Abstract / Summary
Background: Given the significant global burden of hypertension and the need to understand patients’ self-management needs, preferences, and barriers when developing mobile health (mHealth) interventions, this study aimed to develop and validate a Focus Group Discussion (FGD) guide to these aspects for designing a contextually relevant mHealth application. Methods The FGD guide was developed through a six-step systematic process, including literature review and domain identification, development of the initial FGD guide, face-validity assessment, expert content validation, translation and cultural/linguistic adaptation, and pilot testing with final refinement. Face validity was assessed by five experts to evaluate the flow, clarity, and comprehensibility of the guide. Content validity was assessed by a separate panel of ten experts using a structured three-point rating scale, with findings analyzed using the Content Validity Index (CVI), Content Validity Ratio (CVR), and modified Kappa. The guide was pilot-tested with five individuals with hypertension to further assess its clarity, sequencing, and feasibility and to inform final refinement. Results Expert evaluations demonstrated high item-level content validity, with I-CVI values ranging from 0.90 to 1.00. The S-CVI/Ave was 0.97, while the S-CVI/UA was 0.68. CVR values ranged from 0.80 to 1.00, with all 19 questions meeting the prespecified criterion for retention. Modified Kappa values ranged from 0.899 to 1.00, indicating high chance-adjusted expert agreement. Feedback from healthcare professionals and individuals with hypertension supported refinement of the guide’s wording, clarity, and contextual relevance. Conclusion This systematically developed FGD guide demonstrated high item-level and average content validity, with high chance-adjusted expert agreement among the participating experts. The guide provides a content-validated qualitative data-collection guide for exploring patient perspectives on hypertension self-management and informing the development of patient-centered mHealth interventions. Further evaluation in larger and more diverse populations and settings is needed.