Evidence map›Paper›PMID 39363183›Full record

ArticleHealth research policy and systems2024

Working in a relational way is everything: Perceptions of power and value in a drug policy-making network.

Naomi Zakimi, Martin Bouchard, Alison Ritter, Alissa Greer

Abstract read
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Article in Health research policy and systems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Naomi ZakimiSchool of Criminology, Simon Fraser University, Burnaby, BC, Canada. nzakimi@sfu.ca.
Martin BouchardSchool of Criminology, Simon Fraser University, Burnaby, BC, Canada.
Alison RitterDrug Policy Modelling Program, Social Policy Research Centre, University of New South Wales, Sydney, NSW, Australia.
Alissa GreerSchool of Criminology, Simon Fraser University, Burnaby, BC, Canada.

Funding

Social Sciences and Humanities Research Council 435-2021-0749
6 · The paper itself

Abstract

backgroundThe development of drug policies has been a major focus for policy-makers across North America in light of the ongoing public health emergency caused by the overdose crisis. In this context, the current study examined stakeholders' experiences and perceptions of power and value in a drug policy-making process in a North American city using qualitative, questionnaire, and social network data.

methodsWe interviewed 18 people who participated in the development of a drug policy proposal between October 2021 and March 2022. They represented different groups and organizations, including government (n = 3), people who use drugs-led advocacy organizations (n = 5), other drug policy advocacy organizations (n = 5), research (n = 3) and police (n = 2). Most of them identified as men (n = 8) and white (n = 16), and their ages ranged between 30 and 80 years old (median = 50). Social network analysis questionnaires and semi-structured qualitative interviews were administered via Zoom. Social network data were analysed using igraph in R, and qualitative data were analysed using thematic analysis. The analyses explored perceptions of value and power within a drug policy-making network.

resultsThe policy-making network showed that connections could be found across participants from different groups, with government officials being the most central. Qualitative data showed that inclusion in the network and centrality did not necessarily translate into feeling powerful or valued. Many participants were dissatisfied with the process despite having structurally advantageous positions or self-reporting moderately high quantitative value scores. Participants who viewed themselves as more valued acknowledged many process shortcomings, but they also saw it as more balanced or fair than those who felt undervalued.

conclusionsWhile participation can make stakeholders and communities feel valued and empowered, our findings highlight that inclusion, position and diversity of connections in a drug policy-making network do not, in and of itself, guarantee these outcomes. Instead, policy-makers must provide transparent terms of reference guidelines and include highly skilled facilitators in policy discussions. This is particularly important in policy processes that involve historical power imbalances in the context of a pressing public health emergency.

Indexed as

Health PolicyIllicit DrugsPolicy MakingPower, PsychologicalSocial InteractionSocial Network AnalysisStakeholder ParticipationConsumer AdvocacyDecision MakingDrug OverdoseGuidelines as TopicHumansInterviews as TopicNorth AmericaQualitative ResearchSocial FacilitationIllicit DrugsDrug policyParticipationpolicy-making processPolicy networkPowerSocial network analysisValue

Identifiers

PMID39363183
PMCPMC11448052

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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.