change experiment definition

What Is Behavior Change in Psychology? 5 Models and Theories

Can the answer to this question help us change our less desirable behaviors?

Changing less desirable behaviors can help individuals, communities, and our environment.

However, behaviors can be highly ingrained and become habits we perform automatically without thinking. This poses a significant challenge to changing these behaviors.

To design effective interventions with which to change behavior, it is useful to understand the theories and models of behavior change.

This article will cover the leading theories and models, as well as an interesting study and some simple techniques to help your clients change their behavior.

Before you continue, we thought you might like to download our three Goal Achievement Exercises for free . These detailed, science-based exercises will help you or your clients create actionable goals and master techniques to create lasting behavior change.

This Article Contains:

What is behavioral change 14 examples, 2 psychology theories about changing behavior, 3 scientific models and frameworks explained, behavior change research: a fascinating study, why is behavioral change difficult, how to elicit behavior change: 4 techniques, helpful resources from positivepsychology.com, a take-home message.

Behavioral change is about altering habits and behaviors for the long term. The majority of research around health-related behaviors (Davis, Campbell, Hildon, Hobbs, & Michie, 2015) indicates that small changes can lead to enormous improvements in people’s health and life expectancy. These changes can have knock-on effects on the health of others (Swann et al., 2010).

Examples include:

• Smoking cessation
• Reducing alcohol intake
• Eating healthily
• Exercising regularly
• Practicing safe sex
• Driving safely

Other behaviors that are the target of change interventions are those affecting the environment, for example:

• Leaving lights on
• Not recycling

Some behavior changes may be related to improving wellbeing, such as

• Reducing procrastination
• Incorporating regular self-care activities
• Being more assertive at work
• Going to bed earlier
• Practicing mindfulness

These are just a few examples of behavior changes that many have tried at some time in their lives. Some changes may be easy, but others prove quite challenging.

In a literature review by Davis et al. (2015), researchers identified 82 theories of behavior change applicable to individuals. We will discuss the most frequently occurring theories and models in this article.

The theory of planned behavior/reasoned action

Fishbein and Ajzen developed the theory of reasoned action in the 1970s. This theory posits that behaviors occur because of intention, and intention is influenced by personal attitude and the perceived social norm (Madden, Ellen, & Ajzen, 1992).

This means that the more positive a person’s attitude toward changing their behavior and the more others are doing the desired behavior or supporting the behavior change, the stronger the person’s intention to change their behavior will be and the more likely they are to successfully change it.

In the 1980s, Ajzen extended this model to incorporate perceived behavioral control as an influencer of intention and sometimes as a direct influence on behavior (Madden et al., 1992).

Perceived behavioral control is a person’s confidence in their capability to perform the behavior and whether they believe they can overcome barriers and challenges. This extended model is known as the theory of planned behavior  and accounts for more variation in behavior change than the theory of reasoned action (Madden et al., 1992).

The theories of planned behavior/reasoned action

The image above, adapted from Madden et al. (1992), shows the theory of reasoned action in gray and the addition of perceived behavioral control in brown to create the theory of planned behavior.

Here is a useful YouTube explanation of the theory of planned behavior.

Social cognitive theory

The social cognitive theory, proposed by Bandura in 1986, is an expansion of his earlier social learning theory, in which he states that many behaviors are learned by observing others in our social environment (Bandura, 1999).

For us to adopt a behavior, we have to pay attention to the behavior being modeled, remember it, and reproduce it. We may be rewarded for this, which reinforces the behavior, or punished, which reduces the likelihood we will do it again. However, Bandura acknowledged that there is more to adopting a behavior than this.

He expanded his theory to include personal factors of the individual: cognitive, affective, and biological. This includes an individual’s personal resources and abilities, their perceived self-efficacy (capability of performing the behavior), their expectations of the costs and benefits of changing their behavior, and the perceived barriers and opportunities that may help or hinder them.

Bandura emphasizes that we are the agents of our own development and change, and our perceived self-efficacy and outcome expectations play an important role in determining our actions . Our social surroundings can aid or inhibit our goals by providing opportunities or imposing restrictions, which in turn can affect our perceived self-efficacy and outcome expectations for next time (Bandura, 1999).

A model of this theory is shown below, highlighting a bidirectional relationship between an individual’s personal factors, the environment, and their behavior, with each factor influencing the others.

Social cognitive theory model

YouTube has this good summary video on Bandura’s social cognitive theory.

Theories can be used to build models and frameworks that have more practical applications and can be used to develop interventions. Three frequently occurring models are explained below.

Transtheoretical model

Otherwise known as the stages of change , this is the most frequently occurring model in the literature. The transtheoretical model was developed by Prochaska and DiClemente in the late ’70s and suggests six stages of behavior change (Prochaska, 1979; Prochaska & DiClemente, 1982).

Identifying the stage an individual is in helps health professionals, coaches, and therapists provide targeted interventions for that stage.

The six stages of change are:

• Precontemplation The individual is not intending to change their behavior. They may be uninformed about the consequences of their behavior or lack confidence in their ability to change, sometimes because of previous failed attempts.
• Contemplation The individual is intending to change their behavior within the next six months. They can see the benefits of making a change but are also very aware of the disadvantages and challenges, which can keep them stuck in this stage.
• Preparation The individual is planning to change their behavior within the next month. They have usually taken some steps already, such as joining a support group, buying a self-help book, finding a coach etc., and have some form of plan in place.
• Action The individual has made significant changes to their behavior within the last six months, which has led to a different outcome in their health and/or wellbeing.
• Maintenance The individual continues to change their behavior enough to prevent relapse but is not putting as much time and effort into this as in the action stage.NOTE: Relapse can occur at any stage up to and including this one, going back to any of the earlier stages in the model. People most frequently return to contemplation or preparation for another attempt at changing their behavior (Prochaska & Velicer, 1997).
• Termination The individual is no longer tempted to use their old behavior as a coping method and feels confident in their ability to keep this change. Many people will struggle to reach this end state.

The transtheoretical model/stages of change

Here is a short YouTube animation about the transtheoretical model of change.

Information–motivation–behavioral skills model

This model was designed by Fisher and Fisher (1992) after reviewing the literature on changing AIDS-risk behavior. They propose three key factors that influence behavior change:

• Information about the behavior
• Motivation to perform the behavior
• Behavioral skills to perform the behavior

Information includes automatic thoughts about a behavior as well as consciously learned information. Motivation includes both personal motivation , the desire to change behavior for oneself, and social motivation, the desire to change behavior to fit into the social environment.

Information and motivation influence behavioral skills, which include objective skills and perceived self-efficacy. The combination of information, motivation, and behavioral skills influences behavior change (see image below).

As a helping professional, increasing the amount of information your client has, helping them find their motivation, or increasing their objective behavioral skills or perceived self-efficacy could help them change their behavior.

The information–motivation–behavioral skills model (Fisher & Fisher, 1992)

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Behavior change wheel & COM-B model

In 2011, Michie, van Stralen, and West pulled together different behavior change frameworks to create a behavior change wheel. The aim of this was to provide guidance for policy makers and those performing behavioral interventions, based on the existing evidence.

The behavior change wheel from Michie et al. (2011)

The hub of this wheel, the most relevant part for us, involves three conditions: capability, opportunity, and motivation.

• Capability includes both physical and psychological ability to perform the behavior, including having the necessary knowledge and skills.
• Opportunity is about the environment around the individual, which either facilitates or inhibits a behavior.
• Motivation is the drive and energy to perform a behavior, including habits, emotions, and thoughts.

These components have been put together to form the COM-B model, where opportunity and capability influence motivation, and all three factors influence behavior. Improving any of these areas could help your client change their behavior.

COM-B model (Michie et al., 2011)

They wanted to see if interventions to promote sustainable behaviors were more likely to induce behavior change in people who had recently moved.

They studied 800 participants, half of whom had moved within the previous six months. The other half lived in the same areas and were matched for home ownership, house size, access to public transport, and recycling facilities, but had not recently moved.

The researchers gave an intervention on sustainable behaviors to half of the movers and half of the non-movers, and compared self-report data on behaviors before and after the intervention.

After accounting for environmental values, past behavior, habit strength, intentions, perceived control, personal norms, and involvement, they found that the intervention had the strongest effect on the self-reported sustainable behaviors of those who had recently moved within the last three months, termed the “window of opportunity.”

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The process of change can seem daunting, and many people find it difficult. It is important to remember that change is a process and not a one-off event. It can be difficult to make large changes in one step, but breaking up a large goal into smaller parts takes planning and commitment.

It’s challenging to stay motivated if the reward for behavior change seems far off in the future or is vague; for example, exercising more to reduce risk of heart disease in older age.

If there are no immediate rewards for changing a behavior, or if there are immediate costs, such as nicotine cravings when quitting smoking, this can make it difficult to stay motivated. This is why it is helpful to identify these issues in advance and create plans for when they occur.

As described in the theories and models above, there are many elements at play that determine how successful a behavior change will be. Having the intention does not necessarily translate into the behavior (Gollwitzer, 1999). A meta-analysis by Webb and Sheeran (2006) found that a medium-to-large change in intention leads to a small-to-medium change in behavior, known as the intention–behavior gap.

Factors that help with behavior change include the following (Gollwitzer, 1999):

• Goals should be as specific as possible, not vague.
• The goal should be in the immediate rather than the distant future.
• The reason for a behavior change should be for positive gain rather than the loss of a negative.
• The reason for behavior change should be for learning rather than for performance/achievement.

Change is difficult, and you will probably face setbacks during your progress. Habits are easy and helpful in freeing up resources by making small decisions and non-decisions. Disrupting habits requires removing triggers, inhibiting automated responses, and replacing habituated responses with more adaptable, positive behaviors (Orbell & Verplanken, 2020).

As this quote suggests, genuine change comes from within ourselves when we are willing to change our behavior.

Motivation and resilience are important factors in initiating change, overcoming resistance, and remaining determined. It is helpful to identify the psychological capital available to you to support you along the journey of behavioral change. Several approaches aim to help you change your habits.

Planning and goal setting are proven methods in mental health interventions for behavioral change (Keyworth et al., 2020).

Goal definition, e.g., SMART Goals, can effectively motivate and guide toward goal achievement (Kremer, Moran, & Kearney, 2019).

To achieve goals in the long run, it is important to establish new good habits and undo existing bad habits (Clear, 2018).

One way to adopt new habits can be by changing your environment. If you, for example, want to do more sports to become healthier and fitter, you can prepare before going to bed by arranging your sports clothes or other necessities.

Self-tracking and self-contracts are valuable tools to promote the development of habits. Monitoring your progress helps to centralize goal-relevant activities and keeps resources mobilized to remain committed (Locke & Latham, 2002).

If we want to change something in our lives, we will probably adjust how we behave. Otherwise, we will get more of the same. Nonetheless, we want to stress that you should also be grateful for your prior transformations and proud of current, positive behavior patterns.

Here are some examples:

Implementation intentions

An implementation intention links a particular behavior to a specific situation: “If X happens, then I will do Y.” This means that if a specific situation occurs, the thinking process automatically reminds a person of the particular behavior they intended to apply.

It is a way to create new habits and has been effective in a multitude of situations (Gollwitzer, 1999). An example might be telling yourself, “If I see the lights on in an empty room, I will switch them off.” This means you are more likely to notice this situation and do something about it when it arises.

Motivational interviewing

Motivational interviewing helps individuals gain clarity in their thoughts and motivations for change, and identifies barriers to change so that solutions can be considered. This is known as change talk .

Motivational interviewing is a process of guiding rather than directing, helping a client to identify their strengths and goals, and improving their sense of self-efficacy and autonomy.

This approach is particularly useful in those who are reluctant or ambivalent about changing their behavior and outperforms traditional advice giving in helping clients to change their behavior (Rubak, Sandboek, Lauritzen, & Christensen, 2005).

Get inspired by TED talks

There are many fantastic TED talks on behavior change. Here are two examples.

In this wonderful talk, behavioral neuroscientist Tali Sharot explains why the common method used to promote behavior change – threatening people with the risks of continuing as they are – does not work: “Fear induces inaction, whereas the thrill of a gain induces action.”

She suggests that three key factors are important in changing our behavior:

• Social incentives
• Immediate reward
• Progress monitoring

In this nine-minute talk, American psychiatrist, neuroscientist, and author Judson Brewer suggests that mindfulness can be a useful method in behavior change. He invites us to notice our urge toward a certain behavior, be curious about why we have the urge, and decide whether the behavior is truly rewarding or whether we can let it go.

• Notice the urge.
• Get curious.
• Feel the joy in letting go.

On our site, we have several resources that are invaluable for implementing behavior changes. To help, check out some of the following:

• Abstraction Worksheet This worksheet presents three simple prompts to help clients clearly define and illustrate a desired behavior change and its consequences.
• Motivational Interviewing: Querying Extremes Worksheet This worksheet helps clients systematically explore possible negative consequences of continuing with a current behavior and possible positive consequences of changing their behavior.
• Reward Replacement Worksheet This worksheet helps clients identify the negative consequences of behaviors they use to reward themselves and select different reward behaviors with positive consequences to replace them.
• Motivational Interviewing Worksheets These worksheets present a series of motivational interviewing questions according to the DARN Acronym , which stands for Desires , Ability , Reasons , and Need .

If you’re looking for more science-based ways to help others reach their goals, this collection contains 17 validated motivation & goals-achievement tools for practitioners. Use them to help others turn their dreams into reality by applying the latest science-based behavioral change techniques.

17 Tools To Increase Motivation and Goal Achievement

These 17 Motivation & Goal Achievement Exercises [PDF] contain all you need to help others set meaningful goals, increase self-drive, and experience greater accomplishment and life satisfaction.

Created by Experts. 100% Science-based.

If your aim is to design interventions that are effective in helping clients change their behavior, then understanding the theories and models of behavior change is a useful first step.

Behavior change is more complicated than having the knowledge or even the right intentions to behave a certain way. There are so many factors at play, including an individual’s beliefs about their capabilities and barriers, as well as environmental factors, such as social norms.

We hope that this article gave you the guidance, inspiration, techniques, and resources you need to help your clients implement change. Don’t forget to download our three Goal Achievement Exercises for free .

• Bandura, A. (1999). Social cognitive theory: An agentic perspective. Asian Journal of Social Psychology , 2 (1), 21–41.
• Clear, J. (2018). How To Start New Habits That Actually Stick. Retrieved from https://jamesclear.com/three-steps-habit-change.
• Davis, R., Campbell, R., Hildon, Z., Hobbs, L., & Michie, S. (2015). Theories of behaviour and behaviour change across the social and behavioural sciences: A scoping review. Health Psychology Review , 9 (3), 323–344.
• Fisher, J. D., & Fisher, W. A. (1992). Changing AIDS-risk behavior. Psychological Bulletin , 111 (3), 455–474.
• Gollwitzer, P. M. (1999). Implementation intentions: Strong effects of simple plans. American Psychologist , 54 (7), 493–503.
• Keyworth, C., Epton, T., Goldthorpe, J., Calam, R., & Armitage, C. J. (2020). Delivering opportunistic behavior change interventions: a systematic review of systematic reviews. Prevention Science, 21(3) , 319-331.
• Kremer, J., Moran, A. P., & Kearney, C. J. (2019). Pure sport: Sport psychology in action . Routledge.
• Locke, E. A., & Latham, G. P. (2002). Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. American Psychologist, 57(9) , 705.
• Madden, T. J., Ellen, P. S., & Ajzen, I. (1992). A comparison of the theory of planned behavior and the theory of reasoned action. Personality and Social Psychology Bulletin , 18 (1), 3–9.
• Michie, S., van Stralen, M. M., & West, R. (2011). The behaviour change wheel: A new method for characterising and designing behaviour change interventions. Implementation Science , 6 , 42.
• Orbell, S., & Verplanken, B. (2020). 13 Changing behavior using habit theory. The handbook of behavior change, 178 .
• Prochaska, J. O. (1979). Systems of psychotherapy: A transtheoretical analysis. Dorsey Press.
• Prochaska, J. O., & DiClemente, C. C. (1982). Transtheoretical therapy: Toward a more integrative model of change.  Psychotherapy: Theory, research & practice ,  19 (3), 276-288.
• Rubak, S., Sandboek, A., Lauritzen, T., & Christensen, B. (2005). Motivational interviewing: A systematic review and meta-analysis. British Journal of General Practice , 55 (513), 305–312.
• Swann, C., Carmona, C., Ryan, M., Raynor, M., Baris, E., Dunsdon, S., & Kelly, M. P. (2010). Health systems and health-related behaviour change: A review of primary and secondary evidence. National Institute for Health and Clinical Excellence.
• Verplanken, B., & Roy, D. (2016). Empowering interventions to promote sustainable lifestyles: Testing the habit discontinuity hypothesis in a field experiment. Journal of Environmental Psychology , 45 , 127–134.
• Webb, T. L., & Sheeran, P. (2006). Does changing behavioral intentions engender behavior change? A meta-analysis of the experimental evidence. Psychological Bulletin , 132 (2), 249–268.

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Hi, This article is very informative and will be useful for my studies to highlight and annotate – is it possible to request a PDF of this article as when I’ve tried to print it from the webpage some of the writing is cut off. Kind Regards, Sarah

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Hi Nicole, I am a teacher trainer and wanted to know if these theories will work for teachers, who will be implementing a programme with the goal of building joyful reading habits in primary school children using storybooks.

Absolutely! These theories, such as the Theory of Planned Behavior highlight how understanding intentions, social influences, and self-confidence can help shape positive reading habits. By incorporating these insights into your program, you can create an engaging environment that encourages children to embrace reading joyfully.

Very detailed and intelligent article

This article is really doing great work. Concerning with my course unit of Behavioural Change, as a Psychology student. A sum of Applaud to the author

Very helpful article, thank you.

TTM was actually developed in the late 70’s by Prochaska and DiClemente, not 1997 or the individual that you sited in this article. I’m currently doing research on that model for a graduate course and came across your article. Here is a site from Boston University with some great details about the model

https://sphweb.bumc.bu.edu/otlt/mph-modules/sb/behavioralchangetheories/BehavioralChangeTheories_print.html

Hi Darlene,

Whoops! Thanks for picking up this mistake and for the helpful reference.

We’ve corrected this now in the post 🙂

– Nicole | Community Manager

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Independent Variables in Psychology

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• Identifying

Potential Pitfalls

The independent variable (IV) in psychology is the characteristic of an experiment that is manipulated or changed by researchers, not by other variables in the experiment.

For example, in an experiment looking at the effects of studying on test scores, studying would be the independent variable. Researchers are trying to determine if changes to the independent variable (studying) result in significant changes to the dependent variable (the test results).

In general, experiments have these three types of variables: independent, dependent, and controlled.

Identifying the Independent Variable

If you are having trouble identifying the independent variables of an experiment, there are some questions that may help:

• Is the variable one that is being manipulated by the experimenters?
• Are researchers trying to identify how the variable influences another variable?
• Is the variable something that cannot be changed but that is not dependent on other variables in the experiment?

Researchers are interested in investigating the effects of the independent variable on other variables, which are known as dependent variables (DV). The independent variable is one that the researchers either manipulate (such as the amount of something) or that already exists but is not dependent upon other variables (such as the age of the participants).

Below are the key differences when looking at an independent variable vs. dependent variable.

Expected to influence the dependent variable

Doesn't change as a result of the experiment

Can be manipulated by researchers in order to study the dependent variable

Expected to be affected by the independent variable

Expected to change as a result of the experiment

Not manipulated by researchers; its changes occur as a result of the independent variable

There can be all different types of independent variables. The independent variables in a particular experiment all depend on the hypothesis and what the experimenters are investigating.

Independent variables also have different levels. In some experiments, there may only be one level of an IV. In other cases, multiple levels of the IV may be used to look at the range of effects that the variable may have.

In an experiment on the effects of the type of diet on weight loss, for example, researchers might look at several different types of diet. Each type of diet that the experimenters look at would be a different level of the independent variable while weight loss would always be the dependent variable.

To understand this concept, it's helpful to take a look at the independent variable in research examples.

In Organizations

A researcher wants to determine if the color of an office has any effect on worker productivity. In an experiment, one group of workers performs a task in a yellow room while another performs the same task in a blue room. In this example, the color of the office is the independent variable.

In the Workplace

A business wants to determine if giving employees more control over how to do their work leads to increased job satisfaction. In an experiment, one group of workers is given a great deal of input in how they perform their work, while the other group is not. The amount of input the workers have over their work is the independent variable in this example.

In Educational Research

Educators are interested in whether participating in after-school math tutoring can increase scores on standardized math exams. In an experiment, one group of students attends an after-school tutoring session twice a week while another group of students does not receive this additional assistance. In this case, participation in after-school math tutoring is the independent variable.

In Mental Health Research

Researchers want to determine if a new type of treatment will lead to a reduction in anxiety for patients living with social phobia. In an experiment, some volunteers receive the new treatment, another group receives a different treatment, and a third group receives no treatment. The independent variable in this example is the type of therapy .

Sometimes varying the independent variables will result in changes in the dependent variables. In other cases, researchers might find that changes in the independent variables have no effect on the variables that are being measured.

At the outset of an experiment, it is important for researchers to operationally define the independent variable. An operational definition describes exactly what the independent variable is and how it is measured. Doing this helps ensure that the experiments know exactly what they are looking at or manipulating, allowing them to measure it and determine if it is the IV that is causing changes in the DV.

Choosing an Independent Variable

If you are designing an experiment, here are a few tips for choosing an independent variable (or variables):

• Select independent variables that you think will cause changes in another variable. Come up with a hypothesis for what you expect to happen.
• Look at other experiments for examples and identify different types of independent variables.
• Keep your control group and experimental groups similar in other characteristics, but vary only the treatment they receive in terms of the independent variable.   For example, your control group will receive either no treatment or no changes in the independent variable while your experimental group will receive the treatment or a different level of the independent variable.

It is also important to be aware that there may be other variables that might influence the results of an experiment. Two other kinds of variables that might influence the outcome include:

• Extraneous variables : These are variables that might affect the relationships between the independent variable and the dependent variable; experimenters usually try to identify and control for these variables. 
• Confounding variables : When an extraneous variable cannot be controlled for in an experiment, it is known as a confounding variable . 

Extraneous variables can also include demand characteristics (which are clues about how the participants should respond) and experimenter effects (which is when the researchers accidentally provide clues about how a participant will respond).

Kaliyadan F, Kulkarni V. Types of variables, descriptive statistics, and sample size .  Indian Dermatol Online J . 2019;10(1):82-86. doi:10.4103/idoj.IDOJ_468_18

Weiten, W. Psychology: Themes and Variations, 10th ed . Boston, MA: Cengage Learning; 2017.

National Library of Medicine. Dependent and independent variables .

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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Examples Of Physical Change

What is a physical change? Learn to identify a physical change vs. a chemical change with a simple physical change definition and everyday examples of physical change. Explore physical changes with easy, hands-on science experiments kids will love. Fun science project ideas for all ages of kids!

What Is A Physical Change?

Physical changes are changes that occur in matter without changing its chemical composition. In other words, the atoms and molecules that make up the matter stay the same; no new substance is formed . But there is a change in the appearance or physical properties of the substance.

Physical properties include:

• Temperature

For Example…

Crushing an aluminum can: The aluminum can is still made of the same atoms and molecules, but its size has changed.

Tearing paper: The paper is still made of the same atoms and molecules, but its size and shape have changed.

Freezing water: When water freezes, its appearance changes from a liquid to a solid, but its chemical composition remains the same.

Dissolving sugar in water: The sugar and water are still made of the same atoms and molecules, but their appearance has changed.

Understanding physical changes is important for many fields, such as physics , engineering , and materials science. It helps us understand how matter behaves and how to manipulate it.

Physical vs. Chemical Change

Physical changes differ from chemical changes or chemical reactions, which occur when the substances are changed into one or more new substances. A chemical change is a change in the chemical composition of the matter. In contrast, a physical change isn’t! Learn more about chemical change.

For example, when wood burns, it undergoes a chemical change and turns into a different substance, ash, which has different atoms and molecules from the original wood.

However, if a piece of wood is chopped up into smaller pieces, it undergoes a physical change. The wood looks different, but has the same substance as the original wood. Learn more about physical change.

💡 SUGGESTION: Fun Chemical Reaction Experiments

Physical changes are often reversible, especially if they are phase changes. Examples of phase changes are melting (changing from a solid to a liquid), freezing (changing from a liquid to a solid), evaporation (changing from a liquid to a gas), and condensation (changing from a gas to a liquid).

A great question for kids to ask is… Can this change be reversed or not?

Many physical changes are reversible . However, some physical changes are not easy to reverse! Think about what happens when you shred a piece of paper! While you haven’t created a new substance, the change is irreversible. Chemical changes typically are irreversible .

Everyday Examples Of Physical Change

Here are 20 everyday physical change examples. Can you think of any more?

• Boiling a cup of water
• Adding milk to cereal
• Boiling pasta to make it soft
• Munching on candy
• Chopping vegetables into smaller pieces
• Grating an apple
• Melting cheese
• Slicing a loaf of bread
• Washing clothes
• Sharpening a pencil
• Using an eraser
• Crushing a box to put in the trash
• Steam condensing on the mirror from a hot shower
• Ice on the car window on a cold morning
• Mowing the lawn
• Drying clothing in the sun
• A puddle of water drying up
• Trimming trees
• Adding salt to a pool

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Physical Change Experiments

Try one or more of these easy physical change experiments you can do at home or in the classroom. What physical changes can you observe? For some of these experiments, there may be more than one.

Crushed Can Experiment

Observe how changes in atmospheric pressure can crush a can. A fun and easy experiment to try!

Dissolving Candy

Add candy to water for a fun, colorful physical change. Also, investigate what happens when you add candy to other common household liquids.

Freezing Water Experiment

Learn about the freezing point of water and what kind of physical change happens when you add salt to water and freeze it.

Ivory Soap Experiment

What happens to ivory soap when you heat it in the microwave? Observe a cool physical change in action!

Making Paper

Make these paper Earths from old bits of paper. The appearance of the paper changes with this easy recycling paper project.

Making Soap

Not only is making soap from a melt and pour glycerin base a fun example of physical change, you also end up with a cool surprise at the end.

Melting Ice Experiment

What makes ice melt faster? 3 fun experiments to investigate what speeds up the process of ice changing from a solid to a liquid.

Melting Crayons

Turn a box of broken and worn down bits of crayon into new crayons with a fun example of physical change. Follow our step by step instructions to melt the crayons, and make them into new crayons.

Paper Towel Art

What kind of physical change do you get when you add water and ink to a paper towel? This also makes for a fun and easy STEAM (Science + Art) activity.

For another “arty” example of physical change, try salt painting !

Popcorn In A Bag

Science you can eat! Make up some popcorn in a bag, and find out what type of physical change makes popcorn pop.

Rainbow In A Jar

How does adding sugar to water cause a physical change? It changes the density of the liquid. See it in action with this colorful layered density tower.

Separating Mixtures

Explore using different physical methods to isolate the components of a substance based on their physical properties.

Salt Water Density Experiment

Similarly, explore how adding salt to water changes the physical properties of the water. Test it out by floating an egg.

Skittles Experiment

Use your skittles candy and water for this classic   skittles science experiment that everyone has to try! Why don’t the skittles colors mix?

Solid, Liquid, Gas Experiment

A simple science experiment that is great for younger kiddos. Observe how ice becomes a liquid and then a gas.

What Absorbs Water

A simple experiment for your preschoolers! Grab some materials and objects, and investigate what absorbs water and what doesn’t. Physical changes you may notice; changes in volume, texture (wet or dry), size, color.

Compare how fast different everyday items melt in the sun, including ice cubes. A fun experiment to do in the summer!

Physical Change Experiments That Look Like Chemical Reactions

The science experiments below are all examples of physical change. While, at first, you might think a chemical reaction has occurred, all that fizzing action is a physical change!

Dancing Raisins

While it might appear that a chemical change is occurring, a new substance is not formed. The carbon dioxide, which is found in the soda, creates the movement of the raisins.

Diet Coke and Mentos

Adding Mentos candy to Diet coke or soda makes for the best explosion! It is all to do with a physical change! Check out our Mentos and soda version for younger kids as well.

Pop Rocks and Soda

Mix Pop rocks and soda together for a frothy, fizzing physical change that can blow up a balloon.

More Helpful Science Resources

Here are a few resources to help you introduce science more effectively to your kiddos or students and feel confident when presenting materials. You’ll find helpful free printables throughout.

• Best Science Practices (as it relates to the scientific method)
• Science Vocab
• 8 Science Books for Kids
• What Is A Scientist
• Science Supplies List
• Science Tools for Kids

Science Experiments By Age Group

We’ve put together a few separate resources for different age groups, but remember that many experiments will cross over and can be re-tried at several different age levels. Younger kiddos can enjoy the simplicity and hands-on fun. At the same time, you can talk back and forth about what is happening.

As kiddos get older, they can bring more complexity to the experiments, including using the scientific method , developing hypotheses, exploring variables , creating different tests, and writing conclusions from analyzing data.

• Science for Toddlers
• Science for Preschoolers
• Science for Kindergarten
• Science for Early Elementary Grades
• Science for 3rd Grade
• Science for Middle School

Printable Science Experiments Pack

If you’re looking to grab all of our printable science projects in one convenient place plus exclusive worksheets and bonuses like a STEAM Project pack, our Science Project Pack is what you need! Over 300+ Pages!

• 90+ classic science activities  with journal pages, supply lists, set up and process, and science information.  NEW! Activity-specific observation pages!
• Best science practices posters  and our original science method process folders for extra alternatives!
• Be a Collector activities pack  introduces kids to the world of making collections through the eyes of a scientist. What will they collect first?
• Know the Words Science vocabulary pack  includes flashcards, crosswords, and word searches that illuminate keywords in the experiments!
• My science journal writing prompts  explore what it means to be a scientist!!
• Bonus STEAM Project Pack:  Art meets science with doable projects!
• Bonus Quick Grab Packs for Biology, Earth Science, Chemistry, and Physics

Subscribe to receive a free 5-Day STEM Challenge Guide

~ projects to try now ~.

Independent Variables (Definition + 43 Examples)

Have you ever wondered how scientists make discoveries and how researchers come to understand the world around us? A crucial tool in their kit is the concept of the independent variable, which helps them delve into the mysteries of science and everyday life.

An independent variable is a condition or factor that researchers manipulate to observe its effect on another variable, known as the dependent variable. In simpler terms, it’s like adjusting the dials and watching what happens! By changing the independent variable, scientists can see if and how it causes changes in what they are measuring or observing, helping them make connections and draw conclusions.

In this article, we’ll explore the fascinating world of independent variables, journey through their history, examine theories, and look at a variety of examples from different fields.

History of the Independent Variable

Once upon a time, in a world thirsty for understanding, people observed the stars, the seas, and everything in between, seeking to unlock the mysteries of the universe.

The story of the independent variable begins with a quest for knowledge, a journey taken by thinkers and tinkerers who wanted to explain the wonders and strangeness of the world.

Origins of the Concept

The seeds of the idea of independent variables were sown by Sir Francis Galton , an English polymath, in the 19th century. Galton wore many hats—he was a psychologist, anthropologist, meteorologist, and a statistician!

It was his diverse interests that led him to explore the relationships between different factors and their effects. Galton was curious—how did one thing lead to another, and what could be learned from these connections?

As Galton delved into the world of statistical theories , the concept of independent variables started taking shape.

He was interested in understanding how characteristics, like height and intelligence, were passed down through generations.

Galton’s work laid the foundation for later thinkers to refine and expand the concept, turning it into an invaluable tool for scientific research.

Evolution over Time

After Galton’s pioneering work, the concept of the independent variable continued to evolve and grow. Scientists and researchers from various fields adopted and adapted it, finding new ways to use it to make sense of the world.

They discovered that by manipulating one factor (the independent variable), they could observe changes in another (the dependent variable), leading to groundbreaking insights and discoveries.

Through the years, the independent variable became a cornerstone in experimental design . Researchers in fields like physics, biology, psychology, and sociology used it to test hypotheses, develop theories, and uncover the laws that govern our universe.

The idea that originated from Galton’s curiosity had bloomed into a universal key, unlocking doors to knowledge across disciplines.

Importance in Scientific Research

Today, the independent variable stands tall as a pillar of scientific research. It helps scientists and researchers ask critical questions, test their ideas, and find answers. Without independent variables, we wouldn’t have many of the advancements and understandings that we take for granted today.

The independent variable plays a starring role in experiments, helping us learn about everything from the smallest particles to the vastness of space. It helps researchers create vaccines, understand social behaviors, explore ecological systems, and even develop new technologies.

In the upcoming sections, we’ll dive deeper into what independent variables are, how they work, and how they’re used in various fields.

Together, we’ll uncover the magic of this scientific concept and see how it continues to shape our understanding of the world around us.

What is an Independent Variable?

Embarking on the captivating journey of scientific exploration requires us to grasp the essential terms and ideas. It's akin to a treasure hunter mastering the use of a map and compass.

In our adventure through the realm of independent variables, we’ll delve deeper into some fundamental concepts and definitions to help us navigate this exciting world.

Variables in Research

In the grand tapestry of research, variables are the gems that researchers seek. They’re elements, characteristics, or behaviors that can shift or vary in different circumstances.

Picture them as the myriad of ingredients in a chef’s kitchen—each variable can be adjusted or modified to create a myriad of dishes, each with a unique flavor!

Understanding variables is essential as they form the core of every scientific experiment and observational study.

Types of Variables

Independent Variable The star of our story, the independent variable, is the one that researchers change or control to study its effects. It’s like a chef experimenting with different spices to see how each one alters the taste of the soup. The independent variable is the catalyst, the initial spark that sets the wheels of research in motion.

Dependent Variable The dependent variable is the outcome we observe and measure . It’s the altered flavor of the soup that results from the chef’s culinary experiments. This variable depends on the changes made to the independent variable, hence the name!

Observing how the dependent variable reacts to changes helps scientists draw conclusions and make discoveries.

Control Variable Control variables are the unsung heroes of scientific research. They’re the constants, the elements that researchers keep the same to ensure the integrity of the experiment.

Imagine if our chef used a different type of broth each time he experimented with spices—the results would be all over the place! Control variables keep the experiment grounded and help researchers be confident in their findings.

Confounding Variables Imagine a hidden rock in a stream, changing the water’s flow in unexpected ways. Confounding variables are similar—they are external factors that can sneak into experiments and influence the outcome , adding twists to our scientific story.

These variables can blur the relationship between the independent and dependent variables, making the results of the study a bit puzzly. Detecting and controlling these hidden elements helps researchers ensure the accuracy of their findings and reach true conclusions.

There are of course other types of variables, and different ways to manipulate them called " schedules of reinforcement ," but we won't get into that too much here.

Role of the Independent Variable

Manipulation When researchers manipulate the independent variable, they are orchestrating a symphony of cause and effect. They’re adjusting the strings, the brass, the percussion, observing how each change influences the melody—the dependent variable.

This manipulation is at the heart of experimental research. It allows scientists to explore relationships, unravel patterns, and unearth the secrets hidden within the fabric of our universe.

Observation With every tweak and adjustment made to the independent variable, researchers are like seasoned detectives, observing the dependent variable for changes, collecting clues, and piecing together the puzzle.

Observing the effects and changes that occur helps them deduce relationships, formulate theories, and expand our understanding of the world. Every observation is a step towards solving the mysteries of nature and human behavior.

Identifying Independent Variables

Characteristics Identifying an independent variable in the vast landscape of research can seem daunting, but fear not! Independent variables have distinctive characteristics that make them stand out.

They’re the elements that are deliberately changed or controlled in an experiment to study their effects on the dependent variable. Recognizing these characteristics is like learning to spot footprints in the sand—it leads us to the heart of the discovery!

In Different Types of Research The world of research is diverse and varied, and the independent variable dons many guises! In the field of medicine, it might manifest as the dosage of a drug administered to patients.

In psychology, it could take the form of different learning methods applied to study memory retention. In each field, identifying the independent variable correctly is the golden key that unlocks the treasure trove of knowledge and insights.

As we forge ahead on our enlightening journey, equipped with a deeper understanding of independent variables and their roles, we’re ready to delve into the intricate theories and diverse examples that underscore their significance.

Independent Variables in Research

Now that we’re acquainted with the basic concepts and have the tools to identify independent variables, let’s dive into the fascinating ocean of theories and frameworks.

These theories are like ancient scrolls, providing guidelines and blueprints that help scientists use independent variables to uncover the secrets of the universe.

Scientific Method

What is it and How Does it Work? The scientific method is like a super-helpful treasure map that scientists use to make discoveries. It has steps we follow: asking a question, researching, guessing what will happen (that's a hypothesis!), experimenting, checking the results, figuring out what they mean, and telling everyone about it.

Our hero, the independent variable, is the compass that helps this adventure go the right way!

How Independent Variables Lead the Way In the scientific method, the independent variable is like the captain of a ship, leading everyone through unknown waters.

Scientists change this variable to see what happens and to learn new things. It’s like having a compass that points us towards uncharted lands full of knowledge!

Experimental Design

The Basics of Building Constructing an experiment is like building a castle, and the independent variable is the cornerstone. It’s carefully chosen and manipulated to see how it affects the dependent variable. Researchers also identify control and confounding variables, ensuring the castle stands strong, and the results are reliable.

Keeping Everything in Check In every experiment, maintaining control is key to finding the treasure. Scientists use control variables to keep the conditions consistent, ensuring that any changes observed are truly due to the independent variable. It’s like ensuring the castle’s foundation is solid, supporting the structure as it reaches for the sky.

Hypothesis Testing

Making Educated Guesses Before they start experimenting, scientists make educated guesses called hypotheses . It’s like predicting which X marks the spot of the treasure! It often includes the independent variable and the expected effect on the dependent variable, guiding researchers as they navigate through the experiment.

Independent Variables in the Spotlight When testing these guesses, the independent variable is the star of the show! Scientists change and watch this variable to see if their guesses were right. It helps them figure out new stuff and learn more about the world around us!

Statistical Analysis

Figuring Out Relationships After the experimenting is done, it’s time for scientists to crack the code! They use statistics to understand how the independent and dependent variables are related and to uncover the hidden stories in the data.

Experimenters have to be careful about how they determine the validity of their findings, which is why they use statistics. Something called "experimenter bias" can get in the way of having true (valid) results, because it's basically when the experimenter influences the outcome based on what they believe to be true (or what they want to be true!).

How Important are the Discoveries? Through statistical analysis, scientists determine the significance of their findings. It’s like discovering if the treasure found is made of gold or just shiny rocks. The analysis helps researchers know if the independent variable truly had an effect, contributing to the rich tapestry of scientific knowledge.

As we uncover more about how theories and frameworks use independent variables, we start to see how awesome they are in helping us learn more about the world. But we’re not done yet!

Up next, we’ll look at tons of examples to see how independent variables work their magic in different areas.

Examples of Independent Variables

Independent variables take on many forms, showcasing their versatility in a range of experiments and studies. Let’s uncover how they act as the protagonists in numerous investigations and learning quests!

Science Experiments

1) plant growth.

Consider an experiment aiming to observe the effect of varying water amounts on plant height. In this scenario, the amount of water given to the plants is the independent variable!

2) Freezing Water

Suppose we are curious about the time it takes for water to freeze at different temperatures. The temperature of the freezer becomes the independent variable as we adjust it to observe the results!

3) Light and Shadow

Have you ever observed how shadows change? In an experiment, adjusting the light angle to observe its effect on an object’s shadow makes the angle of light the independent variable!

4) Medicine Dosage

In medical studies, determining how varying medicine dosages influence a patient’s recovery is essential. Here, the dosage of the medicine administered is the independent variable!

5) Exercise and Health

Researchers might examine the impact of different exercise forms on individuals’ health. The various exercise forms constitute the independent variable in this study!

6) Sleep and Wellness

Have you pondered how the sleep duration affects your well-being the following day? In such research, the hours of sleep serve as the independent variable!

7) Learning Methods

Psychologists might investigate how diverse study methods influence test outcomes. Here, the different study methods adopted by students are the independent variable!

8) Mood and Music

Have you experienced varied emotions with different music genres? The genre of music played becomes the independent variable when researching its influence on emotions!

9) Color and Feelings

Suppose researchers are exploring how room colors affect individuals’ emotions. In this case, the room colors act as the independent variable!

Environment

10) rainfall and plant life.

Environmental scientists may study the influence of varying rainfall levels on vegetation. In this instance, the amount of rainfall is the independent variable!

11) Temperature and Animal Behavior

Examining how temperature variations affect animal behavior is fascinating. Here, the varying temperatures serve as the independent variable!

12) Pollution and Air Quality

Investigating the effects of different pollution levels on air quality is crucial. In such studies, the pollution level is the independent variable!

13) Internet Speed and Productivity

Researchers might explore how varying internet speeds impact work productivity. In this exploration, the internet speed is the independent variable!

14) Device Type and User Experience

Examining how different devices affect user experience is interesting. Here, the type of device used is the independent variable!

15) Software Version and Performance

Suppose a study aims to determine how different software versions influence system performance. The software version becomes the independent variable!

16) Teaching Style and Student Engagement

Educators might investigate the effect of varied teaching styles on student engagement. In such a study, the teaching style is the independent variable!

17) Class Size and Learning Outcome

Researchers could explore how different class sizes influence students’ learning. Here, the class size is the independent variable!

18) Homework Frequency and Academic Achievement

Examining the relationship between the frequency of homework assignments and academic success is essential. The frequency of homework becomes the independent variable!

19) Telescope Type and Celestial Observation

Astronomers might study how different telescopes affect celestial observation. In this scenario, the telescope type is the independent variable!

20) Light Pollution and Star Visibility

Investigating the influence of varying light pollution levels on star visibility is intriguing. Here, the level of light pollution is the independent variable!

21) Observation Time and Astronomical Detail

Suppose a study explores how observation duration affects the detail captured in astronomical images. The duration of observation serves as the independent variable!

22) Community Size and Social Interaction

Sociologists may examine how the size of a community influences social interactions. In this research, the community size is the independent variable!

23) Cultural Exposure and Social Tolerance

Investigating the effect of diverse cultural exposure on social tolerance is vital. Here, the level of cultural exposure is the independent variable!

24) Economic Status and Educational Attainment

Researchers could explore how different economic statuses impact educational achievements. In such studies, economic status is the independent variable!

25) Training Intensity and Athletic Performance

Sports scientists might study how varying training intensities affect athletes’ performance. In this case, the training intensity is the independent variable!

26) Equipment Type and Player Safety

Examining the relationship between different sports equipment and player safety is crucial. Here, the type of equipment used is the independent variable!

27) Team Size and Game Strategy

Suppose researchers are investigating how the size of a sports team influences game strategy. The team size becomes the independent variable!

28) Diet Type and Health Outcome

Nutritionists may explore the impact of various diets on individuals’ health. In this exploration, the type of diet followed is the independent variable!

29) Caloric Intake and Weight Change

Investigating how different caloric intakes influence weight change is essential. In such a study, the caloric intake is the independent variable!

30) Food Variety and Nutrient Absorption

Researchers could examine how consuming a variety of foods affects nutrient absorption. Here, the variety of foods consumed is the independent variable!

Real-World Examples of Independent Variables

Isn't it fantastic how independent variables play such an essential part in so many studies? But the excitement doesn't stop there!

Now, let’s explore how findings from these studies, led by independent variables, make a big splash in the real world and improve our daily lives!

Healthcare Advancements

31) treatment optimization.

By studying different medicine dosages and treatment methods as independent variables, doctors can figure out the best ways to help patients recover quicker and feel better. This leads to more effective medicines and treatment plans!

32) Lifestyle Recommendations

Researching the effects of sleep, exercise, and diet helps health experts give us advice on living healthier lives. By changing these independent variables, scientists uncover the secrets to feeling good and staying well!

Technological Innovations

33) speeding up the internet.

When scientists explore how different internet speeds affect our online activities, they’re able to develop technologies to make the internet faster and more reliable. This means smoother video calls and quicker downloads!

34) Improving User Experience

By examining how we interact with various devices and software, researchers can design technology that’s easier and more enjoyable to use. This leads to cooler gadgets and more user-friendly apps!

Educational Strategies

35) enhancing learning.

Investigating different teaching styles, class sizes, and study methods helps educators discover what makes learning fun and effective. This research shapes classrooms, teaching methods, and even homework!

36) Tailoring Student Support

By studying how students with diverse needs respond to different support strategies, educators can create personalized learning experiences. This means every student gets the help they need to succeed!

Environmental Protection

37) conserving nature.

Researching how rainfall, temperature, and pollution affect the environment helps scientists suggest ways to protect our planet. By studying these independent variables, we learn how to keep nature healthy and thriving!

38) Combating Climate Change

Scientists studying the effects of pollution and human activities on climate change are leading the way in finding solutions. By exploring these independent variables, we can develop strategies to combat climate change and protect the Earth!

Social Development

39) building stronger communities.

Sociologists studying community size, cultural exposure, and economic status help us understand what makes communities happy and united. This knowledge guides the development of policies and programs for stronger societies!

40) Promoting Equality and Tolerance

By exploring how exposure to diverse cultures affects social tolerance, researchers contribute to fostering more inclusive and harmonious societies. This helps build a world where everyone is respected and valued!

Enhancing Sports Performance

41) optimizing athlete training.

Sports scientists studying training intensity, equipment type, and team size help athletes reach their full potential. This research leads to better training programs, safer equipment, and more exciting games!

42) Innovating Sports Strategies

By investigating how different game strategies are influenced by various team compositions, researchers contribute to the evolution of sports. This means more thrilling competitions and matches for us to enjoy!

Nutritional Well-Being

43) guiding healthy eating.

Nutritionists researching diet types, caloric intake, and food variety help us understand what foods are best for our bodies. This knowledge shapes dietary guidelines and helps us make tasty, yet nutritious, meal choices!

44) Promoting Nutritional Awareness

By studying the effects of different nutrients and diets, researchers educate us on maintaining a balanced diet. This fosters a greater awareness of nutritional well-being and encourages healthier eating habits!

As we journey through these real-world applications, we witness the incredible impact of studies featuring independent variables. The exploration doesn’t end here, though!

Let’s continue our adventure and see how we can identify independent variables in our own observations and inquiries! Keep your curiosity alive, and let’s delve deeper into the exciting realm of independent variables!

Identifying Independent Variables in Everyday Scenarios

So, we’ve seen how independent variables star in many studies, but how about spotting them in our everyday life?

Recognizing independent variables can be like a treasure hunt – you never know where you might find one! Let’s uncover some tips and tricks to identify these hidden gems in various situations.

1) Asking Questions

One of the best ways to spot an independent variable is by asking questions! If you’re curious about something, ask yourself, “What am I changing or manipulating in this situation?” The thing you’re changing is likely the independent variable!

For example, if you’re wondering whether the amount of sunlight affects how quickly your laundry dries, the sunlight amount is your independent variable!

2) Making Observations

Keep your eyes peeled and observe the world around you! By watching how changes in one thing (like the amount of rain) affect something else (like the height of grass), you can identify the independent variable.

In this case, the amount of rain is the independent variable because it’s what’s changing!

3) Conducting Experiments

Get hands-on and conduct your own experiments! By changing one thing and observing the results, you’re identifying the independent variable.

If you’re growing plants and decide to water each one differently to see the effects, the amount of water is your independent variable!

4) Everyday Scenarios

In everyday scenarios, independent variables are all around!

When you adjust the temperature of your oven to bake cookies, the oven temperature is the independent variable.

Or if you’re deciding how much time to spend studying for a test, the study time is your independent variable!

5) Being Curious

Keep being curious and asking “What if?” questions! By exploring different possibilities and wondering how changing one thing could affect another, you’re on your way to identifying independent variables.

If you’re curious about how the color of a room affects your mood, the room color is the independent variable!

6) Reviewing Past Studies

Don’t forget about the treasure trove of past studies and experiments! By reviewing what scientists and researchers have done before, you can learn how they identified independent variables in their work.

This can give you ideas and help you recognize independent variables in your own explorations!

Exercises for Identifying Independent Variables

Ready for some practice? Let’s put on our thinking caps and try to identify the independent variables in a few scenarios.

Remember, the independent variable is what’s being changed or manipulated to observe the effect on something else! (You can see the answers below)

Scenario One: Cooking Time

You’re cooking pasta for dinner and want to find out how the cooking time affects its texture. What is the independent variable?

Scenario Two: Exercise Routine

You decide to try different exercise routines each week to see which one makes you feel the most energetic. What is the independent variable?

Scenario Three: Plant Fertilizer

You’re growing tomatoes in your garden and decide to use different types of fertilizer to see which one helps them grow the best. What is the independent variable?

Scenario Four: Study Environment

You’re preparing for an important test and try studying in different environments (quiet room, coffee shop, library) to see where you concentrate best. What is the independent variable?

Scenario Five: Sleep Duration

You’re curious to see how the number of hours you sleep each night affects your mood the next day. What is the independent variable?

By practicing identifying independent variables in different scenarios, you’re becoming a true independent variable detective. Keep practicing, stay curious, and you’ll soon be spotting independent variables everywhere you go.

Independent Variable: The cooking time is the independent variable. You are changing the cooking time to observe its effect on the texture of the pasta.

Independent Variable: The type of exercise routine is the independent variable. You are trying out different exercise routines each week to see which one makes you feel the most energetic.

Independent Variable: The type of fertilizer is the independent variable. You are using different types of fertilizer to observe their effects on the growth of the tomatoes.

Independent Variable: The study environment is the independent variable. You are studying in different environments to see where you concentrate best.

Independent Variable: The number of hours you sleep is the independent variable. You are changing your sleep duration to see how it affects your mood the next day.

Whew, what a journey we’ve had exploring the world of independent variables! From understanding their definition and role to diving into a myriad of examples and real-world impacts, we’ve uncovered the treasures hidden in the realm of independent variables.

The beauty of independent variables lies in their ability to unlock new knowledge and insights, guiding us to discoveries that improve our lives and the world around us.

By identifying and studying these variables, we embark on exciting learning adventures, solving mysteries and answering questions about the universe we live in.

Remember, the joy of discovery doesn’t end here. The world is brimming with questions waiting to be answered and mysteries waiting to be solved.

Keep your curiosity alive, continue exploring, and who knows what incredible discoveries lie ahead.

Related posts:

• Confounding Variable in Psychology (Examples + Definition)
• 19+ Experimental Design Examples (Methods + Types)
• Variable Interval Reinforcement Schedule (Examples)
• Variable Ratio Reinforcement Schedule (Examples)
• State Dependent Memory + Learning (Definition and Examples)

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Controlled Experiment

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

This is when a hypothesis is scientifically tested.

In a controlled experiment, an independent variable (the cause) is systematically manipulated, and the dependent variable (the effect) is measured; any extraneous variables are controlled.

The researcher can operationalize (i.e., define) the studied variables so they can be objectively measured. The quantitative data can be analyzed to see if there is a difference between the experimental and control groups.

What is the control group?

In experiments scientists compare a control group and an experimental group that are identical in all respects, except for one difference – experimental manipulation.

Unlike the experimental group, the control group is not exposed to the independent variable under investigation and so provides a baseline against which any changes in the experimental group can be compared.

Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to experimental manipulation rather than chance.

Randomly allocating participants to independent variable groups means that all participants should have an equal chance of participating in each condition.

The principle of random allocation is to avoid bias in how the experiment is carried out and limit the effects of participant variables.

What are extraneous variables?

The researcher wants to ensure that the manipulation of the independent variable has changed the changes in the dependent variable.

Hence, all the other variables that could affect the dependent variable to change must be controlled. These other variables are called extraneous or confounding variables.

Extraneous variables should be controlled were possible, as they might be important enough to provide alternative explanations for the effects.

In practice, it would be difficult to control all the variables in a child’s educational achievement. For example, it would be difficult to control variables that have happened in the past.

A researcher can only control the current environment of participants, such as time of day and noise levels.

Why conduct controlled experiments?

Scientists use controlled experiments because they allow for precise control of extraneous and independent variables. This allows a cause-and-effect relationship to be established.

Controlled experiments also follow a standardized step-by-step procedure. This makes it easy for another researcher to replicate the study.

Key Terminology

Experimental group.

The group being treated or otherwise manipulated for the sake of the experiment.

Control Group

They receive no treatment and are used as a comparison group.

Ecological validity

The degree to which an investigation represents real-life experiences.

Experimenter effects

These are the ways that the experimenter can accidentally influence the participant through their appearance or behavior.

Demand characteristics

The clues in an experiment lead the participants to think they know what the researcher is looking for (e.g., the experimenter’s body language).

Independent variable (IV)

The variable the experimenter manipulates (i.e., changes) – is assumed to have a direct effect on the dependent variable.

Dependent variable (DV)

Variable the experimenter measures. This is the outcome (i.e., the result) of a study.

Extraneous variables (EV)

All variables that are not independent variables but could affect the results (DV) of the experiment. Extraneous variables should be controlled where possible.

Confounding variables

Variable(s) that have affected the results (DV), apart from the IV. A confounding variable could be an extraneous variable that has not been controlled.

Random Allocation

Randomly allocating participants to independent variable conditions means that all participants should have an equal chance of participating in each condition.

Order effects

Changes in participants’ performance due to their repeating the same or similar test more than once. Examples of order effects include:

(i) practice effect: an improvement in performance on a task due to repetition, for example, because of familiarity with the task;

(ii) fatigue effect: a decrease in performance of a task due to repetition, for example, because of boredom or tiredness.

What is the control in an experiment?

In an experiment , the control is a standard or baseline group not exposed to the experimental treatment or manipulation. It serves as a comparison group to the experimental group, which does receive the treatment or manipulation.

The control group helps to account for other variables that might influence the outcome, allowing researchers to attribute differences in results more confidently to the experimental treatment.

Establishing a cause-and-effect relationship between the manipulated variable (independent variable) and the outcome (dependent variable) is critical in establishing a cause-and-effect relationship between the manipulated variable.

What is the purpose of controlling the environment when testing a hypothesis?

Controlling the environment when testing a hypothesis aims to eliminate or minimize the influence of extraneous variables. These variables other than the independent variable might affect the dependent variable, potentially confounding the results.

By controlling the environment, researchers can ensure that any observed changes in the dependent variable are likely due to the manipulation of the independent variable, not other factors.

This enhances the experiment’s validity, allowing for more accurate conclusions about cause-and-effect relationships.

It also improves the experiment’s replicability, meaning other researchers can repeat the experiment under the same conditions to verify the results.

Why are hypotheses important to controlled experiments?

Hypotheses are crucial to controlled experiments because they provide a clear focus and direction for the research. A hypothesis is a testable prediction about the relationship between variables.

It guides the design of the experiment, including what variables to manipulate (independent variables) and what outcomes to measure (dependent variables).

The experiment is then conducted to test the validity of the hypothesis. If the results align with the hypothesis, they provide evidence supporting it.

The hypothesis may be revised or rejected if the results do not align. Thus, hypotheses are central to the scientific method, driving the iterative inquiry, experimentation, and knowledge advancement process.

What is the experimental method?

The experimental method is a systematic approach in scientific research where an independent variable is manipulated to observe its effect on a dependent variable, under controlled conditions.

What Is a Variable in Science?

Understanding Variables in a Science Experiment

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• Ph.D., Biomedical Sciences, University of Tennessee at Knoxville
• B.A., Physics and Mathematics, Hastings College

Variables are an important part of science projects and experiments. What is a variable? Basically, a variable is any factor that can be controlled, changed, or measured in an experiment. Scientific experiments have several types of variables. The independent and dependent variables are the ones usually plotted on a chart or graph, but there are other types of variables you may encounter.

Types of Variables

• Independent Variable: The independent variable is the one condition that you change in an experiment. Example: In an experiment measuring the effect of temperature on solubility, the independent variable is temperature.
• Dependent Variable: The dependent variable is the variable that you measure or observe. The dependent variable gets its name because it is the factor that is dependent on the state of the independent variable . Example: In the experiment measuring the effect of temperature on solubility, solubility would be the dependent variable.
• Controlled Variable: A controlled variable or constant variable is a variable that does not change during an experiment. Example : In the experiment measuring the effect of temperature on solubility, controlled variable could include the source of water used in the experiment, the size and type of containers used to mix chemicals, and the amount of mixing time allowed for each solution.
• Extraneous Variables: Extraneous variables are "extra" variables that may influence the outcome of an experiment but aren't taken into account during measurement. Ideally, these variables won't impact the final conclusion drawn by the experiment, but they may introduce error into scientific results. If you are aware of any extraneous variables, you should enter them in your lab notebook . Examples of extraneous variables include accidents, factors you either can't control or can't measure, and factors you consider unimportant. Every experiment has extraneous variables. Example : You are conducting an experiment to see which paper airplane design flies longest. You may consider the color of the paper to be an extraneous variable. You note in your lab book that different colors of papers were used. Ideally, this variable does not affect your outcome.

Using Variables in Science Experiment

In a science experiment , only one variable is changed at a time (the independent variable) to test how this changes the dependent variable. The researcher may measure other factors that either remain constant or change during the course of the experiment but are not believed to affect its outcome. These are controlled variables. Any other factors that might be changed if someone else conducted the experiment but seemed unimportant should also be noted. Also, any accidents that occur should be recorded. These are extraneous variables.

Variables and Attributes

In science, when a variable is studied, its attribute is recorded. A variable is a characteristic, while an attribute is its state. For example, if eye color is the variable, its attribute might be green, brown, or blue. If height is the variable, its attribute might be 5 m, 2.5 cm, or 1.22 km.

• Earl R. Babbie. The Practice of Social Research , 12th edition. Wadsworth Publishing, 2009.
• What Is a Dependent Variable?
• What Is an Experiment? Definition and Design
• Six Steps of the Scientific Method
• Examples of Independent and Dependent Variables
• How To Design a Science Fair Experiment
• The Role of a Controlled Variable in an Experiment
• Scientific Variable
• What Are the Elements of a Good Hypothesis?
• Dependent Variable vs. Independent Variable: What Is the Difference?
• What Is the Difference Between a Control Variable and Control Group?
• Independent Variable Definition and Examples
• Null Hypothesis Examples
• What Is a Controlled Experiment?
• DRY MIX Experiment Variables Acronym
• Scientific Method Vocabulary Terms
• What Is the Difference Between Hard and Soft Science?

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Columbia’s Antisemitism Task Force Finds ‘Urgent Need’ for Change

The group, which had previously resisted defining “antisemitism,” issued a definition, and called on the university to institute anti-bias training and revamp its systems for handling complaints.

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By Claire Fahy

A Columbia University task force set up to combat antisemitism on campus released its latest report on Friday, detailing numerous instances of harassment and even physical violence directed at Jewish students in the wake of the Oct. 7 Hamas attacks on Israel. The task force found “an urgent need to reshape everyday social norms” at Columbia and recommended changes in how the university prevents and responds to bias incidents.

Students will return on Tuesday to a campus that was roiled by pro-Palestinian protests in the spring, culminating in a canceled commencement ceremony in May. The 90-page report , based in part on listening sessions with students, follows one published in March that called for limits on protests and stronger enforcement of existing rules.

Since Oct. 7, the task force found, Jewish and Israeli students described being harassed with ethnic slurs and stereotypes, threatened and in some cases assaulted, and some said they were barred from certain student groups because of their Zionism. The task force heard from nearly 500 students, according to the latest report.

Most of the student experiences detailed in both reports took place before a pro-Palestinian encampment sprung up on campus in April; “at that point, things got worse,” Friday’s report said.

“Students came to share their stories from a variety of religious, geographical, ideological, national, racial, ethnic and political backgrounds,” the report said. “We heard from Zionists, and anti-Zionists, and those whose opinions are not easily categorized.”

Ester R. Fuchs, a public affairs professor at Columbia and a co-chair of the task force, said that what set this report apart from similar efforts at other universities was its focus on student voices.

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• Diet & Nutrition

Why One Dietitian is Speaking Up for “Ultra-Processed” Foods

J essica Wilson is passionate about the pupusas from Costco. Not just because they’re tasty, but also because they’ve helped the California-based registered dietitian fight back against the mounting war on ultra-processed foods .

It all started in the summer of 2023, when author and infectious-disease physician Dr. Chris van Tulleken was promoting his book, Ultra-Processed People. While writing it, van Tulleken spent a month eating mostly foods like chips, soda, bagged bread, frozen food, and cereal. “What happened to me is exactly what the research says would happen to everyone,” van Tulleken says: he felt worse, he gained weight, his hormone levels went crazy, and before-and-after MRI scans showed signs of changes in his brain. As van Tulleken saw it, the experiment highlighted the “terrible emergency” of society’s love affair with ultra-processed foods.

Wilson, who specializes in working with clients from marginalized groups, was irked. She felt that van Tulleken’s experiment was over-sensationalized and that the news coverage of it shamed people who regularly eat processed foods—in other words, the vast majority of Americans , particularly the millions who are food insecure or have limited access to fresh food; they also tend to be lower income and people of color. Wilson felt the buzz ignored this “food apartheid,” as well as the massive diversity of foods that can be considered ultra-processed: a category that includes everything from vegan meat replacements and nondairy milks to potato chips and candy. “How can this entire category of foods be something we’re supposed to avoid?” Wilson wondered.

So she did her own experiment. Like van Tulleken, Wilson for a month got 80% of her daily calories from highly processed foods, not much more than the average American . She swapped her morning eggs for soy chorizo and replaced her thrown-together lunches—sometimes as simple as beans with avocado and hot sauce—with Trader Joe’s ready-to-eat tamales. She snacked on cashew-milk yogurt with jam. For dinner she’d have one of her beloved Costco pupusas, or maybe chicken sausage with veggies and Tater-Tots. She wasn’t subsisting on Fritos, but these were also decidedly not whole foods.

Read More : Why Your Diet Needs More Fermented Pickles

A weird thing happened. Wilson found that she had more energy and less anxiety. She didn’t need as much coffee to get through the day and felt more motivated. She felt better eating an ultra-processed diet than she had before, a change she attributes to taking in more calories by eating full meals, instead of haphazard combinations of whole-food ingredients.

How could two people eating the same type of foods have such different experiences? And could it be true that not all ultra-processed foods deserve their bad reputation?

These hotly debated questions come at a crucial moment. In 2025, the U.S. government will release an updated version of the Dietary Guidelines for Americans, which tell people what they should eat and policymakers how to shape things like school lunches and SNAP education programs. The new edition may include, for the first time, guidance on ultra-processed foods. Officials at the U.S. Food and Drug Administration are also reportedly weighing new regulatory approaches for these products.

The food industry, predictably, maintains that ultra-processed foods have been unfairly demonized and can be part of a healthy diet. Likely sensing a threat to their bottom line, large food companies have reportedly already started lobbying against recommendations around processed-food consumption.

What’s more surprising is that even one dietitian would take their side, defending a group of foods that, according to 2024 research , has been linked to dozens of poor health outcomes ranging from depression and diabetes to cancer, cardiovascular disease, and cognitive impairment . Wilson has endured plenty of criticism for her position, which is not popular among the nutrition-science establishment. But she stands by it. Sweeping recommendations to avoid all ultra-processed foods stand to confuse people and make them feel bad about their diets, Wilson says—with questionable upside for their health.

What is a processed food, anyway? It’s a rather new concept. Foods are mainly judged by how many vitamins, minerals, and macronutrients (think fat, protein, and carbs) they contain, as well as their sugar, salt, and saturated-fat contents. There’s no level of processing on a food label.

Scientists don’t agree on exactly how to define processed foods. If you give two experts the same ingredient list, “they will have different opinions about whether something is processed or not,” says Giulia Menichetti, a faculty member at Harvard Medical School who researches food chemistry. Take milk. Some experts consider it a processed food because it goes through pasteurization to kill pathogens . Others don’t think it belongs in that category because plain milk typically contains few additives beyond vitamins.

The most widely used food-classification system, known as NOVA , uses the latter interpretation. It defines an unprocessed food as one that comes directly from a plant or animal, like a fresh-picked apple. A minimally processed food may have undergone a procedure like cleaning, freezing, or drying, but hasn’t been much altered from its original form. Examples include eggs, whole grains, some frozen produce, and milk.

Read More : What's So Great About Cottage Cheese?

Under NOVA, a processed food contains added ingredients to make it taste better or last longer, such as many canned products, cured meats, and cheeses. An ultra-processed food, meanwhile, is made largely or entirely from oils, sugars, starches, and ingredients you wouldn’t buy yourself at the grocery store—things like hydrogenated fats, emulsifiers, flavor enhancers, and other additives. Everything from packaged cookies to flavored yogurt to baby formula fits that description.

“You end up with a system where gummy bears and canned kidney beans” aren’t treated so differently, says Julie Hess, a research nutritionist with the USDA. At the end of the day, they’re both processed.

Why should that matter to anyone aside from researchers and dietitians? Because most people who care about their health have the same question about processed foods: Are they killing me? And right now—despite their looming possible inclusion in dietary guidelines—no one really knows the answer. There’s limited cause-and-effect research on how processed foods affect health, and scientists and policymakers have yet to come up with a good way to, as Hess says, “meaningfully delineate between nutrient-dense foods and nutrient-poor options”—to separate the kidney beans from the gummy bears.

Hess and her colleagues drove home that point in a 2023 study , for which they created a hypothetical diet almost entirely made up of ultra-processed foods like breakfast burritos, canned soup, and instant oatmeal. The diet wasn’t nutritionally stellar—it was high in sodium and low in whole grains—but scored an 86 out of 100 on a measure of adherence to the federal dietary guidelines, considerably better than the average American’s score of 59. The experiment highlighted that there are nutritious ultra-processed foods, and that certain ones “may make it easier and more convenient to have a healthy diet, because a lot of these foods are more shelf-stable, they’re more cost-effective, they’re sometimes easier to access,” Hess says.

A 2024 study backs up the idea that people who eat processed foods can still be healthy. Although the researchers did find links between heavily processed diets and risk of premature death, they concluded that overall diet quality may be more important than how many processed foods someone eats. In other words, if someone is eating plenty of nutritious foods, maybe it’s OK if some come from a wrapper. The study aimed to correct “the potential misperception that all ultra-processed food products should be universally restricted and to avoid oversimplification when formulating dietary recommendations,” the authors wrote.

Even vocal critics of ultra-processed foods, like van Tulleken, agree that not all are equal. He’s particularly concerned about those that are high in salt, sugar, or saturated fat, which is true of many ultra-processed foods but not all of them. These elements have long been nemeses of the nutrition world, but van Tulleken argues they’re especially damaging when eaten in industrially made foods spiked with additives and designed to be as appetizing as possible . “We’ve had fat, salt, and sugar in abundance in our diet for a century, and I'm the first to say they are the nutrients of concern,” van Tulleken says. “But they weren’t a concern when we were mixing them up at home, because when you cook at home, your purpose is not to get me to eat 3,000 calories in half an hour.”

Read More : 6 Health Myths About Oils

Industrial production means that ingredients undergo complex chemical changes, the implications of which researchers don’t fully understand, says Menichetti, from Harvard. “We co-evolved with our food, so if our bodies got used to certain chemicals in certain ranges,” altering foods’ compositions via processing could change the way they affect human health, she says.

Already, some studies suggest that ultra-processed foods affect the body differently than unprocessed ones, regardless of their nutrient profiles. One 2024 study found that plant-based foods, which are traditionally considered healthy , lose many of their benefits and even contribute to higher risks of heart disease and death when they’re ultra-processed (when a whole grain turns into store-bought bread, for example). And a 2020 review article found numerous bad outcomes—cancer, cardiovascular disease, IBS , depression, and more—linked to ultra-processed diets and not a single study connecting them to better health. Those results suggest that a food’s processing level is linked to its “healthiness,” the authors wrote.

A 2019 study from the National Institutes of Health (NIH) provides some of the strongest evidence that ultra-processed foods can directly cause health problems. For the study, 20 U.S. adults lived in an NIH laboratory for a month. For two weeks, they ate minimally processed foods like vegetables and nuts. For the other two, they ate ultra-processed foods like bagels and canned pasta.

The two diets were designed to be equivalent in calories, sugar, salt, and macronutrients, but people could eat as much or as little as they wanted at mealtimes. On the ultra-processed diet, people ate more and gained weight. Meanwhile, on the minimally processed one, they lost weight, had positive hormonal changes, and saw markers of inflammation drop. Those findings suggest something about ultra-processed foods drives people to overeat and may cause health problems, says lead author Kevin Hall—but it’s not yet clear what that something may be.

“There’s a very, very long list of potential candidates,” Hall says. Is it the combination of ingredients manufacturers use to make foods tasty? Is there a problematic ingredient or additive? Does something about the manufacturing process degrade the food’s quality? Or is the explanation something else entirely?

In November, the 2025 Dietary Guidelines Advisory Committee is expected to release a report on ultra-processed foods, which will assess the available data on how they affect the body. More research is needed. But at a meeting in May, committee member Dr. Fatima Cody Stanford, an obesity-medicine specialist at Massachusetts General Hospital, previewed the group’s findings: that people who eat highly processed diets are at risk of obesity.

Even with questions outstanding, we already know that some ultra-processed foods are harmful, says Kendra Chow, a registered dietitian and policy and public affairs manager at the nonprofit World Cancer Research Fund International. Stereotypical “junk foods” that are high in salt, sugar, or saturated fat—things like chips, candy, and hot dogs—have long been linked to health problems like cancer and heart disease. The science on those foods is clear enough that people should limit how often they eat them, she says.

What’s trickier, Chow says, is figuring out what to do about foods that are ultra-processed but seem to have more nutritional value, like flavored yogurts and store-bought vegetable pasta sauces. “Stigmatizing a broad category of foods that also includes lower-cost, accessible options, especially without providing an alternative or improving access and affordability of healthy foods,” is not the answer, she says.

Read More : Can Food Really Change Your Hormones

Despite his prominent campaign against ultra-processed foods, van Tulleken agrees. He realizes a ban on them wouldn’t be practical; it would essentially wipe out the modern food system, with particularly disastrous consequences for people of lower socio-economic status. (He would, however, like to see more regulation of food marketing and warning labels on processed products high in salt, sugar, or saturated fat.) Though he feels strongly that ultra-processed foods are contributing to a modern public-health crisis, van Tulleken also recognizes that they serve an imperfect purpose in a world where many people are strapped for time and money.

Even Hall, the NIH researcher, eats ultra-processed foods—and not infrequently. Most days for lunch, he heats up a frozen meal in the microwave. “I’ll try to choose one that is high in fiber and whole grains and legumes and low in sodium and saturated fat and sugar,” he says. But he knows that technically, it’s in the same category as a Twinkie.

After her experiment last summer, Wilson also continues to eat plenty of processed foods—and to feel good about it. To her, the debate is about more than food; it’s also about the realities of living in a country where grocery prices are spiking and lots of people simply don’t have the resources to eat three home-cooked meals made from fresh ingredients every single day.

“People often assume that a dietitian’s day is telling people to eat less,” Wilson says. But she says she spends far more time helping people figure out how to eat more—whether because they’re trying to feed a family on a tight budget or because they simply don’t have time and energy to cook—and how to add nutrient-rich foods to their diets in a way that’s affordable. For some of those people, ultra-processed foods may be the difference between going to bed hungry or full, Wilson says. She’d pick full every time.

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Write to Jamie Ducharme at [email protected]

Soft Matter

Accessing the free expansion of a crystalline colloidal drop by optical experiments †.

* Corresponding authors

a Institute of Physics, Johannes Gutenberg University, Mainz, Germany E-mail: [email protected]

b Institute of Theoretical Physics II: Soft Matter, Heinrich-Heine-Universität, Düsseldorf, Germany

c Institute for Biophysics, Goethe University, Frankfurt, Germany

d Pontifícia Universidade Católica, Rio de Janeiro, Brazil

We study poly-crystalline spherical drops of an aqueous suspension of highly charged colloidal spheres exposed to a colloid-free aqueous environment. Crystal contours were obtained from standard optical imaging. The crystal spheres first expand to nearly four times their initial volume before slowly shrinking due to dilution-induced melting. Exploiting coherent multiple-scattering by (110) Bragg reflecting crystals, time-dependent density profiles were recorded within the drop interior. These show a continuously flattening radial density gradient and a decreasing central density. Expansion curves and density profiles are qualitatively consistent with theoretical expectations based on dynamical density functional theory for the expansion of a spherical crystallite made of charged Brownian spheres. We anticipate that our study opens novel experimental access to density determination in turbid crystals.

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Accessing the free expansion of a crystalline colloidal drop by optical experiments

M. U. Witt, G. H. P. Nguyen, J. R. von Puttkamer-Luerssen, C. H. Yilderim, J. A. B. Wagner, E. Malek, S. Juretzka, J. L. Meyrelles, M. Hofmann, H. Löwen and T. Palberg, Soft Matter , 2024, Advance Article , DOI: 10.1039/D4SM00413B

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• 2025 HSA and Excepted Benefits Inflation-Adjusted Limits

The IRS released Rev Proc 2024-25, 2024-22 IRB 1333, dated May 9, 2024, which outlines the inflation-adjusted contribution limits for Health Savings Accounts (HSAs) for the year 2025, as determined under Code Section 223. This annual adjustment is crucial for individuals and families who rely on HSAs to manage their healthcare expenses. Let’s delve into the details of these new limits and what they mean for you.

HSA Contribution Limits for 2025

For the calendar year 2025, the IRS has increased the annual contribution limits for Health Savings Accounts (HSAs):

• Self-Only Coverage: The annual deduction limit for individuals with self-only coverage under a high deductible health plan (HDHP) will be $4,300. This marks an increase of $150 from the previous limit.
• Family Coverage: For individuals with family coverage under an HDHP, the annual deduction limit will be $8,550, representing a $250 increase from the prior limit.

Definition of a High Deductible Health Plan (HDHP) for 2025

To qualify for HSA contributions, your health insurance plan must meet the IRS definition of a high deductible health plan (HDHP). For 2025, an HDHP is defined as follows:

• Self-Only Coverage: The plan must have an annual deductible of at least $1,650, and the annual out-of-pocket expenses (including deductibles, co-payments, and other amounts, but excluding premiums) must not exceed $8,300.
• Family Coverage: The plan must have an annual deductible of at least $3,300, and the annual out-of-pocket expenses must not exceed $16,600.

Excepted Benefit HRA Limits for 2025

For plan years beginning in 2025, the maximum amount that may be newly made available for the plan year for an excepted benefit Health Reimbursement Arrangement (HRA) is set at $2,150. Excepted benefit HRAs are designed to cover limited benefits, such as dental and vision care, which are not subject to the same requirements as traditional HRAs.

What These Changes Mean for HSA beneficiaries

These adjustments reflect the ongoing efforts to keep pace with inflation and the rising costs of healthcare. Here’s how you might be affected:

• Increased Savings Potential: With higher contribution limits, you can save more in your HSA, allowing you to better prepare for future healthcare expenses. This is especially beneficial for those who anticipate higher medical costs.
• Tax Benefits: Contributions to HSAs are tax-deductible, and the funds grow tax-free. Additionally, withdrawals for qualified medical expenses are also tax-free, providing a triple tax advantage.
• Planning for Out-of-Pocket Expenses: Understanding the new definitions of HDHPs and their associated out-of-pocket limits can help you choose the right health plan for your needs.

Staying informed about these changes can help you maximize the benefits of your HSA and make more informed decisions about your healthcare coverage. If you have any questions or need further assistance, consider consulting with a tax professional or financial advisor to make the most of your HSA contributions and benefits.

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Independent and Dependent Variables Examples

The independent and dependent variables are key to any scientific experiment, but how do you tell them apart? Here are the definitions of independent and dependent variables, examples of each type, and tips for telling them apart and graphing them.

Independent Variable

The independent variable is the factor the researcher changes or controls in an experiment. It is called independent because it does not depend on any other variable. The independent variable may be called the “controlled variable” because it is the one that is changed or controlled. This is different from the “ control variable ,” which is variable that is held constant so it won’t influence the outcome of the experiment.

Dependent Variable

The dependent variable is the factor that changes in response to the independent variable. It is the variable that you measure in an experiment. The dependent variable may be called the “responding variable.”

Examples of Independent and Dependent Variables

Here are several examples of independent and dependent variables in experiments:

• In a study to determine whether how long a student sleeps affects test scores, the independent variable is the length of time spent sleeping while the dependent variable is the test score.
• You want to know which brand of fertilizer is best for your plants. The brand of fertilizer is the independent variable. The health of the plants (height, amount and size of flowers and fruit, color) is the dependent variable.
• You want to compare brands of paper towels, to see which holds the most liquid. The independent variable is the brand of paper towel. The dependent variable is the volume of liquid absorbed by the paper towel.
• You suspect the amount of television a person watches is related to their age. Age is the independent variable. How many minutes or hours of television a person watches is the dependent variable.
• You think rising sea temperatures might affect the amount of algae in the water. The water temperature is the independent variable. The mass of algae is the dependent variable.
• In an experiment to determine how far people can see into the infrared part of the spectrum, the wavelength of light is the independent variable and whether the light is observed is the dependent variable.
• If you want to know whether caffeine affects your appetite, the presence/absence or amount of caffeine is the independent variable. Appetite is the dependent variable.
• You want to know which brand of microwave popcorn pops the best. The brand of popcorn is the independent variable. The number of popped kernels is the dependent variable. Of course, you could also measure the number of unpopped kernels instead.
• You want to determine whether a chemical is essential for rat nutrition, so you design an experiment. The presence/absence of the chemical is the independent variable. The health of the rat (whether it lives and reproduces) is the dependent variable. A follow-up experiment might determine how much of the chemical is needed. Here, the amount of chemical is the independent variable and the rat health is the dependent variable.

How to Tell the Independent and Dependent Variable Apart

If you’re having trouble identifying the independent and dependent variable, here are a few ways to tell them apart. First, remember the dependent variable depends on the independent variable. It helps to write out the variables as an if-then or cause-and-effect sentence that shows the independent variable causes an effect on the dependent variable. If you mix up the variables, the sentence won’t make sense. Example : The amount of eat (independent variable) affects how much you weigh (dependent variable).

This makes sense, but if you write the sentence the other way, you can tell it’s incorrect: Example : How much you weigh affects how much you eat. (Well, it could make sense, but you can see it’s an entirely different experiment.) If-then statements also work: Example : If you change the color of light (independent variable), then it affects plant growth (dependent variable). Switching the variables makes no sense: Example : If plant growth rate changes, then it affects the color of light. Sometimes you don’t control either variable, like when you gather data to see if there is a relationship between two factors. This can make identifying the variables a bit trickier, but establishing a logical cause and effect relationship helps: Example : If you increase age (independent variable), then average salary increases (dependent variable). If you switch them, the statement doesn’t make sense: Example : If you increase salary, then age increases.

How to Graph Independent and Dependent Variables

Plot or graph independent and dependent variables using the standard method. The independent variable is the x-axis, while the dependent variable is the y-axis. Remember the acronym DRY MIX to keep the variables straight: D = Dependent variable R = Responding variable/ Y = Graph on the y-axis or vertical axis M = Manipulated variable I = Independent variable X = Graph on the x-axis or horizontal axis

• Babbie, Earl R. (2009). The Practice of Social Research (12th ed.) Wadsworth Publishing. ISBN 0-495-59841-0.
• di Francia, G. Toraldo (1981). The Investigation of the Physical World . Cambridge University Press. ISBN 978-0-521-29925-1.
• Gauch, Hugh G. Jr. (2003). Scientific Method in Practice . Cambridge University Press. ISBN 978-0-521-01708-4.
• Popper, Karl R. (2003). Conjectures and Refutations: The Growth of Scientific Knowledge . Routledge. ISBN 0-415-28594-1.

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New DEA laboratory will quicken drug evidence analysis in New England

• Updated: Aug. 28, 2024, 2:11 p.m.
• | Published: Aug. 28, 2024, 2:06 p.m.

The U.S. Drug Enforcement Administration has broken ground on a New England laboratory in Londonderry, New Hampshire. Pictured is a rendering. Courtesy DEA

• Hadley Barndollar | [email protected]

Expected to quicken the region’s ability to analyze drug evidence and respond to emerging threats, the U.S. Drug Enforcement Administration has broken ground on a new, state-of-the-art laboratory for New England investigations.

Located in Londonderry, New Hampshire, the facility will be the eighth regional DEA laboratory specializing in drug chemistry and latent fingerprint identification.

Scheduled to open in April 2026, the DEA expects the lab will analyze more than 5,000 drug exhibits per year and employ more than 50 people.

The evidence analysis conducted at the new facility — serving Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont, and upstate New York — will be used to prosecute drug crimes.

It also will allow the DEA to identify new and emerging trends in the region’s drug supply.

• Related news: How ‘one pill can kill’: Why the DEA was in Worcester this week

“The New Hampshire laboratory will analyze evidence that will be used to defeat the two cartels responsible for thousands of drug poisonings across the country and will help us stay ahead of emerging drug threats and save lives,” DEA Administrator Anne Milgram said in a statement.

According to the Centers for Disease Control and Prevention, fatal drug overdoses — approximately 70% related to fentanyl — are the leading cause of death for Americans between the ages of 18 and 45.

• Related news: Why a Worcester drug overdose increase is causing outsize concern

With the emergence of synthetic fentanyl, Milgram said modern forensic laboratories staffed by highly trained chemists “help protect our communities.”

Stephen Belleau, acting DEA special agent in charge of the New England Field Division, said the New Hampshire laboratory will provide quick analyses, and in turn lead to drug trafficking organizations being dismantled “at a quicker rate.”

“Additionally, emerging drug threats will be identified faster leading to a more knowledgeable and safer public at large,” he said.

More about drugs and public health

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• Cloud infrastructure design and management

What is cloud elasticity?

• Nicole Lewis

Cloud elasticity is the ability, in real time, to increase or decrease cloud computing resources, such as central processing unit (CPU) power, memory and storage capacity, as well as input and output bandwidth, to meet unexpected changes in online traffic.

Why is cloud elasticity important?

Organizations often experience unexpected increases in the use of their cloud-based applications. At peak periods, they need their cloud systems to run continuously without interruption. Those with insufficient cloud elasticity risk losing customers and can suffer reputational damage.

At times like these, elastic cloud services are essential to support both the high levels of online traffic and transactions, as well as the drop in demand when the event ends. In the absence of cloud elasticity, organizations might suffer service outages and computer failures, which increase the threat of viruses and other vulnerabilities. Companies might also have to resort to fixes, such as operating system upgrades and patches, which can be costly.

Cloud elasticity vs. cloud scalability

Cloud elasticity and cloud scalability are common cloud computing concepts that have some similarities, but there are fundamental differences in how they operate in a cloud environment.

Cloud elasticity involves the ability to automatically or manually add or shrink cloud resources quickly to meet sudden changes in demand and prevent disruptions in service. The flexibility and agility of elastic cloud services give organizations the ability to adapt to short-term variations in workloads. Companies with cloud operations that experience unpredictable shifts in demand often turn to the elastic cloud services available in a public cloud .

In contrast, cloud scalability involves increasing and decreasing resources to meet workload demands over time and supports a deliberate approach to long-term planning. A company that is building a music streaming service, for example, would find cloud scalability important for accommodating fast growth in subscribers without having to worry about constraints.

How does cloud elasticity work?

With elasticity, organizations can quickly and nimbly scale up or down -- either automatically or manually -- the resources needed to support cloud-based applications. During this process, the cloud provider resizes its cloud by provisioning or deprovisioning resources such as RAM , storage capacity and CPU processing capability to match changes in an organization's overall demand profile.

Horizontal scaling, which involves increasing the number of machines in an organization's IT infrastructure to accommodate new demand, is often used to achieve cloud elasticity. So, too, is the public cloud, which provides pay-as-you-go billing. Both options are critical to business expansion and cost containment.

As more customers visit a website -- or new employees require access to the organization's internal cloud applications -- and the demand for resources grows, autoscaling of resources starts to occur. There are three main types:

• Dynamic scaling , the most common configuration, uses various metrics to automatically adjust the amount of compute power in response to triggering events.
• Predictive scaling refers to the predetermined increase of server capacity based on expected periods of high traffic at a public website, for example, during holiday travel; major sporting events, like the Super Bowl or World Cup final; or Black Friday.
• Scheduled scaling refers to the deployment of server resources to manage routine high-traffic periods, such as peak business hours.

All three can be scaled down when the demand for resources declines.

Benefits of cloud elasticity

Cloud elasticity enables organizations to equip their IT environment with a fail-safe amount of cloud capacity that ensures online systems stay up and running to whatever capacity customers and employees need during peak periods of cloud application use.

Organizations must be able to manage bursts of activity on their cloud systems without knowing exactly how many additional resources they'll need, but once the surge is over, they can reset their resource use to normal levels and avoid wasteful expenses.

Cloud elasticity is both financially and operationally advantageous to organizations. Using elastic cloud services avoids overprovisioning (using too many resources), which comes with unnecessary expenses, as well as underprovisioning (using too few resources), which can result in users being unable to access the service. An optimally performing cloud elasticity model avoids overprovisioning and underprovisioning, resulting in cost efficiency in cloud environments. In essence, organizations only pay for the resources they use.

Challenges of cloud elasticity

Cloud elasticity presents several challenges. For a start, because elasticity in cloud computing requires managing many different resources in an organization's IT infrastructure, cloud elasticity entails a learning curve and experience to understand how to manage services in an efficient and cost-effective way.

Organizations that run their cloud environment on premises rather than outsourcing their cloud infrastructure have to find technical expertise, such as developers, architects and administrators, to manage the increase and decrease in demand for cloud resources when they implement a cloud elasticity strategy.

In addition, cloud services that are subjected to frequent increases and decreases in demand are more likely to be exposed to cybersecurity threats, which requires them to be carefully reevaluated according to security criteria.

Another challenge is preventing a sudden surge in demand from negatively impacting performance if additional resources can't be allocated in time.

Cloud elasticity examples

Businesses with e-commerce websites that offer sales starting from Black Friday until early January when the holiday season comes to an end experience huge surges in online visits and transactions.

Airlines that experience higher volumes of ticket sales during holidays such as Christmas see a surge in online visits and ticket purchases.

Online ticket distribution companies that sell concert tickets for high-demand events, such as Taylor Swift's The Eras Tour or Beyoncé's Renaissance World Tour, typically experience a rapid rise in demand and a need for elastic cloud services to handle ticket sales, often over an extended period.

Companies also need elasticity when adding cloud capacity for software testing and development projects and removing the resources once the project ends.

Elastic cloud services are also useful for short-term projects, such as batch processing, data analytics and media rendering.

If a disaster occurs at an organization's production site, the organization often implements a business continuity and disaster recovery plan that calls for using the public cloud and elastic computing to support a replica of the production site, which then requires constant replication and saving of data to ensure that is it always accessible in the cloud.

Organizations might also need to expand their data sources when, for example, they create new business units or combine data and IT infrastructure in a corporate merger or acquisition. The process can result in a high volume of information being assigned to data warehouses and data lakes. By using elastic cloud services, organizations can prevent the data management challenges of an expansion from interfering with daily operations.

Continue Reading About What is cloud elasticity?

• The importance of cloud capacity management and how to do it
• Metrics that matter in cloud application monitoring
• Apply these FinOps best practices to optimize cloud costs
• Different types of cloud load balancing and algorithms

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‘Definition of a Buckeye’: Ohio State football unveils statue for legend Archie Griffin

• Updated: Aug. 30, 2024, 5:03 p.m.
• | Published: Aug. 30, 2024, 1:33 p.m.

Former Ohio State running back Archie Griffin poses by his statue outside Ohio Stadium. Stefan Krajisnik

• Stefan Krajisnik, cleveland.com

COLUMBUS, Ohio — There’s the stiff arm that can be felt 50 years later. There’s the No. 45 that is popular on the chests and backs of many Ohio State football fans. There’s the stern look that stared into the eyes of countless defenders.

Those elements accompany a powerful figure in Columbus. Now, those pieces that helped make Archie Griffin the legend he is, won’t be forgotten.

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If you or a loved one has questions and needs to talk to a professional about gambling, call the Ohio Problem Gambling Helpline at 1-800-589-9966 or the National Council on Program Gambling Helpline (NCPG) at 1-800-522-4700 or visit 1800gambler.net for more information. 21+ and present in Ohio. Gambling problem? Call 1-800-Gambler.

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Seven Things That Indicate a Chemical Change Is Occurring

5 Ways to Know if a Chemical Change Has Occurred

Gas bubbles appear.

Gas bubbles appear after a chemical reaction has occurred and the mixture becomes saturated with gas. The chemical change that creates the gas is completed after the gas bubbles leave the mixture. Examples of this type of reaction are when an antacid is dropped in a glass of water and begins to bubble or when boiling water bubbles.

Formation of a Precipitate

A solid, known as a precipitate, that forms after two solutions are mixed is also a sign of a chemical change. The precipitate will sometimes fall to the bottom of the container or it may remain suspended in the mixture and make the mixture cloudy. An example of a precipitate formation is when magnesium and calcium oxides mix with water in plumbing and form deposits that clog the pipes.

Color Change

Each chemical compound has a characteristic color. When the compound changes during a chemical reaction, the color may change as well. A color change does not always indicate that a chemical change has occurred since there are other factors that can contribute to a change in color. An example of a color change due to a chemical reaction is when a half eaten apple turns brown after it has been exposed to the air.

Temperature Change

Energy is required to break and form chemical bonds. Chemical reactions that involve bond-breaking tend to absorb energy from the surroundings, making the surroundings cooler. Chemical reactions that involve making bonds release energy, which makes the surroundings hotter. An example of a temperature change in a chemical reaction is when a burning fire produces heat.

Production of Light

When energy is released due to a chemical change it sometimes creates a light source. This type of chemical reaction tends to occur in combustion reactions such as a fire or burning process. Man-made examples of a light being emitted due to a chemical change include fireworks, exploding in the sky and creating a colorful display. Natural examples include fireflies, which use a chemical reaction in their bodies to produce light.

Volume Change

Each chemical compound has a specific density. If the chemical compound changes due to a chemical reaction, the density changes as well. This causes the volume of the substance to recede or expand during the reaction process. If the volume changes too rapidly, it may cause an explosion. An example of a volume change due to a chemical reaction is when gas bubbles form in magma inside a volcano and expand too rapidly, leading to a volcanic eruption.

Change in Smell or Taste

Each chemical compound has its own distinct smell or taste. When the compound changes after a chemical reaction, the taste or smell of the compound changes as well. An example of this is when fresh food that once smelled delicious slowly spoils and smells rotten. This bad smell sends a warning signal to the brain that tells the person not to eat the food.

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• Frostburg State University: 10 Signs of Chemical Change
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