Category Archives: research

“How many articles are enough?” Is that even the right question?

How do you know when you have found enough research evidence on a topic to be able to use the findings in clinical practice? How many articles are enough? 5? 50? 100? 1000? Good question!

You have probably heard general rules like these for finding enough applicable evidence: Stick close to your key search terms derived from PICOT statement of problem; Use only research published in the last 5-7 years unless it is a “classic; & Find randomized controlled trials (RCTs), meta-analyses, & systematic reviews of RCTs that document cause-and-effect relationships. These are good strategies. The only problem is that sometimes they don’t work!

Unfortunately, some clinical issues are “orphan topics.” No one has adequately researched them. And while there may be a few, well-done, valuable published studies on the topic, those studies may simply describe bits of the phenomena or focus on how to measure the phenomena (i.e., instrument development). They may give us little to no information on correlation and causation. There may be no RCTs. This situation may tempt us just to discard our clinical issue and to wait for more research (or of course to do research, but that could take years).

In her classic 1998 1-page article, “When is enough, enough?” Dr. Carol Deets, argues that asking how many research reports we need may be the wrong question! Instead, she proposes, we should ask, “What should be done to evaluate the implementation of research findings in the clinical setting?”

When research evidence is minimal, then careful process and outcome evaluation of its use in clinical practice can: 1) Keep patient safety as the top priority, 2) Document cost-effectiveness and efficacy of new interventions, and 3) Facilitate swift, ethical use of findings that contributes to nursing knowledge. At the same time, Deets recognizes that for many this idea may be revolutionary, requiring us to change the way we think.

So back to the original question…How many articles are enough? Deets’ answer? “One study is enough” if we build in strong evaluation as we translate it into practice.

Reference: Deets, C. (1998). When is enough, enough? Journal of Professional Nursing, 14(4), 196. doi.org/10.1016/S8755-7223(98)80058-6

simply put: the step-by-step research process

Research is not all white lab coats and test tubes. Simply put, research is a systematic way to ask and answer your questions by looking for patterns in new or existing data. Typical steps are clockwise are in Figure 1 below.

Begin by identifying your problem clearly and concisely. A great way to do that is using the acronym PICO. (Learn how to use PICO by clicking here.)

In the Figure 1 below, I’ve included the step of IRB review. Remember that an IRB (institutional review board/ AKA human subjects review board) must review all research procedures for your compliance with federal ethical and legal rules before you begin any data collection or subject contact.

Search discoveringyourinnerscientist.com for what I’ve already written on some of these steps, and watch for more in upcoming posts.

Figure 1. Research Process Summary 

Research: What it is and isn’t

WHAT RESEARCH IS

Research is using the scientific process to ask and answer questions by examining new or existing data for patterns. The data are measurements of variables of interest. The simplest definition of a variable is that it is something that varies, such as height, income, or country of origin. For example, a researcher might be interested in collecting data on triceps skin fold thickness to assess the nutritional status of preschool children. Skin fold thickness will vary.

Research is often categorized in different ways in terms of: data, design, broad aims, and logic.

Qualitative Data
  • Design. Study design is the overall plan for conducting a research study, and there are three basic designs: descriptive, correlational, and experimental.
    1. Descriptive research attempts to answer the question, “What exists?” It tells us what the situation is, but it cannot explain why things are the way they are. e.g., How much money do nurses make?
    2. Correlational research answers the question: “What is the relationship” between variables (e.g., age and attitudes toward work). It cannot explain why those variables are or are not related. e.g., relationship between nurse caring and patient satisfaction
    3. Experimental research tries to answer “Why” question by examining cause and effect connections. e.g., gum chewing after surgery speeds return of bowel function. Gum chewing is a potential cause or “the why”
  • Aims. Studies, too, may be either applied research or basic research. Applied research is when the overall purpose of the research is to uncover knowledge that may be immediately used in practice (e.g., whether a scheduled postpartum quiet time facilitates breastfeeding). In contrast, basic research is when the new knowledge has no immediate application (e.g., identifying receptors on a cell wall).
  • Logic. Study logic may be inductive or deductive. Inductive reasoning is used in qualitative research; it starts with specific bits of information and moves toward generalizations [e.g., This patient’s pain is reduced after listening to music (specific); that means that music listening reduces all patients pain (general)]. Deductive reasoning is typical of quantitative research; it starts with generalizations and moves toward specifics [e.g., If listening to music relaxes people (general), then it may reduce post-operative pain (specific)]. Of course the logical conclusions in each case should be tested with research!

WHAT RESEARCH IS NOT:

Research as a scientific process is not going to the library or searching online to find information. It is also different from processes of applying research and non-research evidence to practice (called Evidence-Based Practice or EBP). And it is not the same as Quality Improvement (QI). See Two Roads Diverged for a flowchart to help differentiate research, QI and EBP.

reposting: dispelling the nice or naughty myth–retrospective observational study of santa claus

Check out this re-post of my Christmas-y blog:

https://discoveringyourinnerscientist.com/2018/01/04/dispelling-the-nice-or-naughty-myth-retrospective-observational-study-of-santa-claus/

Useful…but not enough!

Homemade masks: 1918 & 2020

This Op Ed from Am Assoc for History of Nursing website by Marian Moser Jones
University of Maryland School of Public Health
moserj@umd.edu

Check it out & share your perspective: https://www.aahn.org/home-made-masks–useful-but-not-enough-in-1918–useful-but-not-enough-now

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?

Challenges to “Medical dogma” – Practice your EBP skills

Medscape just came out with Eric J. Topol article: 15 Studies that Challenged Medical Dogma in 2019. Critically check it out to practice your skills in applying evidence to practice. What are the implications for your practice? Are more or stronger studies needed before this overturning of dogma becomes simply more dogma? Are the resources and people’s readiness there for any warranted change? If not, what needs to happen? What are the risks of adopting these findings into practice?

Your thots? https://www.medscape.com/viewarticle/923150?src=soc_fb_share&fbclid=IwAR1SBNNVGW6BBWuKw7zBjhWIoQoMGtXZCy-BwpTTyavHSxmLleJuliKKG4A

On Target all the time and everytime !

“Measure twice. Cut once!” goes the old carpenter adage. Why? Because measuring accurately means you’ll get the outcomes you want!

Same in research. A consistent and accurate measurement will get you the outcomes you want to know. Whether an instrument measures something consistently is called reliability. Whether it measures accurately is called validity. So, before you use a tool, check for its reported reliability and validity.

A good resource for understanding the concepts of reliability (consistency) and validity (accuracy) of research tools is at https://opentextbc.ca/researchmethods/chapter/reliability-and-validity-of-measurement/ Below are quoted Key Takeaways:

  • Psychological researchers do not simply assume that their measures work. Instead, they conduct research to show that they work. If they cannot show that they work, they stop using them.
  • There are two distinct criteria by which researchers evaluate their measures: reliability and validity. Reliability is consistency across time (test-retest reliability), across items (internal consistency), and across researchers (interrater reliability). Validity is the extent to which the scores actually represent the variable they are intended to.
  • Validity is a judgment based on various types of evidence. The relevant evidence includes the measure’s reliability, whether it covers the construct of interest, and whether the scores it produces are correlated with other variables they are expected to be correlated with and not correlated with variables that are conceptually distinct.
  • The reliability and validity of a measure is not established by any single study but by the pattern of results across multiple studies. The assessment of reliability and validity is an ongoing process.

“Two roads diverged in a yellow wood…” R.Frost

TIME TO REPUBLISH THIS ONE:

Below is my adaptation of one of the clearest representations that I have ever seen of when the roads diverge into quality improvement, evidence-based practice, & research.  Well done, Dr. E.Schenk PhD MHI, RN-BC!qi-ebp-research-flow-chart

What’s in a Name?

[this posting back by popular demand]

TITLES!! That’s what you get when you search for research online!

But, whether your search turns up 3 or 32,003 article titles….remember that a title tells you a LOT In fact, if well-written it is a mini-abstract of the study. 

For example take this research article title “What patients with abdominal pain expect about pain relief in the Emergency Department” by Yee et al. in 2006 in JEN.
Variable (key factor that varies)?  Answer = Expectations about pain relief
Population studied? Answer = ED patients with abdominal pain
Setting? Answer = Maybe the ED (because they could’ve been surveyed after they got home or were admitted)
• Design?  Answer = not included, but you might guess that it is a descriptive study because it likely describes the patients’ expectations without any intervention.

There you have it! Now you know about TITLES!!

Now you try. Here’s your title: Gum chewing aids bowel function return and analgesic requirements after bowel surgery: a randomized controlled trial by Byrne CM, Zahid A, Young JM, Solomon MJ, Young CJ in May 2018

  • Variables? (this time there are 3 factors that vary–1 independent variable; & 2 dependent ones connected by “and”) Your answer is……
  • Population? (who is being studied; & if you have trouble identifying variables, identify the population first; then try) Your answer is….
  • Setting? (where; maybe not so clear; might have to go to abstract for this one) Your answer is….
  • Design of study? (it’s right there!) Your answer…..

Congratulate yourself!