Evidence map›Paper›PMID 18556614›Full record

ArticleAmerican journal of public health2008

Identifying heterogeneity among injection drug users: a cluster analysis approach.

Souradet Y Shaw, Lena Shah, Ann M Jolly, John L Wylie

Open access · greenAbstract readComparative Study
In one paragraph

Article in American journal of public health, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

18 citing papers in PubMed, 43 citations in OpenAlex.

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  7. Health research among hard-to-reach people: six degrees of sampling.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2015
    Review
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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

4 authors at 1 institution in 1 country.

Souradet Y ShawCadham Provincial Laboratory, 750 William Ave, Winnipeg, Manitoba R3C3Y1, Canada.
Lena Shah
Ann M Jolly
John L Wylie
Manitoba Health · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesWe used cluster analysis to subdivide a population of injection drug users and identify previously unknown behavioral heterogeneity within that population.

methodsWe applied cluster analysis techniques to data collected in a cross-sectional survey of injection drug users in Winnipeg, Manitoba. The clustering variables we used were based on receptive syringe sharing, ethnicity, and types of drugs injected.

resultsSeven clusters were identified for both male and female injection drug users. Some relationships previously revealed in our study setting, such as the known relationship between Talwin (pentazocine) and Ritalin (methylphenidate) use, injection in hotels, and hepatitis C virus prevalence, were confirmed through our cluster analysis approach. Also, relationships between drug use and infection risk not previously observed in our study setting were identified, an example being a cluster of female crystal methamphetamine users who exhibited high-risk behaviors but an absence or low prevalence of blood-borne pathogens.

conclusionsCluster analysis was useful in both confirming relationships previously identified and identifying new ones relevant to public health research and interventions.

Indexed as

Cluster AnalysisHealth BehaviorAdolescentAdultAnalgesics, OpioidCentral Nervous System StimulantsCross-Sectional StudiesFemaleHepatitis CHumansInterviews as TopicMaleManitobaMethamphetamineMethylphenidateMiddle AgedAnalgesics, OpioidCentral Nervous System StimulantsMethamphetamineMethylphenidatePentazocine

Identifiers

PMID18556614
PMCPMC2446470
OpenAlexW2064835471

What OpenQuestion holds

Textmetadata
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.