{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T12:01:03Z","timestamp":1785326463112,"version":"3.55.0"},"reference-count":47,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T00:00:00Z","timestamp":1785283200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted to comprehensively assess the impact of mobile health (mHealth) application interventions on glycolipid metabolism and quality of life among patients with type 2 diabetes mellitus (T2DM).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A comprehensive search was conducted across major English- and Chinese-language electronic databases, including PubMed, Embase, the Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Data, VIP, and the Chinese Biomedical Literature Database, using a combination of MeSH terms and free words. The search period extended from the inception of each database to 12 March 2026. RCTs evaluating mHealth application interventions for T2DM were included. The risk of bias was assessed using the Cochrane risk of bias tool. Statistical analyses and heterogeneity tests were performed using Review Manager 5.4 and Stata 18.0. The primary outcome was glycated hemoglobin. The secondary outcomes included fasting blood glucose (FBG), 2-h postprandial blood glucose (2hPBG), total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), quality of life, and diabetes distress.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 19 RCTs comprising 2,166 participants were included. The meta-analysis showed that, compared to control interventions, mHealth application-based management significantly reduced HbA1c [MD\u202f=\u202f\u22120.39, 95%CI: \u22120.49, \u22120.30], FBG [MD\u202f=\u202f\u22120.68, 95%CI: \u22120.89, \u22120.46], 2hPBG [MD\u202f=\u202f\u22121.46, 95%CI: \u22121.90, \u22121.02], and TC levels [MD\u202f=\u202f-0.21, 95%CI: \u22120.38, \u22120.05]. The intervention also improved quality of life [SMD\u202f=\u202f0.24, 95%CI: 0.02, 0.47] and reduced diabetes distress [SMD\u202f=\u202f\u22120.22, 95%CI: \u22120.38, \u22120.05]. However, no statistically significant differences were observed between the groups regarding TG, HDL-C, or LDL-C levels.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>mHealth applications positively influence glucose metabolism and quality of life in patients with T2DM; however, their effects on lipid metabolism require further investigation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Systematic review registration<\/jats:title>\n                    <jats:p>\n                      <jats:ext-link>https:\/\/www.crd.york.ac.uk\/PROSPERO\/view\/CRD420261354082<\/jats:ext-link>\n                      , Unique Identifier: CRD420261354082.\n                    <\/jats:p>\n                  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