A contextualized model for a persuasive technology mobile health self-monitoring system for diabetic patients in South African communities

Abstract

Self-care for health is essential as a way to reduce the health inequality gap that manifests itself in a variety of ways. These include the lack of access to medical and food resources and other unmet daily needs. In particular, in less privileged communities the lack of alignment between innovative health-related technologies and disease burdens, as well as a lack of adequate service, contribute to inadequate monitoring of chronically ill patients. Chronic diseases cause a high number of deaths and place a considerable strain on the health systems of many countries, especially developing ones. Patients suffering from chronic conditions become traumatised as they live with an incurable ailment, and this negatively affects their adherence to medical regimes, with serious consequences. This study sought to develop a contextualized model for use by the persuasive technology mHealth self-monitoring (mHealthSM) system for patients with diabetes in South African communities. The model informed the architecture of the artifact (the mHealthSM system) intended to be used as a reminder for diabetic patients to take their medicine. The study followed a positivist paradigm incorporating the quantitative approach and Design Science Research. Data were collected from district hospitals in three provinces of South Africa, namely Gauteng, KwaZulu Natal and Mpumalanga. The model was validated using Smart-PLS and the mHealthSM system artifact was based on this model, and was developed and evaluated. The results indicated that environmental aspects significantly influenced all the strategies used to inform patients about the necessary changes of behaviour for medical adherence. Furthermore, characteristics of the associated technology, such as effort expectancy and performance expectancy, played a significant role in influencing the change of behaviour of patients. However, social aspects, culture and individual characteristics due to skills were found not to be significant. Furthermore, the artifact evaluation indicated that it is reliable, highly valid and performs as expected. Theoretically, this study contributes to the development of a contextualized model that incorporates the interacting effects of the moderating factors to inform the medical adherence by patients. Furthermore, the study contributes to the management and practice of healthcare personnel, as they would leverage the developed model and artifact developed to inform their monitoring of chronically ill patients. Methodologically, the study combined three aspects namely, an analysis of moderating factors, the combination of the quantitative and Design Science approaches to develop both the model and the artifact, and lastly the validation of the model and the evaluation of the artifact into a single study. This study recommends that future research should work jointly with healthcare personnel to enable the collection of data from patients rather than from healthcare workers only. The study also recommends deployment of the developed mHealthSM to the cloud to increase its stability, scalability and data storage.