Tamer Al-Ghraiybah, Jenny Sim, Ritin Fernandez, Luise Lago
{"title":"管理护士编制调查中的缺失和错误数据。","authors":"Tamer Al-Ghraiybah, Jenny Sim, Ritin Fernandez, Luise Lago","doi":"10.7748/nr.2023.e1878","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Analysis can be problematic in research when data are missing or erroneous. Various methods are available for managing missing and erroneous data, but little is known about which are the best to use when conducting cross-sectional surveys of nurse staffing.</p><p><strong>Aim: </strong>To explore how missing and erroneous data were managed in a study that involved a cross-sectional survey of nurse staffing.</p><p><strong>Discussion: </strong>The article describes a study that used a cross-sectional survey to estimate the ratio of registered nurses to patients, using self-reported data by nurses. It details the techniques used in the study to manage missing and erroneous data and presents the results of the survey before and after the treatment of missing data.</p><p><strong>Conclusion: </strong>Managing missing data effectively and reporting procedures transparently reduces the possibility of bias in a study's results and increases its reproducibility. Nurse researchers need to understand the methods available to handle missing and erroneous data. Surveys must contain unambiguous questions, as every participant should have the same understanding of a question's meaning.</p><p><strong>Implication for practice: </strong>Researchers should pilot surveys - even when using validated tools - to ensure participants interpret the questions as intended.</p>","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Managing missing and erroneous data in nurse staffing surveys.\",\"authors\":\"Tamer Al-Ghraiybah, Jenny Sim, Ritin Fernandez, Luise Lago\",\"doi\":\"10.7748/nr.2023.e1878\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Analysis can be problematic in research when data are missing or erroneous. Various methods are available for managing missing and erroneous data, but little is known about which are the best to use when conducting cross-sectional surveys of nurse staffing.</p><p><strong>Aim: </strong>To explore how missing and erroneous data were managed in a study that involved a cross-sectional survey of nurse staffing.</p><p><strong>Discussion: </strong>The article describes a study that used a cross-sectional survey to estimate the ratio of registered nurses to patients, using self-reported data by nurses. It details the techniques used in the study to manage missing and erroneous data and presents the results of the survey before and after the treatment of missing data.</p><p><strong>Conclusion: </strong>Managing missing data effectively and reporting procedures transparently reduces the possibility of bias in a study's results and increases its reproducibility. Nurse researchers need to understand the methods available to handle missing and erroneous data. Surveys must contain unambiguous questions, as every participant should have the same understanding of a question's meaning.</p><p><strong>Implication for practice: </strong>Researchers should pilot surveys - even when using validated tools - to ensure participants interpret the questions as intended.</p>\",\"PeriodicalId\":1,\"journal\":{\"name\":\"Accounts of Chemical Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":16.4000,\"publicationDate\":\"2023-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounts of Chemical Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7748/nr.2023.e1878\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/3/30 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7748/nr.2023.e1878","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/3/30 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Managing missing and erroneous data in nurse staffing surveys.
Background: Analysis can be problematic in research when data are missing or erroneous. Various methods are available for managing missing and erroneous data, but little is known about which are the best to use when conducting cross-sectional surveys of nurse staffing.
Aim: To explore how missing and erroneous data were managed in a study that involved a cross-sectional survey of nurse staffing.
Discussion: The article describes a study that used a cross-sectional survey to estimate the ratio of registered nurses to patients, using self-reported data by nurses. It details the techniques used in the study to manage missing and erroneous data and presents the results of the survey before and after the treatment of missing data.
Conclusion: Managing missing data effectively and reporting procedures transparently reduces the possibility of bias in a study's results and increases its reproducibility. Nurse researchers need to understand the methods available to handle missing and erroneous data. Surveys must contain unambiguous questions, as every participant should have the same understanding of a question's meaning.
Implication for practice: Researchers should pilot surveys - even when using validated tools - to ensure participants interpret the questions as intended.
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.