Patterns in Mental Health Symptoms, Substance Use, and Viral Suppression in People with HIV: A Clustering Analysis.
Mental health conditions and substance use are prevalent among people with HIV (PWH), are correlated with one another, and associate with viral non-suppression independently; their joint association with viral non-suppression may be under-studied because of data sparsity. We conducted a machine lear...
| Published in: | AIDS & Behavior Vol. 29; no. 11; pp. 3534 - 3544 |
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| Main Authors: | , , , , , , , , |
| Format: | research tables/charts Journal Article |
| Published: |
Springer Nature
Nov2025
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=188476547&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 188476547 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10907165 G1T jtl: AIDS & Behavior issn: 10907165 maglogo: N pubinfo: dt: Nov2025 vid: 29 iid: 11 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 188476547 185830765 188476547 188476547 10.1007/s10461-025-04797-6 188476547 ppf: 3534 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Patterns in Mental Health Symptoms, Substance Use, and Viral Suppression in People with HIV: A Clustering Analysis. aug: au: Hwang, Y. Joseph Lesko, Catherine R. Pytell, Jarratt D. Falade-Nwulia, Oluwaseun Jones, Joyce L. Keruly, Jeanne C. Snow, LaQuita N. Moore, Richard D. Fojo, Anthony T. affil: https://ror.org/00za53h95 Department of Medicine, Johns Hopkins University School of Medicine, 2024 E. Monument Street 2-300, 21287, Baltimore, MD, USA sug: subj: HIV-Positive Persons Psychosocial Factors Mental Disorders Epidemiology Substance Use Disorders Epidemiology Viral Load Mental Health HIV Infections Complications Human Male Female Adult Middle Age Nonexperimental Studies Prospective Studies Machine Learning Patient-Reported Outcomes Clinical Assessment Tools Scales Questionnaires Cluster Analysis National Institute on Drug Abuse (U.S.) Data Analysis Software Logistic Regression Descriptive Statistics Funding Source Adult: 19-44 years Middle Aged: 45-64 years Male Female ab: Mental health conditions and substance use are prevalent among people with HIV (PWH), are correlated with one another, and associate with viral non-suppression independently; their joint association with viral non-suppression may be under-studied because of data sparsity. We conducted a machine learning-based clustering analysis to characterize groups of patient-reported mental health symptoms and substance use based on their relationship with HIV viral suppression. Participants in the Johns Hopkins HIV Clinical Cohort reported symptoms of depression, anxiety, and post-traumatic stress, and recent use of alcohol, cocaine, amphetamine, non-prescribed opioids, and cannabis (2013–2023). We fit a random forest model with the viral suppression status as the outcome against self-reported items as predictors and used a forest-derived similarity measure to group participants into three clusters. The cluster with the lowest viral suppression rate (74.5%) had the highest depression symptom score (median score 4, interquartile interval [IQI] 1–8) and anxiety symptom score (median score 2, IQI 0–7) along with the greatest prevalence of recent cocaine (99.9%) and opioid (28.0%) use. The cluster with the highest HIV viral suppression rate (81.1%) had the lowest depression symptom score (median 1, IQI 0–4) and anxiety symptom score (median 0, IQI 0–2) and lowest proportion of recent cocaine (0%) and opioid (2.5%) use. Clinically meaningful groups of PWH with heterogenous mental health and substance use characteristics were formed using a machine learning-based clustering approach. PWH with mental health symptoms and substance use represent an important subpopulation for interventions to improve antiretroviral treatment outcomes. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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