{"title":"Psychometric Analysis of an Integrated Clinical Education Tool for Physical Therapists.","authors":"Marcie Becker, Richard K Shields, Kelly J Sass","doi":"10.1097/JTE.0000000000000341","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Integrated clinical education (ICE) courses require opportunities for practice, assessment of performance, and specific feedback. The purposes of this study were to 1) analyze the internal consistency of a tool for evaluating students during ICE courses, 2) examine the responsiveness of the tool between midterm and final assessments, and 3) develop a model to predict the final score from midterm assessments and explore relationships among the 6 domains.</p><p><strong>Review of literature: </strong>Several clinical education assessment tools have been developed for terminal clinical experiences, but few have focused on the needs of learners during the ICE.</p><p><strong>Subjects: </strong>Eighty-five student assessments were collected from 2 consecutive cohorts of physical therapist students in a first full-time ICE course.</p><p><strong>Methods: </strong>The tool contained 29 items within 6 domains. Items were rated on a 5-point scale from dependent to indirect supervision. Cronbach's alpha was used to analyze the internal consistency of the tool, whereas responsiveness was examined with paired t -test and Cohen's d . A best subsets regression model was used to determine the best combination of midterm variables that predicted the final total scores. Coefficients of determination ( R2 ) were calculated to explore the relationships among domains.</p><p><strong>Results: </strong>The tool was found to have high internal consistency at midterm and final assessment (α = 0.97 and 0.98, respectively). Mean scores increased over time for each domain score and for the total score ( P < .001; d = 1.5). Scores in 3 midterm domains predicted more than 57% of the variance in the final total score.</p><p><strong>Discussion and conclusion: </strong>Results support the use of this tool to measure student performance and growth in a first full-time ICE course. Targeted measurement of students' abilities in ICE courses assists with differentiating formative and summative learning needed to achieve academic success.</p>","PeriodicalId":517432,"journal":{"name":"Journal, physical therapy education","volume":" ","pages":"277-284"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal, physical therapy education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1097/JTE.0000000000000341","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/4/30 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Integrated clinical education (ICE) courses require opportunities for practice, assessment of performance, and specific feedback. The purposes of this study were to 1) analyze the internal consistency of a tool for evaluating students during ICE courses, 2) examine the responsiveness of the tool between midterm and final assessments, and 3) develop a model to predict the final score from midterm assessments and explore relationships among the 6 domains.
Review of literature: Several clinical education assessment tools have been developed for terminal clinical experiences, but few have focused on the needs of learners during the ICE.
Subjects: Eighty-five student assessments were collected from 2 consecutive cohorts of physical therapist students in a first full-time ICE course.
Methods: The tool contained 29 items within 6 domains. Items were rated on a 5-point scale from dependent to indirect supervision. Cronbach's alpha was used to analyze the internal consistency of the tool, whereas responsiveness was examined with paired t -test and Cohen's d . A best subsets regression model was used to determine the best combination of midterm variables that predicted the final total scores. Coefficients of determination ( R2 ) were calculated to explore the relationships among domains.
Results: The tool was found to have high internal consistency at midterm and final assessment (α = 0.97 and 0.98, respectively). Mean scores increased over time for each domain score and for the total score ( P < .001; d = 1.5). Scores in 3 midterm domains predicted more than 57% of the variance in the final total score.
Discussion and conclusion: Results support the use of this tool to measure student performance and growth in a first full-time ICE course. Targeted measurement of students' abilities in ICE courses assists with differentiating formative and summative learning needed to achieve academic success.