Evidence map›Paper›PMID 40687393›Full record

ArticleDrug and alcohol dependence reports2025

On-site health service delivery models at syringe services programs in the United States: Results of a national cross-sectional survey.

Czarina N Behrends, Don C Des Jarlais, Winston Luhur, Xinlin Lu, Grace J Corry, Sara N Glick, Shashi N Kapadia, David C Perlman, Bruce R Schackman

Abstract read
In one paragraph

Article in Drug and alcohol dependence reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Syringe Services Participants' Preferences for Wound Care, HIV/Hepatitis C Virus Screening, and Opioid Use Disorder Treatment: A Discrete Choice Experiment.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2026
    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

9 authors.

Czarina N BehrendsDepartment of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States.
Don C Des JarlaisCollege of Global Public Health, New York University, New York, NY, United States.
Winston LuhurDepartment of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States.
Xinlin LuCollege of Global Public Health, New York University, New York, NY, United States.
Grace J CorryDepartment of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States.
Sara N GlickDivision of Allergy and Infectious Diseases, School of Medicine, University of Washington, Seattle, WA, United States.
Shashi N KapadiaDepartment of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States.
David C PerlmanDivision of Infectious Diseases, Mount Sinai Beth Israel, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Bruce R SchackmanDepartment of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States.

Funding

Transdisciplinary Theoretical Svnthesis and Development CoreP30DA011041 · NIDA · NEW YORK UNIVERSITY · PI Holly Hagan · 1998 to 2026
$38.9M
Utilization of health services after engagement with opioid use disorder (OUD) treatment provider by individuals with and without post-traumatic stress disorderP30DA040500 · NIDA · WEILL MEDICAL COLL OF CORNELL UNIV · PI Yuhua Bao · 2015 to 2026
$20.7M
Economic Analysis of Rapid HIV and HCV Testing in Drug Abuse Treatment ProgramsR01DA027379 · NIDA · WEILL MEDICAL COLL OF CORNELL UNIV · PI SCHACKMAN, BRUCE R · 2009 to 2021
$5.3M
Integrated Care for Hepatitis C: Current Uptake & Impact on Future TreatmentK01DA048172 · NIDA · WEILL MEDICAL COLL OF CORNELL UNIV · PI KAPADIA, SHASHI · 2019 to 2023
$948k
NIDA NIH HHS K01 DA048172NIDA NIH HHS P30 DA011041NIDA NIH HHS P30 DA040500NIDA NIH HHS R01 DA027379
6 · The paper itself

Abstract

Background: People who inject drugs (PWID) have many needs for health services, but frequently lack access to and/or do not utilize those services. Syringe services programs (SSPs) are low-stigma environments where health services can be provided, but are not well described. Objective: We characterized types of health services delivery available at syringe services programs (SSPs) nationally and assess SSP characteristics associated with them. Methods: Using a national survey of SSPs on services provided in 2019 (N = 153), we conducted latent class analysis to determine the best fit model for health service delivery types. We examined the association between health delivery types and SSP organizational characteristics using multinomial logistic regression. Results: A 3-class model was best fit and included 1) a comprehensive care model that had a high probability of offering multiple health services (11 %), 2) a testing and wound care model that offers mostly HIV/HCV testing and wound care (57 %), and 3) a minimal or no health services model that predominantly do no offer medical services (32 %). Comprehensive care and HIV/HCV testing and wound care SSPs were significantly more likely to have ≥ 50 % of their funding from public sources (OR=13.7 and OR=18.0), be a larger program (4th quartile in syringe distribution, OR=25.2 and OR=4.7), and less likely to be a grassroots program (OR=0.1 for both) compared to minimal care SSPs. Conclusions: With 11 % of SSPs providing comprehensive care and one-third providing minimal services, there is an opportunity to expand health care services at SSPs with further public funding investments.

Indexed as

Harm reductionHCVHealth servicesHIVSyringe services programs

Identifiers

PMID40687393
PMCPMC12273473

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.