Effectiveness of mobile health intervention in medication adherence: A systematic review and meta-analysis

Abstract

Abstract Background: Low medication adherence is known to pose a great risk of poor treatment outcomes among patients with chronic diseases. Recently, mobile applications (apps) have been recognized as effective interventions, enabling patients to adhere to their prescriptions. This study aimed to establish the effectiveness of mobile app interventions for medication adherence and the affecting features and dropout rates by focusing on randomized controlled trials (RCTs). Method: This study conducted a systematic review and meta-analysis of mobile app interventions targeting medication adherence in patients with chronic diseases. Electronic searches of eight databases were conducted on April 21, 2023. Comprehensive meta-analysis (CMA) software was used to estimate the standardized mean difference (SMD) of pooled outcomes, odds ratios (ORs), and confidence intervals (CIs). Subgroup analysis was applied to investigate and compare the effectiveness of the interventional strategies and their features. The risk of bias of the included RCTs was evaluated by applying the risk of bias (ROB) tool. Publication bias was also examined using the fail-safe N method. Results: Twenty-nine studies with 2,684 participants were included. The meta-analysis findings showed a positive impact of mobile apps on improving medication adherence (SMD = 0.386, OR = 2.34). The subgroup analysis results revealed greater effectiveness of interventions using interactive strategies (SMD=1.367, OR=2.678), context-aware reminders (SMD = 0.664, OR = 2.452), data-sharing (SMD = 0.321, OR = 2.449), and pill dispenser (OR = 2.436). Conclusion: The current study found that mobile interventions had significant effects on medication adherence improvement. Subgroup analysis showed that the roles of stakeholders in health providers’ interactions with patients and developers’ understanding of patients and disease characteristics are critical. Future studies should incorporate advanced technology reflecting acceptability and the needs of the target population.