ArticleThe journal of pain2023
The Problem of Pain in the United States: A Population-Based Characterization of Biopsychosocial Correlates of High Impact Chronic Pain Using the National Health Interview Survey.
Article in The journal of pain, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 24 citations in OpenAlex.
- Skill-Based Virtual Reality Therapy in High-Impact Chronic Pain: 2-Year Follow-Up Results From a Secondary Analysis of a Randomized Controlled Trial.Journal of medical Internet research · 2026Trial
- Differential treatment response to virtual reality in high-impact chronic pain: secondary analysis of a randomized trial.Scientific reports · 2025Trial
- Article
- Does Interoceptive Sensibility Mediate the Relationship Between Emotional Distress and Pain Severity? A Cross-Sectional Study in Chronic Pain and Pain-Free Individuals.European journal of pain (London, England) · 2026Article
- Impact of chronic pain on the families of U.S. adults.Pain reports · 2026Article
- Predicting the course of high-impact chronic pain using machine learning algorithms.The journal of pain · 2026Article
- Urban-rural disparities in high-impact chronic pain among older adults in Southwest China: a community-based cross-sectional study.International journal for equity in health · 2026Article
- Pain in systemic lupus erythematosus: emerging insights and paradigms.Nature reviews. Rheumatology · 2025Review
- Graded chronic noncancer pain distribution using the Graded Chronic Pain Scale-Revised framework: a cross-sectional study.Pain reports · 2025Article
- Impact of Pain Self-Efficacy on Health Outcomes in High-Impact Chronic Pain: A Longitudinal Study.The Clinical journal of pain · 2025Article
- Article
- Brief interventions for chronic pain: Approaches and evidence.Current opinion in psychology · 2025Review
- Problem of pain in the USA: evaluating the generalisability of high-impact chronic pain models over time using National Health Interview Survey (NHIS) data.BMJ public health · 2025Article
- Concurrent Validity of the Operationalization of High-Impact Pain Construct in the Health and Retirement Study.Journal of pain research · 2025Article
- Vibration-Induced Alteration in Trunk Extensor Muscle Proprioception as a Model for Impaired Trunk Control in Low Back Pain.Brain sciences · 2024Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
Over 20 million adults in the United States live with high impact chronic pain (HICP), or chronic pain that limits life or work activities for ≥3 months. It is critically important to differentiate people with HICP from those who sustain normal activities although experiencing chronic pain. Therefore, we aim to help clinicians and researchers identify those with HICP by: 1) developing models that identify factors associated with HICP using the 2016 national health interview survey (NHIS) and 2) evaluating the performances of those models overall and by sociodemographic subgroups (sex, age, and race/ethnicity). Our analysis included 32,980 respondents. We fitted logistic regression models with LASSO (a parametric model) and random forest (a nonparametric model) for predicting HICP using the whole sample. Both models performed well. The most important factors associated with HICP were those related to underlying ill-health (arthritis and rheumatism, hospitalizations, and emergency department visits) and poor psychological well-being. These factors can be used for identifying higher-risk sub-groups for screening for HICP. We will externally validate these findings in future work. We need future studies that longitudinally predict the initiation and maintenance of HICP, then use this information to prevent HICP and direct patients to optimal treatments. PERSPECTIVE: Our study developed models to identify factors associated with high-impact chronic pain (HICP) using the 2016 National Health Interview Survey. There was homogeneity in the factors associated with HICP by gender, age, and race/ethnicity. Understanding these risk factors is crucial to support the identification of populations and individuals at highest risk for developing HICP and improve access to interventions that target these high-risk subgroups.
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Registered trials
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.