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11 reviewsSmoking cessation is the only evidence-based approach to reducing tobacco-related health risks, yet traditional interventions sufer from limited coverage. Although digital interventions show promise, their comparative efcacy across methodological frameworks and technology types remains unclear. Here we assessed digital interventions versus standard care via frequentist random-efects network meta-analysis of 152 randomized controlled trials (48.8% USA, 7.5% China). Interventions were categorized by methodology and technology type, with cross-matched subgroup analyses. Results showed that personalized interventions signifcantly improved smoking cessation rates compared with standard care (relative risk (RR) 1.86, 95% confdence interval (CI) 1.54–2.24), while group-customized interventions were more efective (RR 1.93, 95% CI 1.30–2.86) compared with standard digital interventions (RR 1.50, 95% CI 1.31–1.72). Among the various technology types, text message-based interventions were the most efective (RR 1.63, 95% CI 1.38–1.92). Intervention efectiveness was also infuenced by age, with middle-aged individuals beneftting more than younger individuals. Short- and medium-term interventions were more efective than long-term interventions. Sensitivity analyses further confrmed these low-to-moderate fndings. However, this study has some limitations, including methodological heterogeneity, potential bias and inconsistent defnitions of numerical interventions. In addition, long-term follow-up data remain limited. Future studies require large-scale trials to assess long-term sustainability and population-specifc responses, as well as standardization of methods and integration of data at the individual level.