Category Archives: Correlation research

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New book: “Doing Research: A Practical Guide”

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Author: Martha “Marty” E. Farrar Highfield

NOW AVAILABLE ELECTRONICALLY & SOON IN PRINT.

CHECK OUT: https://link.springer.com/book/10.1007/978-3-031-79044-7

This book provides a step-by-step summary of how to do clinical research. It explains what research is and isn’t, where to begin and end, and the meaning of key terms. A project planning worksheet is included and can be used as readers work their way through the book in developing a research protocol. The purpose of this book is to empower curious clinicians who want data-based answers.

Doing Research is a concise, user-friendly guide to conducting research, rather than a comprehensive research text. The book contains 12 main chapters followed by the protocol worksheet. Chapter 1 offers a dozen tips to get started, Chapter 2 defines research, and Chapters 3-9 focus on planning. Chapters 10-12 then guide readers through challenges of conducting a study, getting answers from the data, and disseminating results. Useful key points, tips, and alerts are strewn throughout the book to advise and encourage readers.

Correlation research, non-experimental research, Uncategorized

Correlation Studies: Primer on Design Part 2

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REMEMBER:

Research design = overall plan for a study.

The 2 major categories of research study design are:

  1. Non-experimental, observation-only studies, &
  2. Experimental testing of an intervention studies.

Correlation study designs are in that first category. Correlation studies focus on whether changes in at least one variable are statistically related to changes in another. In other words, do two or more variables change at the same time.

Such studies do not test whether one variable causes change in the other. Instead they are analogous to the chicken-and-egg dilemma in which one can confirm that the number of chickens and eggs are related to each other, but no one can say which came first or which caused the other. Correlation study questions may take this form, “Is there a relationship between changes in [variable x] and changes in [variable y]?” while a correlation hypothesis might be a prediction that, “As [variable x] increases, [variable y] decreases.”

An example of a question appropriate to this design is, “Are nurses’ age and educational levels related to their professional quality of life?” Sometimes a yet-unidentified, mediating variable may be creating the changes in one or all correlated variables. For example, rising nurse age and education may make them likely to choose certain work settings with high professional quality of life; this means the mediating variable of work setting—not age or education—might be creating a particular professional quality of life.

Alert! Correlation is not causation.
Correlation research, Evidence based nursing, Professional Nursing, reading research

“Which Came 1st–The chicken or the egg?” (or, Why Correlation is Not Causation)

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Correlation is not causation. RNs who want to use research in practice must take this seriously.

What does it mean?   Answer: Just because two things happen together, we cannot say that one causes the other.

Consider the example of drinking coffee and staying awake. The more coffee you drink, the more hours you will stay awake.   But isn’t it also true that the more hours you try to stay awake, the more coffee you will likely drink?

Thus, in a study about coffee drinking and sleep, you may read that coffee and hours of being awake are correlated. In other words, they occur together. When one goes up, the other goes up.   What is not clear is whether the coffee is causing the person to be awake longer, OR whether being awake longer is causing the effect of more coffee consumption.   The unsolved mystery is: “Which is the cause and which is the effect?”[1]

Likewise consider the consistent relationship between chickens and eggs. Every egg was produced by a hen. Every one. In statistical terms this means that on a scale of 0 to 1 (with 0 being no relationship whatsoever and 1 being a relationship that occurs 100% of the time) eggs and chickens have a perfect 100% relationship of 1. (A statistician would write this as r=1.0).   What is unclear is whether (when the world was young), the chicken appeared first and caused the first egg, or the egg came first and caused the first chicken. Again the unsolved mystery is: “Which is a cause and which is the effect?”

Okay, so let’s do some critical thinking about actual research.  You read these results:

“More calls for assistance related to less fall-related patient harm. Surprisingly, longer response time to call lights also related to fewer total falls and less fall-related patient harm. Generally speaking, more call light use related to longer response times.”[2]

When you read this article, what should you be assuming about the researchers’ findings in terms of relationships instead of cause-and-effect? (Hint: Think about chickens & eggs, or coffee & insomnia.)

[1] Bonus info: We call causes “independent variables” and we call effects, “dependent variables”

[2] Tzeng, H.M,. & Yin, C.Y. (2009). Relationship between call light use and response time and inpatient falls in acute care settings. Journal of Clinical Nursing, 18(23), 3333-3341. doi: 10.1111/j.1365-2702.2009.02916.x. Epub 2009 Sep 4.