Abstract:
Background: Diabetes is a chronic disease that requires constant monitoring of blood glucose levels. However, in developing nations, most patients with diabetes fail to manage this disease. This is chiefly because the prevailing traditional methods involve infrequent hospital visits and the use of glucometers, spreadsheets, and logbooks. This is a tedious and inaccurate process that lacks real-time decision-making. Thus, most patients fail to be actively involved in the management of the disease, leading to serious complications. Quantified self-technology (QST), which uses wearable devices and mobile applications to monitor physiological parameters, offers an interactive, integrated solution for managing diabetes. However, owing to a lack of expertise, sociocultural challenges, and insufficient tailored theoretical frameworks, the adoption of QST is minimal in developing nations.
Objective: The main objective of this study was to propose a framework for adopting quantified self-technology for managing diabetes in developing countries.
Methodology: To understand QST, a systematic literature review identified the components of the QST framework. Resultantly, a conceptual framework was developed, which served as a guide in designing the research instruments for data collection. Thus, this study employed a single, embedded case study design and face-to-face interviews for data gathering. An interpretivist paradigm was used to interview 35 patients with diabetes from a hospital in Bulawayo, who were purposively and self-selected. Braun and Clarke's thematic analysis, facilitated by ATLAS.ti software, was used to improve methodological rigour.
Results: The six core drivers and inhibitors of QST adoption among diabetics were identified as user characteristics, technology preparedness, perceived benefits, usability, social norms, and cybersecurity risks. Key user characteristics include digital literacy, self-efficacy, and awareness. Technological preparedness depends on cost, access to resources, training, and lowering technology anxieties. Over 70% of participants had a tertiary education, yet 69% were unaware of QST before the study. Participants perceived usability to be determined by usefulness, ease of use, and enjoyment. Furthermore, social norms can encourage or discourage adoption, depending on the views of the family and social surroundings. Cybersecurity risks may include privacy breaches, financial losses, and the misuse of information. Conclusion: This study proposes a framework for adopting QST to enhance diabetes self-care in developing countries. With the help of QST, patients can prevent acute complications, reduce hospital admissions, and be proactive in managing diabetes. The cybersecurity risks identified must be addressed to build trust and unlock QST benefits, including improved monitoring, adherence, motivation, data sharing, and cost savings. Thus, national health strategies should integrate QST into preventive care policies, as it will aid in monitoring, patient empowerment, and personalised treatment. However, the findings should be interpreted within the context of the study’s limitations, including self-selection bias, the single-hospital setting, and the focus on one QST application.
Contributions: This research contributes to the field of health informatics theoretically. This is achieved through, first, offering a new conceptual framework for the adoption of QST within a developing country context and, secondly, identifying two new determinants, namely training and technology anxiety, and demonstrating the contextual operationalisation of digital literacy and motivation in a developing-country diabetes-management context. It also highlights the importance of explicitly recognising perceived benefits in adoption theory, demonstrating that understanding value is essential before introducing new technologies among patients. Practically, the framework provides actionable guidance for designing low-cost, user-friendly QST interventions suited to resource-constrained settings. Lastly, the framework is particularly valuable to healthcare providers, developers, and policymakers who seek to improve diabetes management through innovative self-monitoring solutions.
