Is the Rivermead Post-Concussion Symptoms Questionnaire a Reliable and Valid Measure to Assess Long-Term Symptoms in Traumatic Brain Injury and Orthopedic Injury Patients? A Novel Investigation Using Rasch Analysis.

Rasch analysis brain injuries orthopedic injuries post-concussion syndrome psychometrics

Journal

Neurotrauma reports
ISSN: 2689-288X
Titre abrégé: Neurotrauma Rep
Pays: United States
ID NLM: 101773091

Informations de publication

Date de publication:
2020
Historique:
entrez: 5 7 2021
pubmed: 6 7 2021
medline: 6 7 2021
Statut: epublish

Résumé

Persistent post-concussion syndrome (PCS) symptoms are known to last years after traumatic brain injury (TBI), and similar symptoms are increasingly being documented among those who have not experienced a TBI. There remains however, a dearth of empirical evidence on the structural composition of symptoms beyond the post-acute symptom phase after TBI, and little is known about the potential use of PCS symptom scales to measure PCS-like symptoms in non-TBI individuals. Our objective was therefore to examine the psychometric performance and dimensionality of the Rivermead Post-Concussion Symptoms Questionnaire (RPQ) as a measure of long-term PCS symptoms among a TBI and non-TBI sample. A case-control sample of 223 patients with injury, consisting of age- and sex-matched TBI participants (

Identifiants

pubmed: 34223531
doi: 10.1089/neur.2020.0017
pii: 10.1089/neur.2020.0017
pmc: PMC8240882
doi:

Types de publication

Journal Article

Langues

eng

Pagination

63-72

Informations de copyright

© Shivanthi Balalla et al., 2020; Published by Mary Ann Liebert, Inc.

Déclaration de conflit d'intérêts

No competing financial interests exist.

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Auteurs

Shivanthi Balalla (S)

Department of Psychology and Neuroscience, Auckland University of Technology, Northcote, Auckland, New Zealand.

Chris Krägeloh (C)

Department of Psychology and Neuroscience, Auckland University of Technology, Northcote, Auckland, New Zealand.

Oleg Medvedev (O)

School of Psychology, University of Waikato, Hamilton, New Zealand.

Richard Siegert (R)

Department of Psychology and Neuroscience, Auckland University of Technology, Northcote, Auckland, New Zealand.

Classifications MeSH