Using narrative and informational messages to improve correctional professionals’ attitudes toward medications for opioid use disorder

Both informational and narrative messages can improve attitudes toward MOUD use in criminal legal settings. Well-designed educational messages aimed at changing attitudes and reducing barriers to promoting MOUD use in criminal legal settings are warranted.

Authors

Institutions

Publication Details

Journal
Health & Justice
Published
2025-08-26
DOI
https://doi.org/10.1186/s40352-025-00363-3
Citations
2
Primary Topic
Media Influence and Health
Type
article
Field-Weighted Citation Impact
30.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Using narrative and informational messages to improve correctional professionals’ attitudes toward medications for opioid use disorder

Lindsay Smith, Amy Murphy, Xiaoquan Zhao, Faye S. Taxman et al.
2 citations
Health & Justice
Media Influence and Health
30.35
article

Using narrative and informational messages to improve correctional professionals’ attitudes toward medications for opioid use disorder

Lindsay Smith, Amy Murphy, Xiaoquan Zhao, Faye S. Taxman, Urszula A. Horoszko, Alyssa Harrell-Webber
article en
2 citations

Abstract

Both informational and narrative messages can improve attitudes toward MOUD use in criminal legal settings. Well-designed educational messages aimed at changing attitudes and reducing barriers to promoting MOUD use in criminal legal settings are warranted.

Health & JusticeVol. 13(1)
George Mason University (US)
Openalex Percentile: Top 1%
Media Influence and Health
30.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.