{"title":"Closing the Digital Divide in Interventions for Substance Use Disorder.","authors":"Jazmin Hampton, Purity Mugambi, Emily Caggiano, Reynalde Eugene, Alycia Valente, Melissa Taylor, Stephanie Carreiro","doi":"10.20900/jpbs.20240002","DOIUrl":null,"url":null,"abstract":"<p><p>Digital 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.</p>","PeriodicalId":73912,"journal":{"name":"Journal of psychiatry and brain science","volume":"9 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11081399/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of psychiatry and brain science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20900/jpbs.20240002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/3/26 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Digital 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.
数字健康干预措施在当今的医疗实践中呈爆炸式增长,在支持药物使用障碍 (SUD) 治疗方面具有巨大的潜力。开发者和医疗服务提供者都必须认识到,数字干预措施有可能加剧药物滥用障碍治疗中现有的不公平现象,尤其是与健康的社会决定因素(SDoH)相关的不公平现象。为了探索这一不断发展的研究领域,本手稿将回顾数字鸿沟和数字不平等的现有概念,以及 SDoH 作为数字不平等驱动因素所发挥的作用。然后,我们将探讨所使用的数据和建模策略会如何在针对 SUD 的数字健康工具中造成偏差。最后,我们将讨论弥合这些差距的潜在解决方案和未来方向,包括智能手机拥有率、Wi-Fi 接入、数字扫盲以及历史、算法和测量偏差的缓解。深思熟虑的数字干预设计对于降低偏差风险、缩小数字鸿沟以及为患有 SUD 的个人创造公平的健康结果至关重要。