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Qualitative Variable – Types and Examples

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Qualitative Variable

Definition:

Qualitative variable, also known as a categorical variable, is a type of variable in statistics that describes an attribute or characteristic of a data point, rather than a numerical value.

Qualitative variables are typically represented by labels or categories, such as “male” or “female,” and are often used in surveys and polls to gather information about a population’s characteristics.

Types Qualitative Variable

There are two main types of qualitative variables:

Nominal Variables

A nominal variable is a Qualitative Variable where the categories are not ordered in any particular way. For example, gender (male or female), race (Asian, Black, Hispanic, etc.), or religion (Christian, Muslim, Hindu, etc.). Nominal variables can be represented using numbers, but the numbers do not have any quantitative meaning. For example, a researcher might assign the number “1” to male and “2” to female, but these numbers do not represent a quantitative difference between the categories.

Ordinal Variables

An ordinal variable is a Qualitative Variable where the categories are ordered in some way. For example, educational level (high school, college, graduate school), income level (low, medium, high), or level of agreement (strongly agree, somewhat agree, neutral, somewhat disagree, strongly disagree). Ordinal variables can be represented using numbers, and the numbers have a quantitative meaning, but the distance between the categories is not necessarily equal. For example, the difference between “high school” and “college” may not be the same as the difference between “college” and “graduate school.”

Examples of Qualitative Variables

Here are some examples of qualitative variables:

Gender : Male or female
Marital status: Married, single, divorced, widowed
Race : Asian, Black, Hispanic, White, etc.
Religious affiliation: Christian, Muslim, Hindu, Buddhist, etc.
Political affiliation : Democrat, Republican, Independent, etc.
Educational level : High school, college, graduate school
Type of employment : Full-time, part-time, self-employed, unemployed
Type of housing: Apartment, house, condo, etc.
Method of transportation : Car, bus, train, bike, etc.
Language spoken: English, Spanish, French, etc.

Applications of Qualitative Variable

Qualitative variables are used in many applications in different fields, including:

Market research : Qualitative variables are often used in market research to understand consumer behavior and preferences. For example, a company might use qualitative variables such as age, gender, and income to segment their target market and create customized marketing campaigns.
Public opinion polling : Qualitative variables are used in public opinion polling to gather information about people’s attitudes, beliefs, and opinions. Pollsters may ask questions about political affiliation, religious affiliation, or social issues to understand public opinion on a particular topic.
Social sciences research: Qualitative variables are commonly used in social sciences research to study human behavior, culture, and society. Researchers may use qualitative variables to categorize people based on their demographic information or cultural background, and to analyze patterns and trends in behavior or attitudes.
Healthcare research: Qualitative variables are used in healthcare research to identify risk factors and to understand the impact of treatments on patients. Researchers may use qualitative variables such as age, gender, or medical history to identify populations at risk for certain diseases, and to evaluate the effectiveness of different treatment options.
Education research: Qualitative variables are used in education research to study the effectiveness of different teaching methods and to identify factors that influence student learning. Researchers may use qualitative variables such as socio-economic status, educational level, or learning style to analyze patterns and trends in student performance.

When to use Qualitative Variable

Qualitative variables should be used in research when the variable being studied is categorical and does not involve numerical values. Here are some situations where qualitative variables are appropriate:

When studying demographic characteristics: Qualitative variables are useful for studying demographic characteristics such as age, gender, ethnicity, and religion. These variables can be used to segment a population into groups and to compare differences between groups.
When studying attitudes and beliefs : Qualitative variables can be used to study people’s attitudes and beliefs about various topics, such as politics, social issues, or religion. Researchers can use surveys or interviews to gather data on these variables.
When studying cultural differences: Qualitative variables are often used in cross-cultural research to study differences between cultures. Researchers may use qualitative variables such as language spoken, nationality, or cultural background to identify groups for comparison.
When studying consumer behavior : Qualitative variables can be used in market research to study consumer behavior and preferences. Researchers can use qualitative variables such as brand loyalty, product preference, or buying habits to understand consumer behavior.
When studying patient outcomes: Qualitative variables can be used in healthcare research to study patient outcomes, such as quality of life, satisfaction with treatment, or adherence to medication. Researchers can use qualitative variables to identify factors that influence patient outcomes and to develop interventions to improve patient care.

Purpose of Qualitative Variable

The purpose of a qualitative variable is to categorize data into distinct groups based on non-numerical characteristics or attributes. The use of qualitative variables allows researchers to describe and analyze non-quantifiable phenomena, such as attitudes, beliefs, behaviors, and demographic characteristics, and to identify patterns and trends in the data. The main purposes of qualitative variables are:

To describe and categorize : Qualitative variables are used to describe and categorize data into meaningful groups based on characteristics or attributes that are not numerical.
To compare and contrast: Qualitative variables allow researchers to compare and contrast different groups or categories of data, such as different demographic groups or cultural backgrounds.
To identify patterns and trends: Qualitative variables allow researchers to identify patterns and trends in data that may not be apparent with numerical data. For example, a researcher may use qualitative variables to identify cultural differences in attitudes toward healthcare.
To develop hypotheses: Qualitative variables can be used to develop hypotheses or research questions for further study. For example, a researcher may use qualitative variables to identify risk factors for a particular disease, which can then be further studied using quantitative methods.
To inform decision-making: Qualitative variables can provide important information to inform decision-making in fields such as healthcare, education, and business. For example, healthcare providers may use qualitative variables to identify patient preferences and needs, which can inform treatment decisions.

Characteristics of Qualitative Variable

Here are some of the characteristics of qualitative variables:

Categorical : Qualitative variables are categorical in nature, meaning that they describe characteristics or attributes that are not numerical. They can be nominal, ordinal or binary.
Non-numeric : Qualitative variables do not involve numerical values, but rather descriptive or categorical data such as colors, shapes, types, or names.
Limited number of categories: Qualitative variables are often limited to a small number of categories, such as male/female, married/single/divorced, or white/black/Asian.
Mutually exclusive categories : Categories in a qualitative variable must be mutually exclusive, meaning that each observation can only belong to one category.
No numerical order : Unlike quantitative variables, qualitative variables do not have a numerical order or ranking. Categories are assigned based on non-numerical criteria.
Can be used for comparison : Qualitative variables are often used for comparison purposes, such as comparing the frequency of certain behaviors or attitudes across different demographic groups.
Can be used for classification: Qualitative variables can be used to classify data into distinct groups based on common characteristics or attributes. For example, people can be classified into different racial or ethnic groups based on their ancestry.
Can be used for hypothesis testing : Qualitative variables can be used to test hypotheses about differences between groups or categories of data. For example, a researcher may hypothesize that men and women have different attitudes toward a particular social issue, and use a qualitative variable to test this hypothesis.

Advantages of Qualitative Variable

There are several advantages of using qualitative variables.

Rich data: Qualitative variables can provide rich data about complex phenomena such as attitudes, behaviors, and cultural differences. This data can be useful for gaining a deep understanding of a particular issue or topic.
Flexibility : Qualitative variables are flexible and can be used in a variety of research methods, such as interviews, focus groups, and observations. This allows researchers to choose the method that best suits their research question and participants.
Participant perspective : Qualitative variables allow researchers to capture the participant’s perspective and experience. By using open-ended questions or prompts, researchers can gain insight into how participants perceive and interpret a particular issue.
Depth of understanding: Qualitative variables allow for a depth of understanding that may not be possible with quantitative variables alone. Qualitative data can provide details and context that quantitative data may miss.
Contextualization : Qualitative variables can provide contextualization, allowing researchers to understand the cultural, social, and historical factors that shape attitudes and behaviors.
Theory development: Qualitative variables can be useful for developing new theories or refining existing ones. By gathering rich data and analyzing it using qualitative methods, researchers can identify patterns and relationships that can inform the development of new theories.
Researcher reflexivity : Qualitative variables require the researcher to be reflexive and acknowledge their own biases and assumptions. This can help to ensure that the research is ethical and inclusive, and that the data collected is valid and reliable.

Limitations of Qualitative Variable

Some Limitations of Qualitative Variable are as follows:

Subjectivity : Qualitative data is often collected through open-ended questions or prompts, which can lead to subjective responses that are difficult to quantify or compare. This can make it challenging to establish inter-rater reliability and can limit the generalizability of the findings.
Limited sample size : Qualitative research often involves small sample sizes, which can limit the generalizability of the findings. While qualitative research is typically focused on gaining a deep understanding of a particular issue, the findings may not be representative of the broader population.
Time-consuming: Qualitative research can be time-consuming, particularly when collecting and analyzing data. Researchers must spend significant amounts of time in the field, conducting interviews or focus groups, and then transcribing and analyzing the data.
Limited control: Qualitative research often involves limited control over the research environment and the participants. This can make it challenging to ensure that the data collected is valid and reliable.
Limited generalizability: Qualitative research is typically focused on gaining a deep understanding of a particular issue, rather than testing hypotheses or making generalizations about the broader population. As a result, the findings may be less generalizable than those obtained through quantitative research methods.
Ethical concerns: Qualitative research often involves collecting sensitive or personal information from participants. Researchers must take care to ensure that participants are fully informed about the research, that their privacy is protected, and that they are not harmed in any way by their participation.
Bias : Qualitative research can be subject to bias, particularly if the researcher has a vested interest in the outcome of the research. Researchers must take care to acknowledge their own biases and assumptions, and to use multiple sources of data to ensure the validity and reliability of the findings.

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Muhammad Hassan

Researcher, Academic Writer, Web developer

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Qualitative Variable: What is it?

A qualitative variable, also called a categorical variable, is a variable that isn’t numerical . It describes data that fits into categories. For example:

Eye colors (variables include: blue, green, brown, hazel).
States (variables include: Florida, New Jersey, Washington).
Dog breeds (variables include: Alaskan Malamute, German Shepherd, Siberian Husky, Shih tzu).

These are all qualitative variables as they have no natural order. On the other hand, quantitative variables have a value and they can be added, subtracted, divided or multiplied.


Fractions	Cat breeds
Decimals	Cities
Odd Numbers	Fast Food Chains
	College Major
Irrational Numbers	Fraternities
Ordered pairs (x,y)	Hair Color
Negative Numbers	Computer Brands
Map coordinates	Beer breweries
Positive Numbers	Pop music genre
Exponents	Tribe

As a general rule, if you can apply some kind of math (like addition), it’s a quantitative variable . Otherwise, it’s qualitative. For example, you can’t add blue + green (unless you’re in an art class — even then you “mix” them, you don’t add them!).

Numbers are sometimes assigned to qualitative variables for data analysis , but they are still classified as qualitative variables despite the numerical classification. For example, a study may assign the number “1” to males and “2” to females.

Qualitative Variables and the Nominal Scale

Qualitative variables aren’t ordered on a numerical scale so they are placed on a nominal scale . The word “nominal” means “name”, which is exactly what qualitative variables are. A nominal scale is a scale where no ordering is possible or implied (except for alphabetical ordering like New York, Washington, West Virginia or Chelsea, Edinburgh, London). In other words, the nominal scale is where data is assigned to a category.

Qualitative Research : Definition

Qualitative research is the naturalistic study of social meanings and processes, using interviews, observations, and the analysis of texts and images. In contrast to quantitative researchers, whose statistical methods enable broad generalizations about populations (for example, comparisons of the percentages of U.S. demographic groups who vote in particular ways), qualitative researchers use in-depth studies of the social world to analyze how and why groups think and act in particular ways (for instance, case studies of the experiences that shape political views).

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Quantitative vs. Qualitative Research in Psychology

Key Differences

Quantitative Research Methods

Qualitative research methods.

How They Relate

In psychology and other social sciences, researchers are faced with an unresolved question: Can we measure concepts like love or racism the same way we can measure temperature or the weight of a star? Social phenomena⁠—things that happen because of and through human behavior⁠—are especially difficult to grasp with typical scientific models.

At a Glance

Psychologists rely on quantitative and quantitative research to better understand human thought and behavior.

Qualitative research involves collecting and evaluating non-numerical data in order to understand concepts or subjective opinions.
Quantitative research involves collecting and evaluating numerical data.

This article discusses what qualitative and quantitative research are, how they are different, and how they are used in psychology research.

Qualitative Research vs. Quantitative Research

In order to understand qualitative and quantitative psychology research, it can be helpful to look at the methods that are used and when each type is most appropriate.

Psychologists rely on a few methods to measure behavior, attitudes, and feelings. These include:

Self-reports , like surveys or questionnaires
Observation (often used in experiments or fieldwork)
Implicit attitude tests that measure timing in responding to prompts

Most of these are quantitative methods. The result is a number that can be used to assess differences between groups.

However, most of these methods are static, inflexible (you can't change a question because a participant doesn't understand it), and provide a "what" answer rather than a "why" answer.

Sometimes, researchers are more interested in the "why" and the "how." That's where qualitative methods come in.

Qualitative research is about speaking to people directly and hearing their words. It is grounded in the philosophy that the social world is ultimately unmeasurable, that no measure is truly ever "objective," and that how humans make meaning is just as important as how much they score on a standardized test.

Used to develop theories

Takes a broad, complex approach

Answers "why" and "how" questions

Explores patterns and themes

Used to test theories

Takes a narrow, specific approach

Answers "what" questions

Explores statistical relationships

Quantitative methods have existed ever since people have been able to count things. But it is only with the positivist philosophy of Auguste Comte (which maintains that factual knowledge obtained by observation is trustworthy) that it became a "scientific method."

The scientific method follows this general process. A researcher must:

Generate a theory or hypothesis (i.e., predict what might happen in an experiment) and determine the variables needed to answer their question
Develop instruments to measure the phenomenon (such as a survey, a thermometer, etc.)
Develop experiments to manipulate the variables
Collect empirical (measured) data
Analyze data

Quantitative methods are about measuring phenomena, not explaining them.

Quantitative research compares two groups of people. There are all sorts of variables you could measure, and many kinds of experiments to run using quantitative methods.

These comparisons are generally explained using graphs, pie charts, and other visual representations that give the researcher a sense of how the various data points relate to one another.

Basic Assumptions

Quantitative methods assume:

That the world is measurable
That humans can observe objectively
That we can know things for certain about the world from observation

In some fields, these assumptions hold true. Whether you measure the size of the sun 2000 years ago or now, it will always be the same. But when it comes to human behavior, it is not so simple.

As decades of cultural and social research have shown, people behave differently (and even think differently) based on historical context, cultural context, social context, and even identity-based contexts like gender , social class, or sexual orientation .

Therefore, quantitative methods applied to human behavior (as used in psychology and some areas of sociology) should always be rooted in their particular context. In other words: there are no, or very few, human universals.

Statistical information is the primary form of quantitative data used in human and social quantitative research. Statistics provide lots of information about tendencies across large groups of people, but they can never describe every case or every experience. In other words, there are always outliers.

Correlation and Causation

A basic principle of statistics is that correlation is not causation. Researchers can only claim a cause-and-effect relationship under certain conditions:

The study was a true experiment.
The independent variable can be manipulated (for example, researchers cannot manipulate gender, but they can change the primer a study subject sees, such as a picture of nature or of a building).
The dependent variable can be measured through a ratio or a scale.

So when you read a report that "gender was linked to" something (like a behavior or an attitude), remember that gender is NOT a cause of the behavior or attitude. There is an apparent relationship, but the true cause of the difference is hidden.

Pitfalls of Quantitative Research

Quantitative methods are one way to approach the measurement and understanding of human and social phenomena. But what's missing from this picture?

As noted above, statistics do not tell us about personal, individual experiences and meanings. While surveys can give a general idea, respondents have to choose between only a few responses. This can make it difficult to understand the subtleties of different experiences.

Quantitative methods can be helpful when making objective comparisons between groups or when looking for relationships between variables. They can be analyzed statistically, which can be helpful when looking for patterns and relationships.

Qualitative data are not made out of numbers but rather of descriptions, metaphors, symbols, quotes, analysis, concepts, and characteristics. This approach uses interviews, written texts, art, photos, and other materials to make sense of human experiences and to understand what these experiences mean to people.

While quantitative methods ask "what" and "how much," qualitative methods ask "why" and "how."

Qualitative methods are about describing and analyzing phenomena from a human perspective. There are many different philosophical views on qualitative methods, but in general, they agree that some questions are too complex or impossible to answer with standardized instruments.

These methods also accept that it is impossible to be completely objective in observing phenomena. Researchers have their own thoughts, attitudes, experiences, and beliefs, and these always color how people interpret results.

Qualitative Approaches

There are many different approaches to qualitative research, with their own philosophical bases. Different approaches are best for different kinds of projects. For example:

Case studies and narrative studies are best for single individuals. These involve studying every aspect of a person's life in great depth.
Phenomenology aims to explain experiences. This type of work aims to describe and explore different events as they are consciously and subjectively experienced.
Grounded theory develops models and describes processes. This approach allows researchers to construct a theory based on data that is collected, analyzed, and compared to reach new discoveries.
Ethnography describes cultural groups. In this approach, researchers immerse themselves in a community or group in order to observe behavior.

Qualitative researchers must be aware of several different methods and know each thoroughly enough to produce valuable research.

Some researchers specialize in a single method, but others specialize in a topic or content area and use many different methods to explore the topic, providing different information and a variety of points of view.

There is not a single model or method that can be used for every qualitative project. Depending on the research question, the people participating, and the kind of information they want to produce, researchers will choose the appropriate approach.

Interpretation

Qualitative research does not look into causal relationships between variables, but rather into themes, values, interpretations, and meanings. As a rule, then, qualitative research is not generalizable (cannot be applied to people outside the research participants).

The insights gained from qualitative research can extend to other groups with proper attention to specific historical and social contexts.

Relationship Between Qualitative and Quantitative Research

It might sound like quantitative and qualitative research do not play well together. They have different philosophies, different data, and different outputs. However, this could not be further from the truth.

These two general methods complement each other. By using both, researchers can gain a fuller, more comprehensive understanding of a phenomenon.

For example, a psychologist wanting to develop a new survey instrument about sexuality might and ask a few dozen people questions about their sexual experiences (this is qualitative research). This gives the researcher some information to begin developing questions for their survey (which is a quantitative method).

After the survey, the same or other researchers might want to dig deeper into issues brought up by its data. Follow-up questions like "how does it feel when...?" or "what does this mean to you?" or "how did you experience this?" can only be answered by qualitative research.

By using both quantitative and qualitative data, researchers have a more holistic, well-rounded understanding of a particular topic or phenomenon.

Qualitative and quantitative methods both play an important role in psychology. Where quantitative methods can help answer questions about what is happening in a group and to what degree, qualitative methods can dig deeper into the reasons behind why it is happening. By using both strategies, psychology researchers can learn more about human thought and behavior.

Gough B, Madill A. Subjectivity in psychological science: From problem to prospect . Psychol Methods . 2012;17(3):374-384. doi:10.1037/a0029313

Pearce T. “Science organized”: Positivism and the metaphysical club, 1865–1875 . J Hist Ideas . 2015;76(3):441-465.

Adams G. Context in person, person in context: A cultural psychology approach to social-personality psychology . In: Deaux K, Snyder M, eds. The Oxford Handbook of Personality and Social Psychology . Oxford University Press; 2012:182-208.

Brady HE. Causation and explanation in social science . In: Goodin RE, ed. The Oxford Handbook of Political Science. Oxford University Press; 2011. doi:10.1093/oxfordhb/9780199604456.013.0049

Chun Tie Y, Birks M, Francis K. Grounded theory research: A design framework for novice researchers . SAGE Open Med . 2019;7:2050312118822927. doi:10.1177/2050312118822927

Reeves S, Peller J, Goldman J, Kitto S. Ethnography in qualitative educational research: AMEE Guide No. 80 . Medical Teacher . 2013;35(8):e1365-e1379. doi:10.3109/0142159X.2013.804977

Salkind NJ, ed. Encyclopedia of Research Design . Sage Publishing.

Shaughnessy JJ, Zechmeister EB, Zechmeister JS. Research Methods in Psychology . McGraw Hill Education.

By Anabelle Bernard Fournier Anabelle Bernard Fournier is a researcher of sexual and reproductive health at the University of Victoria as well as a freelance writer on various health topics.

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Neag School of Education

Educational Research Basics by Del Siegle

Each person/thing we collect data on is called an OBSERVATION (in our work these are usually people/subjects. Currently, the term participant rather than subject is used when describing the people from whom we collect data).

OBSERVATIONS (participants) possess a variety of CHARACTERISTICS .

If a CHARACTERISTIC of an OBSERVATION (participant) is the same for every member of the group (doesn’t vary) it is called a CONSTANT .

If a CHARACTERISTIC of an OBSERVATION (participant) differs for group members it is called a VARIABLE . In research we don’t get excited about CONSTANTS (since everyone is the same on that characteristic); we’re more interested in VARIABLES. Variables can be classified as QUANTITATIVE or QUALITATIVE (also known as CATEGORICAL).

QUANTITATIVE variables are ones that exist along a continuum that runs from low to high. Ordinal, interval, and ratio variables are quantitative. QUANTITATIVE variables are sometimes called CONTINUOUS VARIABLES because they have a variety (continuum) of characteristics. Height in inches and scores on a test would be examples of quantitative variables.

QUALITATIVE variables do not express differences in amount, only differences. They are sometimes referred to as CATEGORICAL variables because they classify by categories. Nominal variables such as gender, religion, or eye color are CATEGORICAL variables. Generally speaking, categorical variables

Categorical variables are groups…such as gender or type of degree sought. Quantitative variables are numbers that have a range…like weight in pounds or baskets made during a ball game. When we analyze data we do turn the categorical variables into numbers but only for identification purposes…e.g. 1 = male and 2 = female. Just because 2 = female does not mean that females are better than males who are only 1. With quantitative data having a higher number means you have more of something. So higher values have meaning.

A special case of a CATEGORICAL variable is a DICHOTOMOUS VARIABLE. DICHOTOMOUS variables have only two CHARACTERISTICS (male or female). When naming QUALITATIVE variables, it is important to name the category rather than the levels (i.e., gender is the variable name, not male and female).

Variables have different purposes or roles…

Independent (Experimental, Manipulated, Treatment, Grouping) Variable- That factor which is measured, manipulated, or selected by the experimenter to determine its relationship to an observed phenomenon. “In a research study, independent variables are antecedent conditions that are presumed to affect a dependent variable. They are either manipulated by the researcher or are observed by the researcher so that their values can be related to that of the dependent variable. For example, in a research study on the relationship between mosquitoes and mosquito bites, the number of mosquitoes per acre of ground would be an independent variable” (Jaeger, 1990, p. 373)

While the independent variable is often manipulated by the researcher, it can also be a classification where subjects are assigned to groups. In a study where one variable causes the other, the independent variable is the cause. In a study where groups are being compared, the independent variable is the group classification.

Dependent (Outcome) Variable- That factor which is observed and measured to determine the effect of the independent variable, i.e., that factor that appears, disappears, or varies as the experimenter introduces, removes, or varies the independent variable. “In a research study, the independent variable defines a principal focus of research interest. It is the consequent variable that is presumably affected by one or more independent variables that are either manipulated by the researcher or observed by the researcher and regarded as antecedent conditions that determine the value of the dependent variable. For example, in a study of the relationship between mosquitoes and mosquito bites, the number of mosquito bites per hour would be the dependent variable” (Jaeger, 1990, p. 370). The dependent variable is the participant’s response.

The dependent variable is the outcome. In an experiment, it may be what was caused or what changed as a result of the study. In a comparison of groups, it is what they differ on.

Moderator Variable- That factor which is measured, manipulated, or selected by the experimenter to discover whether it modifies the relationship of the independent variable to an observed phenomenon. It is a special type of independent variable.

The independent variable’s relationship with the dependent variable may change under different conditions. That condition is the moderator variable. In a study of two methods of teaching reading, one of the methods of teaching reading may work better with boys than girls. Method of teaching reading is the independent variable and reading achievement is the dependent variable. Gender is the moderator variable because it moderates or changes the relationship between the independent variable (teaching method) and the dependent variable (reading achievement).

Suppose we do a study of reading achievement where we compare whole language with phonics, and we also include students’ social economic status (SES) as a variable. The students are randomly assigned to either whole language instruction or phonics instruction. There are students of high and low SES in each group.

Let’s assume that we found that whole language instruction worked better than phonics instruction with the high SES students, but phonics instruction worked better than whole language instruction with the low SES students. Later you will learn in statistics that this is an interaction effect. In this study, language instruction was the independent variable (with two levels: phonics and whole language). SES was the moderator variable (with two levels: high and low). Reading achievement was the dependent variable (measured on a continuous scale so there aren’t levels).

With a moderator variable, we find the type of instruction did make a difference, but it worked differently for the two groups on the moderator variable. We select this moderator variable because we think it is a variable that will moderate the effect of the independent on the dependent. We make this decision before we start the study.

If the moderator had not been in the study above, we would have said that there was no difference in reading achievement between the two types of reading instruction. This would have happened because the average of the high and low scores of each SES group within a reading instruction group would cancel each other an produce what appears to be average reading achievement in each instruction group (i.e., Phonics: Low—6 and High—2; Whole Language: Low—2 and High—6; Phonics has an average of 4 and Whole Language has an average of 4. If we just look at the averages (without regard to the moderator), it appears that the instruction types produced similar results).

Extraneous Variable- Those factors which cannot be controlled. Extraneous variables are independent variables that have not been controlled. They may or may not influence the results. One way to control an extraneous variable which might influence the results is to make it a constant (keep everyone in the study alike on that characteristic). If SES were thought to influence achievement, then restricting the study to one SES level would eliminate SES as an extraneous variable.

Here are some examples similar to your homework:

Null Hypothesis: Students who receive pizza coupons as a reward do not read more books than students who do not receive pizza coupon rewards. Independent Variable: Reward Status Dependent Variable: Number of Books Read

High achieving students do not perform better than low achieving student when writing stories regardless of whether they use paper and pencil or a word processor. Independent Variable: Instrument Used for Writing Moderator Variable: Ability Level of the Students Dependent Variable: Quality of Stories Written When we are comparing two groups, the groups are the independent variable. When we are testing whether something influences something else, the influence (cause) is the independent variable. The independent variable is also the one we manipulate. For example, consider the hypothesis “Teachers given higher pay will have more positive attitudes toward children than teachers given lower pay.” One approach is to ask ourselves “Are there two or more groups being compared?” The answer is “Yes.” “What are the groups?” Teachers who are given higher pay and teachers who are given lower pay. Therefore, the independent variable is teacher pay (it has two levels– high pay and low pay). The dependent variable (what the groups differ on) is attitude towards school.

We could also approach this another way. “Is something causing something else?” The answer is “Yes.” “What is causing what?” Teacher pay is causing attitude towards school. Therefore, teacher pay is the independent variable (cause) and attitude towards school is the dependent variable (outcome).

Research Questions and Hypotheses

The research question drives the study. It should specifically state what is being investigated. Statisticians often convert their research questions to null and alternative hypotheses. The null hypothesis states that no relationship (correlation study) or difference (experimental study) exists. Converting research questions to hypotheses is a simple task. Take the questions and make it a positive statement that says a relationship exists (correlation studies) or a difference exists (experiment study) between the groups and we have the alternative hypothesis. Write a statement that a relationship does not exist or a difference does not exist and we have the null hypothesis.

Format for sample research questions and accompanying hypotheses:

Research Question for Relationships: Is there a relationship between height and weight? Null Hypothesis: There is no relationship between height and weight. Alternative Hypothesis: There is a relationship between height and weight.

When a researcher states a nondirectional hypothesis in a study that compares the performance of two groups, she doesn’t state which group she believes will perform better. If the word “more” or “less” appears in the hypothesis, there is a good chance that we are reading a directional hypothesis. A directional hypothesis is one where the researcher states which group she believes will perform better. Most researchers use nondirectional hypotheses.

We usually write the alternative hypothesis (what we believe might happen) before we write the null hypothesis (saying it won’t happen).

Directional Research Question for Differences: Do boys like reading more than girls? Null Hypothesis: Boys do not like reading more than girls. Alternative Hypothesis: Boys do like reading more than girls.

Nondirectional Research Question for Differences: Is there a difference between boys’ and girls’ attitude towards reading? –or– Do boys’ and girls’ attitude towards reading differ? Null Hypothesis: There is no difference between boys’ and girls’ attitude towards reading. –or– Boys’ and girls’ attitude towards reading do not differ. Alternative Hypothesis: There is a difference between boys’ and girls’ attitude towards reading. –or– Boys’ and girls’ attitude towards reading differ.

Del Siegle, Ph.D. Neag School of Education – University of Connecticut [email protected] www.delsiegle.com

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Qualitative vs. Quantitative Research | Differences, Examples & Methods

Qualitative vs. Quantitative Research | Differences, Examples & Methods

Published on April 12, 2019 by Raimo Streefkerk . Revised on June 22, 2023.

When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Both are important for gaining different kinds of knowledge.

Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions.

Quantitative research is at risk for research biases including information bias , omitted variable bias , sampling bias , or selection bias . Qualitative research Qualitative research is expressed in words . It is used to understand concepts, thoughts or experiences. This type of research enables you to gather in-depth insights on topics that are not well understood.

Common qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories.

The differences between quantitative and qualitative research, data collection methods, when to use qualitative vs. quantitative research, how to analyze qualitative and quantitative data, other interesting articles, frequently asked questions about qualitative and quantitative research.

Quantitative and qualitative research use different research methods to collect and analyze data, and they allow you to answer different kinds of research questions.

Quantitative and qualitative data can be collected using various methods. It is important to use a data collection method that will help answer your research question(s).

Many data collection methods can be either qualitative or quantitative. For example, in surveys, observational studies or case studies , your data can be represented as numbers (e.g., using rating scales or counting frequencies) or as words (e.g., with open-ended questions or descriptions of what you observe).

However, some methods are more commonly used in one type or the other.

Quantitative data collection methods

Surveys : List of closed or multiple choice questions that is distributed to a sample (online, in person, or over the phone).
Experiments : Situation in which different types of variables are controlled and manipulated to establish cause-and-effect relationships.
Observations : Observing subjects in a natural environment where variables can’t be controlled.

Qualitative data collection methods

Interviews : Asking open-ended questions verbally to respondents.
Focus groups : Discussion among a group of people about a topic to gather opinions that can be used for further research.
Ethnography : Participating in a community or organization for an extended period of time to closely observe culture and behavior.
Literature review : Survey of published works by other authors.

A rule of thumb for deciding whether to use qualitative or quantitative data is:

Use quantitative research if you want to confirm or test something (a theory or hypothesis )
Use qualitative research if you want to understand something (concepts, thoughts, experiences)

For most research topics you can choose a qualitative, quantitative or mixed methods approach . Which type you choose depends on, among other things, whether you’re taking an inductive vs. deductive research approach ; your research question(s) ; whether you’re doing experimental , correlational , or descriptive research ; and practical considerations such as time, money, availability of data, and access to respondents.

Quantitative research approach

You survey 300 students at your university and ask them questions such as: “on a scale from 1-5, how satisfied are your with your professors?”

You can perform statistical analysis on the data and draw conclusions such as: “on average students rated their professors 4.4”.

Qualitative research approach

You conduct in-depth interviews with 15 students and ask them open-ended questions such as: “How satisfied are you with your studies?”, “What is the most positive aspect of your study program?” and “What can be done to improve the study program?”

Based on the answers you get you can ask follow-up questions to clarify things. You transcribe all interviews using transcription software and try to find commonalities and patterns.

Mixed methods approach

You conduct interviews to find out how satisfied students are with their studies. Through open-ended questions you learn things you never thought about before and gain new insights. Later, you use a survey to test these insights on a larger scale.

It’s also possible to start with a survey to find out the overall trends, followed by interviews to better understand the reasons behind the trends.

Qualitative or quantitative data by itself can’t prove or demonstrate anything, but has to be analyzed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.

Analyzing quantitative data

Quantitative data is based on numbers. Simple math or more advanced statistical analysis is used to discover commonalities or patterns in the data. The results are often reported in graphs and tables.

Applications such as Excel, SPSS, or R can be used to calculate things like:

Average scores ( means )
The number of times a particular answer was given
The correlation or causation between two or more variables
The reliability and validity of the results

Analyzing qualitative data

Qualitative data is more difficult to analyze than quantitative data. It consists of text, images or videos instead of numbers.

Some common approaches to analyzing qualitative data include:

Qualitative content analysis : Tracking the occurrence, position and meaning of words or phrases
Thematic analysis : Closely examining the data to identify the main themes and patterns
Discourse analysis : Studying how communication works in social contexts

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.

Chi square goodness of fit test
Degrees of freedom
Null hypothesis
Discourse analysis
Control groups
Mixed methods research
Non-probability sampling
Quantitative research
Inclusion and exclusion criteria

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 .

The research methods you use depend on the type of data you need to answer your research question .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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.

There are various approaches to qualitative data analysis , but they all share five steps in common:

Prepare and organize your data.
Review and explore your data.
Develop a data coding system.
Assign codes to the data.
Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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Qualitative vs Quantitative Research Methods & Data Analysis

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The main difference between quantitative and qualitative research is the type of data they collect and analyze.

Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed numerically. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.
Qualitative research gathers non-numerical data (words, images, sounds) to explore subjective experiences and attitudes, often via observation and interviews. It aims to produce detailed descriptions and uncover new insights about the studied phenomenon.

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What Is Qualitative Research?

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.

Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.

Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Denzin and Lincoln (1994, p. 2)

Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner ).

Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human. Exploring participants’ experiences is known as a phenomenological approach (re: Humanism ).

Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.

Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.

Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.

Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.

Qualitative Methods

There are different types of qualitative research methods, including diary accounts, in-depth interviews , documents, focus groups , case study research , and ethnography .

The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.

The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience. Denzin and Lincoln (1994, p. 14)

Here are some examples of qualitative data:

Interview transcripts : Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.

Observations : The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.

Unstructured interviews : generate qualitative data through the use of open questions. This allows the respondent to talk in some depth, choosing their own words. This helps the researcher develop a real sense of a person’s understanding of a situation.

Diaries or journals : Written accounts of personal experiences or reflections.

Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.

Qualitative Data Analysis

Qualitative research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.

Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006), or discourse analysis .

For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded .

Key Features

Events can be understood adequately only if they are seen in context. Therefore, a qualitative researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.
Qualitative researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, qualitative research is an interactive process in which the persons studied teach the researcher about their lives.
The qualitative researcher is an integral part of the data; without the active participation of the researcher, no data exists.
The study’s design evolves during the research and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality. It is subjective and exists only in reference to the observer.
The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.

Limitations of Qualitative Research

Because of the time and costs involved, qualitative designs do not generally draw samples from large-scale data sets.
The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.

Advantages of Qualitative Research

Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.
Qualitative descriptions can be important in suggesting possible relationships, causes, effects, and dynamic processes.
Qualitative analysis allows for ambiguities/contradictions in the data, which reflect social reality (Denscombe, 2010).
Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative reports to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.

What Is Quantitative Research?

Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.

The goals of quantitative research are to test causal relationships between variables , make predictions, and generalize results to wider populations.

Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.

Quantitative Methods

Experiments typically yield quantitative data, as they are concerned with measuring things. However, other research methods, such as controlled observations and questionnaires , can produce both quantitative information.

For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).

Experimental methods limit how research participants react to and express appropriate social behavior.

Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.

There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:

Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles .

The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.

Neuroimaging data : Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.

This data can be analyzed to identify brain regions involved in specific mental processes or disorders.

For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.

The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms.

Quantitative Data Analysis

Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.

Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).

Quantitative researchers try to control extraneous variables by conducting their studies in the lab.
The research aims for objectivity (i.e., without bias) and is separated from the data.
The design of the study is determined before it begins.
For the quantitative researcher, the reality is objective, exists separately from the researcher, and can be seen by anyone.
Research is used to test a theory and ultimately support or reject it.

Limitations of Quantitative Research

Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions they may have for those participants (Carr, 1994).
Researcher expertise: Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).
Variability of data quantity: Large sample sizes are needed for more accurate analysis. Small-scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.
Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.

Advantages of Quantitative Research

Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective and rational (Carr, 1994; Denscombe, 2010).
Useful for testing and validating already constructed theories.
Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).
Replication: Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.
Hypotheses can also be tested because of statistical analysis (Antonius, 2003).

Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage.

Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage.

Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101.

Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing? Journal of advanced nursing, 20(4) , 716-721.

Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.

Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.

Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4) , 364.

Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.

Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage

Further Information

Mixed methods research
Designing qualitative research
Methods of data collection and analysis
Introduction to quantitative and qualitative research
Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
Qualitative research in health care: Analysing qualitative data
Qualitative data analysis: the framework approach
Using the framework method for the analysis of
Qualitative data in multi-disciplinary health research
Content Analysis
Grounded Theory
Thematic Analysis

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what is the variable in qualitative research

Variables and Data Collection

Read these sections and complete the questions at the end of each section. This section introduces several types of data and their distinguishing features. You will learn about independent and dependent variables and how common data can be coded and collected.

Qualitative and Quantitative Variables

An important distinction between variables is between qualitative variables and quantitative variables. Qualitative variables are those that express a qualitative attribute such as hair color, eye color, religion, favorite movie, gender, and so on. The values of a qualitative variable do not imply a numerical ordering. Values of the variable "religion" differ qualitatively; no ordering of religions is implied. Qualitative variables are sometimes referred to as categorical variables. Quantitative variables are those variables that are measured in terms of numbers. Some examples of quantitative variables are height, weight, and shoe size.

In the study on the effect of diet discussed above, the independent variable was type of supplement: none, strawberry, blueberry, and spinach. The variable "type of supplement" is a qualitative variable; there is nothing quantitative about it. In contrast, the dependent variable "memory test" is a quantitative variable since memory performance was measured on a quantitative scale (number correct).

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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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What is Qualitative in Qualitative Research

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Published: 27 February 2019
Volume 42 , pages 139–160, ( 2019 )

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What is qualitative research? If we look for a precise definition of qualitative research, and specifically for one that addresses its distinctive feature of being “qualitative,” the literature is meager. In this article we systematically search, identify and analyze a sample of 89 sources using or attempting to define the term “qualitative.” Then, drawing on ideas we find scattered across existing work, and based on Becker’s classic study of marijuana consumption, we formulate and illustrate a definition that tries to capture its core elements. We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. This formulation is developed as a tool to help improve research designs while stressing that a qualitative dimension is present in quantitative work as well. Additionally, it can facilitate teaching, communication between researchers, diminish the gap between qualitative and quantitative researchers, help to address critiques of qualitative methods, and be used as a standard of evaluation of qualitative research.

What is Qualitative in Research

Unsettling definitions of qualitative research, what is “qualitative” in qualitative research why the answer does not matter but the question is important, explore related subjects.

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If we assume that there is something called qualitative research, what exactly is this qualitative feature? And how could we evaluate qualitative research as good or not? Is it fundamentally different from quantitative research? In practice, most active qualitative researchers working with empirical material intuitively know what is involved in doing qualitative research, yet perhaps surprisingly, a clear definition addressing its key feature is still missing.

To address the question of what is qualitative we turn to the accounts of “qualitative research” in textbooks and also in empirical work. In his classic, explorative, interview study of deviance Howard Becker ( 1963 ) asks ‘How does one become a marijuana user?’ In contrast to pre-dispositional and psychological-individualistic theories of deviant behavior, Becker’s inherently social explanation contends that becoming a user of this substance is the result of a three-phase sequential learning process. First, potential users need to learn how to smoke it properly to produce the “correct” effects. If not, they are likely to stop experimenting with it. Second, they need to discover the effects associated with it; in other words, to get “high,” individuals not only have to experience what the drug does, but also to become aware that those sensations are related to using it. Third, they require learning to savor the feelings related to its consumption – to develop an acquired taste. Becker, who played music himself, gets close to the phenomenon by observing, taking part, and by talking to people consuming the drug: “half of the fifty interviews were conducted with musicians, the other half covered a wide range of people, including laborers, machinists, and people in the professions” (Becker 1963 :56).

Another central aspect derived through the common-to-all-research interplay between induction and deduction (Becker 2017 ), is that during the course of his research Becker adds scientifically meaningful new distinctions in the form of three phases—distinctions, or findings if you will, that strongly affect the course of his research: its focus, the material that he collects, and which eventually impact his findings. Each phase typically unfolds through social interaction, and often with input from experienced users in “a sequence of social experiences during which the person acquires a conception of the meaning of the behavior, and perceptions and judgments of objects and situations, all of which make the activity possible and desirable” (Becker 1963 :235). In this study the increased understanding of smoking dope is a result of a combination of the meaning of the actors, and the conceptual distinctions that Becker introduces based on the views expressed by his respondents. Understanding is the result of research and is due to an iterative process in which data, concepts and evidence are connected with one another (Becker 2017 ).

Indeed, there are many definitions of qualitative research, but if we look for a definition that addresses its distinctive feature of being “qualitative,” the literature across the broad field of social science is meager. The main reason behind this article lies in the paradox, which, to put it bluntly, is that researchers act as if they know what it is, but they cannot formulate a coherent definition. Sociologists and others will of course continue to conduct good studies that show the relevance and value of qualitative research addressing scientific and practical problems in society. However, our paper is grounded in the idea that providing a clear definition will help us improve the work that we do. Among researchers who practice qualitative research there is clearly much knowledge. We suggest that a definition makes this knowledge more explicit. If the first rationale for writing this paper refers to the “internal” aim of improving qualitative research, the second refers to the increased “external” pressure that especially many qualitative researchers feel; pressure that comes both from society as well as from other scientific approaches. There is a strong core in qualitative research, and leading researchers tend to agree on what it is and how it is done. Our critique is not directed at the practice of qualitative research, but we do claim that the type of systematic work we do has not yet been done, and that it is useful to improve the field and its status in relation to quantitative research.

The literature on the “internal” aim of improving, or at least clarifying qualitative research is large, and we do not claim to be the first to notice the vagueness of the term “qualitative” (Strauss and Corbin 1998 ). Also, others have noted that there is no single definition of it (Long and Godfrey 2004 :182), that there are many different views on qualitative research (Denzin and Lincoln 2003 :11; Jovanović 2011 :3), and that more generally, we need to define its meaning (Best 2004 :54). Strauss and Corbin ( 1998 ), for example, as well as Nelson et al. (1992:2 cited in Denzin and Lincoln 2003 :11), and Flick ( 2007 :ix–x), have recognized that the term is problematic: “Actually, the term ‘qualitative research’ is confusing because it can mean different things to different people” (Strauss and Corbin 1998 :10–11). Hammersley has discussed the possibility of addressing the problem, but states that “the task of providing an account of the distinctive features of qualitative research is far from straightforward” ( 2013 :2). This confusion, as he has recently further argued (Hammersley 2018 ), is also salient in relation to ethnography where different philosophical and methodological approaches lead to a lack of agreement about what it means.

Others (e.g. Hammersley 2018 ; Fine and Hancock 2017 ) have also identified the treat to qualitative research that comes from external forces, seen from the point of view of “qualitative research.” This threat can be further divided into that which comes from inside academia, such as the critique voiced by “quantitative research” and outside of academia, including, for example, New Public Management. Hammersley ( 2018 ), zooming in on one type of qualitative research, ethnography, has argued that it is under treat. Similarly to Fine ( 2003 ), and before him Gans ( 1999 ), he writes that ethnography’ has acquired a range of meanings, and comes in many different versions, these often reflecting sharply divergent epistemological orientations. And already more than twenty years ago while reviewing Denzin and Lincoln’ s Handbook of Qualitative Methods Fine argued:

While this increasing centrality [of qualitative research] might lead one to believe that consensual standards have developed, this belief would be misleading. As the methodology becomes more widely accepted, querulous challengers have raised fundamental questions that collectively have undercut the traditional models of how qualitative research is to be fashioned and presented (1995:417).

According to Hammersley, there are today “serious treats to the practice of ethnographic work, on almost any definition” ( 2018 :1). He lists five external treats: (1) that social research must be accountable and able to show its impact on society; (2) the current emphasis on “big data” and the emphasis on quantitative data and evidence; (3) the labor market pressure in academia that leaves less time for fieldwork (see also Fine and Hancock 2017 ); (4) problems of access to fields; and (5) the increased ethical scrutiny of projects, to which ethnography is particularly exposed. Hammersley discusses some more or less insufficient existing definitions of ethnography.

The current situation, as Hammersley and others note—and in relation not only to ethnography but also qualitative research in general, and as our empirical study shows—is not just unsatisfactory, it may even be harmful for the entire field of qualitative research, and does not help social science at large. We suggest that the lack of clarity of qualitative research is a real problem that must be addressed.

Towards a Definition of Qualitative Research

Seen in an historical light, what is today called qualitative, or sometimes ethnographic, interpretative research – or a number of other terms – has more or less always existed. At the time the founders of sociology – Simmel, Weber, Durkheim and, before them, Marx – were writing, and during the era of the Methodenstreit (“dispute about methods”) in which the German historical school emphasized scientific methods (cf. Swedberg 1990 ), we can at least speak of qualitative forerunners.

Perhaps the most extended discussion of what later became known as qualitative methods in a classic work is Bronisław Malinowski’s ( 1922 ) Argonauts in the Western Pacific , although even this study does not explicitly address the meaning of “qualitative.” In Weber’s ([1921–-22] 1978) work we find a tension between scientific explanations that are based on observation and quantification and interpretative research (see also Lazarsfeld and Barton 1982 ).

If we look through major sociology journals like the American Sociological Review , American Journal of Sociology , or Social Forces we will not find the term qualitative sociology before the 1970s. And certainly before then much of what we consider qualitative classics in sociology, like Becker’ study ( 1963 ), had already been produced. Indeed, the Chicago School often combined qualitative and quantitative data within the same study (Fine 1995 ). Our point being that before a disciplinary self-awareness the term quantitative preceded qualitative, and the articulation of the former was a political move to claim scientific status (Denzin and Lincoln 2005 ). In the US the World War II seem to have sparked a critique of sociological work, including “qualitative work,” that did not follow the scientific canon (Rawls 2018 ), which was underpinned by a scientifically oriented and value free philosophy of science. As a result the attempts and practice of integrating qualitative and quantitative sociology at Chicago lost ground to sociology that was more oriented to surveys and quantitative work at Columbia under Merton-Lazarsfeld. The quantitative tradition was also able to present textbooks (Lundberg 1951 ) that facilitated the use this approach and its “methods.” The practices of the qualitative tradition, by and large, remained tacit or was part of the mentoring transferred from the renowned masters to their students.

This glimpse into history leads us back to the lack of a coherent account condensed in a definition of qualitative research. Many of the attempts to define the term do not meet the requirements of a proper definition: A definition should be clear, avoid tautology, demarcate its domain in relation to the environment, and ideally only use words in its definiens that themselves are not in need of definition (Hempel 1966 ). A definition can enhance precision and thus clarity by identifying the core of the phenomenon. Preferably, a definition should be short. The typical definition we have found, however, is an ostensive definition, which indicates what qualitative research is about without informing us about what it actually is :

Qualitative research is multimethod in focus, involving an interpretative, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Qualitative research involves the studied use and collection of a variety of empirical materials – case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts – that describe routine and problematic moments and meanings in individuals’ lives. (Denzin and Lincoln 2005 :2)

Flick claims that the label “qualitative research” is indeed used as an umbrella for a number of approaches ( 2007 :2–4; 2002 :6), and it is not difficult to identify research fitting this designation. Moreover, whatever it is, it has grown dramatically over the past five decades. In addition, courses have been developed, methods have flourished, arguments about its future have been advanced (for example, Denzin and Lincoln 1994) and criticized (for example, Snow and Morrill 1995 ), and dedicated journals and books have mushroomed. Most social scientists have a clear idea of research and how it differs from journalism, politics and other activities. But the question of what is qualitative in qualitative research is either eluded or eschewed.

We maintain that this lacuna hinders systematic knowledge production based on qualitative research. Paul Lazarsfeld noted the lack of “codification” as early as 1955 when he reviewed 100 qualitative studies in order to offer a codification of the practices (Lazarsfeld and Barton 1982 :239). Since then many texts on “qualitative research” and its methods have been published, including recent attempts (Goertz and Mahoney 2012 ) similar to Lazarsfeld’s. These studies have tried to extract what is qualitative by looking at the large number of empirical “qualitative” studies. Our novel strategy complements these endeavors by taking another approach and looking at the attempts to codify these practices in the form of a definition, as well as to a minor extent take Becker’s study as an exemplar of what qualitative researchers actually do, and what the characteristic of being ‘qualitative’ denotes and implies. We claim that qualitative researchers, if there is such a thing as “qualitative research,” should be able to codify their practices in a condensed, yet general way expressed in language.

Lingering problems of “generalizability” and “how many cases do I need” (Small 2009 ) are blocking advancement – in this line of work qualitative approaches are said to differ considerably from quantitative ones, while some of the former unsuccessfully mimic principles related to the latter (Small 2009 ). Additionally, quantitative researchers sometimes unfairly criticize the first based on their own quality criteria. Scholars like Goertz and Mahoney ( 2012 ) have successfully focused on the different norms and practices beyond what they argue are essentially two different cultures: those working with either qualitative or quantitative methods. Instead, similarly to Becker ( 2017 ) who has recently questioned the usefulness of the distinction between qualitative and quantitative research, we focus on similarities.

The current situation also impedes both students and researchers in focusing their studies and understanding each other’s work (Lazarsfeld and Barton 1982 :239). A third consequence is providing an opening for critiques by scholars operating within different traditions (Valsiner 2000 :101). A fourth issue is that the “implicit use of methods in qualitative research makes the field far less standardized than the quantitative paradigm” (Goertz and Mahoney 2012 :9). Relatedly, the National Science Foundation in the US organized two workshops in 2004 and 2005 to address the scientific foundations of qualitative research involving strategies to improve it and to develop standards of evaluation in qualitative research. However, a specific focus on its distinguishing feature of being “qualitative” while being implicitly acknowledged, was discussed only briefly (for example, Best 2004 ).

In 2014 a theme issue was published in this journal on “Methods, Materials, and Meanings: Designing Cultural Analysis,” discussing central issues in (cultural) qualitative research (Berezin 2014 ; Biernacki 2014 ; Glaeser 2014 ; Lamont and Swidler 2014 ; Spillman 2014). We agree with many of the arguments put forward, such as the risk of methodological tribalism, and that we should not waste energy on debating methods separated from research questions. Nonetheless, a clarification of the relation to what is called “quantitative research” is of outmost importance to avoid misunderstandings and misguided debates between “qualitative” and “quantitative” researchers. Our strategy means that researchers, “qualitative” or “quantitative” they may be, in their actual practice may combine qualitative work and quantitative work.

In this article we accomplish three tasks. First, we systematically survey the literature for meanings of qualitative research by looking at how researchers have defined it. Drawing upon existing knowledge we find that the different meanings and ideas of qualitative research are not yet coherently integrated into one satisfactory definition. Next, we advance our contribution by offering a definition of qualitative research and illustrate its meaning and use partially by expanding on the brief example introduced earlier related to Becker’s work ( 1963 ). We offer a systematic analysis of central themes of what researchers consider to be the core of “qualitative,” regardless of style of work. These themes – which we summarize in terms of four keywords: distinction, process, closeness, improved understanding – constitute part of our literature review, in which each one appears, sometimes with others, but never all in the same definition. They serve as the foundation of our contribution. Our categories are overlapping. Their use is primarily to organize the large amount of definitions we have identified and analyzed, and not necessarily to draw a clear distinction between them. Finally, we continue the elaboration discussed above on the advantages of a clear definition of qualitative research.

In a hermeneutic fashion we propose that there is something meaningful that deserves to be labelled “qualitative research” (Gadamer 1990 ). To approach the question “What is qualitative in qualitative research?” we have surveyed the literature. In conducting our survey we first traced the word’s etymology in dictionaries, encyclopedias, handbooks of the social sciences and of methods and textbooks, mainly in English, which is common to methodology courses. It should be noted that we have zoomed in on sociology and its literature. This discipline has been the site of the largest debate and development of methods that can be called “qualitative,” which suggests that this field should be examined in great detail.

In an ideal situation we should expect that one good definition, or at least some common ideas, would have emerged over the years. This common core of qualitative research should be so accepted that it would appear in at least some textbooks. Since this is not what we found, we decided to pursue an inductive approach to capture maximal variation in the field of qualitative research; we searched in a selection of handbooks, textbooks, book chapters, and books, to which we added the analysis of journal articles. Our sample comprises a total of 89 references.

In practice we focused on the discipline that has had a clear discussion of methods, namely sociology. We also conducted a broad search in the JSTOR database to identify scholarly sociology articles published between 1998 and 2017 in English with a focus on defining or explaining qualitative research. We specifically zoom in on this time frame because we would have expect that this more mature period would have produced clear discussions on the meaning of qualitative research. To find these articles we combined a number of keywords to search the content and/or the title: qualitative (which was always included), definition, empirical, research, methodology, studies, fieldwork, interview and observation .

As a second phase of our research we searched within nine major sociological journals ( American Journal of Sociology , Sociological Theory , American Sociological Review , Contemporary Sociology , Sociological Forum , Sociological Theory , Qualitative Research , Qualitative Sociology and Qualitative Sociology Review ) for articles also published during the past 19 years (1998–2017) that had the term “qualitative” in the title and attempted to define qualitative research.

Lastly we picked two additional journals, Qualitative Research and Qualitative Sociology , in which we could expect to find texts addressing the notion of “qualitative.” From Qualitative Research we chose Volume 14, Issue 6, December 2014, and from Qualitative Sociology we chose Volume 36, Issue 2, June 2017. Within each of these we selected the first article; then we picked the second article of three prior issues. Again we went back another three issues and investigated article number three. Finally we went back another three issues and perused article number four. This selection criteria was used to get a manageable sample for the analysis.

The coding process of the 89 references we gathered in our selected review began soon after the first round of material was gathered, and we reduced the complexity created by our maximum variation sampling (Snow and Anderson 1993 :22) to four different categories within which questions on the nature and properties of qualitative research were discussed. We call them: Qualitative and Quantitative Research, Qualitative Research, Fieldwork, and Grounded Theory. This – which may appear as an illogical grouping – merely reflects the “context” in which the matter of “qualitative” is discussed. If the selection process of the material – books and articles – was informed by pre-knowledge, we used an inductive strategy to code the material. When studying our material, we identified four central notions related to “qualitative” that appear in various combinations in the literature which indicate what is the core of qualitative research. We have labeled them: “distinctions”, “process,” “closeness,” and “improved understanding.” During the research process the categories and notions were improved, refined, changed, and reordered. The coding ended when a sense of saturation in the material arose. In the presentation below all quotations and references come from our empirical material of texts on qualitative research.

Analysis – What is Qualitative Research?

In this section we describe the four categories we identified in the coding, how they differently discuss qualitative research, as well as their overall content. Some salient quotations are selected to represent the type of text sorted under each of the four categories. What we present are examples from the literature.

Qualitative and Quantitative

This analytic category comprises quotations comparing qualitative and quantitative research, a distinction that is frequently used (Brown 2010 :231); in effect this is a conceptual pair that structures the discussion and that may be associated with opposing interests. While the general goal of quantitative and qualitative research is the same – to understand the world better – their methodologies and focus in certain respects differ substantially (Becker 1966 :55). Quantity refers to that property of something that can be determined by measurement. In a dictionary of Statistics and Methodology we find that “(a) When referring to *variables, ‘qualitative’ is another term for *categorical or *nominal. (b) When speaking of kinds of research, ‘qualitative’ refers to studies of subjects that are hard to quantify, such as art history. Qualitative research tends to be a residual category for almost any kind of non-quantitative research” (Stiles 1998:183). But it should be obvious that one could employ a quantitative approach when studying, for example, art history.

The same dictionary states that quantitative is “said of variables or research that can be handled numerically, usually (too sharply) contrasted with *qualitative variables and research” (Stiles 1998:184). From a qualitative perspective “quantitative research” is about numbers and counting, and from a quantitative perspective qualitative research is everything that is not about numbers. But this does not say much about what is “qualitative.” If we turn to encyclopedias we find that in the 1932 edition of the Encyclopedia of the Social Sciences there is no mention of “qualitative.” In the Encyclopedia from 1968 we can read:

Qualitative Analysis. For methods of obtaining, analyzing, and describing data, see [the various entries:] CONTENT ANALYSIS; COUNTED DATA; EVALUATION RESEARCH, FIELD WORK; GRAPHIC PRESENTATION; HISTORIOGRAPHY, especially the article on THE RHETORIC OF HISTORY; INTERVIEWING; OBSERVATION; PERSONALITY MEASUREMENT; PROJECTIVE METHODS; PSYCHOANALYSIS, article on EXPERIMENTAL METHODS; SURVEY ANALYSIS, TABULAR PRESENTATION; TYPOLOGIES. (Vol. 13:225)

Some, like Alford, divide researchers into methodologists or, in his words, “quantitative and qualitative specialists” (Alford 1998 :12). Qualitative research uses a variety of methods, such as intensive interviews or in-depth analysis of historical materials, and it is concerned with a comprehensive account of some event or unit (King et al. 1994 :4). Like quantitative research it can be utilized to study a variety of issues, but it tends to focus on meanings and motivations that underlie cultural symbols, personal experiences, phenomena and detailed understanding of processes in the social world. In short, qualitative research centers on understanding processes, experiences, and the meanings people assign to things (Kalof et al. 2008 :79).

Others simply say that qualitative methods are inherently unscientific (Jovanović 2011 :19). Hood, for instance, argues that words are intrinsically less precise than numbers, and that they are therefore more prone to subjective analysis, leading to biased results (Hood 2006 :219). Qualitative methodologies have raised concerns over the limitations of quantitative templates (Brady et al. 2004 :4). Scholars such as King et al. ( 1994 ), for instance, argue that non-statistical research can produce more reliable results if researchers pay attention to the rules of scientific inference commonly stated in quantitative research. Also, researchers such as Becker ( 1966 :59; 1970 :42–43) have asserted that, if conducted properly, qualitative research and in particular ethnographic field methods, can lead to more accurate results than quantitative studies, in particular, survey research and laboratory experiments.

Some researchers, such as Kalof, Dan, and Dietz ( 2008 :79) claim that the boundaries between the two approaches are becoming blurred, and Small ( 2009 ) argues that currently much qualitative research (especially in North America) tries unsuccessfully and unnecessarily to emulate quantitative standards. For others, qualitative research tends to be more humanistic and discursive (King et al. 1994 :4). Ragin ( 1994 ), and similarly also Becker, ( 1996 :53), Marchel and Owens ( 2007 :303) think that the main distinction between the two styles is overstated and does not rest on the simple dichotomy of “numbers versus words” (Ragin 1994 :xii). Some claim that quantitative data can be utilized to discover associations, but in order to unveil cause and effect a complex research design involving the use of qualitative approaches needs to be devised (Gilbert 2009 :35). Consequently, qualitative data are useful for understanding the nuances lying beyond those processes as they unfold (Gilbert 2009 :35). Others contend that qualitative research is particularly well suited both to identify causality and to uncover fine descriptive distinctions (Fine and Hallett 2014 ; Lichterman and Isaac Reed 2014 ; Katz 2015 ).

There are other ways to separate these two traditions, including normative statements about what qualitative research should be (that is, better or worse than quantitative approaches, concerned with scientific approaches to societal change or vice versa; Snow and Morrill 1995 ; Denzin and Lincoln 2005 ), or whether it should develop falsifiable statements; Best 2004 ).

We propose that quantitative research is largely concerned with pre-determined variables (Small 2008 ); the analysis concerns the relations between variables. These categories are primarily not questioned in the study, only their frequency or degree, or the correlations between them (cf. Franzosi 2016 ). If a researcher studies wage differences between women and men, he or she works with given categories: x number of men are compared with y number of women, with a certain wage attributed to each person. The idea is not to move beyond the given categories of wage, men and women; they are the starting point as well as the end point, and undergo no “qualitative change.” Qualitative research, in contrast, investigates relations between categories that are themselves subject to change in the research process. Returning to Becker’s study ( 1963 ), we see that he questioned pre-dispositional theories of deviant behavior working with pre-determined variables such as an individual’s combination of personal qualities or emotional problems. His take, in contrast, was to understand marijuana consumption by developing “variables” as part of the investigation. Thereby he presented new variables, or as we would say today, theoretical concepts, but which are grounded in the empirical material.

Qualitative Research

This category contains quotations that refer to descriptions of qualitative research without making comparisons with quantitative research. Researchers such as Denzin and Lincoln, who have written a series of influential handbooks on qualitative methods (1994; Denzin and Lincoln 2003 ; 2005 ), citing Nelson et al. (1992:4), argue that because qualitative research is “interdisciplinary, transdisciplinary, and sometimes counterdisciplinary” it is difficult to derive one single definition of it (Jovanović 2011 :3). According to them, in fact, “the field” is “many things at the same time,” involving contradictions, tensions over its focus, methods, and how to derive interpretations and findings ( 2003 : 11). Similarly, others, such as Flick ( 2007 :ix–x) contend that agreeing on an accepted definition has increasingly become problematic, and that qualitative research has possibly matured different identities. However, Best holds that “the proliferation of many sorts of activities under the label of qualitative sociology threatens to confuse our discussions” ( 2004 :54). Atkinson’s position is more definite: “the current state of qualitative research and research methods is confused” ( 2005 :3–4).

Qualitative research is about interpretation (Blumer 1969 ; Strauss and Corbin 1998 ; Denzin and Lincoln 2003 ), or Verstehen [understanding] (Frankfort-Nachmias and Nachmias 1996 ). It is “multi-method,” involving the collection and use of a variety of empirical materials (Denzin and Lincoln 1998; Silverman 2013 ) and approaches (Silverman 2005 ; Flick 2007 ). It focuses not only on the objective nature of behavior but also on its subjective meanings: individuals’ own accounts of their attitudes, motivations, behavior (McIntyre 2005 :127; Creswell 2009 ), events and situations (Bryman 1989) – what people say and do in specific places and institutions (Goodwin and Horowitz 2002 :35–36) in social and temporal contexts (Morrill and Fine 1997). For this reason, following Weber ([1921-22] 1978), it can be described as an interpretative science (McIntyre 2005 :127). But could quantitative research also be concerned with these questions? Also, as pointed out below, does all qualitative research focus on subjective meaning, as some scholars suggest?

Others also distinguish qualitative research by claiming that it collects data using a naturalistic approach (Denzin and Lincoln 2005 :2; Creswell 2009 ), focusing on the meaning actors ascribe to their actions. But again, does all qualitative research need to be collected in situ? And does qualitative research have to be inherently concerned with meaning? Flick ( 2007 ), referring to Denzin and Lincoln ( 2005 ), mentions conversation analysis as an example of qualitative research that is not concerned with the meanings people bring to a situation, but rather with the formal organization of talk. Still others, such as Ragin ( 1994 :85), note that qualitative research is often (especially early on in the project, we would add) less structured than other kinds of social research – a characteristic connected to its flexibility and that can lead both to potentially better, but also worse results. But is this not a feature of this type of research, rather than a defining description of its essence? Wouldn’t this comment also apply, albeit to varying degrees, to quantitative research?

In addition, Strauss ( 2003 ), along with others, such as Alvesson and Kärreman ( 2011 :10–76), argue that qualitative researchers struggle to capture and represent complex phenomena partially because they tend to collect a large amount of data. While his analysis is correct at some points – “It is necessary to do detailed, intensive, microscopic examination of the data in order to bring out the amazing complexity of what lies in, behind, and beyond those data” (Strauss 2003 :10) – much of his analysis concerns the supposed focus of qualitative research and its challenges, rather than exactly what it is about. But even in this instance we would make a weak case arguing that these are strictly the defining features of qualitative research. Some researchers seem to focus on the approach or the methods used, or even on the way material is analyzed. Several researchers stress the naturalistic assumption of investigating the world, suggesting that meaning and interpretation appear to be a core matter of qualitative research.

We can also see that in this category there is no consensus about specific qualitative methods nor about qualitative data. Many emphasize interpretation, but quantitative research, too, involves interpretation; the results of a regression analysis, for example, certainly have to be interpreted, and the form of meta-analysis that factor analysis provides indeed requires interpretation However, there is no interpretation of quantitative raw data, i.e., numbers in tables. One common thread is that qualitative researchers have to get to grips with their data in order to understand what is being studied in great detail, irrespective of the type of empirical material that is being analyzed. This observation is connected to the fact that qualitative researchers routinely make several adjustments of focus and research design as their studies progress, in many cases until the very end of the project (Kalof et al. 2008 ). If you, like Becker, do not start out with a detailed theory, adjustments such as the emergence and refinement of research questions will occur during the research process. We have thus found a number of useful reflections about qualitative research scattered across different sources, but none of them effectively describe the defining characteristics of this approach.

Although qualitative research does not appear to be defined in terms of a specific method, it is certainly common that fieldwork, i.e., research that entails that the researcher spends considerable time in the field that is studied and use the knowledge gained as data, is seen as emblematic of or even identical to qualitative research. But because we understand that fieldwork tends to focus primarily on the collection and analysis of qualitative data, we expected to find within it discussions on the meaning of “qualitative.” But, again, this was not the case.

Instead, we found material on the history of this approach (for example, Frankfort-Nachmias and Nachmias 1996 ; Atkinson et al. 2001), including how it has changed; for example, by adopting a more self-reflexive practice (Heyl 2001), as well as the different nomenclature that has been adopted, such as fieldwork, ethnography, qualitative research, naturalistic research, participant observation and so on (for example, Lofland et al. 2006 ; Gans 1999 ).

We retrieved definitions of ethnography, such as “the study of people acting in the natural courses of their daily lives,” involving a “resocialization of the researcher” (Emerson 1988 :1) through intense immersion in others’ social worlds (see also examples in Hammersley 2018 ). This may be accomplished by direct observation and also participation (Neuman 2007 :276), although others, such as Denzin ( 1970 :185), have long recognized other types of observation, including non-participant (“fly on the wall”). In this category we have also isolated claims and opposing views, arguing that this type of research is distinguished primarily by where it is conducted (natural settings) (Hughes 1971:496), and how it is carried out (a variety of methods are applied) or, for some most importantly, by involving an active, empathetic immersion in those being studied (Emerson 1988 :2). We also retrieved descriptions of the goals it attends in relation to how it is taught (understanding subjective meanings of the people studied, primarily develop theory, or contribute to social change) (see for example, Corte and Irwin 2017 ; Frankfort-Nachmias and Nachmias 1996 :281; Trier-Bieniek 2012 :639) by collecting the richest possible data (Lofland et al. 2006 ) to derive “thick descriptions” (Geertz 1973 ), and/or to aim at theoretical statements of general scope and applicability (for example, Emerson 1988 ; Fine 2003 ). We have identified guidelines on how to evaluate it (for example Becker 1996 ; Lamont 2004 ) and have retrieved instructions on how it should be conducted (for example, Lofland et al. 2006 ). For instance, analysis should take place while the data gathering unfolds (Emerson 1988 ; Hammersley and Atkinson 2007 ; Lofland et al. 2006 ), observations should be of long duration (Becker 1970 :54; Goffman 1989 ), and data should be of high quantity (Becker 1970 :52–53), as well as other questionable distinctions between fieldwork and other methods:

Field studies differ from other methods of research in that the researcher performs the task of selecting topics, decides what questions to ask, and forges interest in the course of the research itself . This is in sharp contrast to many ‘theory-driven’ and ‘hypothesis-testing’ methods. (Lofland and Lofland 1995 :5)

But could not, for example, a strictly interview-based study be carried out with the same amount of flexibility, such as sequential interviewing (for example, Small 2009 )? Once again, are quantitative approaches really as inflexible as some qualitative researchers think? Moreover, this category stresses the role of the actors’ meaning, which requires knowledge and close interaction with people, their practices and their lifeworld.

It is clear that field studies – which are seen by some as the “gold standard” of qualitative research – are nonetheless only one way of doing qualitative research. There are other methods, but it is not clear why some are more qualitative than others, or why they are better or worse. Fieldwork is characterized by interaction with the field (the material) and understanding of the phenomenon that is being studied. In Becker’s case, he had general experience from fields in which marihuana was used, based on which he did interviews with actual users in several fields.

Grounded Theory

Another major category we identified in our sample is Grounded Theory. We found descriptions of it most clearly in Glaser and Strauss’ ([1967] 2010 ) original articulation, Strauss and Corbin ( 1998 ) and Charmaz ( 2006 ), as well as many other accounts of what it is for: generating and testing theory (Strauss 2003 :xi). We identified explanations of how this task can be accomplished – such as through two main procedures: constant comparison and theoretical sampling (Emerson 1998:96), and how using it has helped researchers to “think differently” (for example, Strauss and Corbin 1998 :1). We also read descriptions of its main traits, what it entails and fosters – for instance, an exceptional flexibility, an inductive approach (Strauss and Corbin 1998 :31–33; 1990; Esterberg 2002 :7), an ability to step back and critically analyze situations, recognize tendencies towards bias, think abstractly and be open to criticism, enhance sensitivity towards the words and actions of respondents, and develop a sense of absorption and devotion to the research process (Strauss and Corbin 1998 :5–6). Accordingly, we identified discussions of the value of triangulating different methods (both using and not using grounded theory), including quantitative ones, and theories to achieve theoretical development (most comprehensively in Denzin 1970 ; Strauss and Corbin 1998 ; Timmermans and Tavory 2012 ). We have also located arguments about how its practice helps to systematize data collection, analysis and presentation of results (Glaser and Strauss [1967] 2010 :16).

Grounded theory offers a systematic approach which requires researchers to get close to the field; closeness is a requirement of identifying questions and developing new concepts or making further distinctions with regard to old concepts. In contrast to other qualitative approaches, grounded theory emphasizes the detailed coding process, and the numerous fine-tuned distinctions that the researcher makes during the process. Within this category, too, we could not find a satisfying discussion of the meaning of qualitative research.

Defining Qualitative Research

In sum, our analysis shows that some notions reappear in the discussion of qualitative research, such as understanding, interpretation, “getting close” and making distinctions. These notions capture aspects of what we think is “qualitative.” However, a comprehensive definition that is useful and that can further develop the field is lacking, and not even a clear picture of its essential elements appears. In other words no definition emerges from our data, and in our research process we have moved back and forth between our empirical data and the attempt to present a definition. Our concrete strategy, as stated above, is to relate qualitative and quantitative research, or more specifically, qualitative and quantitative work. We use an ideal-typical notion of quantitative research which relies on taken for granted and numbered variables. This means that the data consists of variables on different scales, such as ordinal, but frequently ratio and absolute scales, and the representation of the numbers to the variables, i.e. the justification of the assignment of numbers to object or phenomenon, are not questioned, though the validity may be questioned. In this section we return to the notion of quality and try to clarify it while presenting our contribution.

Broadly, research refers to the activity performed by people trained to obtain knowledge through systematic procedures. Notions such as “objectivity” and “reflexivity,” “systematic,” “theory,” “evidence” and “openness” are here taken for granted in any type of research. Next, building on our empirical analysis we explain the four notions that we have identified as central to qualitative work: distinctions, process, closeness, and improved understanding. In discussing them, ultimately in relation to one another, we make their meaning even more precise. Our idea, in short, is that only when these ideas that we present separately for analytic purposes are brought together can we speak of qualitative research.

Distinctions

We believe that the possibility of making new distinctions is one the defining characteristics of qualitative research. It clearly sets it apart from quantitative analysis which works with taken-for-granted variables, albeit as mentioned, meta-analyses, for example, factor analysis may result in new variables. “Quality” refers essentially to distinctions, as already pointed out by Aristotle. He discusses the term “qualitative” commenting: “By a quality I mean that in virtue of which things are said to be qualified somehow” (Aristotle 1984:14). Quality is about what something is or has, which means that the distinction from its environment is crucial. We see qualitative research as a process in which significant new distinctions are made to the scholarly community; to make distinctions is a key aspect of obtaining new knowledge; a point, as we will see, that also has implications for “quantitative research.” The notion of being “significant” is paramount. New distinctions by themselves are not enough; just adding concepts only increases complexity without furthering our knowledge. The significance of new distinctions is judged against the communal knowledge of the research community. To enable this discussion and judgements central elements of rational discussion are required (cf. Habermas [1981] 1987 ; Davidsson [ 1988 ] 2001) to identify what is new and relevant scientific knowledge. Relatedly, Ragin alludes to the idea of new and useful knowledge at a more concrete level: “Qualitative methods are appropriate for in-depth examination of cases because they aid the identification of key features of cases. Most qualitative methods enhance data” (1994:79). When Becker ( 1963 ) studied deviant behavior and investigated how people became marihuana smokers, he made distinctions between the ways in which people learned how to smoke. This is a classic example of how the strategy of “getting close” to the material, for example the text, people or pictures that are subject to analysis, may enable researchers to obtain deeper insight and new knowledge by making distinctions – in this instance on the initial notion of learning how to smoke. Others have stressed the making of distinctions in relation to coding or theorizing. Emerson et al. ( 1995 ), for example, hold that “qualitative coding is a way of opening up avenues of inquiry,” meaning that the researcher identifies and develops concepts and analytic insights through close examination of and reflection on data (Emerson et al. 1995 :151). Goodwin and Horowitz highlight making distinctions in relation to theory-building writing: “Close engagement with their cases typically requires qualitative researchers to adapt existing theories or to make new conceptual distinctions or theoretical arguments to accommodate new data” ( 2002 : 37). In the ideal-typical quantitative research only existing and so to speak, given, variables would be used. If this is the case no new distinction are made. But, would not also many “quantitative” researchers make new distinctions?

Process does not merely suggest that research takes time. It mainly implies that qualitative new knowledge results from a process that involves several phases, and above all iteration. Qualitative research is about oscillation between theory and evidence, analysis and generating material, between first- and second -order constructs (Schütz 1962 :59), between getting in contact with something, finding sources, becoming deeply familiar with a topic, and then distilling and communicating some of its essential features. The main point is that the categories that the researcher uses, and perhaps takes for granted at the beginning of the research process, usually undergo qualitative changes resulting from what is found. Becker describes how he tested hypotheses and let the jargon of the users develop into theoretical concepts. This happens over time while the study is being conducted, exemplifying what we mean by process.

In the research process, a pilot-study may be used to get a first glance of, for example, the field, how to approach it, and what methods can be used, after which the method and theory are chosen or refined before the main study begins. Thus, the empirical material is often central from the start of the project and frequently leads to adjustments by the researcher. Likewise, during the main study categories are not fixed; the empirical material is seen in light of the theory used, but it is also given the opportunity to kick back, thereby resisting attempts to apply theoretical straightjackets (Becker 1970 :43). In this process, coding and analysis are interwoven, and thus are often important steps for getting closer to the phenomenon and deciding what to focus on next. Becker began his research by interviewing musicians close to him, then asking them to refer him to other musicians, and later on doubling his original sample of about 25 to include individuals in other professions (Becker 1973:46). Additionally, he made use of some participant observation, documents, and interviews with opiate users made available to him by colleagues. As his inductive theory of deviance evolved, Becker expanded his sample in order to fine tune it, and test the accuracy and generality of his hypotheses. In addition, he introduced a negative case and discussed the null hypothesis ( 1963 :44). His phasic career model is thus based on a research design that embraces processual work. Typically, process means to move between “theory” and “material” but also to deal with negative cases, and Becker ( 1998 ) describes how discovering these negative cases impacted his research design and ultimately its findings.

Obviously, all research is process-oriented to some degree. The point is that the ideal-typical quantitative process does not imply change of the data, and iteration between data, evidence, hypotheses, empirical work, and theory. The data, quantified variables, are, in most cases fixed. Merging of data, which of course can be done in a quantitative research process, does not mean new data. New hypotheses are frequently tested, but the “raw data is often the “the same.” Obviously, over time new datasets are made available and put into use.

Another characteristic that is emphasized in our sample is that qualitative researchers – and in particular ethnographers – can, or as Goffman put it, ought to ( 1989 ), get closer to the phenomenon being studied and their data than quantitative researchers (for example, Silverman 2009 :85). Put differently, essentially because of their methods qualitative researchers get into direct close contact with those being investigated and/or the material, such as texts, being analyzed. Becker started out his interview study, as we noted, by talking to those he knew in the field of music to get closer to the phenomenon he was studying. By conducting interviews he got even closer. Had he done more observations, he would undoubtedly have got even closer to the field.

Additionally, ethnographers’ design enables researchers to follow the field over time, and the research they do is almost by definition longitudinal, though the time in the field is studied obviously differs between studies. The general characteristic of closeness over time maximizes the chances of unexpected events, new data (related, for example, to archival research as additional sources, and for ethnography for situations not necessarily previously thought of as instrumental – what Mannay and Morgan ( 2015 ) term the “waiting field”), serendipity (Merton and Barber 2004 ; Åkerström 2013 ), and possibly reactivity, as well as the opportunity to observe disrupted patterns that translate into exemplars of negative cases. Two classic examples of this are Becker’s finding of what medical students call “crocks” (Becker et al. 1961 :317), and Geertz’s ( 1973 ) study of “deep play” in Balinese society.

By getting and staying so close to their data – be it pictures, text or humans interacting (Becker was himself a musician) – for a long time, as the research progressively focuses, qualitative researchers are prompted to continually test their hunches, presuppositions and hypotheses. They test them against a reality that often (but certainly not always), and practically, as well as metaphorically, talks back, whether by validating them, or disqualifying their premises – correctly, as well as incorrectly (Fine 2003 ; Becker 1970 ). This testing nonetheless often leads to new directions for the research. Becker, for example, says that he was initially reading psychological theories, but when facing the data he develops a theory that looks at, you may say, everything but psychological dispositions to explain the use of marihuana. Especially researchers involved with ethnographic methods have a fairly unique opportunity to dig up and then test (in a circular, continuous and temporal way) new research questions and findings as the research progresses, and thereby to derive previously unimagined and uncharted distinctions by getting closer to the phenomenon under study.

Let us stress that getting close is by no means restricted to ethnography. The notion of hermeneutic circle and hermeneutics as a general way of understanding implies that we must get close to the details in order to get the big picture. This also means that qualitative researchers can literally also make use of details of pictures as evidence (cf. Harper 2002). Thus, researchers may get closer both when generating the material or when analyzing it.

Quantitative research, we maintain, in the ideal-typical representation cannot get closer to the data. The data is essentially numbers in tables making up the variables (Franzosi 2016 :138). The data may originally have been “qualitative,” but once reduced to numbers there can only be a type of “hermeneutics” about what the number may stand for. The numbers themselves, however, are non-ambiguous. Thus, in quantitative research, interpretation, if done, is not about the data itself—the numbers—but what the numbers stand for. It follows that the interpretation is essentially done in a more “speculative” mode without direct empirical evidence (cf. Becker 2017 ).

Improved Understanding

While distinction, process and getting closer refer to the qualitative work of the researcher, improved understanding refers to its conditions and outcome of this work. Understanding cuts deeper than explanation, which to some may mean a causally verified correlation between variables. The notion of explanation presupposes the notion of understanding since explanation does not include an idea of how knowledge is gained (Manicas 2006 : 15). Understanding, we argue, is the core concept of what we call the outcome of the process when research has made use of all the other elements that were integrated in the research. Understanding, then, has a special status in qualitative research since it refers both to the conditions of knowledge and the outcome of the process. Understanding can to some extent be seen as the condition of explanation and occurs in a process of interpretation, which naturally refers to meaning (Gadamer 1990 ). It is fundamentally connected to knowing, and to the knowing of how to do things (Heidegger [1927] 2001 ). Conceptually the term hermeneutics is used to account for this process. Heidegger ties hermeneutics to human being and not possible to separate from the understanding of being ( 1988 ). Here we use it in a broader sense, and more connected to method in general (cf. Seiffert 1992 ). The abovementioned aspects – for example, “objectivity” and “reflexivity” – of the approach are conditions of scientific understanding. Understanding is the result of a circular process and means that the parts are understood in light of the whole, and vice versa. Understanding presupposes pre-understanding, or in other words, some knowledge of the phenomenon studied. The pre-understanding, even in the form of prejudices, are in qualitative research process, which we see as iterative, questioned, which gradually or suddenly change due to the iteration of data, evidence and concepts. However, qualitative research generates understanding in the iterative process when the researcher gets closer to the data, e.g., by going back and forth between field and analysis in a process that generates new data that changes the evidence, and, ultimately, the findings. Questioning, to ask questions, and put what one assumes—prejudices and presumption—in question, is central to understand something (Heidegger [1927] 2001 ; Gadamer 1990 :368–384). We propose that this iterative process in which the process of understanding occurs is characteristic of qualitative research.

Improved understanding means that we obtain scientific knowledge of something that we as a scholarly community did not know before, or that we get to know something better. It means that we understand more about how parts are related to one another, and to other things we already understand (see also Fine and Hallett 2014 ). Understanding is an important condition for qualitative research. It is not enough to identify correlations, make distinctions, and work in a process in which one gets close to the field or phenomena. Understanding is accomplished when the elements are integrated in an iterative process.

It is, moreover, possible to understand many things, and researchers, just like children, may come to understand new things every day as they engage with the world. This subjective condition of understanding – namely, that a person gains a better understanding of something –is easily met. To be qualified as “scientific,” the understanding must be general and useful to many; it must be public. But even this generally accessible understanding is not enough in order to speak of “scientific understanding.” Though we as a collective can increase understanding of everything in virtually all potential directions as a result also of qualitative work, we refrain from this “objective” way of understanding, which has no means of discriminating between what we gain in understanding. Scientific understanding means that it is deemed relevant from the scientific horizon (compare Schütz 1962 : 35–38, 46, 63), and that it rests on the pre-understanding that the scientists have and must have in order to understand. In other words, the understanding gained must be deemed useful by other researchers, so that they can build on it. We thus see understanding from a pragmatic, rather than a subjective or objective perspective. Improved understanding is related to the question(s) at hand. Understanding, in order to represent an improvement, must be an improvement in relation to the existing body of knowledge of the scientific community (James [ 1907 ] 1955). Scientific understanding is, by definition, collective, as expressed in Weber’s famous note on objectivity, namely that scientific work aims at truths “which … can claim, even for a Chinese, the validity appropriate to an empirical analysis” ([1904] 1949 :59). By qualifying “improved understanding” we argue that it is a general defining characteristic of qualitative research. Becker‘s ( 1966 ) study and other research of deviant behavior increased our understanding of the social learning processes of how individuals start a behavior. And it also added new knowledge about the labeling of deviant behavior as a social process. Few studies, of course, make the same large contribution as Becker’s, but are nonetheless qualitative research.

Understanding in the phenomenological sense, which is a hallmark of qualitative research, we argue, requires meaning and this meaning is derived from the context, and above all the data being analyzed. The ideal-typical quantitative research operates with given variables with different numbers. This type of material is not enough to establish meaning at the level that truly justifies understanding. In other words, many social science explanations offer ideas about correlations or even causal relations, but this does not mean that the meaning at the level of the data analyzed, is understood. This leads us to say that there are indeed many explanations that meet the criteria of understanding, for example the explanation of how one becomes a marihuana smoker presented by Becker. However, we may also understand a phenomenon without explaining it, and we may have potential explanations, or better correlations, that are not really understood.

We may speak more generally of quantitative research and its data to clarify what we see as an important distinction. The “raw data” that quantitative research—as an idealtypical activity, refers to is not available for further analysis; the numbers, once created, are not to be questioned (Franzosi 2016 : 138). If the researcher is to do “more” or “change” something, this will be done by conjectures based on theoretical knowledge or based on the researcher’s lifeworld. Both qualitative and quantitative research is based on the lifeworld, and all researchers use prejudices and pre-understanding in the research process. This idea is present in the works of Heidegger ( 2001 ) and Heisenberg (cited in Franzosi 2010 :619). Qualitative research, as we argued, involves the interaction and questioning of concepts (theory), data, and evidence.

Ragin ( 2004 :22) points out that “a good definition of qualitative research should be inclusive and should emphasize its key strengths and features, not what it lacks (for example, the use of sophisticated quantitative techniques).” We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. Qualitative research, as defined here, is consequently a combination of two criteria: (i) how to do things –namely, generating and analyzing empirical material, in an iterative process in which one gets closer by making distinctions, and (ii) the outcome –improved understanding novel to the scholarly community. Is our definition applicable to our own study? In this study we have closely read the empirical material that we generated, and the novel distinction of the notion “qualitative research” is the outcome of an iterative process in which both deduction and induction were involved, in which we identified the categories that we analyzed. We thus claim to meet the first criteria, “how to do things.” The second criteria cannot be judged but in a partial way by us, namely that the “outcome” —in concrete form the definition-improves our understanding to others in the scientific community.

We have defined qualitative research, or qualitative scientific work, in relation to quantitative scientific work. Given this definition, qualitative research is about questioning the pre-given (taken for granted) variables, but it is thus also about making new distinctions of any type of phenomenon, for example, by coining new concepts, including the identification of new variables. This process, as we have discussed, is carried out in relation to empirical material, previous research, and thus in relation to theory. Theory and previous research cannot be escaped or bracketed. According to hermeneutic principles all scientific work is grounded in the lifeworld, and as social scientists we can thus never fully bracket our pre-understanding.

We have proposed that quantitative research, as an idealtype, is concerned with pre-determined variables (Small 2008 ). Variables are epistemically fixed, but can vary in terms of dimensions, such as frequency or number. Age is an example; as a variable it can take on different numbers. In relation to quantitative research, qualitative research does not reduce its material to number and variables. If this is done the process of comes to a halt, the researcher gets more distanced from her data, and it makes it no longer possible to make new distinctions that increase our understanding. We have above discussed the components of our definition in relation to quantitative research. Our conclusion is that in the research that is called quantitative there are frequent and necessary qualitative elements.

Further, comparative empirical research on researchers primarily working with ”quantitative” approaches and those working with ”qualitative” approaches, we propose, would perhaps show that there are many similarities in practices of these two approaches. This is not to deny dissimilarities, or the different epistemic and ontic presuppositions that may be more or less strongly associated with the two different strands (see Goertz and Mahoney 2012 ). Our point is nonetheless that prejudices and preconceptions about researchers are unproductive, and that as other researchers have argued, differences may be exaggerated (e.g., Becker 1996 : 53, 2017 ; Marchel and Owens 2007 :303; Ragin 1994 ), and that a qualitative dimension is present in both kinds of work.

Several things follow from our findings. The most important result is the relation to quantitative research. In our analysis we have separated qualitative research from quantitative research. The point is not to label individual researchers, methods, projects, or works as either “quantitative” or “qualitative.” By analyzing, i.e., taking apart, the notions of quantitative and qualitative, we hope to have shown the elements of qualitative research. Our definition captures the elements, and how they, when combined in practice, generate understanding. As many of the quotations we have used suggest, one conclusion of our study holds that qualitative approaches are not inherently connected with a specific method. Put differently, none of the methods that are frequently labelled “qualitative,” such as interviews or participant observation, are inherently “qualitative.” What matters, given our definition, is whether one works qualitatively or quantitatively in the research process, until the results are produced. Consequently, our analysis also suggests that those researchers working with what in the literature and in jargon is often called “quantitative research” are almost bound to make use of what we have identified as qualitative elements in any research project. Our findings also suggest that many” quantitative” researchers, at least to some extent, are engaged with qualitative work, such as when research questions are developed, variables are constructed and combined, and hypotheses are formulated. Furthermore, a research project may hover between “qualitative” and “quantitative” or start out as “qualitative” and later move into a “quantitative” (a distinct strategy that is not similar to “mixed methods” or just simply combining induction and deduction). More generally speaking, the categories of “qualitative” and “quantitative,” unfortunately, often cover up practices, and it may lead to “camps” of researchers opposing one another. For example, regardless of the researcher is primarily oriented to “quantitative” or “qualitative” research, the role of theory is neglected (cf. Swedberg 2017 ). Our results open up for an interaction not characterized by differences, but by different emphasis, and similarities.

Let us take two examples to briefly indicate how qualitative elements can fruitfully be combined with quantitative. Franzosi ( 2010 ) has discussed the relations between quantitative and qualitative approaches, and more specifically the relation between words and numbers. He analyzes texts and argues that scientific meaning cannot be reduced to numbers. Put differently, the meaning of the numbers is to be understood by what is taken for granted, and what is part of the lifeworld (Schütz 1962 ). Franzosi shows how one can go about using qualitative and quantitative methods and data to address scientific questions analyzing violence in Italy at the time when fascism was rising (1919–1922). Aspers ( 2006 ) studied the meaning of fashion photographers. He uses an empirical phenomenological approach, and establishes meaning at the level of actors. In a second step this meaning, and the different ideal-typical photographers constructed as a result of participant observation and interviews, are tested using quantitative data from a database; in the first phase to verify the different ideal-types, in the second phase to use these types to establish new knowledge about the types. In both of these cases—and more examples can be found—authors move from qualitative data and try to keep the meaning established when using the quantitative data.

A second main result of our study is that a definition, and we provided one, offers a way for research to clarify, and even evaluate, what is done. Hence, our definition can guide researchers and students, informing them on how to think about concrete research problems they face, and to show what it means to get closer in a process in which new distinctions are made. The definition can also be used to evaluate the results, given that it is a standard of evaluation (cf. Hammersley 2007 ), to see whether new distinctions are made and whether this improves our understanding of what is researched, in addition to the evaluation of how the research was conducted. By making what is qualitative research explicit it becomes easier to communicate findings, and it is thereby much harder to fly under the radar with substandard research since there are standards of evaluation which make it easier to separate “good” from “not so good” qualitative research.

To conclude, our analysis, which ends with a definition of qualitative research can thus both address the “internal” issues of what is qualitative research, and the “external” critiques that make it harder to do qualitative research, to which both pressure from quantitative methods and general changes in society contribute.

Åkerström, Malin. 2013. Curiosity and serendipity in qualitative research. Qualitative Sociology Review 9 (2): 10–18.

Google Scholar

Alford, Robert R. 1998. The craft of inquiry. Theories, methods, evidence . Oxford: Oxford University Press.

Alvesson, Mats, and Dan Kärreman. 2011. Qualitative research and theory development. Mystery as method . London: SAGE Publications.

Book Google Scholar

Aspers, Patrik. 2006. Markets in Fashion, A Phenomenological Approach. London Routledge.

Atkinson, Paul. 2005. Qualitative research. Unity and diversity. Forum: Qualitative Social Research 6 (3): 1–15.

Becker, Howard S. 1963. Outsiders. Studies in the sociology of deviance . New York: The Free Press.

Becker, Howard S. 1966. Whose side are we on? Social Problems 14 (3): 239–247.

Article Google Scholar

Becker, Howard S. 1970. Sociological work. Method and substance . New Brunswick: Transaction Books.

Becker, Howard S. 1996. The epistemology of qualitative research. In Ethnography and human development. Context and meaning in social inquiry , ed. Jessor Richard, Colby Anne, and Richard A. Shweder, 53–71. Chicago: University of Chicago Press.

Becker, Howard S. 1998. Tricks of the trade. How to think about your research while you're doing it . Chicago: University of Chicago Press.

Becker, Howard S. 2017. Evidence . Chigaco: University of Chicago Press.

Becker, Howard, Blanche Geer, Everett Hughes, and Anselm Strauss. 1961. Boys in White, student culture in medical school . New Brunswick: Transaction Publishers.

Berezin, Mabel. 2014. How do we know what we mean? Epistemological dilemmas in cultural sociology. Qualitative Sociology 37 (2): 141–151.

Best, Joel. 2004. Defining qualitative research. In Workshop on Scientific Foundations of Qualitative Research , eds . Charles, Ragin, Joanne, Nagel, and Patricia White, 53-54. http://www.nsf.gov/pubs/2004/nsf04219/nsf04219.pdf .

Biernacki, Richard. 2014. Humanist interpretation versus coding text samples. Qualitative Sociology 37 (2): 173–188.

Blumer, Herbert. 1969. Symbolic interactionism: Perspective and method . Berkeley: University of California Press.

Brady, Henry, David Collier, and Jason Seawright. 2004. Refocusing the discussion of methodology. In Rethinking social inquiry. Diverse tools, shared standards , ed. Brady Henry and Collier David, 3–22. Lanham: Rowman and Littlefield.

Brown, Allison P. 2010. Qualitative method and compromise in applied social research. Qualitative Research 10 (2): 229–248.

Charmaz, Kathy. 2006. Constructing grounded theory . London: Sage.

Corte, Ugo, and Katherine Irwin. 2017. “The Form and Flow of Teaching Ethnographic Knowledge: Hands-on Approaches for Learning Epistemology” Teaching Sociology 45(3): 209-219.

Creswell, John W. 2009. Research design. Qualitative, quantitative, and mixed method approaches . 3rd ed. Thousand Oaks: SAGE Publications.

Davidsson, David. 1988. 2001. The myth of the subjective. In Subjective, intersubjective, objective , ed. David Davidsson, 39–52. Oxford: Oxford University Press.

Denzin, Norman K. 1970. The research act: A theoretical introduction to Ssociological methods . Chicago: Aldine Publishing Company Publishers.

Denzin, Norman K., and Yvonna S. Lincoln. 2003. Introduction. The discipline and practice of qualitative research. In Collecting and interpreting qualitative materials , ed. Norman K. Denzin and Yvonna S. Lincoln, 1–45. Thousand Oaks: SAGE Publications.

Denzin, Norman K., and Yvonna S. Lincoln. 2005. Introduction. The discipline and practice of qualitative research. In The Sage handbook of qualitative research , ed. Norman K. Denzin and Yvonna S. Lincoln, 1–32. Thousand Oaks: SAGE Publications.

Emerson, Robert M., ed. 1988. Contemporary field research. A collection of readings . Prospect Heights: Waveland Press.

Emerson, Robert M., Rachel I. Fretz, and Linda L. Shaw. 1995. Writing ethnographic fieldnotes . Chicago: University of Chicago Press.

Esterberg, Kristin G. 2002. Qualitative methods in social research . Boston: McGraw-Hill.

Fine, Gary Alan. 1995. Review of “handbook of qualitative research.” Contemporary Sociology 24 (3): 416–418.

Fine, Gary Alan. 2003. “ Toward a Peopled Ethnography: Developing Theory from Group Life.” Ethnography . 4(1):41-60.

Fine, Gary Alan, and Black Hawk Hancock. 2017. The new ethnographer at work. Qualitative Research 17 (2): 260–268.

Fine, Gary Alan, and Timothy Hallett. 2014. Stranger and stranger: Creating theory through ethnographic distance and authority. Journal of Organizational Ethnography 3 (2): 188–203.

Flick, Uwe. 2002. Qualitative research. State of the art. Social Science Information 41 (1): 5–24.

Flick, Uwe. 2007. Designing qualitative research . London: SAGE Publications.

Frankfort-Nachmias, Chava, and David Nachmias. 1996. Research methods in the social sciences . 5th ed. London: Edward Arnold.

Franzosi, Roberto. 2010. Sociology, narrative, and the quality versus quantity debate (Goethe versus Newton): Can computer-assisted story grammars help us understand the rise of Italian fascism (1919- 1922)? Theory and Society 39 (6): 593–629.

Franzosi, Roberto. 2016. From method and measurement to narrative and number. International journal of social research methodology 19 (1): 137–141.

Gadamer, Hans-Georg. 1990. Wahrheit und Methode, Grundzüge einer philosophischen Hermeneutik . Band 1, Hermeneutik. Tübingen: J.C.B. Mohr.

Gans, Herbert. 1999. Participant Observation in an Age of “Ethnography”. Journal of Contemporary Ethnography 28 (5): 540–548.

Geertz, Clifford. 1973. The interpretation of cultures . New York: Basic Books.

Gilbert, Nigel. 2009. Researching social life . 3rd ed. London: SAGE Publications.

Glaeser, Andreas. 2014. Hermeneutic institutionalism: Towards a new synthesis. Qualitative Sociology 37: 207–241.

Glaser, Barney G., and Anselm L. Strauss. [1967] 2010. The discovery of grounded theory. Strategies for qualitative research. Hawthorne: Aldine.

Goertz, Gary, and James Mahoney. 2012. A tale of two cultures: Qualitative and quantitative research in the social sciences . Princeton: Princeton University Press.

Goffman, Erving. 1989. On fieldwork. Journal of Contemporary Ethnography 18 (2): 123–132.

Goodwin, Jeff, and Ruth Horowitz. 2002. Introduction. The methodological strengths and dilemmas of qualitative sociology. Qualitative Sociology 25 (1): 33–47.

Habermas, Jürgen. [1981] 1987. The theory of communicative action . Oxford: Polity Press.

Hammersley, Martyn. 2007. The issue of quality in qualitative research. International Journal of Research & Method in Education 30 (3): 287–305.

Hammersley, Martyn. 2013. What is qualitative research? Bloomsbury Publishing.

Hammersley, Martyn. 2018. What is ethnography? Can it survive should it? Ethnography and Education 13 (1): 1–17.

Hammersley, Martyn, and Paul Atkinson. 2007. Ethnography. Principles in practice . London: Tavistock Publications.

Heidegger, Martin. [1927] 2001. Sein und Zeit . Tübingen: Max Niemeyer Verlag.

Heidegger, Martin. 1988. 1923. Ontologie. Hermeneutik der Faktizität, Gesamtausgabe II. Abteilung: Vorlesungen 1919-1944, Band 63, Frankfurt am Main: Vittorio Klostermann.

Hempel, Carl G. 1966. Philosophy of the natural sciences . Upper Saddle River: Prentice Hall.

Hood, Jane C. 2006. Teaching against the text. The case of qualitative methods. Teaching Sociology 34 (3): 207–223.

James, William. 1907. 1955. Pragmatism . New York: Meredian Books.

Jovanović, Gordana. 2011. Toward a social history of qualitative research. History of the Human Sciences 24 (2): 1–27.

Kalof, Linda, Amy Dan, and Thomas Dietz. 2008. Essentials of social research . London: Open University Press.

Katz, Jack. 2015. Situational evidence: Strategies for causal reasoning from observational field notes. Sociological Methods & Research 44 (1): 108–144.

King, Gary, Robert O. Keohane, S. Sidney, and S. Verba. 1994. Designing social inquiry. In Scientific inference in qualitative research . Princeton: Princeton University Press.

Chapter Google Scholar

Lamont, Michelle. 2004. Evaluating qualitative research: Some empirical findings and an agenda. In Report from workshop on interdisciplinary standards for systematic qualitative research , ed. M. Lamont and P. White, 91–95. Washington, DC: National Science Foundation.

Lamont, Michèle, and Ann Swidler. 2014. Methodological pluralism and the possibilities and limits of interviewing. Qualitative Sociology 37 (2): 153–171.

Lazarsfeld, Paul, and Alan Barton. 1982. Some functions of qualitative analysis in social research. In The varied sociology of Paul Lazarsfeld , ed. Patricia Kendall, 239–285. New York: Columbia University Press.

Lichterman, Paul, and Isaac Reed I (2014), Theory and Contrastive Explanation in Ethnography. Sociological methods and research. Prepublished 27 October 2014; https://doi.org/10.1177/0049124114554458 .

Lofland, John, and Lyn Lofland. 1995. Analyzing social settings. A guide to qualitative observation and analysis . 3rd ed. Belmont: Wadsworth.

Lofland, John, David A. Snow, Leon Anderson, and Lyn H. Lofland. 2006. Analyzing social settings. A guide to qualitative observation and analysis . 4th ed. Belmont: Wadsworth/Thomson Learning.

Long, Adrew F., and Mary Godfrey. 2004. An evaluation tool to assess the quality of qualitative research studies. International Journal of Social Research Methodology 7 (2): 181–196.

Lundberg, George. 1951. Social research: A study in methods of gathering data . New York: Longmans, Green and Co..

Malinowski, Bronislaw. 1922. Argonauts of the Western Pacific: An account of native Enterprise and adventure in the archipelagoes of Melanesian New Guinea . London: Routledge.

Manicas, Peter. 2006. A realist philosophy of science: Explanation and understanding . Cambridge: Cambridge University Press.

Marchel, Carol, and Stephanie Owens. 2007. Qualitative research in psychology. Could William James get a job? History of Psychology 10 (4): 301–324.

McIntyre, Lisa J. 2005. Need to know. Social science research methods . Boston: McGraw-Hill.

Merton, Robert K., and Elinor Barber. 2004. The travels and adventures of serendipity. A Study in Sociological Semantics and the Sociology of Science . Princeton: Princeton University Press.

Mannay, Dawn, and Melanie Morgan. 2015. Doing ethnography or applying a qualitative technique? Reflections from the ‘waiting field‘. Qualitative Research 15 (2): 166–182.

Neuman, Lawrence W. 2007. Basics of social research. Qualitative and quantitative approaches . 2nd ed. Boston: Pearson Education.

Ragin, Charles C. 1994. Constructing social research. The unity and diversity of method . Thousand Oaks: Pine Forge Press.

Ragin, Charles C. 2004. Introduction to session 1: Defining qualitative research. In Workshop on Scientific Foundations of Qualitative Research , 22, ed. Charles C. Ragin, Joane Nagel, Patricia White. http://www.nsf.gov/pubs/2004/nsf04219/nsf04219.pdf

Rawls, Anne. 2018. The Wartime narrative in US sociology, 1940–7: Stigmatizing qualitative sociology in the name of ‘science,’ European Journal of Social Theory (Online first).

Schütz, Alfred. 1962. Collected papers I: The problem of social reality . The Hague: Nijhoff.

Seiffert, Helmut. 1992. Einführung in die Hermeneutik . Tübingen: Franke.

Silverman, David. 2005. Doing qualitative research. A practical handbook . 2nd ed. London: SAGE Publications.

Silverman, David. 2009. A very short, fairly interesting and reasonably cheap book about qualitative research . London: SAGE Publications.

Silverman, David. 2013. What counts as qualitative research? Some cautionary comments. Qualitative Sociology Review 9 (2): 48–55.

Small, Mario L. 2009. “How many cases do I need?” on science and the logic of case selection in field-based research. Ethnography 10 (1): 5–38.

Small, Mario L 2008. Lost in translation: How not to make qualitative research more scientific. In Workshop on interdisciplinary standards for systematic qualitative research, ed in Michelle Lamont, and Patricia White, 165–171. Washington, DC: National Science Foundation.

Snow, David A., and Leon Anderson. 1993. Down on their luck: A study of homeless street people . Berkeley: University of California Press.

Snow, David A., and Calvin Morrill. 1995. New ethnographies: Review symposium: A revolutionary handbook or a handbook for revolution? Journal of Contemporary Ethnography 24 (3): 341–349.

Strauss, Anselm L. 2003. Qualitative analysis for social scientists . 14th ed. Chicago: Cambridge University Press.

Strauss, Anselm L., and Juliette M. Corbin. 1998. Basics of qualitative research. Techniques and procedures for developing grounded theory . 2nd ed. Thousand Oaks: Sage Publications.

Swedberg, Richard. 2017. Theorizing in sociological research: A new perspective, a new departure? Annual Review of Sociology 43: 189–206.

Swedberg, Richard. 1990. The new 'Battle of Methods'. Challenge January–February 3 (1): 33–38.

Timmermans, Stefan, and Iddo Tavory. 2012. Theory construction in qualitative research: From grounded theory to abductive analysis. Sociological Theory 30 (3): 167–186.

Trier-Bieniek, Adrienne. 2012. Framing the telephone interview as a participant-centred tool for qualitative research. A methodological discussion. Qualitative Research 12 (6): 630–644.

Valsiner, Jaan. 2000. Data as representations. Contextualizing qualitative and quantitative research strategies. Social Science Information 39 (1): 99–113.

Weber, Max. 1904. 1949. Objectivity’ in social Science and social policy. Ed. Edward A. Shils and Henry A. Finch, 49–112. New York: The Free Press.

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Acknowledgements

Financial Support for this research is given by the European Research Council, CEV (263699). The authors are grateful to Susann Krieglsteiner for assistance in collecting the data. The paper has benefitted from the many useful comments by the three reviewers and the editor, comments by members of the Uppsala Laboratory of Economic Sociology, as well as Jukka Gronow, Sebastian Kohl, Marcin Serafin, Richard Swedberg, Anders Vassenden and Turid Rødne.

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Aspers, P., Corte, U. What is Qualitative in Qualitative Research. Qual Sociol 42 , 139–160 (2019). https://doi.org/10.1007/s11133-019-9413-7

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Quantitative research questions	Quantitative research hypotheses
Descriptive research questions	Simple hypothesis
Comparative research questions	Complex hypothesis
Relationship research questions	Directional hypothesis
	Non-directional hypothesis
	Associative hypothesis
	Causal hypothesis
	Null hypothesis
	Alternative hypothesis
	Working hypothesis
	Statistical hypothesis
	Logical hypothesis
	Hypothesis-testing
Qualitative research questions	Qualitative research hypotheses
Contextual research questions	Hypothesis-generating
Descriptive research questions
Evaluation research questions
Explanatory research questions
Exploratory research questions
Generative research questions
Ideological research questions
Ethnographic research questions
Phenomenological research questions
Grounded theory questions
Qualitative case study questions

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Quantitative research questions
Descriptive research question
	- Measures responses of subjects to variables
	- Presents variables to measure, analyze, or assess
	What is the proportion of resident doctors in the hospital who have mastered ultrasonography (response of subjects to a variable) as a diagnostic technique in their clinical training?
Comparative research question
	- Clarifies difference between one group with outcome variable and another group without outcome variable
	Is there a difference in the reduction of lung metastasis in osteosarcoma patients who received the vitamin D adjunctive therapy (group with outcome variable) compared with osteosarcoma patients who did not receive the vitamin D adjunctive therapy (group without outcome variable)?
	- Compares the effects of variables
	How does the vitamin D analogue 22-Oxacalcitriol (variable 1) mimic the antiproliferative activity of 1,25-Dihydroxyvitamin D (variable 2) in osteosarcoma cells?
Relationship research question
	- Defines trends, association, relationships, or interactions between dependent variable and independent variable
	Is there a relationship between the number of medical student suicide (dependent variable) and the level of medical student stress (independent variable) in Japan during the first wave of the COVID-19 pandemic?

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Quantitative research hypotheses
Simple hypothesis
	- Predicts relationship between single dependent variable and single independent variable
	If the dose of the new medication (single independent variable) is high, blood pressure (single dependent variable) is lowered.
Complex hypothesis
	- Foretells relationship between two or more independent and dependent variables
	The higher the use of anticancer drugs, radiation therapy, and adjunctive agents (3 independent variables), the higher would be the survival rate (1 dependent variable).
Directional hypothesis
	- Identifies study direction based on theory towards particular outcome to clarify relationship between variables
	Privately funded research projects will have a larger international scope (study direction) than publicly funded research projects.
Non-directional hypothesis
	- Nature of relationship between two variables or exact study direction is not identified
	- Does not involve a theory
	Women and men are different in terms of helpfulness. (Exact study direction is not identified)
Associative hypothesis
	- Describes variable interdependency
	- Change in one variable causes change in another variable
	A larger number of people vaccinated against COVID-19 in the region (change in independent variable) will reduce the region’s incidence of COVID-19 infection (change in dependent variable).
Causal hypothesis
	- An effect on dependent variable is predicted from manipulation of independent variable
	A change into a high-fiber diet (independent variable) will reduce the blood sugar level (dependent variable) of the patient.
Null hypothesis
	- A negative statement indicating no relationship or difference between 2 variables
	There is no significant difference in the severity of pulmonary metastases between the new drug (variable 1) and the current drug (variable 2).
Alternative hypothesis
	- Following a null hypothesis, an alternative hypothesis predicts a relationship between 2 study variables
	The new drug (variable 1) is better on average in reducing the level of pain from pulmonary metastasis than the current drug (variable 2).
Working hypothesis
	- A hypothesis that is initially accepted for further research to produce a feasible theory
	Dairy cows fed with concentrates of different formulations will produce different amounts of milk.
Statistical hypothesis
	- Assumption about the value of population parameter or relationship among several population characteristics
	- Validity tested by a statistical experiment or analysis
	The mean recovery rate from COVID-19 infection (value of population parameter) is not significantly different between population 1 and population 2.
	There is a positive correlation between the level of stress at the workplace and the number of suicides (population characteristics) among working people in Japan.
Logical hypothesis
	- Offers or proposes an explanation with limited or no extensive evidence
	If healthcare workers provide more educational programs about contraception methods, the number of adolescent pregnancies will be less.
Hypothesis-testing (Quantitative hypothesis-testing research)
	- Quantitative research uses deductive reasoning.
	- This involves the formation of a hypothesis, collection of data in the investigation of the problem, analysis and use of the data from the investigation, and drawing of conclusions to validate or nullify the hypotheses.

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative research questions
Contextual research question
	- Ask the nature of what already exists
	- Individuals or groups function to further clarify and understand the natural context of real-world problems
	What are the experiences of nurses working night shifts in healthcare during the COVID-19 pandemic? (natural context of real-world problems)
Descriptive research question
	- Aims to describe a phenomenon
	What are the different forms of disrespect and abuse (phenomenon) experienced by Tanzanian women when giving birth in healthcare facilities?
Evaluation research question
	- Examines the effectiveness of existing practice or accepted frameworks
	How effective are decision aids (effectiveness of existing practice) in helping decide whether to give birth at home or in a healthcare facility?
Explanatory research question
	- Clarifies a previously studied phenomenon and explains why it occurs
	Why is there an increase in teenage pregnancy (phenomenon) in Tanzania?
Exploratory research question
	- Explores areas that have not been fully investigated to have a deeper understanding of the research problem
	What factors affect the mental health of medical students (areas that have not yet been fully investigated) during the COVID-19 pandemic?
Generative research question
	- Develops an in-depth understanding of people’s behavior by asking ‘how would’ or ‘what if’ to identify problems and find solutions
	How would the extensive research experience of the behavior of new staff impact the success of the novel drug initiative?
Ideological research question
	- Aims to advance specific ideas or ideologies of a position
	Are Japanese nurses who volunteer in remote African hospitals able to promote humanized care of patients (specific ideas or ideologies) in the areas of safe patient environment, respect of patient privacy, and provision of accurate information related to health and care?
Ethnographic research question
	- Clarifies peoples’ nature, activities, their interactions, and the outcomes of their actions in specific settings
	What are the demographic characteristics, rehabilitative treatments, community interactions, and disease outcomes (nature, activities, their interactions, and the outcomes) of people in China who are suffering from pneumoconiosis?
Phenomenological research question
	- Knows more about the phenomena that have impacted an individual
	What are the lived experiences of parents who have been living with and caring for children with a diagnosis of autism? (phenomena that have impacted an individual)
Grounded theory question
	- Focuses on social processes asking about what happens and how people interact, or uncovering social relationships and behaviors of groups
	What are the problems that pregnant adolescents face in terms of social and cultural norms (social processes), and how can these be addressed?
Qualitative case study question
	- Assesses a phenomenon using different sources of data to answer “why” and “how” questions
	- Considers how the phenomenon is influenced by its contextual situation.
	How does quitting work and assuming the role of a full-time mother (phenomenon assessed) change the lives of women in Japan?

Qualitative research hypotheses
Hypothesis-generating (Qualitative hypothesis-generating research)
	- Qualitative research uses inductive reasoning.
	- This involves data collection from study participants or the literature regarding a phenomenon of interest, using the collected data to develop a formal hypothesis, and using the formal hypothesis as a framework for testing the hypothesis.
	- Qualitative exploratory studies explore areas deeper, clarifying subjective experience and allowing formulation of a formal hypothesis potentially testable in a future quantitative approach.

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

Variables	Unclear and weak statement (Statement 1)	Clear and good statement (Statement 2)	Points to avoid
Research question	Which is more effective between smoke moxibustion and smokeless moxibustion?	“Moreover, regarding smoke moxibustion versus smokeless moxibustion, it remains unclear which is more effective, safe, and acceptable to pregnant women, and whether there is any difference in the amount of heat generated.”	1) Vague and unfocused questions
			2) Closed questions simply answerable by yes or no
			3) Questions requiring a simple choice
Hypothesis	The smoke moxibustion group will have higher cephalic presentation.	“Hypothesis 1. The smoke moxibustion stick group (SM group) and smokeless moxibustion stick group (-SLM group) will have higher rates of cephalic presentation after treatment than the control group.	1) Unverifiable hypotheses
		Hypothesis 2. The SM group and SLM group will have higher rates of cephalic presentation at birth than the control group.	2) Incompletely stated groups of comparison
		Hypothesis 3. There will be no significant differences in the well-being of the mother and child among the three groups in terms of the following outcomes: premature birth, premature rupture of membranes (PROM) at < 37 weeks, Apgar score < 7 at 5 min, umbilical cord blood pH < 7.1, admission to neonatal intensive care unit (NICU), and intrauterine fetal death.”	3) Insufficiently described variables or outcomes
Research objective	To determine which is more effective between smoke moxibustion and smokeless moxibustion.	“The specific aims of this pilot study were (a) to compare the effects of smoke moxibustion and smokeless moxibustion treatments with the control group as a possible supplement to ECV for converting breech presentation to cephalic presentation and increasing adherence to the newly obtained cephalic position, and (b) to assess the effects of these treatments on the well-being of the mother and child.”	1) Poor understanding of the research question and hypotheses
Research objective			2) Insufficient description of population, variables, or study outcomes

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

Variables	Unclear and weak statement (Statement 1)	Clear and good statement (Statement 2)	Points to avoid
Research question	Does disrespect and abuse (D&A) occur in childbirth in Tanzania?	How does disrespect and abuse (D&A) occur and what are the types of physical and psychological abuses observed in midwives’ actual care during facility-based childbirth in urban Tanzania?	1) Ambiguous or oversimplistic questions
Research question			2) Questions unverifiable by data collection and analysis
Hypothesis	Disrespect and abuse (D&A) occur in childbirth in Tanzania.	Hypothesis 1: Several types of physical and psychological abuse by midwives in actual care occur during facility-based childbirth in urban Tanzania.	1) Statements simply expressing facts
Hypothesis	Disrespect and abuse (D&A) occur in childbirth in Tanzania.	Hypothesis 2: Weak nursing and midwifery management contribute to the D&A of women during facility-based childbirth in urban Tanzania.	2) Insufficiently described concepts or variables
Research objective	To describe disrespect and abuse (D&A) in childbirth in Tanzania.	“This study aimed to describe from actual observations the respectful and disrespectful care received by women from midwives during their labor period in two hospitals in urban Tanzania.”	1) Statements unrelated to the research question and hypotheses
Research objective			2) Unattainable or unexplorable objectives

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

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Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

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EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

EXAMPLE 1. Descriptive research question (quantitative research)
- Presents research variables to be assessed (distinct phenotypes and subphenotypes)
“BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
EXAMPLE 2. Relationship research question (quantitative research)
- Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
“Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
EXAMPLE 3. Comparative research question (quantitative research)
- Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
“BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
EXAMPLE 4. Exploratory research question (qualitative research)
- Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
“Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
EXAMPLE 5. Relationship research question (quantitative research)
- Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
“Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

EXAMPLE 1. Working hypothesis (quantitative research)
- A hypothesis that is initially accepted for further research to produce a feasible theory
“As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
“In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
EXAMPLE 2. Exploratory hypothesis (qualitative research)
- Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
“We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
“Conclusion
Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
“We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
EXAMPLE 4. Statistical hypothesis (quantitative research)
- An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
“Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
“Statistical Analysis
( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

EXAMPLE 1. Background, hypotheses, and aims are provided
“Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
“ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
“This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
EXAMPLE 2. Background, hypotheses, and aims are provided
“We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
“ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
EXAMPLE 3. Background, aim, and hypothesis are provided
“In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
“This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
“ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

Conceptualization: Barroga E, Matanguihan GJ.
Methodology: Barroga E, Matanguihan GJ.
Writing - original draft: Barroga E, Matanguihan GJ.
Writing - review & editing: Barroga E, Matanguihan GJ.

Open access
Published: 28 August 2024

Long-lasting insecticidal nets use and the prevalence of Plasmodium falciparum infection among pregnant women attending antenatal care at the Bonassama District Hospital, Littoral Region of Cameroon: a cross-sectional study

Marcelus U. Ajonina 1 , 2 , 3 , 8 ,
Irene U. Ajonina-Ekoti 4 ,
John Ngulefac 5 ,
Nicholas Ade 1 , 6 ,
Derick N. Awambeng 1 ,
Carine K. Nfor 7 ,
Martin Ayim 8 &
Tobias O. Apinjoh 9

BMC Pregnancy and Childbirth volume 24 , Article number: 560 ( 2024 ) Cite this article

Metrics details

Malaria during pregnancy continues to be a significant cause of morbidity and mortality for both infants and mothers, particularly in sub-Saharan African (SSA) countries, despite increased efforts to control it. The utilization of long-lasting insecticide-treated nets (LLINs) during pregnancy is a well-established strategy to reduce the prevalence of malaria. Nonetheless, inadequate adherence remains a persistent challenge in certain regions with high malaria endemicity. This research aimed to assess the effectiveness of long-lasting insecticidal nets in preventing asymptomatic malaria infections among pregnant women attending antenatal care at the Bonassama District Hospital in the Littoral Region of Cameroon.

A hospital-based cross-sectional study was conducted from March to June 2022. Data on sociodemographic characteristics and LLIN usage were collected through a structured questionnaire, while asymptomatic malaria infections were identified using a PfHRP2/pLDH malaria qualitative rapid diagnostic kit. The relationship between categorical variables was analyzed using the chi-square test and logistic regression at a significance level of 5%.

Out of the 411 pregnant women included in the study, 35.4% were diagnosed with malaria. The LLIN utilization rate was 65.1%. The risk of malaria infection was 2.7 times higher (AOR = 2.75, 95% CI = 1.83–4.14, p < 0.001) among women who did not consistently use LLINs compared to those who did. Pregnant women in their first trimester (AOR = 3.40, 95% CI = 1.24–4.64, p = 0.010) and second trimester (AOR = 1.90, 95%CI = 0.99–3.62, p = 0.055) were more likely to sleep under net when compared to those in the third trimester. Younger women 20–29 years (71.4%), those in the first trimester (69.6%) and those who had the nets before pregnancy (68.9%) were amongst those who frequently used use the nets. Among the reasons reported for not frequently using LLINs were heat (55.2%), suffocation (13.6%) and the smell of nets (8.4%).

The use of LLIN was moderately high among the participants in this study, though still below national target. Age group, religion and gestation period were the major factors determining the use of LLINs. Considering the proven effectiveness of LLINs in reducing malaria morbidity and mortality, it is imperative for the National Malaria Control Programme (NMCP) to remain focused in promoting both LLIN ownership and utilization to achieve the national target of 100% and 80%, respectively.

Peer Review reports

Malaria due to Plasmodium falciparum remains a significant public health challenge, particularly in endemic regions where vulnerable populations such as pregnant women are at increased risk of infection [ 1 ]. According to the World Health Organization (WHO), over 249 million cases and 608,000 deaths were recorded in 2022 across the world [ 2 ]. Malaria is the most widespread endemic disease in Cameroon. The country is among the 15 highest burden malaria countries, with 2.7% of all global malaria cases and deaths, and 2.3% of malaria deaths occurring in 2021 [ 3 ]. The disease burden is disproportionately higher in pregnant women and their newborns who are at increasing risk of severe illness and deaths, with 65% of confirmed cases in Cameroon in 2021 being children under five years of age [ 4 , 5 ]. According to the 2022 World Malaria Report, more than 13 million cases of malaria occur in pregnancy globally [ 2 ], with Cameroon recording a prevalence rate of 39.8% in 2019 [ 6 ]. This in part is due to changes in their immune system, making them more prone to severe complications, including maternal anemia, low birth weight, and maternal mortality [ 7 , 8 ]. A pregnant woman suffering from malaria is estimated to be three times more at risk of dying of the disease compared to a non-pregnant woman suffering from the disease [ 9 ]. To mitigate these risks, the use of long-lasting insecticidal nets (LLINs) among other preventive methods, is recommended as a cost-effective and proven intervention to prevent malaria transmission.

Efforts so far put in by the Cameroonian Ministry of health to minimize malaria transmission in pregnancy include the Health Sector Strategy 2016–2027. This has prioritized the fight against malaria with focus on reducing the high maternal and infant mortality through effective control of malaria in pregnancy [ 3 ]. The national policy to contain malaria transmission is aligned with the current WHO three-pronged strategic approach in areas of stable Plasmodium falciparum transmission which includes Intermittent Preventive Treatment in pregnancy (IPTp), use of Long-Lasting Insecticidal Net (LLIN) and prompt case management [ 10 ]. It is worth noting that preventing malaria in pregnancy is also a priority for the Roll Back Malaria (RBM) partnership program [ 11 ]. LLINs serve as a physical barrier preventing the mosquito from gaining contact with the body and also kills the mosquito, offering a definitive shield against malaria [ 12 ]. Studies carried out in various malaria endemic countries have shown that the effective use of LLINs by pregnant women can reduce the frequency of malaria by half [ 13 , 14 , 15 , 16 ]. While these endemic countries are benefiting from LLINs use, some do not adhere to this recommendation [ 17 ], yet others are still far behind with a low rate of LLIN utilization with consequently, a higher prevalence in pregnant women [ 18 , 19 ]. The probability of LLINs used to reduce the reproduction number R (mean population where all individuals are susceptible to infection) of malarial parasites implies that malaria could be eliminated from a community if three quarters of the population uses LLINs [ 20 ]. If therefore used properly in endemic areas, LLINs can reduce malaria vector transmission and burden of malaria in the community [ 12 , 21 ].

Despite the proven efficacy of LLINs in preventing malaria, there are persistent challenges related to their utilization among pregnant women. The effective use of LLINS faces several challenges in Cameroon and statistics indicate that they are used only by half of the pregnant women in the country [ 6 ]. Despite the mass distribution of LLINs to pregnant women in Cameroon, it is important to note that mere availability may not necessarily lead to their effective utilization as there exist some perceptions and misconceptions about the commodity within the population. Factors such as access to nets, knowledge about their importance, cultural beliefs, and socioeconomic factors can influence the uptake and consistent use of LLINs among this vulnerable population [ 22 , 23 ]. Evaluating the effective use of LLINs, and knowledge that addresses the constraints and promotes positive behaviour is key in preventing malaria in the community [ 13 , 24 ].

Considering the proven effectiveness of LLINs in reducing malaria morbidity and mortality, it is imperative for the National Malaria Control Programme (NMCP) to remain focused in promoting both LLIN ownership and utilization [ 3 , 19 ]. Therefore, understanding the prevalence of malaria among pregnant women and their utilization of LLINs is crucial for targeted interventions to improve maternal and child health outcomes in malaria endemic regions [ 25 , 26 ]. By elucidating the factors associated with both malaria prevalence and LLIN utilization, policymakers and healthcare providers can develop tailored strategies to enhance coverage, promote compliance, and ultimately reduce the burden of malaria in pregnant women [ 27 ]. This study aims to investigate the relationship between malaria prevalence and the utilization of LLINs among women attending antenatal care (ANC) at the Bonassama District Hospital. By examining the determinants of LLIN utilization and their impact on malaria infection rates, we seek to inform evidence-based strategies that can enhance the effectiveness of malaria prevention initiatives and ultimately reduce the burden of malaria among pregnant women in Cameroon.

Study setting and population

This was a hospital based cross-sectional study conducted at the Bonassama District Hospital (BDH) from March-June, 2022. The BDH is one of seven health district hospitals in the cosmopolitan city of Douala [ 28 ]. The hospital is located in Bonassama Health District which is one of the thirty health districts in the Littoral Region of Cameroon. The district has a surface area of about 55km 2 with a population of over 350,000 inhabitants and is situated just before the Bonaberi bridge. It attracts patients of diverse socio-economic status living in the city of Douala because of the high quality of services they offer. BDH offers antenatal care to pregnant women, with the hospital being managed by the Director and assisted by the General Supervisor, who coordinates the activities of the hospital.

The study population comprises of pregnant women who owned LLIN and attending ANC in the health facility during the study period. Any pregnant woman who resided for six months or more prior to data collection period and attending ANC at BDH were included in the study. Those who were sick or mentally ill were excluded from the study.

Sample size and sampling method

The minimum sample size was calculated using the Lorentz’s formula as follows:

Where z 2 = (1.96) 2 , p = previous malaria prevalence and q = 1-p, d 2 = (0.05) 2 . Rapport National de Lutte contre le Paludisme (PNLP) [ 16 ] reported a national malaria in pregnancy prevalence (p) of 39.8% in 2019. To compensate for the non-response rate, 10% of the determined sample size was added. The minimum sample size was therefore estimated at 406 women attending ANC at Bonassama District Hospital.

Data collection

Malaria diagnosis.

Asymptomatic malaria infection was determined using Bioline rapid diagnostic test (RDT). Capillary blood samples were collected from each participant following a finger prick under standard aseptic procedure. Plasmodium infection status was ascertained using PfHRP2/pLDH malaria rapid diagnostic kit (SD BiolineTM, Alere, South Korea) and results interpreted following manufacturer’s instructions. Briefly, about 5 µl of blood sample from each participant was placed in the sample window of the RDT cassette and three drops of diluent added. The results were then read after 15 min, with the presence of two (or three), one or no distinct line indicative of a positive, negative or invalid result, respectively.

Survey instrument

A pre-tested structured interviewer administered questionnaire was developed (supplementary file no. 1 ) and used to document information on sociodemographic characteristics of respondents, use of LLINs and source of LLINs. The questionnaire consisted of 14- items. Ten items queried demographic information that included age group, education level, marital status, religion, area of residence, number of children, and gestation period. Four items assessed ownership and utilization of mosquito nets including, source of LLINS, period when the LLINS was gotten, how often the net was used per week, and reasons for not sleeping under the net.

Dependent variables

The outcome variables for this study were the usage of LLIN and malaria status. The variable “usage of LLIN” was reduced to binary classes. Sleeping under the net everyday was coded as “Always use LLIN” while “once in a while” or “seldom use” were coded as “Did not always use LLIN”. Malaria status, defined as the result of the asymptomatic malaria qualitative rapid diagnostic test, which was a binary outcome variable was coded as “positive” or “negative”.

Explanatory variables

We included possible determinants of LLIN usage previously used in existing literature [ 17 , 24 , 29 , 30 ]. The following demographic variables: age group (less than 20, 20–29, 30–39 and above 39); level of education (primary, secondary or tertiary); marital status (single, married or divorced); Religion (Christianity or Islam); place of residence (Bojongo, Bonassama, Mabanda, Sodiko); gestation period (first trimester, second trimester, or third trimester) and gravida (primigravida or multigravida) were included. LLIN related variables such as source of LLIN (purchased or free distribution), period owned LLIN (before ANC or during ANC) were also included.

Data analysis

All data were entered into Excel and analyzed using SPSS Statistics 26 (SPSS Inc, Chicago, USA). Pearson’s χ 2 test was used to explore significant difference between malaria prevalence and the use of LLIN among pregnant women. Two sample proportion test was used to predict malaria prevalence and use of LLINS among pregnant women after controlling for demographic variables. To identify the predictors of use of LLIN, variables with p value of 0.1 or lower in bivariate analysis were included in the logistic regression model at 5% level of significance. Adjusted Odds Ratio (AOR) with 95% confidence interval (CI) was used as a measure of association.

A total of 441 pregnant women who owned LLIN were enrolled into this study. Most of the women were married (61.0%), within the 20–29 years age group (59.4%), had secondary level of education (51.5%), of Christianity religion (85.7%), and resident at Bojongo (44.0%) (Table 1 ). The mean age (± SD) of the participants was 27.28 ± 6.95 years. Majority of pregnant women were enrolled in their second trimester (46.5%) of pregnancy and multigravida (81.6%) (Table 1 ). Most of the pregnant women reportedly had nets before pregnancy (57.6%) and under free distribution (70.1%) either during ANC or by a community health worker (CHW).

Asymptomatic malaria infection

The prevalence of asymptomatic malaria infection was 35.4% (156/441), with a higher prevalence registered among women within the 30–39 years age group (38.0%, 41/108). Although there was no association between the prevalence of malaria infection and marital status, area of residence, gestation period and gravida, it was generally higher among pregnant women divorced (43.8%), those with Islam religion (42.9%), those residing at Bonassama neighborhood (40.5%) (Table 1 ). Higher rates of P. falciparum infections were also recorded among pregnant women in the first trimester (36.6%), primigravida (43.2%) and among those who received LLIN during ANC (39.4%) (Table 1 ). Malaria prevalence was significantly associated with use of mosquito nets ( p < 0.001). The infection was higher in pregnant women who rarely slept under the mosquito net (86.4%) compared with those that slept under the net daily (27.2%).

LLIN usage during pregnancy

Of the 441 LLIN owners, 65.1% of women reported always sleeping under the net, while 29.9% sleep under the net only once in the while. Another 5% seldomly sleep under mosquito nets (Table 1 ). The primary reason for not always sleeping under the net was due to heat (55.2%). Among other reasons indicated for not always sleeping under the net were, feeling of suffocation (13.6%), windows already have net (9.7%), chemical smell (8.4%), (Fig. 1 ).

Bed net usage information among women who did not use a LLINS ( N = 154). *Other Reasons: Allergic reaction ( n = 8); Torn net ( n = 4); Dirty ( n = 6); Irregular mosquitos ( n = 2)

To determine the association between sociodemographic factors and use of LLIN, the variable “usage of LLIN” was reduced to binary classes. Sleeping under the net everyday was considered as “Always use LLIN” while “once in a while” or “seldom use” were considered as “Did not always use LLIN”. The majority, 287 (65.1%) of pregnant women always use LLIN, while 154 (34.9%) respondents did not always use LLIN. LLIN usage was significantly associated with age group, religion, gestation period, source of LLIN and prevalence of malaria infection( p < 0.05) (Table 2 ). Pregnant women in the 20–29 years age category were 3.5 times more likely to use LLIN (adjusted OR = 3.53, 95%CI = 1.61–7.75, p = 0.002) compared to 30–39 and > 39 age groups (Table 3 ). Women of Christianity religion were 1.7 times (adjusted OR = 1.72, 95% CI = 1.01–2.96, p = 0.047) more likely to always use a net compared to Islam religion. It was observed that pregnant women in their first trimester (adjusted OR = 3.40, 95%CI = 1.24–4.64, p = 0.010) and second trimester (adjusted OR = 1.90, 95%CI = 0.99–3.62, p = 0.055) were more likely to sleep under net when compared to those in the third trimester. It was observed that women who did not sleep under LLIN were more susceptible to malaria parasite infection (adjusted OR = 2.75-, 95%CI = 1.83–4.14, p < 0.001).

LLIN usage and risk of malaria infection

Of the 441 pregnant women who owned LLIN, the rate of malaria infection was 27.7% (78/287) and 50.6% (78/154) for those who always use and do not always use LLIN, respectively. LLIN usage was significantly associated with malaria infection ( p < 0.001). However, the risk of malaria infection was 2.7 times (adjusted OR = 2.75, 95%CI = 1.83–4.14, p < 0.001) higher among those who did use LLIN compared to those who always used LLIN (Table 4 ).

Though LLINS have been shown to reduce maternal and child malaria related morbidity and mortality, their effective use remains a problem in malaria endemic regions. Measures to promote their effective utilization are crucial in improving maternal and child health outcomes. The current study was conducted to evaluate the prevalence of malaria infection and the use of mosquito bed net among pregnant women in Bonassama District Hospital in the Littoral Region of Cameroon. The prevalence of asymptomatic malaria infection among pregnant women in this study was 35.4% (156/441). The result corroborates other studies conducted in malaria endemic regions in Nigeria (41.6%) [ 9 ] and Ghana (42%) [ 31 ]. However, the observed prevalence was lower when compared to the 39.8% national prevalence obtained in Cameroon in 2019 [ 6 ], and other studies conducted in Cameroon [ 32 ] and Nigeria [ 33 ] reporting an asymptomatic malaria prevalence of 82.4% and Nigeria 79.5%, respectively. On the other hand, the finding of this study was much higher than primary studies in Bangladesh (2.3%) [ 34 ], Cameroon (10.1%) [ 16 ], a meta-analysis in Nigeria (23.4%) [ 33 ] and primary study in Burkina Faso (23.9%) [ 35 ]. The Littoral Region of Cameroon is characterized by poor drainage/sewage disposal systems and flooding which are suitable breeding grounds for malaria vectors which contribute to the high prevalence observed in this study. Moreover, the high prevalence reported in this study may also be due to multiple factors including seasonal changes intensity of the transmission, adherence to malaria preventive measures and the type of diagnostic test done [ 29 , 36 , 37 ]. Overall, this result emphasizes the need to include routine laboratory diagnosis of asymptomatic malaria infection as part of ANC follow-up for early detection and treatment to prevent negative effects due to malaria infection.

In this study, pregnant women who were in the first trimester of pregnancy were at risk of developing malaria infection compared to women in the second and third trimester. Moreover, women who were primigravida have increased risk of malaria infection compared to multigravida. Similar results were found from studies conducted in Gabon [ 38 ], Ghana [ 21 ], Ethiopia [ 39 ] and Cameroon [ 29 ]. Saito et al [ 40 ] suggested that the high prevalence of malaria observed during the first trimester is the lack of protection against malaria infection during the first few months of pregnancy due to systematic cytokine bias, which leads to weakened immunity. In addition, It is conceivable that women may acquire malaria prior to pregnancy, which could account for the higher prevalence observed during the first trimester [ 41 ]. The reason for primigravida having a higher risk and burden of asymptomatic infection than multigravida could be due to the lack of antiadhesion antibodies in primigravida women and the fact that multigravida women must have developed immunity to sequestered malaria parasites [ 42 , 43 ].

The result from this study indicates that majority of pregnant women (65.1%) used LLIN as a measure to prevent malaria in the current pregnancy. This result is consistent with research from Zambia (68%) [ 44 ], South Eastern Nigeria (70%) [ 45 ], Uganda (73%) [ 17 ] with some studies from Ghana (94.8%) [ 46 ] and Rwanda (87.6%) [ 30 ] having higher rates of utilization. The varied socioeconomic situations, geographic locations, and approaches to malaria control in the aforementioned nations may be the reason for these differences. These percentages are however higher than the 58.3% [ 24 ], 57.8% [ 16 ] and 42.7% [ 29 ] reported in the South West, North West and West regions of Cameroon, respectively. Though the utilization of LLIN by participants of this study was relatively high, it still falls below the national target of 80%, suggesting the need for continuous sensitization on effective utilization of LLINS.

Furthermore, this study identified factors associated with the use of LLINs among pregnant women. Age group was found to be significantly associated with the use of LLINs. The odds of using LLINs for pregnant women who were older (> 39 years) were 2 times higher than those who were younger (< 20 years). This is supported by research conducted in northern Ethiopia [ 47 ] and Rwanda [ 30 ] which to the fact that older women are more apt to have had prior pregnancies, accumulated life experiences related to pregnancy, may have encountered the negative impacts of malaria, possess improved communication skills, be financially independent, exhibit healthier behaviors within society, and have positive attitudes. These factors may make them more inclined to understand the importance of using mosquito bed nets.

Moreover, in our study, pregnant women who were Christians were 2 times more likely to sleep under LLIN than their Muslim counterpart. The findings of religion as a possible determinant of LLIN use is supported by studies conducted in Ghana [ 48 , 49 ]. Dun-Dery et al. [ 48 ] suggested that this could be due to the fact that Muslim men are less supportive to their spouses. The study also revealed that pregnant women who were in their first trimester were 3 times more likely to use their LLINs than those in the third trimester. This is likely because they are excited and aware of dangers that could occur during the first trimester and want to prevent them. This is however contrary to results obtained in Rwanda where women in the third trimester were positively associated with bed net use than those in the first semester [ 50 ]. In this study pregnant women who purchased LLINs were more likely to use LLIN than those who had received them freely. Free delivery of LLINs has been shown not to necessarily increase LLIN use [ 23 ]. Some studies have shown that personal decision to purchase a net may motivate one to use it rather than getting it for free [ 51 ]. This study found that the level of education, marital status, area of residence, gravida, and period in which the participants own the LLIN were not associated with use of LLINs.

In this study, not using LLIN increases the odds of developing malaria infection during pregnancy. In fact, the prevalence of asymptomatic malaria infection was 3 times higher in those that do not always used LLIN than those who always used LLIN. This study’s finding was in agreement with the study conducted in the South West Region of Cameroon [ 24 ], Ethiopia [ 19 , 39 ], Malawi and Nigeria [ 18 ] which showed that the use of bed nets has a significant impact on decreasing malaria infection.

Limitations

Our study was a cross-sectional study design, it does not show a direct temporal relationship. Moreover, though using PCR and microscopy may have higher sensitivity in the diagnosis of malaria infection, we could not do these tests therefore, the result of this study could be affected by the inherent performance of the RDT utilized. In addition, with all survey data, the findings are limited by recall and social desirability biases. Some answers to questions such as sleeping under LLINs, were reported by the participants not observed by the researcher. Likewise, it was not possible for the team to verify the status of nets during the survey. Finally, this study cannot be generalized to the whole population in Cameroon as the sample was selected in only one health facility.

In this study, the prevalence of asymptomatic malaria among pregnant women was found to be lower than the national average. Factors such as age group, religion, duration of ownership, and consistent use of LLINs showed significant associations with malaria infection. The utilization rate of LLINs was moderately high and was notably linked to age group, religion, gestational period, and the source of LLINs. These findings underscore the importance of conducting ongoing awareness campaigns to promote both ownership and proper usage of LLINs. Additionally, there is a clear need to incorporate routine laboratory screening for asymptomatic malaria into ANC protocols to enable early detection and treatment, thus minimizing the adverse impacts of malaria infection.

Data availability

The dataset used in the present study is available from the corresponding author upon reasonable request.

Abbreviations

Antenatal care

Bonassama District Hospital

Community health worker (CHW)

Intermittent Preventive Treatment in pregnancy

Infected red blood cells (IRBCs)

Long-lasting insecticide-treated nets

National Malaria Control Programme

P. falciparum erythrocyte membrane protein 1

Roll Back Malaria

Rapid diagnostic test

Sub-Saharan African

World Health Organization

Dellicour S, Tatem AJ, Guerra CA, Snow RW, ter Kuile FO. Quantifying the number of pregnancies at risk of malaria in 2007: a demographic study. PLoS Med. 2010;7:e1000221. https://doi.org/10.1371/journal.pmed.1000221 .

Article PubMed PubMed Central Google Scholar

World malaria report. 2023 [cited 17 May 2024]. Available: https://www.who.int/publications-detail-redirect/9789240086173

World malaria report. 2021 [cited 17 May 2024]. Available: https://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2021

Dombrowski JG, de Souza RM, Silva NRM, Barateiro A, Epiphanio S, Gonçalves LA, et al. Malaria during pregnancy and newborn outcome in an unstable transmission area in Brazil: a population-based record linkage study. PLoS ONE. 2018;13:e0199415. https://doi.org/10.1371/journal.pone.0199415 .

Article CAS PubMed PubMed Central Google Scholar

Severe Malaria Observatory. Cameroon malaria fact. In: Severe Malaria Observatory [Internet]. 2022 [cited 17 May 2024]. Available: https://www.severemalaria.org/countries/cameroon

Rapport National de Lutte contre le Paludisme (PNLP). Guide national du diagnostic biologique du paludisme. 2019. Available: http://onsp.minsante.cm/sites/default/files/publications/230/Rapport%20d%27activit_s%20PNLP%202019.pdf

Achidi EA, Apinjoh TO, Mbunwe E, Besingi R, Yafi C, Wenjighe Awah N, et al. Febrile status, malarial parasitaemia and gastro-intestinal helminthiases in schoolchildren resident at different altitudes, in south-western Cameroon. Ann Trop Med Parasitol. 2008;102:103–18. https://doi.org/10.1179/136485908X252287 .

Article CAS PubMed Google Scholar

Desai M, ter Kuile FO, Nosten F, McGready R, Asamoa K, Brabin B, et al. Epidemiology and burden of malaria in pregnancy. Lancet Infect Dis. 2007;7:93–104. https://doi.org/10.1016/S1473-3099(07)70021-X .

Article PubMed Google Scholar

Fana SA, Bunza MDA, Anka SA, Imam AU, Nataala SU. Prevalence and risk factors associated with malaria infection among pregnant women in a semi-urban community of north-western Nigeria. Infect Dis Poverty. 2015;4:24. https://doi.org/10.1186/s40249-015-0054-0 .

World Health Organization. WHO policy brief for the implementation of intermittent preventive treatment of malaria in pregnancy using sulfadoxine-pyrimethamine (IPTp-SP). Geneva; Switzerland. 2014. Available: https://www.who.int>atoz>i…

Roll Back Malaria. RBM Partnership to End Malaria Overview. 2022 [cited 18 May 2024]. Available: https://endmalaria.org/

Brake S, Gomez-Maldonado D, Hummel M, Zohdy S, Peresin MS. Understanding the current state-of-the-art of long-lasting insecticide nets and potential for sustainable alternatives. Curr Res Parasitol Vector-Borne Dis. 2022;2:100101. https://doi.org/10.1016/j.crpvbd.2022.100101 .

Gamble C, Ekwaru PJ, Garner P, ter Kuile FO. Insecticide-treated nets for the prevention of malaria in pregnancy: a systematic review of randomised controlled trials. PLoS Med. 2007;4:e107. https://doi.org/10.1371/journal.pmed.0040107 .

Hounkonnou C, Djènontin A, Egbinola S, Houngbegnon P, Bouraima A, Soares C, et al. Impact of the use and efficacy of long lasting insecticidal net on malaria infection during the first trimester of pregnancy - a pre-conceptional cohort study in southern Benin. BMC Public Health. 2018;18:683. https://doi.org/10.1186/s12889-018-5595-2 .

Nduka F, Wogu M. Effectiveness and compliance of long lasting insecticide – treated nets (LLINs) on malaria parasitemia in some pregnant women attending antenatal clinic in Rivers State Nigeria. Int J Infect Dis. 2012;16:e169. https://doi.org/10.1016/j.ijid.2012.05.710 .

Article Google Scholar

Nlinwe NO, Nchefor FG, Takwi NB. Impact of long lasting insecticidal nets on asymptomatic malaria during pregnancy, in a rural and urban setting in Cameroon. Parasite Epidemiol Control. 2022;18:e00265. https://doi.org/10.1016/j.parepi.2022.e00265 .

Sangaré LR, Weiss NS, Brentlinger PE, Richardson BA, Staedke SG, Kiwuwa MS et al. Determinants of Use of Insecticide Treated Nets for the Prevention of Malaria in Pregnancy: Jinja, Uganda. Kazembe L, editor. PLoS ONE. 2012;7: e39712. https://doi.org/10.1371/journal.pone.0039712

Adedeji OA. Intermittent preventive treatment and long-lasting insecticide nets use among pregnant women attending traditional Birth homes in Ibadan, Nigeria. J Interv Epidemiol Public Health. 2023;6. https://doi.org/10.37432/jieph.2023.6.3.84 .

Nadew J, Obsa MS, Alemayehu A, Haji Y. Utilization of insecticide treated nets among pregnant women in Sodo Zuria Woreda Southern Ethiopia. Front Trop Dis. 2022;3:926893. https://doi.org/10.3389/fitd.2022.926893 .

Agusto FB, Del Valle SY, Blayneh KW, Ngonghala CN, Goncalves MJ, Li N, et al. The impact of bed-net use on malaria prevalence. J Theor Biol. 2013;320:58–65. https://doi.org/10.1016/j.jtbi.2012.12.007 .

Dosoo DK, Chandramohan D, Atibilla D, Oppong FB, Ankrah L, Kayan K, et al. Epidemiology of malaria among pregnant women during their first antenatal clinic visit in the middle belt of Ghana: a cross sectional study. Malar J. 2020;19:381. https://doi.org/10.1186/s12936-020-03457-5 .

Kuetche MTC, Tabue RN, Fokoua-Maxime CD, Evouna AM, Billong S, Kakesa O. Prevalence and risk factors determinants of the non-use of insecticide-treated nets in an endemic area for malaria: analysis of data from Cameroon. Malar J. 2023;22:205. https://doi.org/10.1186/s12936-023-04510-9 .

Manu G, Boamah-Kaali EA, Febir LG, Ayipah E, Owusu-Agyei S, Asante KP. Low utilization of insecticide-treated Bed net among pregnant women in the Middle Belt of Ghana. Malar Res Treat. 2017;2017:1–7. https://doi.org/10.1155/2017/7481210 .

Apinjoh TO, Anchang-Kimbi JK, Mugri RN, Tangoh DA, Nyingchu RV, Chi HF et al. The Effect of Insecticide Treated Nets (ITNs) on Plasmodium falciparum Infection in Rural and Semi-Urban Communities in the South West Region of Cameroon. Culleton R, editor. PLOS ONE. 2015;10: e0116300. https://doi.org/10.1371/journal.pone.0116300

Hambisa MT, Debela T, Dessie Y, Gobena T. Long lasting insecticidal net use and its associated factors in Limmu Seka District, South West Ethiopia. BMC Public Health. 2018;18:124. https://doi.org/10.1186/s12889-018-5022-8 .

Kumar R, Farzeen M, Ahmed J, Lal M, Somrongthong R. Predictors of knowledge and use of long-lasting insecticidal nets for the prevention of malaria among the pregnant women in Pakistan. Malar J. 2021;20:347. https://doi.org/10.1186/s12936-021-03878-w .

Mayor A, Menéndez C, Walker PG. Targeting pregnant women for malaria surveillance. Trends Parasitol. 2019;35:677–86. https://doi.org/10.1016/j.pt.2019.07.005 .

Halle-Ekane GE, Emade FK, Bechem NN, Palle JN, Fongaing D, Essome H, et al. Prevalence and Risk Factors of Primary Postpartum Hemorrhage after Vaginal deliveries in the Bonassama District Hospital, Cameroon. Int J Trop Dis Health. 2016;1–12. https://doi.org/10.9734/IJTDH/2016/23078 .

Sidiki NNA, Payne VK, Cedric Y, Nadia NAC. Effect of impregnated Mosquito Bed nets on the prevalence of Malaria among pregnant women in Foumban Subdivision, West Region of Cameroon. J Parasitol Res. 2020;2020:1–10. https://doi.org/10.1155/2020/7438317 .

Habimana A, Gikunju J, Magu D, Tuyizere M. Assessing knowledge and Factors Associated to long lasting insecticide nets use among pregnant women in southern Rwanda. Rwanda J Med Health Sci. 2020;3:60–70. https://doi.org/10.4314/rjmhs.v3i1.8 .

Mockenhaupt FP, Rong B, Till H, Eggelte TA, Beck S, Gyasi-Sarpong C, et al. Submicroscopic Plasmodium falciparum infections in pregnancy in Ghana. Trop Med Int Health. 2000;5:167–73. https://doi.org/10.1046/j.1365-3156.2000.00532.x .

Walker-Abbey A, Djokam RRT, Eno A, Leke RFG, Titanji VPK, Fogako J, et al. Malaria in pregnant Cameroonian women: the effect of age and gravidity on submicroscopic and mixed-species infections and multiple parasite genotypes. Am J Trop Med Hyg. 2005;72:229–35.

Omang J, Antor O, Ndep D, Offiong F, Otu KO. Malaria in pregnancy in Nigeria: A literature review. Int Healthc Res J. 2020;3:346–8. https://doi.org/10.26440/IHRJ/0311.02315 .

Khan WA, Galagan SR, Prue CS, Khyang J, Ahmed S, Ram M, et al. Asymptomatic Plasmodium Falciparum Malaria in pregnant women in the Chittagong Hill districts of Bangladesh. PLoS ONE. 2014;9:e98442. https://doi.org/10.1371/journal.pone.0098442 .

Rouamba T, Samadoulougou S, Ouédraogo M, Hien H, Tinto H, Kirakoya-Samadoulougou F. Asymptomatic malaria and anaemia among pregnant women during high and low malaria transmission seasons in Burkina Faso: household-based cross-sectional surveys in Burkina Faso, 2013 and 2017. Malar J. 2021;20:211. https://doi.org/10.1186/s12936-021-03703-4 .

Antonio-Nkondjio C, Ndo C, Njiokou F, Bigoga JD, Awono-Ambene P, Etang J, et al. Review of malaria situation in Cameroon: technical viewpoint on challenges and prospects for disease elimination. Parasit Vectors. 2019;12:501. https://doi.org/10.1186/s13071-019-3753-8 .

Achidi EA, Apinjoh TO, Anchang-Kimbi JK, Mugri RN, Ngwai AN, Yafi CN. Severe and uncomplicated falciparum malaria in children from three regions and three ethnic groups in Cameroon: prospective study. Malar J. 2012;11:215. https://doi.org/10.1186/1475-2875-11-215 .

Jäckle MJ, Blumentrath CG, Zoleko RM, Akerey-Diop D, Mackanga J-R, Adegnika AA, et al. Malaria in pregnancy in rural Gabon: a cross-sectional survey on the impact of seasonality in high-risk groups. Malar J. 2013;12:412. https://doi.org/10.1186/1475-2875-12-412 .

Gontie GB, Wolde HF, Baraki AG. Prevalence and associated factors of malaria among pregnant women in Sherkole district, Benishangul Gumuz regional state, West Ethiopia. BMC Infect Dis. 2020;20:573. https://doi.org/10.1186/s12879-020-05289-9 .

Saito S, Nakashima A, Shima T, Ito M, REVIEW, ARTICLE. Th1/Th2/Th17 and Regulatory T-Cell paradigm in pregnancy. Am J Reprod Immunol. 2010;63:601–10. https://doi.org/10.1111/j.1600-0897.2010.00852.x .

Mangusho C, Mwebesa E, Izudi J, Aleni M, Dricile R, Ayiasi RM, et al. High prevalence of malaria in pregnancy among women attending antenatal care at a large referral hospital in northwestern Uganda: a cross-sectional study. PLoS ONE. 2023;18:e0283755. https://doi.org/10.1371/journal.pone.0283755 .

Aitken EH, Mbewe B, Luntamo M, Maleta K, Kulmala T, Friso M, et al. Antibodies to Chondroitin Sulfate A–Binding infected erythrocytes: Dynamics and Protection during pregnancy in women receiving intermittent preventive treatment. J Infect Dis. 2010;201:1316–25. https://doi.org/10.1086/651578 .

Kassie GA, Azeze GA, Gebrekidan AY, Lombebo AA, Adella GA, Haile KE, et al. Asymptomatic malaria infection and its associated factors among pregnant women in Ethiopia; a systematic review and meta-analysis. Parasite Epidemiol Control. 2024;24:e00339. https://doi.org/10.1016/j.parepi.2024.e00339 .

Mwangu LM, Mapuroma R, Ibisomi L. Factors associated with non-use of insecticide-treated bed nets among pregnant women in Zambia. Malar J. 2022;21:290. https://doi.org/10.1186/s12936-022-04313-4 .

Okafor CJ, Ogbonnaya NP. Knowledge, accessibility, and utilization of insecticide treated nets among pregnant women in a selected hospital in South-Eastern Nigeria. Eur J Midwifery. 2020;4:48. https://doi.org/10.18332/ejm/130591 .

Asumah M, Akugri F, Akanlu P, Taapena A, Boateng F. Utilization of insecticides treated mosquito bed nets among pregnant women in Kassena-Nankana East municipality in the upper east region of Ghana. Public Health Toxicol. 2021;1:1–11. https://doi.org/10.18332/pht/144533 .

Yitayew AE, Enyew HD, Goshu YA. Utilization and Associated factors of insecticide treated Bed net among pregnant women attending Antenatal Clinic of Addis Zemen Hospital, North-Western Ethiopia: an institutional based study. Malar Res Treat. 2018;2018:1–9. https://doi.org/10.1155/2018/3647184 .

Dun-Dery F, Kuunibe N, Meissner P, Winkler V, Jahn A, Müller O. Determinants of the use of insecticide-treated mosquito nets in pregnant women: a mixed-methods study in Ghana. Int Health. 2022;14:619–31. https://doi.org/10.1093/inthealth/ihab087 .

Kanmiki EW, Awoonor-Williams JK, Phillips JF, Kachur SP, Achana SF, Akazili J et al. Socio-economic and demographic disparities in ownership and use of insecticide-treated bed nets for preventing malaria among rural reproductive-aged women in northern Ghana. Arez AP, editor. PLOS ONE. 2019;14: e0211365. https://doi.org/10.1371/journal.pone.0211365

Kawuki J, Donkor E, Gatasi G, Nuwabaine L. Mosquito bed net use and associated factors among pregnant women in Rwanda: a nationwide survey. BMC Pregnancy Childbirth. 2023;23:419. https://doi.org/10.1186/s12884-023-05583-9 .

Baume CA, Franca-Koh AC. Predictors of mosquito net use in Ghana. Malar J. 2011;10:265. https://doi.org/10.1186/1475-2875-10-265 .

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We would like to thank the study participants who made this study realistic, and the Director of the Bonassama District Hospital for the permission granted to conduct the study in the health facility.

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MUA and TOA conceived and designed the experiments. CKN and DNA conducted the study. MUA, TOA and IUA performed the analysis. MUA, NA, JN and MA drafted the manuscript. All authors contributed to revision of the manuscript prior to submission.

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Ajonina, M.U., Ajonina-Ekoti, I.U., Ngulefac, J. et al. Long-lasting insecticidal nets use and the prevalence of Plasmodium falciparum infection among pregnant women attending antenatal care at the Bonassama District Hospital, Littoral Region of Cameroon: a cross-sectional study. BMC Pregnancy Childbirth 24 , 560 (2024). https://doi.org/10.1186/s12884-024-06769-5

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IMAGES

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Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research. Qualitative research is the opposite of quantitative research, which involves collecting and ...
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1. Quantitative Variables: Sometimes referred to as "numeric" variables, these are variables that represent a measurable quantity. Examples include: 2. Qualitative Variables: Sometimes referred to as "categorical" variables, these are variables that take on names or labels and can fit into categories. Examples include: Every single ...
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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 ...
Qualitative Variable (Categorical Variable ...
A qualitative variable, also called a categorical variable, is a variable that isn't numerical. It describes data that fits into categories. For example: Breeds of dog is a qualitative variable. Eye colors (variables include: blue, green, brown, hazel). States (variables include: Florida, New Jersey, Washington).
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What is qualitative research? If we look for a precise definition of qualitative research, and specifically for one that addresses its distinctive feature of being "qualitative," the literature is meager. ... contrasted with *qualitative variables and research" (Stiles 1998:184). From a qualitative perspective "quantitative research ...
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Abstract. This paper aims to provide an overview of the use and assessment of qualitative research methods in the health sciences. Qualitative research can be defined as the study of the nature of phenomena and is especially appropriate for answering questions of why something is (not) observed, assessing complex multi-component interventions ...
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Qualitative research is the naturalistic study of social meanings and processes, using interviews, observations, and the analysis of texts and images. In contrast to quantitative researchers, whose statistical methods enable broad generalizations about populations (for example, comparisons of the percentages of U.S. demographic groups who vote in particular ways), qualitative researchers use ...
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Qualitative research does not look into causal relationships between variables, but rather into themes, values, interpretations, and meanings. As a rule, then, qualitative research is not generalizable (cannot be applied to people outside the research participants).
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Limitations. Qualitative research is a type of research methodology that focuses on gathering and analyzing non-numerical data to gain a deeper understanding of human behavior, experiences, and perspectives. It aims to explore the "why" and "how" of a phenomenon rather than the "what," "where," and "when" typically addressed ...
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Quantitative variables are measured differently than qualitative variables and knowing which type of variable(s) you are working with is a crucial first step in statistical analysis. Quantitative ...
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Categorical variables are groups…such as gender or type of degree sought. Quantitative variables are numbers that have a range…like weight in pounds or baskets made during a ball game. When we analyze data we do turn the categorical variables into numbers but only for identification purposes…e.g. 1 = male and 2 = female.
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Qualitative/nominal variables name or label different categories of objects. Something is either an apple or an orange, halfway between an apple and an orange doesn't mean anything. Qualitative variables are counted, and the counts are used in statistical analyses.The name or label of a qualitative variable can be a number, but the number ...
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A variable can collect either qualitative or quantitative data. A variable differing in quantity is called a quantitative variable (e.g., weight of a group of patients), whereas a variable differing in quality is called a qualitative variable (e.g., the Fitzpatrick skin type) A simple test which can be used to differentiate between qualitative ...
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Qualitative variables are sometimes referred to as categorical variables. Quantitative variables are those variables that are measured in terms of numbers. Some examples of quantitative variables are height, weight, and shoe size. In the study on the effect of diet discussed above, the independent variable was type of supplement: none ...
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Research Variables: Types, Uses and Definition of Terms
The purpose of research is to describe and explain variance in the world, that is, variance that. occurs naturally in the world or chang e that we create due to manipulation. Variables are ...
What is Qualitative in Qualitative Research
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Long-lasting insecticidal nets use and the prevalence of Plasmodium
Malaria status, defined as the result of the asymptomatic malaria qualitative rapid diagnostic test, which was a binary outcome variable was coded as "positive" or "negative". Explanatory variables. We included possible determinants of LLIN usage previously used in existing literature [17, 24, 29, 30]. The following demographic ...

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