{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T06:26:55Z","timestamp":1786688815568,"version":"build-2736575974"},"reference-count":36,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T00:00:00Z","timestamp":1786665600000},"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. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Digital health services hold real promise for older adults managing chronic conditions, yet this population consistently struggles to engage with them meaningfully. In Saudi Arabia, the national Sehhaty mHealth platform has been deployed at scale under Vision 2030, but there is limited evidence on why older users do or do not engage, and what structural factors drive those patterns.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>This study examined the structural determinants of digital health service engagement among Saudi adults aged 55 and above, focusing on the role of access barriers, technology anxiety, digital health literacy, facilitating conditions, and social influence in shaping behavioural intention to use Sehhaty and AI-enabled virtual physician chatbots.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A cross-sectional survey was conducted with 316 community-dwelling adults aged 55\u202fyears and above across Saudi Arabia. Participants completed a 28-item validated questionnaire covering nine constructs adapted from the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Internal consistency, composite reliability, and average variance extracted were assessed for each construct. Structural Equation Modelling (SEM) with bootstrapped mediation analysis and non-parametric group comparisons (Mann\u2013Whitney\n                      <jats:italic>U<\/jats:italic>\n                      ; Kruskal-Wallis) were conducted. The SEM model demonstrated good fit: CFI\u202f=\u202f0.947, TLI\u202f=\u202f0.938, RMSEA\u202f=\u202f0.064 [90% CI: 0.055\u20130.073], SRMR\u202f=\u202f0.071.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The model explained 61.0% of variance in behavioural intention (\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \u202f=\u202f0.610) and 54.0% in digital health literacy (\n                      <jats:italic>R<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \u202f=\u202f0.540). Technology anxiety was the dominant inhibitor, directly suppressing both engagement intention (\n                      <jats:italic>B<\/jats:italic>\n                      \u202f=\u202f\u22120.44,\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&amp;lt;\u202f0.001) and digital health literacy (\n                      <jats:italic>B<\/jats:italic>\n                      \u202f=\u202f\u22120.60,\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&amp;lt;\u202f0.001). Literacy partially mediated the anxiety-intention relationship (indirect\n                      <jats:italic>B<\/jats:italic>\n                      \u202f=\u202f\u22120.281; 95% CI [\u22120.246, \u22120.104]; 25.9% of total effect). One finding was unexpected: Arabic-language smartphone users reported substantially lower technology anxiety than English-language users (\n                      <jats:italic>r<\/jats:italic>\n                      \u202f=\u202f0.404, medium effect), despite lower average digital proficiency.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Technology anxiety and digital health literacy are the primary targets for improving older adult digital health engagement. The Arabic-language anxiety difference carries direct implications for platform design: native language interface concordance appears to reduce anxiety independently of technical skill. Scaffolded onboarding, community literacy programmes, and structured clinician endorsement are recommended as practical complements.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1872211","type":"journal-article","created":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T05:31:55Z","timestamp":1786685515000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Technology anxiety and digital health literacy as structural determinants of mHealth engagement among older adults: a SEM study in Saudi Arabia"],"prefix":"10.3389","volume":"14","author":[{"given":"Haitham","family":"Alzghaibi","sequence":"first","affiliation":[{"name":"Department of Health Informatics, College of Applied Medical Sciences, Qassim University","place":["Buraydah, Saudi 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