Evidence map›Paper›PMID 31617916›Full record

ArticlePain medicine (Malden, Mass.)2020

Negative Affect-Related Factors Have the Strongest Association with Prescription Opioid Misuse in a Cross-Sectional Cohort of Patients with Chronic Pain.

Gadi Gilam, John A Sturgeon, Dokyoung S You, Ajay D Wasan, Beth D Darnall, Sean C Mackey

Open access · bronzeAbstract read
In one paragraph

Article in Pain medicine (Malden, Mass.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
3.8field-weighted citation impact, top 7% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

24 citing papers in PubMed, 43 citations in OpenAlex.

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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

6 authors at 3 institutions in 1 country.

Gadi GilamDivision of Pain Medicine, Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Palo Alto, California.
John A SturgeonCenter for Pain Relief, Department of Anesthesiology and Pain Medicine, University of Washington School of Medicine, Seattle, Washington.
Dokyoung S YouDivision of Pain Medicine, Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Palo Alto, California.
Ajay D WasanDivision of Chronic Pain, Department of Anesthesiology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Beth D DarnallDivision of Pain Medicine, Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Palo Alto, California.
Sean C MackeyDivision of Pain Medicine, Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Palo Alto, California.
Stanford University · USUniversity of Pittsburgh · USUniversity of Washington · US

Funding

fMRI-based Biomarkers for Multiple Components of PainR01DA035484 · NIDA · UNIVERSITY OF COLORADO · PI WAGER, TOR D. · 2013 to 2017
$3.1M
Neuroimaging and Mentoring in Translational Pain ResearchK24DA029262 · NIDA · STANFORD UNIVERSITY · PI MACKEY, SEAN C · 2010 to 2019
$1.9M
Effect of pain catastrophizing on prescription opioid cravingK23DA048972 · NIDA · STANFORD UNIVERSITY · PI YOU, DOKYOUNG SOPHIA · 2019 to 2023
$758k
NIDA NIH HHS K23 DA048972NIDA NIH HHS K24 DA029262NIDA NIH HHS R01 DA035484
6 · The paper itself

Abstract

objectiveIncreased opioid prescription to relieve pain among patients with chronic pain is associated with increased risk for misuse, potentially leading to substance use disorders and overdose death. We aimed to characterize the relative importance and identify the most significant of several potential risk factors for the severity of self-reported prescribed opioid misuse behaviors.

methodsA sample of 1,193 patients (mean age ± SD = 50.72 ± 14.97 years, 64.04% female) with various chronic pain conditions completed a multidimensional registry assessing four pain severity measures and 14 physical, mental, and social health status factors using the National Institutes of Health's Patient-Reported Outcomes Measurement Information System (PROMIS). A validated PROMIS measure of medication misuse was completed by 692 patients who endorsed currently taking opioid medication. Patients taking opioid medications were compared across all measures with those who do not take opioid medications. Subsequently, a data-driven regression analysis was used to determine which measures best explained variability in severity of misuse. We hypothesized that negative affect-related factors, namely anxiety, anger, and/or depression, would be key predictors of misuse severity due to their crucial role in chronic pain and substance use disorders.

resultsPatients taking opioid medications had significantly greater impairment across most measures. Above and beyond demographic variables, the only and most significant predictors of prescribed opioid misuse severity were as follows: anxiety (β = 0.15, P = 0.01), anger (β = 0.13, P = 0.02), Pain Intensity-worst (β = 0.09, P = 0.02), and depression (β = 0.13, P = 0.04).

conclusionsFindings suggest that anxiety, anger, and depression are key factors associated with prescribed opioid misuse tendencies in patients with chronic pain and that they are potential targets for therapeutic intervention.

Indexed as

AngerAdultAffectAnxietyChronic PainCohort StudiesCross-Sectional StudiesDepressionFemaleHumansMaleMiddle AgedOpioid-Related DisordersPrescription Drug MisuseAngerAnxietyCHOIRChronic PainDepressionPrescribed Opioids Misuse

Identifiers

PMID31617916
PMCPMC7049262
OpenAlexW2980769650

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.