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Q. How do I identify a research study?

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Answered by: david hisle last updated: aug 30, 2022     views: 66236.

These guidelines can help you identify a research study and distinguish an article that presents the findings of a research study from other types of articles.

• Ask a research question
• Identify a research population or group
• Describe a research method
• Test or measure something
• Summarize the results

Research studies are almost always published in peer-reviewed (scholarly) journals. The articles often contain headings similar to these: Literature Review, Method, Results, Discussion , and Conclusion .

Articles that review other studies without presenting new research results are not research studies. Examples of article types that are NOT research studies include:

• literature reviews
• meta-analyses
• case studies
• comments or letters relating to previously-published research studies

Some databases allow you to limit by publication type. Use this feature to help identify research studies. Here are tips for limiting by publication type in several popular databases:

• Click on the Advanced Search button.
• Type your search terms in the top boxes.
• In the area below the search boxes, find the box labeled "Publication Type".
• Select "Peer Reviewed Journal"
• empirical study
• follow-up study
• longitudinal study
• prospective study
• retrospective study
• treatment outcomes study

ERIC via EBSCO host :

• In the area below the search boxes, find the box labeled "Journal or Document".
• Select "Journal Articles" from the menu choices.
• Further down the screen, find the box labeled "Publication Type".
• Select "Reports - Research / Technical."
• Look carefully at the article abstracts to see if the article meets the requirements of a research study. Sometimes, you may have to look at the actual article to make this determination.

Some databases, like Sociological Abstracts , and Social Work Abstracts allow you to limit to "Articles" or "Abstracts of Journal Articles," but do not have more specific publication types. In Sociological Abstracts , a quick and dirty way to find research studies is to limit to "Articles" and then add "tables" to your search. This works because most research studies contain tables, and this is an indexed field in this database. For example, you might search for "gender and tables." This doesn't work well in Social Work Abstracts , though, because "tables" is not indexed. Instead, try something like "gender and research study" or even "gender and study." In all of these examples, you need to carefully examine the abstracts to see if the articles meet the requirements of a research study.

Many of the EBSCO host databases (e.g., Academic Search Complete , Health Source Nursing/Academic Edition, Sociological Collection ) allow you to limit to peer reviewed journals, but not by specific publication type. Be sure to click in the box to limit to peer reviewed journals. Then, add terms like "research study," "empirical," or "longitudinal" to your search. Again, carefully examine the abstracts to see if the articles meet the requirements of a research study.

Here is an example of an abstract of a research study from Sociological Collection . Phrases that help identify it as a research study are in bold:

Self-pity is a frequent response to stressful events. So far, however, empirical research has paid only scant attention to this subject. The present article aims at exploring personality characteristics associated with individual differences in feeling sorry for oneself . Two studies with N=5141 and N=5161 university students were conducted, employing multidimensional measures of personality, control beliefs, anger, loneliness, and adult attachment. With respect to personality, results showed strong associations of self-pity with neuroticism, particularly with the depression facet. With respect to control beliefs, individuals high in self-pity showed generalized externality beliefs, seeing themselves as controlled by both chance and powerful others. With respect to anger expression, self-pity was primarily related to anger-in. Strong connections with anger rumination were also found. Furthermore, individuals high in self-pity reported emotional loneliness and ambivalent-worrisome attachments. Finally, in both studies, a strong correlation with gender was found, with women reporting more self-pity reactions to stress than men. Findings are discussed with respect to how they support, extend, and qualify the previous literature on self-pity, and directions for future empirical research are pointed out.

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What Makes a Good Research Study?

Find out what separates a solid research study from a so-so one..

Posted March 31, 2018

One day you read online that drinking coffee reduces the chances of having age-related memory decline . You start drinking coffee. The next month you read that drinking coffee increases your chances of having age-related memory decline. What gives? In this article, you will learn how to "decipher" research studies to figure out what a research study is really saying - and what it doesn't say. You'll also discover how to tell if the reporting on a particular study was accurate or not. Ask yourself the following six questions when looking at a research study. Keep in mind these are just six of the many factors that make up a "clean" study.

1. Did the study use a placebo , and were the staff blinded to treatment?

The brain is very susceptible to placebos. There is evidence that even when you tell study subjects (participants) that they are getting a placebo, they improve (Carvalho, et al., 2016). In pharmaceutical studies, the US Food and Drug Administration (FDA) requires pharmaceutical companies to do double-blind placebo-controlled studies. This means that the study subjects, the physicians dispensing the drug, and the clinicians rating the subjects' behavior don't know what subjects are getting - drug or placebo. This eliminates a lot of bias , and it helps show whether the drug actually works.

2. Was there a bogus/sham treatment?

A bogus/sham treatment is one in which subjects are given a treatment that looks very much like the real treatment, except for one major difference. The bogus/sham treatment doesn't actually provide the therapeutic part of the treatment. For example, some acupuncture studies use a sham/bogus treatment, such as a 2017 study by Ugurlu, et al. regarding acupuncture treatment for fibromyalgia .

Bogus/sham treatments, when compared to active treatments, help researchers discover whether the active treatment is what works, or the fact that people think they are getting the active treatment.

3. How many people were there in the study (N)?

Logic says the more people you have in a study, or the study's "N", the better chance you have of your study representing of the general population (the "generalizability" of a study). Let's say you're studying the effects of apple juice on ADHD symptoms, and you have a total N of ten people. By chance, seven of those ten people have severe ADHD, two have moderate ADHD, and one has mild ADHD. You now could throw off the results of your study because you have so many people with severe ADHD in the study. When you have more subjects, or a larger N, in a study, there is more of a chance that you would have people that have mild, moderate, and severe ADHD.

4. Were the study groups randomized?

A good study randomizes their subjects into the active treatment and placebo groups. This means that the subjects are in those particular groups by chance. This provides extra "backup" that the effects from a treatment were actually from that treatment, not from study staff bias.

5. Who conducted the research, and who is paying for it?

If the people that created a treatment are also testing a treatment, this is a concern. When you have a horse in the race, so to speak, it is more difficult to be unbiased. Another concern is if an entity with a vested interest in a particular study outcome is paying for that study. For example, if there is a study on the effectiveness of widgets, and the sole source of funding is Widgets are Wonderful, Inc., and the researchers are employees of Widgets are Wonderful, that study better have some seriously good methodology to help eliminate bias. Even better, an independent research group is funded by an organization without ties to the study outcome.

6. Was the article published in a refereed (peer-reviewed/scholarly) journal?

In a refereed journal, a manuscript is reviewed by other experts in the field before it is published as an article. The authors of the manuscript are not disclosed to the reviewers, in order to reduce possible bias. When we review manuscripts for a journal, there are three main categories: reject, meaning the article goes no further; accept, with revisions, meaning the authors must edit their article before resubmitting it for publication; and accept as written, which is rare, but once in a while there is a manuscript with such good research methodology and writing that no additional editing is needed.

When a journal is not refereed, the standard of inclusion into that journal is not as high. This means the quality of the research may not be up to the same standards. Look up the journal online to find out if it is a peer-reviewed journal.

If you don't have university access, you can at least access the abstracts of journal articles at Google Scholar . The abstract lets you know the study's methodology, the number of study subjects, the outcomes, and the author's conclusions.

You may also see the term "open-access" used to describe a journal. An open-access journal is one that users can freely access, without a subscription or fees. Some open-access journals are peer-reviewed, some are not.

Copyright 2018 Sarkis Media

Carvalho, C., Caetano, J. M., Cunha, L., Rebouta, P., Kaptchuk, T. J., & Kirsch, I. (2016). Open-label Placebo Treatment in Chronic Low Back Pain: A Randomized Controlled Trial. Pain, 157(12), 2766–2772. http://doi.org/10.1097/j.pain.0000000000000700

Uğurlu, F. G., Sezer, N., Aktekin, L., Fidan, F., Tok, F., & Akkuş, S. (2017). The effects of acupuncture versus sham acupuncture in the treatment of fibromyalgia: a randomized controlled clinical trial. Acta reumatologica portuguesa, (1).

Stephanie Moulton Sarkis, Ph.D., N.C.C., D.C.M.H.S., L.M.H.C ., is the author of Gaslighting: Recognize Manipulative and Emotionally Abusive People — and Break Free .

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Science, health, and public trust.

September 8, 2021

Explaining How Research Works

We’ve heard “follow the science” a lot during the pandemic. But it seems science has taken us on a long and winding road filled with twists and turns, even changing directions at times. That’s led some people to feel they can’t trust science. But when what we know changes, it often means science is working.

Explaining the scientific process may be one way that science communicators can help maintain public trust in science. Placing research in the bigger context of its field and where it fits into the scientific process can help people better understand and interpret new findings as they emerge. A single study usually uncovers only a piece of a larger puzzle.

Questions about how the world works are often investigated on many different levels. For example, scientists can look at the different atoms in a molecule, cells in a tissue, or how different tissues or systems affect each other. Researchers often must choose one or a finite number of ways to investigate a question. It can take many different studies using different approaches to start piecing the whole picture together.

Sometimes it might seem like research results contradict each other. But often, studies are just looking at different aspects of the same problem. Researchers can also investigate a question using different techniques or timeframes. That may lead them to arrive at different conclusions from the same data.

Using the data available at the time of their study, scientists develop different explanations, or models. New information may mean that a novel model needs to be developed to account for it. The models that prevail are those that can withstand the test of time and incorporate new information. Science is a constantly evolving and self-correcting process.

Scientists gain more confidence about a model through the scientific process. They replicate each other’s work. They present at conferences. And papers undergo peer review, in which experts in the field review the work before it can be published in scientific journals. This helps ensure that the study is up to current scientific standards and maintains a level of integrity. Peer reviewers may find problems with the experiments or think different experiments are needed to justify the conclusions. They might even offer new ways to interpret the data.

It’s important for science communicators to consider which stage a study is at in the scientific process when deciding whether to cover it. Some studies are posted on preprint servers for other scientists to start weighing in on and haven’t yet been fully vetted. Results that haven't yet been subjected to scientific scrutiny should be reported on with care and context to avoid confusion or frustration from readers.

We’ve developed a one-page guide, "How Research Works: Understanding the Process of Science" to help communicators put the process of science into perspective. We hope it can serve as a useful resource to help explain why science changes—and why it’s important to expect that change. Please take a look and share your thoughts with us by sending an email to  [email protected].

Below are some additional resources:

• Discoveries in Basic Science: A Perfectly Imperfect Process
• When Clinical Research Is in the News
• What is Basic Science and Why is it Important?
• ​ What is a Research Organism?
• What Are Clinical Trials and Studies?
• Basic Research – Digital Media Kit
• Decoding Science: How Does Science Know What It Knows? (NAS)
• Can Science Help People Make Decisions ? (NAS)

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Research vs. Study

What's the difference.

Research and study are two essential components of the learning process, but they differ in their approach and purpose. Research involves a systematic investigation of a particular topic or issue, aiming to discover new knowledge or validate existing theories. It often involves collecting and analyzing data, conducting experiments, and drawing conclusions. On the other hand, study refers to the process of acquiring knowledge or understanding through reading, memorizing, and reviewing information. It is typically focused on a specific subject or discipline and aims to deepen one's understanding or mastery of that subject. While research is more exploratory and investigative, study is more focused on acquiring and retaining information. Both research and study are crucial for intellectual growth and expanding our knowledge base.

Further Detail

Introduction.

Research and study are two fundamental activities that play a crucial role in acquiring knowledge and understanding. While they share similarities, they also have distinct attributes that set them apart. In this article, we will explore the characteristics of research and study, highlighting their differences and similarities.

Definition and Purpose

Research is a systematic investigation aimed at discovering new knowledge, expanding existing knowledge, or solving specific problems. It involves gathering and analyzing data, formulating hypotheses, and drawing conclusions based on evidence. Research is often conducted in a structured and scientific manner, employing various methodologies and techniques.

On the other hand, study refers to the process of acquiring knowledge through reading, memorizing, and understanding information. It involves examining and learning from existing materials, such as textbooks, articles, or lectures. The purpose of study is to gain a comprehensive understanding of a particular subject or topic.

Approach and Methodology

Research typically follows a systematic approach, involving the formulation of research questions or hypotheses, designing experiments or surveys, collecting and analyzing data, and drawing conclusions. It often requires a rigorous methodology, including literature review, data collection, statistical analysis, and peer review. Research can be qualitative or quantitative, depending on the nature of the investigation.

Study, on the other hand, does not necessarily follow a specific methodology. It can be more flexible and personalized, allowing individuals to choose their own approach to learning. Study often involves reading and analyzing existing materials, taking notes, summarizing information, and engaging in discussions or self-reflection. While study can be structured, it is generally less formalized compared to research.

Scope and Depth

Research tends to have a broader scope and aims to contribute to the overall body of knowledge in a particular field. It often involves exploring new areas, pushing boundaries, and generating original insights. Research can be interdisciplinary, involving multiple disciplines and perspectives. The depth of research is often extensive, requiring in-depth analysis, critical thinking, and the ability to synthesize complex information.

Study, on the other hand, is usually more focused and specific. It aims to gain a comprehensive understanding of a particular subject or topic within an existing body of knowledge. Study can be deep and detailed, but it is often limited to the available resources and materials. While study may not contribute directly to the advancement of knowledge, it plays a crucial role in building a solid foundation of understanding.

Application and Output

Research is often driven by the desire to solve real-world problems or contribute to practical applications. The output of research can take various forms, including scientific papers, patents, policy recommendations, or technological advancements. Research findings are typically shared with the academic community and the public, aiming to advance knowledge and improve society.

Study, on the other hand, focuses more on personal development and learning. The application of study is often seen in academic settings, where individuals acquire knowledge to excel in their studies or careers. The output of study is usually reflected in improved understanding, enhanced critical thinking skills, and the ability to apply knowledge in practical situations.

Limitations and Challenges

Research faces several challenges, including limited resources, time constraints, ethical considerations, and the potential for bias. Conducting research requires careful planning, data collection, and analysis, which can be time-consuming and costly. Researchers must also navigate ethical guidelines and ensure the validity and reliability of their findings.

Study, on the other hand, may face challenges such as information overload, lack of motivation, or difficulty in finding reliable sources. It requires self-discipline, time management, and the ability to filter and prioritize information. Without proper guidance or structure, study can sometimes lead to superficial understanding or misconceptions.

In conclusion, research and study are both essential activities in the pursuit of knowledge and understanding. While research focuses on generating new knowledge and solving problems through a systematic approach, study aims to acquire and comprehend existing information. Research tends to be more formalized, rigorous, and contributes to the advancement of knowledge, while study is often more flexible, personalized, and focused on individual learning. Both research and study have their unique attributes and challenges, but together they form the foundation for intellectual growth and development.

Comparisons may contain inaccurate information about people, places, or facts. Please report any issues.

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• 1 University of Nebraska Medical Center
• 2 GDB Research and Statistical Consulting
• 3 GDB Research and Statistical Consulting/McLaren Macomb Hospital
• PMID: 29262162
• Bookshelf ID: NBK470395

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. Instead of collecting numerical data points or intervening or introducing treatments just like in quantitative research, qualitative research helps generate hypothenar to further investigate and understand quantitative data. Qualitative research gathers participants' experiences, perceptions, and behavior. It answers the hows and whys instead of how many or how much. It could be structured as a standalone study, purely relying on qualitative data, or part of mixed-methods research that combines qualitative and quantitative data. This review introduces the readers to some basic concepts, definitions, terminology, and applications of qualitative research.

Qualitative research, at its core, asks open-ended questions whose answers are not easily put into numbers, such as "how" and "why." Due to the open-ended nature of the research questions, qualitative research design is often not linear like quantitative design. One of the strengths of qualitative research is its ability to explain processes and patterns of human behavior that can be difficult to quantify. Phenomena such as experiences, attitudes, and behaviors can be complex to capture accurately and quantitatively. In contrast, a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a particular time or during an event of interest. Quantifying qualitative data certainly is possible, but at its core, qualitative data is looking for themes and patterns that can be difficult to quantify, and it is essential to ensure that the context and narrative of qualitative work are not lost by trying to quantify something that is not meant to be quantified.

However, while qualitative research is sometimes placed in opposition to quantitative research, where they are necessarily opposites and therefore "compete" against each other and the philosophical paradigms associated with each other, qualitative and quantitative work are neither necessarily opposites, nor are they incompatible. While qualitative and quantitative approaches are different, they are not necessarily opposites and certainly not mutually exclusive. For instance, qualitative research can help expand and deepen understanding of data or results obtained from quantitative analysis. For example, say a quantitative analysis has determined a correlation between length of stay and level of patient satisfaction, but why does this correlation exist? This dual-focus scenario shows one way in which qualitative and quantitative research could be integrated.

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Disclosure: Steven Tenny declares no relevant financial relationships with ineligible companies.

Disclosure: Janelle Brannan declares no relevant financial relationships with ineligible companies.

Disclosure: Grace Brannan declares no relevant financial relationships with ineligible companies.

• Introduction
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Masks strongly recommended but not required in maryland, starting immediately.

Due to the downward trend in respiratory viruses in Maryland, masking is no longer required but remains strongly recommended in Johns Hopkins Medicine clinical locations in Maryland. Read more .

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New Co-STAR Receptor Shows Promise Treating Cancers in Laboratory Study

Investigators from @hopkinskimmel, @bloombergkimmel create a novel cell type that is uniquely able to kill cancers in research models. ›

Using genetic engineering techniques, investigators at the Johns Hopkins Kimmel Cancer Center and its Ludwig Center , the Lustgarten Laboratory and Bloomberg~Kimmel Institute for Cancer Immunotherapy have designed a novel type of cell to recognize and fight cancer.

To produce the cells, called Co-STAR (Co-stimulatory Synthetic T-cell receptor and Antigen Receptor) cells, the researchers combined genetic components of four types of cells that the body normally uses to defend against invaders to make a powerful new cell type: T-cell receptors (TCRs) from T cells, antibodies from B cells, MyD88 from white blood cells called monocytes, and CD40 from dendritic and other cells. The TCR and antibody components served as an “invader detecting device,” recognizing cancer cells as foreign, and the “alarm” triggered by this hybrid detector was boosted by the MyD88 and C40 components.   

In laboratory studies, Co-STARs led to a sustained anti-tumor response against human cancer cells growing in test tubes and in mice. A description of the work was published July 10 in Science Translational Medicine .

T cell-based therapies are among the most promising approaches to treat advanced cancer and are the subject of intense research, explains lead study author Brian Mog, M.D., Ph.D., an internal medicine resident at Brigham and Women’s Hospital in Boston. He was a medical and graduate student at the Johns Hopkins University School of Medicine when the research was conducted.

However, TCR and CAR (chimeric antigen receptor, usually using antibody as the detector), which are aimed at stimulating an immune response by activating T cells, each has limits. The combination of the two can overcome these limitations.

“We needed to make a new type of cell, because we were trying to target specific antigens called peptide-HLA (human leukocyte antigen) antigens, which are peptide fragments from mutant proteins inside the cancer cell that are displayed on the cell surface by peptide-holding proteins called HLAs,” Mog explains. Their specific target was a peptide containing the R175H mutation of p53 (the 175th amino acid of p53 is mutated from arginine to histidine), displayed on the HLA-A2 allele (gene variation). This is the most common mutation in the tumor suppressor protein p53, which is in turn the most commonly mutated gene in human cancers. 

However, these antigens are present at very low numbers (just one to 10) on a cancer cell, and the classic CAR format would not be able to react to such a small amount.  “Our goal was to combine some of the advantages of the CAR format with those of the natural T cell receptor on T cells, supplemented with additional signaling boosters, so that they could fight cancers more effectively,” Mog says.

The team went through multiple rounds of engineering to come up with the final design, testing their receptors in model cancer cell lines in test tubes and then in mouse models of cancer. The final Co-STAR T cells were able to continuously kill human cancer cells in test tubes.  When tested in mouse models of cancer, Co-STARs induced a robust, long-lasting proliferation of T cells that were able to induce profound remissions, and often cure, human cancer cells growing in mice. By contrast, more conventional T cells or CAR T cells were not able to eradicate the cancer cells in vitro and only brought about temporary tumor control in mice, with the cancers re-emerging days later. 

“Brian’s results demonstrated that Co-STAR T cells combine the advantages of many features of immune cells that normally fight infection in a way that allowed them to effectively kill cancer cells in mouse models,” says co-senior investigator Bert Vogelstein, M.D. , Clayton Professor of Oncology, Howard Hughes Medical Institute investigator and co-director of the Ludwig Center. “Co-STARs address some, but certainly not all, challenges confronting T cell-based therapeutics but are certainly worthy of continued investigation.”

“I was, honestly, incredibly surprised that the Co-STARs worked so well in mice, given that I had generated so many different types of T cells over four years that could only slow the growth of cancers in mice” adds Mog. “Witnessing those cures was a very exciting moment.”

Study co-authors were Nikita Marcou, Sarah DiNapoli, Alexander Pearlman, Tushar Nichakawade, Michael Hwang, Jacqueline Douglass, Emily Han-Chung Hsiue, Stephanie Glavaris, Katharine Wright, Maximilian Konig, Suman Paul, Nicolas Wyhs, Jiaxin Ge, Michelle Miller, P. Aitana Azurmendi, Evangeline Watson, Drew Pardoll, Sandra Gabelli, Chetan Bettegowda, Nickolas Papadopoulos, Kenneth Kinzler and Shibin Zhou of Johns Hopkins.

The work was supported by the Virginia and D.K. Ludwig Fund for Cancer Research, the Lustgarten Foundation, the Commonwealth Fund, Bloomberg Philanthropies and the Bloomberg~Kimmel Institute for Cancer Immunotherapy, the National Institutes of Health (NH) Cancer Center Support Grant P30 CA006973, NIH grants (T32 GM136577, T32 AR048522, 1R21 AI176764, and K08CA270403), the National Institute of General Medical Sciences (grant T32GM148383), the National Cancer Institute (grants T32CA153952 and R37CA230400) and awards from the Leukemia & Lymphoma Society Translational Research Program, the American Society of Hematology, Swim Across America translational cancer research, the Jerome Greene Foundation, the Cupid Foundation, the Stephen and Renee Bisciotti Foundation, the Harrington Scholar-Innovator grant and the Rheumatology Research Foundation.

The Johns Hopkins University has filed patent applications related to technologies described in this paper on which Hsiue, Wright, Douglass, Mog, Hwang, Pearlman, Papadopoulos, Kinzler, Vogelstein, Gabelli, Pardoll and Zhou are listed as inventors. Vogelstein, Kinzler and Papadopoulos are founders of (and Kinzler and Papadopoulos are consultants to) Thrive Earlier Detection, an Exact Sciences company. Vogelstein, Kinzler, Papadopoulos and Zhou hold equity in Exact Sciences and are founders of or consultants to and own equity in Clasp Therapeutics, NeoPhore, and Personal Genome Diagnostics. Vogelstein, Kinzler and Papadopoulos are founders of or consultants to and own equity in Haystack Oncology and Cage Pharma. Papadopoulos is a consultant to Vidium. Vogelstein is a consultant to and holds equity in Catalio Capital Management. Zhou has a research agreement with BioMed Valley Discoveries. Bettegowda is a consultant to DePuy Synthes, Bionaut Labs, Haystack Oncology, Galectin Therapeutics, and Privo Technologies, and is a co-founder of OrisDX and Belay Diagnostics. Gabelli is a founder and holds equity in AMS LLC. Konig received consulting fees from Argenx, Atara Biotherapeutics, Revel Pharmaceuticals, Sana Biotechnology and Sanofi. Douglass previously consulted for Hemogenyx Pharmaceuticals. Paul is a consultant for Merck, owns equity in Gilead and received payment from IQVIA and Curio Science. Pardoll reports grant and patent royalties through Johns Hopkins from BMS, a grant from Compugen, stock from Trieza Therapeutics and Dracen Pharmaceuticals, and founder equity from Potenza. He is a consultant for Aduro Biotech, Amgen, AstraZeneca (MedImmune/Amplimmune), Bayer, DNAtrix, Dynavax Technologies, Ervaxx, FLX Bio, Rock Springs Capital, Janssen, Merck, Tizona and Immunomic Therapeutics. Pardoll is also on the scientific advisory boards of Five Prime Therapeutics, Camden Nexus II and WindMIL and the board of directors for Dracen Pharmaceuticals. Wright and Gabelli are current or former employees of Merck Sharp & Dohme and may own stock or stock options. The companies named above, as well as others, have licensed previously described technologies related to the work described in this paper from The Johns Hopkins University. Vogelstein, Kinzler and Papadopoulos are inventors of some of these technologies. Licenses for these technologies are or will be associated with equity or royalty payments to the inventors as well as to The Johns Hopkins University. Patent applications for the work described in this paper may be filed by The Johns Hopkins University. The terms of all of these arrangements are being managed by The Johns Hopkins University in accordance with its conflict-of-interest policies.

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Methodology

• What Is Quantitative Research? | Definition, Uses & Methods

What Is Quantitative Research? | Definition, Uses & Methods

Published on June 12, 2020 by Pritha Bhandari . Revised on June 22, 2023.

Quantitative research is the process of collecting and analyzing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalize results to wider populations.

Quantitative research is the opposite of qualitative research , which involves collecting and analyzing non-numerical data (e.g., text, video, or audio).

Quantitative research is widely used in the natural and social sciences: biology, chemistry, psychology, economics, sociology, marketing, etc.

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Table of contents

Quantitative research methods, quantitative data analysis, advantages of quantitative research, disadvantages of quantitative research, other interesting articles, frequently asked questions about quantitative research.

You can use quantitative research methods for descriptive, correlational or experimental research.

• In descriptive research , you simply seek an overall summary of your study variables.
• In correlational research , you investigate relationships between your study variables.
• In experimental research , you systematically examine whether there is a cause-and-effect relationship between variables.

Correlational and experimental research can both be used to formally test hypotheses , or predictions, using statistics. The results may be generalized to broader populations based on the sampling method used.

To collect quantitative data, you will often need to use operational definitions that translate abstract concepts (e.g., mood) into observable and quantifiable measures (e.g., self-ratings of feelings and energy levels).

Note that quantitative research is at risk for certain research biases , including information bias , omitted variable bias , sampling bias , or selection bias . Be sure that you’re aware of potential biases as you collect and analyze your data to prevent them from impacting your work too much.

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Once data is collected, you may need to process it before it can be analyzed. For example, survey and test data may need to be transformed from words to numbers. Then, you can use statistical analysis to answer your research questions .

Descriptive statistics will give you a summary of your data and include measures of averages and variability. You can also use graphs, scatter plots and frequency tables to visualize your data and check for any trends or outliers.

Using inferential statistics , you can make predictions or generalizations based on your data. You can test your hypothesis or use your sample data to estimate the population parameter .

First, you use descriptive statistics to get a summary of the data. You find the mean (average) and the mode (most frequent rating) of procrastination of the two groups, and plot the data to see if there are any outliers.

You can also assess the reliability and validity of your data collection methods to indicate how consistently and accurately your methods actually measured what you wanted them to.

Quantitative research is often used to standardize data collection and generalize findings . Strengths of this approach include:

• Replication

Repeating the study is possible because of standardized data collection protocols and tangible definitions of abstract concepts.

• Direct comparisons of results

The study can be reproduced in other cultural settings, times or with different groups of participants. Results can be compared statistically.

• Large samples

Data from large samples can be processed and analyzed using reliable and consistent procedures through quantitative data analysis.

• Hypothesis testing

Using formalized and established hypothesis testing procedures means that you have to carefully consider and report your research variables, predictions, data collection and testing methods before coming to a conclusion.

Despite the benefits of quantitative research, it is sometimes inadequate in explaining complex research topics. Its limitations include:

• Superficiality

Using precise and restrictive operational definitions may inadequately represent complex concepts. For example, the concept of mood may be represented with just a number in quantitative research, but explained with elaboration in qualitative research.

• Narrow focus

Predetermined variables and measurement procedures can mean that you ignore other relevant observations.

• Structural bias

Despite standardized procedures, structural biases can still affect quantitative research. Missing data , imprecise measurements or inappropriate sampling methods are biases that can lead to the wrong conclusions.

• Lack of context

Quantitative research often uses unnatural settings like laboratories or fails to consider historical and cultural contexts that may affect data collection and results.

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If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

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• Degrees of freedom
• Null hypothesis
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• Non-probability sampling
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Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

Reliability and validity are both about how well a method measures something:

• Reliability refers to the  consistency of a measure (whether the results can be reproduced under the same conditions).
• Validity   refers to the  accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research, you also have to consider the internal and external validity of your experiment.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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Are tampons safe or harmful? Study finds that tampons contain arsenic, lead, other metals

"despite this large potential for public health concern, very little research has been done to measure chemicals in tampons,” said the study's lead author..

A new study has found that tampons contain several metals, including arsenic and lead.

"Our findings point towards the need for regulations requiring the testing of metals in tampons by manufacturers," the study says.

The study, which was published by Environment International on July 3, analyzed 30 tampons from 14 tampon brands and found they had measurable concentrations of the following metals:

“Although toxic metals are ubiquitous and we are exposed to low levels at any given time, our study clearly shows that metals are also present in menstrual products and that women might be at higher risk for exposure using these products,” said study co-author  Kathrin Schilling .

Acne treatments abound but what works? Expert gets into pimples and skincare essentials

Metal exposure in tampons is 'large potential for public concern'

According to a news release about the study, tampons "are of particular concern as a potential source of exposure to chemicals, including metals, because the skin of the vagina has a higher potential for chemical absorption than skin elsewhere on the body."

Fifty percent to 80% of people who menstruate use tampons, but the metals listed above "could be absorbed by the vagina’s highly absorptive tissue, resulting in systemic exposure," the study says.

“Despite this large potential for public health concern, very little research has been done to measure chemicals in tampons,” Jenni A. Shearston , the study's lead author, said in a statement. “To our knowledge, this is the first paper to measure metals in tampons. Concerningly, we found concentrations of all metals we tested for, including toxic metals like arsenic and lead.”

More research is needed to measure the presence of other chemicals in tampons and determine whether the metals can affect a person's health.

Metal exposure no different in organic tampon products, study finds

The study analyzed tampons from the USA and the U.K., as well as organic and non-organic tampons, and found that no matter where the tampons came from or how they were classified, neither had lower amounts of metals in them.

How did the metals get into the tampon?

There are a number of ways the metals could have ended up on the tampons, the study says.

• The cotton material could have absorbed it from its environment or nearby contaminants.
• The metals could have been added as a way to add pigment, whitener or an antibacterial agent.

“I really hope that manufacturers are required to test their products for metals, especially for toxic metals,” Shearston said. “It would be exciting to see the public call for this, or to ask for better labeling on tampons and other menstrual products.”

More From Forbes

Study finds rapid rise of telehealth use in u.s. hospitals.

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Telemedicine use soared between 2017 and 2021, according to the results of a new study.

The percentage of U.S. hospitals offering telemedicine services sharply rose between 2017 and 2021, according to the results of a new study. In 2017, the percentage of hospitals offering at least one telemedicine was 46%, rising to 72% in 2021.

The study published in the Journal of General Internal Medicine was conducted between 2017 and 2022, encompassing the critical stages of the Covid-19 pandemic. The number of individual telemedicine encounters soured from 114million in 2020 to 194.4 million in 2021 as the Covid-19 pandemic forced providers to quickly pivot to virtual care in many scenarios.

"Our findings demonstrate the rapid acceleration of telemedicine adoption, particularly in response to the Covid-19 pandemic,” said John Jiang, PhD, Professor of accounting and information systems at Michigan State University, who led the study. “However, we also uncovered significant disparities in implementation across different hospital types and persistent challenges in health information exchange that need to be addressed to fully realize telemedicine’s benefits.”

But is the surge in telehealth use solely due to the pandemic?

"The pandemic was certainly an accelerant, but all of the other needed elements to increase telehealth utilization were there," said Joseph C. Kvedar, MD, Professor at Harvard Medical School in Boston, MA and Board Member and Senior Clinical Advisor for the American Telemedicine Association . "For example, during Covid, people became more comfortable with video calls, and patients and clinicians also became more comfortable communicating virtually."

The study used data from the American Hospital Association's annual survey and the organizations IT supplemental survey, which holds information about electronic medical records, data exchange and use of electronic data. As well as provision and utilization, the study also looked at barriers to implementation, finding that smaller centers and for-profit hospitals tended to have less telemedicine availability than centers which were larger, academic and/or were not-for-profit.

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"Smaller healthcare organizations a lean-running organizations, typically at about a 3% margin, so it becomes more difficult to carve out the type of investment needed," said Kvedar. "One model we could look to not just for small organizations – when, in 2010, clinicians were incentivized to adopt medical records. It could be very powerful if the federal government put funding programs like this in place to support telehealth services."

The study also revealed issues with exchange of electronic health information, with 85% of hospitals studied reporting issues with data exchange due to use of different vendor platforms with different operability. Another finding was that although 90% of hospitals studied allowed patients to view and download their own medical records, only 41% of these permit data to be submitted online.

"By addressing the disparities in adoption and overcoming technical barriers, we can create a more accessible, efficient and patient-centered health care system," said Jiang. "The rapid growth we’ve observed shows the potential; now it’s time to ensure that all patients and health care providers can fully benefit from these technological advancements.”

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Qualitative study.

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Last Update: September 18, 2022 .

• Introduction

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. [1] Instead of collecting numerical data points or intervening or introducing treatments just like in quantitative research, qualitative research helps generate hypothenar to further investigate and understand quantitative data. Qualitative research gathers participants' experiences, perceptions, and behavior. It answers the hows and whys instead of how many or how much. It could be structured as a standalone study, purely relying on qualitative data, or part of mixed-methods research that combines qualitative and quantitative data. This review introduces the readers to some basic concepts, definitions, terminology, and applications of qualitative research.

Qualitative research, at its core, asks open-ended questions whose answers are not easily put into numbers, such as "how" and "why." [2] Due to the open-ended nature of the research questions, qualitative research design is often not linear like quantitative design. [2] One of the strengths of qualitative research is its ability to explain processes and patterns of human behavior that can be difficult to quantify. [3] Phenomena such as experiences, attitudes, and behaviors can be complex to capture accurately and quantitatively. In contrast, a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a particular time or during an event of interest. Quantifying qualitative data certainly is possible, but at its core, qualitative data is looking for themes and patterns that can be difficult to quantify, and it is essential to ensure that the context and narrative of qualitative work are not lost by trying to quantify something that is not meant to be quantified.

However, while qualitative research is sometimes placed in opposition to quantitative research, where they are necessarily opposites and therefore "compete" against each other and the philosophical paradigms associated with each other, qualitative and quantitative work are neither necessarily opposites, nor are they incompatible. [4] While qualitative and quantitative approaches are different, they are not necessarily opposites and certainly not mutually exclusive. For instance, qualitative research can help expand and deepen understanding of data or results obtained from quantitative analysis. For example, say a quantitative analysis has determined a correlation between length of stay and level of patient satisfaction, but why does this correlation exist? This dual-focus scenario shows one way in which qualitative and quantitative research could be integrated.

Qualitative Research Approaches

Ethnography

Ethnography as a research design originates in social and cultural anthropology and involves the researcher being directly immersed in the participant’s environment. [2] Through this immersion, the ethnographer can use a variety of data collection techniques to produce a comprehensive account of the social phenomena that occurred during the research period. [2] That is to say, the researcher’s aim with ethnography is to immerse themselves into the research population and come out of it with accounts of actions, behaviors, events, etc, through the eyes of someone involved in the population. Direct involvement of the researcher with the target population is one benefit of ethnographic research because it can then be possible to find data that is otherwise very difficult to extract and record.

Grounded theory

Grounded Theory is the "generation of a theoretical model through the experience of observing a study population and developing a comparative analysis of their speech and behavior." [5] Unlike quantitative research, which is deductive and tests or verifies an existing theory, grounded theory research is inductive and, therefore, lends itself to research aimed at social interactions or experiences. [3] [2] In essence, Grounded Theory’s goal is to explain how and why an event occurs or how and why people might behave a certain way. Through observing the population, a researcher using the Grounded Theory approach can then develop a theory to explain the phenomena of interest.

Phenomenology

Phenomenology is the "study of the meaning of phenomena or the study of the particular.” [5] At first glance, it might seem that Grounded Theory and Phenomenology are pretty similar, but the differences can be seen upon careful examination. At its core, phenomenology looks to investigate experiences from the individual's perspective. [2] Phenomenology is essentially looking into the "lived experiences" of the participants and aims to examine how and why participants behaved a certain way from their perspective. Herein lies one of the main differences between Grounded Theory and Phenomenology. Grounded Theory aims to develop a theory for social phenomena through an examination of various data sources. In contrast, Phenomenology focuses on describing and explaining an event or phenomenon from the perspective of those who have experienced it.

Narrative research

One of qualitative research’s strengths lies in its ability to tell a story, often from the perspective of those directly involved in it. Reporting on qualitative research involves including details and descriptions of the setting involved and quotes from participants. This detail is called a "thick" or "rich" description and is a strength of qualitative research. Narrative research is rife with the possibilities of "thick" description as this approach weaves together a sequence of events, usually from just one or two individuals, hoping to create a cohesive story or narrative. [2] While it might seem like a waste of time to focus on such a specific, individual level, understanding one or two people’s narratives for an event or phenomenon can help to inform researchers about the influences that helped shape that narrative. The tension or conflict of differing narratives can be "opportunities for innovation." [2]

Research Paradigm

Research paradigms are the assumptions, norms, and standards underpinning different research approaches. Essentially, research paradigms are the "worldviews" that inform research. [4] It is valuable for qualitative and quantitative researchers to understand what paradigm they are working within because understanding the theoretical basis of research paradigms allows researchers to understand the strengths and weaknesses of the approach being used and adjust accordingly. Different paradigms have different ontologies and epistemologies. Ontology is defined as the "assumptions about the nature of reality,” whereas epistemology is defined as the "assumptions about the nature of knowledge" that inform researchers' work. [2] It is essential to understand the ontological and epistemological foundations of the research paradigm researchers are working within to allow for a complete understanding of the approach being used and the assumptions that underpin the approach as a whole. Further, researchers must understand their own ontological and epistemological assumptions about the world in general because their assumptions about the world will necessarily impact how they interact with research. A discussion of the research paradigm is not complete without describing positivist, postpositivist, and constructivist philosophies.

Positivist versus postpositivist

To further understand qualitative research, we must discuss positivist and postpositivist frameworks. Positivism is a philosophy that the scientific method can and should be applied to social and natural sciences. [4] Essentially, positivist thinking insists that the social sciences should use natural science methods in their research. It stems from positivist ontology, that there is an objective reality that exists that is wholly independent of our perception of the world as individuals. Quantitative research is rooted in positivist philosophy, which can be seen in the value it places on concepts such as causality, generalizability, and replicability.

Conversely, postpositivists argue that social reality can never be one hundred percent explained, but could be approximated. [4] Indeed, qualitative researchers have been insisting that there are “fundamental limits to the extent to which the methods and procedures of the natural sciences could be applied to the social world,” and therefore, postpositivist philosophy is often associated with qualitative research. [4] An example of positivist versus postpositivist values in research might be that positivist philosophies value hypothesis-testing, whereas postpositivist philosophies value the ability to formulate a substantive theory.

Constructivist

Constructivism is a subcategory of postpositivism. Most researchers invested in postpositivist research are also constructivist, meaning they think there is no objective external reality that exists but instead that reality is constructed. Constructivism is a theoretical lens that emphasizes the dynamic nature of our world. "Constructivism contends that individuals' views are directly influenced by their experiences, and it is these individual experiences and views that shape their perspective of reality.” [6]  constructivist thought focuses on how "reality" is not a fixed certainty and how experiences, interactions, and backgrounds give people a unique view of the world. Constructivism contends, unlike positivist views, that there is not necessarily an "objective"reality we all experience. This is the ‘relativist’ ontological view that reality and our world are dynamic and socially constructed. Therefore, qualitative scientific knowledge can be inductive as well as deductive.” [4]

So why is it important to understand the differences in assumptions that different philosophies and approaches to research have? Fundamentally, the assumptions underpinning the research tools a researcher selects provide an overall base for the assumptions the rest of the research will have. It can even change the role of the researchers. [2] For example, is the researcher an "objective" observer, such as in positivist quantitative work? Or is the researcher an active participant in the research, as in postpositivist qualitative work? Understanding the philosophical base of the study undertaken allows researchers to fully understand the implications of their work and their role within the research and reflect on their positionality and bias as it pertains to the research they are conducting.

Data Sampling 

The better the sample represents the intended study population, the more likely the researcher is to encompass the varying factors. The following are examples of participant sampling and selection: [7]

• Purposive sampling- selection based on the researcher’s rationale for being the most informative.
• Criterion sampling selection based on pre-identified factors.
• Convenience sampling- selection based on availability.
• Snowball sampling- the selection is by referral from other participants or people who know potential participants.
• Extreme case sampling- targeted selection of rare cases.
• Typical case sampling selection based on regular or average participants. 

Data Collection and Analysis

Qualitative research uses several techniques, including interviews, focus groups, and observation. [1] [2] [3] Interviews may be unstructured, with open-ended questions on a topic, and the interviewer adapts to the responses. Structured interviews have a predetermined number of questions that every participant is asked. It is usually one-on-one and appropriate for sensitive topics or topics needing an in-depth exploration. Focus groups are often held with 8-12 target participants and are used when group dynamics and collective views on a topic are desired. Researchers can be participant-observers to share the experiences of the subject or non-participants or detached observers.

While quantitative research design prescribes a controlled environment for data collection, qualitative data collection may be in a central location or the participants' environment, depending on the study goals and design. Qualitative research could amount to a large amount of data. Data is transcribed, which may then be coded manually or using computer-assisted qualitative data analysis software or CAQDAS such as ATLAS.ti or NVivo. [8] [9] [10]

After the coding process, qualitative research results could be in various formats. It could be a synthesis and interpretation presented with excerpts from the data. [11] Results could also be in the form of themes and theory or model development.

Dissemination

The healthcare team can use two reporting standards to standardize and facilitate the dissemination of qualitative research outcomes. The Consolidated Criteria for Reporting Qualitative Research or COREQ is a 32-item checklist for interviews and focus groups. [12] The Standards for Reporting Qualitative Research (SRQR) is a checklist covering a more comprehensive range of qualitative research. [13]

Applications

Many times, a research question will start with qualitative research. The qualitative research will help generate the research hypothesis, which can be tested with quantitative methods. After the data is collected and analyzed with quantitative methods, a set of qualitative methods can be used to dive deeper into the data to better understand what the numbers truly mean and their implications. The qualitative techniques can then help clarify the quantitative data and also help refine the hypothesis for future research. Furthermore, with qualitative research, researchers can explore poorly studied subjects with quantitative methods. These include opinions, individual actions, and social science research.

An excellent qualitative study design starts with a goal or objective. This should be clearly defined or stated. The target population needs to be specified. A method for obtaining information from the study population must be carefully detailed to ensure no omissions of part of the target population. A proper collection method should be selected that will help obtain the desired information without overly limiting the collected data because, often, the information sought is not well categorized or obtained. Finally, the design should ensure adequate methods for analyzing the data. An example may help better clarify some of the various aspects of qualitative research.

A researcher wants to decrease the number of teenagers who smoke in their community. The researcher could begin by asking current teen smokers why they started smoking through structured or unstructured interviews (qualitative research). The researcher can also get together a group of current teenage smokers and conduct a focus group to help brainstorm factors that may have prevented them from starting to smoke (qualitative research).

In this example, the researcher has used qualitative research methods (interviews and focus groups) to generate a list of ideas of why teens start to smoke and factors that may have prevented them from starting to smoke. Next, the researcher compiles this data. The research found that, hypothetically, peer pressure, health issues, cost, being considered "cool," and rebellious behavior all might increase or decrease the likelihood of teens starting to smoke.

The researcher creates a survey asking teen participants to rank how important each of the above factors is in either starting smoking (for current smokers) or not smoking (for current nonsmokers). This survey provides specific numbers (ranked importance of each factor) and is thus a quantitative research tool.

The researcher can use the survey results to focus efforts on the one or two highest-ranked factors. Let us say the researcher found that health was the primary factor that keeps teens from starting to smoke, and peer pressure was the primary factor that contributed to teens starting smoking. The researcher can go back to qualitative research methods to dive deeper into these for more information. The researcher wants to focus on keeping teens from starting to smoke, so they focus on the peer pressure aspect.

The researcher can conduct interviews and focus groups (qualitative research) about what types and forms of peer pressure are commonly encountered, where the peer pressure comes from, and where smoking starts. The researcher hypothetically finds that peer pressure often occurs after school at the local teen hangouts, mostly in the local park. The researcher also hypothetically finds that peer pressure comes from older, current smokers who provide the cigarettes.

The researcher could further explore this observation made at the local teen hangouts (qualitative research) and take notes regarding who is smoking, who is not, and what observable factors are at play for peer pressure to smoke. The researcher finds a local park where many local teenagers hang out and sees that the smokers tend to hang out in a shady, overgrown area of the park. The researcher notes that smoking teenagers buy their cigarettes from a local convenience store adjacent to the park, where the clerk does not check identification before selling cigarettes. These observations fall under qualitative research.

If the researcher returns to the park and counts how many individuals smoke in each region, this numerical data would be quantitative research. Based on the researcher's efforts thus far, they conclude that local teen smoking and teenagers who start to smoke may decrease if there are fewer overgrown areas of the park and the local convenience store does not sell cigarettes to underage individuals.

The researcher could try to have the parks department reassess the shady areas to make them less conducive to smokers or identify how to limit the sales of cigarettes to underage individuals by the convenience store. The researcher would then cycle back to qualitative methods of asking at-risk populations their perceptions of the changes and what factors are still at play, and quantitative research that includes teen smoking rates in the community and the incidence of new teen smokers, among others. [14] [15]

Qualitative research functions as a standalone research design or combined with quantitative research to enhance our understanding of the world. Qualitative research uses techniques including structured and unstructured interviews, focus groups, and participant observation not only to help generate hypotheses that can be more rigorously tested with quantitative research but also to help researchers delve deeper into the quantitative research numbers, understand what they mean, and understand what the implications are. Qualitative research allows researchers to understand what is going on, especially when things are not easily categorized. [16]

• Issues of Concern

As discussed in the sections above, quantitative and qualitative work differ in many ways, including the evaluation criteria. There are four well-established criteria for evaluating quantitative data: internal validity, external validity, reliability, and objectivity. Credibility, transferability, dependability, and confirmability are the correlating concepts in qualitative research. [4] [11] The corresponding quantitative and qualitative concepts can be seen below, with the quantitative concept on the left and the qualitative concept on the right:

• Internal validity: Credibility
• External validity: Transferability
• Reliability: Dependability
• Objectivity: Confirmability

In conducting qualitative research, ensuring these concepts are satisfied and well thought out can mitigate potential issues from arising. For example, just as a researcher will ensure that their quantitative study is internally valid, qualitative researchers should ensure that their work has credibility. 

Indicators such as triangulation and peer examination can help evaluate the credibility of qualitative work.

• Triangulation: Triangulation involves using multiple data collection methods to increase the likelihood of getting a reliable and accurate result. In our above magic example, the result would be more reliable if we interviewed the magician, backstage hand, and the person who "vanished." In qualitative research, triangulation can include telephone surveys, in-person surveys, focus groups, and interviews and surveying an adequate cross-section of the target demographic.
• Peer examination: A peer can review results to ensure the data is consistent with the findings.

A "thick" or "rich" description can be used to evaluate the transferability of qualitative research, whereas an indicator such as an audit trail might help evaluate the dependability and confirmability.

• Thick or rich description:  This is a detailed and thorough description of details, the setting, and quotes from participants in the research. [5] Thick descriptions will include a detailed explanation of how the study was conducted. Thick descriptions are detailed enough to allow readers to draw conclusions and interpret the data, which can help with transferability and replicability.
• Audit trail: An audit trail provides a documented set of steps of how the participants were selected and the data was collected. The original information records should also be kept (eg, surveys, notes, recordings).

One issue of concern that qualitative researchers should consider is observation bias. Here are a few examples:

• Hawthorne effect: The effect is the change in participant behavior when they know they are being observed. Suppose a researcher wanted to identify factors that contribute to employee theft and tell the employees they will watch them to see what factors affect employee theft. In that case, one would suspect employee behavior would change when they know they are being protected.
• Observer-expectancy effect: Some participants change their behavior or responses to satisfy the researcher's desired effect. This happens unconsciously for the participant, so it is essential to eliminate or limit the transmission of the researcher's views.
• Artificial scenario effect: Some qualitative research occurs in contrived scenarios with preset goals. In such situations, the information may not be accurate because of the artificial nature of the scenario. The preset goals may limit the qualitative information obtained.
• Clinical Significance

Qualitative or quantitative research helps healthcare providers understand patients and the impact and challenges of the care they deliver. Qualitative research provides an opportunity to generate and refine hypotheses and delve deeper into the data generated by quantitative research. Qualitative research is not an island apart from quantitative research but an integral part of research methods to understand the world around us. [17]

• Enhancing Healthcare Team Outcomes

Qualitative research is essential for all healthcare team members as all are affected by qualitative research. Qualitative research may help develop a theory or a model for health research that can be further explored by quantitative research. Much of the qualitative research data acquisition is completed by numerous team members, including social workers, scientists, nurses, etc. Within each area of the medical field, there is copious ongoing qualitative research, including physician-patient interactions, nursing-patient interactions, patient-environment interactions, healthcare team function, patient information delivery, etc. 

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Disclosure: Steven Tenny declares no relevant financial relationships with ineligible companies.

Disclosure: Janelle Brannan declares no relevant financial relationships with ineligible companies.

Disclosure: Grace Brannan declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

• Cite this Page Tenny S, Brannan JM, Brannan GD. Qualitative Study. [Updated 2022 Sep 18]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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