Can pain and function be distinguished in the Oxford Knee Score in a meaningful way? An exploratory and confirmatory factor ... View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2013-11

AUTHORS

Kristina Harris, Jill Dawson, Helen Doll, Richard E. Field, David W. Murray, Raymond Fitzpatrick, Crispin Jenkinson, Andrew J. Price, David J. Beard

ABSTRACT

PURPOSE: The purpose of this paper was to examine if pain and functioning can be distinguished in the Oxford Knee Score (OKS) in a meaningful way. This was done by (1) conducting exploratory factor analysis to explore the factorial structure of the OKS and (2) conducting confirmatory factor analysis to examine whether a two-factor solution is superior to a one-factor solution. METHODS: Secondary data analysis of four independent datasets containing OKS scores on 161,973 patients was performed. Four independent datasets contained data on: (1) 156, 788 patients from the NHS HES/PROMS dataset, (2) 2,405 consecutive patients from the South West London Elective Operating Centre, (3) 2,353 patients enrolled in the Knee Arthroplasty Trial and (4) 427 consecutive patients listed for knee replacement surgery at the Nuffield Orthopaedic Centre in Oxford. RESULTS: Factor extraction methods suggested that, depending on the method employed, both one- and two-factor solutions are meaningful. Overall and in each data set some cross-loading occurred and item loadings were consistent across two factors. On confirmatory factor analysis, both one- and two-factor models had acceptable fit indices. This allowed the creation of the 'OKS pain component' and the 'OKS functional component' subscales. CONCLUSIONS: Factor analysis confirmed the original conceptual basis of the OKS but offered an option to perform additional analyses using pain and functional subscales. Further research should focus on providing further evidence on construct validity and responsiveness of the newly derived subscales. More... »

PAGES

2561-2568

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11136-013-0393-x

DOI

http://dx.doi.org/10.1007/s11136-013-0393-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1005403591

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/23526094


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s11136-013-0393-x'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s11136-013-0393-x'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11136-013-0393-x'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11136-013-0393-x'


 

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