{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T20:11:08Z","timestamp":1790107868855,"version":"4.0.1"},"reference-count":39,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T00:00:00Z","timestamp":1790035200000},"content-version":"vor","delay-in-days":264,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"New York Regional Center for Diabetes Translation Research","award":["P30 DK111022"],"award-info":[{"award-number":["P30 DK111022"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Prediabetes affects nearly one in three U.S. adults-often progressing to type 2 diabetes within 10\u2009years. Although prediabetes is increasingly identified in primary care and prevention strategies exist, uptake remains low, particularly in urban safety-net settings. This translational gap reflects the complexity of prevention, which is preference- and context-sensitive. Mobile health could bridge this gap and improve engagement, but effective design requires understanding patient needs, barriers, and care context.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Guided by the Obesity-Related Behavioral Intervention Trials (ORBIT) model, this formative study identified perspectives on prediabetes and diabetes prevention and translated them into components of a patient-facing digital intervention.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Semi-structured qualitative interviews were conducted among 24 adult primary care patients with documented prediabetes in an urban safety-net health system. Interviews explored understanding of prediabetes, decision-making about prevention options, motivation for lifestyle change, and integration of behavioral changes into daily routines. Interviews were transcribed and analyzed using rapid qualitative analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Participants (mean age 58.8 years; 83% women; 46% African American\/Black; 46% Hispanic\/Latino) described six interrelated themes: understanding the diagnosis; making informed treatment decisions; integrating lifestyle change into daily life; finding motivation; staying on track with behavior change; and navigating prevention within health and financial constraints. Themes revealed gaps in risk understanding, counseling, and action planning and were mapped to preliminary app features.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study translated patient-identified needs into initial components for a patient-informed mHealth tool. The findings define early-stage content domains and behavioral targets that will inform prototype refinement, usability testing, and evaluation in primary care.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/tbm\/ibag065","type":"journal-article","created":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T11:51:45Z","timestamp":1789041105000},"source":"Crossref","is-referenced-by-count":0,"title":["Applying the ORBIT model to design a patient-facing mHealth app for diabetes prevention in urban primary care: translating patient perspectives into app design"],"prefix":"10.1093","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1380-3761","authenticated-orcid":false,"given":"Cara","family":"Stephenson-Hunter","sequence":"first","affiliation":[{"name":"Department of Family and Social Medicine, Albert Einstein College of Medicine , Bronx, NY,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katherine","family":"Florian","sequence":"additional","affiliation":[{"name":"Department of Family and Social Medicine, Albert Einstein College of Medicine , Bronx, NY,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chandra","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Family and Social Medicine, Albert Einstein College of Medicine , Bronx, NY,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1323-0556","authenticated-orcid":false,"given":"Earle C","family":"Chambers","sequence":"additional","affiliation":[{"name":"Department of Family and Social Medicine, Albert Einstein College of Medicine , Bronx, NY,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1695-9809","authenticated-orcid":false,"given":"Andrew","family":"Telzak","sequence":"additional","affiliation":[{"name":"Department of Family and Social Medicine, Albert Einstein College of Medicine , Bronx, NY,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3678-5888","authenticated-orcid":false,"given":"Linda C","family":"Gallo","sequence":"additional","affiliation":[{"name":"Department of Psychology, San Diego State University , San Diego, CA,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,9,22]]},"reference":[{"key":"2026092215350029700_ibag065-B1","volume-title":"National Diabetes Statistics Report, 2020","author":"Control CFD Prevention","year":"2020"},{"key":"2026092215350029700_ibag065-B2","volume-title":"National Diabetes Statistics Report Website","author":"Control CFD Prevention","year":"2022"},{"key":"2026092215350029700_ibag065-B3","doi-asserted-by":"publisher","first-page":"860","DOI":"10.1093\/tbm\/ibac032","article-title":"Barriers to participation and lifestyle change among lower versus higher income participants in the national diabetes prevention program: lifestyle coach perspectives","volume":"12","author":"Baucom","year":"2022","journal-title":"Transl Behav Med"},{"key":"2026092215350029700_ibag065-B4","doi-asserted-by":"publisher","first-page":"1331","DOI":"10.2337\/dc16-2099","article-title":"A national effort to prevent type 2 diabetes: participant-level evaluation of CDC\u2019s national diabetes prevention program","volume":"40","author":"Ely","year":"2017","journal-title":"Diabetes Care"},{"key":"2026092215350029700_ibag065-B5","doi-asserted-by":"publisher","first-page":"E83","DOI":"10.5888\/pcd20.230072","article-title":"Factors influencing the referral of patients with prediabetes to a diabetes prevention program in the Bronx, New York","volume":"20","author":"Stephenson-Hunter","year":"2023","journal-title":"Prev Chronic Dis"},{"key":"2026092215350029700_ibag065-B6","doi-asserted-by":"crossref","first-page":"W3-66","DOI":"10.1377\/hlthaff.W3.66","article-title":"How much medical care do the uninsured use, and who pays for it? 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