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Psychometric evaluation of the DePaul Symptom Questionnaire-Short Form (DSQ-SF) among adults with Long Covid, ME/CFS, and healthy controls

A machine learning approach

Bibliographic Data

ID5116267
AuthorsWilliam J Mcgarrigle (0000-0001-5938-6815, University of Kentucky), Jacob Furst (DePaul University), Leonard A Jason (0000-0002-9972-4425, DePaul University)
Year2024
Volume29
Issue11
Pages1241-1252
Publication date2024-09-01
Open AccessYes
TypeARTICLE
VenueJournal of Health Psychology (JOURNAL)
Journal identifiersISSN: 1359-1053 • E-ISSN: 1461-7277
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/13591053231223882
PMID38282368
OpenAlexW4391319836
LanguageEN
References cited30

Long COVID shares a number of clinical features with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), including post-exertional malaise, severe fatigue, and neurocognitive deficits. Utilizing validated assessment tools that accurately and efficiently screen for these conditions can facilitate diagnostic and treatment efforts, thereby improving patient outcomes. In this study, we generated a series of random forest machine learning algorithms to evaluate the psychometric properties of the DePaul Symptom Questionnaire-Short Form (DSQ-SF) in classifying large groups of adults with Long COVID, ME/CFS (without Long COVID), and healthy controls. We demonstrated that the DSQ-SF can accurately classify these populations with high degrees of sensitivity and specificity. In turn, we identified the particular DSQ-SF symptom items that best distinguish Long COVID from ME/CFS, as well as those that differentiate these illness groups from healthy controls

Chronic fatigue syndrome · Cognition · Coronavirus disease 2019 (COVID-19 · Disease · Neurocognitive · Psychiatry · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 · Fibromyalgia and Chronic Fatigue Syndrome Research · Long-Term Effects of COVID-19 · Medicine · Psychology · Psychosomatic Disorders and Their Treatments · Clinical Psychology · Internal Medicine

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    Open Access•Hannah Davis, Gina Assaf et al.•EClinicalMedicine•2021

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    Open Access•Keiji Fukuda, STEPHEN E STRAUS et al.•Annals of Internal Medicine•1994

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    Open Access•Chen Chen, Spencer R Haupert et al.•The Journal of Infectious Diseases•2022

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    Open Access•Leo Breiman•Machine Learning•2001

  • The utility of patient-reported outcome measures among patients with myalgic encephalomyelitis/chronic fatigue syndrome

    Open Access•Kyle W Murdock, Xin Shelley Wang et al.•Quality of Life Research•2016

Highly citedNo

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