A Quantitative Report on Type 2 Diabetes Care in Port Harcourt: Insights into Socio-demographic Influences and Opportunities for Digital Health Promotion (Preprint)

Background A significant percentage of the Nigerian population has type 2 diabetes (T2D), and a notable portion of these patients also live with comorbidities. Despite its increasing prevalence in Nigeria due to factors such as poor eating and exercise habits, there are insufficient reliable data on its incidence in major cities such as Port Harcourt, as well as on the influence of sociodemographic factors on current self-care and collaborative T2D care approaches using technology. This, coupled with a significant lack of context-specific digital health interventions for T2D care, is our major motivation for the study. Objective This study aims to (1) explore the sociodemographic profile of people with T2D and understand how it directly influences their care; (2) generate an accurate understanding of collaborative care practices, with a focus on nuances in the contextual provision of T2D care; and (3) identify opportunities for improving the adoption of digital health technologies based on the current understanding of technology use and T2D care. Methods We designed questionnaires aligned with the study’s objectives to obtain quantitative data, using both WhatsApp (Meta Platforms, Inc) and in-person interactions. A social media campaign aimed at reaching a hard-to-reach audience facilitated questionnaire delivery via WhatsApp, also allowing us to explore its feasibility as a data collection tool. In parallel, we distributed surveys in person. We collected 110 responses in total: 83 (75.5%) from in-person distributions and 27 (24.5%) from the WhatsApp approach. Data analysis was conducted using descriptive and inferential statistical methods on SPSS Premium (version 29; IBM Corp) and JASP (version 0.16.4; University of Amsterdam) software. This dual approach ensured comprehensive data collection and analysis for our study. Results Results were categorized into 3 groups to address our research objectives. We found that men with T2D were significantly older (mean 61 y), had higher household incomes, and generally held higher academic degrees compared to women (P=.03). No statistically significant relationship was found between gender and the frequency of hospital visits (P=.60) or pharmacy visits (P=.48), and cultural differences did not influence disease incidence. Regarding management approaches, 75.5% (83/110) relied on prescribed medications; 60% (66/110) on dietary modifications; and 35.5% (39/110) and 20% (22/110) on traditional medicines and spirituality, respectively. Most participants (82/110, 74.5%) were unfamiliar with diabetes care technologies, and 89.2% (98/110) of those using technology were only familiar with glucometers. Finally, participants preferred seeking health information in person (96/110, 87.3%) over digital means. Conclusions By identifying the influence of sociodemographic factors on diabetes care and health or information seeking behaviors, we were able to identify context-specific opportunities for enhancing the adoption of digital health technologies.