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Record W3092276995 · doi:10.1186/s12954-020-00414-y

To what extent do supervised drug consumption services incorporate non-injection routes of administration? A systematic scoping review documenting existing facilities

2020· article· en· W3092276995 on OpenAlexafffund
Kelsey A. Speed, Nicole D. Gehring, Katherine Launier, Daniel C. O’Brien, Sandy Campbell, Elaine Hyshka

Bibliographic record

VenueHarm Reduction Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsRoyal Alexandra HospitalUniversity of Alberta
FundersGovernment of AlbertaRoyal Alexandra Hospital FoundationAlberta Health Services
KeywordsHealth psychologyConsumption (sociology)Administration (probate law)Social policyEnvironmental healthDrugMedicinePublic healthHealth services researchHarm reductionHealth administrationBusinessNursingPharmacologyPolitical scienceSociologySocial science

Abstract

fetched live from OpenAlex

BACKGROUND: Most of the existing research on supervised consumption services (SCS) is focused on injection drug use. Less is known about the applicability of SCS for people who consume drugs orally, intranasally, or through inhalation. This is problematic because people who use drugs through modes other than injection are also at risk of overdose death and other harm, and experience barriers accessing health and social services. We aimed to describe existing SCS models that accommodate these alternate routes of drug consumption, and synthesize available information on characteristics of program participants. METHODS: We conducted a systematic scoping review of 9 peer-reviewed and 13 grey literature databases on SCS that incorporate non-injection routes of consumption. We screened 22,882 titles, and excluded 22,843 (99.8%) articles. We ultimately included 39 (0.2%) full-text articles; 28 (72%) of these articles explicitly identified SCS that permit alternate routes of consumption and 21 (54%) discussed characteristics of participants who consume drugs through non-injection routes. Data on study characteristics, terms and definitions, and site and program participant characteristics were extracted and double-coded. Extracted data were analyzed using descriptive statistics and narrative synthesis. RESULTS: Included articles describe 48 SCS that permit non-injection routes of consumption, most of which were located in Germany. The majority of these SCS were legally sanctioned and had models of care that were largely comparable to supervised injection services. Notable differences included physical infrastructure such as ventilated rooms or outdoor areas to accommodate inhalation, and shorter time limits on non-injection drug consumption episodes. Program participants engaging in non-injection forms of consumption were typically men over the age of 30 and structurally vulnerable (e.g., experiencing homelessness or unstable housing). CONCLUSIONS: Extant academic and grey literature indicates that site characteristics and demographics of program participants of SCS that permit non-injection routes of consumption largely reflect those of supervised injection services. Further research on the range of existing SCS that incorporate non-injection routes of consumption is needed to ensure high quality service provision, and improved health outcomes for people who consume drugs via oral, intranasal, and inhalation routes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.045
metaresearch head score (Gemma)0.187
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.045
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.187
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0060.008
Bibliometrics0.0200.022
Science and technology studies0.0020.003
Scholarly communication0.0080.008
Open science0.0030.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.091
GPT teacher head0.374
Teacher spread0.283 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations32
Published2020
Admission routes2
Has abstractyes

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