{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T17:21:08Z","timestamp":1784308868567,"version":"3.55.0"},"reference-count":27,"publisher":"Public Library of Science (PLoS)","issue":"10","license":[{"start":{"date-parts":[[2022,10,25]],"date-time":"2022-10-25T00:00:00Z","timestamp":1666656000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000968","name":"American Heart Association","doi-asserted-by":"publisher","award":["0000031288"],"award-info":[{"award-number":["0000031288"]}],"id":[{"id":"10.13039\/100000968","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000057","name":"National Institute of General Medical Sciences","doi-asserted-by":"publisher","award":["1U01GM132771"],"award-info":[{"award-number":["1U01GM132771"]}],"id":[{"id":"10.13039\/100000057","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","award":["UL1TR002378"],"award-info":[{"award-number":["UL1TR002378"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosdigitalhealth.org"],"crossmark-restriction":false},"short-container-title":["PLOS Digit Health"],"abstract":"<jats:p>Digital health innovations, such as telehealth and remote monitoring, have shown promise in addressing patient barriers to accessing evidence-based programs and providing a scalable path for tailored behavioral interventions that support self-management skills, knowledge acquisition and promotion of relevant behavioral change. However, significant attrition continues to plague internet-based studies, a result we believe can be attributed to characteristics of the intervention, or individual user characteristics. In this paper, we provide the first analysis of determinants of non usage attrition in a randomized control trial of a technology-based intervention for improving self-management behaviors among Black adults who face increased cardiovascular risk factors. We introduce a different way to measure nonusage attrition that considers usage over a specific period of time and estimate a cox proportional hazards model of the impact of intervention factors and participant demographics on the risk of a nonusage event. Our results indicated that not having a coach (compared to having a coach) decreases the risk of becoming an inactive user by 36% (HR = .63, P = 0.04). We also found that several demographic factors can influence Non-usage attrition: The risk of nonusage attrition amongst those who completed some college or technical school (HR = 2.91, P = 0.04) or graduated college (HR = 2.98, P = 0.047) is significantly higher when compared to participants who did not graduate high school. Finally, we found that the risk of nonsage attrition among participants with poor cardiovascular from \u201cat-risk\u201d neighborhoods with higher morbidity and mortality rates related to CVD is significantly higher when compared to participants from \u201cresilient\u201d neighborhoods (HR = 1.99, P = 0.03). Our results underscore the importance of understanding challenges to the use of mhealth technologies for cardiovascular health in underserved communities. Addressing these unique barriers is essential, because a lack of diffusion of digital health innovations exacerbates health disparities.<\/jats:p>","DOI":"10.1371\/journal.pdig.0000119","type":"journal-article","created":{"date-parts":[[2022,10,25]],"date-time":"2022-10-25T17:22:33Z","timestamp":1666718553000},"page":"e0000119","update-policy":"https:\/\/doi.org\/10.1371\/journal.pdig.corrections_policy","source":"Crossref","is-referenced-by-count":10,"title":["The law of non-usage attrition in a technology-based behavioral intervention for black adults with poor cardiovascular health"],"prefix":"10.1371","volume":"1","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3899-3728","authenticated-orcid":true,"given":"Muhammed Y.","family":"Idris","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohamed","family":"Mubasher","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ernest","family":"Alema-Mensah","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"Awad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3838-2601","authenticated-orcid":true,"given":"Kofi","family":"Vordzorgbe","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elizabeth","family":"Ofili","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arshed","family":"Ali Quyyumi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Priscilla","family":"Pemu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2022,10,25]]},"reference":[{"key":"pdig.0000119.ref001","unstructured":"National Vital Statistics Report; 2021. 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