Evidence map›Paper›PMID 35227646›Full record

ArticlePain management nursing : official journal of the American Society of Pain Management Nurses2022

Sociodemographic and Clinical Characteristics Associated With Worst Pain Intensity Among Cancer Patients.

Verlin Joseph, Jinhai Huo, Robert Cook, Roger B Fillingim, Yingwei Yao, Gebre Egziabher-Kiros, Enrique Velazquez Villarreal, Xinguang Chen, Robert Molokie, Diana J Wilkie

Open access · bronzeAbstract read
In one paragraph

Article in Pain management nursing : official journal of the American Society of Pain Management Nurses, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
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

10 authors at 5 institutions in 1 country.

Verlin JosephCenter on Alcohol, Substance use And Addictions (CASAA), Department of Psychology, University of New Mexico, Albuquerque, New Mexico. Electronic address: vjoseph8@unm.edu.
Jinhai HuoDepartment of Health Services Research, Management and Policy College of Public Health and Health Professions University of Florida, Gainesville, Florida.
Robert CookDepartment of Epidemiology, College of Public Health and Health Professions, College of Medicine, University of Florida, Gainesville, Florida.
Roger B FillingimDepartment of Dentistry, College of Public Health and Health Professions, University of Florida, Gainesville, Florida.
Yingwei YaoDepartment of Nursing, College of Public Health and Health Professions, University of Florida, Gainesville, Florida.
Gebre Egziabher-KirosInstitute of Public Health, College of Pharmacy, Florida Agricultural & Mechanical University, Tallahassee, Florida.
Enrique Velazquez VillarrealDepartment of Translational Genomics, Keck School of Medicine of University of Southern California, Los Angeles, California.
Xinguang ChenDepartment of Epidemiology, College of Public Health and Health Professions, College of Medicine, University of Florida, Gainesville, Florida.
Robert MolokieCollege of Medicine, University of Illinois at Chicago, Chicago, Illinois.
Diana J WilkieDepartment of Nursing, College of Public Health and Health Professions, University of Florida, Gainesville, Florida.
University of Florida · USFlorida Agricultural and Mechanical University · USUniversity of Illinois Chicago · USUniversity of New Mexico · USUniversity of Southern California · US

Funding

University of Florida Older Americans Independence Center (OAIC)P30AG028740 · NIA · UNIVERSITY OF FLORIDA · PI Yenisel Cruz-Almeida · 2007 to 2026
$22.8M
Tissue Modeling & Drug Development Shared Resources CoreU54CA233444 · NCI · UNIVERSITY OF FLORIDA · PI Chanita A. Hughes-Halbert, Tianze Jiao · 2018 to 2026
$12.1M
Tissue Modeling CoreU54CA233396 · NCI · FLORIDA AGRICULTURAL AND MECHANICAL UNIV · PI Hernan Alcides Flores-Rozas · 2018 to 2026
$9.8M
COMPUTERIZED SYMPTOM REPORT CONSULT FOR CANCER PATIENTSR01CA081918 · NCI · UNIVERSITY OF WASHINGTON · PI WILKIE, DIANA J · 1999 to 2006
$3.9M
INTEGRATED TREATMENT FOR VETERANS WITH CO-OCCURRING CHRONIC PAIN AND OPIOID USE DISORDERUH3DA051241 · NIDA · UNIVERSITY OF NEW MEXICO · PI VOWLES, KEVIN E, WITKIEWITZ, KATIE A · 2020 to 2024
$2.6M
COMPUTERIZED PAIN REPORT &NURSING PAIN CONSULT PROTOCOR01CA062477 · NCI · UNIVERSITY OF WASHINGTON · PI WILKIE, DIANA J · 1999 to 2001
$875k
Patterns of Marijuana Use for HIV Pain: A Mixed Methods ApproachF31DA047200 · NIDA · UNIVERSITY OF FLORIDA · PI JOSEPH, VERLIN WARNEFORD · 2019 to 2020
$62k
NURSE COACHING PROTOCOL EFFECTS ON CANCER PAINR29CA062477 · NCI · UNIVERSITY OF WASHINGTON · PI WILKIE, DIANA J · 1994 to 1998
–
NCI NIH HHS R01 CA062477NCI NIH HHS R01 CA081918NCI NIH HHS R29 CA062477NCI NIH HHS U54 CA233396NCI NIH HHS U54 CA233444NIA NIH HHS P30 AG028740NIDA NIH HHS F31 DA047200NIDA NIH HHS UH3 DA051241
6 · The paper itself

Abstract

aimsPatients with cancer have pain due to their cancer, the cancer treatment and other causes, and the pain intensity varies considerably between individuals. Additional research is needed to understand the factors associated with worst pain intensity. Our study aim was to determine the association between worst pain intensity and sociodemographics and cancerspecific factors among patients with cancer.

designA total of 1,280 patients with cancer recruited from multiple cancer centers over 25 years in the United States were asked to complete a questionnaire that collected respondents' demographic, chronic pain, and cancer-specific information. SETTINGS: Worst, least, and current pain intensities were captured using a modified McGill Pain Questionnaire (pain intensity measured on 0-10 scale). A generalized linear regression analysis was utilized to assess the associations between significant bivariate predictors and worst pain intensity scores.Our study sample was non-Hispanic White (64.5%), non-Hispanic Black (28.3%), and Hispanic (7.2%). On average, participants were 59.4 (standard deviation = 14.4) years old. The average worst pain intensity score was 6.6 (standard deviation = 2.50). After controlling for selected covariates, being Hispanic (β = 0.6859), previous toothache pain (β = 0.0960), headache pain (β = 0.0549), and stomachache pain (β = 0.0577) were positively associated with worse cancer pain. Notably, year of enrollment was not statistically associated with pain.

conclusionsOur study sample was non-Hispanic White (64.5%), non-Hispanic Black (28.3%), and Hispanic (7.2%). On average, participants were 59.4 (standard deviation = 14.4) years old. The average worst pain intensity score was 6.6 (standard deviation = 2.50). After controlling for selected covariates, being Hispanic (β = 0.6859), previous toothache pain (β = 0.0960), headache pain (β = 0.0549), and stomachache pain (β = 0.0577) were positively associated with worse cancer pain. Notably, year of enrollment was not statistically associated with pain. Findings identified being Hispanic and having previous severe toothache, stomachache, and headache pain as significant predictors of worst pain intensity among patients with cancer. After controlling for selected covariates, we did not note statistical differences in worst pain during a 25-year period. Therefore,studies focused on improving the management of pain among patients with cancer should target interventions for those with Hispanic heritage and those with past history of severe common pain.

Indexed as

Cancer PainNeoplasmsAgedHeadacheHispanic or LatinoHumansMiddle AgedPain MeasurementToothacheUnited States

Identifiers

PMID35227646
PMCPMC9308655
OpenAlexW4214707190

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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.