Any research project not worth doing is not worth doing well.
In honor of Nurse Week, I offer this tribute to the avante garde research work of Florence Nightingale in the Crimea that saved lives and set a precedent worth following.
Nightingale was a “passionate statistician” knowing that outcome data are convincing when one wants to change the world. She did not merely collect the data, but also documented it in a way that revealed its critical meaning for care.
As noted by John H. Lienhard (1998-2002): “Once you see Nightingale’s graph, the terrible picture is clear. The Russians were a minor enemy. The real enemies were cholera, typhus, and dysentery. Once the military looked at that eloquent graph, the modern army hospital system was inevitable. You and I are shown graphs every day. Some are honest; many are misleading….So you and I could use a Florence Nightingale today, as we drown in more undifferentiated data than anyone could’ve imagined during the Crimean War.” (Source: Leinhard, 1998-2002)
As McDonald (2001) writes in the BMJ free, full-text, Nightingale was “a systemic thinker and a “passionate statistician.” She insisted on improving care by making policy & care decisions based on “the best available government statistics and expertise, and the collection of new material where the existing stock was inadequate.”(p.68)
Moreover, her display of the data brought its message home through visual clarity!
Thus while Nightingale adhered to some well-accepted, but mistaken, scientific theories of the time (e.g., miasma) her work was superb and scientific in the best sense of the word. We could all learn from Florence.
CRITICAL THINKING: What issue in your own practice could be solved by more data? How could you collect that data? If you have data already, how can you display it so that it it meaningful to others and “brings the point home”?
FOR MORE INFO:
- Leinhard, J.H. (1998-2002). No. 1712: Nightingale’s graph. Engines of our Ingenuity. Retrieved form http://www.uh.edu/engines/epi1712.htm
- McDonald, L. (2001). EBN notebook: Florence Nightingale and the early origins of evidence-based nursing. Retrieved from http://ebn.bmj.com/content/ebnurs/4/3/68.full.pdf
- Nightingale, F. (1860). Notes on nursing: What it is and what it is not. New York, NY: D.Appleton & Co. Retrieved from http://digital.library.upenn.edu/women/nightingale/nursing/nursing.html
HAPPY NURSE WEEK TO ALL MY COLLEAGUES.
MAY YOU GO WHERE THE DATA TAKES YOU!
I love sharing a great resource, don’t you?
Today, I stumbled onto Study Design 101 at https://himmelfarb.gwu.edu/tutorials/studydesign101/index.html
If you’re a research afficianado, then you probably already know that some types of research studies are considered stronger than others. Stronger ones are those that support a hypothesis that X really did cause a change in Y. [For example, study results that suggest that a pain script (X) really does improve patient satisfaction with pain management (Y)]
You may even know that meta-analyses of randomized controlled trials are the strongest type of research evidence and that case studies are considered the weakest. (Expert opinion that is not research at all is even below that.)
But….are you clear on what a meta-analysis, a case study, a cohort study or a randomized controlled trial is? If not or if you want a review, Study Design 101 is for YOU! Check it out. Short descriptions followed by 2 question quizzes for self-testing will keep you on track. Enjoy.
Is it just the thought that counts? or not? (Probably depends on the relationship between giver & recipeient as per Paul Tournier’s The Meaning of Gifts that I highly recommend.)
In the meantime enjoy this article in the Washington Post on the holiday evidence for picking the best kinds of gifts. OR as it is actually titled: “The trick to not giving a terrible gift this year”
Critical Thinking: Note the outcome measures cited for each study:
- Were they direct or indirect; & what is the advantage of each
- Were they self-report or observation; & what are the pros & cons of each?
- Were the studies descriptive? or experimental? What does that tell you about cause & effect?
- Read Tournier’s tiny book, The Meaning of Gifts & draw your own conclusions.
For more info: Ask yourself what you would most like for Christmas & check out your friends wishlists! Check some of the studies cited in the Washington Post article, including Gino & Flynn (2011) evidence on preferences for $, solicited gifts, & unsolicited gifts. The findings might surprise you: http://www.sciencedirect.com/science/article/pii/S0022103111000801
A few suggestions from me
- You should have the goal of disseminating a project that will help others. Just trying to publish “something” won’t take you far. Figure out the unique twist of your ideas. Talk it over with colleagues & see what they find interesting.
- Select as many journals from this list or other lists that you think might be interested: https://nursingeditors.com/journals-directory/
- Write a query email to each journal to see if they are interested. NOTE: some journals will tell you what format your query should follow. You can write as many query letters as you want.
- Pick a journal from those interested. YOU CAN SUBMIT YOUR ARTICLE TO ONLY 1 JOURNAL at a time. If that journal rejects you can then submit to 1 other, and so on.
- Edit your paper with that journal’s audience in mind.
- Get a peer to read thoroughly and critique your article! THEN you have to LISTEN to all their concerns. If something is unclear to a peer, it will probably be unclear to a peer-reviewer.
- Format & submit EXACTLY, EXACTLY as they ask on the journal instructions to authors. (If you want to annoy editors and reviewers just ignore their instructions to potential authors.)
- Wait & keep your fingers crossed
- If they turn back to you for revisions that is a GOOD SIGN. It means they’re interested and you should address every concern.
FOR MORE INFORMATION: Check our Nurse Author & Editor for sure! http://naepub.com/
Is pain experience as diverse as our populations? This week I came across an interesting meta-analysis.
A meta-analysis (MA) is one of the strongest types of evidence there is. Some place it at the top; others, 2nd after evidence-based clinical practice guidelines. (For more on strength of evidence, click here.)
MA is not merely a review of literature, but is a statistical integration of studies on the same topic. MA that is based on integration of randomized controlled trials (RCTs) or experimental studies is the strongest type of MA. MA based on descriptive or non-experimental studies is a little less strong, because it just describes things as they seem to be; & it cannot show that one thing causes another.
MA example: This brand, new MA included 41 peer-reviewed, English-language, experimental studies with humans: Kim HJ, Yang GS, Greenspan JD, Downton KD, Griffith KA, Renn CL, Johantgen M, Dorsey SG. Racial and ethnic differences in experimental pain sensitivity: Systematic review and meta-analysis. Pain. 2016 Sep 24 [Epub ahead of print] doi: 10.1097/j.pain.0000000000000731. PMID: 27682208. All 41 studies used experimental pain stimuli such as heat, cold, ischemic, electrical and others and compared differences between racial/ethnic groups.
Main findings? “AAs [African Americans], Asians, and Hispanics had higher pain sensitivity compared to NHWs [non-Hispanic Whites], particularly lower pain tolerance, higher pain ratings, and greater temporal summation of pain.” (https://www.ncbi.nlm.nih.gov/pubmed/27682208) (Temporal summation is the increase in subjective pain ratings as a pain stimulus is repeated again and again.)
Critical thinking: Given that this is a well-done meta-analysis and that the pain was created by researchers in each study, how should this change your practice? Or should it? How can you use the findings with your patients? Should each patient be treated as a completely unique individual? Or what are the pros & cons of using this MA to give us a starting point with groups of patients? [To dialogue about this, comment below.]
For more info? Request the full Kim et al. article via interlibrary loan from your med center or school library using reference above. It is available electronically pre-publication. Also check out my blog on strength of different types of evidence.
Happy evidence hunting. -Dr.H
Key point! The data collection section of a research article includes: who collects what data when, where & how.
In previous blogs we’ve looked at title, introduction, and other elements of methods section (design, sample, & setting). In this one let’s take a look at data collection.
Data are a collection of measurements. For example, student scores on a classroom test might be 97, 90, 88, 85, & so on. Each single score is a datum; collectively they are data.
What data are collected is answered in this section. The data (or measurements) can be numbers OR words. For example, numbers data might include patient ratings of their pain on a 0-10 scale. An example of word data would asking participants to describe something in words without counting the words or anything else. For example, word data might include patient descriptions pain in words, like “stabbing,” “achy,” and so on. Sometimes a researcher collects both number and word data in the same study to give a more complete description. You can see how knowing the patient’s pain rating and hearing a description would give you a much clearer picture of pain.
- Studies reporting data in numbers are called quantitative studies
- Studies reporting data in words/descriptions are called qualitative studies
- Studies reporting number & word data are called mixed methods studies
How the data are collected includes what instrument or tool was used to gather data (e.g., observation, biophysical measure, or self-report) and how consistently & accurately that tool measures what it is supposed to measure (e.g., reliability & validity). Also included is who collected the data and the procedures that they followed—how did they obtain consent, interaction with subjects, timing of data collection and so on.
Now you know!
Critical thinking question: Did these authors use qualitative or quantitative data collection methods? Coelho, A., Parola, V., Escobar-Bravo, M., & Apostolo, J. (2016). Comfort experience in palliative care, BMD Palliative care, 15(71). doi: 10.1186/s12904-016-0145-0. Explain your answer.