Principal Findings
hypertension
HYPERTENSION
This study assesses the short-term efficacy of an mHealth app–based intervention to support patient self-management of hypertension in a lower-income region with a high-salt diet in China. We compared the efficacy of an mHealth app–based intervention with that of usual care in supporting patient self-management of hypertension through a 6-month randomized controlled trial with 226 participants. There were no significant differences in demographic characteristics and medication use between the 2 groups of participants. Hence, the significant differences in evaluation outcomes between the 2 groups might be attributed to the efficacy of the mHealth intervention.Participants in both groups showed a significant reduction in SBP and DBP at 6 months compared to those at baseline. This suggests that traditional treatment methods can effectively help patients to control their BP [It is noteworthy that the control group also experienced a significant improvement in BP outcomes. Three possible reasons can be posited to elucidate this occurrence. First, the research itself may have engendered a placebo effect to some degree. Despite the absence of an mHealth intervention for the control group participants, their BP outcomes might have been inadvertently affected. Second, it is possible that participation in the study heightened their cognizance and emphasis on BP control. Lastly, it is conceivable that some participants in the control group acquired a more sophisticated comprehension of BP management during subsequent clinical visits. Further research is required to control for potential confounding factors to more accurately ascertain the specific effects of the mHealth intervention.We observed no significant differences in baseline weight between the 2 groups at baseline and after the intervention. However, a significant weight change was observed within the intervention group on comparing pre- and postintervention measures. This alteration could potentially be attributed to the implementation of the app, such as educational material and reminders about diet modifications and physical activities. While the control group did not receive the same intervention via electronic means, they were provided with traditional self-management training, suggesting that traditional management remains effective, with mHealth further enhancing responsiveness and efficiency. The weight change observed in the intervention group might be attributed to the use of the mHealth app. Nevertheless, it remains inconclusive whether the intervention exerted a uniform effect on all participants, implying that interindividual variability could have impacted the overall weight change in this group. The observed results might also be subject to random factors, thus necessitating further studies to determine the generalizability of these findings.Patients’ awareness of all 8 aspects of hypertension knowledge in the intervention group has significantly improved during both pre-post and intergroup comparisons after the trial. This confirms the efficacy of the mHealth intervention in providing health education to patients [Self-reported management behaviors with regard to diet, physical activity, and medication adherence in the intervention group significantly improved 6 months after the intervention compared to those at baseline. However, there was no significant change in cigarette smoking and alcohol consumption, reflecting the considerable challenge of giving up addictive substances [Nonetheless, there are potential problems associated with the use of such an app. If many patients use the app, health care providers may be overwhelmed by the workload of manually reviewing and responding to patient data. One solution might be to develop automated processes for data analysis. Thus, follow-up studies could consider using artificial intelligence technologies, such as chatbots and predictive algorithms, to address this issue. Examples include answering frequently asked questions and providing general information to patient users, thus reducing the need for health care providers to respond to such inquiries, and monitoring a patient’s progress over time, identifying potential health issues and allowing health care providers to focus on higher-priority cases. However, it is worth noting that these technologies are still under development and should be validated before being used in clinical practice. Health care providers should validate the predictions made by these algorithms to ensure patient safety.