Evidence map›Paper›PMID 35351160›Full record

ArticleHarm reduction journal2022

Service utilization patterns and characteristics among clients of integrated supervised consumption sites in Toronto, Canada.

Tanner Nassau, Gillian Kolla, Kate Mason, Shaun Hopkins, Paula Tookey, Elizabeth McLean, Dan Werb, Ayden Scheim

Open access · goldAbstract read
In one paragraph

Article in Harm reduction journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

10 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
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  4. Predictors of overdose response hotline use for mental health and fatal overdose prevention.Canadian journal of public health = Revue canadienne de sante publique · 2025
    Article
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  9. Observational
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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

8 authors at 5 institutions in 2 countries.

Tanner NassauDepartment of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, 3215 Market St, Nesbitt Hall, 5th Floor, Philadelphia, PA, 19104, USA.
Gillian KollaCanadian Institute for Substance Use Research, University of Victoria, Victoria, BC, Canada.
Kate MasonSouth Riverdale Community Health Centre, Toronto, ON, Canada.
Shaun HopkinsThe Works, Toronto Public Health, Toronto, ON, Canada.
Paula TookeySouth Riverdale Community Health Centre, Toronto, ON, Canada.
Elizabeth McLeanCentre On Drug Policy Evaluation, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada.
Dan WerbCentre On Drug Policy Evaluation, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada.
Ayden ScheimDepartment of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, 3215 Market St, Nesbitt Hall, 5th Floor, Philadelphia, PA, 19104, USA. ayden@cdpe.org.
St. Michael's Hospital · CARegent Park Community Health Centre · CADrexel University · USToronto Public Health · CAUniversity of California, San Diego · US

Funding

CIHR PJT-53152
6 · The paper itself

Abstract

introductionSupervised consumption services (SCS), intended to reduce morbidity and mortality among people who inject drugs, have been implemented in a variety of delivery models. We describe and compare access to and uptake of co-located and external services among clients accessing harm reduction-embedded (HR-embedded) and community health center-embedded (CHC-embedded) SCS models.

methodsCross-sectional baseline data were collected between November 2018 and March 2020 as part of a cohort of people who inject drugs in Toronto, Canada designed to evaluate one HR-embedded and two CHC-embedded SCS. This analysis was restricted to clients who reported accessing these SCS more than once in the previous 6 months. Participants were classified as HR-embedded or CHC-embedded SCS clients based on self-reported usage patterns. Client characteristics, as well as access to onsite services and referral and uptake of external services, were compared by SCS model.

resultsAmong 469 SCS clients, 305 (65.0%) primarily used HR-embedded SCS and 164 (35.0%) primarily used CHC-embedded SCS. Compared to clients accessing CHC-embedded SCS, clients accessing HR-embedded SCS were somewhat younger (37.6 vs. 41.4, p < 0.001), more likely to report fentanyl as their primary injected drug (62.6% vs. 42.7%, p < 0.001), and visited SCS more often (49.5% vs. 25.6% ≥ daily, p < 0.001). HR-embedded SCS clients were more likely to access harm reduction services onsite compared to CHC-embedded SCS clients (94.8% vs. 89.6%, p = 0.04), while CHC-embedded SCS clients were more likely to access non-harm reduction services onsite (57.3% vs. 26.6%, p < 0.001). For external services, HR-embedded SCS clients were more likely to receive a referral (p = 0.03) but less likely to report referral uptake (p = 0.009).

conclusionsClients accessing HR-embedded and CHC-embedded SCS were largely demographically similar but had different drug and SCS use patterns, with CHC-embedded SCS clients using the site less frequently. While clients of CHC-embedded SCS reported greater access to ancillary health services onsite, external service use remained moderate overall, underscoring the importance of co-location and support for clients with system navigation. Importantly, lack of capacity in services across the system may impact ability of staff to make referrals and/or the ability of clients to take up a referral.

Indexed as

Community Health ServicesHarm ReductionCanadaCommunity Health CentersCross-Sectional StudiesHumans

Identifiers

PMID35351160
PMCPMC8966307
OpenAlexW4220828231

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.