{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,13]],"date-time":"2026-08-13T00:19:44Z","timestamp":1786580384428,"version":"build-2736575974"},"reference-count":74,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Med Internet Res"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Telemedicine has revolutionized the management of type 2 diabetes mellitus (T2DM) in primary care by improving access to health care services and enhancing health outcomes. Despite these advancements, it remains unclear whether telemedicine has reduced access inequalities among different demographic and socioeconomic groups.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study aimed to investigate the most important demographic and socioeconomic factors associated with telemedicine use among individuals with T2DM in primary care.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n We conducted a systematic review and meta-analysis. Databases including MEDLINE, Embase, PsycINFO, Google Scholar, Scopus, and CINAHL were searched from inception to December 2023. The reference lists of eligible studies and other relevant systematic reviews were also searched. We included observational and cohort studies that assessed the effects of telemedicine interventions on individuals with T2DM in primary care. The core outcomes were the factors associated with telemedicine use, reported as adjusted odds ratios and 95% CIs for each factor, using a random-effects model. Heterogeneity was quantified using the\n I<\/jats:italic>\n \u00b2 statistic, and publication bias was assessed. The protocol for this review was registered with PROSPERO (CRD42024550410).\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Of the 3006 records identified, 16 studies involving 71,336 patients were included in the meta-analysis. Female patients had higher odds of using telemedicine than males (pooled adjusted odds ratio [OR] 1.05, 95% CI 1.02-1.09). Older patients were significantly less likely to use telemedicine than younger patients (pooled OR 0.979, 95% CI 0.98-0.98). Compared with White patients, Black patients were less likely to use telemedicine (pooled OR 0.55, 95% CI 0.32-0.94), while no statistically significant differences were observed for Hispanic (pooled OR 1.075, 95% CI 0.36-3.24) or Asian participants (pooled OR 0.56, 95% CI 0.29-1.06). Patients with higher education levels had greater odds of using telemedicine than those with lower education levels (pooled OR 1.681, 95% CI 1.48-1.91).<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n This systematic review and meta-analysis provide evidence of significant disparities in telemedicine use among men, older adults, Black individuals, and those with lower levels of education who have T2DM in primary care. Given that these groups are among the most vulnerable to T2DM, these disparities highlight the critical need for strategic interventions and robust policies that ensure telemedicine fosters equitable access to health care while preventing further exacerbation of existing health inequalities.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/73113","type":"journal-article","created":{"date-parts":[[2025,7,14]],"date-time":"2025-07-14T19:45:06Z","timestamp":1752522306000},"page":"e73113-e73113","source":"Crossref","is-referenced-by-count":8,"title":["Demographic and Socioeconomic Disparities in Telemedicine Use Among Individuals With Type 2 Diabetes in Primary Care: Systematic Review and Meta-Analysis"],"prefix":"10.2196","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-6949-4487","authenticated-orcid":false,"given":"Nawwarah","family":"Alfarwan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7153-5745","authenticated-orcid":false,"given":"Maria","family":"Panagioti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2063-0977","authenticated-orcid":false,"given":"Alexander","family":"Hodkinson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5888-422X","authenticated-orcid":false,"given":"Lamiece","family":"Hassan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7978-1094","authenticated-orcid":false,"given":"Salwa S","family":"Zghebi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6450-5815","authenticated-orcid":false,"given":"Evangelos","family":"Kontopantelis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2025,9,9]]},"reference":[{"key":"R1","unstructured":"IDF Diabetes Atlas. 10th ed. 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