Developing a mobile application for promoting periodontal health and metabolic control in diabetic patients: testing and feasibility study
Diabetes mellitus and periodontal disease are highly prevalent chronic conditions globally, with a well-established bidirectional relationship. Diabetes negatively affects periodontal health, while severe periodontal disease can worsen glycaemic control. Effective management of both conditions is essential to improving overall health outcomes. Mobile health (mHealth) technologies are increasingly recognised for their potential in chronic disease management, yet their effectiveness in periodontal health management remains underexplored. This feasibility study aims to investigate Diabetes Dental Care (DiaDent Care) mobile application's potential to improve periodontal health and metabolic control in diabetic patients. This study was conducted in three phases. First, a systematic review and meta-analysis synthesised evidence from randomised controlled trials (RCTs) on the effectiveness of mobile health (mHealth) interventions in improving periodontal health outcomes, including gingival index (GI), bleeding index (BI), probing pocket depth (PPD), and clinical attachment level (CAL). In the second phase, findings from the systematic review informed the development of the DiaDent Care mobile application, designed to enhance diabetes-periodontal selfmanagement. A user-centred design approach was employed to create an interactive platform integrating educational content, oral hygiene reminders, self-monitoring tools, and motivational features. Usability testing ensured the application’s functionality, accessibility, and engagement strategies aligned with user needs. The third phase involved a three-month feasibility study assessing DiaDent Care’s usability, adherence, and preliminary clinical impact among diabetic patients with periodontal disease. Baseline and follow-up assessments measured periodontal health (Basic Periodontal Examination, BPE) and metabolic control (HbA1c levels). Descriptive and inferential statistical analyses, including Spearman correlation and multivariate multiple regression models, evaluated engagement trends and clinical outcomes
mHealth, Mobile application, Diabetes mellitus, Periodontal health, Metabolic control
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