Last post I commented on the potentially misleading terms of Filtered & Unfiltered research. My key point? Much so-called “unfiltered research” has been screened (filtered) carefully through peer-review before publication; while some “filtered research” may have been ‘filtered’ only by a single expert & be out of date. If we use the terms filtered and unfiltered we should not be naive about their meanings. (Pyramid source: Wikimedia Commons )
This week, I address what I see as a 2nd problem with this evidence based medicine pyramid. That is, missing in action from it are descriptive, correlation, & in-depth qualitative research are not mentioned. Where are they? This undercuts the EBM pyramid as a teaching tool and also (intentionally or not) denigrates the necessary basic type of research on which stronger levels of evidence are built. That foundation of the pyramid, called loosely “background information,” includes such basic, essential research.
You may have heard of Benner’s Novice to Expert theory. Benner used in-depth, qualitative interview descriptions as data to generate her theory. Yet that type of research evidence is missing from medicine’s pyramid! Without a clear foundation the pyramid will just topple over. Better be clear!
I recommend substituting (or at least adding to your repertoire) anEvidence Based NURSING (EBN)pyramid. Several versions exist & one is below that includes some of the previously missing research! This one includes EBP & QI projects, too! Notice the explicit addition of detail to the below pyramid as described at https://www.youtube.com/watch?v=MfRbuzzKjcM.
In a couple of recent blog entries I noted what you can and cannot learn from research 1) titles & 2) abstracts. Now, let me introduce you to the next part of research article: Introduction (or sometimes called Background or no title at all!). Introduction immediately follows the abstract.
The introduction/background “[a] outlines the background of the problem or issue being examined, [b] summarizes the existing literature on the subject, and [c] states the research questions, objectives, and possibly hypothesis” (p. 6, Davies & Logan, 2012)
This section follows the abstract. It may or may not have a heading(s) of “Introduction” or “Background” or both. Like the abstract, the Introduction describes the problem in which the researcher is interested & sometimes the specific research question or hypothesis that will be measured.
In the Intro/Background you will get a more full description of why the problem is a priority for research and what is already known about the problem (i.e., literature review).
Key point #1: Articles & research that are reviewed in theIntro/Background should be mostly within the past 5-7 years. Sometimes included are classic works that may be much older OR sometimes no recent research exists. If recent articles aren’t used, this should raise some questions in your mind. You know well that healthcare changes all the time!! If old studies are used the author should explain.
Key point #2: The last sentence or two in theIntro/Background is usually the research question or hypothesis (unless the author awards it its own section). If you need to know the research question/hypothesis right away, you can skip straight to the end of the Intro/background—and there it is!
Self-report by participants is one of the most common ways that researchers collect data, yet it is fraught with problems. Some worries for researchers are: “Will participants be honest or will they say what they think I want to hear?” “Will they understand the questions correctly?” “Will those who respond (as opposed to those who don’t respond) have unique ways of thinking so that my respondents do not represent everyone well?” and a BIG worry “Will they even fill out and return the questionnaire?”
One way to solve at least the latter 2 problems is to increase the response rate, and Edwards et al (2009 July 8) reviewed randomized trials to learn how to do just that!!
If you want to improve your questionnaire response rates, check it out! Here is Edwards et al.’s plain language summary as published in Cochrane Database of Systematic Reviews,where you can read the entire report.
Postal and electronic questionnaires are a relatively inexpensive way to collect information from people for research purposes. If people do not reply (so called ‘non-responders’), the research results will tend to be less accurate. This systematic review found several ways to increase response. People can be contacted before they are sent a postal questionnaire. Postal questionnaires can be sent by first class post or recorded delivery, and a stamped-return envelope can be provided. Questionnaires, letters and e-mails can be made more personal, and preferably kept short. Incentives can be offered, for example, a small amount of money with a postal questionnaire. One or more reminders can be sent with a copy of the questionnaire to people who do not reply.
Critical/reflective thinking: Imagine that you were asked to participate in a survey. Which of these strategies do you think would motivate or remind you to respond and why?
Researchers collect two types of data in their studies
Numbers (called quantitative data)
Words & narratives (called qualitative data)
One source of rich word or narrative (qualitative) data for answering nursing questions is nurses’ stories. Dr. Pat Benner RN, author of Novice to Expert explains two things we can do to help nurses fully tell their stories so we can learn the most from their practice.
Critical thinking: For a study using narratives in research see Leboul et al. (2017). Palliative sedation challenging the professional competency of health care providers and staff: A qualitative focus group and personal written narrative study. [full text available thru PubMed at https://www.ncbi.nlm.nih.gov/pubmed/28399846]. 1) Do you think the authors listened and unpacked information from the focus groups & written narratives; 2) Do you think there might be a difference in the way people write narratives and verbally tell narratives? 3) How might that difference if any affect the research findings?
Quasi-experiments are a lot of work, yet don’t have the same scientific powerto 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 and 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 & experimental 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 to 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?
In the last “Quasi-wha??” blogpost, I described 1 type of experimental design: Quasi-experimental. To review… In quasi-experimental designs, the researcher manipulates some variable, but either 1) doesn’t randomly assign subjects to a control and experimental group OR 2) doesn’t have a control group at all.
For example, the researcher may introduce pet therapy on unit #1 and avoid pet therapy on unit #2 and then afterwards compare the anxiety levels of patients on the 2 units. That study has a control group (unit #2), but because patients weren’t (& probably couldn’t be) randomly assigned to the units, this would be a quasi-experimental study. The control group in this pet therapy case is what researchers call a “non-equivalent control group.” Non-equivalent means the groups are different in ways that might affect study results! [Note: For review of what constitutes a true experimental study see first part of “Quasi-wha??” blogpost.]
Herein lies a weak link in the cause-and-effect chain. Quasi- designs are NOT as strong as true experimental designs because something other than our treatment (in this case pet therapy) may have created any difference in outcomes (e.g., anxiety levels). Why? Here’s your answer.
In an experimental study, randomly assigning subjects to a
control and a separate experimental group means that all the little, variable weirdities of all subjects are equally distributed to each group. Each group is the same mix of different types of people. This means we can assume that both groups are the exact same type of
people in regard to things that may influence study outcomes, such as attitudes, values, preferences, beliefs, anxiety level, psychology, physiology and so on.
In contrast, in the quasi-experimental pet therapy example above, there is probably something that caused a certain type of person to be on unit #1 and a different type to be on unit #2. Maybe it was their diagnosis, their doctor, their type of surgery, or other. Thus, we cannot assume that people in unit #1 and unit #2 groups are the same before pet therapy, and so any differences between them after pet therapy might have already existed.
So why do quasi-experimental studies at all?? There are great reasons! Stay tuned for next blogpost.
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.
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.
In 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.
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!