Category Archives: RCT

HOMEMADE cloth masks: The good, the bad, & the Ugly

So I’ve been pretty skeptical about people sewing protective face masks at home. And, as with a lot of things we don’t have all the data that we wish we had. So…I’m putting this scientific evidence out there and encouraging you to contribute to this blog by adding other scientific data.

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Here is a 2015 randomized controlled trial (RCT) data: Penetration of cloth masks by particles was almost 97% and medical masks 44%. (N = 1607 HCW > 18 years).

Nevertheless, the expert opinion at CDC is that they are in the “Better Than Nothing” category and gives this additional advice. “In settings where N95 respirators are so limited that routinely practiced standards of care for wearing N95 respirators and equivalent or higher level of protection respirators are no longer possible, and surgical masks are not available, as a last resort, it may be necessary for HCP to use masks that have never been evaluated or approved by NIOSH or homemade masks. It

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may be considered to use these masks for care of patients with COVID-19, tuberculosis, measles, and varicella. However, caution should be exercised when considering this option.1,2

Anecdotally, providers are using them to extend the life of other masks or N95s. Women are also making some with little pockets for other filters, and a material called HANIBON that can be purchased online is used often on the outer layer of disposable masks and works to block out dust and fluids from entering. 

References

  1. Dato, VM, Hostler, D, and Hahn, ME. Simple Respiratory Maskexternal iconEmerg Infect Dis. 2006;12(6):1033–1034.
  2. Rengasamy S, Eimer B, and Shaffer R. Simple respiratory protection-evaluation of the filtration performance of cloth masks and common fabric materials against 20-1000 nm size particlesexternal iconAnn Occup Hyg. 2010;54(7):789-98.

“Sew” there you have it. Expert opinion is that as a last resort you may use inadequately tested cloth masks if it is all you have. I am grateful for all those sewists out there responding to medical center calls to supply them with cotton and elastic homemade masks, and sending out the patterns to do so. Field medicine.

CDC also says “The filters used in modern surgical masks and respirators are considered “fibrous” in nature—constructed from flat, nonwoven mats of fine fibers” If this is true then would nonwoven interfacing undefinedimprove the homemade masks?

iS IT 2? OR 3?

Credible sources often disagree on technicalities. Sometimes this includes classification of research design. Some argue that there are only 2 categories of research design:

  1. True experiments. True experiments have 3 elements: 1) randomization to groups, 2) a control group and an 3) intervention; and
  2. Non-experiments. Non-experiments may have 1 to none of those 3 elements.
Within-subject Control Group

Fundamentally, I agree with the above. But what about designs that include an intervention and a control group, but Not randomization?

Those may be called quasi-experiments; the most often performed quasi-experiment is pre/post testing of a single group. The control group are subjects at baseline and the experimental group are the same subjects after they receive a treatment or intervention. That means the control group is a within-subjects control group (as opposed to between-group control). Quasi-experiments can be used to answer cause-and-effect hypothesis when an experiment may not be feasible or ethical.

One might even argue that a strength of pre/post, quasi-experiments is that we do Not have to Assume that control and experimental groups are equivalent–an assumption we would make about the subjects randomized (randomly assigned) to a control or experimental group. Instead the control and experimental  are exactly equivalent because they are the same persons (barring maturation of subjects and similar threats to validity that are also true of experiments).

I think using the term quasi-experiments makes it clear that persons in the study receive an intervention. Adding “pre/post” means that the

This image has an empty alt attribute; its file name is intervention.jpg
Baseline ->Intervention->Post

researcher is using a single group as their own controls. I prefer to use the term non-experimental to mean a) descriptive studies (ones that just describe the situation) and b) correlation studies (ones without an intervention that look for whether one factor is related to another).

What do you think? 2? or 3?

Write Away!

Want to know the standardized format for writing up your research study, QI report, Writing1case study, systematic review, or clinical practice guideline?    Check out these standardized reporting guidelines: http://www.equator-network.org/reporting-guidelines/

Of course you should always give priority to the author instructions for the particular journal in which you want to publish, but most adhere generally or fully to these standardized guides.

Write away!

“Should you? Can you?”

ApplesOranges2Quasi-experiments are a lot of work, yet don’t have the same scientific power to show cause and effect, as do randomized controlled trials (RCTs).   An RCT would provide better support for any hypothesis that X causes Y.   [As a quick review of what quasi-experimental versus RCT studies are, see “Of Mice & Cheese” and/or “Out of Control (Groups).”]

So why do quasi-experimental studies at all?  Why not always do RCTs when we are testing cause and effect?  Here are 3 reasons:

#1  Sometimes ETHICALLY the researcher canNOT randomly assign subjects to a control Smokingand an experimental group.  If the researcher wants to compare health outcomes of smokers with non-smokers, the researcher cannot assign some people to smoke and others not to smoke!  Why?  Because we already know that smoking has significant harmful effects. (Of course, in a dictatorship, by using the police a researcher could assign them to smoke or not smoke, but I don’t think we wanna go there.)

#2 Sometimes PHYSICALLY the researcher canNOT randomly assign subjects to control & Country of Originexperimental groups.   If the researcher wants to compare health outcomes of
individuals from different countries, it is physically impossible to assign country of origin.

#3 Sometimes FINANCIALLY the researcher canNOT afford to assign subjects randomly PiggyBankto control & experimental groups.   It costs $ & time to get a list of subjects and then assign them to control & experimental groups using random numbers table or drawing names from a hat.

Thus, researchers sometimes are left with little alternative, but to do a quasi-experiment as the next best thing to an RCT, then discuss its limitations in research reports.

Critical Thinking: You read a research study in which a researcher recruits the 1st 100 patients on a surgical ward January-March quarter as a control group.  Then the researcher recruits the 2nd 100 patients on that same surgical ward April-June for the experimental group.  With the experimental group, the staff uses a new, standardized pain script for better pain communications.  Then the pain communication outcomes of each group are compared statistically.

  • Is this a quasi-experiment or a randomized controlled trial (RCT)?
  • What factors (variables) might be the same among control & experimental groups in this study?
  • What factors (variables) might be different between control & experimental groups that might affect study outcomes?
  • How could you design an ethical & possible RCT that would overcome the problems with this study?
  • Why might you choose to do the study the same way that this researcher did?

For more info: see “Of Mice & Cheese” and/or “Out of Control (Groups).”

Quasi- wha??

Two basic kinds of research design exist:  

  1. Experimental design in which
    • the researcher manipulates some variable,randomized
    • the participants are randomly assigned to groups, &
    • one group is a control group that gets a placebo or some inert treatment so that outcomes in that group can be compared to the group(s) that did get the treatment.
  2. Non-experimental design in which the researcher doesn’t manipulate anything, but just observes & records what is going on.   Some of these are descriptive, correlational, case, or cohort study designs for example.

One particularly interesting “experimental” design is one in which 1 or 2 of the experimental design ideal requirements as listed above are missing.  These are called quasi-experimental designs.

thinking3In a quasi experimental design

  • The researcher manipulates some variable, but….
  • Either the participants are NOT randomly assigned to groups
  • &/OR there is no control group.

A quasi-experimental design is not as strong as a true experiment in showing that the manipulated variable X causes changes in the outcome variable Y.  For example, a true experimental study with manipulation, randomization, and a control group would create much stronger evidence that hospital therapy dogs really reduced patient pain and anxiety.  We would not be as confident in the results of a quasi-experimental design examining the exact same thing.  In the next blog, we’ll examine why.

For more info:  Check out earlier blog:    “What is an RCT anyway?” at https://discoveringyourinnerscientist.com/2015/01/23/whats-a-randomized-controlled-trial/Idea2

Critical thinking:  Go to PubMed & use search terms “experiment AND nurse” (without the quotation marks).  Open an interesting abstract and look for the 3 elements of a classic experimental design. Now look for “quasi experiment AND nurse” (without the quotation marks.)  See what element is missing!

True or False: Experiment or Not

Experiments are the way that we confirm that one thing causes another.   If the study is not an experiment (or combined experiments in a meta-analysis), then the research does not show cause and effect. imagesCALQ0QK9

Experiments are one of the strongest types of research.

So…how can you tell a true experiment from other studies?   Hazel B can tell you in 4:04 and simple language at https://www.youtube.com/watch?v=x2i-MrwdTqI&index=1&list=PL7A7F67C6B94EB97E

Go for it!

[After watching video:  Note that the variable that is controlled by the researcher is call the Independent variable or Cause variable because it creates a change in something else. That something else that changes is the Dependent variable or Outcome variable.]Learning

CRITICAL THINKING:  

  1. Based on the video, can you explain why true experiments are often called randomized controlled trial (RCT)?
  2. Take a look at The Effect of the Physical and Mental Exercises During Hemodialysis on Fatigue: A Controlled Clinical Trial, that is free in full-text via PubMed. How does it meet the criteria of a true experiment as described by Hazel B in the video?

FOR MORE INFORMATION:   Go to “What’s an RCT Anyway?” (https://discoveringyourinnerscientist.wordpress.com/2015/01/23/whats-a-randomized-controlled-trial/ )

Telling the Future: The Research Hypothesis

What is a research hypothesis?   A research hypothesis is a predicted answer; an educated guess.  It is a statement of the outcome that a researcher expects to find in an experimental study.Hypothesis

Why care?  Because it tells you precisely the problem that the research study is about!  Either the researcher’s prediction turns out to be true (supported by data) or not!
A hypothesis includes 3 key elements: 1) the population of interest, 2) the experimental treatment, & 3) the outcome expected.  It is a statement of cause and effect. The experimental treatment that the researcher manipulates is called the independent or cause variable.  The result of the study is an outcome that is called the dependent variable because it depends on the independent/cause variable.

For example, let’s take the hypothesis “Heart failure patients who receive exmeds2perimental drug X will have better cardiac function than will heart failure patients who receive standard drug Y.”  You can see that the researcher is manipulating the drug (independent variable) that patients will receive.  And patient cardiac outcomes are expected to vary—in fact cardiac function is expected to be better—for patients who receive the experimental drug X.

Ideally that researcher will randomly assign subjects to an experimental group that receives drug X and a control group that receives standard therapy drug Y.   Outcome cardiac function data will be collected and analyzed to see if the researcher’s predicted answer (AKA hypothesis) is true.

In a research article, the hypothesis is usually stated right at the end of the introduction or background section.

If you see a hypothesis, how can you tell what is the independent/cause variable and the dependent/effect/outcome variable?question   1st – Identify the population in the hypothesis—the population does not vary (& so, it is not a variable).   2nd – Identify the independent variable–This will be the one that is the cause & it will vary.  3rd – Identify the dependent variable–This will be the one that is the outcome & its variation depends on changes/variation in the independent variable.

PRACTICE:  What are the population, independent variable(s) & dependent variable(s) in these actual research study titles that reflect the research hypotheses:

FOR MORE INFORMATION:  See SlideShare by Domocmat (n.d.) Formulating hypothesis at http://www.slideshare.net/kharr/formulating-hypothesis-cld-handout