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Record W4291163161 · doi:10.1016/j.dadr.2022.100086

Guideline development in harm reduction: Considerations around the meaningful involvement of people who access services

2022· review· en· W4291163161 on OpenAlexaff
A.E. Adams, Max Ferguson, Alissa Greer, Charlene Burmeister, Kurt Lock, Jenny McDougall, Marnie Scow, Jane A. Buxton

Bibliographic record

VenueDrug and Alcohol Dependence Reports · 2022
Typereview
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsSimon Fraser UniversityBC Centre for Disease ControlUniversity of British Columbia
Fundersnot available
KeywordsGuidelineHarm reductionHarmMedicineThematic analysisPsychologyNursingPublic healthQualitative researchSociologySocial psychology

Abstract

fetched live from OpenAlex

Background: Harm reduction seeks to minimizes the negative effects of drug use while respecting the rights of people with lived and living experience of substance use (PWLLE). Guideline standards ("guidelines for guidelines") provide direction on developing healthcare guidelines. To identify essential considerations for guideline development within harm reduction, we examined whether guideline standards are consistent with a harm reduction approach in their recommendations on involving people who access services. Methods: We searched the literature from 2011-2021 to identify guideline standards used in harm reduction and publications on involving PWLLE in developing harm reduction services. We used thematic analysis to compare their guidance on involving people who access services. Findings were validated with two organizations of PWLLE. Results: . Subthemes varied across the literature. We identified five essential considerations for guideline development in harm reduction: establishing a shared understanding of reasons for involving PWLLE; respecting their expertise; partnering with PWLLE to ensure appropriate engagement; incorporating perspectives of populations disproportionately affected by substance use; and securing resources. Conclusion: Guideline standards and the harm reduction literature approach the involvement of people who access services from different perspectives. Thoughtful integration of the two paradigms can improve guidelines while empowering PWLLE. Our findings can support the development of high-quality guidelines that align with the fundamental principles of harm reduction in their involvement of PWLLE.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.955
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.135
GPT teacher head0.409
Teacher spread0.274 · 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
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

Citations12
Published2022
Admission routes1
Has abstractyes

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