Evidence map›Paper›PMID 41032213›Full record

ArticleHealth & justice2025

A qualitative study of police officers' knowledge of the relationship between police opioid seizures and subsequent risk of overdose.

Brandon Del Pozo, Erin Thompson, Alina Whiteside

Abstract read
In one paragraph

Article in Health & justice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

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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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Brandon Del PozoThe Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA. bdelpozo@brownhealth.org.
Erin ThompsonBrown University Health, Providence, Rhode Island, USA.
Alina WhitesideBrown University Health, Providence, Rhode Island, USA.

Funding

Police Diversion to Treatment for Opioid Use Disorder: A Mixed Methods StudyK01DA056654 · NIDA · RHODE ISLAND HOSPITAL · PI Brandon del Pozo · 2022 to 2026
$878k
Evaluating the decriminalization of non-prescribed buprenorphine in Rhode IslandR21DA057171 · NIDA · RHODE ISLAND HOSPITAL · PI DEL POZO, BRANDON, RICH, JOSIAH D · 2022 to 2023
$445k
NIDA NIH HHS K01 DA056654NIDA NIH HHS R21 DA057171NIDA NIH HHS R21DA057171
6 · The paper itself

Abstract

People who use opioids (PWUO) have asserted police opioid seizures increase risk of overdose in their proximate aftermath. Ecological studies and causal models exhibit a positive association between police opioid seizures and overdose risk. To further characterize this relationship, this qualitative study explores how police officers who conduct drug enforcement understand the relationship between their opioid seizures and overdose risk. Semi-structured interviews were conducted with officers from the Providence, Rhode Island (USA) Police Department (n = 26) who patrolled areas with highly concentrated public substance use, or who conducted narcotics investigations. Interviews explored beliefs about the effects of police opioid seizures on overdose risk, reasons why seizures may modify this risk, and the motivations for narcotics enforcement. In contrast to patrol officers, narcotics investigators and patrol supervisors with narcotics investigation experience expressed four themes: (1) police opioid seizures increase subsequent overdose risk; (2) the reasons why closely track accounts put forth by researchers, and PWUO who experience this risk firsthand; (3) this risk was one of many faced by PWUO, and (4) police narcotics work should weigh it against the perceived need to address the effects of the illicit narcotics trade on a community. This consensus across diverse study populations, supported by ecological research and causal models, suggests the overdose risks generated by police opioid enforcement should be taken seriously in formulating drug policy.

Identifiers

PMID41032213
PMCPMC12487143

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Registered trials

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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.