Although Item Response Theory (IRT) has been recommended for helping advance interprofessional education (IPE) research, its use remains limited. This may be partly explained by potential misconceptions regarding IRT`s “limitation” to cross-sectional data. The aim of this study is to demonstrate how Item Response Theory (IRT) can be applied effectively in before-and-after designs in IPE research. Specifically, a two-week before-after design with survey methodology using the Extended Professional Identity Scale (EPIS), an interprofessional identity measure, was conducted among n = 146 mixed health-science students. Results indicated that EPIS increased significantly before-after intervention by.74 standardised mean differences, t146 = 7.73, p
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To evaluate the effectiveness of Employee Assistance Program (EAP) interventions, the Workplace Outcome Suite (WOS) was developed. This study aims to determine if the new WOS 5-item version can be used to approximate the WOS 25-item version without excessive loss of reliability, validity, or sensitivity. A quantitative psychometric evaluation study design was employed. Secondary data analysis of the WOS 25-item questionnaire was conducted before and after EAP services were delivered to participants. This analysis used 2046 data responses from 1023 participants. Quantitative data analysis included descriptive statistics, Cohen’s d, paired t-test, the Wilcoxon signed-rank (non-parametric test), and bivariate factor analysis. Findings demonstrate that the WOS 5-item version can successfully detect changes in workplace functioning. Within all five constructs, users’ scores improved after EAP interventions, indicating improvement in mental health. Significant changes were detected for absenteeism, presenteeism, work engagement, and workplace distress. Bivariate correlation results indicate the WOS 5-item is a good representation of the 25-item version. There are strong correlations between each item on the WOS-5 and the corresponding items in each construct on the WOS-25. This evidence suggests the WOS 5-item version can be used to approximate the WOS 25-item version without excessive loss of reliability, validity, or sensitivity.
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Psychologists, psycholinguists, and other researchers using language stimuli have been struggling for more than 30 years with the problem of how to analyze experimental data that contain two crossed random effects (items and participants). The classical analysis of variance does not apply; alternatives have been proposed but have failed to catch on, and a statistically unsatisfactory procedure of using two approximations (known as F 1 and F 2) has become the standard. A simple and elegant solution using mixed model analysis has been available for 15 years, and recent improvements in statistical software have made mixed models analysis widely available. The aim of this article is to increase the use of mixed models by giving a concise practical introduction and by giving clear directions for undertaking the analysis in the most popular statistical packages. The article also introduces the djmixed add-on package for SPSS, which makes entering the models and reporting their results as straightforward as possible.
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