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Quality of Life Research
Gepubliceerd in:

01-04-2015 | Brief Communication

Measuring quality of life with fuzzy numbers: in the perspectives of reliability, validity, measurement invariance, and feasibility

Auteurs: Po-Yi Chen, Grace Yao

Gepubliceerd in: Quality of Life Research | Uitgave 4/2015

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Abstract

Purpose

Fuzzy set theory (FST) can improve various aspects of measurement with questionnaires. However, very little is known about how to use FST to measure quality of life (QOL). The main purpose of our study was to find an appropriate fuzzy measure for QOL that, while demonstrating the advantages of FST, can also be compared with mainstream QOL measures, most of which use traditional Likert-type scales.

Methods

Referring to the literature on fuzzy scoring methods, we first revised the measurement scale and scoring method of the traditional WHOQOL-BREF (i.e., a five-point Likert-type scale) to create three versions of a fuzzy WHOQOL-BREF. Then, we examined the psychometric relationships of these three fuzzy measures and the traditional WHOQOL-BREF in a within-subject design.

Results

Our results show that a fuzzy-scales weighted-by-membership (FSWM) version of the WHOQOL-BREF is comparable to the traditional WHOQOL-BREF in that it accepts strong invariance and shows almost perfect agreement. It also demonstrates higher reliability and face validity than the traditional WHOQOL-BREF.

Conclusion

We recommend that future studies examine the use of FSWM to measure QOL.
volgende artikel Factor analyses of a social support scale using two methods
Literatuur
1.
Neisser, U. (1967). Cognitive psychology. New York: Aooletion-Centry-Crofts.
2.
Rabius, P. V., & Black, B. S. (2007). Measuring quality of life in dementia: Purposes, goals, challenges and progress. International Psychogeriatrics, 19(3), 401–407.CrossRef
3.
Schneider, S. (2001). In search of realistic optimism: Meaning, knowledge, and warm fuzziness. American Psychologist, 56, 250–263.CrossRefPubMed
4.
Smithson, M. (1987). Fuzzy set analysis for behavior and social science. New York: Springer.CrossRef
5.
Brown, S. J., & Morley, A. M. (2007). Risk perception, fuzzy representations and comparative optimism. British Journal of Psychology, 98, 578–587.CrossRef
6.
Matt, G. E., Turingan, M. R., Dinh, Q. T., Felsch, J. A., Hovell, M. F., & Gehrman, C. (2003). Improving self-reports of drug-use: Numeric estimates as fuzzy sets. Addiction, 98, 1239–1247.CrossRefPubMed
7.
8.
Yu, S. C., & Yu, M. M. (2007). Fuzzy partial credit scaling: A more valid approach to scoring beck depression inventory II. Social Behavior and Personality, 35(9), 1163–1172.CrossRef
9.
Pryor, R. G., Hesketh, B., & Gleitzman, M. (1989). Making things clearer by making them fuzzy: Counseling illustrations of a fuzzy graphic rating scale. The Career Development Quarterly, 38(2), 136–147.CrossRef
10.
11.
Schwartz, C. E., & Rapkin, B. D. (2004). Reconsidering the psychometrics of quality of life assessment in light of response shift and appraisal. Health and Quality of Life Outcomes, 2, 16–27.CrossRefPubMedCentralPubMed
12.
O’Leary, T. E., Diller, L., & Recklitis, C. J. (2007). The effects of response bias on self-reported quality of life among childhood cancer survivors. Quality of Life Research, 16, 1211–1220.CrossRefPubMed
13.
Hesketh, B., Pryor, R., & Gleitzman, M., & Hesketh, T. (1988). Practical applications and psychometric evaluation of a computerized fuzzy graphic ration scale. In: T. Zetenyi (Eds.), Fuzzy Sets in Psychology (pp. 425–454). Amsterdam: Elsevier, North-Holland.
14.
Lin, Y. H. (2002). The construction of fuzzy linguistics numbers for questionnaire and its empirical study. Survey Research-Method and Application, 11, 31–68.
15.
Costas, C. S. L., Maranon, P. P., & Cabrera, J. A. H. (1994). Application of diffuse measurement to the evaluation of psychological structures. Quality and Quantity, 28(3), 305–313.CrossRef
16.
The WHOQOL-Taiwan Group. (2005). The User’s Manual of the Development of the WHOQOL-BREF Taiwan Version (2nd ed.). Taipei: Taiwan WHOQOL Group.
17.
Muthen, L. K., & Muthen, B. O. (2002). How to use a Monte Carlo study to decide on sample size and determine power. Structural Equation Modeling, 4, 599–620.CrossRef
18.
Beauducel, A., & Herzberg, P. Y. (2006). On the performance of maximum likelihood versus means and variance adjusted weighted least squares estimation in CFA. Structural Equation Modeling, 13(2), 186–203.CrossRef
19.
Rhemtulla, M., Brosseau-Liard, P. É., & Savalei, V. (2012). When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions. Psychological Methods, 17(3), 354–373.CrossRefPubMed
20.
Meade, A. W., & Kroustalis, C. M. (2006). Problem with item parceling for confirmatory factor analytic tests of measurement invariance. Organizational Research Methods, 9(3), 369–403.CrossRef
21.
Hollen, P. J., Gralla, R. J., Kris, M. G., McCoy, S., Donaldson, D. W., & Moinpour, C. M. (2005). A comparison of visual analogue and numerical rating scale formats for the Lung Cancer Symptom Scale (LCSS): Does format affect patient ratings of symptoms and quality of life? Quality of Life Research, 14(3), 837–847.CrossRefPubMed
22.
23.
Revelle, W., & Zinbarg, R. E. (2009). Coefficients alpha, beta, omega and the glb: Comments on Sijtsma. Psychometrika, 74(1), 145–154.CrossRef
24.
Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9(2), 233–255.CrossRef
25.
Little, T. D. (1997). Mean and covariance structures (MACS) analyses of cross-cultural data: Practical and theoretical issues. Multivariate Behavioral Research, 32, 53–76.CrossRef
Metagegevens
Titel
Measuring quality of life with fuzzy numbers: in the perspectives of reliability, validity, measurement invariance, and feasibility
Auteurs
Po-Yi Chen
Grace Yao
Publicatiedatum
01-04-2015
Uitgeverij
Springer International Publishing
Gepubliceerd in
Quality of Life Research / Uitgave 4/2015
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-014-0816-3

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