Newborn and Infant Nursing Reviews RSS feed: Current Issue. Newborn and Infant Nursing Reviews provides clinically relevant information that you can use daily. Its coverage goes beyond the scope of traditional NICU nursing, exploring concerns relevant to care outside of the neonatal period and the confines of the hospital. Each quarterly issue addresses a single topic, providing in-depth discussions of diagnosis, treatment, nursing implications/applications, new developments, clinical/evidence-based research, and controversies in the field. You'll also find case studies related to the issue topic. New! Newborn and Infant Nursing Reviews now includes regular columns that you can count on in every issue. Each column will relate to the issue's subject matter. Look forward to these columns: International Issues, Research Corner, Family, and Pharmacology. Plus, you will now find a crossword puzzle or related activity in every issue. 2010 Topics , Volume 10, Issues 1-4 March Quantitative Research Methodology Leigh Wang, PhD June NICU Design Sharon Cone, PhD (c), RNC, NNP September Legal Issues Roslynn Mertens, MSN, RN, IBCLC December Infection Lori Baas Rubarth, PhD, APRN-NP, NNP-BChttp://www.nainr.com/?rss=yesElsevier Inc.en © 2010 Elsevier Inc. All rights reserved. Newborn and Infant Nursing Reviews1527-3369101March 2010 © 2010 Elsevier Inc. All rights reserved. healthpermissions@elsevier.comhttp://www.nainr.com/article/PIIS152733690900169X/abstract?rss=yes W hile research topics are the theme of this issue, neonatal intensive care unit nurses' knowledge and experience with qualitative and quantitative research vary greatly. As new graduate nurses are entering the neonatal intensive care unit, the need for a consistent, evidence-based practice and knowledge of this is crucial. The effective practice of nursing is a balance between personal experience, best available clinical evidence, and logic or common sense. Sackett defined evidence-based practice as “the use of clinical experience combined with current best evidence to make decisions about the care of individual patients.” This definition implies that evidence-based practice has three components. These components would be the clinical expertise of the health care provider, the needs of the individual patient, and the interpretation of current best evidence.Leslie Altimier10.1053/j.nainr.2009.12.001Newborn and Infant Nursing Reviews 10, 1 (2010)2010-03-01Newborn and Infant Nursing Reviews2010-03-01101S1527-3369(10)X0002-2Editorial11http://www.nainr.com/article/PIIS1527336909001706/abstract?rss=yesQuantitative research methodology, which is characterized by positivism, measurement, and statistics, has dominated the scientific literatures in many disciplines. Clinical research, in particular, often relies on quantitative data to describe, predict, and explain the complex phenomena at work. Other disciplines sometimes turn to medical paradigms as learning models and benchmark standards for improving scientific rigor and assessing intellectual merit.Quantitative Research Methodology: Common Pitfalls and Recommended SolutionsLihshing Leigh Wang10.1053/j.nainr.2009.12.002Newborn and Infant Nursing Reviews 10, 1 (2010)2010-03-01Newborn and Infant Nursing Reviews2010-03-01101S1527-3369(10)X0002-2Guest Editorial24http://www.nainr.com/article/PIIS1527336909001767/abstract?rss=yesDawn Nahlen Drennan10.1053/j.nainr.2009.12.008Newborn and Infant Nursing Reviews 10, 1 (2010)2010-03-01Newborn and Infant Nursing Reviews2010-03-01101S1527-3369(10)X0002-2News Flashe1e3http://www.nainr.com/article/PIIS152733690900172X/abstract?rss=yesAs advances in technology and neonatal survival rates increase and younger less mature preterm infants are surviving, the need for excellent research to better guide our practice is also increasing. Yet, it must be emphasized that the neonatal population is a vulnerable population protected by federal restrictions. Neonatal researchers and practitioners are in a unique position to identify relevant and ethical research, to protect patients' safety, and to act as resources for families considering participation in research. Understanding the regulations associated with neonatal research, the role practitioners play in the process, and the experience of families who consent for their infant's participation in research will improve the experience for researchers, practitioners, and families.Engaging Families in Neonatal ResearchBrenda Baker, Jacqueline M. McGrath10.1053/j.nainr.2009.12.004Newborn and Infant Nursing Reviews 10, 1 (2010)2010-03-01Newborn and Infant Nursing Reviews2010-03-01101S1527-3369(10)X0002-2Family Dynamics57http://www.nainr.com/article/PIIS1527336909001743/abstract?rss=yesOur world is shrinking due to computerized linkages and the mobility of society. Information is shared rapidly around the world. Issues surrounding newborn and infant nursing are global. In efforts to acknowledge the international community, each Newborn and Infant Nursing Review issue will feature a column that highlights care and educational-related issues from a featured country or region of the world. This article focuses on research from an international perspective using the United Kingdom and Australia as examples.Neonatal ResearchLinda Johnston, Carole Kenner10.1053/j.nainr.2009.12.006Newborn and Infant Nursing Reviews 10, 1 (2010)2010-03-01Newborn and Infant Nursing Reviews2010-03-01101S1527-3369(10)X0002-2International Connections89http://www.nainr.com/article/PIIS1527336909001718/abstract?rss=yesResearch on the prevention and management of chronic illnesses involves understanding changes in complex and interrelated aspects of each individual. To capture these changes or to control for them, nursing and health research needs to be longitudinal. However, there are a number of potential pitfalls in analyzing longitudinal data from a chronically ill population. This article will examine four major pitfalls: selection of time points, measurement, choosing appropriate statistical procedures, and missing values. Although the frequency of data collection is often driven primarily by practical concerns, it will affect the results. In addition, outcome measures may capture different constructs at different points in times. Traditional analysis techniques often have assumptions about data characteristics that are violated in clinical populations. Missing values are common in research with chronically ill individuals because of problems of subject retention and because individuals have frequent medical complications. Solutions to these pitfalls are also discussed.Potential Pitfalls in Collecting and Analyzing Longitudinal Data From Chronically Ill PopulationsDiane Holditch-Davis, Janet Levy10.1053/j.nainr.2009.12.003Newborn and Infant Nursing Reviews 10, 1 (2010)2010-03-01Newborn and Infant Nursing Reviews2010-03-01101S1527-3369(10)X0002-2Articles1018http://www.nainr.com/article/PIIS1527336909001780/abstract?rss=yesThis article discusses the role that propensity score analysis can play in assessing the effects of interventions. It mostly focuses on identifying the range of solutions to practical problems that occur in propensity score analysis, especially with regard to propensity score construction (logistic regression, classification trees, ensemble methods), balancing (significance tests, other metrics), and analysis (matching, stratifying, weighting, covariance). Throughout, the article will identify particularly important or common pitfalls that need to be avoided in these analyses. The article ends with a discussion of the comparative advantages and disadvantages of propensity scores compared to alternative analytic and design options.A Primer on Propensity Score AnalysisWilliam R. Shadish, Peter M. Steiner10.1053/j.nainr.2009.12.010Newborn and Infant Nursing Reviews 10, 1 (2010)2010-03-01Newborn and Infant Nursing Reviews2010-03-01101S1527-3369(10)X0002-2Articles1926http://www.nainr.com/article/PIIS1527336909001792/abstract?rss=yesAbstract: This article introduces a number of examples demonstrating the importance of going beyond the observed sum of positive or correct responses when analyzing responses from clinical rating scales or educational test or psychological assessment data. Recent developments that allow more in-depth analysis of test data using modern psychometric methods based on statistical models for binary or ordered response data are discussed.Why Sum Scores May Not Tell Us All About Test TakersMatthias von Davier10.1053/j.nainr.2009.12.011Newborn and Infant Nursing Reviews 10, 1 (2010)2010-03-01Newborn and Infant Nursing Reviews2010-03-01101S1527-3369(10)X0002-2Articles2736http://www.nainr.com/article/PIIS1527336909001779/abstract?rss=yesAbstract: In quantitative research, it is critical to perform data cleaning to ensure that the conclusions drawn from the data are as generalizable as possible, yet few researchers report doing so (Osborne JW. Educ Psychol. 2008;28:1-10). Extreme scores are a significant threat to the validity and generalizability of the results. In this article, I argue that researchers need to examine extreme scores to determine which of many possible causes contributed to the extreme score. From this, researchers can take appropriate action, which has many laudatory effects, from reducing error variance and improving the accuracy of parameter estimates to reducing the probability of errors of inference.Data Cleaning Basics: Best Practices in Dealing with Extreme ScoresJason W. Osborne10.1053/j.nainr.2009.12.009Newborn and Infant Nursing Reviews 10, 1 (2010)2010-03-01Newborn and Infant Nursing Reviews2010-03-01101S1527-3369(10)X0002-2Articles3743http://www.nainr.com/article/PIIS1527336909001731/abstract?rss=yesStatistical tools are delicate instruments. When used properly, they help quantitative researchers illuminate relationships important to both practitioners and theorists; when used carelessly, they can bring about unjustified, distorted, and/or misleading claims. Almost every statistical tool has underlying assumptions (ie, prerequisite conditions) that supposedly govern its use. In this article, four questions concerning such assumptions are raised: What is an underlying statistical assumption? What are the consequences, if any, of violating them? Do applied researchers (and particularly those who publish articles in Newborn and Infant Nursing Reviews) pay attention to the assumptions that underlie the statistical procedures they use? What new insights into statistical assumptions have come about during the last 10 to 15 years?The Importance of Attending to Underlying Statistical AssumptionsHongwei Yang, Schuyler W. Huck10.1053/j.nainr.2009.12.005Newborn and Infant Nursing Reviews 10, 1 (2010)2010-03-01Newborn and Infant Nursing Reviews2010-03-01101S1527-3369(10)X0002-2Articles4449http://www.nainr.com/article/PIIS1527336909001755/abstract?rss=yesIt is a common misconception that statistical significance indicates a large and/or important effect. In fact the three concepts—statistical significance, effect size, and practical importance—are distinct from one another and a favorable result on one dimension does not guarantee the same on any other. In this article, we explain these concepts and distinguish between them. Finally, we propose reporting confidence intervals as a step toward disambiguating these concepts.Interpreting Significance: The Differences Between Statistical Significance, Effect Size, and Practical ImportancePawel Kalinowski, Fiona Fidler10.1053/j.nainr.2009.12.007Newborn and Infant Nursing Reviews 10, 1 (2010)2010-03-01Newborn and Infant Nursing Reviews2010-03-01101S1527-3369(10)X0002-2Articles5054http://www.nainr.com/article/PIIS1527336909001809/abstract?rss=yesThe calculation of statistical power after a study has been concluded is a highly controversial practice in quantitative research. Retrospective power in association with statistical nonsignificance presents special challenge to applied researchers in interpreting their statistical outcomes. The purposes of the present study are to review the current debate on retrospective power analysis, to examine the evidential basis of some myths associated with it, and to recommend some practical guidelines for quantitative researchers. I first briefly explain the theoretical concepts of prospective and retrospective power. I then describe three fallacies in misusing and abusing retrospective power. I conclude by providing some recommendations for improving the statistical practice associated with statistically nonsignificant findings.Retrospective Statistical Power: Fallacies and RecommendationsLihshing Leigh Wang10.1053/j.nainr.2009.12.012Newborn and Infant Nursing Reviews 10, 1 (2010)2010-03-01Newborn and Infant Nursing Reviews2010-03-01101S1527-3369(10)X0002-2Articles5559http://www.nainr.com/article/PIIS1527336909001810/abstract?rss=yesThe downward bias in correlation coefficients due to measurement error has long been recognized in the quantitative methodology literature. Whether to adjust for such bias in attenuated correlations, however, remains a heated debate among methodologists. As a result, applied researchers have largely ignored the controversial practice of treating observed correlations as error free. This article revisits the theoretical framework for disattenuation of correlations and critically examines the current reporting practice in applied research. I begin by summarizing the rationale for disattenuation and obstacles in implementing such disattenuation. I then highlight the chaotic status in applied research with a recent meta-analysis study on neuroimaging research. I conclude by calling for a renewed interest in addressing this disconnect between theory and practice and providing some practical guidelines for researchers and practitioners.Disattenuation of Correlations Due to Fallible MeasurementLihshing Leigh Wang10.1053/j.nainr.2009.12.013Newborn and Infant Nursing Reviews 10, 1 (2010)2010-03-01Newborn and Infant Nursing Reviews2010-03-01101S1527-3369(10)X0002-2Articles6065http://www.nainr.com/article/PIIS1527336910000048/abstract?rss=yesEditorial Board10.1053/S1527-3369(10)00004-8Newborn and Infant Nursing Reviews 10, 1 (2010)2010-03-01Newborn and Infant Nursing Reviews2010-03-01101S1527-3369(10)X0002-2FrontmatterA1A1http://www.nainr.com/article/PIIS152733691000005X/abstract?rss=yesContents10.1053/S1527-3369(10)00005-XNewborn and Infant Nursing Reviews 10, 1 (2010)2010-03-01Newborn and Infant Nursing Reviews2010-03-01101S1527-3369(10)X0002-2FrontmatterA2A3