en <span style=font-size:12pt><span style=tab-stops:311.7pt><span style=font-family:Times New Roman,serif><b><span style=font-size:10.0pt><span style=font-family:Cambria,serif><span style=color:#4f81bd>Aims:</span></span></span></b><span style=font-size:10.0pt><span style=font-family:Cambria,serif> This study aimed to analyze the role of technology in maternal health education to improve maternal readiness, measure its effectiveness in terms of knowledge, mental and physical readiness, and identify challenges and implementation strategies.</span></span><span lang=EN-ID style=font-size:10.0pt><span style=font-family:Cambria,serif></span></span></span></span></span><br> <span style=font-size:12pt><span style=tab-stops:311.7pt><span style=font-family:Times New Roman,serif><b><span lang=EN-ID style=font-size:10.0pt><span style=font-family:Cambria,serif><span style=color:#4f81bd>Instrument & Methods</span></span></span></b><b><span style=font-size:10.0pt><span style=font-family:Cambria,serif><span style=color:#4f81bd>:</span></span></span></b> <span style=font-size:10.0pt><span style=font-family:Cambria,serif>This quantitative research utilized partial least squares structural equation modeling with a sample of 99 pregnant women at the Umar Damanik Health Center in Tanjung Balai. Sampling was conducted using the Slovin formula (with a 5% margin of error). Data were collected through valid and reliable questionnaires and analyzed using SmartPLS to test construct reliability (Cronbach’s alpha, composite reliability), convergent validity (average variance extracted), and hypothesis testing (bootstrapping).</span></span><span lang=EN-ID style=font-size:10.0pt><span style=font-family:Cambria,serif></span></span></span></span></span><br> <span style=font-size:12pt><span style=tab-stops:311.7pt><span style=font-family:Times New Roman,serif><b><span lang=EN-ID style=font-size:10.0pt><span style=font-family:Cambria,serif><span style=color:#4f81bd>Findings</span></span></span></b><b><span style=font-size:10.0pt><span style=font-family:Cambria,serif><span style=color:#4f81bd>:</span></span></span></b><span style=font-size:10.0pt><span style=font-family:Cambria,serif> All constructs met the reliability and validity criteria (Cronbach’s alpha>0.7; AVE>0.5). Technology significantly influenced childbirth readiness (R²=0.717-0.899; p<0.05). Mobile health applications provided interactive information access, IoT facilitated real-time monitoring, streaming platforms expanded educational resources, and telemedicine increased access to health consultations. The PLS-SEM model explained 84.1% of the data variability (adjusted R²).</span></span></span></span></span><br> <span style=font-size:12pt><span style=tab-stops:311.7pt><span style=font-family:Times New Roman,serif><b><span style=font-size:10.0pt><span style=font-family:Cambria,serif><span style=color:#4f81bd>Conclusion:</span></span></span></b><span style=font-size:10.0pt><span style=font-family:Cambria,serif> Technology effectively improves childbirth readiness through accessible, interactive, and personalized education.</span></span></span></span></span> Digital Health Technology,Mobile Applications,Internet of Things (IoT),Telemedicine, 323 329 http://hehp.modares.ac.ir/browse.php?a_code=A-10-88288-2&slc_lang=en&sid=4 M.F.A. Tanjung 1003194753284600369393 1003194753284600369393 Yes Sakinah Husada College of Health Sciences, Tanjungbalai, Indonesia E.E.R. Siringoringo 1003194753284600369394 1003194753284600369394 No Sakinah Husada College of Health Sciences, Tanjungbalai, Indonesia M. Sinaga 1003194753284600369395 1003194753284600369395 No Medan Sehati College of Health Sciences, University Medan Sehati, Medan, Indonesia