITATIONS OF THIS STUDY.

• The review follows a rigorous methodology based on JBI guidelines, and the methodological quality of included systematic reviews will be independently assessed using the AMSTAR-2 tool.

• The results will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for reporting systematic reviews.

• The review will include international studies without language or country restrictions, enhancing its global relevance and comprehensiveness.

• Meta-analyses and systematic reviews focusing on long-term follow-up of digital health interventions for non-communicable diseases are likely to be scarce, but if identified, they will offer the strongest evidence of sustained effectiveness.

Introduction

Global mortality due to non-communicable diseases (NCDs), such as cardiovascular diseases, cancer, chronic respiratory diseases, type 2 diabetes mellitus (T2DM), chronic neurological and mental disorders, is expected to remain at a high level or even increase in the coming years, especially if insufficient measures are implemented to minimise the risk.¹ Many NCD-related deaths are considered preventable, and 60% of avoidable cases are associated with modifiable risk factors, such as consumption of tobacco and alcohol, unhealthy diets or physical inactivity.1,5 People affected by an NCD often suffer from physical and mental health conditions simultaneously or share common risk factors.⁶ Mental health conditions contribute significantly to non-fatal health impairments and affect global mortality rates, given the persistently high number of suicide-related deaths each year.⁷

Digital health interventions (DHIs) are a rapidly growing field, especially since the COVID-19 pandemic exposed significant gaps in healthcare systems, which in turn heightened awareness and underscored the value of digital tools for personalised disease prevention and management.^{8 9} Digital health has developed into a broad and multifaceted field encompassing areas such as telemedicine, electronic health (eHealth), mobile health (mHealth), wearable technologies (including wearable or implantable devices), virtual reality and artificial intelligence applications based on the collection of health data.¹⁰ While these innovative technologies play a central role, digital health also broadened the perspective to include societal dimensions and the wider digital transformation of healthcare services.¹¹ The use of digital devices for health delivery enables low-threshold access to care, improving accessibility and potentially reducing structural and personal barriers to healthcare services.¹² Digital tools allow for an extended view on patients (more than a snapshot at clinical encounters) and bear the potential to mitigate the risk of chronic disease by facilitating personalised, preventive healthcare, essentially by influencing modifiable risk factors and supporting/nudging individuals to healthier habits.1012,14

DHIs facilitate primary prevention by assisting individuals in adopting and maintaining healthier lifestyles, thereby reducing the risk of developing certain NCDs.¹⁵ In 2016, the National Health Service launched the Diabetes Prevention Programme,¹⁶ providing people at risk of T2DM with wearable devices that monitor physical activity, apps to access health coaches and online peer support groups to help prevent or delay onset of disease.^{12 16} The programme demonstrated clinically significant health outcomes, including influencing surrogate risk factors (reduction in body weight and glycated haemoglobin levels).¹⁷ Similarly, systematic reviews and meta-analyses found that DHIs (text messaging, web platforms or smartphone applications) hold strong potential by effectively modifying key risk factors for T2DM such as excess body weight.^{18 19}

Other studies and reviews have highlighted the potential of DHIs in reducing or preventing substance abuse and addressing other mental health conditions that share the same risk factors in adolescents.20,22 In the adult population, one systematic review showed that self-directed online programmes have the potential to reduce anxiety and depression symptoms and prevent new incidents. Another review demonstrated that DHIs improved mental health literacy, but had a moderate effect on mental health outcomes (by reducing depression, anxiety, loneliness), resilience and quality of life.^{23 24}

Other reviews published in this context have found only low-quality studies and highlight the need for more high-quality research,²⁵ or emphasise the need to integrate digital health tools with personal communication with healthcare providers or professional supervision to increase the effectiveness of these tools.²⁶ Further, DHIs may have their limitations in terms of socio-emotional skills, context-sensitive appraisal and ethical responsibility. It is argued that DHIs in the prevention context should support clinical practice and act as ‘health-care companion’ integrated into broader healthcare strategies, rather than basing primarily on a quantified self.^{12 27}

The objective of the proposed umbrella review is to systematically identify, evaluate and synthesise evidence from existing systematic reviews and meta-analyses on effectiveness of DHIs in facilitating prevention of NCDs, including mental health issues in the overall population and at-risk individuals. Given the volume of publications in the proposed field, this evidence synthesis will summarise comprehensive, high-level findings from the most recently published systematic reviews across multiple NCDs. This will provide an up-to-date perspective, capturing emerging interventions and technologies, such as virtual reality, which have not been comprehensively addressed in earlier literature. The umbrella review will compile the specific components that contribute to the interventions’ success or limit their impact. Further, the proposed umbrella review aims to be sufficiently sensitive to identify whether DHIs account for individuals within the context of their specific social, economic and environmental circumstances. Particular attention will be placed on how data derived from these interventions can inform and enhance preventive measures at the system, population, group and individual levels, without placing disproportionate responsibility on individuals.²⁷

Review question

What evidence do systematic reviews and meta-analyses provide regarding the effectiveness of DHIs in strengthening primary prevention of NCDs?

Subquestions:

• What types of DHIs (eg, mobile applications, wearables) have been used in the primary prevention of NCDs?

• Which specific NCDs are targeted by these interventions?

• Which risk factors are addressed and at which levels? (eg, individual, interpersonal, structural)

• How has effectiveness been assessed? (eg, modification of risk factors, disease incidence, health outcomes)

• What key factors contribute to the success or failure of the DHIs?

• How are health outcomes framed within DHIs (eg, individual, systemic, population or group level)?

• To what extent do DHIs consider individuals within their broader contexts, versus reinforcing a narrative of individual responsibility for health outcomes?

• How is engagement with mobile apps measured/addressed?

• What is the overall strength and quality of the evidence reported across reviews and meta-analyses?

Methods

The planned umbrella review follows the Joanna Briggs Institute (JBI) methodology for umbrella reviews²⁸ and will adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for reporting systematic reviews.²⁹ The review has been registered at PROSPERO (CRD420251139744) and will be conducted following this protocol. Deviations from the protocol will be justified in the publication of the umbrella review.

Inclusion criteria

The Patient/Population/Problem, Intervention, Comparison/Control and Outcome (PICO) framework served as a guide for structuring the research question, selecting the inclusion criteria and deriving the appropriate search string. With regard to the inclusion criteria, the PICO format helped to align the eligibility criteria with the research question.³⁰ An overview of the inclusion and exclusion criteria is shown in table 1.

Table 1. Inclusion and exclusion criteria for the umbrella review.

Population
Inclusion	Exclusion (‘wrong population’)
Human individuals.	Animals.
All ages.	N/A
Community-dwelling people.	Individuals receiving care in hospitals or institutional settings.
Individuals without a diagnosed NCD as defined in the global burden of disease study (eg, metabolic disorders, cardiovascular diseases, respiratory diseases, cancers or mental health conditions) and whose onset could be prevented or delayed through modification of risk factors. Individuals diagnosed with an NCD will be included only if the intervention targets the prevention of a different or additional NCD.	People diagnosed with NCDs or survivors of these diseases.
Mental health context: people without a clinical diagnosis at baseline, unless targeting prevention of another NCD (eg, DHI aiming to reduce anxiety symptoms in the general population includes participants who do not have a clinical diagnosis of anxiety or depression at baseline. However, individuals with diabetes are included because the intervention additionally aims to prevent depression as a comorbid NCD).	People with a clinical diagnosis.
People at risk of developing a certain NCD (eg, people with pre-diabetes before developing manifest T2DM)	N/A
Intervention
Inclusion	Exclusion (‘wrong exposure’)
DHIs (eg, eHealth, mHealth, wearables, virtual reality, chatbots, artificial intelligence).	Non-digital (eg, face-to-face interventions).
DHIs for the primary prevention of NCDs.	Digital health interventions that target: Disease therapy and disease management. Secondary prevention. Tertiary prevention. Quaternary prevention. Recovery measures.
DHIs targeting factors associated with NCDs: Behavioural factors (eg, diet, physical activity, smoking, alcohol use, screen time, sun exposure). Psychosocial factors (eg, distress, self-esteem, self-efficacy, social isolation, discrimination, violence exposure). Environmental conditions (eg, exposure to pollution, chemical substances, drugs). Family and social networks (eg, social support, social media, peer pressure). Healthcare access and availability. Health policies and regulations. Socioeconomic factors (education, income, employment, profession, poverty, housing). …	Genetics Sex Age
N/A	Health promotion independent of NCD prevention.
Outcome
Inclusion	Exclusion (‘wrong outcome’)
Data on effectiveness of the DHI for prevention of NCDs and how they were measured (eg, modifiable risk factors, onset of disease, disease incidence, mortality, disability, long-term effects of the DHI, prevention of acute events in the frame of the NCD, suicide prevention, mental health literacy). Factors that yield statistically significant and homogeneous results (systematic reviews). Heterogeneous or non-significant results will be included for completeness (systematic reviews).	Data that assess other dimensions of evidence.
Study type
Inclusion	Exclusion (‘wrong study type’)
Meta-analyses. Systematic reviews.	Any original research. Protocols, opinion papers, position papers, editorials, conference papers. Umbrella reviews. Scoping reviews. Narrative reviews. Rapid reviews. Mini reviews. Integrative reviews. Qualitative meta-synthesis.
Time frame
Inclusion	Exclusion (‘wrong timeframe’)
1 January 2020–15 December 2025	Date of database establishment until 31 December 2019.
Geographical region and language
Inclusion	Exclusion
Any language or country.	No exclusions based on language or country.

DHI, digital health intervention; eHealth, electronic health; mHealth, mobile health; N/A, not assessed; NCDs, non-communicable diseases; T2DM, type 2 diabetes mellitus.

Population

People of all ages who were not initially diagnosed with NCDs as defined in the global burden of disease study (eg, metabolic disorders, cardiovascular diseases, respiratory diseases, cancers or mental health conditions) will be included.³¹ At-risk populations for the specific NCDs (eg, people with pre-diabetes) will be included.

Intervention

Any DHI (eg, eHealth, mHealth, wearables, virtual reality, artificial intelligence) to modify environmental, psychosocial, behavioural or social factors to influence primary prevention of NCDs will be included.

Comparator

The Comparator may vary depending on how the original systematic reviews define the comparison group. A possible comparison group could consist of non-digital, face-to-face interventions.

Outcome

Systematic reviews and meta-analyses reporting on effectiveness of DHIs associated with the primary prevention of NCDs will be taken into account. Effectiveness of interventions will be measured by modifiable risk factors, incidence of disease, mortality, disability or other outcomes deemed relevant in the included reviews. In the case of mental health conditions, effectiveness will be measured by mental health literacy, delay of onset of symptoms, improvement of protective factors (eg, such as resilience) or other factors identified as relevant in the reviews.^{23 24} However, because disease incidence or evidence of long-lasting impacts of interventions in the context of NCDs requires long-term follow-up, such studies are expected to be scarce; nevertheless, if identified, they are of particular relevance to this review, as they provide the strongest evidence for the effectiveness of interventions over time.

Types of sources

The studies included in the planned umbrella review are compilations of existing research results from systematic reviews and meta-analyses.

Search strategy

The search strategy was drafted according to the PICO format and was handed over to the librarian of the Medical University of Vienna, who further refined and adapted the search strategy. The review team tested the strategy in MEDLINE (via PubMed), discussed the outcome and further refined the search strategy. The detailed search strategy is shown in online supplemental appendix 1.

The search strategy will be applied in MEDLINE (via PubMed), Web of Science Core Collection (Clarivate Analytics), CINAHL (via EBSCOhost), Embase (via Elsevier), Scopus (Elsevier) and will be adapted to searches in Epistemonikos (open-access database for systematic reviews and evidence). Search filters for reviews (systematic reviews, meta-analysis) will be used if available for the respective database.

Study/source of evidence selection

The identified literature will be compiled, imported into EndNote and will be checked for duplicates.³² Then, a systematic screening process will follow: in a first round of title/abstract screening, the inclusion and exclusion criteria will be tested and further refined if necessary. Titles and abstracts will be screened in Rayyan by four independent reviewers (SH, MB, MS, CL).³³ The screening process will be blinded. After discussing discrepancies in the selection of included studies, the relevant citations will be compiled in a shared folder, read in full text and checked for their inclusion potential. Numbers of included and excluded studies, as well as reasons for exclusion of full texts, will be recorded in a PRISMA flow diagram.²⁹ Any questions that will come up during the screening will be discussed and resolved within the team or, if necessary, in a research panel. For reviews published in languages other than German, English, Spanish or French (languages in which the core team is fluent), we plan to use translation services, such as DeepL, to assist with abstract/title screening. Should a review progress to the full-text screening stage, researchers fluent in the respective language will be consulted to ensure accurate assessment.

Assessment of methodological quality

To support the goal of including high-quality evidence, the systematic reviews included in the umbrella review are subjected to a methodological quality assessment (eg, low or high risk of bias). Using the Assessing the Methodological Quality of Systematic Reviews (AMSTAR) tool, we will assess whether each review appropriately evaluated, reported and addressed heterogeneity. The quality will be evaluated by two independent scientists, blinded to each other’s assessment. ³⁴

Data extraction

For data extraction, a template will be developed by two researchers (MJ and SH) and tested using two reviews. The data extraction tool will then be presented to the members of the extended team to ensure that all relevant topics are captured. Data from the included papers will be extracted by four independent reviewers (MB, MS, CL, SH) and will be verified by one researcher (MJ). The extracted data will provide information on study characteristics (including author, year, study type, aim and key findings of the reviews) as well as details based on the following PICO criteria:

Population: Number of cases, specifics of the population characteristics (eg, age, gender, as well as context specific data of the population).

Intervention: Characteristics of the DHI; targeted NCD(s) and targeted measures (factors) influencing prevention of the specific NCDs.

Comparator: Any information on the control group (eg, non-digital, face-to-face intervention).

Outcome: Overall outcome, textual details on effectiveness, and if available, information on the common or unique factors that influence the success or failure of the examined DHIs, as well as data that reflects individual, systemic, population-level and group-level determinants. In systematic reviews, outcomes will include factors that yield statistically significant and homogeneous results. Heterogeneous or non-significant results will be extracted for completeness.

In line with the JBI guidelines for umbrella reviews, we will extract what already has been calculated. We will report heterogeneity measures if they are available in the included meta-analyses.

Summary of evidence

Depending on the consistency of results across the included meta-analyses and systematic reviews, we will decide on the appropriate approach for summarising the evidence. When effect estimates across reviews are reasonably consistent and heterogeneity is adequately addressed, we will present the findings in a summary table. When substantial heterogeneity is present, whether statistical or methodological, we will provide a narrative synthesis to more appropriately describe the evidence. To address potential heterogeneity among interventions, we will conduct a narrative synthesis, grouping interventions by targeted NCDs and by the type of DHI. Where relevant, we will also highlight differences in data sources and discuss their implications for interpreting the findings.

Data statement

The planned umbrella review will include data extracted from published systematic reviews and meta-analyses, which will be assessed for methodological quality. No new primary data will be collected. The extracted data will be made available as extraction sheets included in the supplementary files to ensure accessibility and enable reproducibility.