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Fear Essay | Essay on Fear for Students and Children in English

February 13, 2024 by Prasanna

Fear Essay:  Fear is a natural, powerful, and primitive emotion experienced by humans, usually triggered by an unpleasant perception of danger that is either real or imaginary—fear causes psychological and, ultimately, behavioral changes in people.

Human beings experience fear as a response to a specific stimulus that occurs either in the present or in expectation or anticipation of a future threat that might be a risk to themselves. Response to any kind of fear varies from person to person.

You can also find more  Essay Writing  articles on events, persons, sports, technology and many more.

Long and Short Essays on Fear for Students and Kids in English

We are providing students with samples of a long essay of 500 words on the topic Fear and a short essay of 150 words on the topic Fear for reference.

Long Essay on Fear 500 Words in English

Long Essay on Fear is usually given to classes 7, 8, 9, and 10.

Fear, the quintessential human emotion, is an utterly unavoidable human emotion. The extent and range of fear from different things vary from person to person, but the emotion is the same. Fear is capable of causing psychological changes and, ultimately, behavioral changes in a person.

Humans experience fear as a response to a specific stimulus to a situation occurring in the present or an anticipated future threat that is a risk to oneself. The response to fear arises from the recognition of danger, leading to the confrontation of the situation or escaping the fear or avoiding the situation – also known as fight or flight response.

We all humans are programmed in a manner to recognize fear to avoid or reduce being harmed. Learning from the past about what can protect one in dangerous situations makes people capable of doing many things that one wouldn’t typically be able to or willing to respond to the threat.

Fear is broadly classified into two types, innate fears, and identity fears. Innate fears are the fears that every individual has on some level, and humans are born with these fears, which also serve as a kind of survival instinct. Humans develop identity fears as they evolve.

Apart from this, many people also fear love and connection. These fears are a subset of identity fears. As humans grow in their lives, they tend to grow connections with people, and these bonds become of great value to the person. Losing these bonds is one of the biggest fears of many.

Sometimes fear originates from real threats, but it can also originate from imagined danger – which makes fear experienced by people either rational or irrational. Rational fear is the fear of something that is real – occurring from something entirely possible or will occur. Fear of mortality is an example of a rational fear as we humans are immortal. However, irrational fears are necessarily implausible, but the fear arises from a real place in the psyche.

In some people, fear is also a response to mental health conditions such as anxiety disorders, panic attacks, phobias, post-traumatic stress disorder (PTSD). Phobia is an irrational or extreme or aversion of something. An aspect of anxiety disorder can be the tendency to develop a fear of fear.

Many people confuse fear of phobias. Fears are typical responses to objects or events. Still, fear becomes a phobia when the fear interferes with functioning correctly and maintains a consistent quality of life. Fear in humans involves a biochemical response to the situation as well as a high individual emotional response.

Fear is an emotion experienced in the mind, but it triggers some strong physical reaction in one’s body. As soon as one’s body recognizes fear, the brain starts working, alerting the nervous system, which sets the body’s response to fear into motion. The human brain releases stress hormones like cortisol and adrenaline, increasing blood pressure, and adrenaline. One starts breathing faster, and blood flow in the body changes – blood flows away from the heart into the limbs.

Short Essay on Fear 150 Words in English

Short Essay on Fear is usually given to classes 1, 2, 3, 4, 5, and 6.

Fear is one of the seven universal emotions experience by humans all over the world. Any fear arises with the threat of harm, physical, emotional, or psychological – from a real or imaginary situation.

Usually perceived as a negative emotion, fear can also be positive and healthy. Fear serves as a survival instinct helping humans in recognizing situations that can be harmful or dangerous.

Fear makes one foggy and makes it impossible to think clearly or make the correct decision. However, some people enjoy fear and gain pleasure due to the adrenaline rush experienced in some situations.

Fear will hold one back from achieving victories and significant accomplishments. Everything that one does in life will strike a little bit of fear in their hearts; however, overcoming the fear and giving one’s best is the most satisfying feeling. Don’t let your fears stop you from fulfilling your dreams.

10 Lines on Fear Essay in English

1. Researches have shown that humans can smell others’ fear and react to each other’s scents. 2. One can inherit fear from their parents or grandparents just like any other genetic trait. 3. We humans aren’t born with most of the fears; fear is often learned from knowledge and experience. 4. Fear is the opposite of love as the brain releases chemical oxytocin when in love, which helps overcome learned fears. 5. Sleep offers a unique state in which selected fears can be eliminated. 6. One big scary event in one’s life is not what causes fear; instead, it is a mixture of environment and genetics. 7. Fear can become extinct by associating non-fearful memories with the event. 8. Stress hormones released by humans helps in enhancing the extinction of fear. 9. Some people associate fears with pleasure – the thrill of the experience doesn’t end with the process’s end. 10. Fear can make one foggy making it difficult to make the right decision or think clearly.

FAQ’s on Fear Essay

Question 1.  Why do we experience fear?

Answer: Fear is an unavoidable feeling that is experienced by all. Fear is programmed into humans’ nervous system, and it works like a response to the perception of danger.

Question 2. Is it necessary to experience fear?

Answer: Fear helps in protecting us. Humans are equipped with survival and instinct, which is a response to the sense of danger or an unsafe feeling.

Question 3.  How can fear be avoided?

Answer: Talking about your fear, imagining the worst that could happen, distracting oneself with happy thoughts, and clearing out the mind by taking time in understanding what is causing the fear and anxiety.

Question 4. What are a few most common fears of humans?

Answer: Fear of height, fear of the dark, fear of closed spaces, fear of insects, fear of blood, fear of the violent weather, fear of dying are a few most common types of fear experienced by people.

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Home — Essay Samples — Life — Fear — The Causes And Effects Of Fear

The Causes and Effects of Fear

• Categories: Fear Feeling

About this sample

Words: 569 |

Published: Feb 8, 2022

Words: 569 | Page: 1 | 3 min read

Works Cited:

• Chen, K. (2004). Chinese silk: A cultural history. Hong Kong: Hong Kong University Press.
• Chinese Silk Association. (2020). Chinese Silk Association. Retrieved from https://www.silk.org.cn/index.html
• Kuhn, D. (2009). The age of Confucian rule: The Song transformation of China. Cambridge, MA: Harvard University Press.
• Liu, X. (2012). The silk road in world history. Oxford: Oxford University Press.
• Mazumdar, S. (2015). Silk textiles of India. London: Bloomsbury Academic.
• Ministry of Culture and Tourism of the People's Republic of China. (2020). Silk Road. Retrieved from http://en.silkroad.org.cn/
• Park, J., & Han, D. (2019). Historical review on the characteristics and manufacturing process of silk. Journal of Textile and Apparel, Technology and Management, 11(3), 1-22.
• Tong, X. (2016). A history of silk: The history of China's legendary silk cloth, from its creation to the 21st century. London: Academic Press.
• Wei, L., & Lai, W. (2013). Analysis of the production and export of silk in ancient China. The Journal of International Trade & Economic Development, 22(4), 488-503.
• Yang, Y. (2014). Exploring the silk road. New York: China Institute Gallery.

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Fear: Definition, Effects, and Overcoming Essay

• To find inspiration for your paper and overcome writer’s block
• As a source of information (ensure proper referencing)
• As a template for you assignment

Effects of fear

How to overcome fear.

Webster’s dictionary defines fear as “an unpleasant, sometimes strong emotion caused by an anticipation or awareness of danger” or “anxious concern” Fear is a feeling that causes agitation and anxiety mostly caused by presence or imminence of danger. It is a state or condition marked by feeling of agitation or anxiety. It can also be described as a feeling of disquiet. Fear is an abstract concept and may have different meanings. Holder (2007) adds that fear is more pervasive when there is lack of faith that we have greater significance in the universe than what we own or how others perceive us.

Fear is manifested in many ways in human beings. It may manifest as showing signs of withdrawing or by cowering. But the most profound manifestation of fear is anger and hatred. People acts out their insecurity as anger which shows that they are the most fearful people.

Effects of fear have been documented in many studies. Fear has been documented to case mind paralyses, heart attacks and closure of fallopian tube due to fear of pain during child birth (Jim Rohn, 2004), describes fear, indifference, indecision, doubt, worry and timidness as the five greatest enemies within us which can destroy our lives completely. Fear may manifest itself in physical short term effects or affect your whole life. It will affect both he physiology of the body and the brain. Fear generates stress which manifests itself physically in many signs physically and emotionally. It causes judgmental errors and affects our reasoning that most of time when we are in a fearful situation; we tend to take the wrong action.

According to Sidney B., (1988), fear is a great paralyzer. It will keep you from making positive changes in your life and thus retard your recovery from depression. He continues to argue that fear persuades you to set easier goals and do less than your capability. It will also cause internal defense system fooling you that you have good reasons not to change. Fear of failure reduces the available alternatives you can pursue because you cannot stand by the outcome of what you do. You always feel that you cannot succeed in anything you try. It will keep you away from seeking help because you don’t want others to see you as a failure. Fear has been identified by psychologist as what causes people to give up when they are one step short to their goal. It will keep you stuck or make you develop unhealthy habits and behavior problems. Most of all fear keeps many people from taking risks.

Rim Rohn, (2004), argues that we are not born with courage, neither are we born with fear. He argues that some of our fears are brought on by our own experiences by what someone has told us or what we read in papers and books. Sri Swami Sivananda, (2007), describes fear as an illusion that cannot live. He suggests that to overcome fear we should always feel the presence of a Supreme Being watching us, by meditating and developing positive thoughts all the time. We should devote ourselves to eradicating fear. Since we have seen that fear is developed within our minds, it can also be eradicated within our mind and hence it is just a matter of reconditioning our minds that will help us overcome fear. It is also suggesting that we should share with others our fears. In this way they will help us find solutions to the cause of fears. President Roosevelt said, “We have nothing to fear but the fear itself” hence fearing fear starts and ends with us.

Holder P. (2007): FEAR… YOUR WORST ENEMY . Web.

Rohn, J., (2004). Build courage to face the enemies within. Web.

Sidney S., (1998). Getting Unstuck: Breaking through Your Barriers to Change . Web.

Sri Sivanand, S. (2007). The Divine Life Society: How to overcome fear. Web.

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IvyPanda. (2021, September 3). Fear: Definition, Effects, and Overcoming. https://ivypanda.com/essays/fear-definition-effects-and-overcoming/

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Thesis Statements

What this handout is about.

This handout describes what a thesis statement is, how thesis statements work in your writing, and how you can craft or refine one for your draft.

Introduction

Writing in college often takes the form of persuasion—convincing others that you have an interesting, logical point of view on the subject you are studying. Persuasion is a skill you practice regularly in your daily life. You persuade your roommate to clean up, your parents to let you borrow the car, your friend to vote for your favorite candidate or policy. In college, course assignments often ask you to make a persuasive case in writing. You are asked to convince your reader of your point of view. This form of persuasion, often called academic argument, follows a predictable pattern in writing. After a brief introduction of your topic, you state your point of view on the topic directly and often in one sentence. This sentence is the thesis statement, and it serves as a summary of the argument you’ll make in the rest of your paper.

What is a thesis statement?

A thesis statement:

• tells the reader how you will interpret the significance of the subject matter under discussion.
• is a road map for the paper; in other words, it tells the reader what to expect from the rest of the paper.
• directly answers the question asked of you. A thesis is an interpretation of a question or subject, not the subject itself. The subject, or topic, of an essay might be World War II or Moby Dick; a thesis must then offer a way to understand the war or the novel.
• makes a claim that others might dispute.
• is usually a single sentence near the beginning of your paper (most often, at the end of the first paragraph) that presents your argument to the reader. The rest of the paper, the body of the essay, gathers and organizes evidence that will persuade the reader of the logic of your interpretation.

If your assignment asks you to take a position or develop a claim about a subject, you may need to convey that position or claim in a thesis statement near the beginning of your draft. The assignment may not explicitly state that you need a thesis statement because your instructor may assume you will include one. When in doubt, ask your instructor if the assignment requires a thesis statement. When an assignment asks you to analyze, to interpret, to compare and contrast, to demonstrate cause and effect, or to take a stand on an issue, it is likely that you are being asked to develop a thesis and to support it persuasively. (Check out our handout on understanding assignments for more information.)

How do I create a thesis?

A thesis is the result of a lengthy thinking process. Formulating a thesis is not the first thing you do after reading an essay assignment. Before you develop an argument on any topic, you have to collect and organize evidence, look for possible relationships between known facts (such as surprising contrasts or similarities), and think about the significance of these relationships. Once you do this thinking, you will probably have a “working thesis” that presents a basic or main idea and an argument that you think you can support with evidence. Both the argument and your thesis are likely to need adjustment along the way.

Writers use all kinds of techniques to stimulate their thinking and to help them clarify relationships or comprehend the broader significance of a topic and arrive at a thesis statement. For more ideas on how to get started, see our handout on brainstorming .

How do I know if my thesis is strong?

If there’s time, run it by your instructor or make an appointment at the Writing Center to get some feedback. Even if you do not have time to get advice elsewhere, you can do some thesis evaluation of your own. When reviewing your first draft and its working thesis, ask yourself the following :

• Do I answer the question? Re-reading the question prompt after constructing a working thesis can help you fix an argument that misses the focus of the question. If the prompt isn’t phrased as a question, try to rephrase it. For example, “Discuss the effect of X on Y” can be rephrased as “What is the effect of X on Y?”
• Have I taken a position that others might challenge or oppose? If your thesis simply states facts that no one would, or even could, disagree with, it’s possible that you are simply providing a summary, rather than making an argument.
• Is my thesis statement specific enough? Thesis statements that are too vague often do not have a strong argument. If your thesis contains words like “good” or “successful,” see if you could be more specific: why is something “good”; what specifically makes something “successful”?
• Does my thesis pass the “So what?” test? If a reader’s first response is likely to  be “So what?” then you need to clarify, to forge a relationship, or to connect to a larger issue.
• Does my essay support my thesis specifically and without wandering? If your thesis and the body of your essay do not seem to go together, one of them has to change. It’s okay to change your working thesis to reflect things you have figured out in the course of writing your paper. Remember, always reassess and revise your writing as necessary.
• Does my thesis pass the “how and why?” test? If a reader’s first response is “how?” or “why?” your thesis may be too open-ended and lack guidance for the reader. See what you can add to give the reader a better take on your position right from the beginning.

Suppose you are taking a course on contemporary communication, and the instructor hands out the following essay assignment: “Discuss the impact of social media on public awareness.” Looking back at your notes, you might start with this working thesis:

Social media impacts public awareness in both positive and negative ways.

You can use the questions above to help you revise this general statement into a stronger thesis.

• Do I answer the question? You can analyze this if you rephrase “discuss the impact” as “what is the impact?” This way, you can see that you’ve answered the question only very generally with the vague “positive and negative ways.”
• Have I taken a position that others might challenge or oppose? Not likely. Only people who maintain that social media has a solely positive or solely negative impact could disagree.
• Is my thesis statement specific enough? No. What are the positive effects? What are the negative effects?
• Does my thesis pass the “how and why?” test? No. Why are they positive? How are they positive? What are their causes? Why are they negative? How are they negative? What are their causes?
• Does my thesis pass the “So what?” test? No. Why should anyone care about the positive and/or negative impact of social media?

After thinking about your answers to these questions, you decide to focus on the one impact you feel strongly about and have strong evidence for:

Because not every voice on social media is reliable, people have become much more critical consumers of information, and thus, more informed voters.

This version is a much stronger thesis! It answers the question, takes a specific position that others can challenge, and it gives a sense of why it matters.

Let’s try another. Suppose your literature professor hands out the following assignment in a class on the American novel: Write an analysis of some aspect of Mark Twain’s novel Huckleberry Finn. “This will be easy,” you think. “I loved Huckleberry Finn!” You grab a pad of paper and write:

Mark Twain’s Huckleberry Finn is a great American novel.

You begin to analyze your thesis:

• Do I answer the question? No. The prompt asks you to analyze some aspect of the novel. Your working thesis is a statement of general appreciation for the entire novel.

Think about aspects of the novel that are important to its structure or meaning—for example, the role of storytelling, the contrasting scenes between the shore and the river, or the relationships between adults and children. Now you write:

In Huckleberry Finn, Mark Twain develops a contrast between life on the river and life on the shore.

• Do I answer the question? Yes!
• Have I taken a position that others might challenge or oppose? Not really. This contrast is well-known and accepted.
• Is my thesis statement specific enough? It’s getting there–you have highlighted an important aspect of the novel for investigation. However, it’s still not clear what your analysis will reveal.
• Does my thesis pass the “how and why?” test? Not yet. Compare scenes from the book and see what you discover. Free write, make lists, jot down Huck’s actions and reactions and anything else that seems interesting.
• Does my thesis pass the “So what?” test? What’s the point of this contrast? What does it signify?”

After examining the evidence and considering your own insights, you write:

Through its contrasting river and shore scenes, Twain’s Huckleberry Finn suggests that to find the true expression of American democratic ideals, one must leave “civilized” society and go back to nature.

This final thesis statement presents an interpretation of a literary work based on an analysis of its content. Of course, for the essay itself to be successful, you must now present evidence from the novel that will convince the reader of your interpretation.

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

Anson, Chris M., and Robert A. Schwegler. 2010. The Longman Handbook for Writers and Readers , 6th ed. New York: Longman.

Lunsford, Andrea A. 2015. The St. Martin’s Handbook , 8th ed. Boston: Bedford/St Martin’s.

Ramage, John D., John C. Bean, and June Johnson. 2018. The Allyn & Bacon Guide to Writing , 8th ed. New York: Pearson.

Ruszkiewicz, John J., Christy Friend, Daniel Seward, and Maxine Hairston. 2010. The Scott, Foresman Handbook for Writers , 9th ed. Boston: Pearson Education.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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How to Write a Strong Thesis Statement: 4 Steps + Examples

What’s Covered:

What is the purpose of a thesis statement, writing a good thesis statement: 4 steps, common pitfalls to avoid, where to get your essay edited for free.

When you set out to write an essay, there has to be some kind of point to it, right? Otherwise, your essay would just be a big jumble of word salad that makes absolutely no sense. An essay needs a central point that ties into everything else. That main point is called a thesis statement, and it’s the core of any essay or research paper.

You may hear about Master degree candidates writing a thesis, and that is an entire paper–not to be confused with the thesis statement, which is typically one sentence that contains your paper’s focus. 

Read on to learn more about thesis statements and how to write them. We’ve also included some solid examples for you to reference.

Typically the last sentence of your introductory paragraph, the thesis statement serves as the roadmap for your essay. When your reader gets to the thesis statement, they should have a clear outline of your main point, as well as the information you’ll be presenting in order to either prove or support your point. 

The thesis statement should not be confused for a topic sentence , which is the first sentence of every paragraph in your essay. If you need help writing topic sentences, numerous resources are available. Topic sentences should go along with your thesis statement, though.

Since the thesis statement is the most important sentence of your entire essay or paper, it’s imperative that you get this part right. Otherwise, your paper will not have a good flow and will seem disjointed. That’s why it’s vital not to rush through developing one. It’s a methodical process with steps that you need to follow in order to create the best thesis statement possible.

Step 1: Decide what kind of paper you’re writing

When you’re assigned an essay, there are several different types you may get. Argumentative essays are designed to get the reader to agree with you on a topic. Informative or expository essays present information to the reader. Analytical essays offer up a point and then expand on it by analyzing relevant information. Thesis statements can look and sound different based on the type of paper you’re writing. For example:

• Argumentative: The United States needs a viable third political party to decrease bipartisanship, increase options, and help reduce corruption in government.
• Informative: The Libertarian party has thrown off elections before by gaining enough support in states to get on the ballot and by taking away crucial votes from candidates.
• Analytical: An analysis of past presidential elections shows that while third party votes may have been the minority, they did affect the outcome of the elections in 2020, 2016, and beyond.

Step 2: Figure out what point you want to make

Once you know what type of paper you’re writing, you then need to figure out the point you want to make with your thesis statement, and subsequently, your paper. In other words, you need to decide to answer a question about something, such as:

• What impact did reality TV have on American society?
• How has the musical Hamilton affected perception of American history?
• Why do I want to major in [chosen major here]?

If you have an argumentative essay, then you will be writing about an opinion. To make it easier, you may want to choose an opinion that you feel passionate about so that you’re writing about something that interests you. For example, if you have an interest in preserving the environment, you may want to choose a topic that relates to that. 

If you’re writing your college essay and they ask why you want to attend that school, you may want to have a main point and back it up with information, something along the lines of:

“Attending Harvard University would benefit me both academically and professionally, as it would give me a strong knowledge base upon which to build my career, develop my network, and hopefully give me an advantage in my chosen field.”

Step 3: Determine what information you’ll use to back up your point

Once you have the point you want to make, you need to figure out how you plan to back it up throughout the rest of your essay. Without this information, it will be hard to either prove or argue the main point of your thesis statement. If you decide to write about the Hamilton example, you may decide to address any falsehoods that the writer put into the musical, such as:

“The musical Hamilton, while accurate in many ways, leaves out key parts of American history, presents a nationalist view of founding fathers, and downplays the racism of the times.”

Once you’ve written your initial working thesis statement, you’ll then need to get information to back that up. For example, the musical completely leaves out Benjamin Franklin, portrays the founding fathers in a nationalist way that is too complimentary, and shows Hamilton as a staunch abolitionist despite the fact that his family likely did own slaves. 

Step 4: Revise and refine your thesis statement before you start writing

Read through your thesis statement several times before you begin to compose your full essay. You need to make sure the statement is ironclad, since it is the foundation of the entire paper. Edit it or have a peer review it for you to make sure everything makes sense and that you feel like you can truly write a paper on the topic. Once you’ve done that, you can then begin writing your paper.

When writing a thesis statement, there are some common pitfalls you should avoid so that your paper can be as solid as possible. Make sure you always edit the thesis statement before you do anything else. You also want to ensure that the thesis statement is clear and concise. Don’t make your reader hunt for your point. Finally, put your thesis statement at the end of the first paragraph and have your introduction flow toward that statement. Your reader will expect to find your statement in its traditional spot.

If you’re having trouble getting started, or need some guidance on your essay, there are tools available that can help you. CollegeVine offers a free peer essay review tool where one of your peers can read through your essay and provide you with valuable feedback. Getting essay feedback from a peer can help you wow your instructor or college admissions officer with an impactful essay that effectively illustrates your point.

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Tips and Examples for Writing Thesis Statements

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Tips for Writing Your Thesis Statement

1. Determine what kind of paper you are writing:

• An analytical paper breaks down an issue or an idea into its component parts, evaluates the issue or idea, and presents this breakdown and evaluation to the audience.
• An expository (explanatory) paper explains something to the audience.
• An argumentative paper makes a claim about a topic and justifies this claim with specific evidence. The claim could be an opinion, a policy proposal, an evaluation, a cause-and-effect statement, or an interpretation. The goal of the argumentative paper is to convince the audience that the claim is true based on the evidence provided.

If you are writing a text that does not fall under these three categories (e.g., a narrative), a thesis statement somewhere in the first paragraph could still be helpful to your reader.

2. Your thesis statement should be specific—it should cover only what you will discuss in your paper and should be supported with specific evidence.

3. The thesis statement usually appears at the end of the first paragraph of a paper.

4. Your topic may change as you write, so you may need to revise your thesis statement to reflect exactly what you have discussed in the paper.

Thesis Statement Examples

Example of an analytical thesis statement:

The paper that follows should:

• Explain the analysis of the college admission process
• Explain the challenge facing admissions counselors

Example of an expository (explanatory) thesis statement:

• Explain how students spend their time studying, attending class, and socializing with peers

Example of an argumentative thesis statement:

• Present an argument and give evidence to support the claim that students should pursue community projects before entering college

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• Knowledge Base
• How to Write a Thesis Statement | 4 Steps & Examples

How to Write a Thesis Statement | 4 Steps & Examples

Published on January 11, 2019 by Shona McCombes . Revised on August 15, 2023 by Eoghan Ryan.

A thesis statement is a sentence that sums up the central point of your paper or essay . It usually comes near the end of your introduction .

Your thesis will look a bit different depending on the type of essay you’re writing. But the thesis statement should always clearly state the main idea you want to get across. Everything else in your essay should relate back to this idea.

You can write your thesis statement by following four simple steps:

• Start with a question
• Write your initial answer
• Develop your answer
• Refine your thesis statement

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Table of contents

What is a thesis statement, placement of the thesis statement, step 1: start with a question, step 2: write your initial answer, step 3: develop your answer, step 4: refine your thesis statement, types of thesis statements, other interesting articles, frequently asked questions about thesis statements.

A thesis statement summarizes the central points of your essay. It is a signpost telling the reader what the essay will argue and why.

The best thesis statements are:

• Concise: A good thesis statement is short and sweet—don’t use more words than necessary. State your point clearly and directly in one or two sentences.
• Contentious: Your thesis shouldn’t be a simple statement of fact that everyone already knows. A good thesis statement is a claim that requires further evidence or analysis to back it up.
• Coherent: Everything mentioned in your thesis statement must be supported and explained in the rest of your paper.

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The thesis statement generally appears at the end of your essay introduction or research paper introduction .

The spread of the internet has had a world-changing effect, not least on the world of education. The use of the internet in academic contexts and among young people more generally is hotly debated. For many who did not grow up with this technology, its effects seem alarming and potentially harmful. This concern, while understandable, is misguided. The negatives of internet use are outweighed by its many benefits for education: the internet facilitates easier access to information, exposure to different perspectives, and a flexible learning environment for both students and teachers.

You should come up with an initial thesis, sometimes called a working thesis , early in the writing process . As soon as you’ve decided on your essay topic , you need to work out what you want to say about it—a clear thesis will give your essay direction and structure.

You might already have a question in your assignment, but if not, try to come up with your own. What would you like to find out or decide about your topic?

For example, you might ask:

After some initial research, you can formulate a tentative answer to this question. At this stage it can be simple, and it should guide the research process and writing process .

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Now you need to consider why this is your answer and how you will convince your reader to agree with you. As you read more about your topic and begin writing, your answer should get more detailed.

In your essay about the internet and education, the thesis states your position and sketches out the key arguments you’ll use to support it.

The negatives of internet use are outweighed by its many benefits for education because it facilitates easier access to information.

In your essay about braille, the thesis statement summarizes the key historical development that you’ll explain.

The invention of braille in the 19th century transformed the lives of blind people, allowing them to participate more actively in public life.

A strong thesis statement should tell the reader:

• Why you hold this position
• What they’ll learn from your essay
• The key points of your argument or narrative

The final thesis statement doesn’t just state your position, but summarizes your overall argument or the entire topic you’re going to explain. To strengthen a weak thesis statement, it can help to consider the broader context of your topic.

These examples are more specific and show that you’ll explore your topic in depth.

Your thesis statement should match the goals of your essay, which vary depending on the type of essay you’re writing:

• In an argumentative essay , your thesis statement should take a strong position. Your aim in the essay is to convince your reader of this thesis based on evidence and logical reasoning.
• In an expository essay , you’ll aim to explain the facts of a topic or process. Your thesis statement doesn’t have to include a strong opinion in this case, but it should clearly state the central point you want to make, and mention the key elements you’ll explain.

If you want to know more about AI tools , college essays , or fallacies make sure to check out some of our other articles with explanations and examples or go directly to our tools!

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A thesis statement is a sentence that sums up the central point of your paper or essay . Everything else you write should relate to this key idea.

The thesis statement is essential in any academic essay or research paper for two main reasons:

• It gives your writing direction and focus.
• It gives the reader a concise summary of your main point.

Without a clear thesis statement, an essay can end up rambling and unfocused, leaving your reader unsure of exactly what you want to say.

Follow these four steps to come up with a thesis statement :

• Ask a question about your topic .
• Write your initial answer.
• Develop your answer by including reasons.
• Refine your answer, adding more detail and nuance.

The thesis statement should be placed at the end of your essay introduction .

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25 Thesis Statement Examples

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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A thesis statement is needed in an essay or dissertation . There are multiple types of thesis statements – but generally we can divide them into expository and argumentative. An expository statement is a statement of fact (common in expository essays and process essays) while an argumentative statement is a statement of opinion (common in argumentative essays and dissertations). Below are examples of each.

Strong Thesis Statement Examples

1. School Uniforms

“Mandatory school uniforms should be implemented in educational institutions as they promote a sense of equality, reduce distractions, and foster a focused and professional learning environment.”

Best For: Argumentative Essay or Debate

Read More: School Uniforms Pros and Cons

2. Nature vs Nurture

“This essay will explore how both genetic inheritance and environmental factors equally contribute to shaping human behavior and personality.”

Best For: Compare and Contrast Essay

Read More: Nature vs Nurture Debate

3. American Dream

“The American Dream, a symbol of opportunity and success, is increasingly elusive in today’s socio-economic landscape, revealing deeper inequalities in society.”

Best For: Persuasive Essay

Read More: What is the American Dream?

4. Social Media

“Social media has revolutionized communication and societal interactions, but it also presents significant challenges related to privacy, mental health, and misinformation.”

Best For: Expository Essay

Read More: The Pros and Cons of Social Media

5. Globalization

“Globalization has created a world more interconnected than ever before, yet it also amplifies economic disparities and cultural homogenization.”

Read More: Globalization Pros and Cons

6. Urbanization

“Urbanization drives economic growth and social development, but it also poses unique challenges in sustainability and quality of life.”

Read More: Learn about Urbanization

7. Immigration

“Immigration enriches receiving countries culturally and economically, outweighing any perceived social or economic burdens.”

Read More: Immigration Pros and Cons

8. Cultural Identity

“In a globalized world, maintaining distinct cultural identities is crucial for preserving cultural diversity and fostering global understanding, despite the challenges of assimilation and homogenization.”

Best For: Argumentative Essay

Read More: Learn about Cultural Identity

9. Technology

“Medical technologies in care institutions in Toronto has increased subjcetive outcomes for patients with chronic pain.”

Best For: Research Paper

10. Capitalism vs Socialism

“The debate between capitalism and socialism centers on balancing economic freedom and inequality, each presenting distinct approaches to resource distribution and social welfare.”

11. Cultural Heritage

“The preservation of cultural heritage is essential, not only for cultural identity but also for educating future generations, outweighing the arguments for modernization and commercialization.”

12. Pseudoscience

“Pseudoscience, characterized by a lack of empirical support, continues to influence public perception and decision-making, often at the expense of scientific credibility.”

Read More: Examples of Pseudoscience

13. Free Will

“The concept of free will is largely an illusion, with human behavior and decisions predominantly determined by biological and environmental factors.”

Read More: Do we have Free Will?

14. Gender Roles

“Traditional gender roles are outdated and harmful, restricting individual freedoms and perpetuating gender inequalities in modern society.”

Read More: What are Traditional Gender Roles?

15. Work-Life Ballance

“The trend to online and distance work in the 2020s led to improved subjective feelings of work-life balance but simultaneously increased self-reported loneliness.”

Read More: Work-Life Balance Examples

16. Universal Healthcare

“Universal healthcare is a fundamental human right and the most effective system for ensuring health equity and societal well-being, outweighing concerns about government involvement and costs.”

Read More: The Pros and Cons of Universal Healthcare

17. Minimum Wage

“The implementation of a fair minimum wage is vital for reducing economic inequality, yet it is often contentious due to its potential impact on businesses and employment rates.”

Read More: The Pros and Cons of Raising the Minimum Wage

18. Homework

“The homework provided throughout this semester has enabled me to achieve greater self-reflection, identify gaps in my knowledge, and reinforce those gaps through spaced repetition.”

Best For: Reflective Essay

Read More: Reasons Homework Should be Banned

19. Charter Schools

“Charter schools offer alternatives to traditional public education, promising innovation and choice but also raising questions about accountability and educational equity.”

Read More: The Pros and Cons of Charter Schools

20. Effects of the Internet

“The Internet has drastically reshaped human communication, access to information, and societal dynamics, generally with a net positive effect on society.”

Read More: The Pros and Cons of the Internet

21. Affirmative Action

“Affirmative action is essential for rectifying historical injustices and achieving true meritocracy in education and employment, contrary to claims of reverse discrimination.”

Best For: Essay

Read More: Affirmative Action Pros and Cons

22. Soft Skills

“Soft skills, such as communication and empathy, are increasingly recognized as essential for success in the modern workforce, and therefore should be a strong focus at school and university level.”

Read More: Soft Skills Examples

23. Moral Panic

“Moral panic, often fueled by media and cultural anxieties, can lead to exaggerated societal responses that sometimes overlook rational analysis and evidence.”

Read More: Moral Panic Examples

24. Freedom of the Press

“Freedom of the press is critical for democracy and informed citizenship, yet it faces challenges from censorship, media bias, and the proliferation of misinformation.”

Read More: Freedom of the Press Examples

25. Mass Media

“Mass media shapes public opinion and cultural norms, but its concentration of ownership and commercial interests raise concerns about bias and the quality of information.”

Best For: Critical Analysis

Read More: Mass Media Examples

Checklist: How to use your Thesis Statement

✅ Position: If your statement is for an argumentative or persuasive essay, or a dissertation, ensure it takes a clear stance on the topic. ✅ Specificity: It addresses a specific aspect of the topic, providing focus for the essay. ✅ Conciseness: Typically, a thesis statement is one to two sentences long. It should be concise, clear, and easily identifiable. ✅ Direction: The thesis statement guides the direction of the essay, providing a roadmap for the argument, narrative, or explanation. ✅ Evidence-based: While the thesis statement itself doesn’t include evidence, it sets up an argument that can be supported with evidence in the body of the essay. ✅ Placement: Generally, the thesis statement is placed at the end of the introduction of an essay.

Try These AI Prompts – Thesis Statement Generator!

One way to brainstorm thesis statements is to get AI to brainstorm some for you! Try this AI prompt:

💡 AI PROMPT FOR EXPOSITORY THESIS STATEMENT I am writing an essay on [TOPIC] and these are the instructions my teacher gave me: [INSTUCTIONS]. I want you to create an expository thesis statement that doesn’t argue a position, but demonstrates depth of knowledge about the topic.

💡 AI PROMPT FOR ARGUMENTATIVE THESIS STATEMENT I am writing an essay on [TOPIC] and these are the instructions my teacher gave me: [INSTRUCTIONS]. I want you to create an argumentative thesis statement that clearly takes a position on this issue.

💡 AI PROMPT FOR COMPARE AND CONTRAST THESIS STATEMENT I am writing a compare and contrast essay that compares [Concept 1] and [Concept2]. Give me 5 potential single-sentence thesis statements that remain objective.

• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 25 Number Games for Kids (Free and Easy)
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 25 Word Games for Kids (Free and Easy)
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 25 Outdoor Games for Kids
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 50 Incentives to Give to Students

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Appealing to fear: A Meta-Analysis of Fear Appeal Effectiveness and Theories

Melanie b. tannenbaum.

University of Illinois at Urbana-Champaign

Justin Hepler

University of Nevada, Reno

Rick S. Zimmerman

University of Missouri – St. Louis

Lindsey Saul

Virginia Commonwealth University

Samantha Jacobs

Kristina wilson, dolores albarracin.

Fear appeals are a polarizing issue, with proponents confident in their efficacy and opponents confident that they backfire. We present the results of a comprehensive meta-analysis investigating fear appeals’ effectiveness for influencing attitudes, intentions, and behaviors. We tested predictions from a large number of theories, the majority of which have never been tested meta-analytically until now. Studies were included if they contained a treatment group exposed to a fear appeal, a valid comparison group, a manipulation of depicted fear, a measure of attitudes, intentions, or behaviors concerning the targeted risk or recommended solution, and adequate statistics to calculate effect sizes. The meta-analysis included 127 papers (9% unpublished) yielding 248 independent samples (N Total = 27,372) collected from diverse populations. Results showed a positive effect of fear appeals on attitudes, intentions, and behaviors, with the average effect on a composite index being random-effects d ¯ = 0.29. Moderation analyses based on prominent fear appeal theories showed that the effectiveness of fear appeals increased when the message included efficacy statements, depicted high susceptibility and severity, recommended one-time only (vs. repeated) behaviors, and targeted audiences that included a larger percentage of female message recipients. Overall, we conclude that (a) fear appeals are effective at positively influencing attitude, intentions, and behaviors, (b) there are very few circumstances under which they are not effective, and (c) there are no identified circumstances under which they backfire and lead to undesirable outcomes.

Fear appeals are persuasive messages that attempt to arouse fear by emphasizing the potential danger and harm that will befall individuals if they do not adopt the messages’ recommendations ( Dillard, 1996 ; Maddux & Rogers, 1983 ). Although these messages are often used in political, public health, and advertising campaigns in the hopes of reducing risky attitudes, intentions, or behaviors, their use is often a polarizing issue. Whereas some practitioners are confident in the power of fear appeals to persuade audiences (e.g., CDC, 2014 ; Xu et al., 2015 ), others are adamant that such messages are counterproductive (e.g., Drug Free Action Alliance, 2013 ; Ruiter et al., 2014 ). The fear appeal literature reflects this disagreement, and empirical studies, literature reviews, and meta-analyses conducted over the past six decades have offered a diverse array of perspectives on the topic. Although some meta-analytic examinations have found positive effects of fear appeals on some outcomes ( Witte & Allen, 2000 ), others have found null effects ( de Hoog et al., 2007 ) or even negative effects ( Peters et al., 2012 ). In the current paper, we present the results of a comprehensive meta-analysis of fear appeal research with two goals in mind. Our first goal was to compile the largest available meta-analytic database of fear appeal research and estimate average effects. Our second goal was to test a variety of theoretical predictions, many of which have never been examined meta-analytically, and to organize them within a framework that takes into account characteristics of a fear appeal’s message, recommended behavior, and audience.

Existing theories about fear appeals have focused on either the content of the message , the nature of the behavior recommended by the communication, or the characteristics of the audience receiving the message. However, all three of these aspects (message, behavior, and audience) are important and were considered in the framework that guided this review. This integrative framework gave our meta-analysis a broader scope beyond past analyses of fear appeals. Specifically, each prior meta-analysis has only tested theories relevant to the message portion of our framework, and thus was only able to address a limited set of questions pertaining to fear appeal effectiveness (for a description of prior meta-analyses, see Table 1 ) ( Boster & Mongeau, 1984 ; de Hoog et al., 2007 ; Earl & Albarracin, 2007 ; Floyd et al., 2000 ; Milne et al., 2000 ; Peters et al., 2012 ; Sutton, 1982 ; Witte & Allen, 2000 ). By adopting this more holistic view of fear appeals, we connected existing models that are generally treated as separate and examined novel hypotheses about fear appeal effectiveness that have previously gone untested. Further, the current meta-analysis used a substantially larger meta-analytic database than prior analyses, thus providing us with more precision to test relevant hypotheses.

Theories and hypotheses tested.

Note: LM = Linear Model. CM = Curvilinear Model. ES = Efficacy Statements. SM = Stage Model. RSAT = Robertson’s Single Action Theory. PT = Prospect Theory. TMT = Terror Management Theory. RFT = Regulatory Focus Theory. TM = Transtheoretical Model. SEE = Self-esteem enhancing. SEH = Self-esteem hindering.

The Content of Fear Appeals

Six prominent theories make predictions about the impact of message characteristics on fear appeal effectiveness 1 : The linear model of fear appeals (e.g., Witte & Allen, 2000 ), the curvilinear model of fear appeals (e.g., Hovland et al., 1953 ), the health belief model ( Rosenstock, 1966 ; Becker, 1974 ; Becker et al., 1977 ; Becker et al., 1978 ; Rosenstock, 1974 ), the parallel process model ( Leventhal, 1970 ), the extended parallel process model ( Witte, 1992 ; Witte, 1998 ), and the stage model ( de Hoog et al., 2007 ). These theories concern the level of depicted fear within messages, the use (or omission) of efficacy statements within messages, and the level of depicted susceptibility and/or severity within messages.

Amount of depicted fear

Perhaps the most central aspect of a fear appeal message is the amount of fear it is intended to arouse in message recipients. We will refer to this as depicted fear to emphasize that it reflects a property of the message’s content, rather than the subjective state of fear that message recipients experience. 2 Two competing theories make predictions about amount of depicted fear, which we will refer to as the linear model (e.g., Witte & Allen, 2000 ) and the curvilinear model ( Hovland et al., 1953 ; Janis, 1967 ; Janis & Feshbach, 1953 ; McGuire, 1968 ; McGuire, 1969 ). Both theoretical perspectives conceptualize depicted fear as a source of motivation, such that exposure to depicted fear increases motivation to adopt the message’s recommendations ( Hovland et al., 1953 ; Witte & Allen, 2000 ). Further, both models predict that low levels of depicted fear will be relatively less motivating and thus less effective than moderate levels of fear. However, the linear model predicts that depicted fear has a positive and monotonic influences on attitudes, intentions, and behaviors, such that high depicted fear is more effective than moderate depicted fear (e.g., Witte & Allen, 2000 ). In contrast, the curvilinear model predicts that high depicted fear elicits defensive avoidance, a reaction in which message recipients disengage from the message, avoid further exposure to the message, and/or derogate the message because it is too frightening ( Higbee, 1969 ; Hovland et al., 1953 ; Janis, 1967 ; 1968 ; Janis & Feshbach, 1953 ; Janis & Leventhal, 1968 ; McGuire, 1968 ; 1969 ; Millman, 1968 ). Consequently, the curvilinear theory predicts that high levels of depicted fear should be less effective than moderate levels of depicted fear.

The linear and curvilinear models have been tested in prior meta-analyses, and the linear model has consistently been supported by existing data, whereas the curvilinear model has not (e.g., Witte & Allen, 2000 ). One drawback to prior investigations of the linear and curvilinear models is that the analyses included comparisons from studies that used two levels of depicted fear, even though it is difficult to equate levels of depicted fear across different studies – what may qualify as moderate depicted fear in one study may qualify as low depicted fear in a different study. Thus, an appropriate test of the linear and curvilinear models requires depicted fear to be manipulated with at least three levels within the same study to ensure that moderate depicted fear is operationalized as an intermediate level between extremes. We therefore tested the linear and curvilinear models in the current meta-analysis by comparing the effects of high versus moderate depicted fear, using only studies that manipulated depicted fear across several levels. The linear model predicts that high depicted fear will be more effective than moderate depicted fear, whereas the curvilinear model predicts that high depicted fear will be less effective than moderate depicted fear.

Efficacy statements

According to the health belief model (HBM; Rosenstock, 1966 ; Becker, 1974 ; Becker et al., 1977 ; Becker et al., 1978 ; Rosenstock, 1974 ), the stage model (e.g., de Hoog et al., 2007 ), the parallel process model (PPM; Leventhal, 1970 ), and the extended parallel process model (EPPM; Witte, 1992 ; Witte, 1998 ), fear appeals “work only when accompanied by… efficacy messages” ( Witte & Allen, 2000 , p.606). An efficacy message is a statement that assures message recipients that they are capable of performing the fear appeal’s recommended actions (self-efficacy) and/or that performing the recommended actions will result in desirable consequences (response-efficacy). The HBM, stage model, PPM, and EPPM suggest that when message recipients are presented with a threat (i.e., depicted fear), resulting feelings of vulnerability lead them to evaluate whether or not adopting the message’s recommendations will protect them from the threat-related negative consequences. If recipients decide that adopting the recommended action(s) will protect them, the fear appeal should be more effective. As efficacy statements provide this assurance, fear appeal messages that include statements about self- or response-efficacy should be more effective than fear appeal messages that include neither ( de Hoog et al., 2007 ; Witte & Allen, 2000 ).

There are two forms of the efficacy statement hypothesis. The strong hypothesis is that fear appeals without efficacy statements will produce negative effects (i.e., will backfire). The weak hypothesis is that fear appeals without efficacy statements will produce weaker (i.e., less positive or null) effects relative to fear appeals with efficacy statements. Three meta-analyses have tested whether the inclusion of efficacy statements in fear appeals leads to increased effectiveness, and all found support for the weak hypothesis ( de Hoog et al., 2007 ; Mongeau, 1998 ; Witte & Allen, 2000 ). However, those studies were conducted using less comprehensive meta-analytic databases, and thus the current synthesis can provide a more thorough assessment of the strong and weak hypotheses.

Depicted susceptibility and severity

According to the stage model ( de Hoog et al., 2007 ), the effectiveness of fear appeals should depend on their levels of depicted susceptibility and severity. A message high in depicted susceptibility emphasizes the message recipient’s personal risk for negative consequences (e.g., “One of fourteen women is destined to develop breast cancer during her life. So every woman may get breast cancer. You also run that risk!”; Siero et al., 1984 ), whereas a message low in depicted susceptibility does not personalize risk (e.g., “One of fourteen women is destined to develop breast cancer during her life.”; Siero et al., 1984 ). A message high in depicted severity describes the negative consequences of not taking action (e.g., “Breast cancer is a serious disease of which many women die, contrary to, for example, cancer of the uterus, where 90% to 95% recover.”; Siero et al., 1984 ), whereas a message low in depicted severity portrays manageable consequences (e.g., “If breast cancer is detected at an early stage it can be cured in a number of cases, contrary to, for example, lung cancer where 90% die of it.”; Siero et al., 1984 ). According to this model, high depicted severity (but not susceptibility) should improve attitudes, whereas high depicted susceptibility (but not severity) should improve intentions and behaviors. Consequently, only the combination of high-depicted susceptibility and severity should improve attitudes, intentions, and behaviors. A previous meta-analysis found mixed results concerning these predictions ( de Hoog et al., 2007 ). Specifically, messages with high depicted severity positively influenced attitudes, intentions, and behaviors, whereas messages with high depicted susceptibility positively influenced intentions and behaviors but not attitudes. We tested these hypotheses on our more comprehensive database.

Three prominent theories make predictions about the impact of the recommended behaviors on fear appeal effectiveness: Robertson’s single action theory ( Robertson, 1975 ; Rothman, Martino, Bedell, Detweiler, & Salovey, 1999 ), prospect theory ( Rothman et al., 1999 ; Rothman & Salovey, 1997 ; Tversky & Kahneman, 1981 ) and terror management theory ( Goldenberg & Arndt, 2008 ; Pyszczynski, Greenberg, & Solomon, 1999 ; Shehryar & Hunt, 2005 ; Solomon, Greenberg, & Pyszczynski, 1991 ). These theories concern whether the recommended behavior is a one-time or recurring activity, involves detection or prevention/promotion, occurs immediately or after a delay, can enhance self-esteem, and is intended to replace a self-esteem enhancing behavior.

One-time versus repeated behaviors

According to Robertson (1975 ; also see Rothman et al., 1999 ), persuasive messages should be more successful when they recommend one-time behaviors (e.g., getting vaccinated) compared to behaviors that must be repeated over an extended period of time (e.g., exercising). As it takes less effort to do something once than many times, people are likely to be more compliant when a single behavior is recommended. Using this principle, we compared the effectiveness of fear appeals recommending one-time versus repeated behaviors.

Detection versus prevention/promotion behaviors

According to prospect theory, negative outcomes can be categorized as incurring a loss or foregoing a gain, and losses tend to be more psychologically impactful than foregone gains of objectively equal magnitude ( Tversky & Kahneman, 1981 ). Several researchers have extended the logic of prospect theory to fear appeals, hypothesizing that fear appeals should be more effective when recommending detection behaviors relative to prevention/promotion behaviors ( Rothman, Martino, Bedell, Detweiler, & Salovey, 1999 ; Rothman & Salovey, 1997 ). Detection behaviors are enacted to obtain information about potential risk factors or existing health issues (e.g., being screened for cancer), and thus engaging in a detection behavior increases risk for incurring a loss (e.g., acquiring the unwanted and undesirable information that one has cancer). In contrast, prevention/promotion behaviors are enacted to obtain desirable outcomes (e.g., exercising to lose weight or avoid weight gain), and thus engaging in prevention/promotion behaviors does not increase risk for incurring a loss (e.g., exercising will only bring one closer to the desired outcome of losing weight or avoiding weight gain, so there is no potential for loss by engaging in exercise). Fear appeals are loss-framed messages because they emphasize negative consequences, and loss-framed information makes people more willing than usual to take risks ( Meyerowitz & Chaiken, 1987 ; van’t Riet et al., 2014 ). Therefore, although fear appeals should be effective for both detection and prevention/promotion behaviors, they should be particularly effective for detection behaviors because the loss-framed nature of the message should make people more willing than usual to take on the risk of the detection behavior ( Meyerowitz & Chaiken, 1987 ; Rothman, Martino, Bedell, Detweiler, & Salovey, 1999 ; Rothman & Salovey, 1997 ; van’t Riet et al., 2014 ).

Mentioning death, self-esteem relevance, and time delays

Many fear appeals explicitly mention death (89 of the 248 studies in our meta-analysis), and terror management theory (TMT) makes three predictions about this factor. According to TMT, when people are reminded of their mortality by being exposed to the concept of death, they often become motivated to buffer their self-esteem to reduce mortality related anxiety ( Goldenberg & Arndt, 2008 ; Pyszczynski et al., 1999 ; Shehryar & Hunt, 2005 ; Solomon et al., 1991 ). Some fear appeals recommend behaviors that can enhance self-esteem (e.g., dieting, which can improve body image; Goldenberg & Arndt, 2008 ), whereas others attempt to persuade people to stop engaging in behaviors that enhance self-esteem (e.g., tanning, which can also improve body image; Janssen et al., 2013 ). When fear appeals mention death, message recipients should increase commitment to behaviors that enhance self-esteem, regardless of whether the fear appeals encourage or discourage those behaviors. Consequently, fear appeals recommending self-esteem enhancing behaviors (e.g., dieting) should be more effective when they mention death than when they do not. In contrast, fear appeals recommending the cessation of behaviors that enhance self-esteem (e.g., tanning abstinence) should be less effective when they mention death than when they do not.

TMT also posits that reminders of death activate two types of defensive responses: Short-term proximal defenses and long-term distal defenses. Proximal defenses involve refuting information to avoid considering one’s death, whereas distal defenses involve buffering one’s self-esteem and pursuing long-term goals (e.g., a healthy lifestyle; Goldenberg & Arndt, 2008 ). Consequently, fear appeals that mention death should be more effective if there is a delay between fear appeal exposure and occurrence of the outcome, rather than if outcomes occur immediately after exposure when proximal defenses are still active (e.g., Greenberg et al., 1990; Shehryar & Hunt, 2005 ). 3

Two prominent theories make predictions about the impact of the audience on fear appeal effectiveness: Regulatory fit theory ( Higgins, Pierro, & Kruglanski, 2008 ; Kurman & Hui, 2011 ; Lockwood, Marshall, & Sadler, 2005 ) and the transtheoretical model ( Prochaska & DiClemente, 1983 ; Prochaska et al., 1992 ; Prochaska & Velicer, 1997 ). These predictions concern whether the message’s audience is primarily female (versus male), from a collectivist culture (versus an individualistic culture), and already attempting to change risk behaviors (versus not).

Gender and culture

According to regulatory fit theory, people can be promotion or prevention focused, placing greater value on either the pursuit of positive outcomes or on the avoidance of negative outcomes, respectively ( Higgins et al., 2008 ; Kurman & Hui, 2011 ; Lockwood et al., 2005 ). Message frames that match the promotion versus prevention tendencies of the audience are more persuasive ( Cesario, Higgins, & Scholar, 2008 ), and fear appeals are definitionally prevention-framed messages because they emphasize what one should do to avoid negative outcomes. Consequently, prevention-focused populations should be more persuaded by fear appeals relative to promotion-focused populations. Cultural research in the area of regulatory focus has found that women tend to be more prevention focused than men, and members of collectivist groups tend to be more prevention focused than members of individualist ones ( Kurman & Hui, 2011 ; Lockwood, Marshall, & Sadler, 2005 ). Therefore, fear appeals should be particularly effective for female (versus male) and collectivist (versus individualist) audiences.

Early versus late stages of change

According to the transtheoretical model, people engaging in risky behaviors can be classified as belonging to an early stage (the model’s precontemplation, contemplation, and preparation stages) or a late stage (the model’s action and maintenance stages) in the change process ( Prochaska & DiClemente, 1983 ; Prochaska et al., 1992 ; Prochaska & Velicer, 1997 ). According to the early-effectiveness hypothesis, fear appeals should be more effective for individuals in the early (vs. late) stages because the former require motivational appeals to understand that a threat exists and to increase commitment to adopting desirable behaviors and/or abandoning undesirable behaviors. In contrast, late stage individuals are already committed to behavior change and do not require such motivational appeals ( DiClemente et al., 1991 ; Nabi et al., 2008 ; Prochaska & DiClemente, 1983 ; Prochaska et al., 1992 ). The late-effectiveness hypothesis competes with the early one, and predicts that success at behavior change is associated with increases in self- and response efficacy ( Cho & Salmon, 2000 ). As a result, exposure to a fear appeal should lead individuals who have already enacted change to process the fear appeal in the context of their high response efficacy ( Cho & Salmon, 2006 ). Consequently, the late-effectiveness hypothesis predicts that fear appeals should be more effective for late stage relative to early stage individuals. 4 To test the early-effectiveness and late-effectiveness hypotheses, we classified each study’s sample as belonging to one of the transtheoretical model’s first three stages or last two stages. We then compared the effectiveness of fear appeals for individuals in the early versus late stages.

We compiled the largest meta-analytic database of fear appeals to date to examine the effectiveness of fear appeals for changing attitudes, intentions, and behaviors, and also to test moderator predictions made by a variety of influential fear appeal theories. Each of these theories tends to focus on one of three things – the content of the message , the type of behavior recommended by the communication, or the characteristics of the audience receiving the message (see Table 1 for a full list of theories and related hypotheses). Of the 16 fear appeal hypotheses discussed, only seven have been tested in prior meta-analyses, and all of them fall under the message aspect of our framework ( Table 1 ). Thus, the present research represents the first meta-analytic test for nine of the 16 hypotheses and the first meta-analytic test for any hypotheses related to the behavior and audience aspects of our framework.

Review and Inclusion Criteria

To locate studies, we conducted a search of the PsycInfo and Medline databases using the keywords (risk or fear or shock or severity or susceptibility) AND (persuasion or appeal or argument or tactic or campaign or communication or intervention). To supplement these database searches, we examined the reference lists of previous fear appeal meta-analyses, review articles, and chapters. We also contacted researchers to request unpublished data and sent requests to the e-mail lists of the Society of Behavioral Medicine , the Society for Personality and Social Psychology , the European Health Psychology Society , and the American Academy of Health Behavior . Our search extended through February 2015 and yielded 430 potentially eligible articles, which were subsequently screened for inclusion in the current meta-analysis based on several inclusion criteria. For inclusion in this meta-analysis, studies had to meet the following eligibility criteria:

• Studies were included if they contained an experimental research design in which a treatment group was exposed to a message designed to induce fear (i.e., a fear appeal).
• Studies were included if they contained a comparison group. The comparison group could have been a group that was not exposed to any message, a group that was exposed to a message that was not designed to induce fear, or a message that was designed to induce less fear than the treatment group’s message. When a study included more than one potential comparison groups, we opted to compare the highest depicted fear condition with the lowest depicted fear condition, prioritizing them in the following order: No message comparison group, neutral message comparison group, and low depicted fear comparison group. Thus, for a study containing a low depicted fear group and a neutral message group, we used the neutral message group as the comparison group. Overall, all results should be interpreted as the effect of exposure to messages designed to depict relatively high levels of fear compared to conditions designed to depict relatively lower levels of fear (including no fear). 5
• Studies were included if they experimentally manipulated depicted fear across groups. Studies were excluded if they used correlational research designs or provided all groups with the same level of depicted fear.
• Studies were included if they measured one or more of the following variables as an outcome in both the treatment and comparison groups: Attitudes, intentions, or behaviors.
• Studies were excluded if they did not contain appropriate statistics (e.g., F ratios, means and standard deviations, frequencies, or exact p values) for calculating an effect size representing the difference of outcomes for treatment versus comparison groups. If a study was otherwise eligible but did not contain appropriate statistics (e.g., it provided path coefficients from a structural equation analysis but did not supply means and standard deviations for treatment and comparison groups), we attempted to contact the study’s authors to retrieve usable data such as means and standard deviations. We contacted authors of 39 papers for this purpose: Three provided us with the requested data, six responded but could not provide us with the relevant data, and the rest did not respond to multiple contact requests.

Of the 430 reports considered for inclusion in this meta-analysis, 127 met our inclusion criteria (9% unpublished), providing 248 statistically independent samples with a total N of 27,372 participants in the treatment and comparison groups combined. Samples ranged in age from 9-87 years ( M = 22.77 years, SD = 9.24 years) and were on average 66% female ( SD = 33%). An average of 81% of each sample had completed high school ( SD = 37%). Further, samples were on average 71% White or European-American ( SD = 34%), 14% Asian or Asian-American ( SD = 31%), 8% Black or African-American ( SD = 18%), and 5% Hispanic/Latino(a) ( SD = 14%).

Coding of Outcomes (Effect Size Calculation)

We calculated a single effect size per sample that compared attitudes, intentions, and behaviors for the treatment group relative to the comparison group. First, for each sample we recorded all measures of attitudes, intentions, and behaviors. For each outcome, we calculated the standardized mean difference between treatment and comparison groups correcting for sample size bias ( Johnson & Eagly, 2014 , p. 686). Effect sizes ( d ) were calculated based on provided F -ratios, t -tests, odds ratios, or means and standard deviations. To produce d for any odds ratios, we divided the log of the odds ratio by 1.81 ( Haddock, Rindskopf, & Shadish, 1998 ; Hasselblad & Hedges, 1995 ).

Note that outcomes could have concerned the negative behavior/issue targeted by the fear appeal (e.g., attitudes toward smoking) or the fear appeal’s recommendations (e.g., attitudes toward smoking cessation). Effect sizes were calculated such that higher positive values indicate the treatment group scored higher in the message’s direction. For example, if a study used anti-smoking messages, a positive d would indicate that the treatment group (relative to the comparison group) had more negative attitudes toward smoking or more positive attitudes toward smoking cessation. Thus, a positive effect size indicates the fear appeal worked, whereas a negative effect size indicates the fear appeal backfired.

The majority of samples ( k = 170) included only one type of dependent measure (attitudes, intentions, or behaviors), but some samples included two types ( k = 61) or all three ( k = 17). Therefore, after calculating d for each outcome in a sample, we averaged all d values together to form a single effect size per sample that represents positive change in the direction advocated by the fear appeal. Further, if a sample included two or more measures of the same outcome type (e.g., attitudes toward smoking and attitudes toward smoking cessation), each was included in the average and weighted equally (the number of samples with multiple attitude, intention, and behavior measures was respectively k = 18, k = 24, and k = 12). This approach is justified on several grounds. First, for studies that included all three types of outcomes (attitudes, intentions, and behaviors), Cronbach’s alpha for the composite measure was .87, indicating that the three types of measures are highly internally consistent. Further, prior research has demonstrated that composite measures combining attitudes, intentions, and behaviors are a valid outcome of interest when investigating the relative persuasiveness of messages ( O’Keefe, 2013 ). We therefore combined all attitude, intention, and behavior measures within each sample to form a single effect size per sample, which is how the results will be presented in the present manuscript. However, we also conducted all analyses separately for attitude, intention, and behavior measures; these results are presented in Appendix A and are consistent with the results based on the combined measure. Several hypotheses made specific predictions about attitudes, intentions, or behaviors, and for those hypotheses (see Table 1 ), we present the relevant outcomes of interest in the body of the manuscript.

Of note, attitudes were most commonly measured with semantic differential scales (e.g., positive/negative, beneficial/harmful, wise/foolish, etc.; Roskos-Ewoldsen, Yu, & Rhodes, 2004 ; Nabi et al., 2008 ) and Likert style scales (e.g., agreement with statements such as, “I don’t like speeding”; Cauberghe et al, 2009 , p. 280). Intentions were frequently measured with Likert style scales (e.g., agreement with statements such as, “In the immediate future, I plan to find someone who will teach me to do an accurate breast self-examination”; Roskos-Ewoldsen et al., 2004 , p. 58) and questions with dichotomous response options (e.g., “In the future, I intend to stop spending time outside strictly for the purpose of getting a tan,” with responses Yes and No ; McMath & Prentice-Dunn, 2005 , p.629). Finally, behaviors were often measured dichotomously with self-report questions (e.g., “As a direct result of this message, did you seek help?” with responses Yes and No ; Smalec & Klingle, 2000 , p. 45) or behavioral observation data (e.g., information obtained from medical records; Ordoñana et al., 2009 ).

Coding of Potential Moderators

To test each hypothesis from the message, behavior, and audience portions of our framework, we coded several relevant variables (moderator codes for each paper included in the meta-analysis are displayed in Table 2 ). The first author trained two independent coders, who then coded all study characteristics relevant to each report. Intercoder reliability was calculated on 20% of the overall database using Cohen’s kappa (κ) for categorical variables and Pearson’s r for continuous variables. Agreement for all variables was good: Categorical variables had average κ = .93 (SD = .06, minimum = .80), and continuous variables had average r = .92 (SD = .12, minimum = .73). Disagreements were resolved by discussion and further examination of the studies.

Effect sizes, sample sizes, and moderator codes for each sample in the meta-analysis.

Note: d = Standardized mean effect size. N = Sample size for treatment plus comparison. AIB = Whether d was based on attitude (A), intention (I), and/or behavior (B) outcomes. EFF = Whether an efficacy statement was included (Y) or not (N). Sev = Whether the treatment message was manipulated to be higher in depicted severity than the comparison message (Y) or not (N). Sus = Whether the treatment message was manipulated to be higher in depicted susceptibility than the comparison message (Y) or not (N). OR = Whether the recommended behavior was one-time (O) or repeated (R). DPP = Whether the recommended behavior was detection (D) or prevention/promotion (PP). DP = Whether the word death was present in the message (Y) or not (N). SE = Whether the recommended behavior was self-esteem enhancing (SEE) or self-esteem hindering (SEH). Delay = Whether the outcome followed exposure to the message by less than 24 hours (S), 1–14 days (M), or more than 14 days (L). %F = Percent of sample that was female (0–100%). IC = Whether the sample was from an individualist (I) or collectivist (C) culture. SOC = Whether the sample was in the early (E) or late (L) stages of change. Dash (–) indicates the variable was not relevant for the study.

Moderators related to message content

To test hypotheses concerning the message content, we coded messages’ amount of depicted fear, inclusion (or absence) of efficacy statements, and levels of depicted susceptibility and severity.

To test the linear and curvilinear hypotheses, we coded whether studies included a moderate depicted fear group. To qualify, studies had to contain at least three experimental groups that were exposed to different levels of depicted fear. Thus, a study containing a high depicted fear group, a moderate depicted fear group, and a low depicted fear group would be included, whereas a study containing a high depicted fear group, a low depicted fear group, and a neutral control group would not. As noted above, an appropriate test of the linear and curvilinear hypotheses requires a comparison between high and moderate depicted fear; thus, the moderate group must represent a level of depicted fear between high and low (rather than between high and none). In the entire database ( k = 248), 21 samples included more than two experimental groups exposed to varying levels of depicted fear. To test the linear and curvilinear hypotheses, we calculated effect sizes ( d ) comparing outcomes for the highest versus middle depicted fear groups (the calculation of these effect sizes followed the same procedure detailed above for the calculation of treatment versus comparison effect sizes). The moderate depicted fear groups (total N = 1,626) were not included in other analyses (the studies and corresponding effect sizes included in this analysis can be found in Table 3 )

Effect sizes and sample sizes for each sample included in the linear versus curvilinear test.

Note: d = Standardized mean effect size. N H = Sample size for the high depicted fear group. N M = Sample size for the medium depicted fear group. Combined outcomes = Average of all attitude, intention, and behavior measures. Dash (–) indicates the variable was not relevant for the study. The attitude, intention, and behavior measures are analyzed separately in Appendix A .

For each article, we dichotomously coded whether or not an efficacy message was embedded in the fear appeal. The efficacy message could have focused on self-efficacy (e.g., emphasizing that people have a built-in urge for physical activity and this basic human physical need will make it easy to begin a regular exercise program; Wurtele & Maddux, 1987 ), response-efficacy (e.g., emphasizing that exercise leads to higher levels of high-density lipoprotein and thus prevents heart attacks; Wurtele & Maddux, 1987 ), or both (e.g., highlighting that condoms substantially reduce the risk of HIV transmission if used correctly and are easy to use consistently; Witte & Morrison, 1995 ).

For each article, we coded whether depicted severity was manipulated to be higher in the treatment group relative to the comparison group (e.g., the treatment group received a message emphasizing the drastic consequences of not wearing bicycle helmets; Rodriguez, 1995 ) and whether depicted susceptibility was manipulated to be higher in the treatment group relative to the comparison group (e.g., the treatment group received a message focusing on how coffee consumption will likely lead the message recipient to develop fibromyalgia; Lieberman & Chaiken, 1992 ).

Moderators related to behavior characteristics

To test hypotheses concerning the targeted behavior, we coded whether the fear appeals recommended behaviors that were one-time or recurring and whether the behavior was a detection or prevention/promotion behavior. We also coded whether death was mentioned when discussing the behavior, whether the behavior was measured immediately versus after a delay, and whether the recommended behaviors was self-esteem enhancing or self-esteem hindering.

We coded whether the recommended behaviors concerned one-time-only instances (e.g., signing up for a stress management training; Das et al., 2003 ) or would need to be enacted over an extended period of time (e.g., regularly using child safety devices when traveling by car; Chang et al., 1989 ).

Detection versus prevention/promotion

For each article, we coded if the recommended behavior was a detection behavior (e.g., getting tested for syphilis; Fukada 1975 ) or a prevention/promotion behavior (e.g., attending a training to prevent repetitive stress injury; Pengchit, 2010 ). We initially attempted to code prevention and promotion behaviors separately. However, due to the nature of these constructs, it was often difficult to discern how participants would construe a behavior (e.g., did participants conceptualize exercising as promoting a healthy BMI or preventing obesity?). As the relevant hypothesis solely concerned fear appeals being more effective when recommending detection (vs. prevention/promotion) behaviors, promotion and prevention behaviors were collapsed into a single code.

We created a dichotomous code for whether or not the message explicitly used the word death . Messages dealing with behaviors or issues that could clearly lead to death were still coded as non-death if the word death was not explicitly mentioned within the message itself (e.g., messages about smoking or HIV/AIDS that did not explicitly mention death as one of the potential consequences; Insko et al., 1965 ; McMath & Prentice-Dunn, 2005 ; Raleigh, 2002 ; Witte & Allen, 2000 ). This decision allowed for a more stringent test of TMT hypotheses, and provided an even distribution of death versus non-death conditions, which avoids the potential confound of death messages always being about more severe topics than non-death messages.

Self-esteem relevance

We coded whether the recommended behavior was self-esteem hindering or self-esteem enhancing. Self-esteem hindering behaviors were intended to replace existing behaviors that allowed message recipients to derive self-esteem. Samples were coded as containing a self-esteem hindering behavior if the researchers specifically measured self-esteem for the existing behavior being targeted by the fear appeal and described the sample as high (e.g., high driving-related self-esteem; Taubman Ben-Ari et al., 2000 ), if the sample was designated as committed to the existing behavior (e.g., smokers that were highly committed to smoking; Priolo & Milhabet, 2008 ), or if the existing behavior is one that people typically engage in to improve self-esteem and/or physical attractiveness (e.g., tanning or bulimia; Janssen et al., 2013 ; Smalec & Klingle, 2000 ).

In contrast, self-esteem enhancing behaviors have the potential to provide individuals with self-esteem. Samples were coded as containing a self-esteem enhancing behavior if the recommended behavior is commonly associated with the pursuit of improved self-esteem and/or physical attractiveness (e.g., fear appeals recommending a healthy diet to decrease BMI; Goldenberg & Arndt, 2008 ). Samples were also coded as self-esteem enhancing when fear appeals targeted behaviors that the audience had clearly already made the choice to forego (e.g., antismoking ads directed at non-smokers; Insko et al., 1965 ) because message recipients should generally be able to derive self-esteem by continuing to avoid engaging in the discouraged behavior (e.g., non-smokers who are told that smoking is bad and smoking abstinence is good should feel as though their decision to abstain from smoking reflects positively on them). Thus, studies were coded as self-esteem enhancing if the recommended behavior could improve self-esteem via the pursuit of physical attractiveness (e.g., exercise; Wurtele & Maddux, 1987 ), if the addressed behavior was not relevant for the sample (e.g., anti-smoking ads for non-smokers; Insko et al., 1965 ; Smart & Fejer, 1974 ), if the sample was designated as not committed to the behavior in question (e.g., smokers that were not committed to smoking; Priolo & Milhabet, 2008 ), or if the researchers specifically measured self-esteem related to the existing behavior being targeted by the fear appeal and described the sample as low (e.g., low driving-related self-esteem; Taubman Ben-Ari et al., 2000 ).

We coded the amount of time between the fear appeal and the measurement of the outcome variable using three discrete categories: (a) The measure occurred the same day as the fear appeal exposure (e.g., Taubman Ben-Ari et al., 2000 ; Cho & Salmon, 2006 ; Nabi et al., 2008 ; Smart & Fejer, 1974 ; Stainback & Rogers, 1983 ); (b) the measure occurred one to fourteen days after fear appeal exposure (e.g., Berkowitz, 1998 ; Kirscht et al., 1978 ; Muthusamy et al., 2009 ); and (c) the measure occurred more than fourteen days after fear appeal exposure (e.g., Bagley & Low, 1992 ; Smith & Stutts, 2003 ; Witte & Morrison, 1995 ). We used categories because delayed outcomes often occurred within a specified range – e.g., participants returned to the lab during the following two weeks, but the exact number of days was not specified.

Moderators related to the audience

To test hypotheses concerning the audience portion of our framework, we coded the gender composition of the sample, whether the sample was from a collectivist or individualist country, and the transtheoretical model stage of change that was applicable to the sample.

Gender composition

We coded the percent of the sample that was female.

Collectivism and individualism

We dichotomously coded whether each study’s sample came from a primarily collectivist culture (e.g., East Asian cultures like South Korea, Japan, and Taiwan; Chu, 1966 ; Fukada, 1973 ; 1975 ; 1988 ; Kim et al., 2009 ) or a primarily individualist culture (e.g., Western cultures like Australia, Canada, and the United States; Beck, 1984 ; Brouwers & Sorrentino, 1993 ; Dahl et al., 2003 ; Hill & Gardner, 1980 ; Jones & Owen, 2006 ; LaTour & Tanner, 2003 ; Lewis et al., 2010 ; Smart & Fejer, 1974 ).

Stage of change

We coded the transtheoretical model’s stage of change that was most applicable to the audience. As most studies did not specifically measure this variable, we designed a conservative coding scheme to ensure we could include the maximum number of reports in this analysis while avoiding misclassifications. The early-effectiveness and late-effectiveness hypotheses both make predictions that compare individuals in the first three stages of the model (precontemplation, contemplation, and preparation) versus the last two stages of the model (action and maintenance). Thus, we created a dichotomous code indicating whether the sample was in the early or late stages of the model.

Samples were considered precontemplation if there was a clear indication that it was a sample merely at risk for a given behavior (e.g., participants who were designated as noncompliant with safe sex recommendations; Raleigh, 2002 ), or participants were being persuaded about a fictitious or not well-known disease/risk for which they had clearly not been engaging in protective action beforehand (e.g., hypoglycemia; de Hoog et al., 2008 ). We excluded samples in which the participants may have been in the precontemplation stage but for which there were no pretest measures available (e.g., if the sample was given a message about drinking and driving but there were no baseline measures available to indicate whether or not the sample had engaged in drunk driving in the past; Shehryar & Hunt, 2005 ). Samples were considered contemplation or preparation if there was a clear indication that they were already preparing to engage in the recommended action (e.g., a sample of women under 50 years old who had not yet received mammograms, but the majority of whom stated they intended to receive mammograms after age 50; Jones & Owen, 2006 ). Samples were classified into the action/maintenance category if participants had explicitly been engaging in the recommended behavior (e.g., a message promoted breast self-exams and 80% of the sample indicated they already performed breast self-exams regularly; Siero, Kok, & Pruyn, 1984 ) or if they were recruited from a population that would definitionally be in this stage (e.g., patients receiving treatment in alcohol rehabilitation clinics; Brown, 1979 ).

All analyses were conducted in R using the meta-analytic software package metafor, version 1.9.4 ( Viechtbauer, 2010 ). We conducted all analyses using random- and fixed-effects analyses. As both types of analyses produced comparable results, we present the random-effects analyses.

Distribution of Effect Sizes

We first analyzed the distribution of effect sizes in our sample to determine whether there were biases in study retrieval and inclusion. Figure 1 displays a forest plot for our meta-analytic database, and Figure 2 displays the corresponding funnel plot. In a forest plot, each study is represented by a horizontal line that indicates the confidence interval for the study’s effect size. By examining a forest plot, it is possible to assess the precision of effect size estimates from each study. Further, forest plots can also be used to assess the distribution of effect sizes across studies. As can be seen in the forest plot, the precision of effect size estimates varies across studies, with most studies displaying moderate precision. Further, the distribution of effect sizes appears to be roughly continuous and normal, which indicates a lack of inclusion bias. If no retrieval or inclusion bias is present in a meta-analytic database, the distribution of effect sizes in the funnel plot should be centered on and symmetric around the mean effect size, with smaller variability toward the top of the figure. If retrieval or inclusion biases are present, then the distribution should be asymmetric around the mean effect size. As can be seen in the figure, the distribution appears quite symmetric with smaller variability toward the top of the plot. We conducted a formal test of funnel plot asymmetry known as Begg and Mazumdar’s rank correlation test, which is a non-parametric correlation of the effect sizes with their corresponding standard errors ( Begg & Mazumdar, 1994 ). If this correlation is significantly different from zero, there is evidence of inclusion bias. The rank correlation was r = −.02, p = .67. Thus, there is no evidence of retrieval or inclusion bias.

Forest plot of the effect sizes.

Note: This forest plot includes point estimates and confidence intervals for all studies in the manuscript. The solid vertical line represents the combined effect size ( d = .29).

Funnel plot of effect sizes.

Note: Effect size ( d ) is plotted on the x-axis and standard error on the y-axis. The solid vertical line represents the combined effect size ( d = .29). The dotted line represents the x-intercept (x = 0) for a reference line. The white region represents the inside of the 95% pseudo confidence interval, whereas the shaded region represents the outside (i.e., the area of statistical significance).

Another way of testing for biases is to use the normal quantile plot method ( Wang & Bushman, 1999 ). In a normal quantile plot, the observed values of a variable are plotted against the expected values given normality. If the sample of effect sizes is from a normal distribution, data points cluster around the diagonal; if the sample of effect sizes is biased by publication practices or eligibility criteria, data points deviate from the diagonal ( Wang & Bushman, 1999 ). As can be seen from Figure 3 , the effect sizes followed a straight line and generally fell within the 95% confidence interval of the normality line, and thus there is no evidence of retrieval or inclusion bias.

Normal quantile plot.

Note: The dashed lines represents a 95% confidence band. The line on the diagonal indicates normality.

Average Effect Size and Between-Effects Variability

The average weighted effect size comparing outcomes for treatment to comparison groups was d = 0.29 with a 95% CI of [0.22, 0.35]. Therefore, fear appeals have a significant and positive effect on outcomes. That is, relative to participants in comparison groups, participants in treatment groups (i.e., those exposed to relatively high levels of depicted fear) had attitudes, intentions, and behaviors that were more in line with the position advocated by the fear appeal. There was also significant heterogeneity among effect sizes Q (247) = 1,287, I 2 = 85.11, p < .0001.

For studies that included a manipulation check of subjectively experienced fear, we coded this variable and calculated d for treatment versus comparison groups using the same methods employed for primary outcomes. We included all measures that asked respondents to report their current levels of fear (e.g., Cauberghe, De Pelsmacker, Janssens & Dens, 2009 ; Cho & Salmon, 2006 ; Nabi et al., 2008 ). Based on the 71 samples that included such manipulation checks, fear appeals were generally successful at inducing experienced fear, such that treatment groups reported more fear than comparison groups, d = 1.00 (95% CI: [0.83, 1.18]), Q(70) = 697, I 2 = 90.67, p < .0001. Importantly, this result should be taken as an estimate of how much fear was induced by the particular messages used in this sample, rather than an estimate of how much fear is induced by fear appeal messages in general.

Moderator Tests

To test our hypotheses of interest (see Table 1 ), we primarily conducted moderator analyses by calculating weighted effect sizes and corresponding 95% CIs for each level of our moderator variables (i.e., we meta-analyzed samples within each moderator level separately to produce an overall effect size estimate for that level). If the CIs for two moderator levels are not overlapping, then those levels of the moderator are significantly different from each other. In contrast, if the CIs are overlapping, then those levels of the moderator are not different from each other. We also conducted moderated meta-regressions to analyze all moderator variables; the results were the same as the 95% CI analyses and are thus not presented here. Table 5 displays average weighted effect sizes and corresponding 95% CIs for all levels of our moderator variables.

Moderator analysis results for categorical moderators.

Note: SE = Self-esteem. DP = Death present in message. DA = Death absent in message. PP = Promotion/prevention. SEE = Self-esteem enhancing recommended behaviors. SEH = Self-esteem hindering recommended behaviors. d = Standardized mean effect size estimated meta-analytically for the indicated moderator level. 95% CI = The 95% confidence interval for d . k = The number of studies for each moderator level.

Study Characteristics

For descriptive purposes, we recorded the following for each sample: (a) Study source (journal article, unpublished dissertation or thesis, or conference paper); (b) institution of the paper’s first author (university/college, research center); (c) the sampled population (general population, college students, high school students, children, other); (d) whether participants were run individually or in groups; (e) the study setting (laboratory, field); (f) the specificity of the message – whether the message targeted a single specific outcome (e.g., signing up for a training to prevent stress-related illness; Das et al., 2003 ), multiple specific outcomes (e.g., consuming calcium and performing weight-bearing exercises to prevent osteoporosis; Klohn & Rogers, 1991 ), or multiple non-specific outcomes (e.g., general recommendations to improve diet and increase exercise without mentioning specific dietary concerns or specific forms of exercise; Kirscht & Haefner, 1973 ); (g) whether the study measured subjective fear; (h) the type of media used to present the message (text information, pictures/videos); (i) whether the message targeted a health relevant outcome; and (j) the domain of the study’s targeted issue (dental hygiene, driving safety, HIV/STDs, drinking/drugs, smoking, cancer prevention, disease prevention, general safety, environment/society, other). As can be seen in Table 4 , none of these methodological factors moderated fear appeal effectiveness – within each factor, 95% CIs for each factor level overlap for all levels of all factors. In addition to these factors, we also recorded publication year, average age of participants, and sample size. Separate meta-regressions for each of these three variables revealed that none were related to fear appeal effectiveness: b = −0.0029 (SE = 0.0022, p = .18, 95% CI: [−0.0072, 0.0013]), b = −0.0046 (SE = 0.0039, p = .23, 95% CI: [−0.0122, 0.0030]), and b = 0.0000 (SE = 0.0002, p = .91, 95% CI: [−0.0003, 0.0003]), respectively for publication year, average age of sample, and sample size.

Moderator analysis results for methodological variables.

Note: d = Standardized mean effect size estimated meta-analytically for the indicated moderator level. 95% CI = The 95% confidence interval for d . k = The number of studies for each moderator level.

Tests of message content hypotheses

Message content: depicted fear.

To test the linear and curvilinear hypotheses, we calculated an average weighted effect size comparing groups that were exposed to moderate depicted fear versus high depicted fear. The linear hypothesis predicts that this effect size should be positive and significant, whereas the curvilinear hypothesis predicts that this effect size should be negative and significant. The combined effect size was d = −0.05 with a 95% CI of [−0.34, 0.24] and Q(20) = 154 (I 2 = 92.89, p < .0001). Therefore, outcomes did not differ for groups exposed to moderate versus high depicted fear. Instead of supporting either the linear or curvilinear hypothesis, this result suggests that depicted fear may have a maximum effective value, beyond which there is no impact of depicting additional fear. This finding may have implications for practitioners using fear appeals - i.e., once a message depicts moderate fear, there is no value in depicting additional fear, but depicting additional fear will not lead to negative effects.

One caveat is that this analysis was only based on 21 samples. However, to our knowledge, this is the largest and most valid test of the linear and curvilinear hypotheses to date. Specifically, to ensure that the test concerned high depicted fear versus moderate depicted fear, we only included studies with at least three levels of depicted fear. Given that we obtained an overall positive effect of depicted fear when comparing treatment and comparison groups, the results here can be interpreted as supporting a modified version of the linear hypothesis. Specifically, depicted fear has significant positive effects, but depicted fear cannot be effectively manipulated indefinitely and results in diminishing returns beyond a certain point (rather than negative effects causing the message to backfire, as suggested by the curvilinear hypothesis). However, given the limited sample size, this conclusion should be confirmed in future research.

Message content: Efficacy statements

The strong and weak efficacy hypotheses both predict that inclusion of efficacy statements in a fear appeal will lead to increased effectiveness. The results support this hypothesis: Fear appeals were more effective when they included efficacy statements (95% CI: [0.31, 0.55]) than when they did not (95% CI: [0.13, 0.29]). However, the strong hypothesis predicts that fear appeals without efficacy messages will backfire and produce negative effects, whereas the weak hypothesis predicts that fear appeals without efficacy statements will simply produce less positive or null effects. The results clearly support the weak efficacy hypothesis and disconfirm the strong efficacy hypothesis. Thus, fear appeals are effective with or without efficacy statements, but the inclusion of efficacy statements is associated with increased effectiveness. These results confirm the conclusions of prior meta-analyses concerning the use of efficacy statements ( de Hoog et al., 2007 ; Peters et al., 2012 ; Witte & Allen, 2000 ).

Message content: Depicted susceptibility and severity

The first hypothesis concerning depicted susceptibility and severity states that fear appeals high in depicted severity (but not depicted susceptibility) will positively influence attitudes but will not influence intentions or behaviors. The 95% CIs indicated that fear appeals that were only high in depicted severity had positive effects for attitudes (95% CI: [0.06, 0.37]) and intentions (95% CI: [0.20, 0.39]) but not behaviors (95% CI: [−0.08, 0.42]) (see Appendix A for the results of all analyses done separately for attitudes, intentions, and behavior). Although this hypothesis was not supported, our results partially replicated a previous meta-analytic finding in which high depicted severity influenced all three outcome measures ( de Hoog et al., 2007 ). The second hypothesis is that fear appeals high in depicted susceptibility (but not severity) will positively influence intentions and behaviors but will not influence attitudes. The 95% CIs indicated that fear appeals that were only high in depicted susceptibility had positive effects for intentions (95% CI: [0.15, 0.59]) and behaviors (95% CI: [0.01, 0.88]) but not attitudes (95% CI: [−0.51, 1.47]). Therefore, this hypothesis was supported. The third hypothesis is that fear appeals with high depicted severity and high depicted susceptibility will positively influence attitudes, intentions, and behaviors. The 95% CIs confirmed this prediction and indicated that fear appeals high on both moderators had positive effects for attitudes (95% CI: [0.05, 0.38]), intentions (95% CI: [0.23, 0.47]), and behaviors (95% CI: [0.24, 0.63]). Further, the 95% CI for the focal outcome in our meta-analysis (the average of attitude, intention, and behavior outcomes) also supported this result: [0.28, 0.50]. Thus, when testing all three hypotheses, fear appeals generally had positive effects on attitudes, intentions, and behaviors when they were high in depicted severity and/or susceptibility.

Tests of the recommended behavior hypotheses

Recommended behavior: one-time versus repeated behaviors.

According to Robertson’s (1975) single action theory, fear appeals that attempt to persuade people about one-time behaviors (e.g., getting vaccinated) should be more effective than fear appeals that attempt to persuade people about repeated behaviors (e.g., exercising multiple times per week every week). The results supported this hypothesis, such that fear appeals recommending one-time behaviors (95% CI: [0.30, 0.56]) were more effective than fear appeals recommending repeated behaviors (95% CI: [0.14, 0.29]). However, it is worth noting that fear appeals were effective for both types of recommended behaviors, and they were simply more effective for one-time behaviors.

Recommended behavior: Detection versus prevention/promotion behaviors

Based on hypotheses derived from prospect theory, several researchers have hypothesized that fear appeals should be more effective when recommending detection behaviors relative to prevention/promotion behaviors. The results did not support this hypothesis, as fear appeals recommending detection behaviors (95% CI: [0.21, 0.49]) and prevention/promotion behaviors (95% CI: [0.20, 0.38]) were equally effective.

Recommended behavior: Death and self-esteem

Based on predictions from TMT, fear appeals that mention death (versus not) should be more effective when the recommended behavior is self-esteem enhancing but less effective when the recommended behavior is self-esteem hindering. The results did not support these predictions, as fear appeals were equally effective when they mentioned death and recommended a self-esteem hindering behavior (95% CI: [−0.41, 0.18]), did not mention death and recommended a self-esteem hindering behavior (95% CI: [0.00, 0.96]), mentioned death and recommended a self-esteem enhancing behavior (95% CI: [0.11, 0.67]), or did not mention death and recommended a self-esteem enhancing behavior (95% CI: [−0.04, 0.47]). Thus, neither self-esteem hypotheses derived from TMT was supported.

Recommended behavior: Death and delay

A separate prediction derived from TMT is that fear appeals that mention death will be more effective if the recommended behavior is measured after a delay rather than immediately. These predictions were not supported. When fear appeals mentioned death, they were equally effective for outcomes that occurred the same day (95% CI: [0.04, 0.27]), between one and fourteen days after fear appeal exposure (95% CI: [0.21, 1.37]), or more than fourteen days later (95% CI: [0.19, 0.51]). Similarly, when fear appeals did not mention death, they were equally effective for outcomes that occurred the same day (95% CI: [0.25, 0.44]), between one and fourteen days after fear appeal exposure (95% CI: [−0.29, 0.33]), or more than fourteen days later (95% CI: [0.03, 0.88]). Therefore, the death and delay hypothesis was not supported.

Tests of the audience hypotheses

Audience: gender.

Based on predictions derived from regulatory fit theory, fear appeals should be more effective for women than men. We tested this hypothesis via meta-regression, using percent of the sample that was female as a predictor of effect size. This analysis produced a small but significant effect, b = 0.0031 ( SE = 0.0012, 95% CI for the slope: [0.0007, 0.0055]), p < .0001. Therefore, for every 10% increase in the percent of the sample that is female, fear appeal effectiveness increases by approximately d = 0.03. Thus, the hypothesis was supported: Fear appeals are more effective for audiences with a larger percentage of female message recipients than male message recipients.

Audience: Collectivism versus individualism

Based on predictions derived from regulatory fit theory, fear appeals should be more effective for collectivist samples than individualist samples. The results did not support this hypothesis. Fear appeals were equally effective in studies conducted in collectivist countries (95% CI: [0.27, 0.66]) and individualist countries (95% CI: [0.19, 0.33]).

Audience: Stages of change

Based on the early-effectiveness hypothesis, fear appeals should be more effective for samples that occupy the first three stages of the stages of change model relative to the last two stages. In contrast, the late-effectiveness hypothesis predicts the opposite. Neither hypothesis was supported by the data because audiences in the early stages (95% CI: [0.21, 0.40]) and late stages (95% CI: [0.14, 0.54]) were equally impacted by fear appeals.

General Discussion

Fear appeals are effective. The present meta-analysis found that fear appeals were successful at influencing attitudes, intentions, and behaviors across nearly all conditions that were analyzed. Even when a moderator was unrelated to fear appeal effectiveness, fear appeals were still more effective than comparison treatments. Further, there was not one level of any moderator that we tested for which fear appeals backfired to produce worse outcomes relative to the comparison groups. These results are striking given the wide range of theories that attempt to specify conditions under which fear appeals should be ineffective or counter-productive (e.g., the curvilinear model, the strong efficacy hypothesis, the stage model) and given the numerous practitioners who make bold claims stating that fear appeals are futile or even dangerous (e.g., Drug Free Action Alliance, 2013 ; Kok et al., 2014 ; Ruiter et al., 2014 ). Rather, fear appeals consistently work, and through our meta-analysis we were able to identify various factors that can enhance their effectiveness to make them work even better. We believe that these results make important contributions to theory, practice, and policy.

A Message-Behavior-Audience Framework of Fear Appeals

We structured our review around a framework that considers three important aspects of any fear appeal communication: The message’s content, the recommended behavior, and the audience. This model is meant to be an organizing thread to help connect existing theories and research, and to identify areas in need of future research. Specifically, we believe this framework is useful for several reasons. First, each aspect (message, behavior, and audience) has the potential to vary independently of the others and may impact the communication’s effectiveness in ways scholars must consider. Second, this structure connects and organizes seemingly unrelated theories and hypotheses concerning fear appeals, including the linear model, the stage model, and hypotheses derived from prospect theory. Specifically, we found that fear appeals were more effective when the message depicted relatively high amounts of fear, included an efficacy message, and stressed susceptibility and severity related to the concerns being addressed (i.e., factors concerning the message). We also found that fear appeals were more effective when they recommended one-time only behaviors (i.e., a factor concerning the recommended behavior) and when audiences included a higher percentage of women (i.e., a factor concerning the audience).

Our framework also highlights that prior research has strongly focused on one particular aspect of fear appeals somewhat to the exclusion of the other aspects. Specifically, the bulk of prior research on fear appeals has investigated questions about the message’s content – indeed, of the prior meta-analyses on fear appeals, all of them addressed questions related to the message’s content while overlooking questions related to the recommended behavior and audience. However, this bias is clearly not due to a lack of interesting or potentially important effects concerning the behavior or audience, as significant effects emerged pertaining to each. Thus, we hope that our framework will help generate interest in research directed toward these previously under-studied aspects of fear appeal effectiveness.

Limitations

Four specific limitations are worth mentioning. First, as discussed in the introduction, the present results concern fear appeals rather than fear. That is, our meta-analysis did not compare people who were subjectively afraid to people who were subjectively unafraid, but rather we compared groups that were exposed to more or less fear inducing content. Consequently, all comparisons between the treatment and comparison groups must be interpreted as effects of exposure to depicted levels of fear rather than effects of fear per se. However, this feature is not unique to our analyses, and prior meta-analyses of fear appeals are subject to the same considerations (e.g., Boster & Mongeau, 1984 ; de Hoog et al., 2007 ; Peters et al., 2012 ; Sutton, 1984; Witte & Allen, 2000 ). As researchers and practitioners alike are typically concerned with how to design effective communications, knowledge of the effectiveness of fear appeals is quite useful.

Relatedly, although we were able to determine that the treatment groups generally experienced more subjective fear than the comparison groups by analyzing fear-related manipulation check questions, the majority of samples included no assessment of subjective fear ( k = 177, which is 71% of samples in our database). This is a serious limitation of the existing literature for three reasons. First, if fear appeals are presumed to have an effect on outcomes by instilling fear in message recipients, it is important to verify that these messages actually evoke fear, and that it is the evoked fear that mediates the relation between message presentation and response. Indeed, many fear appeals may evoke emotions in addition to fear (e.g., disgust, anger), and these other emotions may partially (or in some cases fully) mediate the effects of fear appeals. Second, the lack of subjective fear measures makes it difficult (if not impossible) to equate fear appeal intensity across studies. What one research team refers to as low fear may represent what another research teams refers to as moderate fear or a control condition. However, the inclusion of subjective measures of fear in response to fear appeals would enable researchers to equate fear appeal intensity across studies and more precisely investigate effects via well-calibrated levels of fear. Finally, the lack of subjective fear measures makes it difficult for researchers interested in the effects of fear (rather than fear appeals) to investigate relevant hypotheses meta-analytically. All three of these issues can be easily resolved by including measures of subjective fear in future studies on fear appeals, and we therefore urge researchers to do so.

Third, our meta-analysis exclusively included experimental studies. As experiments often allow for increased internal validity at the cost of decreased external validity, it will be important for future research to investigate whether the present results generalize to naturalistic settings. For example, do fear appeals produce the same effects when used in real-world public health campaigns as they do when used in highly controlled experimental studies? Although we expect the results will generalize to such settings, future research will be necessary to definitively test this question.

The final limitation of note concerns the coding of variables in the current meta-analysis. Specifically, to test hypotheses related to TMT, studies were coded as either containing the word death or not. However, some studies did not include full texts for fear appeal messages, and thus it is possible that some messages did contain the word death but were nonetheless coded as not containing this word (however, studies were only coded as containing the word death if a portion of the message’s text was available that showed this word). Overall, it is likely that such miscodings would attenuate potential differences across conditions.

Future Directions

Experimental manipulations and mechanisms.

The present meta-analysis only included experimental studies that compared treatment and comparison groups, and thus internal validity is good when considering the effects of relatively high versus low depicted fear. However, meta-analyses are a correlational research design, and thus many of the moderator analyses we conducted should be interpreted with this in mind. For example, does using fear appeals to target one-time behaviors versus recurring behaviors actually cause the fear appeals to be more effective, or are fear appeals that target one-time behaviors systematically different from fear appeals that target recurring behaviors along some other dimension that results in the observed difference? Future experimental work will be necessary to address such questions, and we therefore encourage researchers to experimentally test our moderator findings concerning variables that were not manipulated in the primary studies.

It is also important for future research to uncover the mechanisms behind the moderation effects we identified. For example, why are fear appeals more effective for one-time behaviors? A number of the hypotheses that we substantiated are relatively agnostic concerning mechanisms, and this is a serious gap in the current fear appeal literature. To truly understand fear appeal effectiveness, it is necessary to know why they work. This knowledge could then be used to design more effective fear appeals, and it could potentially be used for other types of communications as well. Although some of the theories investigated do discuss mechanism to some degree (e.g., EPPM; Witte, 1992 ), our updated review of the literature is consistent with conclusions from prior reviews that these mechanisms are often under-studied and are in need of additional research (e.g., Popova, 2012 ).

Relatedly, future research could benefit from developing methods to manipulate perceptions of certain variables that were found to be significant moderators. For example, fear appeals were more effective for one-time behaviors, but this knowledge is currently of little use to researchers or practitioners who address recurring behaviors. However, this knowledge could become useful if methods were developed to successfully re-frame recurring behaviors as one-time behaviors. Such methods would also allow for experimental tests of the relevant dimensions and mechanisms (e.g., test whether fear appeals can be made more effective for a particular behavior if the behavior is framed as one-time rather than recurring).

Linear effect of fear

Another important question to address in future research concerns the linear and curvilinear hypotheses tested in the present study. Strictly speaking, we did not find support for either model. High levels of depicted fear did not lead to different outcomes than moderate depicted fear, suggesting that high and moderate depictions of fear produce similar results. However, the reason for this is unclear – were the high fear messages unsuccessful at evoking more subjective fear than the moderate messages, or is there simply a point beyond which additional fear (depicted or subjective) confers no benefit? To explore these possibilities, future studies should examine a large range of depicted fear along with measures of subjectively experienced fear.

Integration of findings

Finally, we believe that an additional benefit of our framework is its ability to guide researchers in generating future research questions. As mentioned, organizing the existing literature under this framework highlights the relative dearth of research addressing the behavior and audience aspects of the model relative to the message aspect. A number of interesting questions have yet to be explored in these areas. For example, are fear appeals more effective if they address behaviors concerning the self or close others (e.g., one’s children, romantic partners), public or private behaviors (e.g., exercising at a gym versus alone), or socially desirable or undesirable behaviors? Further, are fear appeals differentially effective for target populations that differ in age, education, social class, or personality? Such questions have received relatively little attention, but they have the potential to inform fear appeal theory and practice.

Additionally, what kinds of interactions exist when crossing aspects of message, behavior, and audience? We investigated two such questions in the present study with the hypotheses related to terror management theory – i.e., message content (presence versus absence of the word death) crossed with the recommended behavior (self-esteem enhancing versus hindering behaviors, immediate versus delayed outcomes). Although neither of these hypotheses was supported, the potential to test these types of interactions prompts the question of which variables may interact, particularly variables from separate aspects of the model. For example, might fear appeal effectiveness be moderated by interactions of culture (a factor of the audience) with the kind of behavior addressed by the fear appeal? Cross-cultural differences have rarely been explored in the effectiveness of fear appeals, and it is possible that cultural sensitivity to a behavior/issue may moderate the effectiveness of fear appeals addressing that behavior/issue. For example, East Asian countries have extremely low HIV prevalence rates and thus may be less susceptible to fear appeals on that topic relative to other topics. Whether this is true and whether it interacts with related findings is an empirical question that could be fruitfully explored in future research.

Importantly, aspects other than message content, behavior, and audience may moderate the effectiveness of fear appeal communications. However, based on our review of the literature, there simply appeared to be too little research on other aspects to include them in the current framework. Three potential aspects worth noting are the source of the communication, the subjective experience of the message recipient, and the channel used to transmit the message. First, based on a well-established body of literature in persuasion demonstrating that aspects of a message’s source can influence the persuasiveness of the message ( Briñol & Petty, 2009 ; Kumkale et al., 2010 ; Pornpitakpan, 2004 ; Wilson & Sherrell, 1993 ), the source of a fear appeal communication should be an important moderator for fear appeal effectiveness. For example, fear appeals from benevolent groups (e.g., a respected government institution, a close personal friend) may be more effective than fear appeals from self-interested groups (e.g., corporations or other for-profit entities). However, most empirical studies did not detail source information in a manner that allowed us to test such hypotheses. Further, many fear appeals are delivered in the form of public service announcements, and thus there is relatively little variation across existing studies on this dimension. Second, drawing on our previous distinction between fear appeals and fear, the subjective experience of the message recipient should be an important aspect of fear appeal communications. Although most empirical studies simply do not measure participants’ subjective states, such measures could be very informative to test a variety of interesting questions. For example, is fear the only emotion evoked by fear appeals? If not, what other negative emotions are evoked (e.g., disgust, shame, guilt, anger), and are they partially responsible for the effectiveness of fear appeals? Similarly, perhaps the effects of fear appeals are simply driven by induced negative affect or high arousal, and the specific experience of fear is superfluous? Future research using measures of subjective experience are needed to address these questions. The paucity of existing research addressing source characteristics and subjective experience led us to not include these as aspects of the current review framework, but they would be welcome additions in the future. Third, consistent with the focus of the persuasion literature on source, message, audience, and channel of communication as key components to understand in the persuasion process ( Shannon & Weaver, 1949 ), are certain channels of communication more likely to be effective in delivering fear appeals? For example, are graphic videos more likely to be effective than audio fear appeals without video? How do social media channels (generally more linked to liked peers) differ from mass media in effectiveness of delivered fear appeals?

To conclude, fear appeals are effective, and our synthesis organized and identified factors that make them even more effective. Specifically, fear appeals are particularly effective when the communication depicts relatively high amounts of fear, includes an efficacy message, stresses severity and susceptibility, recommends one-time only behaviors, and targets audiences that include a larger percentage of female message recipients. We formed these conclusions by meta-analytically testing a wide variety of influential fear appeal theories using the largest and most comprehensive fear appeals database to date. We believe our analysis has provided a thorough overview of the state of the literature and also generated a variety of important and exciting future directions.

Acknowledgments

This paper was facilitated by grants R01 MH094241, R01 NR08325, and R56 AI114501.

In the body of the manuscript, we presented random-effects analyses for a combined measure averaging across attitudes, intentions, and behaviors. Here, we present the analyses done separately for each type of measure.

First, the overall average effect size comparing treatment to comparison groups separately for attitudes, intentions, and behaviors was respectively d = 0.23 (95% CI: [0.11, 0.34]), d = 0.31 (95% CI: [0.24, 0.38]), and d = 0.27 (95% CI: [0.13, 0.42]). The heterogeneity statistics for each measure were respectively Q(109) = 614 (I 2 = 86.52, p < .0001), Q(162) = 615 (I 2 = 75.48, p < .0001), and Q(69) = 733 (I 2 = 92.37, p < .0001).

To examine the linear and curvilinear hypotheses for each outcome, we computed the average weighted effect size comparing outcomes for high fear versus moderate fear groups. For attitudes, intentions, and behaviors, the results were respectively d = 0.05 (95% CI: [−0.27, 0.36]), d = −0.09 (95% CI: [−0.29, 0.11]), and d = −0.04 (95% CI: [−0.63, 0.56]). The heterogeneity statistics for each measure were respectively Q(7) = 19 (I 2 = 66.10, p = .009), Q(8) = 19 (I 2 = 65.95, p = .01), and Q(9) = 118 (I 2 = 96.12, p < .0001).

To examine the gender hypothesis, we regressed outcomes onto the percent of the sample that was female. The results for attitudes, intentions, and behaviors were respectively b = 0.0019 ( SE = 0.0022, 95% CI for the slope: [−0.0024, 0.0061], p = .38, k = 72), b = 0.0043 ( SE = 0.0013, 95% CI for the slope: [0.0016, 0.0069], p = .002, k = 119), and b = 0.0037 ( SE = 0.0028, 95% CI for the slope: [−0.0018, 0.0091], p = .19, k = 49).

The results for all categorical moderator analyses are presented in Table A.1 .

Random-effects moderator analyses done separately for attitudes, intentions, and behaviors.

Note: SE = Self-esteem. DP = Death present in message. DA = Death absent in message. PP = Promotion/prevention. SEE = Self-esteem enhancing recommended behaviors. SEH = Self-esteem hindering recommended behaviors. d = Standardized mean effect size estimated meta-analytically for the indicated moderator level. 95% CI = The 95% confidence interval for d . k = The number of studies for each moderator level. Dash (−) indicates there were no observations at a particular moderator level.

1 We use the term effectiveness to indicate whether exposure to a fear appeal message resulted in more persuasion than a comparison condition. Thus, a fear appeal is considered effective if the effect size comparing treatment to control is significantly positive. Consequently, when testing moderation, fear appeals will be considered more effective for one level of a moderator versus another if the average effect size for the first level of the moderator is significantly larger than the average effect size for the second level of the moderator. In other words, when we compare fear appeal effectiveness for a moderator, we are comparing whether treatment led to more persuasion relative to control for one level of a moderator versus another level of that moderator.

2 Our framework addresses the relation between fear appeals and outcomes of interest (e.g., intentions) rather than the relation between fear and outcomes of interest. Although many fear appeal theories discuss fear, empirical studies typically test the impact of fear appeal messages on outcomes, and subsequently infer that message effects were mediated by experienced fear even though fear itself is rarely measured (for a discussion, see Popova, 2012 , p.466). Indeed, only 71 of the 248 studies in the current meta-analysis measured fear directly, and such measures were typically treated as manipulation checks rather than independent variables or mediators. We are therefore careful to discuss the influence of depicted message characteristics rather than subjectively experienced states (e.g., depicted fear versus experienced fear). This distinction applies to prior meta-analyses and primary studies as well, though the distinction is rarely made. We would like to thank an anonymous reviewer for encouraging us to frame our results in line with this distinction.

3 TMT theories also predict a higher order interaction between mentions of death, time delays, and self-esteem, such that the predicted effects of self-esteem discussed above become stronger after a delay ( Goldenberg & Arndt, 2008 ). Of the 12 conditions represented by this prediction (2 death × 3 delay × 2 self-esteem), four had zero observations in our meta-analysis. Thus, we are only able to test the simpler predictions concerning self-esteem and time delay in isolation.

4 Although many researchers investigate stage progression in the transtheoretical model (the process by which people move from one stage of the model to the next; Prochaska & DiClemente, 1983 ), this outcome is not directly relevant for our investigation because we are examining the effect of fear appeals on attitudes, intentions, and behaviors. It is possible that individuals would be classified as moving from one stage of the model to the next due to changes in attitudes, intentions, or behaviors, but such classification decisions are not the focus of the present study. The transtheoretical model also includes three dimensions other than the stages of change — the processes of change, self-efficacy, and decisional balance. Although we test predictions derived from the transtheoretical model more broadly, we limited our predictions to the areas that are relevant to fear appeal audiences (stages of change).

5 A number of papers did not provide the full text of the messages that were presented to each group, which made it impossible to determine if comparison groups labeled with the terms neutral message or control message were actually presented with neutral messages or with low depicted fear messages. Similarly, groups labeled with the term low depicted fear may have actually been presented with a neutral message but were nonetheless labeled as low fear because they were designed to induce relatively less fear than the experimental group. Thus, we could consistently compare relative levels of depicted fear across studies (more depicted fear vs. less depicted fear), but not absolute levels of fear (high depicted fear vs. low depicted fear vs. no depicted fear). Consequently, no message groups, neutral message groups, and low depicted fear groups were all considered appropriate comparison groups. Further, it was generally not possible to combine different potential comparison groups because information about standard deviations for the outcomes of each group was often lacking from reports, which made it unfeasible to calculate correct standard errors for combined comparison groups.

Contributor Information

Melanie B. Tannenbaum, University of Illinois at Urbana-Champaign.

Justin Hepler, University of Nevada, Reno.

Rick S. Zimmerman, University of Missouri – St. Louis.

Lindsey Saul, Virginia Commonwealth University.

Samantha Jacobs, Virginia Commonwealth University.

Kristina Wilson, University of Illinois at Urbana-Champaign.

Dolores Albarracin, University of Illinois at Urbana-Champaign.

References marked with an asterisk indicate studies included in the meta-analysis.

• Thesis SupportAll
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Fear of failure

• Perfectionism
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What is fear of failure?

Fear of failure (atychiphobia) is a paralysing feeling which you experience in a situation where performance really counts or when there is great pressure to do well.

We all have this fear occasionally, but sometimes we can be so concerned with this emotion that it brings about the very failure that was feared. This fear can be so strong that it leads to putting off risks, putting off tasks, not using talents and to undermining success. For some of us the fear of failing becomes so overwhelming that it can prevent us from getting on with and enjoying our lives.

What causes fear of failure? (or, why high achievers fail…)

Every strength can become a weakness; every talent contains an opposite. The academic environment sets high standards and wants you to exploit all your capacities. In this environment you may sometimes fear you will not succeed; when that emotion becomes too big it can undermine your goal.

There are many triggers for this feeling; common are perfectionism (too high expectations from you or your environment), clinging on too long to old habits (which were successful in the past) or simply because you believe that failure was unthinkable (the unexpected and sudden notion paralyzes you). Focusing on the bad things that could happen fuels the fear of failure. For example, if you worry about doing poorly you might have thoughts like, “What if I forget to use theory x”, or “what if my writing is not critical enough”? Too many thoughts like these leave no mental space for thinking positively about your thesis and create a vicious negative circle.

The more you focus on the bad things that could happen, the stronger the feeling of anxiety becomes. This makes you feel worse and, because your head is full of distracting thoughts and fears, it will influence your productivity in the very end.

What are the symptoms?

When you are in a stressful situation your heart beats faster and you breathe quicker, it is your body’s primitive response to a perceived attack, the fight-or-flight-reaction.

This is the physical response, other symptoms that show you are suffering from this fear:

• In case you feel reluctant to venture into new aspects of your thesis (example: instead of writing you keep looking for more articles)
• Refusal to get involved in difficult projects (example: you do all kind of tasks but postpone working on the thesis)
• Self-sabotage (example: excessive delay of plans, because you have rescheduled meetings with your supervisor you find it hard to establish contact again)
• Lack of self-confidence and very low self-esteem, you harbour negative feelings towards your own self like “I will not be able to do this”, etc.

How to manage the fear of failure?

We learn many positive things from making mistakes. Mistakes are not the equivalent of ‘failing’. Not immediately succeeding in what we want, can be seen as good in two ways: it teaches us valuable lessons (how to change things, so that we don’t repeat the same again) and it also makes us stronger by adding to our inner resources.

You can take several action steps to manage your fail of failure by navigating the toggles below.

Accept Your Fear

This is the most important thing you can do for yourself. Failure in life is inevitable. It’s not possible for you to be amazing at something immediately. It’s not possible for you to achieve everything you want to achieve immediately. It takes time. It takes work.

Since fear of failure immobilizes you, in order to overcome it, you need to take action. Do something! Action gives you the ability to change the circumstances that hold you back.

Ask any successful person and they’ll tell you they didn’t succeed after their first attempt. If you give up, failure is inevitable. But if you keep on trying, you’ll eventually get there. Whenever you feel yourself letting your fear of failure get the best of you, just ask yourself, “What would I attempt if I knew I couldn’t fail?”

Treat Failure as a Learning Opportunity

Being successful is all about learning what doesn’t work for you. Once you know what doesn’t work, you can improve on the circumstance and eventually find what does work.

Keep Believing

Believe in yourself! Know that you can do this. Know that you will do this.

Use relaxation techniques

Engage in deep breathing for 2-5 minutes. Close your eyes and concentrate on the air going in and out of your lungs. Take long, deep breaths, fill your lungs and abdomen, hold your breath, and then exhale slowly. The belly goes up and down, it goes up when inhaling and goes down when exhaling. Tense and relax different muscle groups. For example, if your shoulders are tense pull them back and hold them for a few seconds, then relax. This will help you to be aware of the relaxation of muscles and help you to relax more. Engage in guided imagery for a few minutes. Pick a scene that you find peaceful, beautiful, and natural. Think about what you see, what you hear, what you feel and what you smell while in this scene.

General tips

• When we feel afraid that we will fail at something, there are a few things we could do to gain a different perspective.
• Remember how you managed to get through the last ‘failure’ you experienced. Expect that you will sometimes fail.
• When you do fail, embrace it. Turn the failure into a positive by figuring out where you went wrong, then applying what you learned to your next endeavour.
• Consider whether you could lower your standards and still feel ‘OK’ about your result?
• Think about exactly why you are afraid to fail. Is it more about failing yourself, or failing those around you – parents? friends? supervisor?
• When you are fazed by the hugeness of a task, break it down into manageable pieces.

Get support

Seek help early! Sometimes simply talking through a problem can help you find a solution. Pick people whom you know will be sympathetic, will listen and encourage you. Student psychologists can offer short-term counselling and are specialised in fear of failure linked to student issues.

Available workshops at Maastricht University

The Student Services Centre has a wide range of training, workshops and lectures available that can help you with your studies. Take a look at their website for more information , for example on the Fear of failure training.

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Fear Theses Samples For Students

21 samples of this type

Over the course of studying in college, you will surely have to write a bunch of Theses on Fear. Lucky you if putting words together and organizing them into relevant text comes easy to you; if it's not the case, you can save the day by finding an already written Fear Thesis example and using it as a model to follow.

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Effects Of Empowerment On Police Officers In The Singapore Police Force Thesis Examples

Acknowledgments.

I am especially grateful for the support and guidance of my dissertation advisor, Dr. A. P., provided all through the progression and development on this research study.

My thanks also go to the men and women in blue of Singapore Police Force whom had provided their valuable time to participate in the survey and their willingness to share. I also would like to thank DSP (NS) Azrin Abdul Rahim and SSI Selamat Bustaman for their valuable guidance and insights towards this study.

Singapore Police Force Empowerment Thesis Example

Introduction and background, thesis on the theme in t. s. eliot's poem "hollow men".

Thomas Stearns Eliot is one of the most important poets of the 20th century of the English language. The American –born turn British poet and playwright was also a literary critic whose works are still influential to this day. “Hollow Men” is one of Eliot’s major poems published in 1925. Its main thematic concerns include the post war Europe, salvation and to some extent issues of marriage relationships which some critic attribute to Eliot’s own marriage to Vivienne which did not survive their full lives.

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Macbeth – a Study in the Psychology of Evil Thesis

Definition and theories of bisexuality theses examples, shakespeare essay outline thesis sample, introduction.

- The desires and ambition of Macbeth and Lady Macbeth drove them to commit the most hideous act. - Innocent thoughts and ambition become corrupt when you cast aside your moral judgment. - Loyalty and kingship replaced by the sweet taste of success. - Thesis statement: Lady Macbeth, unlike her husband, is unscrupulous. Her strong nature overpowers her husband’s forgiving nature and causes him to think evil. She becomes the most ruthless female, committing one act after another leaves her satiated with blood.

Does Community Policing Lead To Less Abuse Of Police Authority Thesis Examples

Community policing, homeland security thesis examples, free thesis on fable the wisdom of story and the dissemination of human experience, domestic violence: discussions theses example.

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Domestic Violence

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Executive Summary

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One of the risks that illegal migrants face when they illegally cross the border is that they risk being apprehended by the country they are migrating to. The border law enforcement agencies of the country they are migrating to will arrest the immigrants and probably depot them.

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The latest sell-off may be the beginning of the end for the tech bubble, strategist says

• The AI-fueled tech bubble could be approaching its end date, according to Paul Dietrich.
• The market strategist pointed to similarities between the recent tech sell-off and the dot-com crash.
• The economy also looks poised to enter a downturn, which will likely fuel more downside, he said.

The recent bloodbath in stocks might mark the beginning of the end of the artificial intelligence-fueled craze among investors.

Paul Dietrich, chief investment strategist of B. Riley Wealth Portfolio advisors, has been warning for months of an impending recession and stock market crash, particularly as enthusiasm for AI bleeds out of the market.

In a note on Tuesday, Dietrich said that his thesis has been bolstered by the recent sell-off sparked by weak economic data, which pushed the Nasdaq Composite into correction territory.

He pointed to the similarities between the dot-com crash and the latest drop in the stock market. Apple , which lost 79% of its total market value in the early 2000s, has dropped 8% over the past month. Amazon , which lost 93% of its total value in the dot-com era, has plunged 18% over the last month.

The flow of "smart money" in the market also suggests more downside could be on the way for tech stocks, Dietrich noted. He pointed to large stock sales initiated by tech CEOs, like Jeff Bezos, whose total sales of Amazon stock have totaled $13.5 billion so far this year. Meta CEO Mark Zuckerberg has sold off around $1 billion in company stock, while Nvidia CEO Jensen Huang has sold nearly half a billion worth of company shares so far this summer, according to securities filings.

"These investors do not think their companies are bad investments; they merely believe the stock market is currently valuing them far above their worth," Dietrich said. "I feel sorry for many average investors still piling into the stock market chasing the Artificial Intelligence (AI) hype and other tech stocks when many of those founders are selling out."

The economy, meanwhile, looks poised to enter a recession, Dietrich said, posing more bad news for stocks. Historically, stocks have declined 36% when the economy enters a recession, even if the downturn proves to be mild, Dietrich has said in previous notes.

He pointed to a slew of indicators that could suggest a downturn is on its way. Markets are coming off of one of the longest bull markets of all time, he noted. Corporate earnings have been "spotty." Interest rates in the economy remain at their highest levels since 2001. Meanwhile, the economy has triggered multiple recession warnings with near-perfect track records, like the yield curve inverting , and the unemployment rate rising past a key threshold typically associated with recessions.

"What kind of evidence does one need to see that we are moving into a business cycle recession," Dietrich said. "Eventually, we will have another long-term bear market recession."

Though he didn't have an exact prediction for when a downturn could strike, Dietrich said the economy could start entering a mild recession by the end of the year. That could fuel as much as a 40% downside in the S&P 500, he predicted, pointing to historical losses in the stock market when the economy entered a recession.

Recession fears spiked last week after the job market was found to slow more than expected in the month of July, fueling concerns that the Fed may have made a mistake keeping interest rates too-high for too-long. Investors are ramping up bets for steep rate cuts and even an emergency rate cut by the end of the year, a move central bankers have typically only employed during times of extreme volatility.

• Main content

Election Highlights: Trump Takes Stage in Montana After Harris and Walz Rally in Arizona

After the new Democratic ticket made its appeal in the battleground border state, the former president is stumping for the Republican challenging Senator Jon Tester.

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Michael Gold and Simon J. Levien

Reporting from Bozeman, Mont.

Fine-tuning his attacks on Harris, Trump tries using her words against her.

As former President Donald J. Trump continues to reach for attacks on his new opponent, Vice President Kamala Harris, that might halt her political momentum, he unveiled a new tactic at a rally in Bozeman, Mont., on Friday night, aiming to use Ms. Harris’s own words against her.

Interrupting his typical pattern of a digressive and lengthy speech, Mr. Trump played two video compilations of past remarks by Ms. Harris that his campaign hopes will portray her as overly liberal and inept.

The first video drew on statements that Ms. Harris made during the 2020 presidential campaign, when she tacked to the left and backed progressive ideas on criminal justice reform. The second was a montage of interviews and speeches that Mr. Trump’s campaign used to mock her speaking style and insult her intelligence.

The videos did little to alter the message that the Trump campaign has deployed against Ms. Harris for weeks and that Mr. Trump summed up during his speech on Friday.

“America cannot survive for four more years of this bumbling communist lunatic,” Mr. Trump told thousands gathered in the Brick Breeden Fieldhouse at Montana State University. “We cannot let her win this election.”

Mr. Trump and his allies have repeatedly tried to portray Ms. Harris as more liberal than President Biden in the three weeks since he ended his campaign and cleared the way for her to be the Democratic presidential nominee.

The video compiling her past positions accused her of supporting a ban on fracking, mandatory gun buybacks and a single-payer health insurance system like “Medicare for all.”

Ms. Harris has backed away from those policy positions, which largely stem from her time in the 2020 presidential race. But Mr. Trump — who has been known to flip-flop or equivocate on hot-button issues like abortion — argued that her early statements were the only ones that mattered.

Mr. Trump’s rally on Friday was his first since Ms. Harris chose Gov. Tim Walz of Minnesota as her running mate, and he used the selection to bolster his portrait of the Democratic ticket as overly liberal. Effectively likening Mr. Walz to a socialist, he accused the governor of being too lax in his response to protests that turned to riots in Minneapolis after the police murder of George Floyd and for signing a law giving access to menstrual products to transgender children.

Referring to Mr. Walz as “Comrade Walz,” Mr. Trump argued that Ms. Harris tapped him for his progressive bona fides. “This is her ideology,” he said.

Mr. Trump also acknowledged that he has frequently mispronounced Ms. Harris’s given name in recent speeches, though he added that he “couldn’t care less” how it should be pronounced. He admitted that he has in the past “done a lot of bad name-calling” in which he has purposefully mispronounced a person’s name. “They say, ‘Sir, you made a mistake,’” Mr. Trump recounted. “I said, ‘No, I didn’t.’”

Still, Mr. Trump’s speech offered continued evidence of the growing pains he has faced as he tries to shift years of attacks against Mr. Biden toward Ms. Harris.

Even as he argued that Ms. Harris was more extreme than Mr. Biden, he tied her to the president’s policies on immigration and the economy.

At one point, he said she was the one running the country the past four years, even as he repeatedly argued that she was too unintelligent or incompetent to do so effectively. Mr. Trump has long made the same argument about Mr. Biden.

Mr. Trump's rally is part of a western swing that includes fund-raisers in mountain resort towns favored by the wealthy. Before he took the stage in Bozeman, he attended an event in Big Sky, Mont., and on Saturday he will travel to fund-raisers in Jackson Hole, Wyo., and Aspen, Colo.

Montana is not an obvious site for a presidential campaign rally. Mr. Trump won the state handily in both 2016 and 2020, and he is expected to do so again in November. But with Republicans keen on flipping Democrats’ narrow edge in the Senate, Mr. Trump traveled to Montana to support his party’s Senate candidate there, Tim Sheehy, who is looking to unseat the Democratic incumbent, Senator Jon Tester.

At one point, Mr. Trump, whose flight to Bozeman was diverted to another city after his plane suffered a mechanical issue, reflected on how long it takes to travel to Montana.

“I’ve got to like Tim Sheehy a lot to be here,” he said.

Shawn Hubler Maggie Haberman and Heather Knight

Yes, Trump was in a scary helicopter ride, but not with that politician.

Donald J. Trump was doubling down on Friday about his story of nearly crashing during a helicopter ride once with Willie Brown, the notable Black California politician.

He was so adamant that it had happened that he threatened to sue The New York Times for reporting that the story was untrue , then posted on his social media site that there were “‘Logs,’ Maintenance Records, and Witnesses” to back up his account.

“It was Willie Brown,” Mr. Trump, who spent much of the last year hoping to make gains with Black voters, posted. “But now Willie doesn’t remember?”

Mr. Brown, 90, who was mayor of San Francisco and speaker of the California Assembly, gave several interviews on Thursday and Friday saying such a trip never occurred.

Turns out, however, that there was a Black politician from California who once made an emergency landing in a helicopter with Mr. Trump. It just wasn’t Mr. Brown.

Nate Holden, 95, a former Los Angeles city councilman and state senator, said in an interview with The Times that he had been on a helicopter ride with Mr. Trump around 1990 when the aircraft experienced mechanical trouble and was forced to make an emergency landing in New Jersey.

Recounting an episode that he had described earlier on Friday to Politico, Mr. Holden said Mr. Trump had been seeking to develop the site of the Ambassador Hotel in Los Angeles when it was part of Mr. Holden’s district. Mr. Trump wanted him to see his Taj Mahal casino, Mr. Holden said, so on a visit to Manhattan, he rode with Mr. Trump from his Midtown skyscraper to a helipad, where the two took off for Atlantic City, accompanied by Mr. Trump’s brother Robert and by his executive vice president of construction and development, Barbara Res.

“He was trying to impress me,” Mr. Holden said. “We start flying to New Jersey. He said, ‘Look at the skyline! Look at how beautiful it is! And I’m part of it!’”

Mr. Holden said he wasn’t impressed. “I grew up in New Jersey,” he said. “It ain’t nothing new to me.”

“Anyway,” he continued, “we start flying to Atlantic City. He’s talking about how great things are. And about 15, 20 minutes in, the pilot yells, ‘Shut up! Shut up!’”

The hydraulic system had failed, he said. “Donald turned white as snow,” Mr. Holden recalled. “He was shaking.”

Mr. Holden said that as the helicopter’s crew worked frantically to set the aircraft down safely, his own thoughts ran to a helicopter crash in 1989 that had killed three senior executives of Mr. Trump’s casinos over Forked River, N.J.

“I just thought, how the hell do you let your staff not maintain your aircraft after you just had a crash that killed some of your staff? How could you let this happen again? I thought, if we go down, this is your fault.”

The helicopter ultimately landed safely in Linden, N.J., Mr. Holden said.

Ms. Res wrote about the episode in a memoir and corroborated Mr. Holden’s account in a brief interview late Friday. Ms. Res, who also spoke to Politico, recalled that Mr. Trump liked to say that Mr. Holden had “turned white” from fear, but that it was actually Mr. Trump whose face was ashen.

A spokesman for Mr. Trump did not immediately respond to an email seeking comment.

Mr. Holden said he was in his living room watching Mr. Trump’s news conference on TV on Thursday when the former president told of experiencing a brush with death on a helicopter ride with Mr. Brown.

“I said, ‘What the hell is this?’” Mr. Holden said. “‘Was he in two near-fatal helicopter crashes? He didn’t fix those damn helicopters yet?’”

Mr. Holden said that he called Mr. Brown to compare notes. Mr. Brown told him he had never been in a helicopter with Mr. Trump.

“I said, ‘Willie, you know what? That’s me!’” Mr. Holden said. “And I told him, “You’re a short Black guy and I’m a tall Black guy — but we all look alike, right?”

Mr. Holden gave his own height as 6-foot-1. “Willie has to be about 5-foot-6. Maybe 5-foot-5. He comes up to about my shoulders. And he’s bald. And I’m not bald.”

Mr. Brown, he said, “just laughed and laughed.”

Mr. Holden, summing up his assessment of Mr. Trump’s recollection, said: “I just think he makes things up. That’s what I think. He never thought anybody’s going to check.”

Mr. Trump told the story about nearly dying in a helicopter crash with Mr. Brown after a reporter at Thursday’s news conference asked him a leading question about Vice President Kamala Harris’s long-ago relationship with Mr. Brown and whether it helped her career trajectory.

The two dated in 1994 and 1995 when she was a prosecutor in Alameda County, which includes Oakland, and Mr. Brown was the Assembly speaker. Mr. Brown appointed Ms. Harris to two state boards before she ended their relationship.

“Well, I know Willie Brown very well,” Mr. Trump responded. “In fact, I went down in a helicopter with him.”

He recounted how the two had a close brush with death — “We thought maybe this was the end” — and that Mr. Brown used the frightening ride to tell him “terrible things” about Ms. Harris. “He was not fan of hers very much, at that point,” Mr. Trump said.

Mr. Trump had previously told the story, saying it was Mr. Brown on a helicopter with him, in his book, “Letters to Trump,” which was published in 2023.

Reached again Friday night, Mr. Brown reiterated that he had never flown in a helicopter with Mr. Trump and that he had not denigrated Ms. Harris to the former president because he admires and respects her.

“Those are the two things I am certain of,” he said. “All the rest of this is amusing.”

Asked if Mr. Trump might have confused the two California politicians because they are both Black, Mr. Brown said, “I wouldn’t want to conclude that he can’t tell Black people apart, because I’d hate for him to think that I’m Beyoncé.”

And then he burst out laughing.

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Simon J. Levien

People are filing out of the stands at Trump’s rally in Bozeman. He took the stage about 90 minutes after he was originally scheduled to speak after his plane had to land in a different city, and he spoke for about 90 minutes.

Michael Gold

Trump acknowledged that he came to Montana to help boost Republicans’ chances of ousting Senator Jon Tester, the Democratic incumbent. After repeatedly mocking Tester’s weight, he complimented the Republican candidate, Tim Sheehy, over his military service and business acumen. Then, he briefly ceded the stage to Sheehy.

As he continued to try to paint Harris as too liberal for America, Trump stopped his own speech about 40 minutes in to play a video of a number of Harris’s past remarks during her 2020 campaign, when she backed gun buybacks and banning fracking. Harris has moved away from some of the positions she took during her failed presidential bid as she runs now.

And in another unusual interruption, Trump paused his speech with another video, this time a montage of clips from speeches and interviews by Harris that were meant to mock her intelligence and her ability to speak off the cuff.

Trump’s rally in Montana is his first since Kamala Harris chose Gov. Tim Walz of Minnesota as her running mate, and he’s now attacking Walz as overly liberal. He accused Walz of defending socialism, being too lax in his response when protests turned to riots in Minneapolis after the police murder of George Floyd and for being too liberal on issues pertaining to transgender children.

“He ordered tampons in boys’ bathrooms,” Trump said about Walz. “This is her ideology; that’s why she picked him.” While Walz was governor, Minnesota passed a law ordering free menstrual products to be available in public schools for grades 4 through 12. The law Walz signed did not specify putting tampons in boys’ bathrooms, just that schools make tampons available to those who need them.

Trump seemed to acknowledge that his own running mate, Senator JD Vance of Ohio, had a rough start on the trail as old comments he made were unearthed. “He’s got his sea legs now,” Trump insisted at his rally in Bozeman. “He’s going to be great.”

“We’re going back to Butler,” Trump said after talking about the attempt on his life in Butler, Pa., a story that he tells at nearly every rally now, despite saying somberly in his convention speech last month that he would only discuss it that once . He previously announced on his social media site that he would hold a second rally in Butler in part to honor Corey Comperatore, who attended the rally and was shot and killed . His campaign has not announced a date.

Trump just repeated at the Bozeman rally a claim he made on Truth Social previously that Biden would somehow “make a comeback” at the Democratic National Convention and try to take back the nomination. There’s no evidence to support this, and Kamala Harris has already secured the party’s presidential nomination in a virtual roll call of delegates.

Trump has mispronounced Kamala Harris’s name quite a bit in the last few weeks, and in Bozeman, he said he “couldn’t care less” how you say it. Then, he admitted that he has in the past “done a lot of bad name-calling” where he has purposefully mispronounced somebody’s name. “They say, ‘Sir, you made a mistake.’ I said, ‘No, I didn’t.’”

Donald Trump, perhaps flicking at his travel woes earlier after his plane suffered a mechanical issue and was diverted to another city, reflected on how long it takes to travel to Montana. “I’ve got to like Tim Sheehy a lot to be here,” he said. Then, he pledged that Republicans would defeat Senator Jon Tester, the Democratic incumbent, in November, as well as Kamala Harris.

A large screen display at Trump’s rally in Bozeman features a news headline declaring Harris as the first Indian-American senator. This is true. But this display alludes to Trump’s comments last week at a conference for Black journalists when he said Harris “became a Black person” only recently for political advantage. Harris, whose mother was Indian American and whose father is Black, and who attended the historically Black Howard University, has always identified as a Black woman.

Tim Sheehy, the Republican candidate for Senate in Montana, opened his remarks at Trump’s rally in Bozeman by referring derisively to gender pronouns and to transgender athletes, a culture-war issue that fires up Republican voters. Then, Sheehy, a former Navy SEAL, touted his record as a veteran, which drew cheers from a crowded arena.

He then tried to tie his Democratic opponent, Senator Jon Tester of Montana, to Vice President Kamala Harris, accusing both of them of voting against America’s interests.

These opening lines from Sheehy have become tried and true with Republican audiences. He opened his speech at the national convention in Milwaukee last month with similar words.

Kellen Browning and Shane Goldmacher

Harris rides momentum to Arizona, for what her campaign says is largest rally yet.

Vice President Kamala Harris rolled into Arizona on Friday evening with the same political momentum that has infused her first swing across the country this week, drawing a crowd that her campaign estimated at more than 15,000 — her largest yet — in a Western state that not long ago appeared to be falling off the battleground map.

Along with her newly minted running mate, Gov. Tim Walz of Minnesota, Ms. Harris delivered a stump speech that is barely a week old, and yet familiar enough to an impassioned new following that some shouted her lines before she did.

The rally was her fourth in four days with an arena-filling crowd that demonstrated the degree to which her candidacy replacing President Biden’s had remade the 2024 race.

Mr. Walz relished the crowd that filed into the Desert Diamond Arena in Glendale, Ariz., in 100-degree heat as he poked fun at Mr. Trump’s obsession with rally crowds.

“It’s not as if anybody cares about crowd sizes or anything,” Mr. Walz said to knowing cheers.

Despite her momentum, Ms. Harris faces an uphill battle in Arizona , a longtime Republican stronghold that flipped to Mr. Biden in 2020 but, according to polling, had been drifting back to former President Donald J. Trump this year.

To win, she will need to reunite the diverse coalition of voters who delivered the state four years ago, and she made an explicit appeal to one part of that group on Friday: Native American voters.

“As president, I will tell you, I will always honor tribal sovereignty and respect tribal self-determination,” she said. The first speaker at the rally, notably, was Stephen Roe Lewis, the governor of the Gila River Indian Community, south of Phoenix.

In her speech, Ms. Harris zeroed in on two issues that are especially pertinent to Arizonans: immigration and abortion.

Crossings from Mexico into Arizona have remained high this year even as they have dropped elsewhere, and Ms. Harris positioned herself as supporting both an “earned pathway to citizenship” and tougher border restrictions, pointing to her record as California’s attorney general.

“I went after the transnational gangs, the drug cartels and the human traffickers,” Ms. Harris said. “I prosecuted them in case after case, and I won. So I know what I’m talking about.”

By contrast, Ms. Harris said, Mr. Trump was playing politics with the issue. She highlighted his opposition to a bipartisan bill this year that would have beefed up border security.

“He talks a big game about border security,” she said, “but he does not walk the walk.”

The comments come as her campaign began to air a tough-on-immigration ad that labeled her a “border-state prosecutor.” Senior Trump campaign officials see the border and immigration as one of Ms. Harris’s deepest areas of vulnerability, and his campaign has repeatedly labeled her, inaccurately , as Mr. Biden’s failed “border czar.”

Ms. Harris did add a new riff to her speech, responding to Mr. Trump’s muddled comments on Thursday at a news conference in Florida, in which he did not rule out directing the Food and Drug Administration to revoke access to abortion pills.

Ms. Harris said Mr. Trump’s agenda “would ban medication abortion in every state,” adding, “But we are not going to let that happen — because we trust women.”

Mr. Trump has previously supported the Supreme Court’s ruling on the abortion drug mifepristone. Karoline Leavitt, a Trump spokeswoman, said in a statement the former president’s position on mifepristone “remains the same — the Supreme Court unanimously decided on the issue and the matter is settled.”

The abortion rhetoric could prove especially potent in Arizona, where the State Supreme Court reinstated a near-total ban on the procedure this year. The State Legislature eventually repealed it, but abortion is still banned after 15 weeks, and voters will have a chance to enshrine the right to an abortion until fetal viability in the state’s Constitution through a ballot measure in November.

The speakers who preceded Ms. Harris on Friday made a number of appeals to independents and moderate Republicans, another segment she will need to win over.

“I do not recognize my party,” said John Giles, the mayor of Mesa, Ariz., who is a prominent Republican backing Ms. Harris. “We need to elect a ticket who will be the adults in the room.”

Senator Mark Kelly, the Arizona Democrat who is also a Navy veteran and former astronaut, introduced Ms. Harris and Mr. Walz. It was the second time this week that a finalist in Ms. Harris’s running-mate sweepstakes introduced her at a rally. Gov. Josh Shapiro of Pennsylvania did the same in Philadelphia on Tuesday.

Mr. Kelly said Mr. Trump had “zero respect for any of us who have worn the uniform.” Mr. Trump’s allies have raised questions about Mr. Walz’s decision to leave the National Guard in 2005 to run for Congress.

Attendees and speakers said the enormous crowd braving scorching desert temperatures on Friday was a sign that, after months of dreariness among Democrats, momentum in Arizona was finally on their side.

“It may be a little warm outside,” Kate Gallego, the mayor of Phoenix, said, “but based on the energy in this arena, I know it’s Donald Trump who’s feeling the heat.”

Harris has been holding rallies with thousands of attendees this week. At Trump’s rally in Montana this evening — his first since the Democratic ticket was solidified — the venue, which can seat more than 8,000 people, is nearly full. Montana is friendly territory for the former president; it is a state he won in 2016 and 2020 and is not widely considered a battleground this year.

Even though this is a Trump campaign rally, several of the speakers who have taken the stage in the last hour have made it clear that their focus is as much on Montana’s Senate race as the presidential contest. “I want to welcome you to Jon Tester’s retirement party,” Steve Daines said to a cheering crowd, before pivoting to calling for Trump’s election in November.

Kellen Browning

Harris just wrapped up speaking here in Glendale, ending with what has become a classic call-and-response line. “When we fight,” she began, and the crowd roared back: “We win!”

Shane Goldmacher

In Arizona, where immigration is a top issue and the border a daily reality, Harris is citing her work as California attorney general, saying she went after “transnational gangs” and “drug traffickers.” This is a history she did not emphasize in the 2020 Democratic primary. But, as a general election candidate, it is a point of emphasis, including in a new television ad.

Harris is taking the issue of immigration — seen as a political vulnerability for her — head on, saying she supports “strong border security and an earned pathway to citizenship.” She accused Donald Trump of having “no interest or desire to actually fix this problem,” pointing to the fact that he tanked a bipartisan border security deal earlier this year.

Erin Schaff

Vice President Kamala Harris and her chief of staff, Sheila Nix, watching her running mate, Gov. Tim Walz of Minnesota, warming up the Glendale, Ariz., crowd from backstage at their rally.

Chris Cameron

Walz had said that tonight’s rally in Glendale “might be the largest political gathering in the history of Arizona.” That’s a broad claim to make, and it’s hard to exactly measure, but there have been political gatherings of a similar size in Arizona. Trump claimed in 2017 that 15,000 people turned out for a rally in Phoenix, and a city official said that about 10,000 people were inside the rally with another 4,500 to 5,000 turned away at the door. The Harris campaign estimated that more than 15,000 people are at this rally in Glendale.

Senator Steve Daines of Montana, the leader of the National Republican Senatorial Committee, told reporters that he thought Gov. Tim Walz of Minnesota was the best choice Kamala Harris could have made for a running mate from the perspective of the battle to control the Senate. While he thought that Senator Mark Kelly of Arizona and Gov. Josh Shapiro of Pennsylvania would have helped Democratic Senate candidates in those states, Walz, he said, would not provide such a boost anywhere on the map.

Harris makes an explicit appeal to a crucial part of the Democratic coalition in Arizona: Native American voters. “As president, I will tell you, I will always honor tribal sovereignty and respect tribal self-determination,” she said.

Reid J. Epstein

Harris, in a bit of local policy for Arizona’s large Native American population, said that as president she would respect tribal self-determination. “I know we have a number of Native leaders, and as president, I will tell you, I will always honor tribal sovereignty and respect tribal self-determination and fight for a future where every Native person can realize their aspirations,” she said.

Harris, interrupted by pro-Palestinian and anti-Gaza war protesters, addresses them directly: “I have been clear, now is the time to get a cease-fire deal,” she says.

Vice President Kamala Harris, now onstage, is complimenting Senator Mark Kelly, who was a finalist that she passed over to be her running mate. “I am so grateful, Mark, for your friendship and your leadership,” she said.

Walz's defense of I.V.F. and of the freedom to make reproductive health care decisions, peppered throughout his speech, could hit particularly hard in Arizona, where the State Supreme Court reinstated an 1864 near-total ban on abortion this spring. It was eventually repealed by the State Legislature, but there is still a 15-week ban on the books.

Walz called the prospect of electing Ruben Gallego to the Senate a “twofer,” because of who would not be elected instead: a reference to Gallego’s Republican opponent, Kari Lake. The lines criticizing Lake, a Republican who is enormously unpopular among Democrats — and some members of her own party — have gotten some of the biggest applause so far.

The crowd begins chanting “lock him up!” as Walz talks about Donald Trump, but he quickly counters: “Better yet, beat the hell out of him at the ballot box.”

The Harris-Walz ticket is less than a week old and already the crowd feels primed for some of the familiar lines from Walz’s speech. They were waiting for the word “joy” and exploded when it came.

Maggie Haberman

Trump claims he has helicopter trip records and threatens to sue.

Former President Donald J. Trump on Friday afternoon vehemently maintained that he had once been in a dangerous helicopter landing with Willie Brown , the former mayor of San Francisco, and insisted he had records to prove it, despite Mr. Brown’s denial.

In an angry phone call to a New York Times reporter as he landed several hours away from his planned rally in Bozeman, Mont., because of a mechanical issue on his plane, Mr. Trump excoriated The Times for its coverage of his meandering news conference on Thursday at Mar-a-Lago, his private club and home, during which he told of an emergency landing during a helicopter trip that he said both he and Mr. Brown had made together.

Mr. Trump was expected to keep his rally schedule on Friday as planned, boarding a smaller plane to complete the journey.

Mr. Brown denied on Thursday that he had ever flown in a helicopter with Mr. Trump.

It appeared Mr. Trump may have confused Willie Brown with Jerry Brown, the former governor of California, with whom Mr. Trump traveled by helicopter in 2018 while surveying wildfire damage in the state. But Jerry Brown, who left office in January 2019, said through a spokesman, “There was no emergency landing and no discussion of Kamala Harris.”

Willie Brown, who was a boyfriend of Vice President Kamala Harris during the 1990s, knew Mr. Trump as a potential business associate during those years, when Mr. Trump, then a New York developer, was working on new projects. A biography of Ms. Harris, “Kamala’s Way: An American Life,” reported that Mr. Trump had sent his private plane for Mr. Brown and Ms. Harris in 1994 to fly them from Boston to New York City.

“We have the flight records of the helicopter,” Mr. Trump insisted Friday, saying the helicopter had landed “in a field,” and indicating that he intended to release the flight records, before shouting that he was “probably going to sue” over the Times article.

When asked to produce the flight records, Mr. Trump responded mockingly, repeating the request in a sing-song voice. As of early Friday evening, he had not provided them.

Mr. Trump has a history of claiming he will provide evidence to back up his claims but ultimately not doing so.

He has also told the helicopter story before, in his 2023 book, “Letters to Trump,” in which he published letters to him from a number of people, including Mr. Brown. In the book, Mr. Trump wrote, “We actually had an emergency landing in a helicopter together. It was a little scary for both of us, but thankfully we made it.”

Neil Vigdor

Two rivals in Michigan’s crucial Senate contest say they were both swatted.

The two leading contenders for Michigan’s open Senate seat disclosed that they had been targeted in separate “swatting” incidents in a span of less than 24 hours, just days after winning primaries in a crucial contest that could determine which party controls the chamber.

The first incident, involving Representative Elissa Slotkin, a Democrat, happened on Thursday night at her home in Oakland County, north of Detroit. The second one occurred on Friday at an address that had been listed on public records under the name of Mike Rogers, the Republican candidate and former House member, in neighboring Livingston County.

Politicians on both sides of the political aisle have increasingly been the target of swatting in recent years. The hoaxes — when false threats are deliberately made to law enforcement to draw a heavily armed response to a person’s home — have added to a climate of intimidation and the harassment of public officials.

Ms. Slotkin was not home at the time of the incident, according to a spokeswoman for her office, Lynsey Mukomel, who said in a statement that Michigan State Police troopers went to the residence after a false threat was emailed to a local official. She did not elaborate on the nature of the false threat. Michigan State Police confirmed they responded.

“Michigan State Police checked the property and confirmed no one was in danger,” Ms. Mukomel said, adding that U.S. Capitol Police would investigate the incident.

Mr. Rogers, a former longtime House member who was endorsed by former President Donald J. Trump, experienced a similar incident around 12:30 p.m. Eastern time on Friday, said Chris Gustafson, a spokesman for his campaign.

A person reported that a man was holding a woman at gunpoint at the property in Livingston County connected with Mr. Rogers, according to Mr. Gustafson, who said that Mr. Rogers currently does not live there but that other members of his family do.

Shanon Banner, a Michigan State Police spokeswoman, said that a sergeant had responded to a report about a domestic situation at a residence in Livingston County on Friday and determined that it was false. She was not immediately able to confirm whether it was the same property.

Mr. Gustafson, in a statement, said that it was the second time that Mr. Rogers had been targeted in a swatting incident. The first was in 2013, when he was a member of Congress.

“This kind of violence cannot be tolerated, and it is our hope that those responsible will be quickly prosecuted and held accountable,” Mr. Gustafson said.

The rivals are running for a seat that is being vacated by Senator Debbie Stabenow, Michigan’s senior senator and a Democrat, who announced last year that she would not seek a fifth term . Democrats control the Senate by a thin 51-49 seat majority.

Ken Bensinger

Joe Rogan would like to clarify: He did not endorse Robert F. Kennedy Jr.

The world’s most popular podcaster has, sort of, but not really, thrown his support to one of the 2024 presidential race’s least popular candidates.

On Thursday, Joe Rogan said he preferred Robert F. Kennedy Jr., who is running as an independent, for president. “He’s the only one that makes sense to me,” Mr. Rogan said, as a guest on a podcast hosted by Lex Fridman, and called Mr. Kennedy a “legitimate guy.”

Mr. Rogan’s devoted following, one that leans young, male and numbers in the tens of millions, is highly coveted. His remarks about Mr. Kennedy, uttered on a show with a far smaller reach than his own, nonetheless set off a frenzied response.

Supporters of former President Donald J. Trump, worried that Mr. Rogan’s stance could carve off voters and hurt his electoral chances come November, quickly turned on the podcaster, standup comic and U.F.C. announcer. They questioned his intelligence and even mocked his height , a spectacle that was greeted with something akin to joy — or, at least, schadenfreude — among Democrats who have long written off Mr. Rogan as helpful to their cause.

By Friday morning, Mr. Rogan was backpedaling. “This isn’t an endorsement,” he posted on the social media platform X, and advised that he is “not the guy to get political information from.”

Mr. Trump himself weighed in on Friday afternoon, pondering “how loudly Joe Rogan gets BOOED the next time he enters the UFC ring” in a post on his social network that seemingly reflected his concerns that the influential podcaster could tip the scales against him.

“This takes straight from the Trump base,” said Mike Madrid, a Republican political consultant. A New York Times/Siena poll in battleground states in May found that 54 percent of respondents who said they planned to vote for the former president had a favorable opinion of Mr. Rogan.

Mr. Kennedy, long before Mr. Rogan’s unwinding act, had already taken credit for the perceived nod, posting on social media: “From one ‘legitimate’ guy to another, thank you.”

Even if it’s not a true endorsement, Mr. Rogan’s praise could come as a huge shot in the arm for Mr. Kennedy, who has seen his polling average drop from as much as 15 percent in early June to somewhere around 6 percent as of late last month.

While Mr. Kennedy drew national attention this week after acknowledging that he dumped a dead bear cub in Central Park a decade ago, such headlines have not helped ease his struggles raising money . He’s also fighting to get his name on the ballots in critical states, or, in the case of New York , keep it there.

“He doesn’t attack people. He attacks actions and ideas, but he’s much more reasonable and intelligent,” Mr. Rogan said of Mr. Kennedy on the “Lex Fridman Podcast,” which has 4.1 million subscribers on YouTube.

Mr. Rogan’s fan base is much bigger. In March, Spotify said that “The Joe Rogan Experience” had 14.5 million followers , almost triple the platform’s second most popular program. He also has 19 million followers on Instagram and 17 million followers on YouTube.

A poll by YouGov last year found that 81 percent of his listeners are male and 56 percent are under 35 years old , feeding the perception that he has a direct line to a cohort that polling suggests tends to support Mr. Trump over Vice President Kamala Harris.

“This is a group Trump needs strong performance with,” Mr. Madrid said.

During his interview with Mr. Fridman, he said that he was “not a Trump supporter in any way, shape or form” and adding that he turned down multiple offers to have him on his show. “I’ve said no every time,” Mr. Rogan said. “I’m not interested in helping him,”

Mr. Kennedy sat for an interview on the “Joe Rogan Experience” in June 2023.

Ruth Igielnik contributed reporting.

Jazmine Ulloa

Reporting from Washington

A Latino rights group breaks with its history to endorse the Harris-Walz ticket.

The League of United Latin American Citizens, one of the nation’s oldest Latino civil rights organizations, said on Friday that it supported Vice President Kamala Harris and her running mate, Gov. Tim Walz of Minnesota, the first formal endorsement of a presidential ticket in the group’s 95-year history.

Leaders of the group, known as LULAC, acknowledged that it had previously refrained from endorsing political candidates but said that members were stirred to action by concerns over the potential negative impact on Latinos if former President Donald J. Trump were elected again.

The endorsement was carried out through the group’s political action committee, the LULAC Adelante PAC, after internal conversations and a unanimous vote. Leaders said they decided to endorse Ms. Harris and Mr. Walz because they were better equipped to address the issues facing Latino communities.

“We can trust them to do what is right for our community and the country,” Domingo Garcia, the chairman of the PAC and a past LULAC president, said in a statement.

Latinos, a multiracial and multiethnic slice of the electorate that made up 10 percent of American voters in 2020, tend to vote Democratic.

But they have been at the center of a tug of war between Democrats and Republicans since Mr. Trump improved his standing with Latinos in 2020 compared with his 2016 campaign. As Mr. Trump and President Biden appeared to be headed for a rematch in the 2024 presidential election, a significant number of Latinos had been considering a third-party option .

Latino rights leaders and elected officials have quickly coalesced behind Ms. Harris since she replaced Mr. Biden at the top of the ticket. They said Mr. Trump’s pledges to cut low-income assistance programs and enact hard-line immigration policies would hurt Latino communities across the country.

Leaders of LULAC and similar groups said Ms. Harris’s candidacy had shot new energy into their outreach efforts. Some early polling has captured higher enthusiasm for her than Mr. Biden among Latino voters, but reliable data since the switch is limited.

LULAC, founded in South Texas by a group of mostly Mexican American veterans of World War I, has traditionally taken more conservative stances than other Latino rights groups. Its endorsement will allow its councils, which function as local chapters, to register voters and knock on doors in battleground states, particularly Nevada, Arizona, Georgia, Pennsylvania and Wisconsin. The organization has 535 councils nationwide and 140,000 members, 86 percent of whom are registered to vote and more than 75 percent of whom voted in the 2020 election, its officials said.

In a statement, Julie Chavez Rodriguez, Ms. Harris’s campaign manager, called the endorsement an honor. “The stakes of this election require Latinos to unify and organize together like our lives depend on it,” she said.

The Trump campaign said that the LULAC endorsement came as no surprise. In a statement, Jaime Florez, the campaign’s Latino media director, argued such groups were out of touch with Latino voters, saying their lack of interest in what matters to Latinos had caused many to leave the party behind.

Until now, the closest LULAC had come to endorsing a presidential candidate was in 1956, when Felix Tijerina, then the group’s president, personally backed the Eisenhower-Nixon ticket. He wore an Ike pin on his lapel, according to news coverage from that time. Some members of the group were also active in clubs boosting John F. Kennedy in 1960, and others have supported local candidates, including Raymond Telles, the former mayor of El Paso.

Mr. Trump now points to the Eisenhower administration’s mass deportations of Mexicans and Mexican Americans as a model that his own administration would follow as he promises to undertake the largest deportation effort in U.S. history.

In an interview, Juan Proaño, LULAC’s chief executive, said the group’s values had evolved since the 1960s, when fierce wage competition and divisions between Mexican and Mexican American laborers initially put the Latino rights group in favor of Eisenhower’s mass deportations. The organization reversed its stance when it was no longer possible to ignore the devastation that the deportations inflicted on Mexican American neighborhoods and border regions.

Ahead of its endorsement, LULAC released an analysis of Mr. Trump’s promises. It cited a range of his proposals that would hurt Latinos, including cuts to education budgets and social safety net programs, and policies that would shut down the border, undo birthright citizenship and roll back protections for young people brought into the country illegally as children.

“We can’t risk mass deportations, we can’t risk family separations,” Mr. Proaño said.

Tim Walz’s class project on the Holocaust is drawing new attention online.

The prediction was spot on: Rwanda was barreling toward a devastating genocide.

It did not emanate from a think tank, but from a high school geography class in western Nebraska. The year was 1993. The teacher? Tim Walz, now the Democratic vice-presidential candidate and Minnesota governor.

Thirty-one years later, the class project is drawing new attention. Mr. Walz, a geography teacher at the time, had asked his students to take what they had learned about the Holocaust to predict which nation was most at risk for genocide.

“They came up with Rwanda,” Mr. Walz said, talking about the project at a conference last month . “Twelve months later, the world witnessed the horrific genocide in Rwanda.”

The project was reported on in a 2008 On Education column for The New York Times that has been widely shared in recent days. Mr. Walz had drawn the attention of the reporter, Samuel G. Freedman, for an earlier column because Mr. Walz was the only K-12 teacher serving in Congress at the time, Mr. Freedman said.

“While I was interviewing Walz for the initial column, he told me how the genocide project was one of his proudest moments as an educator,” said Mr. Freedman, who is now a journalism professor at Columbia University . That sparked Mr. Freedman to revisit the story later.

Mr. Walz, when he delivered the lesson plan, had been teaching global geography in Alliance, Neb., and had been chosen for a Belfer fellowship to the United States Holocaust Memorial Museum that was opening. Speaking at the conference last month, held by Esri, a company that makes G.I.S. software widely used in mapping, he said the project had a profound effect on his students and bred some cynicism.

“How could a bunch of students in western Nebraska, in Alliance, use a computer program and some past historical knowledge to come up with this?” he said. “Why was nobody doing anything about that?”

Several years later, when he was studying for his master’s degree in experiential education at Minnesota State University, Mankato, Mr. Walz wrote his thesis on Holocaust education, the Jewish Telegraphic Agency reported .

As governor, Mr. Walz signed a bill last year that requires high schools and middle schools to teach about the Holocaust, along with other genocides.