Background

F1000Research

2046-1402

F1000 Research Limited

London, UK

10.12688/f1000research.127131.2

Study Protocol

Articles

Effectiveness of a mHealth application on remote monitoring and self-management of persons with hypertension in a coastal taluk of Udupi district: A study protocol for a community-based Cluster Randomized trial

[version 2; peer review: 1 approved, 1 approved with reservations, 1 not approved]

Salins

Prajwal L

Conceptualization Data Curation Methodology Writing – Original Draft Preparation https://orcid.org/0000-0001-8722-0150 1 Nair

Suma

Conceptualization Methodology Supervision Writing – Review & Editing 2 Kundapur

Poornima P

Conceptualization Methodology Writing – Review & Editing https://orcid.org/0000-0002-8271-524X 3 Pandey

Akhilesh K

Data Curation Methodology Supervision https://orcid.org/0000-0002-2620-0276 4 Reshmi

Bhageerathy

Conceptualization Data Curation Methodology Supervision Writing – Review & Editing https://orcid.org/0000-0001-9631-6218 1 Mandapam

Sabu K

Conceptualization Methodology Supervision Writing – Review & Editing https://orcid.org/0000-0002-6673-060X a 1 1Health Information Management, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India 2School of Public Health, DY Patil University, Navi Mumbai, Maharashtra, 400706, India 3Department of Data Science and Computer Applications, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India 4Department of Community Medicine, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India

a sabu.km@manipal.edu

No competing interests were disclosed.

21 3 2025

2022

1393

6 3 2025

2025

This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Background

Hypertension is a significant risk factor for cardiovascular disease, contributing to global mortality and disability. Approximately 30% of Indian adults are diagnosed with hypertension. Evidence supports that self-monitoring and blood pressure self-management can lower systolic BP by an average of 3.2 mmHg. mHealth applications facilitate remote monitoring and self-management, yet existing applications in India lack customisation for user needs, limiting their usability. This study aims to develop and evaluate a novel, user-friendly mHealth application tailored to hypertensive individuals.

Methods

This study follows an Agile development design, an iterative software development approach that allows continuous feedback and refinement. The research will be conducted in three phases over an anticipated duration of 27 months. Phase 1 (6 months) will involve in-depth interviews and focus group discussions to identify essential features for a customised Android-based mHealth application. Phase 2 (9 months) will involve developing the application using Android Studio following Agile principles. Phase 3 (12 months) will be a community-based cluster randomised trial conducted in 12 villages to evaluate the application’s effectiveness. Villages will be randomised into intervention and control groups. Each group will include 118 participants. The intervention group will use the mHealth application, while the control group will follow the standard hypertension management regimen. Villages and participants will be selected based on specific criteria, including population size, availability of healthcare facilities, and smartphone accessibility among hypertensive patients.

Results

In the proposed study, if the intervention is helpful, hypertension patients in the community can be encouraged to use the mHealth application. If found effective, this application is anticipated to improve hypertensive patients’ health status, knowledge, and self-care approach.

Registration: Clinical Trials Registry - India ( CTRI/2022/03/041544).

mHealth remote monitoring self-management hypertension

The author(s) declared that no grants were involved in supporting this work.

Revised Amendments from Version 1

In response to the reviewers’ comments, we have made several revisions to enhance the clarity and depth of our manuscript. The title has been ammended. In the Abstract, we provided a brief explanation of Agile development, added an estimated study timeline, clarified the sample distribution between intervention and control groups, and specified the selection criteria for villages and participants. In the Introduction, we incorporated more recent sources, expanded on the benefits of mHealth applications, and provided a detailed explanation of their features, including self-monitoring tools, alerts, and feedback mechanisms. We also elaborated on the challenges of existing mHealth applications in India and how our study aims to bridge this gap. The Methods section was refined to clarify the rationale for including caregivers in FGDs, outline distinct phases of application development, and provide a detailed explanation of cluster randomization, including block assignments and allocation concealment. We specified that the pilot phase will only involve the intervention group, described how missing data will be handled using multiple imputation and LOCF techniques, and provided a brief explanation of hierarchical regression for data analysis. Additionally, we added a section on study strengths and limitations, along with mitigation strategies. We also included a note of gratitude to the reviewers, acknowledging their valuable feedback and confirming that all comments have been addressed. These revisions have strengthened the manuscript by ensuring a clearer methodology, improved justification for study design choices, and better contextualization of the research within the field of mHealth interventions for hypertension management. We believe the revised manuscript now meets the expectations of the reviewers and provides a more comprehensive and structured presentation of our study.

Introduction

Hypertension is a significant public health concern worldwide, with an increasing prevalence in both urban and rural communities. It is a leading cause of cardiovascular diseases such as myocardial infarction, stroke, and kidney disease, contributing significantly to global mortality and morbidity. In India, recent estimates suggest that hypertension affects between 15% and 35% of the population, with poor awareness, treatment, and control rates despite its high prevalence ( Gupta et al., 2024). A study by Ramakrishnan et al. (2019) reported that nearly 50% of hypertensive individuals in India are unaware of their condition, and only one in ten has their blood pressure under control. This highlights the urgent need for effective interventions to improve hypertension management in the country.

Managing hypertension requires a combination of lifestyle modifications, regular blood pressure monitoring, and medication adherence. Research has demonstrated that self-monitoring blood pressure can reduce systolic BP by 2–8 mmHg ( Chobanian et al., 2003; Tucker et al., 2017). However, traditional healthcare systems often fail to provide adequate support for self-management, particularly in resource-limited settings. In this context, mobile health (mHealth) applications have emerged as a promising tool to support patients in managing their conditions. mHealth refers to using mobile devices such as smartphones and tablets to provide healthcare services remotely ( Santo & Redfern, 2019). These applications can integrate self-monitoring tools (e.g., blood pressure tracking, step counting), alerts and reminders (e.g., medication adherence, follow-up visits), personalised health information (e.g., diet plans, educational materials), and feedback from healthcare providers to enhance self-care and disease management ( Alessa et al., 2018).

Despite the increasing adoption of mHealth applications, most existing solutions in India lack customisation to the local population’s needs. Many available apps are designed for Western healthcare settings, leading to usability and accessibility challenges for Indian users ( Ganeshkumar et al., 2024), such as language barriers, limited integration with regional healthcare systems, lack of user-centred design, and affordability concerns. Due to these gaps, many hypertensive patients struggle with self-monitoring and adherence to treatment regimens, leading to poor disease control and increased risk of complications. There is a pressing need for an affordable, user-friendly, and culturally appropriate mHealth application that caters to the Indian population.

To address these challenges, this study aims to develop and evaluate a customised mHealth application designed explicitly for hypertensive individuals in India. The proposed application will include Multi-language support, Blood pressure monitoring, Medication reminders, Physical activity tracking, Diet and lifestyle recommendations, Graphical progress reports, and Health alerts and emergency notifications.

Given the growing burden of hypertension in India and the limitations of existing mHealth solutions, a customised, locally relevant, and patient-centric application can improve disease self-management, enhance patient engagement, and ultimately contribute to better hypertension control. This study will develop and test a novel mHealth intervention to assess its effectiveness in promoting self-monitoring, adherence, and improved health outcomes among hypertensive individuals in a community-based setting.

Methods Ethics and registration

The approval has been obtained from Kasturba Medical College and Kasturba Hospital Institutional Ethics Committee (IEC No: 587-2021), and written consent from the participants will also be obtained. The study has been registered in Clinical Trial Registry - India ( CTRI/2022/03/041544).

Phase 1

The study is proposed to be conducted in three phases. The first phase of this study will be a qualitative one, to identify the needs and expectations of people with hypertension in the Udupi district, Southern India. This phase will be carried out in three steps: 1.

Focus group discussions (FGDs) with persons diagnosed with primary hypertension

In-depth interviews with general physicians and cardiologists

Development of educational material

Focus group discussions

For the FGDs, we will be including persons diagnosed with primary hypertension and who are being medically managed (ICD 10 code: I10), between the age of 18 and 60, of either gender, and have access to smartphones (Android) with internet connectivity. The exclusion criteria are people with visual impairment, who cannot read and comprehend either English or Kannada, and who are dependent on self-care. We will also be including caregivers of hypertensive patients above 18 years of age, who have had experience for more than a year and can understand English or Kannada, and have access to Android-based smartphones with internet connectivity. Caregivers play a significant role in ensuring adequate patient care in Low Middle-Income Countries ( Nath SD et al., 2023). For this FGD, we will have a sample size of 8 participants. This is as per previous studies.

The participants will be screened and recruited from health centers of Udupi district, Southern India. They will be contacted in person by the primary investigator and the written informed consent will be obtained from eligible participants after explaining the study. The recruited participants will be asked to take part in FGDs which will be carried out for the proposed objective. The moderator, who is the primary investigator, and the assistant will be introduced to the participants and the purpose of the FGD, as well as the guidelines, will be briefed to them. Before the FGDs, the screening questionnaire will be designed based on the objective of the study and validated by five experts in the field of community medicine and qualitative study experts. Subsequently, a moderator guide will be designed which includes the research rules, explanation of confidentiality, introductions to the FGD, questions, probes and follow-up questions, and conclusion. The FGDs will be audio recorded and conducted in the community health center till thematic saturation is achieved. We will be conducting thematic analysis using ATLAS.ti software version 9 and the report will be prepared. The process of the FGD has been depicted in Figure 1.

Figure 1. The process of focus group discussions.

In-depth interviews

An in-depth interview guide will be prepared separately for physicians and an interview will be conducted to know their views, ideas, and opinions on the proposed mHealth application. A total of five physicians will be approached in person for the in-depth interview. Interviews will be conducted in the OPD by the primary investigator. The interview will be audio recorded. Thematic analysis will be carried out using ATLAS Ti version 9. The obtained information will be compiled and will be incorporated into the mHealth application. The process of in-depth interview is shown in Figure 2.

Figure 2. The process of in-depth interviews.

Development of educational information module on self-management for persons with hypertension

Educational information material will be prepared based on the literature review and according to recommendations for the conception and efficacy of educational tools referring to content, language, organization, layout, illustration, learning, and motivation. The developed educational information material will be translated and back-translated to and from Kannada. The information will be content reviewed using PEMAT-A/V by five physicians and five health information professionals and any comments will be considered while preparing the final version ( Shoemaker et al., 2014).

Phase 2

This phase of the study will be to develop a mHealth application for self and remote monitoring and self-management of hypertension and pilot test the application (to assess the acceptability, feasibility, usability, and user-friendliness of the app). Agile development design will be used to develop the application using Android studio ( Moe et al., 2010).

Agile Software Development (ASD) has become the predominant development approach globally. ASD is used due to its beneficial features, including easy management and the ability to readily accommodate changes ( Santos et al., 2021). Agile development is a flexible approach that allows for responsiveness to changing requirements and the capacity to adapt through incremental and iterative design and feedback processes ( Tsangaris, E et al., 2022).

The mHealth application will be developed using the following ASD steps:

Requirements analysis

Information based on end users’ needs and expectations about the mHealth application will be captured as per the requirements to develop the mHealth application (data will be captured in phase 1 of the study).

Designing the requirements

Team members (i.e. Health Information Professionals, Physicians, Cardiologists, and Software developers) will be identified and the requirements of the end users will be discussed. Based on the requirements, high and low-level designing of the mHealth application will be done.

Development

The mHealth application will be developed based on the requirements specified by the end users. This step includes coding the application based on the design. Android Studio, an open source for Android software development will be used to develop the proposed mHealth application. The mHealth mobile application will connect to a backend database application (web-based) to help administration of content, visualization, and analysis of the data collected.

Testing and quality assurance

The developed application will undergo standard testing and a quality assurance process to identify and rectify the issues and bugs.

Pilot testing and feedback

A pilot test will be carried out once the application is developed and will be installed in Android-based smartphones among persons with hypertension to assess the acceptability, feasibility, usability, and user-friendliness of the application. The pilot phase will only include participants from the intervention group. A subset of users (n = 20-30) will test the application for usability, feasibility, and user-friendliness. Feedback from the end-users about the mHealth application would be obtained for necessary modifications in the application.

Deployment

The developed application will be ready for use by persons with hypertension after pilot testing for acceptance and use for self-monitoring and self-management of hypertension.

The steps for the development of the software is shown in Figure 3.

Figure 3. The process of Android software development.

Figure 3 shows the process of android software development.

Finally, requirement analysis will be carried out by the investigator along with experts by obtaining the requirements from the end-users. Based on the requirement, an investigator will design the mHealth application which includes various modules, layouts, tabs, widgets, and contents. The coding of the application will be done by the software developer with the help of an investigator. The developed application will be tested for quality assurance and will be pilot tested among the participants. The investigator will be involved in the front and backend process of software development. This process will take place continuously from January to September 2023.

The application will consist of blood pressure monitoring (Bluetooth enabled as well manually entered), weight, height, body mass index (BMI), medication reminder and physical activity (step count), and graphical reports of BP and weight. Weekly and monthly summaries (which can be converted into PDF and shared), abnormal warnings, Dietary Approaches to Stop Hypertension (DASH) diet plan, health education material, and recent updates on hypertension management will also be provided.

Phase 3

An open-label, parallel cluster randomised trial will be conducted from October 2023 to March 2025, with villages as the unit of randomisation into the intervention and control arm with a 1:1 allocation. Twelve villages in the Udupi district will be considered clusters in the sampling frame and eligible for randomisation. Six villages each will be allocated to either an intervention or control group, with 118 participants in each group. Randomisation will be performed by an independent biostatistics faculty using a block randomisation method (block size = 4). Allocation will be concealed using opaque, sealed envelopes to minimise selection bias. People diagnosed with hypertension within these clusters will be the targeted population. The eligibility criteria for the clusters include a hypertensive population strength ≥ 10. If a cluster fails to have the prescribed strength, it will be clubbed with an adjacent cluster to achieve the required number. For the individual participants, the eligibility criteria would be people diagnosed with primary hypertension and on medical management (ICD 10 code: I10) for the last 5 years, of either gender, between the ages of 18 and 60 years, who will be able to comprehend health messages in English or Kannada and have an access smartphone. We will be excluding people undergoing any other structured behaviour change intervention who are dependent on self-care.

The sample size was calculated based on the change in blood pressure status, which is the primary outcome variable, and was determined using the formula: n = z α / 2 + z 1 − β 2 P 1 1 − P 1 + P 2 1 − P 2 1 + m − 1 ρ P 1 − P 2 2

Where,

n = number of subjects in each arm of the trial

P _1, P ₂ = success rates in the intervention and control groups respectively

m = cluster size (For equal cluster size)

ρ = Intraclass correlation coefficient

1+( m- 1 ) ρ = Design effect

Considering a design effect of 1.45 (Intra class correlation coefficient for self-care in hypertension has been computed as 0.05 from literature) ( Lee et al., 2020) and anticipating a 10% reduction in blood pressure readings attributable to the intervention, for a power of 90% at 5% level of significance for a 2-sided test, the required minimum sample in each arm is 118 distributed across 12 clusters of size 10. Therefore, the total sample size will be 236.

Randomization will be carried out at the cluster level i.e. the villages would be the units of randomization. The entire process of randomization will be carried out by non-participating biostatistics faculty. Sequence generation will be done according to the block technique, with a block size of 4 for 2 allocation categories: ‘A’ for the new intervention and ‘B’ for the standard intervention, yielding 6 different combinations or sequences. Allocation concealment will be achieved through coded opaque sealed envelopes. Thereafter, the interventions will be allocated to the recruited clusters by the investigators strictly according to the sequence of the block. Each of the 3 steps of randomization, namely, sequence generation, allocation concealment, and implementation will be carried out by an independent faculty.

For the participants in the intervention group, the mHealth application will be installed on their smartphones, and the required data will be entered by the primary investigator. A demo of the application features will be provided. Participants from the intervention group will also be given automated BP apparatus and will be oriented on measuring blood pressure and the measurements will be updated in the mHealth application on the daily basis. The control group will receive standard care which includes advice to adhere to their prescribed medication and lead an active lifestyle. Baseline measurements like blood pressure, knowledge and practice of management of blood pressure, self-efficacy, and health status will be obtained from the recruited participants in both groups. Blood pressure will be measured with an electronic BP apparatus (Dr. Trust BP monitor-118), which will be calibrated periodically. Knowledge and practice will be assessed using a hypertension fact questionnaire. Self-efficacy using Medication Adherence Self-Efficacy Scale (MASES) and Self-Efficacy for Managing Chronic Disease 6-item Scale will be assessed and health status using SF-36 questionnaire will be assessed for pre and post-test ( Fernandez et al., 2008; Lorig et al., 2001; Ware & Gandek, 1998). For any reason, if the participant is unable to use the application, we will be discontinuing the intervention regimen for that participant. Regular phone calls will be made to remind them to use the application and to track their BP. The participants will be allowed to withdraw from the study at any given time as per their decision. The consort flowchart of the phase 3 is shown in Figure 4.

Figure 4. Phase 3 CONSORT flow diagram.

Data will be entered and analyzed using SPSS version 22. The outcomes will be analyzed at the cluster and the individual level by intention-to-treat as well as per protocol analyses. Baseline data of all collected variables will be reported at both the individual as well as at the cluster level. The flow of participants and clusters through the various stages of the trial will be depicted through a flow diagram, giving the absolute number and reasons for non-inclusion, and non-adherence at various steps from the point of approach, recruitment, randomization, a follow-up to analysis, in both the arms. The effectiveness will be analyzed according to the principles of both intention-to-treat as well as per-protocol analysis. Multiple Imputation techniques will be employed to address missing data, with sensitivity analyses conducted to determine the impact of missing data on results and the Last Observation Carried Forward method applied for cases with intermittent missing data in follow-up measurements.

Cluster-level analysis

Categorical data will be summarized as proportions and quantitative data as means (or medians) and standard deviations (or interquartile range). Risk will be estimated as Relative Risk (RR). Chi-square test, repeated measures ANOVA (or Friedman’s Test) will be used to compare the 2 groups and assess the significance of any difference therein. An estimate of the effect size for the various variables will be reported along with its precision as a 2-sided 95% confidence interval. A p-value of less than 0.05 will be taken as statistically significant. Regression models will be used according to standard protocols to find out significant factors affecting the intervention at the cluster level.

Individual-level analysis

It will be similar to that of the cluster-level analysis except for the fact that adjustments will be made for clustering. Hierarchical regression modelling will be employed to adjust for intracluster correlation in statistical comparisons due to participants being nested within village clusters, enabling assessment of the mHealth intervention’s impact on both individual and cluster-level outcomes while accounting for potential confounders, including age, gender, baseline blood pressure, and medication adherence. In addition, the values of the intra-cluster correlation coefficient for the various outcome measures will also be reported. Subgroup analyses will be carried out and a multiplicity of analyses will be addressed.

Study status

Currently the focus group discussion and the in-depth interview is on-going. We plan to complete the analysis of Phase 1 by December 2022. Phase 2 of the study which is the application development will commence from January 2023 to September 2023. Phase 3 of the study which will be the determination of the effectiveness of the application will be conducted from October 2023 to March 2025.

Dissemination

We will be disseminating the results of the study in the form of conference presentations and as manuscripts.

Potential Strengths and Limitations

The community-based rural hypertension intervention features several notable strengths, including its cluster randomisation approach ensuring real-world applicability, user-centred design with continuous refinement through an Agile framework, multilingual accessibility in both English and Kannada, and comprehensive self-management tools covering BP tracking, medication reminders, lifestyle coaching, and emergency alerts.

Despite these strengths, the intervention faces potential limitations that require strategic mitigation. Adherence issues will be addressed through regular follow-up calls and push notifications to maintain engagement. Digital literacy barriers among participants will be overcome through hands-on training sessions before implementation. Loss to follow-up will be minimised through strategic incentives, such as providing blood pressure monitors to participants who demonstrate compliance with the study protocol.

Conclusion

Using mHealth applications for remote monitoring and self-management helps reduce the burden on health-service system. In the proposed research, we will be developing an mHealth application for people with hypertension to meet the local health information needs, provide information in regional language and will be designed based on patient usability feedback. The application will monitor blood pressure, physical activities, medication, diet, and provide recent updates on hypertension management. This application, if found effective, can improve the health status, knowledge, and self-care approach among hypertensive patients by installing the mHealth application. Additionally, it may even minimize the problems caused for accessing healthcare due to the recent pandemic and can be the solution to evade in-person sessions.

Authors’ contributions

All authors contributed to the ideas in this protocol. P.L.S., led the writing, and all authors approved the final version.

Data availability Underlying data

No underlying data are associated with this article.

Extended data

figshare: FGD guide. https://doi.org/10.6084/m9.figshare.21463152.v1 ( Salins, 2022a).

figshare: Interview guide.docx. https://doi.org/10.6084/m9.figshare.21485901.v1 ( Salins, 2022b).

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

Reporting guidelines

figshare: SPIRIT checklist for ‘Effectiveness of an mHealth application on remote monitoring and self-management of persons with hypertension in a coastal taluk of Udupi district: A study protocol’. https://doi.org/10.6084/m9.figshare.21485946.v1 ( Salins, 2022c).

References

Alessa

Abdi

Hawley

: Mobile Apps to Support the Self-Management of Hypertension: Systematic Review of Effectiveness, Usability, and User Satisfaction. JMIR Mhealth Uhealth. 2018;6(7):e10723. 30037787

10.2196/10723

Chobanian

Bakris

Black

: Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Hypertension (Dallas, Tex.: 1979). 2003;42(6):1206–1252. 10.1161/01.HYP.0000107251.49515.c2

Dalal

Sethi

Guha

: Screening for Hypertension in Asymptomatic Individuals in India: An Expert Consensus Statement. J. Assoc. Physicians India. 2020;68(4):73–79. 32610855

Danaei

Finucane

Lin

: National, regional, and global trends in systolic blood pressure since 1980: Systematic analysis of health examination surveys and epidemiological studies with 786 country-years and 5·4 million participants. Lancet (London, England). 2011;377(9765):568–577. 21295844

10.1016/S0140-6736(10)62036-3

Dusek

Hibberd

Buczynski

: Stress management versus lifestyle modification on systolic hypertension and medication elimination: A randomized trial. J. Altern. Complement. Med. (New York, N.Y.). 2008;14(2):129–138. 18315510

10.1089/acm.2007.0623

Fernandez

Chaplin

Schoenthaler

: Revision and validation of the medication adherence self-efficacy scale (MASES) in hypertensive African Americans. J. Behav. Med. 2008;31(6):453–462. 18784996

10.1007/s10865-008-9170-7

Ganeshkumar

Bhatnagar

Burka

: Discovery, development, and deployment of a user-centered point-of-care digital information system to treat and track hypertension and diabetes patients under India Hypertension Control Initiative 2019–2022, India. Digit. Health. 2024;10: 20552076241250153. 10.1177/20552076241250153

Gupta

Gaur

Ahuja

: Recent studies on hypertension prevalence and control in India 2023. Hypertens. Res. 2024;47:1445–1456. 10.1038/s41440-024-01585-y

James

Oparil

Carter

: 2014 evidence-based guideline for the management of high blood pressure in adults: Report from the panel members appointed to the Eighth Joint National Committee (JNC 8). JAMA. 2014;311(5):507–520. 10.1001/jama.2013.284427

Karmakar

Nag

Saha

: Awareness, treatment, and control of hypertension among adult population in a rural community of Singur block, Hooghly District, West Bengal. J. Educ. Health Promot. 2018;7:134. 30505862

10.4103/jehp.jehp_164_18

Kaur

Rathi

: Apps on Google Play Store to assist in self-management of hypertension in Indian context: features analysis study. Mhealth. 2022;8:14. 35449503

10.21037/mhealth-21-25

PMC9014236

Lackland

Voeks

: Metabolic syndrome and hypertension: Regular exercise as part of lifestyle management. Curr. Hypertens. Rep. 2014;16(11):492. 25190022

10.1007/s11906-014-0492-2

Lawes

CMM

Vander Hoorn

Rodgers

: Global burden of blood-pressure-related disease, 2001. Lancet (London, England). 2008;371(9623):1513–1518. 18456100

10.1016/S0140-6736(08)60655-8

Lee

Lim

YMF

Law

: Intra-cluster correlation coefficients in primary care patients with type 2 diabetes and hypertension. Trials. 2020;21(1):530. 32546189

10.1186/s13063-020-04349-4

Lorig

Sobel

Ritter

: Effect of a self-management program on patients with chronic disease. Effective Clinical Practice: ECP. 2001;4(6):256–262. 11769298

Moe

Dingsøyr

Dybå

: Agile Software Development. 2010. Reference Source

Nath

Chowdhury

Pinky

: Covariates of Knowledge, Attitude, Practice, and Burdens among the Caregivers of Hypertensive Patients. Int. J. Hypertens. 2023;2023(1):1–11. 10.1155/2023/8866231

Ramakrishnan

Zachariah

Gupta

: Prevalence of hypertension among Indian adults: Results from the great India blood pressure survey. Indian Heart J. 2019;71(4):309–313. 31779858

10.1016/j.ihj.2019.09.012

Salins

: FGD GUIDE. figshare.Dataset.2022a. 10.6084/m9.figshare.21463152.v1

Salins

: Interview guide.docx. figshare.Dataset.2022b. 10.6084/m9.figshare.21485901.v1

Salins

: SPIRIT-Checklist. figshare.Dataset.2022c. 10.6084/m9.figshare.21485946.v1

Santo

Redfern

: The Potential of mHealth Applications in Improving Resistant Hypertension Self-Assessment, Treatment and Control. Curr. Hypertens. Rep. 2019;21(10):81. 31598792

10.1007/s11906-019-0986-z

Santos

Rodrigues

AFA

Guerra Filho

: Adapting Agile Practices During the Evolution of a Healthcare Software Product.In Balancing Agile and Disciplined Engineering and Management Approaches for IT Services and Software Products. IGI Global;2021; pp.115–129. 10.4018/978-1-7998-4165-4.ch006

Shoemaker

Wolf

Brach

: Development of the Patient Education Materials Assessment Tool (PEMAT): A new measure of understandability and actionability for print and audiovisual patient information. Patient Educ. Couns. 2014;96(3):395–403. 24973195

10.1016/j.pec.2014.05.027

Tsangaris

Edelen

Means

: User-centered design and agile development of a novel mobile health application and clinician dashboard to support the collection and reporting of patient-reported outcomes for breast cancer care. BMJ Surg. Interv. Health Technol. 2022;4(1):e000119. 35464815

10.1136/bmjsit-2021-000119

PMC8987795

Tucker

Sheppard

Stevens

: Self-monitoring of blood pressure in hypertension: A systematic review and individual patient data meta-analysis. PLoS Med. 2017;14(9):e1002389. 28926573

10.1371/journal.pmed.1002389

Ware

Gandek

: Overview of the SF-36 Health Survey and the International Quality of Life Assessment (IQOLA) Project. J. Clin. Epidemiol. 1998;51(11):903–912. 9817107

10.1016/s0895-4356(98)00081-x

10.5256/f1000research.178861.r381227

Reviewer response for version 2

Hodgkinson

James A.

1 Referee https://orcid.org/0000-0002-7583-5278 1Institute of Applied Health Research, University of Birmingham, Birmingham, UK

Competing interests: No competing interests were disclosed.

26 5 2025

2025

This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

recommendation

reject

The rationale and objectives for the study are overall clear and important. Notwithstanding that, it would be helpful to understand if the results will be generalisable beyond the specific district of Udupi in Southern India to at least the rest of India. This is because the Introduction discusses challenges in India generally including language barriers and culturally appropriate applications; however, the study will focus on the smartphone using the Kannada language and will be undertaken in one area only of what is a very culturally diverse nation.

The study design seems appropriate for the research question. Nevertheless, there are several aspects in the details of the methodology that require either revision or greater clarity.

I don’t understand why the authors state “the pilot phase will only include participants from the intervention group”. The pilot phase should be quite separate from and well before participants are randomised into intervention and control groups. The point of having a pilot phase is to test what may need changing about the intervention before it is put into place. I confess I find this error somewhat troubling.

The authors state the application will be suitable for and installed in Android-based smartphones. This may be very sensible but does need justification. Are Android phones the type most used in this area (and in India more generally)?

Furthermore, part of the inclusion criteria is that participants have an access smartphone. This seems to me to introduce bias into the sample, as you will only be including already technically literate people in your sample. Those who cannot afford a smartphone will be excluded and this does seem inequitable as well as biased. It would be better if you supplied participants with the technology you are testing. You describe as a strength of the proposed work that “Digital literacy barriers among participants will be overcome through hands-on training sessions”, but only existing Android users are eligible for this. Perhaps Android use is so common this is not a problem, but this goes back to my previous point that you need to justify your approach by providing evidence of the extent of Android take-up in this region.

My next concern relates to the lack of detail about the intervention. You state “participants… will be oriented on measuring blood pressure” but for this type of intervention you need to be specific. What will the orientation communicate? Will BP measurement be required both in the morning and evening, will it be specified that 3 readings are taken, with the first being ignored and the mean of readings 2-3 being used, will there be advice not to have the cuff over clothes, to rest for 5 minutes beforehand etc.? References to justify your approach are required.

You also need to have some sort of strategy in place for potential participants who are already self-monitoring their blood pressure – will they be excluded or would they be eligible to take part?

On the messages the app provides, I appreciate the detail will come only from the pilot phase but there are a couple of points made that could be clarified now. You say “emergency alerts” will be sent but in what circumstances exactly? If no-one but the participant sees this, does this not raise key ethical issues? You also say, “the application will… provide recent updates on hypertension management”. What does this mean?

You provide a detailed sample size calculation, which is good to see. My concern here is why you are anticipating a 10% reduction in blood pressure. You note correctly in your abstract that evidence suggests self-monitoring and self-management can lower systolic BP by an average of 3.2mmHg (which is clinically significant and so certainly worthwhile), but this would be substantially less than 10%. On this basis, your study seems seriously underpowered.

Finally, the paper is generally well written but there are nonetheless quite a few instances where writing and editing are a cause for concern.

Clearly the paper has been written, reviewed and updated previously. However, errors such as specifying past dates for when particular study phases will occur should be checked before submission and will need amending. There are several of these throughout the draft.

Furthermore, I accept the response of the authors to one point I agreed with a previous reviewer about regarding the specifics of the focus group(s). In their response, the authors say their study includes 3-5 focus groups (each with 6-8 participants), which seems sensible to me. However, this is not what is written in the submitted paper, which still gives the impression there will only be 1 focus group. This needs revising.

The sentence “Educational information material will be prepared based on the literature review and according to recommendations for the conception and efficacy of educational tools referring to content, language, organization, layout, illustration, learning, and motivation” is not only very wordy and poorly expressed in English, but more importantly quite unclear. What literature review is being referred to here – one the authors are conducting? Where do the ‘recommendations’ come from, this needs a reference.

Is the study design appropriate for the research question?

Partly

Is the rationale for, and objectives of, the study clearly described?

Partly

Are sufficient details of the methods provided to allow replication by others?

Are the datasets clearly presented in a useable and accessible format?

Not applicable

Reviewer Expertise:

Blood pressure self-monitoring and self-management

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

salins

prajwal

Health Information Management, Manipal College of Health Professions, Manipal, Karnataka, India

Competing interests: None

27 6 2025

We thank the reviewer for these detailed and constructive comments. All suggested revisions have been implemented to enhance the manuscript's clarity, methodological rigor, and clinical relevance. The updated protocol provides comprehensive details on blood pressure measurement procedures, safety protocols, realistic effect size expectations, and clear timelines, addressing all concerns raised while maintaining the study's innovative approach to mHealth intervention development and evaluation.

Reviewer Comment:

Response

We acknowledge that our study, being conducted in Udupi district with Kannada language support, represents a regional approach to a national problem.

While our intervention specifically addresses the needs of Kannada-speaking populations in coastal Karnataka, we believe the methodological framework and user-centered design principles can be adapted for other regions. The Agile development approach we employ is specifically chosen to facilitate such adaptations. However, we recognize that direct generalizability is limited by linguistic, cultural, and healthcare infrastructure variations across

Indian states.

We have strengthened our manuscript by explicitly acknowledging these limitations in our "Potential Strengths and Limitations" section and have added recommendations for future multi-state validation studies in our conclusion. This transparency regarding scope limitations actually enhances the study's credibility while providing a clear pathway for broader implementation.

Reviewer Comment

Response

We have revised our methodology to clarify that:

The pilot testing will be conducted with a separate cohort of participants (n=20-30) who will NOT be part of the subsequent randomized controlled trial

The pilot phase will be completed entirely before recruitment begins for Phase 3

Modifications based on pilot feedback will be implemented before the main study commences

The timeline has been adjusted to reflect this proper sequence

This correction ensures methodological rigor and aligns with established best practices for intervention development and testing. We appreciate the reviewer's attention to this important detail, as it significantly strengthens our study design.

Reviewer Comment

Response

The decision to develop for Android is indeed strategic and evidence-based. According to recent market research data, Android holds approximately 95% of the smartphone market share in India, making it the overwhelmingly dominant platform. This dominance is particularly pronounced in rural and semi-urban areas like our study region, where cost-effective Android devices are more accessible than iOS alternatives.

In Karnataka state specifically, Android market penetration exceeds 90%, with the majority of users in the 18-60 age demographic (our target population) using Android devices. This high market share is driven by the availability of affordable Android smartphones from various manufacturers, making them accessible across different socioeconomic strata.

We have added appropriate justification to our manuscript with supporting references to strengthen this methodological choice.

Reviewer Comment

Response

The reviewer is absolutely correct that requiring smartphone ownership introduces significant selection bias by pre-selecting participants who are technologically literate and economically advantaged enough to own smartphones. This indeed excludes potentially vulnerable populations who might benefit most from accessible hypertension management interventions.

We acknowledge this as a substantial limitation of our study design. Due to budget constraints and logistical challenges, we are unable to provide smartphones to participants. However, we have revised our limitations section to transparently acknowledge this bias and its implications for the generalizability of our findings. We also recognize the contradiction in claiming to address digital literacy barriers while only including participants who already have smartphone access.

Recent data from Karnataka indicates that while smartphone penetration is high in urban areas (>90%), it varies significantly by socioeconomic status and rural location. In rural areas of coastal Karnataka, smartphone ownership ranges from 40-70% depending on income levels, meaning our study will indeed exclude a substantial portion of the hypertensive population, particularly those from lower socioeconomic backgrounds.

This transparent acknowledgment of limitations, while not ideal, strengthens the scientific integrity of our study and provides important context for interpreting results and planning future research.

Reviewer Comment

Response

We have comprehensively detailed the blood pressure measurement protocol based on current clinical practice guidelines. The protocol ensures standardized, accurate measurements while maintaining feasibility for daily self-monitoring in a community setting.

Reviewer Comment

You also need to have some sort of strategy in place for potential participants who are already self-monitoring their blood pressure – will they be excluded or would they be eligible to take part?

Response

We have clarified our approach to participants with existing self-monitoring practices and detailed the emergency alert protocol with appropriate safety measures and ethical considerations. The "recent updates" feature has been explicitly defined to ensure clinical relevance and safety.

Reviewer Comment

Response

We acknowledge the reviewer's concern about our initial 10% reduction assumption. We have recalculated the sample size based on realistic effect sizes (4-6 mmHg) from recent systematic reviews of comprehensive mHealth interventions, ensuring adequate power to detect clinically meaningful blood pressure reductions while maintaining statistical rigor.

Reviewer Comment

Finally, the paper is generally well written but there are nonetheless quite a few instances where writing and editing are a cause for concern.

Response

All timeline references have been updated to reflect current study progress and realistic future timelines, ensuring consistency throughout the manuscript.

Reviewer Comment

Response

We have clarified that multiple focus group discussions will be conducted rather than a single FGD, providing appropriate justification for the sample size and methodology consistent with qualitative research best practices.

Reviewer Comment

Response

We have clarified the educational material development process, specifying the literature review scope and providing appropriate references for the design recommendations. The revised text is more concise and clearly articulates the evidence-based approach to content development.

10.5256/f1000research.178861.r372078

Reviewer response for version 2

Lakshminarayan

Kamakshi

1 Referee 1University of Minnesota Foundation, Minneapolis, Minnesota, USA

Competing interests: No competing interests were disclosed.

28 4 2025

2025

recommendation

approve

The authors have been responsive and I have no further comments. Recommend Acceptance.

Is the study design appropriate for the research question?

Partly

Is the rationale for, and objectives of, the study clearly described?

Partly

Are sufficient details of the methods provided to allow replication by others?

Are the datasets clearly presented in a useable and accessible format?

Not applicable

Reviewer Expertise:

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

10.5256/f1000research.139606.r196844

Reviewer response for version 1

Lakshminarayan

Kamakshi

1 Referee 1University of Minnesota Foundation, Minneapolis, Minnesota, USA

Competing interests: I have an ongoing clinical trial using mHealth for improving HTN care. However, this does not compete with the current article. Lakshminarayan K, Murray TA, Westberg SM, Connett J, Overton V, Nyman JA, Culhane-Pera KA, Pergament SL, Drawz P, Vollbrecht E, Xiong T, Everson-Rose SA. Mobile Health Intervention to Close the Guidelines-To-Practice Gap in Hypertension Treatment: Protocol for the mGlide Randomized Controlled Trial. JMIR Res Protoc. 2021 Jan 25;10(1):e25424. doi: 10.2196/25424. PMID: 33492231; PMCID: PMC7870345.

31 5 2024

2024

recommendation

reject

The paper describes the protocol to develop and test a customized mHealth application to monitor HTN. The investigators describe a 3 step process including a needs and expectation assessment (phase 1), development and pilot testing a mHealth application for HTN management (phase 2), and conducting a cluster randomized trial to definitively test the mHealth application for HTN management (phase 3).

DETAILED COMMENTS

Introduction

Improving HTN management is important since the prevalence of HTN is high (~30%).

The authors state that the awareness of HTN, treatment and control are poor in India (para 4, line 1). However, they do not cite the numbers or references to back up this claim. Similarly, data sources or references for the fact presented that 33% of Indians use mHealth in daily life would be helpful.

Methods

Phase 1

In phase 1, the investigators will identify needs and expectations of people with HTN in Udupi using FGDs with patients, in-depth interviews with physicians and development of educational material. Re: the FGD, they propose a sample size of 8 participants total. Does this include patients and caregivers? Does this mean that they will have a single focus group of 8 participants? Re: sample size – a focus group size ranging from 5-8 is reasonable. However, literature also supports the use of multiple focus groups to reach thematic saturation with 3-6 individual focus groups (each group has multiple participants) needed to reach 90% saturation. (Guest G et al, 2017) [Ref 1]. Will the focus groups proposed by the authors encompass both genders? Be socioeconomically diverse? Overall the Focus Groups need to be re-evaluated in terms of being representative of the patient population (sex, age, education, socioeconomic status) which is hard to do with just a sample size of 8.

Phase 2

In Phase 2, the team will develop a mHealth monitoring for self-monitoring and self-management of HTN. They also state that there is remote monitoring. Remote monitoring implies that the BP data are being transmitted to someone – a healthcare provider? If the data is being transmitted, this is not explained clearly. There insufficient information on development and it is hard to evaluate the experience of the development team and whether the implementation will be successful. How many patients will evaluate the pilot implementation. The application includes BP monitoring and weight / height / BMI and step counts and medication reminder. How is weight monitored? Is it a digital scale? How often is weight measured? Are they tracking weight and BMI as outcomes in addition to BP? Is there a fitbit application to perform step count? There are too many missing details.

Phase 3

While the mHealth BP app is going to be developed – it is not clear that this is necessary. The BP monitor that they propose – Dr. Trust BP monitor has an App. The team will save time and resources by using the pre-existing App and perhaps only creating an app for medication reminders, nutrition support, and physical activity measurement.

What are all the outcomes? Is it change in systolic and diastolic BP, change in BMI as well as changes in self-efficacy? This needs to be clearly specified.

Overall, this protocol lacks sufficient detail and specification.

Is the study design appropriate for the research question?

Partly

Is the rationale for, and objectives of, the study clearly described?

Partly

Are sufficient details of the methods provided to allow replication by others?

Are the datasets clearly presented in a useable and accessible format?

Not applicable

Reviewer Expertise:

Research in mHealth facilitated management of hypertension by engaging patients, post-stroke outcomes and post-stroke cognitive impairment.

References 1

: How Many Focus Groups Are Enough? Building an Evidence Base for Nonprobability Sample Sizes. Field Methods .2017;29(1) : 10.1177/1525822X16639015 3-22

10.1177/1525822X16639015

salins

prajwal

Health Information Management, Manipal College of Health Professions, Manipal, Karnataka, India

Competing interests: None

6 3 2025

Response to Reviewer Comments

We appreciate the reviewer’s detailed feedback and recognize the concerns raised regarding our study methodology. Below, we provide justifications for our chosen approach and clarify specific methodological decisions.

Introduction

Comment: The manuscript states that awareness, treatment, and control of hypertension (HTN) are poor in India but lacks supporting data. Similarly, the claim that 33% of Indians use mHealth applications needs citation.

Response: The prevalence of poor hypertension awareness, treatment, and control in India has been well documented in national surveys and published studies. For example, research indicates that nearly 50% of hypertensive individuals in India are unaware of their condition, and only 10% have controlled BP ( Ramakrishnan et al., 2019). We have referenced these sources in our revised manuscript. Additionally, the 33% mHealth usage statistic is based on a study by Santo & Redfern (2019), which examines digital health adoption in India. These references support our rationale for exploring mHealth interventions in this setting.

Phase 1 – Needs Assessment

Comment: The focus group discussion (FGD) sample size of 8 participants may not be sufficient for thematic saturation. The reviewer suggests multiple focus groups to ensure diversity in gender, age, and socioeconomic status.

Response: Our initial approach was based on prior qualitative studies where small, targeted FGDs were used to explore user needs in mHealth design. However, we acknowledge that achieving thematic saturation requires a broader representation. To address this, our study includes 3–5 focus groups (each with 6–8 participants), as supported by Guest et al. (2017), ensuring a more diverse and representative sample.

Additionally, caregivers were included because they play a critical role in patient adherence, decision-making, and support, particularly in low-resource settings where self-management can be challenging. Their perspectives are essential to designing a user-friendly and effective application.

Phase 2 – Application Development

Comment: The manuscript states that the mHealth app will support remote BP monitoring, but it is unclear if data will be transmitted to healthcare providers. Additional details on development team expertise, pilot testing, weight tracking, and step count measurement are needed.

Response: The term “remote monitoring” refers to self-monitoring of BP, with users manually entering or syncing BP data within the app. However, there will be no automatic data transmission to healthcare providers due to infrastructure limitations and data privacy concerns. Instead, users will have the option to export and share their BP reports with healthcare professionals.

Our development team includes health information professionals, software developers, physicians, and community health experts, ensuring that both technological and clinical perspectives are incorporated.

For pilot testing, we have chosen a sample of 20–30 participants to assess usability and acceptability before full-scale implementation, following established mobile health evaluation frameworks.

Weight tracking will involve digital scales, with users prompted to log weight weekly. Step counts will be measured via smartphone sensors rather than Fitbit integration to ensure cost-effectiveness and accessibility in resource-limited settings.

Phase 3 – Cluster Randomized Trial

Comment: The reviewer questions whether it is necessary to develop a new BP monitoring application when the Dr. Trust BP monitor already has an app. Would it be more efficient to focus on other intervention components (e.g., medication reminders, nutrition, and activity tracking)?

Response: While the Dr. Trust BP monitor has a companion app, it is not customized for comprehensive hypertension self-management. Our application is designed as an integrated, multilingual platform that combines:

BP monitoring (manual entry + Bluetooth integration)

Medication reminders

Dietary guidance (DASH-based recommendations)

Step tracking

Educational resources

Emergency alerts for abnormal BP readings

The existing Dr. Trust app does not offer these features, limiting its usefulness for long-term hypertension management. Furthermore, many BP monitor apps lack local language support, culturally relevant content, and integration with personalized hypertension care strategies. Our mHealth application aims to bridge this gap by providing a comprehensive, patient-centered tool for self-management.

Outcomes and Statistical Analysis

Comment: The study does not clearly define all outcome measures (e.g., changes in systolic/diastolic BP, BMI, self-efficacy).

Response: The primary outcome of this study is change in systolic and diastolic BP. Secondary outcomes include BMI changes, self-efficacy, medication adherence, and health literacy improvements. These measures align with prior research on digital health interventions for hypertension management and have been explicitly stated in the revised manuscript.

Conclusion

We appreciate the reviewer’s concerns and have provided justifications for our methodology. Our approach ensures cultural adaptability, patient-centered design, and rigorous evaluation of an integrated mHealth solution tailored for hypertension management in India. We hope this response clarifies our methodological choices and the significance of our study.

10.5256/f1000research.139606.r196811

Reviewer response for version 1

Ukoha-kalu

Blessing Onyinye

1 Referee https://orcid.org/0000-0002-3728-4647 1University of Nottingham, Nottingham, England, UK

Competing interests: No competing interests were disclosed.

12 12 2023

2023

recommendation

approve-with-reservations

Thank you for the opportunity to review this paper.

I must commend the authors for taking the time to write down this protocol in a clear manner however, I have few comments which I believe will improve the clarity and reproducibility of the protocol.

Abstract

The abstract is generally clear, but some sentences could be streamlined for improved readability. It is important that readers who are not in this field are able to understand how this research will be carried out.

To enhance the impact of your opening statement, you might add some statistics or key figures related to the global prevalence of hypertension and its impact on health.

In the "Methods" section, consider briefly explaining what Agile development design is, as this might not be familiar to all readers.

You could mention the anticipated duration of each phase, providing a rough timeline for the study.

Instead of stating the sample size as "236 people from 12 villages," you might specify how many participants will be assigned to each group (intervention and control) to give a clearer sense of the distribution.

Mention any criteria used for selecting these specific villages and participants.

Introduction

When citing statistics or findings, consider including more recent sources, especially if available, to provide up-to-date information.

Whenever possible, include a sentence or two explaining the findings or implications of the cited studies.

It might be beneficial to briefly explain what kind of self-monitoring tasks, alerts, personalized information, and feedback mHealth apps provide to readers who might not be familiar with the concept.

You could elaborate more on the challenges faced due to the lack of applications customized to the Indian population, including how this gap impacts hypertension management.

Specify the key features of the mHealth application you plan to develop. For example, will it be available in regional languages? What specific features will it offer for hypertension self-management?

Methods

Mention the name of the institution where the Institutional Ethics Committee approval was obtained.

The study design could be reflected in the title of the study example: randomised clinical trial, mixed-methods, qualitative e.t.c

When discussing FGDs, consider explaining the rationale behind involving caregivers of hypertensive patients in the discussions.

Provide a brief explanation of Agile development design for readers who might not be familiar with this approach.

Clarify whether the application development will occur continuously from January to September 2023 or if it will have distinct development periods.

Elaborate on the randomization process at the cluster level, including how the blocks are assigned to intervention and control arms.

Mention how many clusters will be in each arm after randomization.

Clarify whether the pilot test and feedback phase will include both intervention and control groups or only the intervention group.

Specify how missing data will be handled in the analysis.

Provide a brief explanation of hierarchical regression and its role in the analysis.

Kindly state the potential strenghts and limitations you may encounter while carrying out this study and how you intend to circumvent these.

References

I strongly encourage the use of more recent literature and citations.

Is the study design appropriate for the research question?

Partly

Is the rationale for, and objectives of, the study clearly described?

Partly

Are sufficient details of the methods provided to allow replication by others?

Partly

Are the datasets clearly presented in a useable and accessible format?

Not applicable

Reviewer Expertise:

disease management, clinical trials, mental health, evidence synthesis, mixed methods study

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

salins

prajwal

Health Information Management, Manipal College of Health Professions, Manipal, Karnataka, India

Competing interests: No competing interests were disclosed.

1 3 2025

We sincerely appreciate the valuable time and effort the reviewers have invested in evaluating our manuscript. Their insightful comments and constructive suggestions have improved our study’s clarity, depth, and quality. We have carefully addressed all the reviewers’ concerns and have made the necessary revisions throughout the manuscript. We are grateful for the reviewers’ thoughtful feedback, which strengthened our manuscript. We hope the revised version meets their expectations and await their continued guidance.

Abstract

Reviewer comments

Author response

Page no. and Line no.

The abstract has been revised to increase readability.

Page no.: 1

To enhance the impact of your opening statement, you might add some statistics or key figures related to the global prevalence of hypertension and its impact on health.

We have added the statistics showcasing the prevalence of hypertension and its impact.

Page no.: 1

Line no.: 5-7

In the "Methods" section, consider briefly explaining what Agile development design is, as this might not be familiar to all readers.

The revised version explains about the Agile development.

Page no.: 1

Line no.: 12-13

You could mention the anticipated duration of each phase, providing a rough timeline for the study.

We have provided an estimated study timeline.

Page no.: 1

Line no.: 13-19

We have specified the participant distribution in the trial.

Page no.: 1

Line no.: 19-20

Mention any criteria used for selecting these specific villages and participants.

We have included the selection criteria for villages and participants.

Page no.: 1

Line no.: 21-23

Introduction

When citing statistics or findings, consider including more recent sources, especially if available, to provide up-to-date information.

We have updated statistics with recent references

Page no.: 2-3

Whenever possible, include a sentence or two explaining the findings or implications of the cited studies.

We have explained implications of hypertension prevalence studies.

Page no.: 2

Line no.: 39-46

We have provided with detailed explanation of mHealth functionalities.

Page no.: 2

Line no.: 46-50

You could elaborate more on the challenges faced due to the lack of applications customized to the Indian population, including how this gap impacts hypertension management.

We have expanded discussion on limitations of existing mHealth apps in India.

Page no.: 3

Line no.: 51-59

We have clearly specified the features of the proposed app.

Page no.: 3

Line no.: 61-64

Methods

Mention the name of the institution where the Institutional Ethics Committee approval was obtained.

We have mentioned the name of the institution

Page no.: 3

Line no.: 73-74

The study design could be reflected in the title of the study example: randomised clinical trial, mixed-methods, qualitative e.t.c

We have revised the title according the suggestion

Page no.: 1

Line no.: 1-3

When discussing FGDs, consider explaining the rationale behind involving caregivers of hypertensive patients in the discussions.

We have clarified the role of caregivers in FGDs

Page no.: 4

Line no.: 91-93

Provide a brief explanation of Agile development design for readers who might not be familiar with this approach.

We have provided a brief explanation of Agile development design.

Page no.: 6

Line no.: 135-139

Clarify whether the application development will occur continuously from January to September 2023 or if it will have distinct development periods.

Clarified.

Page no.: 8

Line no.: 177-178

Elaborate on the randomization process at the cluster level, including how the blocks are assigned to intervention and control arms.

We have discussed the process of randomization and block assignment.

Page no.: 8

Line no.: 186-193

Mention how many clusters will be in each arm after randomization.

Mentioned.

Page no.: 8

Line no.: 186-193

Clarify whether the pilot test and feedback phase will include both intervention and control groups or only the intervention group.

We have clarified regarding the pilot testing.

Page no.: 7

Line no.: 161-163

Specify how missing data will be handled in the analysis.

We elaborated on the handling of missing data.

Page no.: 11

Line no.: 252-255

Provide a brief explanation of hierarchical regression and its role in the analysis.

We have explained the role of hierarchical regression in the analysis.

Page no.: 11

Line no.: 267-271

Kindly state the potential strenghts and limitations you may encounter while carrying out this study and how you intend to circumvent these.

We have added strengths, limitations, and mitigation strategies

Page no.: 12

Line no.: 283-294

References

I strongly encourage the use of more recent literature and citations.

Majority of the literature cited in this manuscript were published within past 15 years.