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[Commentary] REDUCING SYRINGE SHARING AMONG INJECTING DRUG USERS IN WINNIPEG: 81% SUCCESS OR 19% FAILURE?

2007· letter· en· W1992893270 on OpenAlexaboutno aff
Don C. Des Jarlais

Bibliographic record

VenueAddiction · 2007
Typeletter
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsnot available
Fundersnot available
KeywordsSyringeSample (material)Needle sharingMedicinePopulationOdds ratioOddsDemographyPsychologySocial psychologyEnvironmental healthFamily medicineHuman immunodeficiency virus (HIV)PsychiatryLogistic regressionInternal medicineSociology

Abstract

fetched live from OpenAlex

Shaw and colleagues [1] present a statistically sophisticated analysis of determinants of syringe sharing among injecting drug users (IDUs) in Winnipeg, Canada. Nineteen per cent of the sample reported receptive syringe sharing in the 6 months prior to the interview. Receptive syringe sharing was associated with difficulties in obtaining syringes (odds ratio = 3.61) and a number of social relationship characteristics. Sharing was more frequent with sex partners, relatives, people to whom the subject felt emotionally close and people with whom the subject cooperated to obtain and use drugs. Interpretation of the ease/difficulty in obtaining syringes factor is relatively straightforward. Interpretation of the social relationship factors is more complicated as there is likely to be overlap among these factors, and the ability of multivariate analysis to determine ‘true’ independent contributions within complicated human relationships is limited. One advantage of the Shaw et al. analysis is that it permits estimating the population-attributable risk percentage for sharing due to difficulties in obtaining clean syringes. Fifteen per cent of the sample reported difficulties, so that almost 40% of the 19% of the subjects reporting sharing would be associated with difficulties in obtaining clean syringes. If these difficulties were removed, the percentage of subjects reporting sharing would presumably fall from 19% to approximately 12%. Before considering how this 12% of subjects sharing due to social factors might be reduced, it is worthwhile to consider what is going right among the IDUs in Winnipeg. Although Shaw and colleagues [1] do not report any trend data, the human immunodeficency virus (HIV) prevalence of 5% in their sample is low. Winnipeg appears to have avoided the rapid outbreaks of HIV among IDUs that occurred in other Canadian cities. This is notable because cocaine is the most commonly injected drug in Winnipeg, and the city has a high proportion of ethnic minorities (First Nations, Metis) IDUs. Cocaine injection and ethnic minority status were important factors in HIV transmission in cities such as Vancouver [2]. The Winnipeg IDUs also appear to be avoiding injecting in the wrong places. Very few report injecting in shooting galleries (6%) and very few in hotels (8%), locations that can generate rapid change in sharing partners and thus drive very rapid HIV transmission [3]. Of particular interest, only 49% of the subjects were hepatitis C virus (HCV) seropositive. This is a relatively low rate; in most IDU populations HCV prevalence ranges from 60% to 90% [4]. The Winnipeg sample reported a mean of over 13 years injecting, so that the relatively low HCV prevalence is not a simple function of short duration of injecting. Shaw et al. provide a sophisticated analysis of the determinants of recent receptive syringe sharing among IDUs in Winnipeg and consider how sharing might be reduced even further. Given what happened with HIV among IDUs in other Canadian cities, such as Montreal, Ottawa and Vancouver, it would be very helpful to have an equally sophisticated analysis of the reasons why IDUs in Winnipeg have such relatively low HIV and HCV seroprevalence.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.323
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2007
Admission routes1
Has abstractyes

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