Exploring the item-sets of the Recovering Quality of Life (ReQoL) measures using factor analysis

Anju Devianee Keetharuth (Lead / Corresponding author), Jakob Bue Bjorner, Michael Barkham, John Browne, Timothy Croudace, John E. Brazier

Research output: Contribution to journalArticle

61 Downloads (Pure)

Abstract

Purpose: This paper presents two studies exploring the latent structure of item sets used in the development of the Recovering Quality of Life mental health outcome measures: ReQoL-10 and ReQoL-20.

Method: In study 1, 2262 participants completed an initial set of 61 items. In study 2, 4266 participants completed a reduced set of 40 items. Study 2 evaluated two formats of the questionnaires: one version where the items were intermingled and one where the positively worded and negatively worded items were presented as two separate blocks. Exploratory and confirmatory factor analyses were conducted on both datasets where models were specified using ordinal treatment of the item responses. Dimensionality based on the conceptual framework and methods effects reflecting the mixture of positively worded and negatively worded items were explored. Factor invariance was tested across the intermingled and block formats.

Results: In both studies, a bi-factor model (study 1: RMSEA = 0.061; CFI = 0.954; study 2: RMSEA = 0.066; CFI = 0.971) with one general factor and two local factors (positively worded questions and negatively worded questions) was preferred. The loadings on the general factor were higher than on the two local factors suggesting that the ReQoL scale scores can be understood in terms of a general factor. Insignificant differences were found between the intermingled and block formats.

Conclusions: The analyses confirmed that the ReQoL item sets are sufficiently unidimensional to proceed to item response theory analysis. The model was robust across different ordering of positive and negative items.

Original languageEnglish
Pages (from-to)1005-1015
Number of pages11
JournalQuality of Life Research
Volume28
Issue number4
Early online date21 Dec 2018
DOIs
Publication statusPublished - Apr 2019

Fingerprint

Statistical Factor Analysis
Quality of Life
Mental Health
Outcome Assessment (Health Care)
chemotactic factor inactivator

Keywords

  • Bi-factor model
  • Dimensionality
  • Factor analysis
  • Latent structure
  • Recovering Quality of Life

Cite this

Keetharuth, Anju Devianee ; Bjorner, Jakob Bue ; Barkham, Michael ; Browne, John ; Croudace, Timothy ; Brazier, John E. / Exploring the item-sets of the Recovering Quality of Life (ReQoL) measures using factor analysis. In: Quality of Life Research. 2019 ; Vol. 28, No. 4. pp. 1005-1015.
@article{436461dd8868483dada3144a5c0c34e5,
title = "Exploring the item-sets of the Recovering Quality of Life (ReQoL) measures using factor analysis",
abstract = "Purpose: This paper presents two studies exploring the latent structure of item sets used in the development of the Recovering Quality of Life mental health outcome measures: ReQoL-10 and ReQoL-20.Method: In study 1, 2262 participants completed an initial set of 61 items. In study 2, 4266 participants completed a reduced set of 40 items. Study 2 evaluated two formats of the questionnaires: one version where the items were intermingled and one where the positively worded and negatively worded items were presented as two separate blocks. Exploratory and confirmatory factor analyses were conducted on both datasets where models were specified using ordinal treatment of the item responses. Dimensionality based on the conceptual framework and methods effects reflecting the mixture of positively worded and negatively worded items were explored. Factor invariance was tested across the intermingled and block formats.Results: In both studies, a bi-factor model (study 1: RMSEA = 0.061; CFI = 0.954; study 2: RMSEA = 0.066; CFI = 0.971) with one general factor and two local factors (positively worded questions and negatively worded questions) was preferred. The loadings on the general factor were higher than on the two local factors suggesting that the ReQoL scale scores can be understood in terms of a general factor. Insignificant differences were found between the intermingled and block formats.Conclusions: The analyses confirmed that the ReQoL item sets are sufficiently unidimensional to proceed to item response theory analysis. The model was robust across different ordering of positive and negative items.",
keywords = "Bi-factor model, Dimensionality, Factor analysis, Latent structure, Recovering Quality of Life",
author = "Keetharuth, {Anju Devianee} and Bjorner, {Jakob Bue} and Michael Barkham and John Browne and Timothy Croudace and Brazier, {John E.}",
note = "Funding: Policy Research Programme, Department of Health, Great Britain (104/0001)",
year = "2019",
month = "4",
doi = "10.1007/s11136-018-2091-1",
language = "English",
volume = "28",
pages = "1005--1015",
journal = "Quality of Life Research",
issn = "0962-9343",
publisher = "Springer Verlag",
number = "4",

}

Exploring the item-sets of the Recovering Quality of Life (ReQoL) measures using factor analysis. / Keetharuth, Anju Devianee (Lead / Corresponding author); Bjorner, Jakob Bue; Barkham, Michael; Browne, John; Croudace, Timothy; Brazier, John E.

In: Quality of Life Research, Vol. 28, No. 4, 04.2019, p. 1005-1015.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Exploring the item-sets of the Recovering Quality of Life (ReQoL) measures using factor analysis

AU - Keetharuth, Anju Devianee

AU - Bjorner, Jakob Bue

AU - Barkham, Michael

AU - Browne, John

AU - Croudace, Timothy

AU - Brazier, John E.

N1 - Funding: Policy Research Programme, Department of Health, Great Britain (104/0001)

PY - 2019/4

Y1 - 2019/4

N2 - Purpose: This paper presents two studies exploring the latent structure of item sets used in the development of the Recovering Quality of Life mental health outcome measures: ReQoL-10 and ReQoL-20.Method: In study 1, 2262 participants completed an initial set of 61 items. In study 2, 4266 participants completed a reduced set of 40 items. Study 2 evaluated two formats of the questionnaires: one version where the items were intermingled and one where the positively worded and negatively worded items were presented as two separate blocks. Exploratory and confirmatory factor analyses were conducted on both datasets where models were specified using ordinal treatment of the item responses. Dimensionality based on the conceptual framework and methods effects reflecting the mixture of positively worded and negatively worded items were explored. Factor invariance was tested across the intermingled and block formats.Results: In both studies, a bi-factor model (study 1: RMSEA = 0.061; CFI = 0.954; study 2: RMSEA = 0.066; CFI = 0.971) with one general factor and two local factors (positively worded questions and negatively worded questions) was preferred. The loadings on the general factor were higher than on the two local factors suggesting that the ReQoL scale scores can be understood in terms of a general factor. Insignificant differences were found between the intermingled and block formats.Conclusions: The analyses confirmed that the ReQoL item sets are sufficiently unidimensional to proceed to item response theory analysis. The model was robust across different ordering of positive and negative items.

AB - Purpose: This paper presents two studies exploring the latent structure of item sets used in the development of the Recovering Quality of Life mental health outcome measures: ReQoL-10 and ReQoL-20.Method: In study 1, 2262 participants completed an initial set of 61 items. In study 2, 4266 participants completed a reduced set of 40 items. Study 2 evaluated two formats of the questionnaires: one version where the items were intermingled and one where the positively worded and negatively worded items were presented as two separate blocks. Exploratory and confirmatory factor analyses were conducted on both datasets where models were specified using ordinal treatment of the item responses. Dimensionality based on the conceptual framework and methods effects reflecting the mixture of positively worded and negatively worded items were explored. Factor invariance was tested across the intermingled and block formats.Results: In both studies, a bi-factor model (study 1: RMSEA = 0.061; CFI = 0.954; study 2: RMSEA = 0.066; CFI = 0.971) with one general factor and two local factors (positively worded questions and negatively worded questions) was preferred. The loadings on the general factor were higher than on the two local factors suggesting that the ReQoL scale scores can be understood in terms of a general factor. Insignificant differences were found between the intermingled and block formats.Conclusions: The analyses confirmed that the ReQoL item sets are sufficiently unidimensional to proceed to item response theory analysis. The model was robust across different ordering of positive and negative items.

KW - Bi-factor model

KW - Dimensionality

KW - Factor analysis

KW - Latent structure

KW - Recovering Quality of Life

UR - http://www.scopus.com/inward/record.url?scp=85058993654&partnerID=8YFLogxK

U2 - 10.1007/s11136-018-2091-1

DO - 10.1007/s11136-018-2091-1

M3 - Article

VL - 28

SP - 1005

EP - 1015

JO - Quality of Life Research

JF - Quality of Life Research

SN - 0962-9343

IS - 4

ER -