Evidence map›Paper›PMID 37507721›Full record

ArticleHarm reduction journal2023

Differential risks of syringe service program participants in Central Ohio: a latent class analysis.

Kyle J Moon, Ian Bryant, Anne Trinh, Kathryn A Hasenstab, Brittany Carter, Rick Barclay, Saira Nawaz

Open access · goldAbstract read
In one paragraph

Article in Harm reduction journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 32% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Kyle J MoonCenter for Health Outcomes and Policy Evaluation Studies (HOPES), The Ohio State University College of Public Health, 381 Cunz Hall, 1841 Neil Avenue, Columbus, OH, 43210, USA.
Ian BryantCenter for Health Outcomes and Policy Evaluation Studies (HOPES), The Ohio State University College of Public Health, 381 Cunz Hall, 1841 Neil Avenue, Columbus, OH, 43210, USA.
Anne TrinhCenter for Health Outcomes and Policy Evaluation Studies (HOPES), The Ohio State University College of Public Health, 381 Cunz Hall, 1841 Neil Avenue, Columbus, OH, 43210, USA.
Kathryn A HasenstabCenter for Health Outcomes and Policy Evaluation Studies (HOPES), The Ohio State University College of Public Health, 381 Cunz Hall, 1841 Neil Avenue, Columbus, OH, 43210, USA.
Brittany CarterEquitas Health, Columbus, OH, USA.
Rick BarclayEquitas Health, Columbus, OH, USA.
Saira NawazCenter for Health Outcomes and Policy Evaluation Studies (HOPES), The Ohio State University College of Public Health, 381 Cunz Hall, 1841 Neil Avenue, Columbus, OH, 43210, USA. Nawaz.16@osu.edu.
The Ohio State University · USOhio Department of Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSignificant heterogeneity exists among people who use drugs (PWUD). We identify distinct profiles of syringe service program (SSP) clients to (a) evaluate differential risk factors across subgroups and (b) inform harm reduction programming.

methodsLatent class analysis (LCA) was applied to identify subgroups of participants (N = 3418) in a SSP in Columbus, Ohio, from 2019 to 2021. Demographics (age, sex, race/ethnicity, sexual orientation, housing status) and drug use characteristics (substance[s] used, syringe gauge, needle length, using alone, mixing drugs, sharing supplies, reducing use, self-reported perceptions on the impact of use, and treatment/support resources) were used as indicators to define latent classes. A five-class LCA model was developed, and logistic regression was then employed to compare risk factors at program initiation and at follow-up visits between latent classes.

resultsFive latent classes were identified: (1) heterosexual males using opioids/stimulants with housing instability and limited resources for treatment/support (16.1%), (2) heterosexual individuals using opioids with stable housing and resources for treatment/support (33.1%), (3) individuals using methamphetamine (12.4%), (4) young white individuals using opioids/methamphetamine (20.5%), and (5) females using opioids/cocaine (17.9%). Class 2 served as the reference group for logistic regression models, and at the time of entry, class 1 was more likely to report history of substance use treatment, overdose, HCV, sharing supplies, and mixing drugs, with persistently higher odds of sharing supplies and mixing drugs at follow-up. Class 3 was more likely to report history of overdose, sharing supplies, and mixing drugs, but outcomes at follow-up were comparable. Class 4 was the least likely to report history of overdose, HCV, and mixing drugs, but the most likely to report HIV. Class 5 was more likely to report history of substance use treatment, overdose, HCV, sharing supplies, and mixing drugs at entry, and higher reports of accessing substance use treatment and testing positive for HCV persisted at follow-up.

conclusionsConsiderable heterogeneity exists among PWUD, leading to differential risk factors that may persist throughout engagement in harm reduction services. LCA can identify distinct profiles of PWUD accessing services to tailor interventions that address risks, improve outcomes, and mitigate disparities.

Indexed as

Drug OverdoseHepatitis CHIV InfectionsMethamphetamineSubstance Abuse, IntravenousSubstance-Related DisordersAnalgesics, OpioidFemaleHumansLatent Class AnalysisMaleNeedle SharingOhioAnalgesics, OpioidMethamphetamineDrug useHarm reductionHepatitis CHIVLCANeedle and syringe exchangeOpioidsOverdoseSSPStimulantsSubstance misuse

Identifiers

PMID37507721
PMCPMC10386257
OpenAlexW4385341036

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.