{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T02:01:39Z","timestamp":1789610499919,"version":"build-2803163510"},"reference-count":65,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Pediatr Parent"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Despite the growing uptake of smart technologies in pediatric type 1 diabetes mellitus (T1DM) care, little is known about caregiving parents\u2019 skills to deal with electronic health information sources.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>We aimed to assess the electronic health literacy of parents caring for children with T1DM and investigate its associations with disease management and children\u2019s outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A cross-sectional survey was performed involving 150 parent-child (8-14 years old with T1DM) dyads in a university pediatric diabetology center. Parents\u2019 electronic health literacy (eHealth Literacy Scale [eHEALS]), general health literacy (Chew questionnaire and Newest Vital Sign [NVS]), and attitudes toward T1DM care (Parental Self-Efficacy Scale for Diabetes Management [PSESDM] and Hypoglycemia Fear Survey [HFS]) were investigated. Children\u2019s treatment, HbA1c level, and quality of life (Pediatric Quality of Life Inventory Diabetes Module [PedsQL Diab] and EQ-5D-Y-3L) were assessed. Multiple linear regression analysis was performed to investigate the determining factors of 6-month average HbA1c.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Of the 150 children, 38 (25.3%) used a pen, 55 (36.7%) used a pen plus a sensor, 6 (4.0%) used an insulin pump, and 51 (34.0%) used an insulin pump plus a sensor. Parents\u2019 average eHEALS score (mean 31.2, SD 4.9) differed significantly by educational level (P=.04) and the children\u2019s treatment (P=.005), being the highest in the pump + sensor subgroup. The eHEALS score showed significant Pearson correlations with the Chew score (r=\u22120.45; P&lt;.001), NVS score (r=0.25; P=.002), and PSESDM score (r=0.35; P&lt;.001) but not with the children\u2019s HbA1c (r=\u22120.143; P=.08), PedsQL Diab (r=\u22120.0002; P&gt;.99), and EQ-5D-Y-3L outcomes (r=\u22120.13; P=.12). Regression analysis revealed significant associations of the child\u2019s HbA1c level with sex (\u03b2=0.58; P=.008), treatment modality (pen + sensor: \u03b2=\u22120.66; P=.03; pump + sensor: \u03b2=\u22120.93; P=.007), and parents\u2019 self-efficacy (PSESDM; \u03b2=\u22120.08; P=.001).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Significantly higher parental electronic health literacy was found in T1DM children using a glucose sensor. The electronic health literacy level was associated with parents\u2019 diabetes management attitude but not with the child\u2019s glycemic control. Studies further investigating the role of parental electronic health literacy in T1DM children managed at different levels of care and the local context are encouraged.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/54807","type":"journal-article","created":{"date-parts":[[2024,1,31]],"date-time":"2024-01-31T06:14:13Z","timestamp":1706681653000},"page":"e54807","source":"Crossref","is-referenced-by-count":18,"title":["The Impact of Parental Electronic Health Literacy on Disease Management and Outcomes in Pediatric Type 1 Diabetes Mellitus: Cross-Sectional Clinical 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