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了解在艾滋病毒护理连续过程中参与度欠佳的非裔美国/黑人及拉丁裔艾滋病毒感染者中的医疗不信任:一种机器学习方法。

Understanding Medical Distrust Among African American/Black and Latino Persons Living With HIV With Sub-Optimal Engagement Along the HIV Care Continuum: A Machine Learning Approach.

作者信息

He Ning, Cleland Charles M, Gwadz Marya, Sherpa Dawa, Ritchie Amanda S, Martinez Belkis Y, Collins Linda M

机构信息

New York University Silver School of Social Work, USA.

New York University School of Medicine, USA.

出版信息

Sage Open. 2021 Oct-Dec;11(4). doi: 10.1177/21582440211061314. Epub 2021 Dec 1.

DOI:10.1177/21582440211061314
PMID:35813871
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9262282/
Abstract

Medical distrust is a potent barrier to participation in HIV care and medication use among African American/Black and Latino (AABL) persons living with HIV (PLWH). However, little is known about sociodemographic and risk factors associated with distrust. We recruited adult AABL PLWH from low socio-economic status backgrounds with insufficient engagement in HIV care ( = 512). Participants completed structured assessments on three types of distrust (of health care providers, health care systems, and counter-narratives), HIV history, and mental health. We used a type of machine learning called random forest to explore predictors of trust. On average, participants were 47 years old ( = 11 years), diagnosed with HIV 18 years prior ( = 9 years), and mainly male (64%) and African American/Black (69%). Depression and age were the most important predictors of trust. Among those with elevated depressive symptoms, younger participants had less trust than older, while among those without depression, trust was greater across all ages. The present study adds nuance to the literature on medical distrust among AABL PLWH and identifies junctures where interventions to build trust are needed most.

摘要

医疗不信任是美国非裔/黑人以及感染艾滋病毒的拉丁裔(AABL)艾滋病毒感染者(PLWH)参与艾滋病毒护理和用药的一个强大障碍。然而,对于与不信任相关的社会人口学和风险因素,我们却知之甚少。我们从社会经济地位较低、对艾滋病毒护理参与不足的背景中招募了成年AABL PLWH(n = 512)。参与者完成了关于三种不信任类型(对医疗服务提供者、医疗系统和反叙事的不信任)、艾滋病毒病史和心理健康的结构化评估。我们使用一种名为随机森林的机器学习类型来探索信任的预测因素。参与者的平均年龄为47岁(标准差 = 11岁),18年前被诊断出感染艾滋病毒(标准差 = 9岁),主要为男性(64%)和非裔美国人/黑人(69%)。抑郁和年龄是信任的最重要预测因素。在抑郁症状加重的人群中,年轻参与者比年长参与者的信任度更低,而在没有抑郁的人群中,各年龄段的信任度都更高。本研究为关于AABL PLWH医疗不信任的文献增添了细微差别,并确定了最需要建立信任干预措施的关键节点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/91a6/9262282/a39ae479737b/nihms-1819727-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/91a6/9262282/a39ae479737b/nihms-1819727-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/91a6/9262282/a39ae479737b/nihms-1819727-f0001.jpg

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