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| data analysis in nursing research: Nursing Research Using Data Analysis Mary De Chesnay, 2014-12-05 This is a concise, step-by-step guide to conducting qualitative nursing research using various forms of data analysis. It is part of a unique series of books devoted to seven different qualitative designs and methods in nursing, written for both novice researchers and specialists seeking to develop or expand their competency. This practical resource encompasses such methodologies as content analysis, a means of organizing and interpreting data to elicit themes and concepts; discourse analysis, used to analyze language to understand social or historical context; narrative analysis, in which the researcher seeks to understand human experience through participant stories; and focus groups and case studies, used to understand the consensus of a group or the experience of an individual and his or her reaction to a difficult situation such as disease or trauma. Written by a noted qualitative research scholar and contributing experts, the book describes the philosophical basis for conducting research using data analysis and delivers an in-depth plan for applying its methodologies to a particular study, including appropriate methods, ethical considerations, and potential challenges. It presents practical strategies for solving problems related to the conduct of research using the various forms of data analysis and presents a rich array of case examples from published nursing research. These include author analyses to support readers in decision making regarding their own projects. The book embraces such varied topics as data security in qualitative research, the image of nursing in science fiction literature, the trajectory of research in several nursing studies throughout Africa, and many others. Focused on the needs of both novice researchers and specialists, it will be of value to health institution research divisions, in-service educators and students, and graduate nursing educators and students. Key Features: Explains how to conduct nursing research using content analysis, discourse analysis, narrative analysis, and focus groups and case studies Presents state-of-the-art designs and protocols Focuses on solving practical problems related to the conduct of research Features rich nursing exemplars in a variety of health/mental health clinical settings in the United States and internationally |
| data analysis in nursing research: Statistics and Data Analysis for Nursing Research Denise F. Polit, 2013-10-03 The second edition of Statistics and Data Analysis for Nursing, uses a conversational style to teach students how to use statistical methods and procedures to analyse research findings. Students are guided through the complete analysis process from performing a statistical analysis to the rationale behind doing so. In addition, management of data, including how and why to recode variables for analysis, how to clean data, and how to work around missing data, is discussed. The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed. |
| data analysis in nursing research: Statistics and Data Analysis for Nursing Denise Polit, Eileen Lake, 2021-06-16 |
| data analysis in nursing research: Nursing Research and Statistics Suresh Sharma, 2010-09-17 Nursing Research and Statistics |
| data analysis in nursing research: Statistics for Nursing Research Susan K. Grove, Daisha J. Cipher, 2016-02-01 Understand the statistical methods used in nursing research articles! Statistics for Nursing Research: A Workbook for Evidence-Based Practice, 2nd Edition helps you interpret and analyze the statistical data found in health sciences research articles. Practical exercises show how to critically appraise sampling and measurement techniques, evaluate results, and conduct a power analysis for a study. Written by nursing statistics experts Susan Grove and Daisha Cipher, this is the only statistics workbook for nursing to include research examples from both nursing and medical literature for a complete perspective on health sciences research. Comprehensive coverage includes exercises that address all common techniques of sampling, measurement, and statistical analysis that you are likely to see in nursing and medical literature. A literature-based approach incorporates a relevant research article into each exercise/chapter, with key excerpts. 45 sampling, measurement, and statistical analysis exercises provide a practical review of both basic and advanced techniques, and prepare you to apply statistics to nursing practice. Consistent format for all chapters facilitates quick review and easier learning, covering the statistical technique in review, results from a research article, and study questions. Study questions in each chapter help you apply concepts to clinical practice. Questions to Be Graded in each chapter may be completed and submitted online, to assess your mastery of key statistical techniques. A concise index makes it easy to locate information quickly. NEW examples show the latest, high-quality research studies. NEW! Expanded coverage helps undergraduate students apply the information learned in statistics and research courses, serves as a refresher/review for graduate students, and also helps in critically appraising studies to determine whether their findings may be used in evidence-based practice. NEW! Understanding Statistical Methods section includes exercises to help in understanding the levels of measurement (nominal, ordinal, interval, and ratio) and in appraising the samples and measurement methods in studies. NEW! Conducting and Interpreting Statistical Analyses section includes exercises to help in understanding the power analysis and how to conduct a power analysis for a study, showing how to determine the most appropriate statistical method(s) for analyzing data for a class project, for a clinical agency project, or for an actual research study. NEW! Answers to study questions are located in the back of the book. |
| data analysis in nursing research: The Application of Content Analysis in Nursing Science Research Helvi Kyngäs, Kristina Mikkonen, Maria Kääriäinen, 2019-10-31 This book provides principles on content analysis and its application into development of nursing theory. It offers clear guidance to students, lecturers and researchers to gain a deeper understanding of the method of content analysis, its implementation into their own research and criteria of trustworthiness evaluation. The book is written in user-friendly language with provided research examples and cases, and the content is illustrated by figures and tables. The authors offer their expertise in providing a well thought through explanation of content analysis in didactical style, which will enhance university education. The book includes highly experienced researchers who have published articles on content analysis and the trustworthiness of the method with more than 10 000 citations. Divided into two parts, this book explores the application of content analysis into nursing science. The first part presents the philosophical position of content analysis, inductive and deductive methods of using content analysis, trustworthiness of the method, and ethical consideration of using content analysis. The second part informs on the theory development based on content analysis, conceptualization of the concepts of content analysis into generation of items and instrument development, and statistical testing of a hypothetical model. The last chapter shows a new approach to using content analysis in systematic reviews and quality evaluation of methodology within systematic review process. The book is an essential tool for nursing science, providing instruction on key methodological elements in order to provide rigorously conducted empirical research for clinical practice and nursing education. |
| data analysis in nursing research: Nursing Research Using Data Analysis Mary De Chesnay, PhD, RN, PMHCNS-BC, FAAN, 2014-12-05 This is a concise, step-by-step guide to conducting qualitative nursing research using various forms of data analysis. It is part of a unique series of books devoted to seven different qualitative designs and methods in nursing, written for both novice researchers and specialists seeking to develop or expand their competency. This practical resource encompasses such methodologies as content analysis, a means of organizing and interpreting data to elicit themes and concepts; discourse analysis, used to analyze language to understand social or historical context; narrative analysis, in which the researcher seeks to understand human experience through participant stories; and focus groups and case studies, used to understand the consensus of a group or the experience of an individual and his or her reaction to a difficult situation such as disease or trauma. Written by a noted qualitative research scholar and contributing experts, the book describes the philosophical basis for conducting research using data analysis and delivers an in-depth plan for applying its methodologies to a particular study, including appropriate methods, ethical considerations, and potential challenges. It presents practical strategies for solving problems related to the conduct of research using the various forms of data analysis and presents a rich array of case examples from published nursing research. These include author analyses to support readers in decision making regarding their own projects. The book embraces such varied topics as data security in qualitative research, the image of nursing in science fiction literature, the trajectory of research in several nursing studies throughout Africa, and many others. Focused on the needs of both novice researchers and specialists, it will be of value to health institution research divisions, in-service educators and students, and graduate nursing educators and students. Key Features: Explains how to conduct nursing research using content analysis, discourse analysis, narrative analysis, and focus groups and case studies Presents state-of-the-art designs and protocols Focuses on solving practical problems related to the conduct of research Features rich nursing exemplars in a variety of health/mental health clinical settings in the United States and internationally |
| data analysis in nursing research: Big Data-Enabled Nursing Connie W. Delaney, Charlotte A. Weaver, Judith J. Warren, Thomas R. Clancy, Roy L. Simpson, 2017-11-02 Historically, nursing, in all of its missions of research/scholarship, education and practice, has not had access to large patient databases. Nursing consequently adopted qualitative methodologies with small sample sizes, clinical trials and lab research. Historically, large data methods were limited to traditional biostatical analyses. In the United States, large payer data has been amassed and structures/organizations have been created to welcome scientists to explore these large data to advance knowledge discovery. Health systems electronic health records (EHRs) have now matured to generate massive databases with longitudinal trending. This text reflects how the learning health system infrastructure is maturing, and being advanced by health information exchanges (HIEs) with multiple organizations blending their data, or enabling distributed computing. It educates the readers on the evolution of knowledge discovery methods that span qualitative as well as quantitative data mining, including the expanse of data visualization capacities, are enabling sophisticated discovery. New opportunities for nursing and call for new skills in research methodologies are being further enabled by new partnerships spanning all sectors. |
| data analysis in nursing research: Narrative Research in Nursing Immy Holloway, Dawn Freshwater, 2009-07-23 Narrative research is an increasingly popular way of carrying outqualitative research by analysing the stories or experience. Thefindings of this type of qualitative research can be used toimprove nursing education, nursing practice and patient care and toexplore the experience of illness and the interaction betweenprofessionals. Narrative Research in Nursing provides acomprehensive yet straightforward introduction to narrativeresearch which examines the skills needed to perform narrativeinterviews, analyse data, and publish results and enables nurseresearchers to use the method systematically and rigorously. Narrative Research in Nursing examines the nature of narratives andtheir role in the development of nursing and health care.Strategies and procedures are identified, including thepracticalities of sampling, data collection, analysis andpresentation of findings. The authors discuss authenticity ofevidence and ethical issues while also exploring problems andpracticalities inherent in narrative inquiry and its dissemination.Narrative Research in Nursing is a valuable resource for nursesinterested in writing and publishing narrative research. |
| data analysis in nursing research: Introduction to Nursing Research Melinda Blackman, Colleen Kvaska, 2011 Nutrition Psychology: Improving Dietary Adherence presents prominent psychological theories that are known to drive human eating behavior, and reveal how these models can be transformed into proactive strategies for adhering to healthy dietary regimens. |
| data analysis in nursing research: Nursing Research & Statistics Rajesh Kumar, 2019-01-04 1 Introduction to Nursing Research 2 Research Problem, Research Question and Hypothesis 3 The Research Process: An Overview 4 Ethical Issues in Research 5 Review of Literature 6 Theories and Conceptual Models in Research 7 Research Designs 8 Sample and Sampling Techniques 9 Data Collection Methods in Research 10 Data Analysis and Interpretation 11 Communication and Dissemination of Research Findings 12 Introduction to Statistics Appendices Glossary Index |
| data analysis in nursing research: Nursing Research Denise F. Polit, Bernadette P. Hungler, 1983 The Sixth Edition of this classic text maintains its place as the Gold Standard of nursing research. Nationally and internationally known, respected and used, the text provides readers with the skills they need to design and implement a research investigation and critically evaluate published research reports. Now completely revised and updated to reflect the latest trends in quantitative and qualitative research, this essential guide offers a focused, how-to approach. New in this edition: expanded discussion of qualitative approaches; demonstration of qualitative and quantitative approaches working together; charts and tables offer description of qualitative approaches; stronger emphasis on the hands-on, how-to methodology; more in-depth examination of reasearch difference; research more powerful research utilization. |
| data analysis in nursing research: Nursing Research Peggy-Anne Field, Janice M. Morse, 1985 This indispensable handbook to qualitative researchthe first of its kindleads you from theory development to research proposals through preparation and methods of research to analysis and reporting data. |
| data analysis in nursing research: Introductory Statistics for Health and Nursing Using SPSS Louise Marston, 2009-12-15 Introductory Statistics for Health & Nursing using SPSS is an impressive introductory statistics text ideal for all health science and nursing students. Health and nursing students can be anxious and lacking in confidence when it comes to handling statistics. This book has been developed with this readership in mind. This accessible text eschews long and off-putting statistical formulae in favour of non-daunting practical and SPSS-based examples. What′s more, its content will fit ideally with the common course content of stats courses in the field. Introductory Statistics for Health & Nursing using SPSS is also accompanied by a companion website containing data-sets and examples for use by lecturers with their students. The inclusion of real-world data and a host of health-related examples should make this an ideal core text for any introductory statistics course in the field. |
| data analysis in nursing research: Secondary Analysis of Electronic Health Records MIT Critical Data, 2016-09-09 This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients. |
| data analysis in nursing research: Burns and Grove's The Practice of Nursing Research - E-Book Jennifer R. Gray, Susan K. Grove, Suzanne Sutherland, 2016-08-10 - NEW Mixed Methods Research chapter and emphasis covers this increasingly popular approach to research. - NEW! Expanded emphasis on qualitative research provides more balanced coverage of qualitative and quantitative methods, addressing the qualitative research methodologies that are often the starting point of research projects, particularly in magnet hospitals and DNP programs. - ENHANCED emphasis on evidence-based practice addresses this key graduate-level QSEN competency. - UPDATED emphasis on the most currently used research methodologies focuses on the methods used in both quantitative research and qualitative research, as well as outcomes research and mixed methods research. - NEW! Quick-reference summaries are located inside the book's covers, including a table of research methods on the inside front cover and a list of types of research syntheses (with definitions) inside the back cover. - NEW student resources on the Evolve companion website include 400 interactive review questions along with a library of 10 Elsevier research articles. - NEW! Colorful design highlights key information such as tables and research examples |
| data analysis in nursing research: Applications Manual to Accompany Data Analysis & Statistics for Nursing Research Denise F. Polit, 1996 Designed to be used with the textbook Data Analysis and Statistics for Nursing Research, this hands-on manual provides nursing students with an opportunity to broaden their statistical and data analysis skills using a computer. The manual includes a guidebook with computer exercises, arranged in chapters corresponding to those in the textbook. Also included is a CD-ROM that contains a large raw data set, and commands for accessing the data set for two widely used statistical software packages, SPSS and SAS. - Back cover. |
| data analysis in nursing research: Nursing Research Carolyn Feher Waltz, R. Barker Bausell, 1981 |
| data analysis in nursing research: Introduction to Research Methods and Data Analysis in the Health Sciences Gareth Hagger-Johnson, 2014-06-20 Whilst the ‘health sciences’ are a broad and diverse area, and includes public health, primary care, health psychology, psychiatry and epidemiology, the research methods and data analysis skills required to analyse them are very similar. Moreover, the ability to appraise and conduct research is emphasised within the health sciences – and students are expected increasingly to do both. Introduction to Research Methods and Data Analysis in the Health Sciences presents a balanced blend of quantitative research methods, and the most widely used techniques for collecting and analysing data in the health sciences. Highly practical in nature, the book guides you, step-by-step, through the research process, and covers both the consumption and the production of research and data analysis. Divided into the three strands that run throughout quantitative health science research – critical numbers, critical appraisal of existing research, and conducting new research – this accessible textbook introduces: Descriptive statistics Measures of association for categorical and continuous outcomes Confounding, effect modification, mediation and causal inference Critical appraisal Searching the literature Randomised controlled trials Cohort studies Case-control studies Research ethics and data management Dissemination and publication Linear regression for continuous outcomes Logistic regression for categorical outcomes. A dedicated companion website offers additional teaching and learning resources for students and lecturers, including screenshots, R programming code, and extensive self-assessment material linked to the book’s exercises and activities. Clear and accessible with a comprehensive coverage to equip the reader with an understanding of the research process and the practical skills they need to collect and analyse data, it is essential reading for all undergraduate and postgraduate students in the health and medical sciences. |
| data analysis in nursing research: Quantitative Nursing Research Thomas R. Knapp, 1998-05-13 You may stop looking now. Quantitative Nursing Research is the answer to the prayers of graduate students and practitioners who have sought the key to this often intimidating subject. In this highly readable (dare we say enjoyable?) work, Thomas R. Knapp guides the reader through the basic definitions, fundamentals of design, and techniques of quantitative research |
| data analysis in nursing research: Nursing Research Janice M. Morse, Peggy-Anne Field, 2013-11-11 |
| data analysis in nursing research: Secondary Qualitative Data Analysis in the Health and Social Sciences Cheryl Tatano Beck, 2019-01-15 Despite a long history in quantitative research, it is only recently that enthusiasm for secondary analysis of qualitative data has gained momentum across health and social science disciplines. Given that researchers have long known the inordinate amount of time and energy invested in conducting qualitative research, the appeal of secondary analysis of qualitative data is clear. Involving the use of an existing dataset to answer research questions that are different from those asked in the original study, this method allows researchers to once again make use of their hard-earned qualitative dataset and to listen to their participants’ voices to the best of their ability in order to improve care and promote understanding. As secondary qualitative data analysis continues to evolve, more methodological guidance is needed. This book outlines three approaches to secondary data analysis and addresses the key issues that researchers need to wrestle with, such as ethical considerations, voice, and representation. Intellectual and interpretive hazards that can jeopardize the outcome of these analyses are highlighted and discussed, as are the criteria for assessing their quality and trustworthiness. Written as a thought-provoking guide for qualitative researchers from across the health and social sciences, this text includes a review of the state of the science in nursing and a number of in-depth illustrative case studies. |
| data analysis in nursing research: Health Services Research and Analytics Using Excel Nalin Johri, PhD, MPH, 2020-02-01 Your all-in-one resource for quantitative, qualitative, and spatial analyses in Excel® using current real-world healthcare datasets. Health Services Research and Analytics Using Excel® is a practical resource for graduate and advanced undergraduate students in programs studying healthcare administration, public health, and social work as well as public health workers and healthcare managers entering or working in the field. This book provides one integrated, application-oriented resource for common quantitative, qualitative, and spatial analyses using only Excel. With an easy-to-follow presentation of qualitative and quantitative data, students can foster a balanced decision-making approach to financial data, patient statistical data and utilization information, population health data, and quality metrics while cultivating analytical skills that are necessary in a data-driven healthcare world. Whereas Excel is typically considered limited to quantitative application, this book expands into other Excel applications based on spatial analysis and data visualization represented through 3D Maps as well as text analysis using the free add-in in Excel. Chapters cover the important methods and statistical analysis tools that a practitioner will face when navigating and analyzing data in the public domain or from internal data collection at their health services organization. Topics covered include importing and working with data in Excel; identifying, categorizing, and presenting data; setting bounds and hypothesis testing; testing the mean; checking for patterns; data visualization and spatial analysis; interpreting variance; text analysis; and much more. A concise overview of research design also provides helpful background on how to gather and measure useful data prior to analyzing in Excel. Because Excel is the most common data analysis software used in the workplace setting, all case examples, exercises, and tutorials are provided with the latest updates to the Excel software from Office365 ProPlus® and newer versions, including all important “Add-ins” such as 3D Maps, MeaningCloud, and Power Pivots, among others. With numerous practice problems and over 100 step-by-step videos, Health Services Research and Analytics Using Excel® is an extremely practical tool for students and health service professionals who must know how to work with data, how to analyze it, and how to use it to improve outcomes unique to healthcare settings. Key Features: Provides a competency-based analytical approach to health services research using Excel Includes applications of spatial analysis and data visualization tools based on 3D Maps in Excel Lists select sources of useful national healthcare data with descriptions and website information Chapters contain case examples and practice problems unique to health services All figures and videos are applicable to Office365 ProPlus Excel and newer versions Contains over 100 step-by-step videos of Excel applications covered in the chapters and provides concise video tutorials demonstrating solutions to all end-of-chapter practice problems Robust Instructor ancillary package that includes Instructor’s Manual, PowerPoints, and Test Bank |
| data analysis in nursing research: Research Basics James V. Spickard, 2016-09-15 Research Basics: Design to Data Analysis in Six Steps offers a fresh and creative approach to the research process based on author James V. Spickard’s decades of teaching experience. Using an intuitive six-step model, readers learn how to craft a research question and then identify a logical process for answering it. Conversational writing and multi-disciplinary examples illuminate the model’s simplicity and power, effectively connecting the “hows” and “whys” behind social science research. Students using this book will learn how to turn their research questions into results. |
| data analysis in nursing research: SAGE Secondary Data Analysis John Goodwin, 2012-07-23 One central and enduring image of the social science researcher is of an individual who commits a great deal of time to collecting original, primary data from a field of enquiry. This approach is often underpinned by a sincerely held belief that key research questions can only be explored by the collection of ever new, and ever greater amounts of data, or that already existing data are insufficient for researchers to test their ideas. Yet such an approach to social science research can be problematic not least because the collection of primary data can be an expensive, time-consuming, and even wasteful approach to social enquiry. Secondary analysis can serve many purposes, as well as being a valid approach in its own right. However, despite its widespread application, secondary analysis is often undervalued or perceived to be the preserve of only those interested in the re-use of large-scale survey data. Highlighting both the theory and practice of secondary analysis and the use of secondary sources, this collection considers the nature of secondary analysis as a research tool; reflects on the definitional debates surrounding terms such as secondary analysis, data re-use and restudies; illustrates how secondary analysis is used in social science research; and finally reviews the practical, methodological and ethical aspects of secondary analysis. Volume One: Using Secondary Sources and Secondary Analysis Volume Two: Quantitative Approaches to Secondary Analysis Volume Three: Qualitative Data and Research in Secondary Analysis Volume Four: Ethical, Methodological and Practical Issues in Secondary Analysis |
| data analysis in nursing research: Data Management and Analysis Using JMP Jane E Oppenlander, Patricia Schaffer, 2017-10-17 A holistic, step-by-step approach to analyzing health care data! Written for both beginner and intermediate JMP users working in or studying health care, Data Management and Analysis Using JMP: Health Care Case Studies bridges the gap between taking traditional statistics courses and successfully applying statistical analysis in the workplace. Authors Jane Oppenlander and Patricia Schaffer begin by illustrating techniques to prepare data for analysis, followed by presenting effective methods to summarize, visualize, and analyze data. The statistical analysis methods covered in the book are the foundational techniques commonly applied to meet regulatory, operational, budgeting, and research needs in the health care field. This example-driven book shows practitioners how to solve real-world problems by using an approach that includes problem definition, data management, selecting the appropriate analysis methods, step-by-step JMP instructions, and interpreting statistical results in context. Practical strategies for selecting appropriate statistical methods, remediating data anomalies, and interpreting statistical results in the domain context are emphasized. The cases presented in Data Management and Analysis Using JMP use multiple statistical methods. A progression of methods--from univariate to multivariate--is employed, illustrating a logical approach to problem-solving. Much of the data used in these cases is open source and drawn from a variety of health care settings. The book offers a welcome guide to working professionals as well as students studying statistics in health care-related fields. |
| data analysis in nursing research: Qualitative Research in Nursing Helen Streubert Speziale, Helen J. Streubert, Dona Rinaldi Carpenter, 2011 Qualitative Research in Nursing is a user-friendly text that systematically provides a sound foundation for understanding a wide range of qualitative research methodologies, including triangulation. It approaches nursing education, administration, and practice and gives step-by-step details to instruct students on how to implement each approach. Features include emphasis on ethical considerations and methodological triangulation, instrument development and software usage; critiquing guidelines and questions to ask when evaluating aspects of published research; and tables of published research that offer resources for further reading--Provided by publisher. |
| data analysis in nursing research: Ethnography in Nursing Research Janice M. Roper, Jill Shapira, 2000 Describing the principles and methods of ethnography used by nurse researchers, the authors demonstrate how to: conduct ethnographic research in health settings; analyze and interpret data collected from field work; make ethical decisions related to the role of being an ethnographer; and how to put ideas in writing. |
| data analysis in nursing research: Reworking Qualitative Data Janet Heaton, 2004-03-02 What is qualitative secondary analysis? How can it be most effectively applied in social research? This timely and accomplished book offers readers a well informed, reliable guide to all aspects of qualitative secondary analysis. The book: · Defines secondary analysis · Distinguishes between quantitative and qualitative secondary analysis · Maps the main types of qualitative secondary analysis · Covers the key ethical and legal issues · Offers a practical guide to effective research · Sets the agenda for future developments in the subject Written by an experienced researcher and teacher with a background in sociology, the book is a comprehensive and invaluable introduction to this growing field of social research. |
| data analysis in nursing research: Nursing Research Denise F. Polit, Cheryl Tatano Beck, 2020-02-12 Research methodology is a dynamic enterprise. Even after writing 10 editions of this book, we have continued to draw new material and inspiration from ground-breaking advances in research methods and in nurse researchers' use of those methods. It is thrilling to share many of those developments in this new edition. We expect that many of the new methodologic and technological enhancements will be translated into powerful evidence for nursing practice. Four years ago, we considered the 10th edition as a watershed edition of a classic textbook, having added two new chapters. We are persuaded, however, that this 11th edition is even better than the previous one. We have retained many features that made this book a classic textbook and resource, including its focus on research as a support for evidence-based nursing, but have introduced important innovations that we hope will help to shape the future of nursing research-- |
| data analysis in nursing research: Statistics for Nursing and Allied Health Stacey Beth Plichta, Laurel S. Garzon, 2009 This introductory textbook explores the role of research in health care and focuses in particular on the importance of organizing and describing research data using basic statistics. The goal of the text is to teach students how to analyze data and present the results of evidence-based data analysis. Based on the commonly-used SPSS software, a comprehensive range of statistical techniques—both parametric and non-parametric—are presented and explained. Examples are given from nursing, health administration, and health professions, followed by an opportunity for students to immediately practice the technique. |
| data analysis in nursing research: How To Do A Systematic Literature Review In Nursing: A Step-By-Step Guide Bettany-Saltikov, Josette, 2012-05-01 This is an excellent book which explains clearly the principles and practice of systematic reviews. The order of contents is logical, information is easy to find and the contents are written for a wide audience from student to practitioner. There are copious examples and illustrations and these should inspire confidence in the novice and remind the expert what the essential features of a good systematic review are. This book should be on every undergraduate and postgraduate reading list for courses on research methods. Roger Watson, Professor of Nursing, The University of Hull, UK This book provides a clear and concise guide for students to produce a systematic review of evidence in health care ... The material is presented as a logical series of steps starting with developing a focussed question up to completing the review and disseminating its findings ... To facilitate the review a number of blank forms are presented for the reader to copy and complete in relation to the topic which they are pursuing ... I would wholly recommend this text. Ian Atkinson, previously Senior Lecturer in Research Methods & Assistant Editor Journal of Clinical Nursing Does the idea of writing a systematic literature review feel daunting? Are you struggling to work out where to begin? By walking you carefully through the entire process from start to finish and breaking the task down into manageable steps, this book is the perfect workbook companion for students undertaking their first literature review for study or clinical practice improvement. Co-published with the Nursing Standard, this handy book: Goes into detail about the precise and practical steps required to carry out a systematic literature review Uses a workbook format, with 3 running examples that you can work through gradually as you carry out your review Offers suggestions and tips to help you write up your own review Features useful templates to help you stay organised and includes case-studies to identify good practice Highlights the pitfalls to avoid Written in an engaging, conversational style with clear explanations throughout, How to do a Systematic Literature Review in Nursing is invaluable reading for all nursing students as well as other healthcare professionals. |
| data analysis in nursing research: Data Analytics in Medicine Information Resources Management Association, 2019-11-18 This book examines practical applications of healthcare analytics for improved patient care, resource allocation, and medical performance, as well as for diagnosing, predicting, and identifying at-risk populations-- |
| data analysis in nursing research: Statistics for Advanced Practice Nurses and Health Professionals Manfred Stommel, PhD, Katherine J. Dontje, 2014-06-09 Print+CourseSmart |
| data analysis in nursing research: Statistical Methods for Health Care Research Barbara Hazard Munro, 2001 This singular text provides nursing students as well as students in all other health-related disciplines with a solid foundation for understanding data and specific statistical techniques. In this newest edition, outstanding faculty contributors focus on the most current and most frequently used statistical methods in today's health care literature, covering essential material for a variety of program levels including in-depth courses beyond the basic statistics course. Well-organized and clear text discussions and great learning tools help you cut through the complexities and fully comprehend the concepts of this often intimidating area of study. Book jacket. |
| data analysis in nursing research: Understanding Research for Nursing Students Peter Ellis, 2016-02-27 Do your students find research difficult to engage with or want a textbook that is easy to read? Right from the start of their programme it is crucial for nursing students to be able to understand and evaluate current research to support their learning. This book helps students recognise what good research is by providing an introductory guide to the main research methodologies used in nursing. It simplifies complex terminology and puts research into context for nursing students, with clear examples and case studies. Key features · Written in clear, easy to follow language · Each chapter is linked to relevant NMC Standards and Essential Skills Clusters · A companion website with 9 podcasts to bring topics from the book to life. |
| data analysis in nursing research: Statistics for Evidence-Based Practice in Nursing MyoungJin Kim, Caroline Mallory, 2017 Statistics for Evidence-Based Practice in Nursing, Second Edition presents statistics in a readable, user-friendly manner for both graduate students and the professional nurse. |
| data analysis in nursing research: Advances in Patient Safety Kerm Henriksen, 2005 v. 1. Research findings -- v. 2. Concepts and methodology -- v. 3. Implementation issues -- v. 4. Programs, tools and products. |
| data analysis in nursing research: Nursing Research: Designs and Methods Roger Watson, Hugh McKenna, Seamus Cowman, John Keady, 2008-02-22 This title is directed primarily towards health care professionals outside of the United States. It has been written by nurses for nurses and is research-minded, conceptually and theoretically up-to-date and student-centred. It is a comprehensive introduction to nursing research that will allow readers to build up their understanding of the research process and develop confidence in its practical application. - Text supported by examples from 'real life' research - International perspective on nursing research - Comprehensive coverage including established and innovative designs and methods |
| data analysis in nursing research: A Cross Section of Nursing Research Roberta J Peteva, 2016-11-18 • The 39 research articles in this collection illustrate a wide variety of models for both quantitative and qualitative nursing research. •The lines in each article are sequentially numbered, which facilitates classroom discussions by allowing professors and students to pinpoint specific parts of an article. •The articles have been carefully selected for use with students who are just beginning their study of research methods. The difficulty level will challenge but not overwhelm. •Factual Questions at the end of each article draw students’ attention to methodologically important points. •Questions for Discussion request students’ opinions on unique aspects of each article. •Helps instructors avoid copyright infringement problems. The publisher has paid fees to the copyright holders for permission to include the research articles in this book. • New to this edition: A copy of our Bonus Articles for A Cross Section of Nursing Research booklet is included free of charge. •The research articles are classified under these major headings: •nonexperimental quantitative research •true experimental research •quasi-experimental research •pre-experimental research •qualitative research •combined qualitative and quantitative research •test reliability and validity research •meta analysis. The articles have been drawn from a wide variety of journals such as: •Behavior Modification •Cancer Nursing •Computers in Nursing •Computers, Informatics, Nursing •Health Education & Behavior •Issues in Mental Health Nursing •Journal for Nurses in Staff Development •Journal of Community Health Nursing •Journal of Gerontological Nursing •Journal of Nursing Care Quality •Journal of Pediatric Nursing •Journal of Research in Nursing •Journal of the Society of Pediatric Nurses •Nurse Educator •Nursing Research •Psychological Reports •Public Health Nursing •Rehabilitation Nursing •Research in Nursing & Health •The Journal of Nursing Administration •Western Journal of Nursing Research |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a Transnational ...
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will enable a broader scientific community to benefit from the identified …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with minimum time delay; Understandable in a way that allows …
Belmont Forum Adopts Open Data Principles for Environmental Change Research
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, released in June, 2015. “A Place to Stand” is the …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, prevents fraud and thereby builds trust in …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will enable a …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels to …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
