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    Depression predicts chronic pain interference in racially diverse, income-disadvantaged patients

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    Authors
    Nephew, Benjamin C.
    Incollingo Rodriguez, Angela C.
    Melican, Veronica
    Polcari, Justin J.
    Nippert, Kathryn E.
    Rashkovskii, Mikhail
    Linnell, Lilly-Beth
    Hu, Ruofan
    Ruiz, Carolina
    King, Jean A.
    Gardiner, Paula
    Show allShow less
    UMass Chan Affiliations
    Center for Integrated Primary Care
    Department of Family Medicine and Community Health
    Document Type
    Journal Article
    Publication Date
    2021-12-15
    Keywords
    Depression
    Chronic Pain
    Stress
    Self-Efficacy
    Sleep
    Pain Interference
    depressive disorders
    income
    pain
    self efficacy
    sleep
    stress
    chronic pain
    sleep quality
    racial/ethnic diversity
    Artificial Intelligence and Robotics
    Epidemiology
    Health Psychology
    Integrative Medicine
    Movement and Mind-Body Therapies
    Pain Management
    Psychiatry and Psychology
    Race and Ethnicity
    Show allShow less
    
    Metadata
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    Link to Full Text
    https://doi.org/10.1093/pm/pnab342
    Abstract
    BACKGROUND: Chronic pain is one of the most common reasons adults seek medical care in the US, with prevalence estimates ranging from 11% to 40%. Mindfulness meditation has been associated with significant improvements in pain, depression, physical and mental health, sleep, and overall quality of life. Group medical visits are increasingly common and are effective at treating myriad illnesses, including chronic pain. Integrative Medical Group Visits (IMGV) combine mindfulness techniques, evidence based integrative medicine, and medical group visits and can be used as adjuncts to medications, particularly in diverse underserved populations with limited access to non-pharmacological therapies. OBJECTIVE AND DESIGN: The objective of the present study was to use a blended analytical approach of machine learning and regression analyses to evaluate the potential relationship between depression and chronic pain in data from a randomized clinical trial of IMGV in diverse, income disadvantaged patients suffering from chronic pain and depression. METHODS: The analytical approach used machine learning to assess the predictive relationship between depression and pain and identify and select key mediators, which were then assessed with regression analyses. It was hypothesized that depression would predict the pain outcomes of average pain, pain severity, and pain interference. RESULTS: Our analyses identified and characterized a predictive relationship between depression and chronic pain interference. This prediction was mediated by high perceived stress, low pain self-efficacy, and poor sleep quality, potential targets for attenuating the adverse effects of depression on functional outcomes. CONCLUSIONS: In the context of the associated clinical trial and similar interventions, these insights may inform future treatment optimization, targeting, and application efforts in racialized, income disadvantaged populations, demographics often neglected in studies of chronic pain. TRIAL REGISTRATION: NCT from clinicaltrials.gov: 02262377. American Academy of Pain Medicine.
    Source

    Nephew BC, Incollingo Rodriguez AC, Melican V, Polcari JJ, Nippert KE, Rashkovskii M, Linnell LB, Hu R, Ruiz C, King JA, Gardiner P. Depression predicts chronic pain interference in racially diverse, income-disadvantaged patients. Pain Med. 2021 Dec 15:pnab342. doi: 10.1093/pm/pnab342. Epub ahead of print. PMID: 34908146. Link to article on publisher's site

    DOI
    10.1093/pm/pnab342
    Permanent Link to this Item
    http://hdl.handle.net/20.500.14038/30730
    PubMed ID
    34908146
    Notes

    This article is based on a previously available preprint in medRxiv, https://doi.org/10.1101/2021.06.17.21259108.

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    Link to Article in PubMed

    ae974a485f413a2113503eed53cd6c53
    10.1093/pm/pnab342
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    Center for Integrated Primary Care Publications

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