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http://dx.doi.org/10.4069/kjwhn.2021.05.18

Psychometric properties of an instrument 2: structural validity, internal consistency, and cross-cultural validity/measurement invariance  

Lee, Eun-Hyun (Graduate School of Public Health, Ajou University)
Publication Information
Women's Health Nursing / v.27, no.2, 2021 , pp. 69-74 More about this Journal
Abstract
Structural validity, internal consistency, and cross-cultural validity/measurement invariance are psychometric properties of the internal structure of an instrument. In psychometric studies published in Korean nursing journals, structural validity has mainly been assessed using confirmatory factor analysis. Cross-cultural validity/measurement invariance has rarely been evaluated. It is recommended for Korean nursing researchers to evaluate the internal structure of instruments using a greater variety of methods, such as item response theory, Rasch analysis, multi-group confirmatory factor analysis, and differential item functioning.
Keywords
Cultural validity; Internal consistency; Instrument; Psychometrics; Structural validity;
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1 Linacre JM. Winsteps® Rasch measurement computer program user's guide. Beaverton, OR: Winsteps.com; 2019.
2 Gomez R, Summers M, Summers A, Wolf A, Summers JJ. Depression Anxiety Stress Scales-21: Factor structure and test-retest invariance, and temporal stability and uniqueness of latent factors in older adults. J Psychopathol Behav Assess. 2014;36(2):308-317. https://doi.org/10.1007/s10862-013-9391-0   DOI
3 Mardia KV. Measures of multivariate skewness and kurtosis with applications. Biometrika. 1970;57(3):519-530. https://doi.org/10.2307/2334770   DOI
4 Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Modeling. 1999;6(1):1-55. https://doi.org/10.1080/10705519909540118   DOI
5 Polit DF, Yang FM. Measurement and the measurement of change. Philadelphia, PA: Wolters Kluwer; 2016. p. 350.
6 MacCallum RC, Browne MW, Sugawara HM. Power analysis and determination of sample size for covariance structure modeling. Psychol Methods. 1996;1(2):130-149. https://psycnet.apa.org/doi/10.1037/1082-989X.1.2.130   DOI
7 Lee EH, van der Bijl J, Shortridge-Baggett LM, Han SJ, Moon SH. Psychometric properties of the diabetes management self-efficacy scale in Korean patients with type 2 diabetes. Int J Endocrinol. 2015;2015:780701. https://doi.org/10.1155/2015/780701   DOI
8 Lee EH, Moon SH, Cho MS, Park ES, Kim SY, Han JS, et al. The 21-item and 12-item versions of the Depression Anxiety Stress Scales: psychometric evaluation in a Korean population. Asian Nurs Res (Korean Soc Nurs Sci). 2019;13(1):30-37. https://doi.org/10.1016/j.anr.2018.11.006   DOI
9 Chen H, Nakatani H, Liu T, Zhao H, Xie D. The core knowledge and skills of nursing competency regarding mealtime assistance for hemiplegic patients in China. Asian Nurs Res (Korean Soc Nurs Sci). 2020;14(2):129-135. https://doi.org/10.1016/j.anr.2020.04.005   DOI
10 de Vet HCW, Terwee CB, Mokkink LB, Knol DL. Measurement in medicine: a practical guide. London: Cambridge University Press; 2011. p. 338.
11 Lee EH, Lee YW, Lee KW, Nam M, Kim SH. A new comprehensive diabetes health literacy scale: development and psychometric evaluation. Int J Nurs Stud. 2018;88:1-8. https://doi.org/10.1016/j.ijnurstu.2018.08.002   DOI
12 Lindkvist EB, Kristensen LJ, Sildorf SM, Kreiner S, Svensson J, Mose AH, et al. A Danish version of self-efficacy in diabetes self-management: a valid and reliable questionnaire affected by age and sex. Pediatr Diabetes. 2018;19(3):544-552. https://doi.org/10.1111/pedi.12601   DOI
13 Mokkink LB, Terwee CB, Patrick DL, Alonso J, Stratford PW, Knol DL, et al. The COSMIN study reached international consensus on taxonomy, terminology, and definitions of measurement properties for health-related patient-reported outcomes. J Clin Epidemiol. 2010;63(7):737-745. https://doi.org/10.1016/j.jclinepi.2010.02.006   DOI
14 Byrne BM. Structural equation modeling with AMOS: basic concepts, applications, and programming. New York: Routledge; 2016. p. 86-89.
15 Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate data analysis. 7th ed. London: Pearson; 2014. p. 600-638.
16 Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. 1981;18(1):39-50. https://doi.org/10.1177/002224378101800104   DOI
17 Furr RM. Psychometrics: an introduction. 3rd ed. Thousand Oaks, CA: Sage; 2018. p. 401-4710.
18 Lee EH, Kang EH, Kang HJ. Evaluation of studies on the measurement properties of self-reported instruments. Asian Nurs Res (Korean Soc Nurs Sci). 2020;14(5):267-276. https://doi.org/10.1016/j.anr.2020.11.004   DOI
19 Zhang J, Zhou X, Wang H, Luo Y, Li W. Development and validation of humanistic practice ability of nursing scale. Asian Nurs Res (Korean Soc Nurs Sci). 2021;S1976-1317(21)00001-3:https://doi.org/10.1016/j.anr.2020.12
20 Yu DS, De Maria M, Barbaranelli C, Vellone E, Matarese M, Ausili D, et al. Cross-cultural applicability of the Self-Care Self-Efficacy Scale in a multi-national study. J Adv Nurs. 2021;77(2):681-692. https://doi.org/10.1111/jan.14617   DOI
21 Kuder GF, Richardson MW. The theory of the estimation of test reliability. Psychometrika. 1937;2(3):151-160. https://doi.org/10.1007/BF02288391   DOI