The National Institutes of Health is the largest public funder of biomedical research around the globe. This support has led to life-saving treatments as well as an ever-growing body of research that paves the way for future breakthroughs. NIH funding comes in the form of grants, of which there are dozens of types. In today's post, we'll look at just one type of grant and why it is so important to research in infection control and prevention.
We have all heard about validity and reliability in research. Validity tells us that your results actually measure what you wanted to measure. Reliability means your results can be consistently reproduced. But before either of those two attributes of research can be considered, there is fidelity: Did you conduct your research as planned? In today's post, we'll explore the lesser-known member of this research quality triumvirate.
Not all scientific studies are created equal. Some studies are well-designed, with results that stand up to the intense scrutiny, analysis, and replication demanded by the scientific method. On the other hand, some studies are designed poorly, resulting in conclusions that can be called into question or that are not supported by the data. In this post, we explore two of the major ways that scientific studies are evaluated, giving you some tools to help in your own evaluation of the caliber of research studies.
The two aspects of research quality we will discuss today are internal validity and external validity. First, let’s consider the word validity. A study is considered valid - from the Latin word for 'strong' - if it is strongly supported by facts and logic. In terms of scientific research, to have valid conclusions, a study must have a valid design. This brings us to internal validity.
What happens after laboratory tests confirm that an environmental product kills bacteria? Is that the end of the line for testing a product's efficacy? One pair of researchers say no. Here is their proposal for an evidence hierarchy that describes how, in theory, data can begin to connect a product to a reduction in HAIs. While many regulatory agencies exist to protect the consumer by ensuring that HAI reduction claims are true, it is important for us to still be aware of the burden of proof in research, and how that plays out in a laboratory and real-life setting.
The scientific method demands that researchers follow logical steps in their process to ensure that results are definitive. Without following these steps, including the proper design of experiments, the resulting data is not reliable. Over time, the research establishment has determined certain types of experimental designs, their advantages and disadvantages, as well as which type of design is appropriate for certain fields or contexts. Today we’ll get an overview of the types of experimental designs and how they impact the research conducted in healthcare infection control.
Discussion of the reduction of microorganisms in healthcare settings will often include the data as “log reductions.” To those of us more accustomed to percentages, this can be confusing. Today's post will explain how to interpret these numbers and, we hope, help our readers better understand how they are used in scientific literature.
In scientific research, we test interventions to a problem and then measure the result: Did a medication improve patient outcomes? Did a training program lead to improved hand hygiene? Did copper-impregnated materials reduce the number of healthcare-associated infections? Simple before-and-after measurement is not enough when it comes to generating strong evidence. While the patients, the hand hygiene, and the infection rates may improve, it is vital to demonstrate that the intervention being studied was the cause of that improvement. How does a researcher demonstrate strong evidence? This post will explore the statistical representation of strength of evidence: The p value.
Scientific articles, also called academic or scholarly papers, are every-day reading for many professionals. For the average person, however, they represent a novel, sometimes intimidating, type of reading material. Unlike science articles found in science magazines such as Scientific American or Psychology Today, which take a journalistic approach to covering breakthroughs, journal articles have a concise writing style, lots of numbers, and scientific jargon. This post will explore the basic parts of a scientific journal article, including what parts to skip to if you just want the big picture.
Scientists around the world toil in their laboratories or in the field conducting research according to the scientific method. One of the final steps in the scientific method is sharing data within the scientific community. The most important way these 15 million + scientists share their work with their colleagues and the world at large is through publication in a scientific journal. Publication in a journal means the wider community has access to research that may help in other studies, but it also means the data has been reviewed and meets established criteria for reliability, meaning fellow scientists can trust the findings and use them with confidence.
Today’s post will explore the steps required for work to achieve publication, and next week's post will describe the resulting article format.
The term "white paper" comes to us from a 100-year-old practice of government reporting in the UK. When government agencies provided data to Parliament to help them make decisions, they would offer three different types: Very long, comprehensive documents with a blue cover, open-ended reports with a green cover, and short, focused reports on a single topic with white covers. This last type, the concise document with information to solve a problem, came to be the formula for what is now known in many industries as a "white paper." Today, white papers are produced for sales purposes by for-profit companies, making them a marketing tool that can often be confused with a neutral scientific paper. While both publications have their purpose, it is important for the consumer to know how they differ. Today we will compare these two documents in order to help our readers see beyond the surface similarities and become aware of the important differences.