Evidence map›Paper›PMID 40291380›Full record

ArticlePain reports2025

Opioid prescription patterns and pain severity among patients with opioid use disorder and other substance use disorders: a mixed methods study.

Erin F Madden, Gintare Daulys, Benjamin Tingey, Felicia Frabis, Pooja Lagisetty, Philip J Kroth, Fares Qeadan

Abstract read
In one paragraph

Article in Pain reports, 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

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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

7 authors.

Erin F MaddenDepartment of Family Medicine and Public Health Sciences, Wayne State University, Detroit, MI, USA.
Gintare DaulysParkinson School of Health Sciences and Public Health, Loyola University Chicago, Maywood, IL, USA.
Benjamin TingeyParkinson School of Health Sciences and Public Health, Loyola University Chicago, Maywood, IL, USA.
Felicia FrabisDepartment of Family Medicine and Public Health Sciences, Wayne State University, Detroit, MI, USA.
Pooja LagisettyDepartment of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
Philip J KrothDepartment of Biomedical Informatics, Western Michigan University, Homer Stryker M.D. School of Medicine, Kalamazoo, MI, USA.
Fares QeadanParkinson School of Health Sciences and Public Health, Loyola University Chicago, Maywood, IL, USA.ORCID https://orcid.org/0000-0002-3376-220X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Pain management for patients with substance use disorders (SUDs) poses challenges, yet little is known about their pain severity perceptions. We conducted a mixed-methods study to understand numeric pain severity reporting among patients with SUD. We assessed how interactions between opioid prescribing and time, medications for opioid use disorder (MOUD), complementary medicine (CM), and outpatient SUD-related services (OS) predict differences in reported pain severity among patients with SUD. Methods: We analyzed electronic health records (EHR) data, from 2003 to 2023, among the Results: Overall, predicted mean pain scores (95% confidence interval) were highest for patients with OUD (4.52 [4.51, 4.53]), lower for other patients with SUD (3.80 [3.79, 3.81]), and lowest for controls (3.28 [3.27, 3.29]) across all opioid prescription doses and durations. Complementary medicine use was associated with lower pain scores for all patients prescribed opioids. Pain scores were also lower for patients with OUD and SUD prescribed opioids and using OS, and for patients with OUD treated with MOUD and prescribed higher dose opioids. Focus-groups revealed pain reporting is influenced by anticipated clinician disbelief, treatment changes, and stigma. Conclusion: These findings highlight the need to address pain within addiction treatment and further examine effective pain management interventions for this complex patient population.

Indexed as

Complementary medicineMedications for opioid use disorderMixed methodsNumeric rating scaleOpioid prescription patternsOpioid use disorderPain severitySubstance use disorders

Identifiers

PMID40291380
PMCPMC12026388

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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.