research design nursing ppt

Research Methods in Nursing

Qualitative, quantitative, observational, correlational, quasi-experimental, experimental, mixed-methods, triangulation, ask a librarian.

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QUALitative research "is best suited for research aimed at rich description or in-depth understanding of a phenomenon, rather than determining causality; it is particularly useful in understanding the relevance of contextual features in the expression of the phenomenon. Qualitative approaches are most often chosen when little is known about a topic or when new perspectives are needed; other functions of qualitative approaches include generating hypotheses, refining theory, providing illustrative examples, creating taxonomies, and generating items for instrument development.

Relying primarily on inductive rather than deductive processes, qualitative studies generally share several “ground-up” features that differentiate them from “top-down” quantitative research. These features are driven by two central tenets: an orientation to cases rather than variables, as well as a preference for emergent rather than fixed designs."

More Information from Encyclopedia of Nursing Research

Four types of qualitative research design often applied to nursing research are:

• Phenomenology - the study of human life experiences and how they appear in human consciousness
• Grounded Theory - seeks to explain variations in social interactional and social structural problems and processes
• Ethnography - As a research process, ethnography is a comparative method for investigating patterns of human behavior and cognition through observations and interactions in natural settings
• Narrative Inquiry - the analysis of meaning in context through interpretation of persons' life experiences

For more details , look up these research designs in:

Encyclopedia of Nursing Research

Dictionary of Nursing Theory and Research

QUANtitative research "consists of the collection, tabulation, summarization, and analysis of numerical data for the purpose of answering research questions or hypotheses. The term quantitative research is of recent origin and is distinguished from qualitative research in design, process, and the use of quantification techniques to measure and analyze the data. The vast majority of all nursing studies can be classified as quantitative.

Quantitative research uses statistical methodology at every stage in the research process. At the inception of a research project, when the research questions are formulated, thought must be given to how the research variables are to be quantified, defined, measured, and analyzed. Study subjects are often selected for a research project through the statistical method of random sampling, which promotes an unbiased representation of the target population among the sample from whom generalizations will be made. Statistical methods are used to summarize study data, to determine sampling error, and in studies in which hypotheses are tested, to analyze whether results obtained exceed those that could be attributed to sampling error (chance) alone."

Quantitative Research Design can be Non-Experimental (Descriptive or Correlational) or Experimental (including Quasi-Experimental).

" Observational designs are nonexperimental, quantitative designs. In contrast to experimental designs in which the investigator manipulates the independent variable and observes its effect, the investigator conducting observational research observes both the independent and dependent variables. In observational studies, variation in the independent variable may be due to genetic endowment, self-selection, or occupational or environmental exposures."

" Correlational research examines the relationships between variables, but unlike experimental or quasi-experimental studies, correlational studies lack active manipulation of the independent variable(s). Therefore, postulation of relationships among study variables in causal terms is risky. Discussion of associations in correlational studies, however, sometimes gives an indication of how likely it is that a cause-and-effect relationship might exist."

More Information from Dictionary of Nursing Theory and Research

" Quasi-experimental research is similar to experimental research in that there is manipulation of an independent variable. It differs from experimental research because there is no control group, no random selection, no random assignment, and/or no active manipulation. Quasi-experimental research is a useful way to test causality in settings when it is impossible or unethical to randomly assign subjects to treatment and control groups or to withhold treatment from some subjects."

Experimental research "involves manipulation of the principal independent variable, i.e., the actual administration of treatments or interventions that comprise the categories of the independent variable. An investigation is made of the effect of the independent variable on the dependent variable.

A true experiment is characterized by random assignment of individual subjects to the treatment conditions and a high degree of control over unwanted influence of extraneous variables and other factors that could bias the results of the study."

"True experiments have the potential to provide strong evidence about the hypothesized causal relationship between independent and dependent variables. Experiments are characterized by manipulation, control, and randomization. The quality of experiments depends on the validity of their design."

" Mixed methods research is a term associated with research that uses a combination of methods that are usually identified with qualitative research and methods that are usually identified with quantitative research. It should not be confused with the terms mixed models or mixed effects that are used in other contexts such as the analysis of variance.

It is important to understand that the use of a mixed methods approach does not make research better or more valid than the use of either a qualitative or a quantitative approach."

"In nursing research, triangulation refers to the use of multiple sources to validate findings by the nursing researcher. It involves the combination of both quantitative and qualitative research methods within a single study."

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Research in Nursing: A Guide to Understanding Research Designs and Techniques

Nurses like any other professionals are expected to participate in research studies since nursing is a science that is fast evolving. Research in nursing paves the way for high quality, evidence-based nursing care. Findings from research highly informs quality nursing practice. Nursing practice needs to be research based; hence, it is worth commending that all nurses understand research techniques and designs and be involved in research. However, some bedside nurses are not aware of the relationship between research and the quality of care provided to patients. Such nurses need to be aware of the importance of research in nursing and get on board. There are different types of research designs and methods, and the type of design employed for a particular study will determine the methods to be used for that study. Generally, the different types of study designs include experimental and non-experimental research designs which can be used according to the need to answer many questions in the field of nursing. Thus, this paper gives an overview of research designs and methods in order to provide novice nurses with the basics of research methodology. This istoensure that nurses have an understanding of the research process and participate in research activities. This will in turn ensure that quality care which is evidenced-based is rendered to all patients.

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Revista Latino-americana De Enfermagem

Martha Driessnack

Journal of Nursing Scholarship

Natalia Flores

Lena Törnkvist

Solomon Jr.

Methodology The research activity is meant to rely on both the secondary and primary data sources that have to inform its findings, discussion, and conclusions. In the same regard, the emphasis is laid on various aspects including extraneous variables, instruments, the reliability of the generation of the instruments and the description of the intervention framework. Another item on the methodology is the analysis of the data collection procedures.

British Journal of Nursing

Sarahjane Jones

qualitative research designs. Phenomenological, ground theory, ethnography, narrative inquiry, and other related qualitative-related research methodologies are described. In addition, the importance of qualitative research as groundwork for quantitative studies is discussed. This link between qualitative and quantitative research is fundamental to promote evidence-based nursing practice. DESCRIPTORS: nursing research; qualitative analysis; methodology; nursing REVISIÓN DE DISEÑOS RELEVANTES PARA ENFERMERÍA:

Elizabeth Mason-Whitehead

PART ONE: PRINCIPLES OF RESEARCH IN HEALTH CARE Evidence-Based Practice and Research - Jo Rycroft-Malone Creating a Research-Based Culture in Healthcare Practice - Joyce Wilkinson The Research Journey - Elizabeth Mason-Whitehead and Becky Hall Paradigms and Philosophies - Mike Thomas Qualitative Research - Ann Bryan Quantitative Research - Charlotte Eost-Telling Mixed Methods Research - Dawn Freshwater Evaluation Research - David Coyle Service User-Led Research - Aidan Worsley Systematic Reviews - Alan Pearson Longitudinal Research - Elisabetta Ruspini Writing Research Bids - Neville J Ford with case study by Jean Mannix PART TWO: QUALITATIVE RESEARCH METHODS Action Research - Chris Whitney-Cooper Case Study Research - Andy Lovell Ethnography - Annette McIntosh-Scott with case study by Jenni Templeman Ethnomethodology - Tom Mason Feminist Research - Elizabeth Mason-Whitehead Grounded Theory - Maureen Deacon Hermeneutics - Dean Garret Historical Research - Pat Starkey Narrative Resea...

Becky Ingham-Broomfield

Objective This article provides a breakdown of the components of the hierarchy, or pyramid, of research designs. Its intention is to simplify the components of the hierarchy to enable novice readers of research to better understand the differing approaches and levels of evidence. Primary Argument Evidence-based Practice (EBP) is the integration of the best research evidence with clinical expertise and the patient's unique circumstances. This includes respect of patient values, and their needs, whilst delivering high‑quality, cost effective health care. Understanding the differing levels of evidence, and their reliability, is paramount to making correct and appropriate health care decisions. Nurses are required to use evidence‑ based practice as they are responsible for a significant amount of judgments and decisions every day, and therefore, they must use research literature as part of their clinical decision‑making. Conclusion The content, or levels of evidence, of the hierarchy will be discussed in a systematic, logical order from the base to the apex of the pyramid. A comparative grid at the end may lead the nurse to better understand the differing components of the seven levels of evidence or, depending on the source, eight.

Global Journal of Medical Sciences

Idongesit Ibanga Akpabio

ABSTRACT Abstract This paper aimed at highlighting the importance of Clinical Nursing Research (CNR) in the professional development of Nursing. CNR often involve patient-oriented research, epidemiologic and behavioural studies, outcomes and health services research. These are all essential in today’s political and societal health care environment with growing shifts and disconnects in patients’ care, and the need for availability of human, material and financial resources required in meeting the health care needs. These and many more require the best available evidence, which could be acquired through CNR. However to achieve the benefits of CNR for professional development, Challenges including low quality research by new and inexperienced researchers; non-availability of research findings to nurses in the practice sectors; inability to identify and work on priority areas needed to improve practice; poor collaboration among researchers and inability to integrate research into practice should be addressed. The key to building and sustaining successful programmes in CNR and evidence-based practice could involve the ground work of establishing forums and structures such as research units in health institutions where discussions and activities about the processes for research and evidence-based practice could be promoted.

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Taking Your Research to the Masses: Publishing Your Results

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Project Dissemination Phase

Dr. Rod Hicks continues the steps and tips for publishing your research study and results.

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Sampling Design in Nursing Research

Affiliation.

• 1 Alexa Colgrove Curtis is assistant dean of graduate nursing and director of the MPH-DNP dual degree program and Courtney Keeler is an associate professor, both at the University of San Francisco School of Nursing and Health Professions. Contact author: Alexa Colgrove Curtis, [email protected] . Nursing Research, Step by Step is coordinated by Bernadette Capili, PhD, NP-C: [email protected]. The authors have disclosed no potential conflicts of interest, financial or otherwise. A podcast with the authors is available at www.ajnonline.com .
• PMID: 33625012
• DOI: 10.1097/01.NAJ.0000737304.14564.51

Editor's note: This is the third article in a series on clinical research by nurses. The series is designed to give nurses the knowledge and skills they need to participate in research, step by step. Each column will present the concepts that underpin evidence-based practice-from research design to data interpretation. The articles will be accompanied by a podcast offering more insight and context from the author.

Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.

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Ten simple rules for effective presentation slides

Kristen m. naegle.

Biomedical Engineering and the Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America

Introduction

The “presentation slide” is the building block of all academic presentations, whether they are journal clubs, thesis committee meetings, short conference talks, or hour-long seminars. A slide is a single page projected on a screen, usually built on the premise of a title, body, and figures or tables and includes both what is shown and what is spoken about that slide. Multiple slides are strung together to tell the larger story of the presentation. While there have been excellent 10 simple rules on giving entire presentations [ 1 , 2 ], there was an absence in the fine details of how to design a slide for optimal effect—such as the design elements that allow slides to convey meaningful information, to keep the audience engaged and informed, and to deliver the information intended and in the time frame allowed. As all research presentations seek to teach, effective slide design borrows from the same principles as effective teaching, including the consideration of cognitive processing your audience is relying on to organize, process, and retain information. This is written for anyone who needs to prepare slides from any length scale and for most purposes of conveying research to broad audiences. The rules are broken into 3 primary areas. Rules 1 to 5 are about optimizing the scope of each slide. Rules 6 to 8 are about principles around designing elements of the slide. Rules 9 to 10 are about preparing for your presentation, with the slides as the central focus of that preparation.

Rule 1: Include only one idea per slide

Each slide should have one central objective to deliver—the main idea or question [ 3 – 5 ]. Often, this means breaking complex ideas down into manageable pieces (see Fig 1 , where “background” information has been split into 2 key concepts). In another example, if you are presenting a complex computational approach in a large flow diagram, introduce it in smaller units, building it up until you finish with the entire diagram. The progressive buildup of complex information means that audiences are prepared to understand the whole picture, once you have dedicated time to each of the parts. You can accomplish the buildup of components in several ways—for example, using presentation software to cover/uncover information. Personally, I choose to create separate slides for each piece of information content I introduce—where the final slide has the entire diagram, and I use cropping or a cover on duplicated slides that come before to hide what I’m not yet ready to include. I use this method in order to ensure that each slide in my deck truly presents one specific idea (the new content) and the amount of the new information on that slide can be described in 1 minute (Rule 2), but it comes with the trade-off—a change to the format of one of the slides in the series often means changes to all slides.

Top left: A background slide that describes the background material on a project from my lab. The slide was created using a PowerPoint Design Template, which had to be modified to increase default text sizes for this figure (i.e., the default text sizes are even worse than shown here). Bottom row: The 2 new slides that break up the content into 2 explicit ideas about the background, using a central graphic. In the first slide, the graphic is an explicit example of the SH2 domain of PI3-kinase interacting with a phosphorylation site (Y754) on the PDGFR to describe the important details of what an SH2 domain and phosphotyrosine ligand are and how they interact. I use that same graphic in the second slide to generalize all binding events and include redundant text to drive home the central message (a lot of possible interactions might occur in the human proteome, more than we can currently measure). Top right highlights which rules were used to move from the original slide to the new slide. Specific changes as highlighted by Rule 7 include increasing contrast by changing the background color, increasing font size, changing to sans serif fonts, and removing all capital text and underlining (using bold to draw attention). PDGFR, platelet-derived growth factor receptor.

Rule 2: Spend only 1 minute per slide

When you present your slide in the talk, it should take 1 minute or less to discuss. This rule is really helpful for planning purposes—a 20-minute presentation should have somewhere around 20 slides. Also, frequently giving your audience new information to feast on helps keep them engaged. During practice, if you find yourself spending more than a minute on a slide, there’s too much for that one slide—it’s time to break up the content into multiple slides or even remove information that is not wholly central to the story you are trying to tell. Reduce, reduce, reduce, until you get to a single message, clearly described, which takes less than 1 minute to present.

Rule 3: Make use of your heading

When each slide conveys only one message, use the heading of that slide to write exactly the message you are trying to deliver. Instead of titling the slide “Results,” try “CTNND1 is central to metastasis” or “False-positive rates are highly sample specific.” Use this landmark signpost to ensure that all the content on that slide is related exactly to the heading and only the heading. Think of the slide heading as the introductory or concluding sentence of a paragraph and the slide content the rest of the paragraph that supports the main point of the paragraph. An audience member should be able to follow along with you in the “paragraph” and come to the same conclusion sentence as your header at the end of the slide.

Rule 4: Include only essential points

While you are speaking, audience members’ eyes and minds will be wandering over your slide. If you have a comment, detail, or figure on a slide, have a plan to explicitly identify and talk about it. If you don’t think it’s important enough to spend time on, then don’t have it on your slide. This is especially important when faculty are present. I often tell students that thesis committee members are like cats: If you put a shiny bauble in front of them, they’ll go after it. Be sure to only put the shiny baubles on slides that you want them to focus on. Putting together a thesis meeting for only faculty is really an exercise in herding cats (if you have cats, you know this is no easy feat). Clear and concise slide design will go a long way in helping you corral those easily distracted faculty members.

Rule 5: Give credit, where credit is due

An exception to Rule 4 is to include proper citations or references to work on your slide. When adding citations, names of other researchers, or other types of credit, use a consistent style and method for adding this information to your slides. Your audience will then be able to easily partition this information from the other content. A common mistake people make is to think “I’ll add that reference later,” but I highly recommend you put the proper reference on the slide at the time you make it, before you forget where it came from. Finally, in certain kinds of presentations, credits can make it clear who did the work. For the faculty members heading labs, it is an effective way to connect your audience with the personnel in the lab who did the work, which is a great career booster for that person. For graduate students, it is an effective way to delineate your contribution to the work, especially in meetings where the goal is to establish your credentials for meeting the rigors of a PhD checkpoint.

Rule 6: Use graphics effectively

As a rule, you should almost never have slides that only contain text. Build your slides around good visualizations. It is a visual presentation after all, and as they say, a picture is worth a thousand words. However, on the flip side, don’t muddy the point of the slide by putting too many complex graphics on a single slide. A multipanel figure that you might include in a manuscript should often be broken into 1 panel per slide (see Rule 1 ). One way to ensure that you use the graphics effectively is to make a point to introduce the figure and its elements to the audience verbally, especially for data figures. For example, you might say the following: “This graph here shows the measured false-positive rate for an experiment and each point is a replicate of the experiment, the graph demonstrates …” If you have put too much on one slide to present in 1 minute (see Rule 2 ), then the complexity or number of the visualizations is too much for just one slide.

Rule 7: Design to avoid cognitive overload

The type of slide elements, the number of them, and how you present them all impact the ability for the audience to intake, organize, and remember the content. For example, a frequent mistake in slide design is to include full sentences, but reading and verbal processing use the same cognitive channels—therefore, an audience member can either read the slide, listen to you, or do some part of both (each poorly), as a result of cognitive overload [ 4 ]. The visual channel is separate, allowing images/videos to be processed with auditory information without cognitive overload [ 6 ] (Rule 6). As presentations are an exercise in listening, and not reading, do what you can to optimize the ability of the audience to listen. Use words sparingly as “guide posts” to you and the audience about major points of the slide. In fact, you can add short text fragments, redundant with the verbal component of the presentation, which has been shown to improve retention [ 7 ] (see Fig 1 for an example of redundant text that avoids cognitive overload). Be careful in the selection of a slide template to minimize accidentally adding elements that the audience must process, but are unimportant. David JP Phillips argues (and effectively demonstrates in his TEDx talk [ 5 ]) that the human brain can easily interpret 6 elements and more than that requires a 500% increase in human cognition load—so keep the total number of elements on the slide to 6 or less. Finally, in addition to the use of short text, white space, and the effective use of graphics/images, you can improve ease of cognitive processing further by considering color choices and font type and size. Here are a few suggestions for improving the experience for your audience, highlighting the importance of these elements for some specific groups:

• Use high contrast colors and simple backgrounds with low to no color—for persons with dyslexia or visual impairment.
• Use sans serif fonts and large font sizes (including figure legends), avoid italics, underlining (use bold font instead for emphasis), and all capital letters—for persons with dyslexia or visual impairment [ 8 ].
• Use color combinations and palettes that can be understood by those with different forms of color blindness [ 9 ]. There are excellent tools available to identify colors to use and ways to simulate your presentation or figures as they might be seen by a person with color blindness (easily found by a web search).
• In this increasing world of virtual presentation tools, consider practicing your talk with a closed captioning system capture your words. Use this to identify how to improve your speaking pace, volume, and annunciation to improve understanding by all members of your audience, but especially those with a hearing impairment.

Rule 8: Design the slide so that a distracted person gets the main takeaway

It is very difficult to stay focused on a presentation, especially if it is long or if it is part of a longer series of talks at a conference. Audience members may get distracted by an important email, or they may start dreaming of lunch. So, it’s important to look at your slide and ask “If they heard nothing I said, will they understand the key concept of this slide?” The other rules are set up to help with this, including clarity of the single point of the slide (Rule 1), titling it with a major conclusion (Rule 3), and the use of figures (Rule 6) and short text redundant to your verbal description (Rule 7). However, with each slide, step back and ask whether its main conclusion is conveyed, even if someone didn’t hear your accompanying dialog. Importantly, ask if the information on the slide is at the right level of abstraction. For example, do you have too many details about the experiment, which hides the conclusion of the experiment (i.e., breaking Rule 1)? If you are worried about not having enough details, keep a slide at the end of your slide deck (after your conclusions and acknowledgments) with the more detailed information that you can refer to during a question and answer period.

Rule 9: Iteratively improve slide design through practice

Well-designed slides that follow the first 8 rules are intended to help you deliver the message you intend and in the amount of time you intend to deliver it in. The best way to ensure that you nailed slide design for your presentation is to practice, typically a lot. The most important aspects of practicing a new presentation, with an eye toward slide design, are the following 2 key points: (1) practice to ensure that you hit, each time through, the most important points (for example, the text guide posts you left yourself and the title of the slide); and (2) practice to ensure that as you conclude the end of one slide, it leads directly to the next slide. Slide transitions, what you say as you end one slide and begin the next, are important to keeping the flow of the “story.” Practice is when I discover that the order of my presentation is poor or that I left myself too few guideposts to remember what was coming next. Additionally, during practice, the most frequent things I have to improve relate to Rule 2 (the slide takes too long to present, usually because I broke Rule 1, and I’m delivering too much information for one slide), Rule 4 (I have a nonessential detail on the slide), and Rule 5 (I forgot to give a key reference). The very best type of practice is in front of an audience (for example, your lab or peers), where, with fresh perspectives, they can help you identify places for improving slide content, design, and connections across the entirety of your talk.

Rule 10: Design to mitigate the impact of technical disasters

The real presentation almost never goes as we planned in our heads or during our practice. Maybe the speaker before you went over time and now you need to adjust. Maybe the computer the organizer is having you use won’t show your video. Maybe your internet is poor on the day you are giving a virtual presentation at a conference. Technical problems are routinely part of the practice of sharing your work through presentations. Hence, you can design your slides to limit the impact certain kinds of technical disasters create and also prepare alternate approaches. Here are just a few examples of the preparation you can do that will take you a long way toward avoiding a complete fiasco:

• Save your presentation as a PDF—if the version of Keynote or PowerPoint on a host computer cause issues, you still have a functional copy that has a higher guarantee of compatibility.
• In using videos, create a backup slide with screen shots of key results. For example, if I have a video of cell migration, I’ll be sure to have a copy of the start and end of the video, in case the video doesn’t play. Even if the video worked, you can pause on this backup slide and take the time to highlight the key results in words if someone could not see or understand the video.
• Avoid animations, such as figures or text that flash/fly-in/etc. Surveys suggest that no one likes movement in presentations [ 3 , 4 ]. There is likely a cognitive underpinning to the almost universal distaste of pointless animations that relates to the idea proposed by Kosslyn and colleagues that animations are salient perceptual units that captures direct attention [ 4 ]. Although perceptual salience can be used to draw attention to and improve retention of specific points, if you use this approach for unnecessary/unimportant things (like animation of your bullet point text, fly-ins of figures, etc.), then you will distract your audience from the important content. Finally, animations cause additional processing burdens for people with visual impairments [ 10 ] and create opportunities for technical disasters if the software on the host system is not compatible with your planned animation.

Conclusions

These rules are just a start in creating more engaging presentations that increase audience retention of your material. However, there are wonderful resources on continuing on the journey of becoming an amazing public speaker, which includes understanding the psychology and neuroscience behind human perception and learning. For example, as highlighted in Rule 7, David JP Phillips has a wonderful TEDx talk on the subject [ 5 ], and “PowerPoint presentation flaws and failures: A psychological analysis,” by Kosslyn and colleagues is deeply detailed about a number of aspects of human cognition and presentation style [ 4 ]. There are many books on the topic, including the popular “Presentation Zen” by Garr Reynolds [ 11 ]. Finally, although briefly touched on here, the visualization of data is an entire topic of its own that is worth perfecting for both written and oral presentations of work, with fantastic resources like Edward Tufte’s “The Visual Display of Quantitative Information” [ 12 ] or the article “Visualization of Biomedical Data” by O’Donoghue and colleagues [ 13 ].

Acknowledgments

I would like to thank the countless presenters, colleagues, students, and mentors from which I have learned a great deal from on effective presentations. Also, a thank you to the wonderful resources published by organizations on how to increase inclusivity. A special thanks to Dr. Jason Papin and Dr. Michael Guertin on early feedback of this editorial.

Funding Statement

The author received no specific funding for this work.

Nursing research

Sep 22, 2014

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Nursing research. provides the foundation for EVIDENCE-BASED NURSING PRACTICE. Research Utilization.

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Presentation Transcript

Nursing research • provides the foundation for • EVIDENCE-BASED NURSING PRACTICE

Research Utilization • Through Research Utilization, efforts and knowledge obtained from research is transformed into clinical practice, culminating in nursing practice that is evidence-based, to help understand the importance of evidence-based practice.

Evidence-based practice • The process of systematically finding, appraising, and using research findings as the basis for clinical practice.

THEORY • Research links theory, educations and practice. • Theoretical formulations supported by research findings may become the foundations of theory-based practice in nursing.

DEFINITION OF NURSING RESEARCH • Research is a process of systematic inquiry or study to build knowledge in a discipline. • The purpose of research is to validate and refine existing knowledge and develop new knowledge. • The results of research process: • provide a foundation on which practice decisions and behaviors are laid • create a strong scientific base for nursing practice and application of results demonstrates profes­sional accountability to insurers and health care consumers.

Nursing research is a systematic approach used to examine phenomena important to nursing and nurses, that clinical practice be based on scientific knowledge. • Evidence generated by nursing research provides support for the quality and cost-effectiveness of nursing interventions.

The introduction of evidence-based change into the direct provision of nursing care may occur at the individual level of a particular nurse or at varied organizational or social levels. • Nursing research aimed at impacting the direct provision of nursing and health care to recipients of nursing care, nursing research also is needed to generate knowledge in areas that affect nursing care processes indirectly.

This helps to begin nursing research adventure by developing an appreciation of the significance of research in nursing and the research roles of nurses through a historical and futuristic approach. • Nurse Researcher Roles • Two nursing roles are specifically focused on research: the clinical nurse specialist (CNS) and the clinical nurse researcher (CNR).

Research findings are being used increasingly as the basis for clinical decisions. • Evidence-based practice can be defined as the process of systematically finding, appraising, and using research findings as a basis for making decisions about patient care.

RESEARCH PRIORITIES • often set by groups that fund research, encourage nurse researchers to invest effort and money into those areas of research likely to generate the most benefit to recipients of care, • the funding opportunities offered by such groups don't hurt the research enterprise either.

Sources of funding for nursing research • The main outcome of research activity for a nurse is to eventually put the knowledge gained to work in health care delivery. • In USA there are the National Institute for Nursing Research (NINR) and the Agency for Healthcare Research and Quality (AHRQ). Both of these organizations are funded by federal congressional appropriations. • Private foundations and nursing organizations also provide funding for nursing research.

Research is a process that takes place in a series of steps: • Formulating the research question or problem • Defining the purpose of the study • Reviewing related literature • Formulating hypotheses and defining variables • Selecting the research design • Selecting the population, sample, and setting • Conducting a pilot study • Collecting the data • Analyzing the data • Communicating conclusions

STUDY DESIGNS Are plans that tell a researcher • how data are to be collected, • from whom data are to be collected, • how data will be analyzed to answer specific research questions.

Research studies are classified into two basic methods: Quantitative research is a formal, objective, systematic process in which numeric data are used. Qualitative research is a systematic approach used to describe and promote understanding of human experiences such as pain

The most common designs used in health care research are case study, survey, needs assessment, experimental, quasiexperimental, methodologic, meta-analysis, and secondary analysis.

Case study designs • Are used to present an in-depth analysis of a single subject, group, institution, or other social unit. • The purpose is to gain insight and provide background information for more controlled broader studies, develop explanations of human processes, and provide rich descriptive anecdotes

Extramural Priority Areas for Nursing research • a. Chronic conditions—arthritis, diabetes, urinary incontinence, long-term care, and care giving • b. Health promotion and risk behaviors—women's health, adolescence, menopause,environmental health, exercise, nutrition, and smoking cessation • c. Cardiopulmonary health—prevention and care of persons with cardiac or respiratory conditions, including research in critical care, trauma, wound healing, and organ transplantation

d. Neurofunction and sensory conditions—pain management, sleep disorders, and symptom management in persons with cognitive impairment and chronic neurologic conditions • e. Immune and neoplastic diseases(oncology)—symptoms primarily associated with cancer andacquired immune deficiency syndrome, such as fatigue, nausea and vomiting, and cachexia, as well as risk-factor prevention research • f. Reproductive and infant health—prevention of premature labor, reduction of health-risk factors during pregnancy, delivery of prenatal care, care of neonates, infant growth and development, and fertility issues (From the National Institutes of Nursing Research (NINR)

Nursing research • (links education, theory, nursing practice) provides the basic for expanding the unique body of scientific knowledge that forms the foundation of nursing practice. • Nurses become knowledgeable consumers of research through educational processes and practical experience, must have a basic understanding of the research process and critical appraisal skills that provide a standard for evaluating the strengths and weaknesses of research studies before applying them in clinical practice.

Nurses at all levels of educational preparation have responsibility to participate in the research process. • The role of the baccalaureate graduate is to be a knowledgeable consumer of research. • Research studies will emphasize clinical issues, problems, and outcomes. Priority will be given to research studies that focus on promoting health and developing cost-effective health care systems.

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Research Design 101

Everything You Need To Get Started (With Examples)

By: Derek Jansen (MBA) | Reviewers: Eunice Rautenbach (DTech) & Kerryn Warren (PhD) | April 2023

Navigating the world of research can be daunting, especially if you’re a first-time researcher. One concept you’re bound to run into fairly early in your research journey is that of “ research design ”. Here, we’ll guide you through the basics using practical examples , so that you can approach your research with confidence.

Overview: Research Design 101

What is research design.

• Research design types for quantitative studies
• Video explainer : quantitative research design
• Research design types for qualitative studies
• Video explainer : qualitative research design
• How to choose a research design
• Key takeaways

Research design refers to the overall plan, structure or strategy that guides a research project , from its conception to the final data analysis. A good research design serves as the blueprint for how you, as the researcher, will collect and analyse data while ensuring consistency, reliability and validity throughout your study.

Understanding different types of research designs is essential as helps ensure that your approach is suitable  given your research aims, objectives and questions , as well as the resources you have available to you. Without a clear big-picture view of how you’ll design your research, you run the risk of potentially making misaligned choices in terms of your methodology – especially your sampling , data collection and data analysis decisions.

The problem with defining research design…

One of the reasons students struggle with a clear definition of research design is because the term is used very loosely across the internet, and even within academia.

Some sources claim that the three research design types are qualitative, quantitative and mixed methods , which isn’t quite accurate (these just refer to the type of data that you’ll collect and analyse). Other sources state that research design refers to the sum of all your design choices, suggesting it’s more like a research methodology . Others run off on other less common tangents. No wonder there’s confusion!

In this article, we’ll clear up the confusion. We’ll explain the most common research design types for both qualitative and quantitative research projects, whether that is for a full dissertation or thesis, or a smaller research paper or article.

Research Design: Quantitative Studies

Quantitative research involves collecting and analysing data in a numerical form. Broadly speaking, there are four types of quantitative research designs: descriptive , correlational , experimental , and quasi-experimental . 

Descriptive Research Design

As the name suggests, descriptive research design focuses on describing existing conditions, behaviours, or characteristics by systematically gathering information without manipulating any variables. In other words, there is no intervention on the researcher’s part – only data collection.

For example, if you’re studying smartphone addiction among adolescents in your community, you could deploy a survey to a sample of teens asking them to rate their agreement with certain statements that relate to smartphone addiction. The collected data would then provide insight regarding how widespread the issue may be – in other words, it would describe the situation.

The key defining attribute of this type of research design is that it purely describes the situation . In other words, descriptive research design does not explore potential relationships between different variables or the causes that may underlie those relationships. Therefore, descriptive research is useful for generating insight into a research problem by describing its characteristics . By doing so, it can provide valuable insights and is often used as a precursor to other research design types.

Correlational Research Design

Correlational design is a popular choice for researchers aiming to identify and measure the relationship between two or more variables without manipulating them . In other words, this type of research design is useful when you want to know whether a change in one thing tends to be accompanied by a change in another thing.

For example, if you wanted to explore the relationship between exercise frequency and overall health, you could use a correlational design to help you achieve this. In this case, you might gather data on participants’ exercise habits, as well as records of their health indicators like blood pressure, heart rate, or body mass index. Thereafter, you’d use a statistical test to assess whether there’s a relationship between the two variables (exercise frequency and health).

As you can see, correlational research design is useful when you want to explore potential relationships between variables that cannot be manipulated or controlled for ethical, practical, or logistical reasons. It is particularly helpful in terms of developing predictions , and given that it doesn’t involve the manipulation of variables, it can be implemented at a large scale more easily than experimental designs (which will look at next).

That said, it’s important to keep in mind that correlational research design has limitations – most notably that it cannot be used to establish causality . In other words, correlation does not equal causation . To establish causality, you’ll need to move into the realm of experimental design, coming up next…

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Experimental Research Design

Experimental research design is used to determine if there is a causal relationship between two or more variables . With this type of research design, you, as the researcher, manipulate one variable (the independent variable) while controlling others (dependent variables). Doing so allows you to observe the effect of the former on the latter and draw conclusions about potential causality.

For example, if you wanted to measure if/how different types of fertiliser affect plant growth, you could set up several groups of plants, with each group receiving a different type of fertiliser, as well as one with no fertiliser at all. You could then measure how much each plant group grew (on average) over time and compare the results from the different groups to see which fertiliser was most effective.

Overall, experimental research design provides researchers with a powerful way to identify and measure causal relationships (and the direction of causality) between variables. However, developing a rigorous experimental design can be challenging as it’s not always easy to control all the variables in a study. This often results in smaller sample sizes , which can reduce the statistical power and generalisability of the results.

Moreover, experimental research design requires random assignment . This means that the researcher needs to assign participants to different groups or conditions in a way that each participant has an equal chance of being assigned to any group (note that this is not the same as random sampling ). Doing so helps reduce the potential for bias and confounding variables . This need for random assignment can lead to ethics-related issues . For example, withholding a potentially beneficial medical treatment from a control group may be considered unethical in certain situations.

Quasi-Experimental Research Design

Quasi-experimental research design is used when the research aims involve identifying causal relations , but one cannot (or doesn’t want to) randomly assign participants to different groups (for practical or ethical reasons). Instead, with a quasi-experimental research design, the researcher relies on existing groups or pre-existing conditions to form groups for comparison.

For example, if you were studying the effects of a new teaching method on student achievement in a particular school district, you may be unable to randomly assign students to either group and instead have to choose classes or schools that already use different teaching methods. This way, you still achieve separate groups, without having to assign participants to specific groups yourself.

Naturally, quasi-experimental research designs have limitations when compared to experimental designs. Given that participant assignment is not random, it’s more difficult to confidently establish causality between variables, and, as a researcher, you have less control over other variables that may impact findings.

All that said, quasi-experimental designs can still be valuable in research contexts where random assignment is not possible and can often be undertaken on a much larger scale than experimental research, thus increasing the statistical power of the results. What’s important is that you, as the researcher, understand the limitations of the design and conduct your quasi-experiment as rigorously as possible, paying careful attention to any potential confounding variables .

Research Design: Qualitative Studies

There are many different research design types when it comes to qualitative studies, but here we’ll narrow our focus to explore the “Big 4”. Specifically, we’ll look at phenomenological design, grounded theory design, ethnographic design, and case study design.

Phenomenological Research Design

Phenomenological design involves exploring the meaning of lived experiences and how they are perceived by individuals. This type of research design seeks to understand people’s perspectives , emotions, and behaviours in specific situations. Here, the aim for researchers is to uncover the essence of human experience without making any assumptions or imposing preconceived ideas on their subjects.

For example, you could adopt a phenomenological design to study why cancer survivors have such varied perceptions of their lives after overcoming their disease. This could be achieved by interviewing survivors and then analysing the data using a qualitative analysis method such as thematic analysis to identify commonalities and differences.

Phenomenological research design typically involves in-depth interviews or open-ended questionnaires to collect rich, detailed data about participants’ subjective experiences. This richness is one of the key strengths of phenomenological research design but, naturally, it also has limitations. These include potential biases in data collection and interpretation and the lack of generalisability of findings to broader populations.

Grounded Theory Research Design

Grounded theory (also referred to as “GT”) aims to develop theories by continuously and iteratively analysing and comparing data collected from a relatively large number of participants in a study. It takes an inductive (bottom-up) approach, with a focus on letting the data “speak for itself”, without being influenced by preexisting theories or the researcher’s preconceptions.

As an example, let’s assume your research aims involved understanding how people cope with chronic pain from a specific medical condition, with a view to developing a theory around this. In this case, grounded theory design would allow you to explore this concept thoroughly without preconceptions about what coping mechanisms might exist. You may find that some patients prefer cognitive-behavioural therapy (CBT) while others prefer to rely on herbal remedies. Based on multiple, iterative rounds of analysis, you could then develop a theory in this regard, derived directly from the data (as opposed to other preexisting theories and models).

Grounded theory typically involves collecting data through interviews or observations and then analysing it to identify patterns and themes that emerge from the data. These emerging ideas are then validated by collecting more data until a saturation point is reached (i.e., no new information can be squeezed from the data). From that base, a theory can then be developed .

As you can see, grounded theory is ideally suited to studies where the research aims involve theory generation , especially in under-researched areas. Keep in mind though that this type of research design can be quite time-intensive , given the need for multiple rounds of data collection and analysis.

Ethnographic Research Design

Ethnographic design involves observing and studying a culture-sharing group of people in their natural setting to gain insight into their behaviours, beliefs, and values. The focus here is on observing participants in their natural environment (as opposed to a controlled environment). This typically involves the researcher spending an extended period of time with the participants in their environment, carefully observing and taking field notes .

All of this is not to say that ethnographic research design relies purely on observation. On the contrary, this design typically also involves in-depth interviews to explore participants’ views, beliefs, etc. However, unobtrusive observation is a core component of the ethnographic approach.

As an example, an ethnographer may study how different communities celebrate traditional festivals or how individuals from different generations interact with technology differently. This may involve a lengthy period of observation, combined with in-depth interviews to further explore specific areas of interest that emerge as a result of the observations that the researcher has made.

As you can probably imagine, ethnographic research design has the ability to provide rich, contextually embedded insights into the socio-cultural dynamics of human behaviour within a natural, uncontrived setting. Naturally, however, it does come with its own set of challenges, including researcher bias (since the researcher can become quite immersed in the group), participant confidentiality and, predictably, ethical complexities . All of these need to be carefully managed if you choose to adopt this type of research design.

Case Study Design

With case study research design, you, as the researcher, investigate a single individual (or a single group of individuals) to gain an in-depth understanding of their experiences, behaviours or outcomes. Unlike other research designs that are aimed at larger sample sizes, case studies offer a deep dive into the specific circumstances surrounding a person, group of people, event or phenomenon, generally within a bounded setting or context .

As an example, a case study design could be used to explore the factors influencing the success of a specific small business. This would involve diving deeply into the organisation to explore and understand what makes it tick – from marketing to HR to finance. In terms of data collection, this could include interviews with staff and management, review of policy documents and financial statements, surveying customers, etc.

While the above example is focused squarely on one organisation, it’s worth noting that case study research designs can have different variation s, including single-case, multiple-case and longitudinal designs. As you can see in the example, a single-case design involves intensely examining a single entity to understand its unique characteristics and complexities. Conversely, in a multiple-case design , multiple cases are compared and contrasted to identify patterns and commonalities. Lastly, in a longitudinal case design , a single case or multiple cases are studied over an extended period of time to understand how factors develop over time.

As you can see, a case study research design is particularly useful where a deep and contextualised understanding of a specific phenomenon or issue is desired. However, this strength is also its weakness. In other words, you can’t generalise the findings from a case study to the broader population. So, keep this in mind if you’re considering going the case study route.

How To Choose A Research Design

Having worked through all of these potential research designs, you’d be forgiven for feeling a little overwhelmed and wondering, “ But how do I decide which research design to use? ”. While we could write an entire post covering that alone, here are a few factors to consider that will help you choose a suitable research design for your study.

Data type: The first determining factor is naturally the type of data you plan to be collecting – i.e., qualitative or quantitative. This may sound obvious, but we have to be clear about this – don’t try to use a quantitative research design on qualitative data (or vice versa)!

Research aim(s) and question(s): As with all methodological decisions, your research aim and research questions will heavily influence your research design. For example, if your research aims involve developing a theory from qualitative data, grounded theory would be a strong option. Similarly, if your research aims involve identifying and measuring relationships between variables, one of the experimental designs would likely be a better option.

Time: It’s essential that you consider any time constraints you have, as this will impact the type of research design you can choose. For example, if you’ve only got a month to complete your project, a lengthy design such as ethnography wouldn’t be a good fit.

Resources: Take into account the resources realistically available to you, as these need to factor into your research design choice. For example, if you require highly specialised lab equipment to execute an experimental design, you need to be sure that you’ll have access to that before you make a decision.

Keep in mind that when it comes to research, it’s important to manage your risks and play as conservatively as possible. If your entire project relies on you achieving a huge sample, having access to niche equipment or holding interviews with very difficult-to-reach participants, you’re creating risks that could kill your project. So, be sure to think through your choices carefully and make sure that you have backup plans for any existential risks. Remember that a relatively simple methodology executed well generally will typically earn better marks than a highly-complex methodology executed poorly.

Recap: Key Takeaways

We’ve covered a lot of ground here. Let’s recap by looking at the key takeaways:

• Research design refers to the overall plan, structure or strategy that guides a research project, from its conception to the final analysis of data.
• Research designs for quantitative studies include descriptive , correlational , experimental and quasi-experimenta l designs.
• Research designs for qualitative studies include phenomenological , grounded theory , ethnographic and case study designs.
• When choosing a research design, you need to consider a variety of factors, including the type of data you’ll be working with, your research aims and questions, your time and the resources available to you.

If you need a helping hand with your research design (or any other aspect of your research), check out our private coaching services .

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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10 Comments

Is there any blog article explaining more on Case study research design? Is there a Case study write-up template? Thank you.

Thanks this was quite valuable to clarify such an important concept.

Thanks for this simplified explanations. it is quite very helpful.

This was really helpful. thanks

Thank you for your explanation. I think case study research design and the use of secondary data in researches needs to be talked about more in your videos and articles because there a lot of case studies research design tailored projects out there.

Please is there any template for a case study research design whose data type is a secondary data on your repository?

This post is very clear, comprehensive and has been very helpful to me. It has cleared the confusion I had in regard to research design and methodology.

This post is helpful, easy to understand, and deconstructs what a research design is. Thanks

how to cite this page

Thank you very much for the post. It is wonderful and has cleared many worries in my mind regarding research designs. I really appreciate .

how can I put this blog as my reference(APA style) in bibliography part?

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