A User-Centered Evaluation of Wayfinding in Outpatient Units of Public Hospitals in Malaysia: UMMC as a Case Study

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Abstract

The difficulty of finding one’s way in a complex structure has been a long-standing issue of many buildings with highly institutionalized functions. This has been especially observed in hospital buildings as an issue that can cause various adverse outcomes for both the institution and the user. Therefore, regular evaluation of the existing wayfinding system and its efficacy is needed. This study aimed to evaluate the wayfinding system efficacy in an outpatient unit of a Malaysian public hospital in order to provide information that could help guide future upgrade initiatives for existing healthcare facilities’ wayfinding systems. This study employed a user survey questionnaire to evaluate the wayfinding system currently in use and investigate users’ needs for a better wayfinding system. The statistical analysis of the gathered data indicated a higher than average level of dissatisfaction regarding the existing wayfinding system. The findings of the study suggest the need for an upgrade in the physical environment. Furthermore, the results of this study suggest the need to devise a set of guidelines to be employed when designing wayfinding systems in Malaysia’s public hospitals.

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Correlation Coefficients

Patrick Schober, Christa Boer, Lothar A Schwarte (2018)

Correlation in the broadest sense is a measure of an association between variables. In correlated data, the change in the magnitude of 1 variable is associated with a change in the magnitude of another variable, either in the same (positive correlation) or in the opposite (negative correlation) direction. Most often, the term correlation is used in the context of a linear relationship between 2 continuous variables and expressed as Pearson product-moment correlation. The Pearson correlation coefficient is typically used for jointly normally distributed data (data that follow a bivariate normal distribution). For nonnormally distributed continuous data, for ordinal data, or for data with relevant outliers, a Spearman rank correlation can be used as a measure of a monotonic association. Both correlation coefficients are scaled such that they range from -1 to +1, where 0 indicates that there is no linear or monotonic association, and the relationship gets stronger and ultimately approaches a straight line (Pearson correlation) or a constantly increasing or decreasing curve (Spearman correlation) as the coefficient approaches an absolute value of 1. Hypothesis tests and confidence intervals can be used to address the statistical significance of the results and to estimate the strength of the relationship in the population from which the data were sampled. The aim of this tutorial is to guide researchers and clinicians in the appropriate use and interpretation of correlation coefficients.

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A psychometric toolbox for testing validity and reliability.

Holli DeVon, Michelle Block, Patricia Moyle-Wright … (2007)

To review the concepts of reliability and validity, provide examples of how the concepts have been used in nursing research, provide guidance for improving the psychometric soundness of instruments, and report suggestions from editors of nursing journals for incorporating psychometric data into manuscripts. CINAHL, MEDLINE, and PsycINFO databases were searched using key words: validity, reliability, and psychometrics. Nursing research articles were eligible for inclusion if they were published in the last 5 years, quantitative methods were used, and statistical evidence of psychometric properties were reported. Reports of strong psychometric properties of instruments were identified as well as those with little supporting evidence of psychometric soundness. Reports frequently indicated content validity but sometimes the studies had fewer than five experts for review. Criterion validity was rarely reported and errors in the measurement of the criterion were identified. Construct validity remains underreported. Most reports indicated internal consistency reliability (alpha) but few reports included reliability testing for stability. When retest reliability was asserted, time intervals and correlations were frequently not included. Planning for psychometric testing through design and reducing nonrandom error in measurement will add to the reliability and validity of instruments and increase the strength of study findings. Underreporting of validity might occur because of small sample size, poor design, or lack of resources. Lack of information on psychometric properties and misapplication of psychometric testing is common in the literature.