Development of a Microsoft Excel tool for applying a factor retention criterion of a dimension coefficient to a survey on patient safety culture

doi:10.1186/s12955-017-0784-8

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Title:	Development of a Microsoft Excel tool for applying a factor retention criterion of a dimension coefficient to a survey on patient safety culture
Authors:	Chien, Tsair-Wei Shao, Yang Jen, Dong-Hui
Contributors:	Chi Mei Med Ctr, Dept Med Res Chia Nan Univ Pharm & Sci, Dept Hosp & Hlth Care Adm Tongji Zhejiang Coll, Dept Elect & Informat Engn, Jiaxing Chi Mei Med Ctr, Dept Chinese Med
Keywords:	Dimension coefficient Patient safety culture survey Visual basic for applications Area under receiver operating characteristic curve Parallel analysis
Date:	2017-10-27
Issue Date:	2018-11-30 15:51:44 (UTC+8)
Publisher:	Biomed Central Ltd
Abstract:	Background: Many quality-of-life studies have been conducted in healthcare settings, but few have used Microsoft Excel to incorporate Cronbach's a with dimension coefficient (DC) for describing a scale's characteristics. To present a computer module that can report a scale's validity, we manipulated datasets to verify a DC that can be used as a factor retention criterion for demonstrating its usefulness in a patient safety culture survey (PSC). Methods: Microsoft Excel Visual Basic for Applications was used to design a computer module for simulating 2000 datasets fitting the Rasch rating scale model. The datasets consisted of (i) five dual correlation coefficients (correl. = 0.3, 0.5, 0.7, 0.9, and 1.0) on two latent traits (i.e., true scores) following a normal distribution and responses to their respective 1/3 and 2/3 items in length; (ii) 20 scenarios of item lengths from 5 to 100; and (iii) 20 sample sizes from 50 to 1000. Each item containing 5-point polytomous responses was uniformly distributed in difficulty across a +/- 2 logit range. Three methods (i.e., dimension interrelation >= 0.7, Horn's parallel analysis (PA) 95% confidence interval, and individual random eigenvalues) were used for determining one factor to retain. DC refers to the binary classification (1 as one factor and 0 as many factors) used for examining accuracy with the indicators sensitivity, specificity, and area under receiver operating characteristic curve (AUC). The scale's reliability and DC were simultaneously calculated for each simulative dataset. PSC real data were demonstrated with DC to interpret reports of the unit-based construct validity using the author-made MS Excel module. Results: The DC method presented accurate sensitivity (=0.96), specificity (=0.92) with a DC criterion (=0.70), and AUC (=0.98) that were higher than those of the two PA methods. PA combined with DC yielded good sensitivity (=0.96), specificity (= 1.0) with a DC criterion (=0.70), and AUC (=0.99). Conclusions: Advances in computer technology may enable healthcare users familiar with MS Excel to apply DC as a factor retention criterion for determining a scale's unidimensionality and evaluating a scale's quality.
Relation:	Health and Quality of Life Outcomes, v.15, pp.2160-
Appears in Collections:	[Dept. of Hospital and Health (including master's program)] Periodical Articles

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