Item reduction and validation of the Chinese version of diabetes quality-of-life measure (DQOL)

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Abstract

Background

The Diabetes Quality-of-Life (DQOL) Measure is a 46-item diabetes-specific quality of life instrument. The original English version of the DQOL has been translated into Chinese after cultural adaption, and the Chinese DQOL has been validated in the Chinese diabetic patient population and used in diabetes-related studies. There are two recognized problems with the Chinese DQOL: 1) the instrument is too long, and 2) the non-response rate of certain items is relatively high. This study aimed to develop and validate a short version for the Chinese DQOL.

Methods

Item reduction was conducted based on the classical test theory (CTT) and item response theory (IRT), each combined with exploratory factor analysis (EFA). The confirmatory factor analysis (CFA) and Spearman correlation coefficient were employed in validating the short versions.

Results

Both the study sample ( n = 2,886) and the validation sample ( n = 2,286) were from a longitudinal observation study of Chinese type 2 diabetic patients. The CTT kept 32 items, and the IRT kept 24 items from the original 46-item version. The two short versions were comparable in psychometric properties.

Conclusion

The 24-item IRT-based short version of the Chinese DQOL was selected as the preferred short version because it imposes a lower burden on patients without compromising the psychometric properties of the instrument.

Electronic supplementary material

The online version of this article (10.1186/s12955-018-0905-z) contains supplementary material, which is available to authorized users.

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Most cited references 27

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A second generation little jiffy

Henry F. Kaiser (1970)

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TESTS OF SIGNIFICANCE IN FACTOR ANALYSIS

J Bartlett (1950)

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Applying item response theory (IRT) modeling to questionnaire development, evaluation, and refinement.

Maria Orlando Edelen, Bryce B Reeve (2007)

Health outcomes researchers are increasingly applying Item Response Theory (IRT) methods to questionnaire development, evaluation, and refinement efforts. To provide a brief overview of IRT, to review some of the critical issues associated with IRT applications, and to demonstrate the basic features of IRT with an example. Example data come from 6,504 adolescent respondents in the National Longitudinal Study of Adolescent Health public use data set who completed to the 19-item Feelings Scale for depression. The sample was split into a development and validation sample. Scale items were calibrated in the development sample with the Graded Response Model and the results were used to construct a 10-item short form. The short form was evaluated in the validation sample by examining the correspondence between IRT scores from the short form and the original, and by comparing the proportion of respondents identified as depressed according to the original and short form observed cut scores. The 19 items varied in their discrimination (slope parameter range: .86-2.66), and item location parameters reflected a considerable range of depression (-.72-3.39). However, the item set is most discriminating at higher levels of depression. In the validation sample IRT scores generated from the short and long forms were correlated at .96 and the average difference in these scores was -.01. In addition, nearly 90% of the sample was classified identically as at risk or not at risk for depression using observed score cut points from the short and long forms. When used appropriately, IRT can be a powerful tool for questionnaire development, evaluation, and refinement, resulting in precise, valid, and relatively brief instruments that minimize response burden.

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All references

Author and article information

Contributors

Xuejing Jin: jinx23@mcmaster.ca

Gordon G. Liu: gordonliu@nsd.pku.edu.cn

Hertzel C. Gerstein: gerstein@mcmaster.ca

Mitchell A. H. Levine: levinem@mcmaster.ca

Kathleen Steeves: steeveka@mcmaster.ca

Haijing Guan: guanhaijing@nsd.pku.edu.cn

Hongchao Li: lihongchao@cpu.edu.cn

Feng Xie:

ORCID: http://orcid.org/0000-0003-3454-6266

fengxie@mcmaster.ca

Journal

Journal ID (nlm-ta): Health Qual Life Outcomes

Journal ID (iso-abbrev): Health Qual Life Outcomes

Title: Health and Quality of Life Outcomes

Publisher: BioMed Central (London )

ISSN (Electronic): 1477-7525

Publication date (Electronic): 27 April 2018

Publication date PMC-release: 27 April 2018

Publication date Collection: 2018

Volume: 16

Electronic Location Identifier: 78

Affiliations

[1 ]ISNI 0000 0004 1936 8227, GRID grid.25073.33, Department of Health Research Methods, Evidence, and Impact, , McMaster University, ; 1280 Main St W, Hamilton, ON L8S 4K1 Canada

[2 ]ISNI 0000 0001 2256 9319, GRID grid.11135.37, China Center for Health Economic Research, , Peking University, ; Beijing, 100800 China

[3 ]ISNI 0000 0001 2256 9319, GRID grid.11135.37, National School of Development, , Peking University, ; Beijing, 100800 China

[4 ]ISNI 0000 0004 1936 8227, GRID grid.25073.33, Department of Medicine, , McMaster University, ; Hamilton, ON L8S 4K1 Canada

[5 ]ISNI 0000 0004 1936 8227, GRID grid.25073.33, Department of Sociology, , McMaster University, ; Hamilton, ON L8S 4K1 Canada

[6 ]ISNI 0000 0001 2256 9319, GRID grid.11135.37, School of Pharmaceutical Science, , Peking University, ; Beijing, 100800 China

[7 ]ISNI 0000 0000 9776 7793, GRID grid.254147.1, School of International Pharmaceutical Business, , China Pharmaceutical University, ; Nanjing, 211198 Jiangsu China

[8 ]ISNI 0000 0001 0742 7355, GRID grid.416721.7, Centre for Evaluation of Medicines, Father Sean O’Sullivan Research Centre, , St. Joseph’s Healthcare Hamilton, ; Hamilton, L8N 4A6 Canada

Author information

Feng Xie http://orcid.org/0000-0003-3454-6266

Article

Publisher ID: 905

DOI: 10.1186/s12955-018-0905-z

PMC ID: 5921810

PubMed ID: 29703205

SO-VID: aea4022d-d56f-46f0-abde-21bb765d610b

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 30 May 2017

Date accepted : 18 April 2018

Funding

Funded by: Guangzhou Zhongyi Pharmaceutical Co Ltd (CN)

Custom metadata

ScienceOpen disciplines: Health & Social care

Keywords: item response theory,classical test theory,factor analysis,diabetes,quality of life,psychometrics

Data availability:

ScienceOpen disciplines: Health & Social care

Keywords: item response theory, classical test theory, factor analysis, diabetes, quality of life, psychometrics

Item reduction and validation of the Chinese version of diabetes quality-of-life measure (DQOL)

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Abstract

Background

Methods

Results

Conclusion

Electronic supplementary material

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Karger: Nutrition and Dietetics

Most cited references 27

A second generation little jiffy

TESTS OF SIGNIFICANCE IN FACTOR ANALYSIS

Applying item response theory (IRT) modeling to questionnaire development, evaluation, and refinement.

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Contributors

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Affiliations

Author information

Article

History

Funding

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