{"title":"Assessing the Inclusion of Foil Items in a Scale to Measure Recognition of Health Messages.","authors":"Helen W Sullivan, Wen-Hung Chen, Kevin R Betts","doi":"10.1080/19312458.2020.1768520","DOIUrl":null,"url":null,"abstract":"<p><p>Researchers frequently measure recognition of information in health messages by presenting participants with statements that were or were not in a message and then asking them to identify which were presented and which were not. Recognition scales are then calculated by summing the correct responses to both the true items and foils, or by summing the correct responses to the true items only. We used a sequence of psychometric analyses, including factor analysis and item response theory (IRT) analysis, to evaluate two recognition measures of this type, using data from previously published studies. We found that foils are less associated with true items than true items are with one another, or more practically, that foils are less associated with the underlying dimension of interest. These results provide researchers with insight into how recognition items function, as well as a better analytic approach for use in future studies.</p>","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":"15 3","pages":""},"PeriodicalIF":6.3000,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8488547/pdf/nihms-1595688.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communication Methods and Measures","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1080/19312458.2020.1768520","RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMMUNICATION","Score":null,"Total":0}
引用次数: 0
Abstract
Researchers frequently measure recognition of information in health messages by presenting participants with statements that were or were not in a message and then asking them to identify which were presented and which were not. Recognition scales are then calculated by summing the correct responses to both the true items and foils, or by summing the correct responses to the true items only. We used a sequence of psychometric analyses, including factor analysis and item response theory (IRT) analysis, to evaluate two recognition measures of this type, using data from previously published studies. We found that foils are less associated with true items than true items are with one another, or more practically, that foils are less associated with the underlying dimension of interest. These results provide researchers with insight into how recognition items function, as well as a better analytic approach for use in future studies.
期刊介绍:
Communication Methods and Measures aims to achieve several goals in the field of communication research. Firstly, it aims to bring attention to and showcase developments in both qualitative and quantitative research methodologies to communication scholars. This journal serves as a platform for researchers across the field to discuss and disseminate methodological tools and approaches.
Additionally, Communication Methods and Measures seeks to improve research design and analysis practices by offering suggestions for improvement. It aims to introduce new methods of measurement that are valuable to communication scientists or enhance existing methods. The journal encourages submissions that focus on methods for enhancing research design and theory testing, employing both quantitative and qualitative approaches.
Furthermore, the journal is open to articles devoted to exploring the epistemological aspects relevant to communication research methodologies. It welcomes well-written manuscripts that demonstrate the use of methods and articles that highlight the advantages of lesser-known or newer methods over those traditionally used in communication.
In summary, Communication Methods and Measures strives to advance the field of communication research by showcasing and discussing innovative methodologies, improving research practices, and introducing new measurement methods.