Development and Validation of a Needs Assessment Guide for mHealth-Based Self-Management among Patients with Hypertension [version 1; peer review: awaiting peer review]

Дата публикации: 17-07-2026 16:32:27

Background Given the significant global burden of hypertension and the perception of service quality significantly influences a patient’s satisfaction and their willingness to engage with mobile health (mHealth) interventions, this study aimed to develop and validate a Focus Group Discussion (FGD) guide to explore the self-management needs, preferences, and barriers of patients with hypertension for designing a contextually relevant mHealth application. Methods The FGD guide was developed via literature review and validated through a two-step process. First, face validity was assessed by a panel of five experts to evaluate flow, clarity, and comprehensiveness. Subsequently, content validity was quantified by a separate panel of ten experts using a structured assessment, with results analyzed via the Content Validity Index (CVI), Content Validity Ratio (CVR), and Kappa statistics. The guide was also pilot-tested with a small sample to refine clarity and depth before final use. Results Expert evaluations demonstrated high item-level content validity, with CVR and Kappa coefficient values ≥0.8 and ≥ 0.89, respectively. The S-CVI (universal agreement) indicated moderate content validity, while the S-CVI (average method) revealed high content validity. Feedback from both healthcare professionals and hypertensive patients resulted in improvements to wording, clarity, and contextual relevance, thereby enhancing the guide’s comprehensibility and cultural alignment. Conclusion This systematically developed FGD guide demonstrates moderate to high content validity and acceptable reliability. It is a suitable, validated tool for exploring patient-reported experiences in hypertension self-management to inform patient-centered mHealth interventions.

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Salins PL, Mandapam SK, Reshmi B et al. Development and Validation of a Needs Assessment Guide for mHealth-Based Self-Management among Patients with Hypertension [version 1; peer review: awaiting peer review]. F1000Research 2026, 15:1185 (https://doi.org/10.12688/f1000research.181812.1)

Research Article

[version 1; peer review: awaiting peer review]

Prajwal L. Salins

https://orcid.org/0000-0001-8722-0150

¹, Sabu K Mandapam

https://orcid.org/0000-0002-6673-060X

¹, Bhageerathy Reshmi

https://orcid.org/0000-0001-9631-6218

¹, Raksha Kamath

https://orcid.org/0009-0006-7035-9352

¹, Suma Nair², Poornima P. Kundapur

https://orcid.org/0000-0002-8271-524X

Prajwal L. Salins

https://orcid.org/0000-0001-8722-0150

¹, Sabu K Mandapam

https://orcid.org/0000-0002-6673-060X

¹, [...] Bhageerathy Reshmi

https://orcid.org/0000-0001-9631-6218

¹, Raksha Kamath

https://orcid.org/0009-0006-7035-9352

¹, Suma Nair², Poornima P. Kundapur

https://orcid.org/0000-0002-8271-524X

Author details Author details

¹ Department of Health Information Management, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, India
² School of Public Health, DY Patil University Deemed to be University, Navi Mumbai, Maharashtra, India
³ Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India

Prajwal L. Salins
Roles: Conceptualization, Data Curation, Investigation, Methodology, Validation, Writing – Original Draft Preparation

Sabu K Mandapam
Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Supervision, Validation, Writing – Review & Editing

Bhageerathy Reshmi
Roles: Conceptualization, Data Curation, Methodology, Supervision, Validation, Writing – Review & Editing

Raksha Kamath
Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Resources, Validation, Writing – Original Draft Preparation

Suma Nair
Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Supervision, Validation, Writing – Review & Editing

Poornima P. Kundapur
Roles: Conceptualization, Data Curation, Methodology, Supervision, Validation, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS AWAITING PEER REVIEW

Abstract

Background

Given the significant global burden of hypertension and the perception of service quality significantly influences a patient’s satisfaction and their willingness to engage with mobile health (mHealth) interventions, this study aimed to develop and validate a Focus Group Discussion (FGD) guide to explore the self-management needs, preferences, and barriers of patients with hypertension for designing a contextually relevant mHealth application.

Methods

The FGD guide was developed via literature review and validated through a two-step process. First, face validity was assessed by a panel of five experts to evaluate flow, clarity, and comprehensiveness. Subsequently, content validity was quantified by a separate panel of ten experts using a structured assessment, with results analyzed via the Content Validity Index (CVI), Content Validity Ratio (CVR), and Kappa statistics. The guide was also pilot-tested with a small sample to refine clarity and depth before final use.

Results

Expert evaluations demonstrated high item-level content validity, with CVR and Kappa coefficient values ≥0.8 and ≥ 0.89, respectively. The S-CVI (universal agreement) indicated moderate content validity, while the S-CVI (average method) revealed high content validity. Feedback from both healthcare professionals and hypertensive patients resulted in improvements to wording, clarity, and contextual relevance, thereby enhancing the guide’s comprehensibility and cultural alignment.

Conclusion

This systematically developed FGD guide demonstrates moderate to high content validity and acceptable reliability. It is a suitable, validated tool for exploring patient-reported experiences in hypertension self-management to inform patient-centered mHealth interventions.

Keywords

Hypertension, High blood pressure, Content validity, mHealth, Self-management.

Corresponding authors: Sabu K Mandapam, Bhageerathy Reshmi, Raksha Kamath Competing interests: No competing interests were disclosed.

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

Copyright: © 2026 Salins PL et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Salins PL, Mandapam SK, Reshmi B et al. Development and Validation of a Needs Assessment Guide for mHealth-Based Self-Management among Patients with Hypertension [version 1; peer review: awaiting peer review]. F1000Research 2026, 15:1185 (https://doi.org/10.12688/f1000research.181812.1) First published: 17 Jul 2026, 15:1185 (https://doi.org/10.12688/f1000research.181812.1) Latest published: 17 Jul 2026, 15:1185 (https://doi.org/10.12688/f1000research.181812.1)

Introduction

Hypertension is a major non-communicable disease requiring long-term management, including medication adherence, lifestyle modification, and regular monitoring.¹^–⁴ In recent years, mobile health (mHealth) applications have emerged as supportive tools in hypertension care by enabling self-monitoring, reminders, personalized health information, and improved patient–provider communication.⁴^–⁶ These digital interventions show promise in supporting behaviour change and self-management among individuals with chronic conditions.⁷^,⁸

Understanding user needs, perceptions, and contextual challenges is essential for the effective development of mHealth applications.⁹ Qualitative research methods, particularly focus group discussions (FGDs), are well suited to elicit in-depth insights into users’ experiences and expectations. However, the quality and credibility of qualitative findings depend heavily on the rigor with which data collection tools are developed. Poorly constructed interview guides may compromise data richness, introduce researcher bias, and limit the applicability of findings.¹⁰^,¹¹

Validation of qualitative data collection instruments is therefore a critical methodological step. Qualitative rigor encompasses credibility, consistency, transparency, and appropriateness of the research process. Content validity specifically ensures that an instrument adequately represents the construct it is intended to explore and that the included items are relevant, clear, and comprehensive. Establishing content validity strengthens methodological rigor, enhances trustworthiness, and improves the interpretability of qualitative findings.¹⁰^,¹²

Content validity links abstract concepts with observable indicators and is widely used in the development of empirical research instruments.¹³^,¹⁴ Lawshe’s content validity approach is a well-recognized and systematic method for evaluating item relevance through expert judgment and has been applied across multiple research disciplines. Demonstrating content validity is particularly important in studies developing interview guides, as these tools form the foundation for data generation.¹⁵^–¹⁷

Despite increasing interest in mHealth-based hypertension management, there is a dearth in studies reporting the systematic development and content validation of qualitative tools used to inform app design, especially within the Indian context. To address this methodological gap, the present study aimed to develop and content-validate an FGD guide by incorporating structured feedback from hypertensive patients and healthcare professionals. This validated guide is intended to generate contextually relevant insights to inform the development of a customized mHealth application for hypertension management.

Methods

Ethics approval

This study was conducted in accordance with the principles of the Declaration of Helsinki. Ethical approval was obtained from the Institutional Ethics Committee of MAHE, Manipal on 8^th January 2022 (IEC:587/2021) and the study was registered prospectively under the clinical trial Registry of India on 31^st March 2022 (CTRI/2022/03/041544), prior to commencement of the study. The study commenced on 2^nd April 2022. Written informed consent was obtained from all expert prior to participation. Participation was voluntary, and experts were informed of their right to withdraw at any time without consequence.

Study design

The guide was developed through literature review, item generation, face validity assessment, expert content validation, and iterative refinement to understand the needs and expectations of hypertensive patients on self-management through mobile based applications. The process was conducted in four sequential steps.

Step 1: Literature search

Literature review on needs and expectations of hypertensive patients in using mHealth applications for self-management of their disease was done using the standard search engines. The Focus Group Discussion Guide was developed by synthesizing the information gathered through a comprehensive literature review, with the aim of aligning the content with the objectives and purpose of the study.²³^–²⁵

Step 2: FGD guide development

The FGD guide was separated into five components which had a welcome content and an introduction to the research objectives The questions were of three types -probe, follow up and exit. The probe had the questions which will help in making them feel them more comfortable and they will be able to share their opinion along with the group. Follow up, which will delve into the main discussion topics and will involve the opinion of the participants. And Exit, which includes the questions to ensure that the moderator did not miss anything in gathering the insights of the participants. Finally, the researcher’s conclusion aided in closing the discussion loop.

Step 3: Face validity

Face validity was assessed prior to the formal content validation process to ensure the clarity and appropriateness of items before expert rating. Five experts – Clinicians experienced in hypertension management, qualitative researchers, and digital health experts reviewed the guides for language, flow and contextual suitability. Feedback on structure, phrasing was received to align with the study’s aims. Minor revisions were made to enhance the clarity and to ensure relevance.

Step 4: Content validation and expert assessment

The content validation of the developed Focus Group Discussion (FGD) guide was conducted in two sequential phases: expert assessment and target population validation.

Expert assessment

A total of ten subject-matter experts were involved in evaluating the initial draft of the FGD guide. These experts included physicians from the Departments of General Medicine and Cardiology, as well as health information management professionals. Experts were selected based on their professional experience and familiarity with hypertension care and qualitative research. Each expert received a participant information sheet, an informed consent form, and an evaluation package containing the FGD guide and an expert evaluation form.

Experts were instructed to review each item in the guide and rate its appropriateness, clarity, comprehensibility, and essentiality. A three-point rating scale was used: 1 = Essential, 2 = Useful but not essential, and 3 = Not necessary. They were also invited to provide written comments and suggestions for improvement. Based on their feedback, redundant or unclear items were revised or removed, and the overall structure of the guide was refined for better alignment with the study objectives. To ensure linguistic and cultural accuracy, the guide was translated into Kannada (the local language) and back-translated into English for verification.

Step 5: Pilot Test: A pilot FGD was conducted using the same guidelines, setting, and participant criteria planned for the main study. This served to both train the moderator and test the appropriateness, clarity, and flow of the interview questions in relation to the study objectives.

A pilot session was held with five hypertension individuals who were selected purposively. The moderator followed the draft FGD guide, while a note-taker documented observations. The discussion lasted approximately 60 minutes and was audio-recorded.

Following the discussion, the recording was transcribed and preliminarily analysed using qualitative data analysis software to identify emerging themes and assess question effectiveness. The debrief between moderator and note-taker highlighted areas for improvement, particularly in the sequencing of questions and the need for additional probing prompts to elicit deeper responses on self-management barriers, their needs and requirement for mHealth application development.

Step 6: Refinement and finalization: Feedback from both healthcare professionals and hypertensive patients resulted in improvements to wording, clarity, and contextual relevance, thereby enhancing the guide’s comprehensibility and cultural alignment. The resulting draft included 19 items, carefully reviewed and finalized in consultation with the experts.

Statistical analysis

Content validity:

In content validity evaluations, quantitative analysis is utilized to ascertain how well things match or reflect a specific domain. This study employed empirical methods to calculate the content validity index and content validity ratio. The domain experts’ opinions were evaluated using the CVR, Kappa statistic, and CVI.

Assessment of content validity:

CV-Index:

The Content Validity Index (CVI) was used to assess the guide’s relevance. Item-level CVI (I-CVI) was calculated as the proportion of experts rating an item as essential. Items with I-CVI >0.79 were retained, those scoring 0.70–0.79 were revised, and those below 0.70 were removed. Scale-level CVI was evaluated using both S-CVI/Ave (average of all I-CVIs) and S-CVI/UA (proportion of items achieving unanimous expert agreement).¹⁸^,¹⁹

CV-Ratio:

To assess item essentiality, the Content Validity Ratio (CVR) was calculated. Experts rated each item as “essential,” “useful,” or “not necessary.” The CVR score, ranging from −1 to 1, was computed as: CVR = (Ne - N/2) / (N/2), where *Ne* is the number of experts rating the item as essential and “N” is the total number of experts. Higher scores indicate stronger expert consensus on the item’s necessity.¹⁸^,¹⁹

Kappa statistic coefficient:

To assess content validity beyond the Content Validity Index (CVI) and mitigate chance agreement, the Kappa coefficient was calculated for each item. For computing kappa statistics, probability of random agreement is determined first, or Pc = [N! /A! (N – A)!] × 0.5 N; N = number of panel experts, and A = the number of panel members agreeing that the item is important in this formula. Next, the kappa statistic was computed using the formula K = (I-CVI – Pc) / (1 – Pc). Kappa values were interpreted as excellent (>0.74), acceptable (0.60–0.74), or fair (0.40–0.59), ensuring that expert consensus was significantly above random agreement.²⁰

Results

The FGD guide was modified and refined as per the experts’ review comments. The developed FGD guide has been elaborated both in English and Kannada (Local language) in Supplementary Material 1: Appendix.

Face validity

Face validity was assessed by a panel of five experts to ensure that the developed guides were appropriate, comprehensible, and aligned with the study’s scope and objectives. The panel comprised clinicians, qualitative researchers, and digital health professionals who reviewed each item for clarity, relevance, and contextual appropriateness. Based on their feedback, minor modifications were made to improve phrasing, refine terminology, reorder select items, and enhance section instructions to better reflect a patient-centered approach.

Specifically, four questions were reworded, and the overall flow of the guide was modified to more effectively capture the challenges faced by both patients and healthcare professionals. Although face validity is inherently subjective, this step provided valuable insights into the guide’s usability and acceptability prior to undertaking formal content validity and reliability testing.

Content - validity

I-CVI (Pertinency of single/each item):

The results presented in Table 1 indicate that the items in the developed FGD guide were found to be highly relevant, with thirteen out of nineteen items receiving an I-CVI score of 1.00. Additionally, six items received a score of 0.9, suggesting that most of the items were perceived as necessary and useful by the evaluators.

Table 1. I- CVI values for each item in the questionnaire.ItemsExpert 1Expert 2Expert 3Expert 4Expert 5Expert 6Expert 7Expert 8Expert 9Expert 10No in agreement I-CVI Item 1xxxxxxxxxx101 Item 2 xxxxxxxxx90.9 Item 3xxxxxxxxxx101 Item 4xxxxxxxxxx101 Item 5xxx xxxxxx90.9 Item 6xxxxxxxxxx101 Item 7xxx xxxxxx90.9 Item 8xxx xxxxxx90.9 Item 9xxx xxxxxx90.9 Item 10xxxxxxxxxx101 Item 11xxxxxxxxxx101 Item 12xxxxxxxxxx101 Item 13xxxxxxxxxx101 Item 14xxxxxxxxxx101 Item 15xxxxxxxxxx101 Item 16xxxxxxxxxx101 Item 17xxxxxxxxxx101 Item 18xxxxxxxxxx101 Item 19xx xxxxxxx90.9

S-CVI (Pertinency of the whole guide):

The S-CVI/Ave, which represents the sum of all item-level content validity indices (17.8) by the total number of items in the scale,¹⁹ was calculated to be 0.93, indicating a high level of content validity. In contrast, the S-CVI/UA, which represents the sum of all ICVIs equal to 1.00¹³ by the total number of items,¹⁹ was calculated to be 0.68, suggesting a moderate level of content validity. Overall, the developed FGD Guide’s content validity is shown to be moderate based on the Universal Agreement technique and high via the Average approach.

CVR:

For every item, a CVR was generated. Non-essential items had a CVR value of less than 0.9. It is possible to remove non-essential components, however in this instance it was not. The content validity ratio scores ranged from 0.8⁶ to 1.00,¹³ with an average of 0.9. The CVR results for the focus group discussion interview guide are presented in Table 2.

Table 2. CVR values for each item in questionnaire.ItemsExpert 1Expert 2Expert 3Expert 4Expert 5Expert 6Expert 7Expert 8Expert 9Expert 10No in agreement CVR Item 1xxxxxxxxxx101 Item 2 xxxxxxxxx90.8 Item 3xxxxxxxxxx101 Item 4xxxxxxxxxx101 Item 5xxx xxxxxx90.8 Item 6xxxxxxxxxx101 Item 7xxx xxxxxx90.8 Item 8xxx xxxxxx90.8 Item 9xxx xxxxxx90.8 Item 10xxxxxxxxxx101 Item 11xxxxxxxxxx101 Item 12xxxxxxxxxx101 Item 13xxxxxxxxxx101 Item 14xxxxxxxxxx101 Item 15xxxxxxxxxx101 Item 16xxxxxxxxxx101 Item 17xxxxxxxxxx101 Item 18xxxxxxxxxx101 Item 19xx xxxxxxx90.8

Kappa coefficient

All 19 items were considered to have excellent kappa statistics. In which, thirteen of the items are score of 1.00, and six of the items score is 0.899. Kappa calculations are shown in Table 3.

Table 3. Kappa statistics for each item in the questionnaire. Items Expert 1 Expert 2 Expert 3 Expert 4 Expert 5 Expert 6 Expert 7 Expert 8 Expert 9 Expert 10 No in agreement Pc Kappa statistics Item 1xxxxxxxxxx100.0009771 Item 2 xxxxxxxxx90.0097660.899014 Item 3xxxxxxxxxx100.0009771 Item 4xxxxxxxxxx100.0009771 Item 5xxx xxxxxx90.0097660.899014 Item 6xxxxxxxxxx100.0009771 Item 7xxx xxxxxx90.0097660.899014 Item 8xxx xxxxxx90.0097660.899014 Item 9xxx xxxxxx90.0097660.899014 Item 10xxxxxxxxxx100.0009771 Item 11xxxxxxxxxx100.0009771 Item 12xxxxxxxxxx100.0009771 Item 13xxxxxxxxxx100.0009771 Item 14xxxxxxxxxx100.0009771 Item 15xxxxxxxxxx100.0009771 Item 16xxxxxxxxxx100.0009771 Item 17xxxxxxxxxx100.0009771 Item 18xxxxxxxxxx100.0009771 Item 19xx xxxxxxx90.0097660.899014

Pilot study

A pilot FGD was conducted one month prior to the main data collection to assess the clarity, structure, and feasibility of the interview guide. The pilot was carried out at the Rural Maternity and Child Welfare (RMCW) a Community Health Center, Manipal, and involved five participants. The session lasted approximately 1.5–2 hours. Prior to the pilot, the researcher refined the structure of the guide and rephrased selected questions to improve clarity and flow. During the pilot, participants’ responses to each topic were reviewed to identify issues related to question comprehension, sequencing, and relevance. Commonly used phrases and recurring expressions were noted, which informed the development of additional probes and minor refinements to the guide. Feedback from the pilot study, along with expert comments, was incorporated to finalize the interview guide.

Discussion

Qualitative research will help in understanding human experience and meaning within a given context text rather than using numbers. Interpreting experiences, requirement’s, needs, expectations, and meaning to generate the understanding. The major question which comes about qualitative research is the quality, appropriateness, and reliability to the objectives.

This guide has been designed and validated to interview hypertensive patients, aiming to understand their needs and expectations for inclusion in customized mHealth applications. It is developed after identifying the specific requirements of patients managing this chronic condition. Extensive literature reviews have shown that various mHealth applications support the self-management of chronic illnesses. However, including feedback from hypertensive patients and medical professionals can improve customisation, making the app simpler to use as well as it will be aligned with patient’s needs.²¹

The developed FGD guide was divided into three elements: probe, follow up and exit questions, along with welcome remark, and conclusion. These semi – structured interview guides are important because they set an agenda, provide appropriate probes and prompts of what needs to be covered and ensure what was planned to be extracted is fulfilled along with the added information shared by the participants. The questions finalized in this guide were sufficient for obtaining the insights from the hypertensive individuals. It concluded that the FGD guide had relevance for future users and participants, including clinical, experiential, and research professionals.

Furthermore, the experts’ comments and suggestions enhanced the significance, clarity, and appropriateness, of the developed FGD guide. Following the recommendations of the expert panels, modifications were done, to get more clarity information from the targeted population. In addition to expert validation, pilot testing enabled minor refinements to the guide, enhancing its clarity and usability in the study context. Overall results indicated moderate to high levels of content validity for the entire guide. I- CVI, S-CVI, kappa coefficient was employed to ascertain how well things match or reflect a specific domain.

By calculating CVR, I-CVI, and S-CVI/UA, kappa coefficient from the responses of ten subject experts, the current study provides a more comprehensive picture than when content validity is calculated using just one method.²² Expert ratings were conducted using a CVR threshold of 0.75 in the Lawshe Table to determine which items represented the domain.¹⁶

The created FGD guide’s content validity evaluation showed high relevance and consistency. With 13 out of 19 items obtaining a perfect score of 1.00 and the other six scoring 0.9, the I-CVI results showed that the majority of the items were extremely important. Using the universal agreement approach, the S-CVI/UA (0.68) indicated a moderate level of content validity, whereas the S-CVI/Ave (0.93) validated a high overall level. The items’ vital nature was confirmed by the CVR ratings, which varied from 0.8 to 1.00 with an average of 0.9. Furthermore, the kappa coefficient values showed great agreement, confirming the guide’s validity. These results imply that the FGD guide is a useful instrument for investigating variables associated with patient -perspective insights in developing a customized mHealth application.

By incorporating both face and content validity, the guide has been rigorously developed and strengthened for use in future research. However, further studies are needed to test the guide across diverse populations and to enhance the assessment of procedural knowledge.

Limitations

However, there are certain drawbacks to this study:

- Limited generalizability in other circumstances.

The study does not develop a new validation framework; instead, it methodically utilizes well-established content validation techniques.

- Potential bias in the selection of experts and cultural subjectivity in their assessments.
- Ten individuals made up the expert panel, which is within the suggested boundaries for content validation but may have limited the range of viewpoints and impacted the stability of agreement indices. Furthermore, judgments about item retention may be impacted by differences in the chosen I-CVI threshold values (e.g., ≥0.78 vs. ≥0.85).
- The goal of the study was to improve qualitative rigor through content validation rather than to determine the psychometric qualities of a quantitative tool.

Future studies involving larger and more diverse expert panels are recommended to enhance the robustness and generalizability of these findings.

Conclusion

This study developed and content-validated a FGD guide to explore hypertension patients’ preferences and requirements for self-management through applications. The guide was designed to capture key self-care domains relevant to personalized mHealth solutions, including medication use, blood pressure self-monitoring, diet (DASH), physical activity, weight management, stress reduction, and health education related to smoking and alcohol use.

Content validity was assessed using expert review. The guide demonstrated moderate to high overall content validity (S-CVI/UA = 0.68; S-CVI/Ave = 0.93) and high item-level validity across all components (I-CVI range: 0.90–1.00). Ten healthcare experts participated in content validation, and five experts assessed face validity, ensuring methodological rigor and practical relevance.

The validated FGD guide provides a robust qualitative instrument to generate patient-centered inputs for the development of contextually appropriate mHealth applications for hypertension self-management. Further evaluation of reliability and additional validity measures is recommended. This methodological study was undertaken as a component of a larger randomized controlled trial (RCT).

Data availability

Underlying data

The dataset supporting the findings of the study are available at Salins, Prajwal (2026). Extended Data: Development and Validation of an FGD Guide guide for Hypertension Self-Management. figshare. Figure. https://doi.org/10.6084/m9.figshare.32182389.v1.²⁶

The dataset includes:

• Anonymized expert ratings for each item of the FGD guide, item-level validity scores (I-CVI), scale-level content validity index (S-CVI), modified Kappa statistics.
• Expert demographic characteristics (designation and years of experience). All data necessary to replicate the findings of this study are provided under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license.
• Extended data including the FGD guide, participant information sheet, and consent forms.
• Expert identities have been anonymized to ensure confidentiality.
• The FGD guide has been copyrighted under Copyright office Government of India, Registration Number: L-163262/2025, Title: EVALUATION OF HYPERTENSIVE PATIENT REQUIREMENTS FOR DEVELOPING MHEALTH APPLICATION: A FOCUS GROUP DISCUSSION GUIDE (EHPMHEALTH-FGD).

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© 2026 Salins PL et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions

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VERSION 1 PUBLISHED 17 Jul 2026

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Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

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Development and Validation of a Needs Assessment Guide for mHealth-Based Self-Management among Patients with Hypertension [version 1; peer review: awaiting peer review]

Дата публикации: 17-07-2026 16:32:27

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