Tag Archives: nursing

New research: Mindfulness

Check out the newest and add your critique in comments.

“Evidence suggests that mindfulness training using a phone application (app) may support neonatal intensive care unit (NICU) nurses in their high stress work.” https://journals.lww.com/advancesinneonatalcare/Abstract/9900/The_Effect_of_a_Mindfulness_Phone_Application_on.63.aspx

The Effect of a Mindfulness Phone Application on NICU Nurses’ Professional Quality of Life

by Egami, Susan MSN, RNC-NIC, IBCLC; Highfield, Martha E. Farrar PhD, RN

Editor(s): Dowling, Donna PhD, RN, Section Editors; Newberry, Desi M. DNP, NNP-BC, Section Editors; Parker, Leslie PhD, APRN, FAAN, Section EditorsAuthor Information

Advances in Neonatal Care ():10.1097/ANC.0000000000001064, April 10, 2023. | DOI: 10.1097/ANC.0000000000001064

Correlation Studies: Primer on Design Part 2


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.

Primer on Research Design: Part 1-Description

A research design is the investigator-chosen, overarching study framework that facilitates getting the most accurate answer to a hypothesis or question. Think of research design as similar to the framing of a house during construction. Just as house-framing provides structure and limits to walls, floors, and ceilings, so does a research design provide structure and limits to a host of protocol details.

Tip. The two major categories of research design are: 1) Non-experimental, observation only and 2) Experimental testing of an intervention.


Non-experimental studies that examine one variable at a time.

When little is known and no theory exists on a topic, descriptive research begins to build theory by identifying and defining key, related concepts (variables). Although a descriptive study may explore several variables, only one of those is measured at a time; there is no examination of relationships between variables. Descriptive studies create a picture of what exists by analyzing quantitative or qualitative

data to answer questions like, “What is [variable x]?” or “How often does it occur?” Examples of such one-variable questions are “What are the experiences of first-time fathers?” or “How many falls occur in the emergency room?” (Variables are in italics.)  The former question produces qualitative data, and the latter, quantitative.

Descriptive results raise important questions for further study, and findings are rarely generalizable. You can see this especially in a descriptive case study: an in-depth exploration of a single event or phenomena that is limited to a particular time and place. Given case study limitations, opinions differ on whether they even qualify as research.

Descriptive research that arises from constructivist or advocacy assumptions merits particular attention. In these designs, researchers collect in-depth qualitative information about only one variable and then critically reflect on that data in order to uncover emerging themes or theories. Often broad data are collected in a natural setting in which researchers exercise little control over other variables. Sample size is not pre-determined, data collection and analysis are concurrent, and the researcher collects and analyzes data until no new ideas emerge (data saturation). The most basic qualitative descriptive method is perhaps content analysis, sometimes called narrative descriptive analysis, in which researchers uncover themes within informant descriptions. Figure 4 identifies major qualitative traditions beyond content analysis and case studies.

Alert! All qualitative studies are descriptive, but not all descriptive studies are qualitative.

Box 1. Descriptive Qualitative Designs

DesignFocusDiscipline of Origin
EthnographyUncovers phenomena within a given culture, such as meanings, communications, and mores.Anthropology
Grounded TheoryIdentifies a  basic social problem and the process that participants use to confront it.Sociology
PhenomenologyDocuments the “lived experience” of informants going through a particular event or situation.Psychology
Community participatory actionSeeks positive social change and empowerment of an oppressed community by engaging them in every step of the research process.Marxist political theory
FeministSeeks positive social change and empowerment of women as an oppressed group.Marxist political theory

EBP: Think Three R’s

Risks, Resources, Readiness

3 things to consider when adapting or adopting research evidence to/in a particular practice setting according to Stetler (2001).

Check out the 1-minute video summary by DrH at https://www.instagram.com/martyhrn/

Testing the Test (or an intro to “Does the measurement measure up?”)

When reading a research article, you may be tempted only to read the Introduction & Background, then go straight to the Discussion, Implications, and Conclusions at the end. You skip all those pesky, procedures, numbers, and p levels in the Methods & Results sections.

Perhaps you are intimidated by all those “research-y” words like content validity, construct validity, test-retest reliability, and Cronbach’s alpha because they just aren’t part of your vocabulary….YET!

WHY should you care about those terms, you ask? Well…let’s start with an example. If your bathroom scale erratically measured your weight each a.m., you probably would toss it and find a more reliable and valid bathroom scale. The quality of the data from that old bathroom scale would be useless in learning how much you weighed. Similarly in research, the researcher wants useful outcome data. And to get that quality data the person must collect it with a measurement instrument that consistently (reliably) measures what it claims to measure (validity). A good research instrument is reliable and valid. So is a good bathroom scale.

Let’s start super-basic: Researchers collect data to answer their research question using an instrument. That test or tool might be a written questionnaire, interview questions, an EKG machine, an observation checklist, or something else. And whatever instrument the researcher uses needs to give them correct data answers.

For example, if I want to collect BP data to find out how a new med is working, I need a BP cuff that collects systolic and diastolic BP without a lot of artifacts or interference. That accuracy in measuring BP only is called instrument validity. Then if I take your BP 3 times in a row, I should get basically the same answer and that consistency is called instrument reliability. I must also use the cuff as intended–correct cuff size and placement–in order to get quality data that reflects the subject’s actual BP.

The same thing is true with questionnaires or other measurement tools. A researcher must use an instrument for the intended purpose and in the correct way. For example, a good stress scale should give me accurate data about a person’s stress level (not their pain, depression, or anxiety)–in other words it should have instrument validity. It should measure stress without a lot of artifacts or interference from other states of mind.

NO instrument is 100% valid–it’s a matter of degree. To the extent that a stress scale measures stress, it is valid. To the extent that it also measures other things besides stress–and it will–it is less valid. The question you should ask is, “How valid is the instrument?” often on a 0 to 1 scale with 1 being unachievable perfection. The same issue and question applies to reliability.

Reliability & validity are interdependent. An instrument that yields inconsistent results under the same circumstances cannot be valid (accurate). Or, an instrument can consistently (reliably) measure the wrong thing–that is, it can measure something other than what the researcher intended to measure. Research instruments need both strong reliability AND validity to be most useful; they need to measure the outcome variable of interest consistently.

Valid for a specific purpose: Researchers must also use measurement instruments as intended. First, instruments are often validated for use with a particular population; they may not be valid for measuring the same variable in other populations. For example, different cultures, genders, professions, and ages may respond differently to the same question. Second, instruments may be valid in predicting certain outcomes (e.g., SAT & ACT have higher validity in predicting NCLEX success than does GPA). As Sullivan (2011) wrote: “Determining validity can be viewed as constructing an evidence-based argument regarding how well a tool measures what it is supposed to do. Evidence can be assembled to support, or not support, a specific use of the assessment tool.”

In summary….

  1. Instrument validity = how accurate the tool is in measuring a particular variable
  2. Instrument reliability = how consistently the tool measures whatever it measures

Fun Practice: In your own words relate the following article excerpt to the concept of validity? “To assess content validity [of the Moral Distress Scale], 10 nurses were asked to provide comments on grammar, use of appropriate words, proper placement of phrases, and appropriate scoring. From p.3, Ghafouri et al. (2021). Psychometrics of the moral distress scale in Iranian mental health nurses. BMC Nursing. https://doi.org/10.1186/s12912-021-00674-4

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


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

“It’s a jungle out there:” Predatory Journals

Cool. You completed your project and now want to publish it.

Beware! Predatory journals are ready to snap up your work!  It helps them, but not you.

What is a predatory journal?  One that can eat you and your paper alive.

  • tiger junglePredatory journals don’t meet quality peer-review standards.
  • The predator may post your manuscript online, which then vanishes from access.
  • If you are writing an article and cite a predator-published manuscript, you undercut your own credibility.
  • If you’re counting on the article for credit towards tenure, your personnel reviewers may toss a predator-published article aside. 0 credit for you & questions about your own credibility. [For more on this in nursing see: Owens, J.K. & Chinn, P. (2018, January 20). “Reference letters & the specter of publications in predatory journals, Nurse Author & Editor, 28(1), 2. Retrieved from http://naepub.com/peer-review/2018-28-1-2/]

Many predators are Open Access Journals. What are Open Access Journals?  Ones “that use a funding model that does not charge readers or their institutions for access” (https://doaj.org/faq#definition).

Open Access Journals may be legitimate OR predatory.

How can you identify predatory journals? While perhaps not Mighty Mouse—yep, I’m showing my age—help from the Directory of Open Access Journals (DOAJ) is on the way. DOAJ provides a searchable list of LEGITIMATE open access journals (click here)A quick search for “nursing” yielded 7.

How does DOAJ define quality  of journals? Quality open access journals “must exercise peer-review with an editor and an editorial board or editorial review (particularly in the Humanities) carried out by at least two editors” (https://doaj.org/faq#definition).

Is there a list of predatory open access journals? YES. To see one that is updated, click here. Also, you can help! If you find an open access journal that claims to have the DOAJ quality seal, but isn’t on the DOAJ legitimate journal list, DOAJ wants to hear from you!

For more on DOAJ, see https://doaj.org/: “DOAJ is a community-curated online directory that indexes and provides access to high quality, open access, peer-reviewed journals. DOAJ is independent.”

predator raptorStay safe. As Randy Newman sings, “It’s a jungle out there.”


Want to change the world? Make a list

For new graduate RNs (& those who help them) entering the workforce, Dr. Pat Benner PhD RN FAAN, who wrote Novice to Expert, has some great, very practical advice: Changehttps://www.youtube.com/watch?v=yxsBVPxS_zg  (1:56)  (hint: Remember the only behavior you can control is your own!)

And…it’s pretty good advice for any who assume a new job, too!

For More Information: If you want to know what it feels like sometimes to be a new growing plantgrad RN, check out the 2 main themes and the subthemes voiced by new graduates in the free full-text: Hussein et al., (2017). New graduate nurses‘ experiences in a clinical specialty: a follow up study of newcomer perceptions of transitional support. BMC Nursing, 16(42). doi: 10.1186/s12912-017-0236-0. eCollection 2017.

Critical Thinking:   Whether or not you are a new grad, did you have experiences similar to those in Hussein’s study?   Can you use Benner’s suggestions to deal with the issues?


Listen up! Don’t interrupt!

Researchers collect two types of data in their studiescounting-sheetword-art

  1. Numbers (called quantitative data)
  2. Words & narratives (called qualitative data)

StorytellerOne 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.

  1. Listen well without interrupting
  2. Help nurses ‘unpack’ their stories 

Check out this excellent 2:59 video of Dr. Benner’s and revolutionize how you learn about nursing from nursing stories:  Preview: The use of Narratives 

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?

For more information:  Check out The Power of Story  by Wang & Geale (2015) at http://www.sciencedirect.com/science/article/pii/S2352013215000496


“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).”