BACKGROUND
This study furnishes a theoretical framework designed to systematize the existing body of research, revealing that the sustained integration of mHealth technology across a duration exceeding three months correlates with considerable enhancements in the physiological condition of patients afflicted by chronic diseases.
OBJECTIVE
The objective of this study is to examine the effectiveness of mobile health technology in enhancing the physiological state of patients with chronic diseases, including conditions such as blood pressure, blood sugar, blood lipids, and obesity. Furthermore, it aims to explore the influence of artificial intelligence on self-efficacy, self-care behaviors, and their subsequent impact on quality of life and treatment adherence.
METHODS
A systematic search was conducted on various databases, including PubMed, Science Direct, Scopus, Web of Science, and IEEE Xplore, up until 20th October 2022, with a search date of 21st October 2022. The search focused on identifying meta-analyses of randomized controlled trials that compared the effects of mobile health technology interventions on self-efficacy, quality of life, behavioral motivation, weight, body fat, blood pressure, and HbA1c in patients with chronic diseases. The experimental group (EG) received health technology interventions, while the control group (CG) received routine interventions, including home phone calls. Two independent reviewers screened potential eligible trials, extracted and categorized data using standardized forms, and resolved discrepancies through discussions with a third reviewer.
RESULTS
A total of 930 articles were retrieved through the search strategy, indicating the practicality and benefits of health technology-based interventions for chronic diseases. However, further research is necessary to gain a comprehensive understanding of their potential for long-term management. Due to limitations in the available research, this study focused solely on self-efficacy, quality of life, behavioral motivation, body weight, body fat, blood pressure, and HbA1c. Future investigations should prioritize assessing the impact and compliance of patients with chronic diseases following mobile health technology interventions.
CONCLUSIONS
The evidence obtained from this study suggests that mobile health technology interventions can significantly enhance outcomes for individuals with chronic diseases. The integration of artificial intelligence into mobile health technology has the potential to augment self-efficacy, self-care behaviors, and treatment adherence, ultimately leading to improved patient outcomes.