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Research Variables 101

By: Derek Jansen (MBA) | Expert Reviewed By: Kerryn Warren (PhD) | January 2023

Overview: Variables In Research

What (exactly) is a variable.

The simplest way to understand a variable is as any characteristic or attribute that can experience change or vary over time or context – hence the name “variable”. For example, the dosage of a particular medicine could be classified as a variable, as the amount can vary (i.e., a higher dose or a lower dose). Similarly, gender, age or ethnicity could be considered demographic variables, because each person varies in these respects.

Within research, especially scientific research, variables form the foundation of studies, as researchers are often interested in how one variable impacts another, and the relationships between different variables. For example:

• How someone’s age impacts their sleep quality
• How different teaching methods impact learning outcomes
• How diet impacts weight (gain or loss)

As you can see, variables are often used to explain relationships between different elements and phenomena. In scientific studies, especially experimental studies, the objective is often to understand the causal relationships between variables. In other words, the role of cause and effect between variables. This is achieved by manipulating certain variables while controlling others – and then observing the outcome. But, we’ll get into that a little later…

The “Big 3” Variables

Variables can be a little intimidating for new researchers because there are a wide variety of variables, and oftentimes, there are multiple labels for the same thing. To lay a firm foundation, we’ll first look at the three main types of variables, namely:

• Independent variables (IV)
• Dependant variables (DV)
• Control variables

What is an independent variable?

Simply put, the independent variable is the “ cause ” in the relationship between two (or more) variables. In other words, when the independent variable changes, it has an impact on another variable.

For example:

• Increasing the dosage of a medication (Variable A) could result in better (or worse) health outcomes for a patient (Variable B)
• Changing a teaching method (Variable A) could impact the test scores that students earn in a standardised test (Variable B)
• Varying one’s diet (Variable A) could result in weight loss or gain (Variable B).

It’s useful to know that independent variables can go by a few different names, including, explanatory variables (because they explain an event or outcome) and predictor variables (because they predict the value of another variable). Terminology aside though, the most important takeaway is that independent variables are assumed to be the “cause” in any cause-effect relationship. As you can imagine, these types of variables are of major interest to researchers, as many studies seek to understand the causal factors behind a phenomenon.

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What is a dependent variable?

While the independent variable is the “ cause ”, the dependent variable is the “ effect ” – or rather, the affected variable . In other words, the dependent variable is the variable that is assumed to change as a result of a change in the independent variable.

Keeping with the previous example, let’s look at some dependent variables in action:

• Health outcomes (DV) could be impacted by dosage changes of a medication (IV)
• Students’ scores (DV) could be impacted by teaching methods (IV)
• Weight gain or loss (DV) could be impacted by diet (IV)

In scientific studies, researchers will typically pay very close attention to the dependent variable (or variables), carefully measuring any changes in response to hypothesised independent variables. This can be tricky in practice, as it’s not always easy to reliably measure specific phenomena or outcomes – or to be certain that the actual cause of the change is in fact the independent variable.

As the adage goes, correlation is not causation . In other words, just because two variables have a relationship doesn’t mean that it’s a causal relationship – they may just happen to vary together. For example, you could find a correlation between the number of people who own a certain brand of car and the number of people who have a certain type of job. Just because the number of people who own that brand of car and the number of people who have that type of job is correlated, it doesn’t mean that owning that brand of car causes someone to have that type of job or vice versa. The correlation could, for example, be caused by another factor such as income level or age group, which would affect both car ownership and job type.

To confidently establish a causal relationship between an independent variable and a dependent variable (i.e., X causes Y), you’ll typically need an experimental design , where you have complete control over the environmen t and the variables of interest. But even so, this doesn’t always translate into the “real world”. Simply put, what happens in the lab sometimes stays in the lab!

As an alternative to pure experimental research, correlational or “ quasi-experimental ” research (where the researcher cannot manipulate or change variables) can be done on a much larger scale more easily, allowing one to understand specific relationships in the real world. These types of studies also assume some causality between independent and dependent variables, but it’s not always clear. So, if you go this route, you need to be cautious in terms of how you describe the impact and causality between variables and be sure to acknowledge any limitations in your own research.

What is a control variable?

In an experimental design, a control variable (or controlled variable) is a variable that is intentionally held constant to ensure it doesn’t have an influence on any other variables. As a result, this variable remains unchanged throughout the course of the study. In other words, it’s a variable that’s not allowed to vary – tough life 🙂

As we mentioned earlier, one of the major challenges in identifying and measuring causal relationships is that it’s difficult to isolate the impact of variables other than the independent variable. Simply put, there’s always a risk that there are factors beyond the ones you’re specifically looking at that might be impacting the results of your study. So, to minimise the risk of this, researchers will attempt (as best possible) to hold other variables constant . These factors are then considered control variables.

Some examples of variables that you may need to control include:

• Temperature
• Time of day
• Noise or distractions

Which specific variables need to be controlled for will vary tremendously depending on the research project at hand, so there’s no generic list of control variables to consult. As a researcher, you’ll need to think carefully about all the factors that could vary within your research context and then consider how you’ll go about controlling them. A good starting point is to look at previous studies similar to yours and pay close attention to which variables they controlled for.

Of course, you won’t always be able to control every possible variable, and so, in many cases, you’ll just have to acknowledge their potential impact and account for them in the conclusions you draw. Every study has its limitations , so don’t get fixated or discouraged by troublesome variables. Nevertheless, always think carefully about the factors beyond what you’re focusing on – don’t make assumptions!

Other types of variables

As we mentioned, independent, dependent and control variables are the most common variables you’ll come across in your research, but they’re certainly not the only ones you need to be aware of. Next, we’ll look at a few “secondary” variables that you need to keep in mind as you design your research.

• Moderating variables
• Mediating variables
• Confounding variables
• Latent variables

Let’s jump into it…

What is a moderating variable?

A moderating variable is a variable that influences the strength or direction of the relationship between an independent variable and a dependent variable. In other words, moderating variables affect how much (or how little) the IV affects the DV, or whether the IV has a positive or negative relationship with the DV (i.e., moves in the same or opposite direction).

For example, in a study about the effects of sleep deprivation on academic performance, gender could be used as a moderating variable to see if there are any differences in how men and women respond to a lack of sleep. In such a case, one may find that gender has an influence on how much students’ scores suffer when they’re deprived of sleep.

It’s important to note that while moderators can have an influence on outcomes , they don’t necessarily cause them ; rather they modify or “moderate” existing relationships between other variables. This means that it’s possible for two different groups with similar characteristics, but different levels of moderation, to experience very different results from the same experiment or study design.

What is a mediating variable?

Mediating variables are often used to explain the relationship between the independent and dependent variable (s). For example, if you were researching the effects of age on job satisfaction, then education level could be considered a mediating variable, as it may explain why older people have higher job satisfaction than younger people – they may have more experience or better qualifications, which lead to greater job satisfaction.

Mediating variables also help researchers understand how different factors interact with each other to influence outcomes. For instance, if you wanted to study the effect of stress on academic performance, then coping strategies might act as a mediating factor by influencing both stress levels and academic performance simultaneously. For example, students who use effective coping strategies might be less stressed but also perform better academically due to their improved mental state.

In addition, mediating variables can provide insight into causal relationships between two variables by helping researchers determine whether changes in one factor directly cause changes in another – or whether there is an indirect relationship between them mediated by some third factor(s). For instance, if you wanted to investigate the impact of parental involvement on student achievement, you would need to consider family dynamics as a potential mediator, since it could influence both parental involvement and student achievement simultaneously.

What is a confounding variable?

A confounding variable (also known as a third variable or lurking variable ) is an extraneous factor that can influence the relationship between two variables being studied. Specifically, for a variable to be considered a confounding variable, it needs to meet two criteria:

• It must be correlated with the independent variable (this can be causal or not)
• It must have a causal impact on the dependent variable (i.e., influence the DV)

Some common examples of confounding variables include demographic factors such as gender, ethnicity, socioeconomic status, age, education level, and health status. In addition to these, there are also environmental factors to consider. For example, air pollution could confound the impact of the variables of interest in a study investigating health outcomes.

Naturally, it’s important to identify as many confounding variables as possible when conducting your research, as they can heavily distort the results and lead you to draw incorrect conclusions . So, always think carefully about what factors may have a confounding effect on your variables of interest and try to manage these as best you can.

What is a latent variable?

Latent variables are unobservable factors that can influence the behaviour of individuals and explain certain outcomes within a study. They’re also known as hidden or underlying variables , and what makes them rather tricky is that they can’t be directly observed or measured . Instead, latent variables must be inferred from other observable data points such as responses to surveys or experiments.

For example, in a study of mental health, the variable “resilience” could be considered a latent variable. It can’t be directly measured , but it can be inferred from measures of mental health symptoms, stress, and coping mechanisms. The same applies to a lot of concepts we encounter every day – for example:

• Emotional intelligence
• Quality of life
• Business confidence
• Ease of use

One way in which we overcome the challenge of measuring the immeasurable is latent variable models (LVMs). An LVM is a type of statistical model that describes a relationship between observed variables and one or more unobserved (latent) variables. These models allow researchers to uncover patterns in their data which may not have been visible before, thanks to their complexity and interrelatedness with other variables. Those patterns can then inform hypotheses about cause-and-effect relationships among those same variables which were previously unknown prior to running the LVM. Powerful stuff, we say!

Let’s recap

In the world of scientific research, there’s no shortage of variable types, some of which have multiple names and some of which overlap with each other. In this post, we’ve covered some of the popular ones, but remember that this is not an exhaustive list .

To recap, we’ve explored:

• Independent variables (the “cause”)
• Dependent variables (the “effect”)
• Control variables (the variable that’s not allowed to vary)

If you’re still feeling a bit lost and need a helping hand with your research project, check out our 1-on-1 coaching service , where we guide you through each step of the research journey. Also, be sure to check out our free dissertation writing course and our collection of free, fully-editable chapter templates .

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15 Independent and Dependent Variable Examples

Dave Cornell (PhD)

Dr. Cornell has worked in education for more than 20 years. His work has involved designing teacher certification for Trinity College in London and in-service training for state governments in the United States. He has trained kindergarten teachers in 8 countries and helped businessmen and women open baby centers and kindergartens in 3 countries.

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Chris Drew (PhD)

This article was peer-reviewed and edited by Chris Drew (PhD). The review process on Helpful Professor involves having a PhD level expert fact check, edit, and contribute to articles. Reviewers ensure all content reflects expert academic consensus and is backed up with reference to academic studies. Dr. Drew has published over 20 academic articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education and holds a PhD in Education from ACU.

An independent variable (IV) is what is manipulated in a scientific experiment to determine its effect on the dependent variable (DV).

By varying the level of the independent variable and observing associated changes in the dependent variable, a researcher can conclude whether the independent variable affects the dependent variable or not.

This can provide very valuable information when studying just about any subject.

Because the researcher controls the level of the independent variable, it can be determined if the independent variable has a causal effect on the dependent variable.

The term causation is vitally important. Scientists want to know what causes changes in the dependent variable. The only way to do that is to manipulate the independent variable and observe any changes in the dependent variable.

Definition of Independent and Dependent Variables

The independent variable and dependent variable are used in a very specific type of scientific study called the experiment .

Although there are many variations of the experiment, generally speaking, it involves either the presence or absence of the independent variable and the observation of what happens to the dependent variable.

The research participants are randomly assigned to either receive the independent variable (called the treatment condition), or not receive the independent variable (called the control condition).

Other variations of an experiment might include having multiple levels of the independent variable.

If the independent variable affects the dependent variable, then it should be possible to observe changes in the dependent variable based on the presence or absence of the independent variable.  

Of course, there are a lot of issues to consider when conducting an experiment, but these are the basic principles.

These concepts should not be confused with predictor and outcome variables .

Examples of Independent and Dependent Variables

1. gatorade and improved athletic performance.

A sports medicine researcher has been hired by Gatorade to test the effects of its sports drink on athletic performance. The company wants to claim that when an athlete drinks Gatorade, their performance will improve.

If they can back up that claim with hard scientific data, that would be great for sales.

So, the researcher goes to a nearby university and randomly selects both male and female athletes from several sports: track and field, volleyball, basketball, and football. Each athlete will run on a treadmill for one hour while their heart rate is tracked.

All of the athletes are given the exact same amount of liquid to consume 30-minutes before and during their run. Half are given Gatorade, and the other half are given water, but no one knows what they are given because both liquids have been colored.

In this example, the independent variable is Gatorade, and the dependent variable is heart rate.  

2. Chemotherapy and Cancer

A hospital is investigating the effectiveness of a new type of chemotherapy on cancer. The researchers identified 120 patients with relatively similar types of cancerous tumors in both size and stage of progression.

The patients are randomly assigned to one of three groups: one group receives no chemotherapy, one group receives a low dose of chemotherapy, and one group receives a high dose of chemotherapy.

Each group receives chemotherapy treatment three times a week for two months, except for the no-treatment group. At the end of two months, the doctors measure the size of each patient’s tumor.

In this study, despite the ethical issues (remember this is just a hypothetical example), the independent variable is chemotherapy, and the dependent variable is tumor size.

3. Interior Design Color and Eating Rate

A well-known fast-food corporation wants to know if the color of the interior of their restaurants will affect how fast people eat. Of course, they would prefer that consumers enter and exit quickly to increase sales volume and profit.

So, they rent space in a large shopping mall and create three different simulated restaurant interiors of different colors. One room is painted mostly white with red trim and seats; one room is painted mostly white with blue trim and seats; and one room is painted mostly white with off-white trim and seats.

Next, they randomly select shoppers on Saturdays and Sundays to eat for free in one of the three rooms. Each shopper is given a box of the same food and drink items and sent to one of the rooms. The researchers record how much time elapses from the moment they enter the room to the moment they leave.

The independent variable is the color of the room, and the dependent variable is the amount of time spent in the room eating.

4. Hair Color and Attraction

A large multinational cosmetics company wants to know if the color of a woman’s hair affects the level of perceived attractiveness in males. So, they use Photoshop to manipulate the same image of a female by altering the color of her hair: blonde, brunette, red, and brown.

Next, they randomly select university males to enter their testing facilities. Each participant sits in front of a computer screen and responds to questions on a survey. At the end of the survey, the screen shows one of the photos of the female.

At the same time, software on the computer that utilizes the computer’s camera is measuring each male’s pupil dilation. The researchers believe that larger dilation indicates greater perceived attractiveness.

The independent variable is hair color, and the dependent variable is pupil dilation.

5. Mozart and Math

After many claims that listening to Mozart will make you smarter, a group of education specialists decides to put it to the test. So, first, they go to a nearby school in a middle-class neighborhood.

During the first three months of the academic year, they randomly select some 5th-grade classrooms to listen to Mozart during their lessons and exams. Other 5 th grade classrooms will not listen to any music during their lessons and exams.

The researchers then compare the scores of the exams between the two groups of classrooms.

Although there are a lot of obvious limitations to this hypothetical, it is the first step.

The independent variable is Mozart, and the dependent variable is exam scores.

6. Essential Oils and Sleep

A company that specializes in essential oils wants to examine the effects of lavender on sleep quality. They hire a sleep research lab to conduct the study. The researchers at the lab have their usual test volunteers sleep in individual rooms every night for one week.

The conditions of each room are all exactly the same, except that half of the rooms have lavender released into the rooms and half do not. While the study participants are sleeping, their heart rates and amount of time spent in deep sleep are recorded with high-tech equipment.

At the end of the study, the researchers compare the total amount of time spent in deep sleep of the lavender-room participants with the no lavender-room participants.

The independent variable in this sleep study is lavender, and the dependent variable is the total amount of time spent in deep sleep.

7. Teaching Style and Learning

A group of teachers is interested in which teaching method will work best for developing critical thinking skills.

So, they train a group of teachers in three different teaching styles : teacher-centered, where the teacher tells the students all about critical thinking; student-centered, where the students practice critical thinking and receive teacher feedback; and AI-assisted teaching, where the teacher uses a special software program to teach critical thinking.

At the end of three months, all the students take the same test that assesses critical thinking skills. The teachers then compare the scores of each of the three groups of students.

The independent variable is the teaching method, and the dependent variable is performance on the critical thinking test.

8. Concrete Mix and Bridge Strength

A chemicals company has developed three different versions of their concrete mix. Each version contains a different blend of specially developed chemicals. The company wants to know which version is the strongest.

So, they create three bridge molds that are identical in every way. They fill each mold with one of the different concrete mixtures. Next, they test the strength of each bridge by placing progressively more weight on its center until the bridge collapses.

In this study, the independent variable is the concrete mixture, and the dependent variable is the amount of weight at collapse.

9. Recipe and Consumer Preferences

People in the pizza business know that the crust is key. Many companies, large and small, will keep their recipe a top secret. Before rolling out a new type of crust, the company decides to conduct some research on consumer preferences.

The company has prepared three versions of their crust that vary in crunchiness, they are: a little crunchy, very crunchy, and super crunchy. They already have a pool of consumers that fit their customer profile and they often use them for testing.

Each participant sits in a booth and takes a bite of one version of the crust. They then indicate how much they liked it by pressing one of 5 buttons: didn’t like at all, liked, somewhat liked, liked very much, loved it.

The independent variable is the level of crust crunchiness, and the dependent variable is how much it was liked.

10. Protein Supplements and Muscle Mass

A large food company is considering entering the health and nutrition sector. Their R&D food scientists have developed a protein supplement that is designed to help build muscle mass for people that work out regularly.

The company approaches several gyms near its headquarters. They enlist the cooperation of over 120 gym rats that work out 5 days a week. Their muscle mass is measured, and only those with a lower level are selected for the study, leaving a total of 80 study participants.

They randomly assign half of the participants to take the recommended dosage of their supplement every day for three months after each workout. The other half takes the same amount of something that looks the same but actually does nothing to the body.

At the end of three months, the muscle mass of all participants is measured.

The independent variable is the supplement, and the dependent variable is muscle mass.  

11. Air Bags and Skull Fractures

In the early days of airbags , automobile companies conducted a great deal of testing. At first, many people in the industry didn’t think airbags would be effective at all. Fortunately, there was a way to test this theory objectively.

In a representative example: Several crash cars were outfitted with an airbag, and an equal number were not. All crash cars were of the same make, year, and model. Then the crash experts rammed each car into a crash wall at the same speed. Sensors on the crash dummy skulls allowed for a scientific analysis of how much damage a human skull would incur.

The amount of skull damage of dummies in cars with airbags was then compared with those without airbags.

The independent variable was the airbag and the dependent variable was the amount of skull damage.

12. Vitamins and Health

Some people take vitamins every day. A group of health scientists decides to conduct a study to determine if taking vitamins improves health.

They randomly select 1,000 people that are relatively similar in terms of their physical health. The key word here is “similar.”

Because the scientists have an unlimited budget (and because this is a hypothetical example, all of the participants have the same meals delivered to their homes (breakfast, lunch, and dinner), every day for one year.

In addition, the scientists randomly assign half of the participants to take a set of vitamins, supplied by the researchers every day for 1 year. The other half do not take the vitamins.

At the end of one year, the health of all participants is assessed, using blood pressure and cholesterol level as the key measurements.

In this highly unrealistic study, the independent variable is vitamins, and the dependent variable is health, as measured by blood pressure and cholesterol levels.

13. Meditation and Stress

Does practicing meditation reduce stress? If you have ever wondered if this is true or not, then you are in luck because there is a way to know one way or the other.

All we have to do is find 90 people that are similar in age, stress levels, diet and exercise, and as many other factors as we can think of.

Next, we randomly assign each person to either practice meditation every day, three days a week, or not at all. After three months, we measure the stress levels of each person and compare the groups.

How should we measure stress? Well, there are a lot of ways. We could measure blood pressure, or the amount of the stress hormone cortisol in their blood, or by using a paper and pencil measure such as a questionnaire that asks them how much stress they feel.

In this study, the independent variable is meditation and the dependent variable is the amount of stress (however it is measured).

14. Video Games and Aggression

When video games started to become increasingly graphic, it was a huge concern in many countries in the world. Educators, social scientists, and parents were shocked at how graphic games were becoming.

Since then, there have been hundreds of studies conducted by psychologists and other researchers. A lot of those studies used an experimental design that involved males of various ages randomly assigned to play a graphic or non-graphic video game.

Afterward, their level of aggression was measured via a wide range of methods, including direct observations of their behavior, their actions when given the opportunity to be aggressive, or a variety of other measures.

So many studies have used so many different ways of measuring aggression.

In these experimental studies, the independent variable was graphic video games, and the dependent variable was observed level of aggression.

15. Vehicle Exhaust and Cognitive Performance

Car pollution is a concern for a lot of reasons. In addition to being bad for the environment, car exhaust may cause damage to the brain and impair cognitive performance.

One way to examine this possibility would be to conduct an animal study. The research would look something like this: laboratory rats would be raised in three different rooms that varied in the degree of car exhaust circulating in the room: no exhaust, little exhaust, or a lot of exhaust.

After a certain period of time, perhaps several months, the effects on cognitive performance could be measured.

One common way of assessing cognitive performance in laboratory rats is by measuring the amount of time it takes to run a maze successfully. It would also be possible to examine the physical effects of car exhaust on the brain by conducting an autopsy.

In this animal study, the independent variable would be car exhaust and the dependent variable would be amount of time to run a maze.

Read Next: Extraneous Variables Examples

The experiment is an incredibly valuable way to answer scientific questions regarding the cause and effect of certain variables. By manipulating the level of an independent variable and observing corresponding changes in a dependent variable, scientists can gain an understanding of many phenomena.

For example, scientists can learn if graphic video games make people more aggressive, if mediation reduces stress, if Gatorade improves athletic performance, and even if certain medical treatments can cure cancer.

The determination of causality is the key benefit of manipulating the independent variable and them observing changes in the dependent variable. Other research methodologies can reveal factors that are related to the dependent variable or associated with the dependent variable, but only when the independent variable is controlled by the researcher can causality be determined.

Ferguson, C. J. (2010). Blazing Angels or Resident Evil? Can graphic video games be a force for good? Review of General Psychology, 14 (2), 68-81. https://doi.org/10.1037/a0018941

Flannelly, L. T., Flannelly, K. J., & Jankowski, K. R. (2014). Independent, dependent, and other variables in healthcare and chaplaincy research. Journal of Health Care Chaplaincy , 20 (4), 161–170. https://doi.org/10.1080/08854726.2014.959374

Manocha, R., Black, D., Sarris, J., & Stough, C.(2011). A randomized, controlled trial of meditation for work stress, anxiety and depressed mood in full-time workers. Evidence-Based Complementary and Alternative Medicine , vol. 2011, Article ID 960583. https://doi.org/10.1155/2011/960583

Rumrill, P. D., Jr. (2004). Non-manipulation quantitative designs. Work (Reading, Mass.) , 22 (3), 255–260.

Taylor, J. M., & Rowe, B. J. (2012). The “Mozart Effect” and the mathematical connection, Journal of College Reading and Learning, 42 (2), 51-66.  https://doi.org/10.1080/10790195.2012.10850354

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The Principles of Biomedical Scientific Writing: Title

Zahra bahadoran, parvin mirmiran, khosrow kashfi, asghar ghasemi.

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Corresponding Author: Endocrine Physiology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Email: [email protected]

Received 2019 Sep 23; Accepted 2019 Oct 12; Revised 2019 Oct 10; Collection date 2019 Oct.

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License ( http://creativecommons.org/licenses/by-nc/4.0/ ) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.

The title of a paper is “like a hat on a head or the front door to a house” and its initial impression. Writing a good and effective title makes the paper more retrievable by search engines and maximizes its impact in the scientific community. The paper’s title presents what has been studied, how it has been done, and what are the major results. A well-written title is balanced for being informative and concise, as well as attractively conveying the main topic, highlighting the importance of the study. For writing a good title, it should be drafted correctly, accurately, carefully, and meticulously by the main study keywords. By removing extra and unspecific words, the final title should be unambiguous, memorable, captivating, and informative. Here, we provided an overview of the importance and function of the title as well as different types of titles in scientific medical writing. We also focused on the content and organization of the title of a hypothesis-testing paper. In addition, the features of a good title were discussed.

Keywords: Title, Scientific Writing, Biomedical Journals

The title is the “single most important line of a publication” ( 1 ). Although the title is a very small part of a research paper, it plays an important role in connecting the writer with potential readers. It also determines whether the paper is read or not ( 2 ). The title of a paper acts as a billboard, a descriptor, an advertisement ( 3 ), or a trailer for the movie ( 4 ). For every person who reads the whole paper, about 500 people only read the title, indicating that the majority of the papers are read by title alone ( 5 ). The title can influence the first impression of the work during the pre-publication process that occurs in the peer-review, as well as the post-publication process, which affects both dissemination and citations ( 3 , 6 ). Therefore, writing an effective title is an important step in scientific writing.

A good title provides a reconciliation between being attractive and being informative ( 4 ); it means that the title should motivate the readers to read an article, give them a summary of the contents, and provide an overview of the topics and findings ( 7 ). A well-written title will help other researchers to find the paper more easily ( 8 ), whereas a poorly written one may make a paper difficult to be retrieved by search engines, discourage readers to go through the text, and reduce an article’s impact ( 9 ). There are examples where journals have withdrawn a published paper because of it having a wrong title ( 10 ), a misleading or an inaccurate title ( 11 , 12 ), or for misuse of words within the title ( 13 ).

Following our previous reports on how to write and construct an introduction ( 14 ), materials and methods ( 15 ), results ( 16 ), and discussion ( 17 ) as sections of a scientific paper, here, we provided an overview of the importance and function of the title. We also focused on different types of titles that are commonly used in scientific and biomedical writings, in particular highlighting the function, content, and organization of the title in a hypothesis-testing paper.

2. Functions of the Title

The title of a biomedical scientific paper has two main functions ( 18 , 19 ): (1) to present the main topic or the message of the paper (the answer to the question) and (2) to attract potential readers and evoke their interest to read the paper. In fact, the title tells the readers what the paper is all about ( 6 , 19 ). The title also provides some keywords for further search ( 19 ) and facilitates the retrieval of the paper from bibliographic databases as this is used by the abstracting and documentation services in order to classify and index the paper ( 20 ).

3. Content of the Title

The main elements of a title include intervention, end-point or outcome, study population, and its specific conditions, design, and setting, which refers to a situation or a place that study was conducted at ( 21 ). The main elements in a hypothesis-testing paper, are (1) the independent variable(s) (X), (2) dependent variable(s) (Y), and (3) the study subjects (i.e. animal, population) or materials (i.e. culture media, cell line, tissue) (Z).

If important, the experimental approach and the condition of the animals/subjects during the study can also be included in the title ( 18 ). The specific organism or the biological system studied (e.g. animals, bacteria, cell culture) must always be included in the title ( 3 , 18 ). In case of humans, they are often removed from the title ( 3 , 18 ). It means that in biomedical journals, it is assumed that the species studied is human unless otherwise stated ( 3 ) and no population in the title indicates that the population is humans ( 18 ). However, if a subpopulation of humans was studied (e.g. patients who have asthma), that should be included in the title ( 18 ). Indication of the study setting (e.g. community-based, home-based, school-based, hospital-based, rural or urban setting) in the title is only important if the results are not generalizable to other settings, or if the setting reflects the magnitude of the research ( 21 ).

In descriptive papers, where a new structure is described, an important element of the title is to name that structure and its key function ( 18 ). In method papers, the name of the method (apparatus or material), its purpose, and the population where the method is used for are key elements of the title ( 18 ). According to the journal’s style or where appropriate, the study design may also be stated ( 8 ). This is especially true for randomized clinical trials, cohort, case-control, and cross-sectional studies ( 4 ). What this does is to alert the readers regarding the level of the evidence in the paper ( 4 ). Stating the study design in the title, usually located after a colon or an Em dash, makes the title more complete ( 21 ). Stating what type the review is (narrative, systematic or quantitative systematic) may also be helpful, especially for quantitative systematic reviews (meta-analysis) where a high level of evidence is suggested ( 4 ).

4. Organization of the Title

4.1. descriptive (neutral) titles.

Descriptive titles describe the subject of the paper but do not reveal the main conclusions ( 22 ) and are usually recommended as the best form of titles ( 23 ). Most of these contain all the elements of the research work (e.g. study population, intervention, study outcome, comparison) ( 21 , 23 ). In a hypothesis-testing paper, a descriptive title traditionally states the topic of the paper using its three essential pieces of information (dependent variable, independent variable, study subject or material), the so-called X, Y, and Z ( 18 ); e.g. a common form of such titles are “effect of X on Y in Z” (e.g. Effect of broccoli sprouts on insulin resistance in type 2 diabetic patients: a randomized double-blind clinical trial ( 24 )) or “Y during X in Z” (e.g. change of maternal serum triglycerides during third trimester of pregnancy in obese women). Usually, Z comes at the end of the title ( 18 ). Where there is no independent variable (X), the title would be Y in Z (e.g. dynamics of the chest wall in preterm infants) ( 18 ). If the study has several independent or dependent variables where they cannot be summarized under the general categories, it is advisable to select the most important ones ( 18 ) since these are new findings and should be presented in the title ( 25 ).

4.2. Declarative Titles

Declarative titles present the main conclusions or the actual message of the study ( 26 , 27 ). The message can be stated in a phrase or in a sentence ( 18 ). When the message is expressed in a phrase, an adjective or a noun (based on the verb used in the question and answer) or a combination of both are placed at the beginning of the title before the dependent variable; e.g. “reduced metabolic rate during radio-frequency irradiation in rats”, in which the message is expressed as an adjective, reduced ( 18 ). When the message is expressed in a sentence, a verb in the present tense is used; e.g. continuous positive airway pressure impairs renal function in anesthetized newborn goats ( 18 ). Using a sentence is stronger than using a phrase (because verbs convey an action more powerful than adjectives and nouns); therefore, it is used only when solid evidence supports a clear message ( 18 ). Some believe that using a sentence as a title overemphasize a conclusion and is best to be avoided ( 4 ).

In hypothesis-testing papers, the message of the paper can be stated in the title, where the message is strong and clear, and is supported by strong and solid evidence ( 18 , 23 ). Authors also need to be ensured that the title is true and is supported by the rest of the paper ( 28 ). When the title is a complete sentence, it conveys the impression that the study has reached a definite conclusion ( 19 ). e.g. “endothelium-derived relaxing factor produced and released from artery and vein is nitric oxide” ( 29 ).

Some believe that declarative titles would help authors to select a more appropriate paper during their search ( 27 ). For some types of papers such as commentaries, journals (e.g. obstetrics and gynecology) may push the authors to write a declarative title regarding the commentary’s main argument(s). Declarative titles give the impression that the findings of the study have general validity, which rarely is the case ( 26 ). Editors are, therefore, more cautious in accepting declarative titles due to its possible impact on public health ( 22 ) and some journals do not accept declarative titles (e.g. New England Journal of Medicine) ( 26 ). In addition, in case of choosing a declarative title, authors need to ask themselves will the title kill the curiosity? Will the readers lose motivation and interest to read the full article? ( 23 ).

Generally, the present tense in the title emphasizes the general validity of the results whereas the past tense indicates that the results are not established knowledge yet. To state results of a single investigation past tense and for results of a systematic review present tense should be used ( 27 ).

4.3. Interrogative Titles

To make a title more attractive, an interrogative form, which phrases the subject of the paper in the form of a question, can be used ( 30 ). However, in hypothesis-testing papers, interrogative titles are not recommended ( 31 ), because the reader would appreciate being told the answer from the beginning ( 30 ). An interrogative title may be appropriate for a review article, where the controversial issues are being discussed in response to the study question ( 30 ); e.g. are shorter article titles more attractive for citations? Cross-sectional study of 22 scientific journals ( 32 ). Interrogative titles in general lead to more paper down-loads but may result in fewer citations ( 22 ).

4.4. Compound Titles

Compound titles (or hanging titles) contain the main title and a subtitle ( 23 ) that are separated by a colon (:) ( 18 ). Compound titles can be started with a short question, a subject sentence, or a noun phrase, followed by a colon and a declarative sentence or a question ( 22 ). These types of titles are used to provide additional relevant information (e.g. about the study design, geographic or temporal scope of the research) or to add substance to a provocative area ( 23 ); e.g. developmental origins of type 2 diabetes: focus on epigenetics ( 33 ). They are useful for complex studies ( 19 ) and series papers ( 18 ). Using subtitles is not recommended except for putting an important word first ( 18 ). Papers with subtitles seem to be more attractive and are less likely to be rejected ( 34 ). In a compound title, the main part (main title) should be standalone ( 4 ).

4.5. Other Types of Title

Other styles, less commonly used to organize the title, are “indicating the direction of the author’s opinion”, “emphasizing the methodology used in the research”, “suggesting guidelines”, or “making a comparison” ( 35 ). To get more attention, the use of “effective opening”, “alliteration”, “irony”, “puns”, “humor” or “mystifying” ( 35 ) may also be used. However, the latter styles do help the paper grab readers’ attention, the authors need to ensure they will be understood and appreciated by all readers and are culturally appropriate ( 23 ). One example of referring to a parable in the title is: challenges for measuring oxytocin: the blind men and the elephant? ( 36 ), in which the subtitle refers to the parable of the 6 blind men and the elephant.

5. The Procedure of Writing an Effective Title

Although it is the first section of a paper that is seen ( 3 , 6 , 19 ), title is drawn from other sections of paper ( 3 ) and the final title is usually written as the last part ( 19 ). Good titles are created with care and craft ( 4 ). Writing a good title needs a back-and-forth process by continuous going back to the text with a sharper focus on what the paper is trying to say ( 35 ).

As shown in Figure 1 , a stepwise process is suggested to be followed to draft a title. What the authors need to do in the first step is to consider the manuscript entirely and then try to describe the content of the paper using essential keywords and phrases. Then, they need to make a sentence by the selected keywords and then remove redundant and nonspecific words/adjectives ( 20 ). The keywords used in the title should be the same as that used in the question and answer in the introduction, discussion, and abstract ( 18 ). The initial title must then be reviewed, refined and finally checked for having features of an effective final title. The title should not be hastily finalized; making a consultation with colleagues to get their opinion and possible suggestions can help improve the title ( 23 ). The authors are highly recommended to adhere to the style of the journal that they are submitting to e.g. word count, other instructions such as acceptable types of title (declarative and interrogative ones are unacceptable by some), use of capital letters, hyphens, colon, etc.

Figure 1. A five-step process of writing a title for a research paper is depicted. Created using BioRender.com.

6. Features of a Suitable Title

In addition to highlighting the subject matter (be informative), the title of the paper should be eye-catching (be attractive) ( 25 , 37 ). The most important concept should be placed at or near the beginning of the title (where it most readily catches the reader’s eye) ( 25 ). Table 1 describes the features of a good title. In brief, a well-written title should be attractive and engaging ( 4 , 6 , 26 ), comprehensive ( 8 , 37 ), accurate ( 18 ), sufficiently descriptive ( 37 ), complete ( 18 ), informative ( 3 , 4 , 6 , 8 ), and specific ( 4 , 18 , 37 ) as well as be concise ( 3 , 4 , 6 , 8 , 18 , 26 , 37 ), clear (unambiguous) ( 3 , 18 ) and begins with an important term ( 3 , 18 ). The title should not be too general ( 19 , 31 ) or too-detailed ( 31 ), be misleading or unrepresentative ( 26 ), omit major elements ( 19 ), or include unnecessary details ( 19 ).

Table 1. Features of a Suitable Title.

7. length of the title.

Although longer titles may provide more information regarding the content, they reduce the interest generated ( 39 ). A short title is easier to understand and can attract a wider readership and increase the influence of the paper ( 40 ). Therefore, the authors are advised to make the title as short as possible without sacrificing accuracy, completeness, specificity, and clarity ( 18 ). High-impact journals usually restrict the length of their papers’ titles ( 40 ).

Try to keep your title shorter than 100 characters (i.e. letters and punctuation marks), including spaces (120 characters are considered the upper limit) ( 18 ). As the rule of thumb, 10 - 12 words may be the ideal length of a paper ( 41 ) and the title should not be more than 12 words ( 31 ).

8. Word Choice in the Title

In addition to being relevant to the target audience ( 3 ), every word (excluding articles e.g. the, a, an, and prepositions e.g. to, about, on) used in the title should add significance ( 28 ). Words in the title need to be checked by Medical Subjects Headings (MeSH) ( 31 ). Using study keywords to formulate a title is highly recommended. Using the most important keywords in the title is essential for appropriate indexing purposes and for retrieval by search engines and available databases ( 38 ). Indexing services (e.g. PubMed) and search engines (e.g. Google) use keywords and terms in the title ( 3 , 6 ). Titles should not start with a numeral, or expressions like “a study of”, “a contribution to”, “investigations on” or “some interesting” ( 20 ). “Influence of” does not evoke much curiosity and if possible should be avoided ( 25 ).

Generally, the use of neutral words (e.g. inquiry, analysis, evaluation, assessment, etc.), that give no information to the readers, is not recommended ( 28 ). However, in some cases, these words may be necessary to inform the scope, intent, or type of a study ( 42 ). Although the use of catchy phrases or non-specific language is not recommended in academic writing, they can be used within the context of the study ( 42 ).

Adjectives (e.g. increased) that modify quantitative words (e.g. metabolic rate) are different from those (e.g. improved) that modify qualitative words (e.g. performance) ( 18 ). Some adjectives such as “novel” or “innovative” need to be replaced by more explicit adjectives to explain to the readers what makes the study novel ( 28 ); e.g. “A noninvasive method of predicting pulmonary-capillary wedge pressure” ( 43 ) or “An ultrasound method for safe and rapid central venous access” ( 44 ). If possible, replace long words with short ones ( 26 ). Try to avoid gerunds (verb forms that end in -ing) in the title as the actor is obscured ( 31 ). Avoid using generic terms such as animal, bacteria, or antibiotic as key terms ( 3 ).

Abbreviations confuse readers and usually are not used by indexing services ( 3 ). In some situations, e.g. long or technical terms in scientific writings, the use of abbreviations can be useful ( 21 ). Using abbreviations that appear as word entries in Webster’s Collegiate Dictionary ( 21 ), are better known than their words (e.g. DNA, AIDS, and FDA) ( 3 , 18 ), or abbreviations for chemicals (e.g. N 2 O 5 ), are acceptable in the title ( 18 ).

9. Word Order in the Title

Paying attention to syntax (word order) in the title is important because it can influence the reader’s interest in the paper ( 3 ). Generally, words at the beginning of the title make the most impact ( 20 ). Put an important word (e.g. independent or dependent variables) first in the title to attract readers ( 3 , 18 , 25 , 26 ). What you want to be emphasized as the primary subject matter i.e. the key concept of the paper needs to appear first and near the beginning of the title ( 3 , 25 ). Because search engines such as Google, typically show only the first 6 - 7 words of a title, most associated terms should, therefore, appear earlier ( 3 ). Using a subtitle (to state-specific topic) following the main title (to state general topic) is a technique for putting an important word or phrase first in the title ( 18 ); e.g. “Holistic review: shaping the medical profession one applicant at a time” ( 45 ) or “Medical school admissions: applicant projections revisited” ( 46 ).

10. Use of Preposition in the Title

A preposition is a word or a group of words used before a noun, pronoun, or noun phrase to show direction, time, place, location, spatial relationships, or to introduce an object. Correct use of prepositions in the title makes it more clear and helps the reader to understand how the title elements are related to each other ( 28 ). Typical prepositions used in the title, are by (to indicate how something is done), for (referring to a purpose), from (referring to the origin of something), in (referring to a location), of (belonging to or regrading) ( 28 ).

11. Running Title

To identify the articles in a journal, short phrases called running titles (running heads) appear at the top or bottom of every page or every other page ( 6 , 18 ). Running titles are short versions of the title ( 6 , 18 ) and help readers to keep track of the article throughout its printed pages ( 21 ). As running titles mostly cannot be longer than 50 characters (including the spaces), authors are recommended to use standard abbreviations and omit the study design ( 21 ). In hypothesis-testing papers, the running title usually names independent and dependent variables ( 18 ). The form “X and Y”, which is unspecific for the title can be used for the running title ( 18 ).

12. Title and Paper Citation

A well-organized title is positively associated with paper citation ( 47 ). Some studies have addressed how the feature and structure of a title can affect pre- and post-publication manuscript success ( 9 ). Association of title’s length and citation of the paper has remained inconclusive ( 47 , 48 ), however, papers with shorter titles ( 40 ) especially when presenting study conclusion ( 49 ) receive more citations ( 40 ). Analysis of published papers in the Lancet journal showed that titles with two components separated by a colon were significantly more common in the well-cited papers ( 47 ). Titles emphasizing broader conceptual or comparative issues get more attention than those being more specific (e.g. use of particular genus or species by their taxonomic name in the title) ( 9 ). Some factors such as referring to a specific country or geographical region may also lead to poor citation of the paper ( 47 , 49 ). Other factors such as punctuations and use of acronyms can also affect the citation rate of a paper ( 47 ). Use of “colon”, “hyphen” and “comma” was most frequent whereas “semi-colon”, “dash” and “single quotation marks” were least frequent punctuation marks in top-cited papers ( 50 ).

13. Conclusions

The essence of research is reflected in its title, which acts as a “signpost” for the main topic of the paper ( 31 ). In addition to presenting the message of the paper, the title should evoke interest in reading the paper. Appropriate types of a title (e.g. descriptive, declarative, interrogative) should be selected by the authors and in all cases, the title should be accurate, unambiguous, interesting, concise, precise, unique, and should not be misleading. “The Title” should present the substance of the work in a clear way.

Authors' Contribution: Study concept and design: Zahra Bahadoran and Asghar Ghasemi; drafting of the manuscript: Zahra Bahadoran, Parvin Mirmiran, and Asghar Ghasemi; critical revision of the manuscript for important intellectual content: Khosrow Kashfi and Parvin Mirmiran.

Conflict of Interests: The authors have no conflict of interest.

Funding/Support: This study was supported by the Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences.

Contributor Information

Zahra Bahadoran, Email: [email protected].

Parvin Mirmiran, Email: [email protected].

Khosrow Kashfi, Email: [email protected].

Asghar Ghasemi, Email: [email protected].

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Organizing Your Social Sciences Research Paper

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The title summarizes the main idea or ideas of your study. A good title contains the fewest possible words needed to adequately describe the content and purpose of your research paper. It serves as the initial gateway to the content of a publication.

Bowman, Deborah, and Stephanie Kinnan. "Creating Effective Titles for Your Scientific Publications." VideoGIE 3 (September 2018): 260-261; Bavdekar, Sandeep B. "Formulating the Right Title for a Research Article." Journal of the Association of Physicians of India 64 (February 2016): 53-56.

Importance of Choosing a Good Title

When searching for research on a topic, the title is almost always read first because it is the key identifier of what is being studied . Given this, it is the most important element that defines the research study. With this in mind, avoid the following when creating a title:

• A title should not be too long . If it is lengthy, this usually means there are too many unnecessary words. Avoid language, such as, "A Study to Investigate the...," or "An Examination of the...." These phrases are obvious and generally superfluous unless they are necessary to covey the scope, intent, or type of study.
• On the other hand, a title which is too short often uses words which are too broad or general and, thus, does not tell the reader what is being studied . For example, a paper with the title, "African Politics" is so non-specific the title could be the title of a book and so ambiguous that it could refer to anything associated with politics in Africa. A good title should provide information about the focus and/or scope of your research study.
• In academic writing, catchy phrases or non-specific language may be used, but only if it's within the context of the study [e.g., "Fair and Impartial Jury--Catch as Catch Can"]. However, in most cases, you should avoid including words or phrases that do not help the reader understand the purpose of your paper. An exception to a catchy phrase could be a short quotation derived from a source used in your study that grabs the reader's attention. However, the quote must be clearly relevant to the topic of the paper.
• Academic writing is a serious and deliberate endeavor . Avoid using humorous or clever journalistic styles of phrasing when creating the title to your paper. Journalistic headlines often use emotional adjectives [e.g., incredible, amazing, effortless] to highlight a problem experienced by the reader or use "trigger words" or interrogative words like how, what, when, or why to persuade people to read the article or click on a link. These approaches are viewed as counter-productive in academic writing. A reader does not need clever or humorous titles to catch their attention because the act of reading research is assumed to be deliberate based on a desire to learn and improve understanding of the problem. In addition, a humorous title can detract from the seriousness and authority of your research. 
• Titles do not have to adhere to rigid grammatical or stylistic standards . Unlike everywhere else in a college-level social sciences research paper [except when using direct quotes], the purpose of the title is to capture the reader's attention. For example, it could be appropriate to begin a title with a coordinating conjunction [i.e., and, but, or, nor, for, so, yet] if it makes sense to do so and does not detract from the purpose of the study [e.g., "Yet Another Look at Mutual Fund Tournaments"], beginning the title with an inflected form of a verb such as those ending in -ing [e.g., "Assessing the Political Landscape: Structure, Cognition, and Power in Organizations"], or using a catchy quote to get the read's attention ["Mobley Jr, Steve D., Ramon W. Johnson, Christopher JP Sewell, Jennifer M. Johnson, and Amon J. Neely. "'We Are Not Victims': Unmasking Black Queer and Trans Student Activism at HBCUs"].

Appiah, Kingsley Richard et al. “Structural Organisation of Research Article Titles: A Comparative Study of Titles of Business, Gynaecology and Law.” Advances in Language and Literary Studies 10 (2019); Bavdekar, Sandeep B. "Formulating the Right Title for a Research Article." Journal of the Association of Physicians of India 64 (February 2016): 53-56. Hartley James. “To Attract or to Inform: What are Titles for?” Journal of Technical Writing and Communication 35 (2005): 203-213; Huggett, Sarah. "Heading for Success: Or How Not to Title your Paper." Research Trends 1 (September 2011): 4; Jaakkola, Maarit. “Journalistic Writing and Style.” In Oxford Research Encyclopedia of Communication . Jon F. Nussbaum, editor. (New York: Oxford University Press, 2018): https://oxfordre.com/communication.

Structure and Writing Style

The following parameters can be used to help you formulate a suitable research paper title:

• The purpose of the research
• The scope of the research
• The narrative tone of the paper [typically defined by the type of research]
• The methods used to study the problem

The aim of a title is to capture the reader’s attention by highlighting the research problem under investigation.

Create a Working Title Typically, the final title you submit to your professor is created after the research is complete so that the title accurately captures what has been done . The working title should be developed early in the research process because it can help anchor the focus of your study in much the same way the research problem does. Referring back to the working title can help you reorient yourself back to the main purpose of the study if you find yourself drifting off on a tangent while researching and writing your paper. The Final Title Effective titles in research papers have a number of characteristics that reflect general principles of academic writing.

• Indicate accurately the subject and scope of the study,
• Rarely use abbreviations or acronyms unless they are commonly known,
• Use words that create a positive impression and stimulate reader interest,
• Use current nomenclature from the field of study,
• Identify key variables, both dependent and independent,
• Reveal how the paper will be organized,
• Suggest a relationship between variables which supports the major hypothesis,
• Is limited to 5 to 12 substantive words,
• Does not include redundant phrasing, such as, "A Study of," "An Analysis of" or similar constructions,
• Takes the form of a question or declarative statement,
• If you use a quote as part of the title, the source of the quote is cited [usually using an asterisk and footnote],
• Use correct grammar and capitalization with all first words and last words capitalized, including the first word of a subtitle. All nouns, pronouns, verbs, adjectives, and adverbs that appear between the first and last words of the title are also capitalized, and
• Avoid using an exclamation mark at the end of the title.

The Subtitle Subtitles are frequently used in social and behavioral sciences research papers because it helps the reader understand the scope of the study in relation to how it was designed to address the research problem. Often, the main title describes the problem and the subtitle clarifies the context, highlights the method of analysis, or identifies the research setting. Think about what type of subtitle listed below reflects the overall approach to your study and whether you believe a subtitle is needed to emphasize the investigative parameters of your research.

1.  Explains or provides additional context , e.g., "Linguistic Ethnography and the Study of Welfare Institutions as a Flow of Social Practices: The Case of Residential Child Care Institutions as Paradoxical Institutions." [Palomares, Manuel and David Poveda.  Text & Talk: An Interdisciplinary Journal of Language, Discourse and Communication Studies 30 (January 2010): 193-212]

2.  Adds substance to a literary, provocative, or imaginative title or quote , e.g., "Listen to What I Say, Not How I Vote": Congressional Support for the President in Washington and at Home." [Grose, Christian R. and Keesha M. Middlemass. Social Science Quarterly 91 (March 2010): 143-167]

3.  Qualifies the geographic scope of the research , e.g., "The Geopolitics of the Eastern Border of the European Union: The Case of Romania-Moldova-Ukraine." [Marcu, Silvia. Geopolitics 14 (August 2009): 409-432]

4.  Qualifies the temporal scope of the research , e.g., "A Comparison of the Progressive Era and the Depression Years: Societal Influences on Predictions of the Future of the Library, 1895-1940." [Grossman, Hal B. Libraries & the Cultural Record 46 (2011): 102-128]

5.  Focuses on investigating the ideas, theories, or work of a particular individual , e.g., "A Deliberative Conception of Politics: How Francesco Saverio Merlino Related Anarchy and Democracy." [La Torre, Massimo. Sociologia del Diritto 28 (January 2001): 75 - 98]

6.  Identifies the methodology used , e.g. "Student Activism of the 1960s Revisited: A Multivariate Analysis Research Note." [Aron, William S. Social Forces 52 (March 1974): 408-414]

7.  Defines the overarching theoretical framework for analyzing the research problem , e.g., "Explaining Territorial Change in Federal Democracies: A Comparative Historical Institutionalist Approach." [ Tillin, Louise. Political Studies 63 (August 2015): 626-641.

With these examples in mind, think about what type of subtitle reflects the overall approach to your study. This will help the reader understand the scope of the study in relation to how it was designed to address the research problem. Keep in mind, however, that although subtitles are commonly used by scholars, they are not required.

Anstey, A. “Writing Style: What's in a Title?” British Journal of Dermatology 170 (May 2014): 1003-1004; Balch, Tucker. How to Compose a Title for Your Research Paper. Augmented Trader blog. School of Interactive Computing, Georgia Tech University; Bavdekar, Sandeep B. “Formulating the Right Title for a Research Article.” Journal of Association of Physicians of India 64 (February 2016); Choosing the Proper Research Paper Titles. AplusReports.com, 2007-2012; Eva, Kevin W. “Titles, Abstracts, and Authors.” In How to Write a Paper . George M. Hall, editor. 5th edition. (Oxford: John Wiley and Sons, 2013), pp. 33-41; Hartley James. “To Attract or to Inform: What are Titles for?” Journal of Technical Writing and Communication 35 (2005): 203-213; Huggett, Sarah. "Heading for Success: Or How Not to Title your Paper." Research Trends 1 (September 2011): 4; General Format. The Writing Lab and The OWL. Purdue University; Kerkut G.A. “Choosing a Title for a Paper.” Comparative Biochemistry and Physiology Part A: Physiology 74 (1983): 1; “Tempting Titles.” In Stylish Academic Writing . Helen Sword, editor. (Cambridge, MA: Harvard University Press, 2012), pp. 63-75; Nundy, Samiran, et al. “How to Choose a Title?” In How to Practice Academic Medicine and Publish from Developing Countries? A Practical Guide . Edited by Samiran Nundy, Atul Kakar, and Zulfiqar A. Bhutta. (Springer Singapore, 2022), pp. 185-192.

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Home » Variables in Research – Definition, Types and Examples

Variables in Research – Definition, Types and Examples

Table of Contents

In research, variables are critical components that represent the characteristics or attributes being studied. They are the elements that researchers measure, control, or manipulate to observe their effects on other variables, ultimately aiming to answer research questions or test hypotheses. Variables are central to both quantitative and qualitative research, enabling scientists to gather data and draw meaningful conclusions.

Variables in Research

A variable is a characteristic, attribute, or value that can change or vary across participants, objects, or conditions within a research study. Variables allow researchers to quantify or categorize aspects of the subject under investigation, serving as the foundation for data collection and analysis. Variables may represent observable qualities like age or income, as well as abstract constructs like intelligence or satisfaction.

Key Features of Variables in Research :

• Measurability : Variables must be quantifiable or classifiable for observation.
• Variability : Variables can differ among individuals, groups, or experimental conditions.
• Relevance : Variables should align with the research objectives to ensure meaningful results.

Types of Variables in Research

Research variables are typically classified into several types based on their roles, characteristics, and nature of measurement. The primary types include independent variables , dependent variables , extraneous variables , and control variables , among others.

1. Independent Variable (IV)

Definition : An independent variable is the variable that is manipulated or controlled by the researcher to observe its effect on the dependent variable. The independent variable is often the “cause” in a cause-and-effect relationship.

Characteristics :

• Controlled or manipulated by the researcher.
• Its changes are intended to produce an effect on another variable.
• Also known as a predictor or explanatory variable.

Examples of Independent Variables :

• Treatment Type : Different types of medication or therapy administered to test their effects on patients.
• Study Hours : Number of hours spent studying in an experiment examining its impact on test scores.
• Advertising Method : Types of advertising methods used to determine their effect on consumer interest.

Example Scenario : In an experiment studying the effect of sleep on cognitive performance, the amount of sleep (e.g., 4, 6, or 8 hours) is the independent variable, as it is controlled by the researcher to observe its impact on cognitive performance.

2. Dependent Variable (DV)

Definition : The dependent variable is the outcome or effect that is measured in response to changes in the independent variable. It is the “effect” in a cause-and-effect relationship and is influenced by the independent variable.

• Dependent on the independent variable.
• Also known as the outcome or response variable.
• Changes in the dependent variable are observed to determine the effect of the independent variable.

Examples of Dependent Variables :

• Test Scores : Used to measure the impact of study hours (IV) on academic performance.
• Blood Pressure : Measured to observe the effects of different medications (IV) on blood pressure levels.
• Sales Volume : Analyzed to determine the impact of advertising methods (IV) on sales.

Example Scenario : In a study examining the impact of exercise on weight loss, weight loss is the dependent variable because it is expected to change in response to different levels or types of exercise (independent variable).

3. Extraneous Variable

Definition : Extraneous variables are additional variables that are not the main focus of a study but could influence the relationship between the independent and dependent variables if not controlled. They can introduce bias and affect the study’s internal validity.

• Not directly related to the hypothesis.
• Can potentially impact the dependent variable if not controlled.
• Should be minimized or controlled to prevent interference.

Examples of Extraneous Variables :

• Room Temperature : In an experiment on cognitive performance, variations in room temperature could influence participants’ concentration levels.
• Participant Mood : In a study examining the effects of a new teaching method, a participant’s mood could influence their engagement and performance.
• Time of Day : In research on reaction times, the time of day may affect participant alertness and thus reaction speed.

Example Scenario : In a study testing the effect of a new diet on weight loss, extraneous variables such as participants’ exercise habits or stress levels could impact the outcome, potentially confounding the relationship between the diet (IV) and weight loss (DV).

4. Control Variable

Definition : Control variables are variables that are intentionally kept constant or controlled throughout a study to ensure that they do not influence the dependent variable. By controlling these variables, researchers isolate the effects of the independent variable on the dependent variable.

• Remain constant across all conditions.
• Ensure that changes in the dependent variable are due to the independent variable alone.
• Increase the reliability of the results by reducing potential confounding factors.

Examples of Control Variables :

• Room Lighting : Keeping lighting constant in an experiment on reading comprehension.
• Equipment Type : Using the same equipment across experimental conditions to ensure consistency.
• Participant Age Range : Keeping the age range of participants within a specific bracket to control for age-related effects.

Example Scenario : In an experiment studying the effect of study methods on test scores, controlling the time of day the test is taken would help to ensure that test performance is not influenced by participant alertness at different times.

5. Moderator Variable

Definition : A moderator variable is a variable that affects the strength or direction of the relationship between the independent and dependent variables. It reveals how the relationship between variables changes under different conditions.

• Influences the relationship between IV and DV without being directly manipulated.
• Helps identify for whom or under what conditions an effect is strongest.
• Used to understand context-dependent effects.

Examples of Moderator Variables :

• Age : In a study on exercise and mental health, age may moderate the effect, with exercise benefiting younger adults more than older ones.
• Income Level : In research on education and career success, income level may moderate the relationship by impacting access to resources.
• Social Support : In a study on stress and job performance, social support may strengthen or weaken the impact of stress.

Example Scenario : In a study examining the effect of workload on job satisfaction, social support might act as a moderator variable. High social support could weaken the negative impact of workload on job satisfaction, while low support could intensify it.

6. Mediator Variable

Definition : A mediator variable explains the process through which the independent variable influences the dependent variable. It acts as a “middle link” in the causal chain, showing how or why an effect occurs.

• Provides insight into the mechanism of an effect.
• Positioned between the IV and DV in the causal pathway.
• Identified through statistical analysis to explain mediation effects.

Examples of Mediator Variables :

• Job Satisfaction : In a study on salary and employee retention, job satisfaction may mediate the relationship, as higher salary might improve satisfaction, leading to higher retention.
• Stress Levels : In research on workload and health outcomes, stress may mediate the relationship, with higher workload leading to increased stress, which in turn affects health.
• Self-Efficacy : In a study on training and job performance, self-efficacy may act as a mediator by showing how training improves confidence, which leads to better performance.

Example Scenario : In a study examining the impact of education level on career success, self-confidence could act as a mediator. Higher education might boost self-confidence, which in turn leads to greater career success.

Examples of Variables in Real Research

• Independent Variable : Type of teaching method.
• Dependent Variable : Student test scores.
• Control Variable : Class size and subject matter.
• Moderator Variable : Student motivation level.
• Independent Variable : Dosage of medication.
• Dependent Variable : Patient blood pressure.
• Extraneous Variable : Patient diet and exercise habits.
• Control Variable : Administration time.
• Independent Variable : Sleep duration.
• Dependent Variable : Cognitive performance.
• Mediator Variable : Alertness levels.
• Moderator Variable : Participant age.

Variables are fundamental elements of research, serving as the building blocks for hypotheses, measurements, and analyses. By understanding different types of variables—including independent, dependent, control, extraneous, moderator, and mediator variables—researchers can design studies that accurately capture the effects and relationships they aim to explore. Proper use of variables enhances the reliability and validity of findings, leading to more meaningful contributions to scientific knowledge.

• Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . SAGE Publications.
• Trochim, W. M., & Donnelly, J. P. (2008). The Research Methods Knowledge Base . Cengage Learning.
• Babbie, E. (2016). The Practice of Social Research . Cengage Learning.
• Kerlinger, F. N., & Lee, H. B. (2000). Foundations of Behavioral Research . Harcourt College Publishers.
• Punch, K. F. (2013). Introduction to Social Research: Quantitative and Qualitative Approaches . SAGE Publications.

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• Types of Variables in Research | Definitions & Examples

Types of Variables in Research | Definitions & Examples

Published on 19 September 2022 by Rebecca Bevans . Revised on 28 November 2022.

In statistical research, a variable is defined as an attribute of an object of study. Choosing which variables to measure is central to good experimental design .

You need to know which types of variables you are working with in order to choose appropriate statistical tests and interpret the results of your study.

You can usually identify the type of variable by asking two questions:

• What type of data does the variable contain?
• What part of the experiment does the variable represent?

Table of contents

Types of data: quantitative vs categorical variables, parts of the experiment: independent vs dependent variables, other common types of variables, frequently asked questions about variables.

Data is a specific measurement of a variable – it is the value you record in your data sheet. Data is generally divided into two categories:

• Quantitative data represents amounts.
• Categorical data represents groupings.

A variable that contains quantitative data is a quantitative variable ; a variable that contains categorical data is a categorical variable . Each of these types of variable can be broken down into further types.

Quantitative variables

When you collect quantitative data, the numbers you record represent real amounts that can be added, subtracted, divided, etc. There are two types of quantitative variables: discrete and continuous .

Categorical variables

Categorical variables represent groupings of some kind. They are sometimes recorded as numbers, but the numbers represent categories rather than actual amounts of things.

There are three types of categorical variables: binary , nominal , and ordinal variables.

*Note that sometimes a variable can work as more than one type! An ordinal variable can also be used as a quantitative variable if the scale is numeric and doesn’t need to be kept as discrete integers. For example, star ratings on product reviews are ordinal (1 to 5 stars), but the average star rating is quantitative.

Example data sheet

To keep track of your salt-tolerance experiment, you make a data sheet where you record information about the variables in the experiment, like salt addition and plant health.

To gather information about plant responses over time, you can fill out the same data sheet every few days until the end of the experiment. This example sheet is colour-coded according to the type of variable: nominal , continuous , ordinal , and binary .

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Experiments are usually designed to find out what effect one variable has on another – in our example, the effect of salt addition on plant growth.

You manipulate the independent variable (the one you think might be the cause ) and then measure the dependent variable (the one you think might be the effect ) to find out what this effect might be.

You will probably also have variables that you hold constant ( control variables ) in order to focus on your experimental treatment.

In this experiment, we have one independent and three dependent variables.

The other variables in the sheet can’t be classified as independent or dependent, but they do contain data that you will need in order to interpret your dependent and independent variables.

What about correlational research?

When you do correlational research , the terms ‘dependent’ and ‘independent’ don’t apply, because you are not trying to establish a cause-and-effect relationship.

However, there might be cases where one variable clearly precedes the other (for example, rainfall leads to mud, rather than the other way around). In these cases, you may call the preceding variable (i.e., the rainfall) the predictor variable and the following variable (i.e., the mud) the outcome variable .

Once you have defined your independent and dependent variables and determined whether they are categorical or quantitative, you will be able to choose the correct statistical test .

But there are many other ways of describing variables that help with interpreting your results. Some useful types of variable are listed below.

A confounding variable is closely related to both the independent and dependent variables in a study. An independent variable represents the supposed cause , while the dependent variable is the supposed effect . A confounding variable is a third variable that influences both the independent and dependent variables.

Failing to account for confounding variables can cause you to wrongly estimate the relationship between your independent and dependent variables.

Discrete and continuous variables are two types of quantitative variables :

• Discrete variables represent counts (e.g., the number of objects in a collection).
• Continuous variables represent measurable amounts (e.g., water volume or weight).

You can think of independent and dependent variables in terms of cause and effect: an independent variable is the variable you think is the cause , while a dependent variable is the effect .

In an experiment, you manipulate the independent variable and measure the outcome in the dependent variable. For example, in an experiment about the effect of nutrients on crop growth:

• The  independent variable  is the amount of nutrients added to the crop field.
• The  dependent variable is the biomass of the crops at harvest time.

Defining your variables, and deciding how you will manipulate and measure them, is an important part of experimental design .

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