Effectiveness of Mobile Health for Improving Medication Adherence in Patients With Cancer: Systematic Review and Meta-Analysis of Randomized Controlled Trials

移动医疗在提高癌症患者用药依从性方面的有效性:随机对照试验的系统评价和荟萃分析

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Abstract

BACKGROUND: Medication adherence among patients with cancer is generally low. Mobile health (mHealth) has gradually been applied to improve this situation, but systematic evidence of its effectiveness remains lacking. OBJECTIVE: We aimed to evaluate the effect of mHealth on improving medication adherence among patients with cancer. METHODS: This systematic review included randomized controlled trials (RCTs) evaluating the impact of mHealth on medication adherence among patients with cancer. Systematic searches were conducted in PubMed, Web of Science, CINAHL, Cochrane Library, Embase, Sinomed, CNKI, Cqvip, and ClinicalTrials.gov from inception to December 31, 2025. Two researchers independently performed literature screening, data extraction, and risk of bias assessment. Effects were pooled using a random-effects model (Hartung-Knapp-Sidik-Jonkman), and standardized mean differences (SMDs) and odds ratios (ORs) with 95% CIs have been reported. Evidence quality was assessed using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) framework. RESULTS: A total of 17 RCTs (1309 participants) from 8 countries published between 2016 and 2025 were included. mHealth interventions included mobile apps, websites, and text messaging services. The meta-analysis revealed that compared with controls, mHealth interventions significantly improved medication adherence rates (OR 3.47, 95% CI 1.92-6.26; P=.002), medication adherence scores (SMD 1.01, 95% CI 0.51-1.52; P=.001), self-efficacy (SMD 0.90, 95% CI 0.29-1.51; P=.01), and service satisfaction while reducing symptom burden (SMD -0.38, 95% CI -0.61 to -0.14; P=.008). However, mHealth had no significant effect on health literacy (SMD 0.51, 95% CI -1.50 to 2.52; P=.29). Subgroup analysis revealed that interventions lasting <3 months outperformed those lasting ≥3 months in improving adherence scores (SMD 1.37, 95% CI 0.78-1.96 vs SMD 0.49, 95% CI -0.39 to 1.37; χ²1=5.98; P=.01). Regarding intervention format, text messaging services demonstrated superior efficacy compared with mobile apps and websites (SMD 1.53, 95% CI -5.49 to 8.55 vs SMD 1.01, 95% CI 0.42-1.61 and SMD 0.11, 95% CI -0.34 to 0.56, respectively; χ²2=10.28; P=.006). Across cancer types, mHealth most significantly improved adherence scores in patients with breast cancer (SMD 1.29, 95% CI -5.25 to 7.83), outperforming the findings in patients with leukemia and other cancer types (SMD 0.28, 95% CI -0.87 to 1.42 and SMD 1.09, 95% CI 0.10-2.08, respectively; χ²2=8.86; P=.01). CONCLUSIONS: Our findings confirm that mHealth plays a positive role in improving medication adherence, enhancing patient self-efficacy, increasing patient satisfaction with services, and alleviating symptom burden. However, these findings should be interpreted with caution owing to substantial heterogeneity, a moderate risk of bias, and a low certainty of evidence. Future research should enhance methodological quality by conducting multicenter, large-sample, high-quality RCTs and should explore the long-term effects and cost-effectiveness of mHealth across diverse health care settings and patient populations to clarify its role and value within comprehensive cancer care management systems.

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