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.
Millions of American children returned to school this week, officially kicking off the academic year filled promise. Alongside the promise of learning new things comes another promise: The certainty of picking up some kind of bug that will cause anything from the sniffles to time in bed. Today we'll explore some of the major pathogens that strike in busy classrooms full of kids as well as a few steps you can take to avoid some of those hallway bullies.
Less than 100 years ago today, American women were given the right to vote. For less than half of that time, August 26th has been recognized as Women’s Equality Day, a day to celebrate the struggles and successes of this movement to allow women to have a say in elections, and a voice in society as a whole. This struggle for a say and a voice continues, and while there has been tremendous progress, this struggle is quite visible in the world of science. Today’s post will celebrate the achievements of female scientists, while also discussing the two major obstacles women in science face, even today.
Today is National Aviation Day, a day to celebrate the many achievements in air travel over the decades since two brothers flew over the dunes of Kitty Hawk, NC. It is also a day when millions will start heading home from Rio’s Summer Olympics via airplane. Therefore, our attention turns to the aircraft that will carry them there, and the stowaways traveling right under their noses (and fingertips): Microorganisms.
Millions of global visitors. Packed venues. One city. How is it possible that the Olympics have always had such a clean bill of health for infectious diseases? Today's post explores the behind-the-scenes heroes that keep everyone healthy
We are now well into the first week of the 2016 Olympics in Rio de Janeiro, Brazil. The first medals have been awarded and the pre-opening frenzy about incomplete structures has calmed down. One concern, however, keeps coming up – the health of those competing in and attending these games of the XXXI Olympiad. More specifically, the threat of the Zika virus and bacteria in the water. This issue has made us wonder about the history of the intersection of the Olympics and infectious diseases has led to our determination that the most important event at any Olympics is the one you never hear about: Epidemiology.
In the 1920’s and 30’s, the nation was swept up in the Efficiency Movement, an effort to rid every aspect of human life of waste and unproductive activity. Researchers were dispatched to factory floors, classrooms, and even family living rooms with the mission of finding the optimal formula for efficient and productive work, a formula supported by the new excitement over science and experimentation. Within this context, a study was conducted at the Hawthorne Works, a factory making telephone equipment for Western Electric, to determine the optimal illumination level for worker productivity. These experiments went on for eight years, and ended with little fanfare. Decades later, however, Henry A. Landsberger revisited these studies, discovering a pattern that revealed more about human nature than about workplace illumination. This pattern still impacts research today, where it is known as the Hawthone effect.
An inescapable phenomenon has infected our nation’s population. Within weeks of the first cases, it has spread to millions, leaving victims walking the streets like zombies, eyes glazed over, chasing what appear to be apparitions or hallucinations. On street corners after sunset they gather together in clusters, as-of-yet uninfected onlookers staring in curiosity – and barely concealed horror. What is this virulent pathogen that is ravaging our neighborhoods, our marriages, our workplaces? It’s Pokémon Go.
This phone-based game that has broken records for downloads, profits, and active users happens to be a fascinating analog to the way humans and microorganisms live together. Come along with us as we explore how Pokémon and pathogens meet.
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.
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 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.