Globally, noncommunicable diseases (NCDs) such as heart disease, diabetes, chronic respiratory problems, and cancer account for over 70% of deaths annually. Nearly 80% of these deaths happen in low- and middle-income countries [1]. In India, these diseases cause about 63% of all deaths, and the identified risk factors, such as limited or no physical activity, poor dietary habits, obesity, tobacco use, and alcohol consumption, are increasingly adding to the overall burden [2,3]. Despite several attempts in India to enhance basic health care with programs like the National Program for the Prevention and Control of NCDs, issues such as failure in early detection, treatment adherence, and receiving continuous care are still persistent in resource-limited settings [4].

The World Health Organization’s Package of Essential NCD (WHO PEN) interventions was introduced as a cost-effective strategy to enable primary health care workers to deliver standardized NCD services in low-resource environments [5]. The major focus of the WHO PEN protocol is on task shifting, screening at the early stage, and risk-based management by using simple tools and strategies. This intervention has been effectively executed to improve the management of diabetes and hypertension at the community level [6]. However, there are several limitations such as inconsistent implementation, limited health worker training, and weak follow-up systems that interfere with the long-term impact in real-world contexts [7].

Recent years have witnessed an influx of digital health interventions that include mobile apps, web-based platforms, teleconsultations, and data-driven dashboards as a promising strategy to enhance health care access and continuity [8]. The use of mobile technologies for NCD prevention and control can enhance health literacy, modification in health-seeking behaviors, and remote monitoring, especially in resource-constrained settings [9]. Digital interventions have demonstrated potential in improving medication adherence, promoting physical activity, and supporting lifestyle modification [10,11].

In the Indian scenario, digital health has amplified to a significant level under the Ayushman Bharat Digital Mission, the goal of which is to integrate digital tools into primary health care delivery [12]. Despite all the developments achieved over the years, there has been limited evidence on the comparative effectiveness of digital interventions versus standardized models such as WHO PEN, particularly in diverse community settings. Furthermore, identifying and understanding the barriers and facilitators to technology adoption and contextual dissimilarities across geographic and sociodemographic groups is critical for scaling such interventions.

There has been an increasing utilization and acceptance of digital health platforms. However, there is a scarcity of evidence that compares and evaluates the impact of digital interventions relative to the established WHO PEN based standard care. Most existing studies focus on single disease domains such as diabetes or hypertension rather than comprehensive NCD prevention frameworks [13]. Moreover, multisite evidence capturing both urban and semiurban populations is scarce in India.

This proposed study will focus on diabetes, hypertension, or cardiovascular diseases. Further, this study will address the gaps by focusing on behavioral modification and implementing and evaluating the digital intervention developed as part of this study and the behavioral component of WHO PEN as part of a multi-site, quasi-experimental design comparing 3 groups:

This study will provide robust empirical evidence on the comparative effectiveness of digital and WHO PEN interventions in enhancing the overall health of the affected individuals by nudging them toward better health-seeking behaviors and self-management practices. Identifying and understanding the barriers and facilitators that influence the adoption of digital interventions in community settings will serve as the foundational guide for developing barriers to digital intervention. Additionally, it will provide enough insights to guide the policy integration of digital health solutions in India’s existing NCD prevention and control programs. The mixed methods approach across 4 diverse sites, namely, Delhi, Chennai, Sikkim, and Dehradun, is expected to capture variations in the demographic, cultural, and infrastructural contexts, thereby enhancing the generalizability of the findings. This study should help by strengthening further discussion on the improvement of digital health and creating successful disease management plans in places with limited resources.

The primary objectives are as follows:

The secondary objectives are as follows:

This is a multi-site, quasi-experimental study, using a cluster-design sampling strategy. This study adopts a mixed methods approach to assess the efficacy of using the WHO PEN in comparison with a control group that received no intervention and a digital intervention platform. The study is being conducted in urban poor settings in India across 4 sites with differing geographic and sociocultural characteristics. Allocation to study arms will occur at the community (cluster) level. Within each site, community clusters (wards/slum clusters) will be assigned to one of the 3 intervention arms to reduce contamination between participants and to align with local service delivery structures. All eligible individuals within a cluster are enrolled into the arm designated for that cluster.

The study will span 3 years and execute 3 distinct phases to achieve the 3 stated objectives. The interventions will be deployed in the third phase of the study and will include follow-up evaluations at 3 months, 6 months, 9 months, and 12 months post intervention.

The individuals will be included if they are 18-70 years old, have diabetes or hypertension or cardiovascular diseases and/or both, can provide written informed consent, have access to a mobile phone (Android or any smartphone), and are willing to use technology. They will be excluded if they are younger than 18 years, have a terminal illness, have impaired cognition, are pregnant, fail to adhere to study procedures, or they are currently enrolled in another interventional study addressing the same outcomes.

To ensure that each site implements all 3 arms while preserving feasibility and minimizing contamination, this study will use a clustered quasi-experimental design at the local community level.

Interviews and focus groups will be audio-recorded, transcribed verbatim, and translated to English where necessary. A thematic analysis approach will be applied using NVivo software (Lumivero). Triangulation across all the data sources will enhance validity. Data will be analyzed using SPSS (version 29; IBM Corp) and R software (R Foundation for Statistical Computing). Heuristic evaluation will involve the estimation of severity ratings, frequency of usability issues, time taken to complete tasks, and interrater reliability. Descriptive statistics will include means (SDs), medians (IQRs), and proportions to summarize baseline characteristics. Between interventions and control arms, the analysis would be performed by ANCOVA or generalized linear models, adjusting for baseline values, cluster effects, and site-level covariates. Statistical significance will be set at P<.05, with 95% CIs.

A generalized linear mixed-effects model will be used to conduct the primary analysis, because the data are clustered and longitudinal in nature. The generalized linear mixed-effects model will include random intercepts for the clusters of communities and the individual study participants to account for the intracluster correlation and repeated measurements over time. Intervention arm, time, and their interaction will be modelled as fixed effects, with study site included as a fixed effect to control for contextual differences. To control the baseline imbalance in outcome variable values, the baseline value will be used as a covariate in the analysis. The maximum likelihood estimation within the mixed-effects framework will handle the missing data in the study, with sensitivity analyses using multiple imputation. Pairwise comparisons among the 3 study arms will be conducted. This will be adjusted for multiple testing using the Holm-Bonferroni method, with statistical significance assessed at 2-tailed α level of .05.

The project duration will be 3 years, from January 2025 to January 2028. A comprehensive overview of the timelines of the different phases of the project is provided in Table 2.

Quality will be ensured across all the elements of data collection and data handling. Data collection and entry will be performed by well-trained field staff. Standard operating procedures will be prepared and followed for qualitative and quantitative data collection. Training sessions will be conducted for all staff involved to orient them to the study aims, objectives, study area, inclusion and exclusion criteria, procedures for obtaining informed consent, and the standard operating procedures for the data collection tools. Weekly meetings and continued training sessions will be an integral part of the project to ensure high quality.

Ethical approval has already been obtained from the institutional human ethics committees of all participating sites from Delhi, Dehradun, Sikkim, and Chennai.

Written informed consent will be obtained from the selected participants in the preferred local language at all 4 sites. This study will strictly protect the data confidentiality and anonymity of research participants. The study will comply with the principles of the Declaration of Helsinki (2013) and the Indian Council of Medical Research ethical guidelines.

The proposed study will offer conclusions about the relative effectiveness and feasibility of digital interventions compared to WHO PEN approaches and identify tailored strategies for NCD prevention and control in diverse resource-limited settings. It will assist in developing an intervention model that integrates strategies specifically designed for urban slums or areas, addressing the unique challenges they encounter. In addition to behavioral and self-management outcomes, clinical assessments of fasting blood sugar, lipid profile, and blood pressure will be conducted to evaluate changes in metabolic risk factors across all 3 study groups. These objective measures will provide evidence of physiological improvements associated with the intervention and help validate its effectiveness in reducing NCD risks. This research could help individuals to enhance their health-seeking behavior, manage their disease condition effectively, and ease the load of certain common NCDs in resource-limited settings by helping people make better health-related choices.

The burden of NCDs falls disproportionately on low- and middle-income countries, where cardiovascular disease, cancers, chronic respiratory disease, and diabetes drive 80% of premature deaths, posing a serious threat to global health and socioeconomic development [1,9]. In India, socioeconomically disadvantaged groups, who lack timely access to health care, bear the brunt of high out-of-pocket costs and are particularly vulnerable to the situation. The rapid adaptation of urban lifestyles, along with the widespread acceptance of nonactive lifestyles, unhealthy eating habits, and addictive behavior, has exacerbated the problem of NCDs’ burden [6,10-12]. The lack of adequate health care infrastructure, financial limitations, and lack of awareness make it extremely difficult for vulnerable individuals in low- and middle-income countries to access timely health care. Inadequate diagnosis or management of NCDs results in serious health problems, diminished productivity, and crippling medical expenses [10]. To overcome this barrier, there is an urgent need for low-cost, scalable interventions, such as digital platforms, to enable communities at risk to maintain self-care and overcome the accessibility gap [22].

The use of digital interventions is gaining traction as a way to enhance primary health care while reducing the burden of NCDs. It is becoming increasingly apparent that digital interventions are improving primary health care and reducing the burden of NCDs. The digital approaches facilitate real-time, adaptable, and tailored communications through mobile platforms, which are increasingly adopted by a wide range of ages and literacy levels [12]. By providing personalized, real-time feedback and sustained engagement, smartphone apps, text messages, and web-based tools improved dietary habits, exercise, and smoking cessation [22-24]. Studies have reported that digital health interventions can improve awareness, behavioral change, and self-management of NCDs in economically disadvantaged countries [25].

Thus, this protocol outlines a novel, multi-site, quasi-experimental study designed to compare the effectiveness of a human-centered digital health intervention against the WHO PEN approach in resource-limited settings. This study addresses that gap by implementing both interventions concurrently across diverse and contextually relevant geographic and sociodemographic settings in India, thereby ensuring that the digital solution is grounded in user needs, cultural context, and practical feasibility. This protocol sets the stage for digital transformation in primary NCD care, closely following India's National Digital Health Mission and the global Universal Health Coverage.

A mixed methods approach will be utilized, integrating insights from behavioral, clinical, and qualitative measures to capture multidimensional outcomes. The human-centered design will ensure the digital intervention is tailored to the context of the target population, enhancing relevance and user engagement. The inclusion of geographically and culturally diverse sites such as Delhi (plains), Dehradun (valley), Chennai (coastal), and Sikkim (hilly) would provide an additional contextual understanding that would support external validity. Moreover, the incorporation of digital monitoring systems facilitates real-time data acquisition and guarantees the integrity of the interventions.

However, this study anticipates certain limitations. The nonrandomized allocation of participants may introduce selection bias, although cluster-based assignment and analytical adjustments will be employed to minimize its effects. Additionally, variations in digital literacy among participants may influence engagement with the intervention. Despite these constraints, the study is expected to yield robust insights into the differential effectiveness, user experience, and implementation feasibility of digital solutions for NCD prevention within the low- and middle-income country-setting contexts.