Comparing higher order models for the EORTC QLQ-C30.
Purpose: To investigate the statistical fit of alternative higher order models for summarizing the health-related quality of life profile generated by the EORTC QLQ-C30 questionnaire.Methods: A 50% random sample was drawn from a dataset of more than 9,000 pre-treatment QLQ-C30 v 3.0 questionnaires c...
| Publicado en: | Quality of Life Research Vol. 21; no. 9; pp. 1607 - 1618 |
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| Autores principales: | , , , , , , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Nov2012
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104375085&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104375085 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09629343 GPQ jtl: Quality of Life Research issn: 09629343 maglogo: N pubinfo: dt: Nov2012 vid: 21 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104375085 NLM22187352 2011718235 10.1007/s11136-011-0082-6 NLM22187352 PMC3472059 104375085 ppf: 1607 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Comparing higher order models for the EORTC QLQ-C30. aug: au: Gundy CM Fayers PM Groenvold M Petersen MA Scott NW Sprangers MA Velikova G Aaronson NK Gundy, Chad M Fayers, Peter M Groenvold, Mogens Petersen, Morten Aa Scott, Neil W Sprangers, Mirjam A G Velikova, Galina Aaronson, Neil K affil: Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands sug: subj: Mental Disorders Diagnosis Psychometrics Methods Quality of Life Psychosocial Factors Chi Square Test Clinical Assessment Tools Factor Analysis Female Human Male Mental Disorders Rehabilitation Mental Health Models, Psychological Models, Statistical Questionnaires Reproducibility of Results Female Male ab: Purpose: To investigate the statistical fit of alternative higher order models for summarizing the health-related quality of life profile generated by the EORTC QLQ-C30 questionnaire.Methods: A 50% random sample was drawn from a dataset of more than 9,000 pre-treatment QLQ-C30 v 3.0 questionnaires completed by cancer patients from 48 countries, differing in primary tumor site and disease stage. Building on a "standard" 14-dimensional QLQ-C30 model, confirmatory factor analysis was used to compare 6 higher order models, including a 1-dimensional (1D) model, a 2D "symptom burden and function" model, two 2D "mental/physical" models, and two models with a "formative" (or "causal") formulation of "symptom burden," and "function."Results: All of the models considered had at least an "adequate" fit to the data: the less restricted the model, the better the fit. The RMSEA fit indices for the various models ranged from 0.042 to 0.061, CFI's 0.90-0.96, and TLI's from 0.96 to 0.98. All chi-square tests were significant. One of the Physical/Mental models had fit indices superior to the other models considered.Conclusions: The Physical/Mental health model had the best fit of the higher order models considered, and enjoys empirical and theoretical support in comparable instruments and applications. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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