Perceived Opioid-Related Health Beliefs Among Homeless-Experienced Individuals Engaging in Opioid Use Disorder Treatment

Individuals with greater opioid use severity endorsed higher perceived opioid-related threats and treatment-related benefits. Interventions that highlight these beliefs may help enhance treatment engagement in this high-risk population.

Authors

Institutions

Publication Details

Journal
Substance Use & Misuse
Published
2026-01-13
DOI
https://doi.org/10.1080/10826084.2025.2612326
Primary Topic
Opioid Use Disorder Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Perceived Opioid-Related Health Beliefs Among Homeless-Experienced Individuals Engaging in Opioid Use Disorder Treatment

Nora Sporn, Danielle R. Fine, Natalia Critchley, Gina R. Kruse et al.
Substance Use & Misuse
Opioid Use Disorder Treatment
article

Perceived Opioid-Related Health Beliefs Among Homeless-Experienced Individuals Engaging in Opioid Use Disorder Treatment

Nora Sporn, Danielle R. Fine, Natalia Critchley, Gina R. Kruse, Travis P. Baggett
article en

Abstract

Individuals with greater opioid use severity endorsed higher perceived opioid-related threats and treatment-related benefits. Interventions that highlight these beliefs may help enhance treatment engagement in this high-risk population.

Substance Use & Misuse
Harvard University (US), Massachusetts General Hospital (US), Boston Health Care for the Homeless Program (US), University of Colorado Denver (US)
Openalex Percentile: Top 89%
Opioid Use Disorder Treatment
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.