{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T11:01:32Z","timestamp":1789038092108,"version":"build-2803163510"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"11-12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Digital health technologies (DHT), including telemedicine and world wide web-based tools, have transformed healthcare delivery by enhancing patient self-management and clinical monitoring capabilities. Despite widespread adoption in many populations, U.S. veterans show notably lower rates of technology use compared to other demographic groups. The objective of this study was to investigate factors influencing the adoption of DHT among veterans at a tertiary referral hospital.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods<\/jats:title>\n                    <jats:p>Following Institutional Review Board (IRB) approval, we conducted structured telephone interviews to assess technology use, knowledge, and preferences using the Technology Acceptance Model (TAM) framework. We supplemented interview data with information, including sociodemographics from electronic health records. Participants were classified as either non-users or adopters (i.e., those with some-or-more use) of DHT. Analysis included descriptive statistics; logistic regression to identify adoption predictors; and consensus clustering to characterize user subgroups based on demographic, psychosocial, and personality factors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The study included 141 veterans, predominantly older white males from suburban areas. DHT adopters (n\u2009=\u200950, 35.4%) were younger than non-users (median age 61 vs. 70 years, P\u2009=\u2009.012). The presence of technology-using family or friends strongly predicted adoption (odds ratios [OR]\u2009=\u20095.59, 95% confidence interval [CI], 1.91-18.12, P\u2009=\u2009.002). Personality traits associated with adoption included openness to new experiences (OR\u2009=\u20097.09, 95% CI, 1.89-32.20, P\u2009=\u2009.006) and anxiety (OR\u2009=\u20093.11, 95% CI, 1.12-9.27, P\u2009=\u2009.034). No significant associations were found between DHT adoption and age, gender, race, income, or education. Among adopters, consensus clustering identified 2 robust subgroups: Cluster 1 with a median age of 62 years and high extroversion (93.3%), and Cluster 2 with a median age of 53 years and lower extroversion (6.7%).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study demonstrates that social support networks and personality characteristics, rather than demographic factors, primarily influence veterans\u2019 adoption of DHT. Our findings suggest a need for personalized implementation strategies that consider psychological and social factors. Future initiatives should focus on developing targeted educational programs that leverage social support systems while accounting for individual personality traits.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/milmed\/usaf258","type":"journal-article","created":{"date-parts":[[2025,5,21]],"date-time":"2025-05-21T09:14:26Z","timestamp":1747818866000},"page":"e2550-e2557","source":"Crossref","is-referenced-by-count":1,"title":["Influence of Social Support and Personality Traits on Digital Health Technology Adoption Among U.S. Veterans: A Mixed-Methods Study"],"prefix":"10.1093","volume":"190","author":[{"given":"Maria","family":"Bolus","sequence":"first","affiliation":[{"name":"Anesthesiology, Perioperative and Pain Medicine Service, Veterans Affairs Palo Alto Health Care System , Palo Alto, CA 94304,","place":["United 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S","family":"Stafford","sequence":"additional","affiliation":[{"name":"Department of Medicine Primary, Stanford Prevention Research Center, Stanford University School of Medicine , Stanford, CA 94305,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edward R","family":"Mariano","sequence":"additional","affiliation":[{"name":"Anesthesiology, Perioperative and Pain Medicine Service, Veterans Affairs Palo Alto Health Care System , Palo Alto, CA 94304,","place":["United States"]},{"name":"Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine , Stanford, CA 94305,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8486-9966","authenticated-orcid":false,"given":"Seshadri C","family":"Mudumbai","sequence":"additional","affiliation":[{"name":"Anesthesiology, Perioperative and Pain Medicine Service, Veterans Affairs Palo Alto Health 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