F1000Research F1000Research 2046-1402 F1000 Research Limited London, UK 10.12688/f1000research.127131.1 Study Protocol Articles 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

[version 1; peer review: 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 Health Information Management, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India School of Public Health, DY Patil University, Navi Mumbai, Maharashtra, 400706, India Department of Data Science and Computer Applications, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India Department of Community Medicine, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India sabu.km@manipal.edu

No competing interests were disclosed.

 28 11 2022 2022 11 1393 3 11 2022 Copyright: © 2022 Salins PL et al. 2022 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 the most important risk factor for cardiovascular disease, a major cause of death and disability globally. There is increasing evidence that demonstrates clinically relevant benefits from self-monitoring and self-management of blood pressure. Evidence suggests a reduction of systolic BP by 3.2 mm/hg through self-monitoring. The use of mHealth applications in health care monitoring and self-management can help in the timely delivery of health information. Around 33% of Indians use mHealth applications in their daily life. However, well-designed, user complied mHealth applications are essential to reach the masses and to be effective. A previously conducted study in India demonstrated that applications are not customized according to users' needs and expectations and lacked usability assessment by patients. Therefore, we aimed to develop and test a novel mHealth application on remote monitoring and self-management in hypertension.

Methods: The study will be carried out in three phases. The first phase will be an in-depth interview to identify the required parameters to develop a customized mHealth android-based application to monitor hypertension. The second phase is to develop the customized application through the Agile development design using the android studio platform. In the third phase, a community-based cluster randomized trial will be carried out to assess the effectiveness of the mHealth intervention on the remote monitoring and self-management of people with hypertension. A sample of 236 people from 12 villages will be randomized and the mHealth application will be delivered to the intervention group and the standard regimen will be continued in the control group.

Results:In the proposed study if the intervention is found to be helpful, then hypertension patients in the community can be encouraged to install the mHealth application. This application, if found effective can improve the health status, knowledge, and self-care approach among hypertensive patients.

Registration: CTR India ( CTRI/2022/03/041544).

 mHealth remote monitoring self-management hypertension The author(s) declared that no grants were involved in supporting this work. Introduction

Hypertension is a major public health concern worldwide and in India with a significantly growing prevalence in both urban and rural communities. It is one of the major causes of mortality and morbidity in elderly people, but hypertension is still a significant health problem ( Karmakar et al., 2018). Approximately 13.5% of global premature deaths are due to increased blood pressure ( Lawes et al., 2008). In low and middle-income nations, the age-adjusted systolic blood pressure (BP) is high and the mean age-adjusted systolic BP has drastically increased in developing countries like East Africa, and South and Southeast Asia. In addition, the number of persons with uncontrolled hypertension rose between 1980 and 2008 due to population growth and aging around the world ( Danaei et al., 2011). Hypertension prevalence in India is enormous. Recent evidence shows a prevalence of hypertension in India of 30.7% ( Ramakrishnan et al., 2019).

Hypertension leads to myocardial infarction, cerebral infarction, heart failure, and kidney disease ( James et al., 2014). Early diagnosis is thus necessary for managing hypertension and preventing future risks ( Dalal et al., 2020). Lifestyle modifications and drug treatment are the two primary types of hypertension care. Managing lifestyle is the primary step in hypertension care for patients over 18 years of age ( James et al., 2014). Lifestyle management including exercise and diet helps in reducing blood pressure ( Lackland & Voeks, 2014). Stress management including various relaxation techniques such as meditation, prayer, and yoga also helps in reducing systolic blood pressure ( Dusek et al., 2008).

There is increasing evidence that demonstrates clinically relevant benefits from self-monitoring and self-management of blood pressure. Evidence suggests a reduction of systolic BP by 2-8 mm/hg ( Chobanian et al., 2003; Tucker et al., 2017). In the recent era, user-friendly technology plays an important role in addressing the challenges with the dissemination of important and relevant health information to the public. mHealth refers to the provision of healthcare services by mobile communications devices ( Santo & Redfern, 2019). The increase in the use of smartphones and tablets has been accompanied by an increase in the use of mHealth applications. The use of mHealth in the self-care of chronic diseases such as hypertension is becoming increasingly popular. Most mHealth apps are designed to assist persons with hypertension in self-management by providing self-monitoring tasks, alerts, personalized information, and feedback ( Santo & Redfern, 2019).

In India, the awareness, medical treatments, and control of hypertension remain poor despite its substantial prevalence. Around 33% of Indians use some mHealth application in their daily life. Although few applications are available in the market, there are no adequate applications customized to the Indian population ( Santo & Redfern, 2019). A recent study conducted demonstrated that applications are not customized according to Indian users’ needs and expectations in regional language and lacked usability assessment by patients ( Alessa et al., 2018; Santo & Redfern, 2019). Most of the evidence that determines the effectiveness of mHealth applications has been conducted in developed countries with very little evidence from developing countries, specifically the South Asian region and India in particular.

Therefore, there is a need to develop an application that meets the local health information needs, provides information in the local language, and is designed based on patient usability feedback. Further studying the effectiveness of the application on knowledge about the disease, self-care among the participants, and blood pressure status of the patients with hypertension will throw more light with regards to this.

Thus, we aim to develop a user-friendly mHealth application for remote monitoring and self-management in persons with hypertension and assess its effectiveness. Further, we propose to test this application for its effectiveness in improving the knowledge, self-efficacy, health status, and self-management of persons with hypertension.

 Methods Ethics and registration

The approval has been obtained from 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:

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. 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.

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.

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).

The mHealth application will be developed in five steps as follows:

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. 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.

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.

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 randomized trial will be conducted from October 2023 to March 2025 with villages as the unit of randomization into the intervention and control arm with a 1:1 allocation. 12 villages in the Udupi district will be considered as the clusters included in the sampling frame and eligible for randomization. People diagnosed with hypertension within these clusters will be the targeted population. The eligibility criteria for the clusters include a hypertensive population strength ≥ 10. In case 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 age 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 behavior change intervention and who are dependent for 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.

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.

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 will be used according to standard protocols to find out significant factors affecting the intervention. 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 be commenced January 2023 and completed by 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.

 Conclusion

Use of 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).

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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 Copyright: © 2024 Lakshminarayan K 2024 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 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?

No

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.

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.

References : 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 University of Nottingham, Nottingham, England, UK

Competing interests: No competing interests were disclosed.

 12 12 2023 Copyright: © 2023 Ukoha-kalu BO 2023 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 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 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.

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

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.

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

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.

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

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?

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.