Chris Dunn, Doyanne Darnell, Sheng Kung Michael Yi, Mark Steyvers, Kristin Bumgardner, Sarah Peregrine Lord, Zac Imel, David C Atkins
{"title":"我们应该相信我们对动机性访谈顾问熟练程度的判断吗?低评级机构间可靠性的影响。","authors":"Chris Dunn, Doyanne Darnell, Sheng Kung Michael Yi, Mark Steyvers, Kristin Bumgardner, Sarah Peregrine Lord, Zac Imel, David C Atkins","doi":"10.5195/mitrip.2014.43","DOIUrl":null,"url":null,"abstract":"<p><p>Standardized rating systems are often used to evaluate the proficiency of Motivational Interviewing (MI) counselors. The published inter-rater reliability (degree of coder agreement) in many studies using these instruments has varied a great deal; some studies report MI proficiency scores that have only fair inter-rater reliability, and others report scores with excellent reliability. How much can we to trust the scores with fair versus excellent reliability? Using a Monte Carlo statistical simulation, we compared the impact of fair (0.50) versus excellent (0.90) reliability on the error rates of falsely judging a given counselor as MI proficient or not proficient. We found that improving the inter-rater reliability of any given score from 0.5 to 0.9 would cause a marked reduction in proficiency judgment errors, a reduction that in some MI evaluation situations would be critical. We discuss some practical tradeoffs inherent in various MI evaluation situations, and offer suggestions for applying findings from formal MI research to problems faced by real-world MI evaluators, to help them minimize the MI proficiency judgment errors bearing the greatest cost.</p>","PeriodicalId":89699,"journal":{"name":"Motivational interviewing : training, research, implementation, practice","volume":"1 3","pages":"38-41"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5008854/pdf/nihms812516.pdf","citationCount":"4","resultStr":"{\"title\":\"Should we trust our judgments about the proficiency of Motivational Interviewing counselors? A glimpse at the impact of low inter-rater reliability.\",\"authors\":\"Chris Dunn, Doyanne Darnell, Sheng Kung Michael Yi, Mark Steyvers, Kristin Bumgardner, Sarah Peregrine Lord, Zac Imel, David C Atkins\",\"doi\":\"10.5195/mitrip.2014.43\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Standardized rating systems are often used to evaluate the proficiency of Motivational Interviewing (MI) counselors. The published inter-rater reliability (degree of coder agreement) in many studies using these instruments has varied a great deal; some studies report MI proficiency scores that have only fair inter-rater reliability, and others report scores with excellent reliability. How much can we to trust the scores with fair versus excellent reliability? Using a Monte Carlo statistical simulation, we compared the impact of fair (0.50) versus excellent (0.90) reliability on the error rates of falsely judging a given counselor as MI proficient or not proficient. We found that improving the inter-rater reliability of any given score from 0.5 to 0.9 would cause a marked reduction in proficiency judgment errors, a reduction that in some MI evaluation situations would be critical. We discuss some practical tradeoffs inherent in various MI evaluation situations, and offer suggestions for applying findings from formal MI research to problems faced by real-world MI evaluators, to help them minimize the MI proficiency judgment errors bearing the greatest cost.</p>\",\"PeriodicalId\":89699,\"journal\":{\"name\":\"Motivational interviewing : training, research, implementation, practice\",\"volume\":\"1 3\",\"pages\":\"38-41\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5008854/pdf/nihms812516.pdf\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Motivational interviewing : training, research, implementation, practice\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5195/mitrip.2014.43\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Motivational interviewing : training, research, implementation, practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5195/mitrip.2014.43","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Should we trust our judgments about the proficiency of Motivational Interviewing counselors? A glimpse at the impact of low inter-rater reliability.
Standardized rating systems are often used to evaluate the proficiency of Motivational Interviewing (MI) counselors. The published inter-rater reliability (degree of coder agreement) in many studies using these instruments has varied a great deal; some studies report MI proficiency scores that have only fair inter-rater reliability, and others report scores with excellent reliability. How much can we to trust the scores with fair versus excellent reliability? Using a Monte Carlo statistical simulation, we compared the impact of fair (0.50) versus excellent (0.90) reliability on the error rates of falsely judging a given counselor as MI proficient or not proficient. We found that improving the inter-rater reliability of any given score from 0.5 to 0.9 would cause a marked reduction in proficiency judgment errors, a reduction that in some MI evaluation situations would be critical. We discuss some practical tradeoffs inherent in various MI evaluation situations, and offer suggestions for applying findings from formal MI research to problems faced by real-world MI evaluators, to help them minimize the MI proficiency judgment errors bearing the greatest cost.