Kgasi Mmamolefe, Chimbo Bester, Motsi Lovemore
Faculty of ICT, Tshwane University of Technology, Pretoria, South Africa.
School of Computing, University of South Africa, Johannesburg, South Africa.
JMIR Form Res. 2023 Oct 23;7:e49407. doi: 10.2196/49407.
The COVID-19 pandemic has led to serious challenges and emphasized the importance of using technology for health care operational transformation. Consequently, the need for technological innovations has increased, thus empowering patients with chronic conditions to tighten their adherence to medical prescriptions.
This study aimed to develop a model for a mobile health (mHealth) self-monitoring system for patients with diabetes in rural communities within resource-limited countries. The developed model could be based on the implementation of a system for the self-monitoring of patients with diabetes to increase medical adherence.
This study followed a quantitative approach, in which data were collected from health care providers using a questionnaire with close-ended questions. Data were collected from district hospitals in 3 South African provinces that were selected based on the prevalence rates of diabetes and the number of patients with diabetes treated. The collected data were analyzed using smart partial least squares to validate the model and test the suggested hypotheses.
Using variance-based structural equation modeling that leverages smart partial least squares, the analysis indicated that environmental factors significantly influence all the independent constructs that inform patients' change of behavior toward the use of mHealth for self-monitoring of medication adherence. Technology characteristics such as effort expectancy, self-efficacy, and performance expectancy were equally significant; hence, their hypotheses were accepted. In contrast, the contributions of culture and social aspects were found to be insignificant, and their hypotheses were rejected. In addition, an analysis was conducted to determine the interaction effects of the moderating variables on the independent constructs. The results indicated that with the exception of cultural and social influences, there were significant interacting effects on other independent constructs influencing mHealth use for self-monitoring.
On the basis of the findings of this study, we conclude that behavioral changes are essential for the self-monitoring of chronic diseases. Therefore, it is important to enhance those effects that stimulate the behavior to change toward the use of mHealth for self-monitoring. Motivational aspects were also found to be highly significant as they triggered changes in behavior. The developed model can be used to extend the research on the self-monitoring of patients with chronic conditions. Moreover, the model will be used as a basic architecture for the implementation of fully fledged systems for self-monitoring of patients with diabetes.
新冠疫情带来了严峻挑战，凸显了利用技术推动医疗保健运营变革的重要性。因此，对技术创新的需求增加，从而使慢性病患者能够更严格地遵守医嘱。
本研究旨在为资源有限国家农村社区的糖尿病患者开发一种移动健康（mHealth）自我监测系统模型。所开发的模型可基于实施糖尿病患者自我监测系统以提高医疗依从性。
本研究采用定量方法，通过一份具有封闭式问题的问卷从医疗保健提供者处收集数据。数据收集自南非3个省份的地区医院，这些省份是根据糖尿病患病率和接受治疗的糖尿病患者数量选定的。使用智能偏最小二乘法对收集到的数据进行分析，以验证模型并检验所提出的假设。
通过利用智能偏最小二乘法的基于方差的结构方程建模分析表明，环境因素显著影响所有独立构建因素，这些因素促使患者改变行为，采用移动健康进行药物依从性自我监测。努力期望、自我效能和绩效期望等技术特征同样显著，因此其假设被接受。相比之下，文化和社会方面的贡献被发现不显著，其假设被拒绝。此外，还进行了一项分析以确定调节变量对独立构建因素的交互作用。结果表明，除了文化和社会影响外，对其他影响移动健康用于自我监测的独立构建因素存在显著的交互作用。
基于本研究的结果，我们得出结论，行为改变对于慢性病的自我监测至关重要。因此，增强那些促使行为向使用移动健康进行自我监测转变的影响因素非常重要。还发现动机方面非常重要，因为它们引发了行为变化。所开发的模型可用于扩展慢性病患者自我监测的研究。此外，该模型将用作实施糖尿病患者全面自我监测系统的基本架构。
