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dc.contributor.authorHampton, Jazmin
dc.contributor.authorMugambi, Purity
dc.contributor.authorCaggiano, Emily
dc.contributor.authorEugene, Reynalde
dc.contributor.authorValente, Alycia
dc.contributor.authorTaylor, Melissa
dc.contributor.authorCarreiro, Stephanie
dc.date.accessioned2024-07-01T19:36:12Z
dc.date.available2024-07-01T19:36:12Z
dc.date.issued2024-03-26
dc.identifier.citationHampton J, Mugambi P, Caggiano E, Eugene R, Valente A, Taylor M, Carreiro S. Closing the Digital Divide in Interventions for Substance Use Disorder. J Psychiatr Brain Sci. 2024;9(1):e240002. doi: 10.20900/jpbs.20240002. Epub 2024 Mar 26. PMID: 38726224; PMCID: PMC11081399.en_US
dc.identifier.eissn2398-385X
dc.identifier.doi10.20900/jpbs.20240002en_US
dc.identifier.pmid38726224
dc.identifier.urihttp://hdl.handle.net/20.500.14038/53529
dc.description.abstractDigital health interventions are exploding in today's medical practice and have tremendous potential to support the treatment of substance use disorders (SUD). Developers and healthcare providers alike must be cognizant of the potential for digital interventions to exacerbate existing inequities in SUD treatment, particularly as they relate to Social Determinants of Health (SDoH). To explore this evolving area of study, this manuscript will review the existing concepts of the digital divide and digital inequities, and the role SDoH play as drivers of digital inequities. We will then explore how the data used and modeling strategies can create bias in digital health tools for SUD. Finally, we will discuss potential solutions and future directions to bridge these gaps including smartphone ownership, Wi-Fi access, digital literacy, and mitigation of historical, algorithmic, and measurement bias. Thoughtful design of digital interventions is quintessential to reduce the risk of bias, decrease the digital divide, and create equitable health outcomes for individuals with SUD.en_US
dc.language.isoen
dc.relation.ispartofJournal of Psychiatry and Brain Scienceen_US
dc.relation.urlhttps://doi.org/10.20900/jpbs.20240002en_US
dc.rightsCopyright © 2024 by the author(s). Licensee Hapres, London, United Kingdom. This is an open access article distributed under the terms and conditions of Creative Commons Attribution 4.0 International License.en_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectalgorithmic biasen_US
dc.subjectartificial intelligenceen_US
dc.subjectdigital divideen_US
dc.subjectdigital healthen_US
dc.subjectdigital inequitiesen_US
dc.subjectmHealthen_US
dc.subjectmachine learningen_US
dc.subjectsocial determinants of healthen_US
dc.subjectsubstance use disorderen_US
dc.titleClosing the Digital Divide in Interventions for Substance Use Disorderen_US
dc.typeJournal Articleen_US
dc.source.journaltitleJournal of psychiatry and brain science
dc.source.volume9
dc.source.issue1
dc.source.countryUnited States
dc.source.countryUnited States
dc.source.countryUnited States
dc.source.countryEngland
dc.identifier.journalJournal of psychiatry and brain science
refterms.dateFOA2024-07-01T19:36:14Z
atmire.contributor.authoremailStephanie.Carreiro@umassmed.eduen_US
dc.contributor.departmentEmergency Medicineen_US
dc.contributor.departmentT.H. Chan School of Medicineen_US
dc.contributor.studentEmily Caggiano


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Copyright © 2024 by the
author(s). Licensee Hapres,
London, United Kingdom. This is
an open access article distributed
under the terms and conditions
of Creative Commons Attribution
4.0 International License.
Except where otherwise noted, this item's license is described as Copyright © 2024 by the author(s). Licensee Hapres, London, United Kingdom. This is an open access article distributed under the terms and conditions of Creative Commons Attribution 4.0 International License.