examples of critical thinking in mental health

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What Is… Critical Thinking

In this series, I dig a little deeper into the meaning of psychology-related terms. This week’s term is critical thinking.

The Stanford Encyclopedia of Philosophy says that, while there are various different definitions, the basic underlying idea is “careful thinking directed to a goal.” Wikipedia describes critical thinking as “the analysis of facts to form a judgment,” involving “rational, skeptical, unbiased analysis, or evaluation of factual evidence.”

The concept has been around since Ancient Greek times and the teachings of Socrates, but American philosopher John Dewey was a major influence in bringing it into modern education in the early 1900s.

What critical thinking is

Dewey identified 5 processes involved in critical thinking:

• identifying possibilities
• intellectualizing the issue into a problem to solve
• selecting a hypothesis to guide the collection of information
• applying reasoning
• testing the hypothesis

It’s kind of like applying the scientific method on a personal level to dealing with problems, in the sense that it involves questioning and testing things out before making an evaluation.

Critical thinking isn’t a single thought process. It involves a number of specific mental acts, including:

• observation
• drawing on stored knowledge
• experimenting

Thinking critically comes from a mix of natural predisposition and skills developed over time. Attitudes that can help include self-confidence, open-mindedness, attentiveness, and truth-seeking. Helpful skills include problem-solving, decision-making, rationality, and metacognition (being aware of one’s own thinking processes).

Skepticism is conducive to critical thinking, but that’s not the same as being unwilling to believe. Someone we might think of as a vaccine skeptic probably wouldn’t be willing to entertain information that’s inconsistent with their beliefs, but someone taking a critical thinking approach would explore and evaluate the individual merits and weaknesses of different pieces of information and their sources.

Similarly, someone with paranoia (in a non-delusional sense) might only be willing to believe information unless from specific sources that are trusted based on personal beliefs, while a critical thinker would evaluate the reliability of sources based on an evaluation of merits and weaknesses.

Applying critical thinking

Critical thinking is an important part of media literacy. We’re bombarded with all kinds of messaging, and the explosion of available information online isn’t that helpful without an effective way to separate the useful from the crap. For all that critical thinking is supposed to be taught in schools, it doesn’t seem like that’s translating into practical world application.

A 2018 article by the Provost at the University of Washington said that “Democracies live and die by the ability of their people to access information and engage in robust discussions based upon facts.” He argued that teaching critical thinking, including skills in accessing and questioning data, is essential for the future of democracy. Granted, that’s coming through his filter as an educator, but the point’s still valid.

Speaking of filters, everything that we’re presented with comes through some sort of filter, whether that’s bias stemming from the source or from the medium. Bias isn’t necessarily a bad thing, but failure to recognize it can be a problem. For example, it’s one thing to choose to watch Fox News and recognize that it’s coming through a filter with a certain bias, and it’s a whole other can of tuna to assume that messaging is unbiased. I watch a couple of late-night comedy shows that I’m well aware are biased to the left, and acknowledging that bias is helpful in contextualizing the information they present in terms of the bigger picture.

Are you a critical thinker?

I’m logically minded to begin with, and the schooling I’ve done has had a huge impact on how I evaluate new information. I’ve certainly got my own biased filter, but I have confidence in my ability to look things up, plus I trust my BS detector.

Monash University has a 3-question quiz to tell you if you’re a critical thinker or not. It’s not enough to tell you much of anything about anything, but it calls me a “critical maestro.”

Do you think our society could use more critical thought? If so, how might we be able to foster that?

Useful resources

• CRAAP test : how to evaluate relevance based on currency, relevance, authority, accuracy, and purpose
• Develop Your Critical Thinking course from OpenClassrooms
• Logical and Critical Thinking course from The University of Auckland on FutureLearn
• MediaSmarts : Canada’s Centre for Digital and Media Literacy
• Medical Library Association : tips on finding good health information
• NAMLE : National Association for Media Literacy Education
• Office for Science and Society : this McGill University group’s aim is “separating sense from nonsense”
• Pew Research Fact Tank : nonpartisan public opinion research and analysis
• Quackwatch.org : maintained by Stephen Barrett MD, with an extensive range of articles on quacky practices
• Verification Handbook : this free book designed for journalists is a guide to detecting inauthentic and manipulated content online
• Baldasty, J. (2018). Fake news and misinformation : Why teaching critical thinking is crucial for democracy . University of Washington Office of the Provost.
• Hitchcock, D. (2018). Critical thinking . Stanford Encyclopedia of Philosophy.
• MediaSmarts: Media literacy fundamentals
• Monash University Learn HQ: Critical thinking

The Psychology Corner has an overview of terms covered in the What Is… series, along with a collection of scientifically validated psychological tests.

Ashley L. Peterson

BScPharm BSN MPN

Ashley is a former mental health nurse and pharmacist and the author of four books.

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40 thoughts on “what is… critical thinking”.

Like most other commenters Ashley, I think it ought to be taught in schools from a young age, as some of their parent don’t have the knowledge of inclination to learn more about what’s happening in our world today.

Yes, it seems pretty clear that parents can’t be relied upon.

Sadly, yes.

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A Crash Course in Critical Thinking

What you need to know—and read—about one of the essential skills needed today..

Posted April 8, 2024 | Reviewed by Michelle Quirk

• In research for "A More Beautiful Question," I did a deep dive into the current crisis in critical thinking.
• Many people may think of themselves as critical thinkers, but they actually are not.
• Here is a series of questions you can ask yourself to try to ensure that you are thinking critically.

Conspiracy theories. Inability to distinguish facts from falsehoods. Widespread confusion about who and what to believe.

These are some of the hallmarks of the current crisis in critical thinking—which just might be the issue of our times. Because if people aren’t willing or able to think critically as they choose potential leaders, they’re apt to choose bad ones. And if they can’t judge whether the information they’re receiving is sound, they may follow faulty advice while ignoring recommendations that are science-based and solid (and perhaps life-saving).

Moreover, as a society, if we can’t think critically about the many serious challenges we face, it becomes more difficult to agree on what those challenges are—much less solve them.

On a personal level, critical thinking can enable you to make better everyday decisions. It can help you make sense of an increasingly complex and confusing world.

In the new expanded edition of my book A More Beautiful Question ( AMBQ ), I took a deep dive into critical thinking. Here are a few key things I learned.

First off, before you can get better at critical thinking, you should understand what it is. It’s not just about being a skeptic. When thinking critically, we are thoughtfully reasoning, evaluating, and making decisions based on evidence and logic. And—perhaps most important—while doing this, a critical thinker always strives to be open-minded and fair-minded . That’s not easy: It demands that you constantly question your assumptions and biases and that you always remain open to considering opposing views.

In today’s polarized environment, many people think of themselves as critical thinkers simply because they ask skeptical questions—often directed at, say, certain government policies or ideas espoused by those on the “other side” of the political divide. The problem is, they may not be asking these questions with an open mind or a willingness to fairly consider opposing views.

When people do this, they’re engaging in “weak-sense critical thinking”—a term popularized by the late Richard Paul, a co-founder of The Foundation for Critical Thinking . “Weak-sense critical thinking” means applying the tools and practices of critical thinking—questioning, investigating, evaluating—but with the sole purpose of confirming one’s own bias or serving an agenda.

In AMBQ , I lay out a series of questions you can ask yourself to try to ensure that you’re thinking critically. Here are some of the questions to consider:

• Why do I believe what I believe?
• Are my views based on evidence?
• Have I fairly and thoughtfully considered differing viewpoints?
• Am I truly open to changing my mind?

Of course, becoming a better critical thinker is not as simple as just asking yourself a few questions. Critical thinking is a habit of mind that must be developed and strengthened over time. In effect, you must train yourself to think in a manner that is more effortful, aware, grounded, and balanced.

For those interested in giving themselves a crash course in critical thinking—something I did myself, as I was working on my book—I thought it might be helpful to share a list of some of the books that have shaped my own thinking on this subject. As a self-interested author, I naturally would suggest that you start with the new 10th-anniversary edition of A More Beautiful Question , but beyond that, here are the top eight critical-thinking books I’d recommend.

The Demon-Haunted World: Science as a Candle in the Dark , by Carl Sagan

This book simply must top the list, because the late scientist and author Carl Sagan continues to be such a bright shining light in the critical thinking universe. Chapter 12 includes the details on Sagan’s famous “baloney detection kit,” a collection of lessons and tips on how to deal with bogus arguments and logical fallacies.

Clear Thinking: Turning Ordinary Moments Into Extraordinary Results , by Shane Parrish

The creator of the Farnham Street website and host of the “Knowledge Project” podcast explains how to contend with biases and unconscious reactions so you can make better everyday decisions. It contains insights from many of the brilliant thinkers Shane has studied.

Good Thinking: Why Flawed Logic Puts Us All at Risk and How Critical Thinking Can Save the World , by David Robert Grimes

A brilliant, comprehensive 2021 book on critical thinking that, to my mind, hasn’t received nearly enough attention . The scientist Grimes dissects bad thinking, shows why it persists, and offers the tools to defeat it.

Think Again: The Power of Knowing What You Don't Know , by Adam Grant

Intellectual humility—being willing to admit that you might be wrong—is what this book is primarily about. But Adam, the renowned Wharton psychology professor and bestselling author, takes the reader on a mind-opening journey with colorful stories and characters.

Think Like a Detective: A Kid's Guide to Critical Thinking , by David Pakman

The popular YouTuber and podcast host Pakman—normally known for talking politics —has written a terrific primer on critical thinking for children. The illustrated book presents critical thinking as a “superpower” that enables kids to unlock mysteries and dig for truth. (I also recommend Pakman’s second kids’ book called Think Like a Scientist .)

Rationality: What It Is, Why It Seems Scarce, Why It Matters , by Steven Pinker

The Harvard psychology professor Pinker tackles conspiracy theories head-on but also explores concepts involving risk/reward, probability and randomness, and correlation/causation. And if that strikes you as daunting, be assured that Pinker makes it lively and accessible.

How Minds Change: The Surprising Science of Belief, Opinion and Persuasion , by David McRaney

David is a science writer who hosts the popular podcast “You Are Not So Smart” (and his ideas are featured in A More Beautiful Question ). His well-written book looks at ways you can actually get through to people who see the world very differently than you (hint: bludgeoning them with facts definitely won’t work).

A Healthy Democracy's Best Hope: Building the Critical Thinking Habit , by M Neil Browne and Chelsea Kulhanek

Neil Browne, author of the seminal Asking the Right Questions: A Guide to Critical Thinking, has been a pioneer in presenting critical thinking as a question-based approach to making sense of the world around us. His newest book, co-authored with Chelsea Kulhanek, breaks down critical thinking into “11 explosive questions”—including the “priors question” (which challenges us to question assumptions), the “evidence question” (focusing on how to evaluate and weigh evidence), and the “humility question” (which reminds us that a critical thinker must be humble enough to consider the possibility of being wrong).

Warren Berger is a longtime journalist and author of A More Beautiful Question .

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41+ Critical Thinking Examples (Definition + Practices)

Critical thinking is an essential skill in our information-overloaded world, where figuring out what is fact and fiction has become increasingly challenging.

But why is critical thinking essential? Put, critical thinking empowers us to make better decisions, challenge and validate our beliefs and assumptions, and understand and interact with the world more effectively and meaningfully.

Critical thinking is like using your brain's "superpowers" to make smart choices. Whether it's picking the right insurance, deciding what to do in a job, or discussing topics in school, thinking deeply helps a lot. In the next parts, we'll share real-life examples of when this superpower comes in handy and give you some fun exercises to practice it.

Critical Thinking Process Outline

Critical thinking means thinking clearly and fairly without letting personal feelings get in the way. It's like being a detective, trying to solve a mystery by using clues and thinking hard about them.

It isn't always easy to think critically, as it can take a pretty smart person to see some of the questions that aren't being answered in a certain situation. But, we can train our brains to think more like puzzle solvers, which can help develop our critical thinking skills.

Here's what it looks like step by step:

Spotting the Problem: It's like discovering a puzzle to solve. You see that there's something you need to figure out or decide.

Collecting Clues: Now, you need to gather information. Maybe you read about it, watch a video, talk to people, or do some research. It's like getting all the pieces to solve your puzzle.

Breaking It Down: This is where you look at all your clues and try to see how they fit together. You're asking questions like: Why did this happen? What could happen next?

Checking Your Clues: You want to make sure your information is good. This means seeing if what you found out is true and if you can trust where it came from.

Making a Guess: After looking at all your clues, you think about what they mean and come up with an answer. This answer is like your best guess based on what you know.

Explaining Your Thoughts: Now, you tell others how you solved the puzzle. You explain how you thought about it and how you answered. 

Checking Your Work: This is like looking back and seeing if you missed anything. Did you make any mistakes? Did you let any personal feelings get in the way? This step helps make sure your thinking is clear and fair.

And remember, you might sometimes need to go back and redo some steps if you discover something new. If you realize you missed an important clue, you might have to go back and collect more information.

Critical Thinking Methods

Just like doing push-ups or running helps our bodies get stronger, there are special exercises that help our brains think better. These brain workouts push us to think harder, look at things closely, and ask many questions.

It's not always about finding the "right" answer. Instead, it's about the journey of thinking and asking "why" or "how." Doing these exercises often helps us become better thinkers and makes us curious to know more about the world.

Now, let's look at some brain workouts to help us think better:

1. "What If" Scenarios

Imagine crazy things happening, like, "What if there was no internet for a month? What would we do?" These games help us think of new and different ideas.

Pick a hot topic. Argue one side of it and then try arguing the opposite. This makes us see different viewpoints and think deeply about a topic.

3. Analyze Visual Data

Check out charts or pictures with lots of numbers and info but no explanations. What story are they telling? This helps us get better at understanding information just by looking at it.

4. Mind Mapping

Write an idea in the center and then draw lines to related ideas. It's like making a map of your thoughts. This helps us see how everything is connected.

There's lots of mind-mapping software , but it's also nice to do this by hand.

5. Weekly Diary

Every week, write about what happened, the choices you made, and what you learned. Writing helps us think about our actions and how we can do better.

6. Evaluating Information Sources

Collect stories or articles about one topic from newspapers or blogs. Which ones are trustworthy? Which ones might be a little biased? This teaches us to be smart about where we get our info.

There are many resources to help you determine if information sources are factual or not.

7. Socratic Questioning

This way of thinking is called the Socrates Method, named after an old-time thinker from Greece. It's about asking lots of questions to understand a topic. You can do this by yourself or chat with a friend.

Start with a Big Question:

"What does 'success' mean?"

Dive Deeper with More Questions:

"Why do you think of success that way?" "Do TV shows, friends, or family make you think that?" "Does everyone think about success the same way?"

"Can someone be a winner even if they aren't rich or famous?" "Can someone feel like they didn't succeed, even if everyone else thinks they did?"

Look for Real-life Examples:

"Who is someone you think is successful? Why?" "Was there a time you felt like a winner? What happened?"

Think About Other People's Views:

"How might a person from another country think about success?" "Does the idea of success change as we grow up or as our life changes?"

Think About What It Means:

"How does your idea of success shape what you want in life?" "Are there problems with only wanting to be rich or famous?"

Look Back and Think:

"After talking about this, did your idea of success change? How?" "Did you learn something new about what success means?"

8. Six Thinking Hats 

Edward de Bono came up with a cool way to solve problems by thinking in six different ways, like wearing different colored hats. You can do this independently, but it might be more effective in a group so everyone can have a different hat color. Each color has its way of thinking:

White Hat (Facts): Just the facts! Ask, "What do we know? What do we need to find out?"

Red Hat (Feelings): Talk about feelings. Ask, "How do I feel about this?"

Black Hat (Careful Thinking): Be cautious. Ask, "What could go wrong?"

Yellow Hat (Positive Thinking): Look on the bright side. Ask, "What's good about this?"

Green Hat (Creative Thinking): Think of new ideas. Ask, "What's another way to look at this?"

Blue Hat (Planning): Organize the talk. Ask, "What should we do next?"

When using this method with a group:

• Explain all the hats.
• Decide which hat to wear first.
• Make sure everyone switches hats at the same time.
• Finish with the Blue Hat to plan the next steps.

9. SWOT Analysis

SWOT Analysis is like a game plan for businesses to know where they stand and where they should go. "SWOT" stands for Strengths, Weaknesses, Opportunities, and Threats.

There are a lot of SWOT templates out there for how to do this visually, but you can also think it through. It doesn't just apply to businesses but can be a good way to decide if a project you're working on is working.

Strengths: What's working well? Ask, "What are we good at?"

Weaknesses: Where can we do better? Ask, "Where can we improve?"

Opportunities: What good things might come our way? Ask, "What chances can we grab?"

Threats: What challenges might we face? Ask, "What might make things tough for us?"

Steps to do a SWOT Analysis:

• Goal: Decide what you want to find out.
• Research: Learn about your business and the world around it.
• Brainstorm: Get a group and think together. Talk about strengths, weaknesses, opportunities, and threats.
• Pick the Most Important Points: Some things might be more urgent or important than others.
• Make a Plan: Decide what to do based on your SWOT list.
• Check Again Later: Things change, so look at your SWOT again after a while to update it.

Now that you have a few tools for thinking critically, let’s get into some specific examples.

Everyday Examples

Life is a series of decisions. From the moment we wake up, we're faced with choices – some trivial, like choosing a breakfast cereal, and some more significant, like buying a home or confronting an ethical dilemma at work. While it might seem that these decisions are disparate, they all benefit from the application of critical thinking.

10. Deciding to buy something

Imagine you want a new phone. Don't just buy it because the ad looks cool. Think about what you need in a phone. Look up different phones and see what people say about them. Choose the one that's the best deal for what you want.

11. Deciding what is true

There's a lot of news everywhere. Don't believe everything right away. Think about why someone might be telling you this. Check if what you're reading or watching is true. Make up your mind after you've looked into it.

12. Deciding when you’re wrong

Sometimes, friends can have disagreements. Don't just get mad right away. Try to see where they're coming from. Talk about what's going on. Find a way to fix the problem that's fair for everyone.

13. Deciding what to eat

There's always a new diet or exercise that's popular. Don't just follow it because it's trendy. Find out if it's good for you. Ask someone who knows, like a doctor. Make choices that make you feel good and stay healthy.

14. Deciding what to do today

Everyone is busy with school, chores, and hobbies. Make a list of things you need to do. Decide which ones are most important. Plan your day so you can get things done and still have fun.

15. Making Tough Choices

Sometimes, it's hard to know what's right. Think about how each choice will affect you and others. Talk to people you trust about it. Choose what feels right in your heart and is fair to others.

16. Planning for the Future

Big decisions, like where to go to school, can be tricky. Think about what you want in the future. Look at the good and bad of each choice. Talk to people who know about it. Pick what feels best for your dreams and goals.

Job Examples

17. solving problems.

Workers brainstorm ways to fix a machine quickly without making things worse when a machine breaks at a factory.

18. Decision Making

A store manager decides which products to order more of based on what's selling best.

19. Setting Goals

A team leader helps their team decide what tasks are most important to finish this month and which can wait.

20. Evaluating Ideas

At a team meeting, everyone shares ideas for a new project. The group discusses each idea's pros and cons before picking one.

21. Handling Conflict

Two workers disagree on how to do a job. Instead of arguing, they talk calmly, listen to each other, and find a solution they both like.

22. Improving Processes

A cashier thinks of a faster way to ring up items so customers don't have to wait as long.

23. Asking Questions

Before starting a big task, an employee asks for clear instructions and checks if they have the necessary tools.

24. Checking Facts

Before presenting a report, someone double-checks all their information to make sure there are no mistakes.

25. Planning for the Future

A business owner thinks about what might happen in the next few years, like new competitors or changes in what customers want, and makes plans based on those thoughts.

26. Understanding Perspectives

A team is designing a new toy. They think about what kids and parents would both like instead of just what they think is fun.

School Examples

27. researching a topic.

For a history project, a student looks up different sources to understand an event from multiple viewpoints.

28. Debating an Issue

In a class discussion, students pick sides on a topic, like school uniforms, and share reasons to support their views.

29. Evaluating Sources

While writing an essay, a student checks if the information from a website is trustworthy or might be biased.

30. Problem Solving in Math

When stuck on a tricky math problem, a student tries different methods to find the answer instead of giving up.

31. Analyzing Literature

In English class, students discuss why a character in a book made certain choices and what those decisions reveal about them.

32. Testing a Hypothesis

For a science experiment, students guess what will happen and then conduct tests to see if they're right or wrong.

33. Giving Peer Feedback

After reading a classmate's essay, a student offers suggestions for improving it.

34. Questioning Assumptions

In a geography lesson, students consider why certain countries are called "developed" and what that label means.

35. Designing a Study

For a psychology project, students plan an experiment to understand how people's memories work and think of ways to ensure accurate results.

36. Interpreting Data

In a science class, students look at charts and graphs from a study, then discuss what the information tells them and if there are any patterns.

Critical Thinking Puzzles

Not all scenarios will have a single correct answer that can be figured out by thinking critically. Sometimes we have to think critically about ethical choices or moral behaviors. 

Here are some mind games and scenarios you can solve using critical thinking. You can see the solution(s) at the end of the post.

37. The Farmer, Fox, Chicken, and Grain Problem

A farmer is at a riverbank with a fox, a chicken, and a grain bag. He needs to get all three items across the river. However, his boat can only carry himself and one of the three items at a time. 

Here's the challenge:

• If the fox is left alone with the chicken, the fox will eat the chicken.
• If the chicken is left alone with the grain, the chicken will eat the grain.

How can the farmer get all three items across the river without any item being eaten? 

38. The Rope, Jar, and Pebbles Problem

You are in a room with two long ropes hanging from the ceiling. Each rope is just out of arm's reach from the other, so you can't hold onto one rope and reach the other simultaneously. 

Your task is to tie the two rope ends together, but you can't move the position where they hang from the ceiling.

You are given a jar full of pebbles. How do you complete the task?

39. The Two Guards Problem

Imagine there are two doors. One door leads to certain doom, and the other leads to freedom. You don't know which is which.

In front of each door stands a guard. One guard always tells the truth. The other guard always lies. You don't know which guard is which.

You can ask only one question to one of the guards. What question should you ask to find the door that leads to freedom?

40. The Hourglass Problem

You have two hourglasses. One measures 7 minutes when turned over, and the other measures 4 minutes. Using just these hourglasses, how can you time exactly 9 minutes?

41. The Lifeboat Dilemma

Imagine you're on a ship that's sinking. You get on a lifeboat, but it's already too full and might flip over. 

Nearby in the water, five people are struggling: a scientist close to finding a cure for a sickness, an old couple who've been together for a long time, a mom with three kids waiting at home, and a tired teenager who helped save others but is now in danger. 

You can only save one person without making the boat flip. Who would you choose?

42. The Tech Dilemma

You work at a tech company and help make a computer program to help small businesses. You're almost ready to share it with everyone, but you find out there might be a small chance it has a problem that could show users' private info. 

If you decide to fix it, you must wait two more months before sharing it. But your bosses want you to share it now. What would you do?

43. The History Mystery

Dr. Amelia is a history expert. She's studying where a group of people traveled long ago. She reads old letters and documents to learn about it. But she finds some letters that tell a different story than what most people believe. 

If she says this new story is true, it could change what people learn in school and what they think about history. What should she do?

The Role of Bias in Critical Thinking

Have you ever decided you don’t like someone before you even know them? Or maybe someone shared an idea with you that you immediately loved without even knowing all the details. 

This experience is called bias, which occurs when you like or dislike something or someone without a good reason or knowing why. It can also take shape in certain reactions to situations, like a habit or instinct. 

Bias comes from our own experiences, what friends or family tell us, or even things we are born believing. Sometimes, bias can help us stay safe, but other times it stops us from seeing the truth.

Not all bias is bad. Bias can be a mechanism for assessing our potential safety in a new situation. If we are biased to think that anything long, thin, and curled up is a snake, we might assume the rope is something to be afraid of before we know it is just a rope.

While bias might serve us in some situations (like jumping out of the way of an actual snake before we have time to process that we need to be jumping out of the way), it often harms our ability to think critically.

How Bias Gets in the Way of Good Thinking

Selective Perception: We only notice things that match our ideas and ignore the rest. 

It's like only picking red candies from a mixed bowl because you think they taste the best, but they taste the same as every other candy in the bowl. It could also be when we see all the signs that our partner is cheating on us but choose to ignore them because we are happy the way we are (or at least, we think we are).

Agreeing with Yourself: This is called “ confirmation bias ” when we only listen to ideas that match our own and seek, interpret, and remember information in a way that confirms what we already think we know or believe. 

An example is when someone wants to know if it is safe to vaccinate their children but already believes that vaccines are not safe, so they only look for information supporting the idea that vaccines are bad.

Thinking We Know It All: Similar to confirmation bias, this is called “overconfidence bias.” Sometimes we think our ideas are the best and don't listen to others. This can stop us from learning.

Have you ever met someone who you consider a “know it”? Probably, they have a lot of overconfidence bias because while they may know many things accurately, they can’t know everything. Still, if they act like they do, they show overconfidence bias.

There's a weird kind of bias similar to this called the Dunning Kruger Effect, and that is when someone is bad at what they do, but they believe and act like they are the best .

Following the Crowd: This is formally called “groupthink”. It's hard to speak up with a different idea if everyone agrees. But this can lead to mistakes.

An example of this we’ve all likely seen is the cool clique in primary school. There is usually one person that is the head of the group, the “coolest kid in school”, and everyone listens to them and does what they want, even if they don’t think it’s a good idea.

How to Overcome Biases

Here are a few ways to learn to think better, free from our biases (or at least aware of them!).

Know Your Biases: Realize that everyone has biases. If we know about them, we can think better.

Listen to Different People: Talking to different kinds of people can give us new ideas.

Ask Why: Always ask yourself why you believe something. Is it true, or is it just a bias?

Understand Others: Try to think about how others feel. It helps you see things in new ways.

Keep Learning: Always be curious and open to new information.

In today's world, everything changes fast, and there's so much information everywhere. This makes critical thinking super important. It helps us distinguish between what's real and what's made up. It also helps us make good choices. But thinking this way can be tough sometimes because of biases. These are like sneaky thoughts that can trick us. The good news is we can learn to see them and think better.

There are cool tools and ways we've talked about, like the "Socratic Questioning" method and the "Six Thinking Hats." These tools help us get better at thinking. These thinking skills can also help us in school, work, and everyday life.

We’ve also looked at specific scenarios where critical thinking would be helpful, such as deciding what diet to follow and checking facts.

Thinking isn't just a skill—it's a special talent we improve over time. Working on it lets us see things more clearly and understand the world better. So, keep practicing and asking questions! It'll make you a smarter thinker and help you see the world differently.

Critical Thinking Puzzles (Solutions)

The farmer, fox, chicken, and grain problem.

• The farmer first takes the chicken across the river and leaves it on the other side.
• He returns to the original side and takes the fox across the river.
• After leaving the fox on the other side, he returns the chicken to the starting side.
• He leaves the chicken on the starting side and takes the grain bag across the river.
• He leaves the grain with the fox on the other side and returns to get the chicken.
• The farmer takes the chicken across, and now all three items -- the fox, the chicken, and the grain -- are safely on the other side of the river.

The Rope, Jar, and Pebbles Problem

• Take one rope and tie the jar of pebbles to its end.
• Swing the rope with the jar in a pendulum motion.
• While the rope is swinging, grab the other rope and wait.
• As the swinging rope comes back within reach due to its pendulum motion, grab it.
• With both ropes within reach, untie the jar and tie the rope ends together.

The Two Guards Problem

The question is, "What would the other guard say is the door to doom?" Then choose the opposite door.

The Hourglass Problem

• Start both hourglasses. 
• When the 4-minute hourglass runs out, turn it over.
• When the 7-minute hourglass runs out, the 4-minute hourglass will have been running for 3 minutes. Turn the 7-minute hourglass over. 
• When the 4-minute hourglass runs out for the second time (a total of 8 minutes have passed), the 7-minute hourglass will run for 1 minute. Turn the 7-minute hourglass again for 1 minute to empty the hourglass (a total of 9 minutes passed).

The Boat and Weights Problem

Take the cat over first and leave it on the other side. Then, return and take the fish across next. When you get there, take the cat back with you. Leave the cat on the starting side and take the cat food across. Lastly, return to get the cat and bring it to the other side.

The Lifeboat Dilemma

There isn’t one correct answer to this problem. Here are some elements to consider:

• Moral Principles: What values guide your decision? Is it the potential greater good for humanity (the scientist)? What is the value of long-standing love and commitment (the elderly couple)? What is the future of young children who depend on their mothers? Or the selfless bravery of the teenager?
• Future Implications: Consider the future consequences of each choice. Saving the scientist might benefit millions in the future, but what moral message does it send about the value of individual lives?
• Emotional vs. Logical Thinking: While it's essential to engage empathy, it's also crucial not to let emotions cloud judgment entirely. For instance, while the teenager's bravery is commendable, does it make him more deserving of a spot on the boat than the others?
• Acknowledging Uncertainty: The scientist claims to be close to a significant breakthrough, but there's no certainty. How does this uncertainty factor into your decision?
• Personal Bias: Recognize and challenge any personal biases, such as biases towards age, profession, or familial status.

The Tech Dilemma

Again, there isn’t one correct answer to this problem. Here are some elements to consider:

• Evaluate the Risk: How severe is the potential vulnerability? Can it be easily exploited, or would it require significant expertise? Even if the circumstances are rare, what would be the consequences if the vulnerability were exploited?
• Stakeholder Considerations: Different stakeholders will have different priorities. Upper management might prioritize financial projections, the marketing team might be concerned about the product's reputation, and customers might prioritize the security of their data. How do you balance these competing interests?
• Short-Term vs. Long-Term Implications: While launching on time could meet immediate financial goals, consider the potential long-term damage to the company's reputation if the vulnerability is exploited. Would the short-term gains be worth the potential long-term costs?
• Ethical Implications : Beyond the financial and reputational aspects, there's an ethical dimension to consider. Is it right to release a product with a known vulnerability, even if the chances of it being exploited are low?
• Seek External Input: Consulting with cybersecurity experts outside your company might be beneficial. They could provide a more objective risk assessment and potential mitigation strategies.
• Communication: How will you communicate the decision, whatever it may be, both internally to your team and upper management and externally to your customers and potential users?

The History Mystery

Dr. Amelia should take the following steps:

• Verify the Letters: Before making any claims, she should check if the letters are actual and not fake. She can do this by seeing when and where they were written and if they match with other things from that time.
• Get a Second Opinion: It's always good to have someone else look at what you've found. Dr. Amelia could show the letters to other history experts and see their thoughts.
• Research More: Maybe there are more documents or letters out there that support this new story. Dr. Amelia should keep looking to see if she can find more evidence.
• Share the Findings: If Dr. Amelia believes the letters are true after all her checks, she should tell others. This can be through books, talks, or articles.
• Stay Open to Feedback: Some people might agree with Dr. Amelia, and others might not. She should listen to everyone and be ready to learn more or change her mind if new information arises.

Ultimately, Dr. Amelia's job is to find out the truth about history and share it. It's okay if this new truth differs from what people used to believe. History is about learning from the past, no matter the story.

Related posts:

• Experimenter Bias (Definition + Examples)
• Hasty Generalization Fallacy (31 Examples + Similar Names)
• Ad Hoc Fallacy (29 Examples + Other Names)
• Confirmation Bias (Examples + Definition)
• Equivocation Fallacy (26 Examples + Description)

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BRIEF RESEARCH REPORT article

How do critical thinking ability and critical thinking disposition relate to the mental health of university students.

• School of Education, Huazhong University of Science and Technology, Wuhan, China

Theories of psychotherapy suggest that human mental problems associate with deficiencies in critical thinking. However, it currently remains unclear whether both critical thinking skill and critical thinking disposition relate to individual differences in mental health. This study explored whether and how the critical thinking ability and critical thinking disposition of university students associate with individual differences in mental health in considering impulsivity that has been revealed to be closely related to both critical thinking and mental health. Regression and structural equation modeling analyses based on a Chinese university student sample ( N = 314, 198 females, M age = 18.65) revealed that critical thinking skill and disposition explained a unique variance of mental health after controlling for impulsivity. Furthermore, the relationship between critical thinking and mental health was mediated by motor impulsivity (acting on the spur of the moment) and non-planning impulsivity (making decisions without careful forethought). These findings provide a preliminary account of how human critical thinking associate with mental health. Practically, developing mental health promotion programs for university students is suggested to pay special attention to cultivating their critical thinking dispositions and enhancing their control over impulsive behavior.

Introduction

Although there is no consistent definition of critical thinking (CT), it is usually described as “purposeful, self-regulatory judgment that results in interpretation, analysis, evaluation, and inference, as well as explanations of the evidential, conceptual, methodological, criteriological, or contextual considerations that judgment is based upon” ( Facione, 1990 , p. 2). This suggests that CT is a combination of skills and dispositions. The skill aspect mainly refers to higher-order cognitive skills such as inference, analysis, and evaluation, while the disposition aspect represents one's consistent motivation and willingness to use CT skills ( Dwyer, 2017 ). An increasing number of studies have indicated that CT plays crucial roles in the activities of university students such as their academic performance (e.g., Ghanizadeh, 2017 ; Ren et al., 2020 ), professional work (e.g., Barry et al., 2020 ), and even the ability to cope with life events (e.g., Butler et al., 2017 ). An area that has received less attention is how critical thinking relates to impulsivity and mental health. This study aimed to clarify the relationship between CT (which included both CT skill and CT disposition), impulsivity, and mental health among university students.

Relationship Between Critical Thinking and Mental Health

Associating critical thinking with mental health is not without reason, since theories of psychotherapy have long stressed a linkage between mental problems and dysfunctional thinking ( Gilbert, 2003 ; Gambrill, 2005 ; Cuijpers, 2019 ). Proponents of cognitive behavioral therapy suggest that the interpretation by people of a situation affects their emotional, behavioral, and physiological reactions. Those with mental problems are inclined to bias or heuristic thinking and are more likely to misinterpret neutral or even positive situations ( Hollon and Beck, 2013 ). Therefore, a main goal of cognitive behavioral therapy is to overcome biased thinking and change maladaptive beliefs via cognitive modification skills such as objective understanding of one's cognitive distortions, analyzing evidence for and against one's automatic thinking, or testing the effect of an alternative way of thinking. Achieving these therapeutic goals requires the involvement of critical thinking, such as the willingness and ability to critically analyze one's thoughts and evaluate evidence and arguments independently of one's prior beliefs. In addition to theoretical underpinnings, characteristics of university students also suggest a relationship between CT and mental health. University students are a risky population in terms of mental health. They face many normative transitions (e.g., social and romantic relationships, important exams, financial pressures), which are stressful ( Duffy et al., 2019 ). In particular, the risk increases when students experience academic failure ( Lee et al., 2008 ; Mamun et al., 2021 ). Hong et al. (2010) found that the stress in Chinese college students was primarily related to academic, personal, and negative life events. However, university students are also a population with many resources to work on. Critical thinking can be considered one of the important resources that students are able to use ( Stupple et al., 2017 ). Both CT skills and CT disposition are valuable qualities for college students to possess ( Facione, 1990 ). There is evidence showing that students with a higher level of CT are more successful in terms of academic performance ( Ghanizadeh, 2017 ; Ren et al., 2020 ), and that they are better at coping with stressful events ( Butler et al., 2017 ). This suggests that that students with higher CT are less likely to suffer from mental problems.

Empirical research has reported an association between CT and mental health among college students ( Suliman and Halabi, 2007 ; Kargar et al., 2013 ; Yoshinori and Marcus, 2013 ; Chen and Hwang, 2020 ; Ugwuozor et al., 2021 ). Most of these studies focused on the relationship between CT disposition and mental health. For example, Suliman and Halabi (2007) reported that the CT disposition of nursing students was positively correlated with their self-esteem, but was negatively correlated with their state anxiety. There is also a research study demonstrating that CT disposition influenced the intensity of worry in college students either by increasing their responsibility to continue thinking or by enhancing the detached awareness of negative thoughts ( Yoshinori and Marcus, 2013 ). Regarding the relationship between CT ability and mental health, although there has been no direct evidence, there were educational programs examining the effect of teaching CT skills on the mental health of adolescents ( Kargar et al., 2013 ). The results showed that teaching CT skills decreased somatic symptoms, anxiety, depression, and insomnia in adolescents. Another recent CT skill intervention also found a significant reduction in mental stress among university students, suggesting an association between CT skills and mental health ( Ugwuozor et al., 2021 ).

The above research provides preliminary evidence in favor of the relationship between CT and mental health, in line with theories of CT and psychotherapy. However, previous studies have focused solely on the disposition aspect of CT, and its link with mental health. The ability aspect of CT has been largely overlooked in examining its relationship with mental health. Moreover, although the link between CT and mental health has been reported, it remains unknown how CT (including skill and disposition) is associated with mental health.

Impulsivity as a Potential Mediator Between Critical Thinking and Mental Health

One important factor suggested by previous research in accounting for the relationship between CT and mental health is impulsivity. Impulsivity is recognized as a pattern of action without regard to consequences. Patton et al. (1995) proposed that impulsivity is a multi-faceted construct that consists of three behavioral factors, namely, non-planning impulsiveness, referring to making a decision without careful forethought; motor impulsiveness, referring to acting on the spur of the moment; and attentional impulsiveness, referring to one's inability to focus on the task at hand. Impulsivity is prominent in clinical problems associated with psychiatric disorders ( Fortgang et al., 2016 ). A number of mental problems are associated with increased impulsivity that is likely to aggravate clinical illnesses ( Leclair et al., 2020 ). Moreover, a lack of CT is correlated with poor impulse control ( Franco et al., 2017 ). Applications of CT may reduce impulsive behaviors caused by heuristic and biased thinking when one makes a decision ( West et al., 2008 ). For example, Gregory (1991) suggested that CT skills enhance the ability of children to anticipate the health or safety consequences of a decision. Given this, those with high levels of CT are expected to take a rigorous attitude about the consequences of actions and are less likely to engage in impulsive behaviors, which may place them at a low risk of suffering mental problems. To the knowledge of the authors, no study has empirically tested whether impulsivity accounts for the relationship between CT and mental health.

This study examined whether CT skill and disposition are related to the mental health of university students; and if yes, how the relationship works. First, we examined the simultaneous effects of CT ability and CT disposition on mental health. Second, we further tested whether impulsivity mediated the effects of CT on mental health. To achieve the goals, we collected data on CT ability, CT disposition, mental health, and impulsivity from a sample of university students. The results are expected to shed light on the mechanism of the association between CT and mental health.

Participants and Procedure

A total of 314 university students (116 men) with an average age of 18.65 years ( SD = 0.67) participated in this study. They were recruited by advertisements from a local university in central China and majoring in statistics and mathematical finance. The study protocol was approved by the Human Subjects Review Committee of the Huazhong University of Science and Technology. Each participant signed a written informed consent describing the study purpose, procedure, and right of free. All the measures were administered in a computer room. The participants were tested in groups of 20–30 by two research assistants. The researchers and research assistants had no formal connections with the participants. The testing included two sections with an interval of 10 min, so that the participants had an opportunity to take a break. In the first section, the participants completed the syllogistic reasoning problems with belief bias (SRPBB), the Chinese version of the California Critical Thinking Skills Test (CCSTS-CV), and the Chinese Critical Thinking Disposition Inventory (CCTDI), respectively. In the second session, they completed the Barrett Impulsivity Scale (BIS-11), Depression Anxiety Stress Scale-21 (DASS-21), and University Personality Inventory (UPI) in the given order.

Measures of Critical Thinking Ability

The Chinese version of the California Critical Thinking Skills Test was employed to measure CT skills ( Lin, 2018 ). The CCTST is currently the most cited tool for measuring CT skills and includes analysis, assessment, deduction, inductive reasoning, and inference reasoning. The Chinese version included 34 multiple choice items. The dependent variable was the number of correctly answered items. The internal consistency (Cronbach's α) of the CCTST is 0.56 ( Jacobs, 1995 ). The test–retest reliability of CCTST-CV is 0.63 ( p < 0.01) ( Luo and Yang, 2002 ), and correlations between scores of the subscales and the total score are larger than 0.5 ( Lin, 2018 ), supporting the construct validity of the scale. In this study among the university students, the internal consistency (Cronbach's α) of the CCTST-CV was 0.5.

The second critical thinking test employed in this study was adapted from the belief bias paradigm ( Li et al., 2021 ). This task paradigm measures the ability to evaluate evidence and arguments independently of one's prior beliefs ( West et al., 2008 ), which is a strongly emphasized skill in CT literature. The current test included 20 syllogistic reasoning problems in which the logical conclusion was inconsistent with one's prior knowledge (e.g., “Premise 1: All fruits are sweet. Premise 2: Bananas are not sweet. Conclusion: Bananas are not fruits.” valid conclusion). In addition, four non-conflict items were included as the neutral condition in order to avoid a habitual response from the participants. They were instructed to suppose that all the premises are true and to decide whether the conclusion logically follows from the given premises. The measure showed good internal consistency (Cronbach's α = 0.83) in a Chinese sample ( Li et al., 2021 ). In this study, the internal consistency (Cronbach's α) of the SRPBB was 0.94.

Measures of Critical Thinking Disposition

The Chinese Critical Thinking Disposition Inventory was employed to measure CT disposition ( Peng et al., 2004 ). This scale has been developed in line with the conceptual framework of the California critical thinking disposition inventory. We measured five CT dispositions: truth-seeking (one's objectivity with findings even if this requires changing one's preconceived opinions, e.g., a person inclined toward being truth-seeking might disagree with “I believe what I want to believe.”), inquisitiveness (one's intellectual curiosity. e.g., “No matter what the topic, I am eager to know more about it”), analyticity (the tendency to use reasoning and evidence to solve problems, e.g., “It bothers me when people rely on weak arguments to defend good ideas”), systematically (the disposition of being organized and orderly in inquiry, e.g., “I always focus on the question before I attempt to answer it”), and CT self-confidence (the trust one places in one's own reasoning processes, e.g., “I appreciate my ability to think precisely”). Each disposition aspect contained 10 items, which the participants rated on a 6-point Likert-type scale. This measure has shown high internal consistency (overall Cronbach's α = 0.9) ( Peng et al., 2004 ). In this study, the CCTDI scale was assessed at Cronbach's α = 0.89, indicating good reliability.

Measure of Impulsivity

The well-known Barrett Impulsivity Scale ( Patton et al., 1995 ) was employed to assess three facets of impulsivity: non-planning impulsivity (e.g., “I plan tasks carefully”); motor impulsivity (e.g., “I act on the spur of the moment”); attentional impulsivity (e.g., “I concentrate easily”). The scale includes 30 statements, and each statement is rated on a 5-point scale. The subscales of non-planning impulsivity and attentional impulsivity were reversely scored. The BIS-11 has good internal consistency (Cronbach's α = 0.81, Velotti et al., 2016 ). This study showed that the Cronbach's α of the BIS-11 was 0.83.

Measures of Mental Health

The Depression Anxiety Stress Scale-21 was used to assess mental health problems such as depression (e.g., “I feel that life is meaningless”), anxiety (e.g., “I find myself getting agitated”), and stress (e.g., “I find it difficult to relax”). Each dimension included seven items, which the participants were asked to rate on a 4-point scale. The Chinese version of the DASS-21 has displayed a satisfactory factor structure and internal consistency (Cronbach's α = 0.92, Wang et al., 2016 ). In this study, the internal consistency (Cronbach's α) of the DASS-21 was 0.94.

The University Personality Inventory that has been commonly used to screen for mental problems of college students ( Yoshida et al., 1998 ) was also used for measuring mental health. The 56 symptom-items assessed whether an individual has experienced the described symptom during the past year (e.g., “a lack of interest in anything”). The UPI showed good internal consistency (Cronbach's α = 0.92) in a Chinese sample ( Zhang et al., 2015 ). This study showed that the Cronbach's α of the UPI was 0.85.

Statistical Analyses

We first performed analyses to detect outliers. Any observation exceeding three standard deviations from the means was replaced with a value that was three standard deviations. This procedure affected no more than 5‰ of observations. Hierarchical regression analysis was conducted to determine the extent to which facets of critical thinking were related to mental health. In addition, structural equation modeling with Amos 22.0 was performed to assess the latent relationship between CT, impulsivity, and mental health.

Descriptive Statistics and Bivariate Correlations

Table 1 presents descriptive statistics and bivariate correlations of all the variables. CT disposition such as truth-seeking, systematicity, self-confidence, and inquisitiveness was significantly correlated with DASS-21 and UPI, but neither CCTST-CV nor SRPBB was related to DASS-21 and UPI. Subscales of BIS-11 were positively correlated with DASS-21 and UPI, but were negatively associated with CT dispositions.

Table 1 . Descriptive results and correlations between all measured variables ( N = 314).

Regression Analyses

Hierarchical regression analyses were conducted to examine the effects of CT skill and disposition on mental health. Before conducting the analyses, scores in DASS-21 and UPI were reversed so that high scores reflected high levels of mental health. Table 2 presents the results of hierarchical regression. In model 1, the sum of the Z-score of DASS-21 and UPI served as the dependent variable. Scores in the CT ability tests and scores in the five dimensions of CCTDI served as predictors. CT skill and disposition explained 13% of the variance in mental health. CT skills did not significantly predict mental health. Two dimensions of dispositions (truth seeking and systematicity) exerted significantly positive effects on mental health. Model 2 examined whether CT predicted mental health after controlling for impulsivity. The model containing only impulsivity scores (see model-2 step 1 in Table 2 ) explained 15% of the variance in mental health. Non-planning impulsivity and motor impulsivity showed significantly negative effects on mental health. The CT variables on the second step explained a significantly unique variance (6%) of CT (see model-2 step 2). This suggests that CT skill and disposition together explained the unique variance in mental health after controlling for impulsivity. 1

Table 2 . Hierarchical regression models predicting mental health from critical thinking skills, critical thinking dispositions, and impulsivity ( N = 314).

Structural equation modeling was performed to examine whether impulsivity mediated the relationship between CT disposition (CT ability was not included since it did not significantly predict mental health) and mental health. Since the regression results showed that only motor impulsivity and non-planning impulsivity significantly predicted mental health, we examined two mediation models with either motor impulsivity or non-planning impulsivity as the hypothesized mediator. The item scores in the motor impulsivity subscale were randomly divided into two indicators of motor impulsivity, as were the scores in the non-planning subscale. Scores of DASS-21 and UPI served as indicators of mental health and dimensions of CCTDI as indicators of CT disposition. In addition, a bootstrapping procedure with 5,000 resamples was established to test for direct and indirect effects. Amos 22.0 was used for the above analyses.

The mediation model that included motor impulsivity (see Figure 1 ) showed an acceptable fit, χ ( 23 ) 2 = 64.71, RMSEA = 0.076, CFI = 0.96, GFI = 0.96, NNFI = 0.93, SRMR = 0.073. Mediation analyses indicated that the 95% boot confidence intervals of the indirect effect and the direct effect were (0.07, 0.26) and (−0.08, 0.32), respectively. As Hayes (2009) indicates, an effect is significant if zero is not between the lower and upper bounds in the 95% confidence interval. Accordingly, the indirect effect between CT disposition and mental health was significant, while the direct effect was not significant. Thus, motor impulsivity completely mediated the relationship between CT disposition and mental health.

Figure 1 . Illustration of the mediation model: Motor impulsivity as mediator variable between critical thinking dispositions and mental health. CTD-l = Truth seeking; CTD-2 = Analyticity; CTD-3 = Systematically; CTD-4 = Self-confidence; CTD-5 = Inquisitiveness. MI-I and MI-2 were sub-scores of motor impulsivity. Solid line represents significant links and dotted line non-significant links. ** p < 0.01.

The mediation model, which included non-planning impulsivity (see Figure 2 ), also showed an acceptable fit to the data, χ ( 23 ) 2 = 52.75, RMSEA = 0.064, CFI = 0.97, GFI = 0.97, NNFI = 0.95, SRMR = 0.06. The 95% boot confidence intervals of the indirect effect and the direct effect were (0.05, 0.33) and (−0.04, 0.38), respectively, indicating that non-planning impulsivity completely mediated the relationship between CT disposition and mental health.

Figure 2 . Illustration of the mediation model: Non-planning impulsivity asmediator variable between critical thinking dispositions and mental health. CTD-l = Truth seeking; CTD-2 = Analyticity; CTD-3 = Systematically; CTD-4 = Self-confidence; CTD-5 = Inquisitiveness. NI-I and NI-2 were sub-scores of Non-planning impulsivity. Solid line represents significant links and dotted line non-significant links. ** p < 0.01.

This study examined how critical thinking skill and disposition are related to mental health. Theories of psychotherapy suggest that human mental problems are in part due to a lack of CT. However, empirical evidence for the hypothesized relationship between CT and mental health is relatively scarce. This study explored whether and how CT ability and disposition are associated with mental health. The results, based on a university student sample, indicated that CT skill and disposition explained a unique variance in mental health. Furthermore, the effect of CT disposition on mental health was mediated by motor impulsivity and non-planning impulsivity. The finding that CT exerted a significant effect on mental health was in accordance with previous studies reporting negative correlations between CT disposition and mental disorders such as anxiety ( Suliman and Halabi, 2007 ). One reason lies in the assumption that CT disposition is usually referred to as personality traits or habits of mind that are a remarkable predictor of mental health (e.g., Benzi et al., 2019 ). This study further found that of the five CT dispositions, only truth-seeking and systematicity were associated with individual differences in mental health. This was not surprising, since the truth-seeking items mainly assess one's inclination to crave for the best knowledge in a given context and to reflect more about additional facts, reasons, or opinions, even if this requires changing one's mind about certain issues. The systematicity items target one's disposition to approach problems in an orderly and focused way. Individuals with high levels of truth-seeking and systematicity are more likely to adopt a comprehensive, reflective, and controlled way of thinking, which is what cognitive therapy aims to achieve by shifting from an automatic mode of processing to a more reflective and controlled mode.

Another important finding was that motor impulsivity and non-planning impulsivity mediated the effect of CT disposition on mental health. The reason may be that people lacking CT have less willingness to enter into a systematically analyzing process or deliberative decision-making process, resulting in more frequently rash behaviors or unplanned actions without regard for consequences ( Billieux et al., 2010 ; Franco et al., 2017 ). Such responses can potentially have tangible negative consequences (e.g., conflict, aggression, addiction) that may lead to social maladjustment that is regarded as a symptom of mental illness. On the contrary, critical thinkers have a sense of deliberativeness and consider alternate consequences before acting, and this thinking-before-acting mode would logically lead to a decrease in impulsivity, which then decreases the likelihood of problematic behaviors and negative moods.

It should be noted that although the raw correlation between attentional impulsivity and mental health was significant, regression analyses with the three dimensions of impulsivity as predictors showed that attentional impulsivity no longer exerted a significant effect on mental effect after controlling for the other impulsivity dimensions. The insignificance of this effect suggests that the significant raw correlation between attentional impulsivity and mental health was due to the variance it shared with the other impulsivity dimensions (especially with the non-planning dimension, which showed a moderately high correlation with attentional impulsivity, r = 0.67).

Some limitations of this study need to be mentioned. First, the sample involved in this study is considered as a limited sample pool, since all the participants are university students enrolled in statistics and mathematical finance, limiting the generalization of the findings. Future studies are recommended to recruit a more representative sample of university students. A study on generalization to a clinical sample is also recommended. Second, as this study was cross-sectional in nature, caution must be taken in interpreting the findings as causal. Further studies using longitudinal, controlled designs are needed to assess the effectiveness of CT intervention on mental health.

In spite of the limitations mentioned above, the findings of this study have some implications for research and practice intervention. The result that CT contributed to individual differences in mental health provides empirical support for the theory of cognitive behavioral therapy, which focuses on changing irrational thoughts. The mediating role of impulsivity between CT and mental health gives a preliminary account of the mechanism of how CT is associated with mental health. Practically, although there is evidence that CT disposition of students improves because of teaching or training interventions (e.g., Profetto-Mcgrath, 2005 ; Sanja and Krstivoje, 2015 ; Chan, 2019 ), the results showing that two CT disposition dimensions, namely, truth-seeking and systematicity, are related to mental health further suggest that special attention should be paid to cultivating these specific CT dispositions so as to enhance the control of students over impulsive behaviors in their mental health promotions.

Conclusions

This study revealed that two CT dispositions, truth-seeking and systematicity, were associated with individual differences in mental health. Furthermore, the relationship between critical thinking and mental health was mediated by motor impulsivity and non-planning impulsivity. These findings provide a preliminary account of how human critical thinking is associated with mental health. Practically, developing mental health promotion programs for university students is suggested to pay special attention to cultivating their critical thinking dispositions (especially truth-seeking and systematicity) and enhancing the control of individuals over impulsive behaviors.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

The studies involving human participants were reviewed and approved by HUST Critical Thinking Research Center (Grant No. 2018CT012). The patients/participants provided their written informed consent to participate in this study.

Author Contributions

XR designed the study and revised the manuscript. ZL collected data and wrote the manuscript. SL assisted in analyzing the data. SS assisted in re-drafting and editing the manuscript. All the authors contributed to the article and approved the submitted version.

This work was supported by the Social Science Foundation of China (grant number: BBA200034).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

1. ^ We re-analyzed the data by controlling for age and gender of the participants in the regression analyses. The results were virtually the same as those reported in the study.

Barry, A., Parvan, K., Sarbakhsh, P., Safa, B., and Allahbakhshian, A. (2020). Critical thinking in nursing students and its relationship with professional self-concept and relevant factors. Res. Dev. Med. Educ. 9, 7–7. doi: 10.34172/rdme.2020.007

CrossRef Full Text | Google Scholar

Benzi, I. M. A., Emanuele, P., Rossella, D. P., Clarkin, J. F., and Fabio, M. (2019). Maladaptive personality traits and psychological distress in adolescence: the moderating role of personality functioning. Pers. Indiv. Diff. 140, 33–40. doi: 10.1016/j.paid.2018.06.026

Billieux, J., Gay, P., Rochat, L., and Van der Linden, M. (2010). The role of urgency and its underlying psychological mechanisms in problematic behaviours. Behav. Res. Ther. 48, 1085–1096. doi: 10.1016/j.brat.2010.07.008

PubMed Abstract | CrossRef Full Text | Google Scholar

Butler, H. A., Pentoney, C., and Bong, M. P. (2017). Predicting real-world outcomes: Critical thinking ability is a better predictor of life decisions than intelligence. Think. Skills Creat. 25, 38–46. doi: 10.1016/j.tsc.2017.06.005

Chan, C. (2019). Using digital storytelling to facilitate critical thinking disposition in youth civic engagement: a randomized control trial. Child. Youth Serv. Rev. 107:104522. doi: 10.1016/j.childyouth.2019.104522

Chen, M. R. A., and Hwang, G. J. (2020). Effects of a concept mapping-based flipped learning approach on EFL students' English speaking performance, critical thinking awareness and speaking anxiety. Br. J. Educ. Technol. 51, 817–834. doi: 10.1111/bjet.12887

Cuijpers, P. (2019). Targets and outcomes of psychotherapies for mental disorders: anoverview. World Psychiatry. 18, 276–285. doi: 10.1002/wps.20661

Duffy, M. E., Twenge, J. M., and Joiner, T. E. (2019). Trends in mood and anxiety symptoms and suicide-related outcomes among u.s. undergraduates, 2007–2018: evidence from two national surveys. J. Adolesc. Health. 65, 590–598. doi: 10.1016/j.jadohealth.2019.04.033

Dwyer, C. P. (2017). Critical Thinking: Conceptual Perspectives and Practical Guidelines . Cambridge: Cambridge University Press.

Google Scholar

Facione, P. A. (1990). Critical Thinking: Astatement of Expert Consensus for Purposes of Educational Assessment and Instruction . Millibrae, CA: The California Academic Press.

Fortgang, R. G., Hultman, C. M., van Erp, T. G. M., and Cannon, T. D. (2016). Multidimensional assessment of impulsivity in schizophrenia, bipolar disorder, and major depressive disorder: testing for shared endophenotypes. Psychol. Med. 46, 1497–1507. doi: 10.1017/S0033291716000131

Franco, A. R., Costa, P. S., Butler, H. A., and Almeida, L. S. (2017). Assessment of undergraduates' real-world outcomes of critical thinking in everyday situations. Psychol. Rep. 120, 707–720. doi: 10.1177/0033294117701906

Gambrill, E. (2005). “Critical thinking, evidence-based practice, and mental health,” in Mental Disorders in the Social Environment: Critical Perspectives , ed S. A. Kirk (New York, NY: Columbia University Press), 247–269.

PubMed Abstract | Google Scholar

Ghanizadeh, A. (2017). The interplay between reflective thinking, critical thinking, self-monitoring, and academic achievement in higher education. Higher Educ. 74. 101–114. doi: 10.1007/s10734-016-0031-y

Gilbert, T. (2003). Some reflections on critical thinking and mental health. Teach. Phil. 24, 333–339. doi: 10.5840/teachphil200326446

Gregory, R. (1991). Critical thinking for environmental health risk education. Health Educ. Q. 18, 273–284. doi: 10.1177/109019819101800302

Hayes, A. F. (2009). Beyond Baron and Kenny: Statistical mediation analysis in the newmillennium. Commun. Monogr. 76, 408–420. doi: 10.1080/03637750903310360

Hollon, S. D., and Beck, A. T. (2013). “Cognitive and cognitive-behavioral therapies,” in Bergin and Garfield's Handbook of Psychotherapy and Behavior Change, Vol. 6 . ed M. J. Lambert (Hoboken, NJ: Wiley), 393–442.

Hong, L., Lin, C. D., Bray, M. A., and Kehle, T. J. (2010). The measurement of stressful events in chinese college students. Psychol. Sch. 42, 315–323. doi: 10.1002/pits.20082

CrossRef Full Text

Jacobs, S. S. (1995). Technical characteristics and some correlates of the california critical thinking skills test, forms a and b. Res. Higher Educ. 36, 89–108.

Kargar, F. R., Ajilchi, B., Goreyshi, M. K., and Noohi, S. (2013). Effect of creative and critical thinking skills teaching on identity styles and general health in adolescents. Proc. Soc. Behav. Sci. 84, 464–469. doi: 10.1016/j.sbspro.2013.06.585

Leclair, M. C., Lemieux, A. J., Roy, L., Martin, M. S., Latimer, E. A., and Crocker, A. G. (2020). Pathways to recovery among homeless people with mental illness: Is impulsiveness getting in the way? Can. J. Psychiatry. 65, 473–483. doi: 10.1177/0706743719885477

Lee, H. S., Kim, S., Choi, I., and Lee, K. U. (2008). Prevalence and risk factors associated with suicide ideation and attempts in korean college students. Psychiatry Investig. 5, 86–93. doi: 10.4306/pi.2008.5.2.86

Li, S., Ren, X., Schweizer, K., Brinthaupt, T. M., and Wang, T. (2021). Executive functions as predictors of critical thinking: behavioral and neural evidence. Learn. Instruct. 71:101376. doi: 10.1016/j.learninstruc.2020.101376

Lin, Y. (2018). Developing Critical Thinking in EFL Classes: An Infusion Approach . Singapore: Springer Publications.

Luo, Q. X., and Yang, X. H. (2002). Revising on Chinese version of California critical thinkingskillstest. Psychol. Sci. (Chinese). 25, 740–741.

Mamun, M. A., Misti, J. M., Hosen, I., and Mamun, F. A. (2021). Suicidal behaviors and university entrance test-related factors: a bangladeshi exploratory study. Persp. Psychiatric Care. 4, 1–10. doi: 10.1111/ppc.12783

Patton, J. H., Stanford, M. S., and Barratt, E. S. (1995). Factor structure of the Barratt impulsiveness scale. J Clin. Psychol. 51, 768–774. doi: 10.1002/1097-4679(199511)51:63.0.CO;2-1

Peng, M. C., Wang, G. C., Chen, J. L., Chen, M. H., Bai, H. H., Li, S. G., et al. (2004). Validity and reliability of the Chinese critical thinking disposition inventory. J. Nurs. China (Zhong Hua Hu Li Za Zhi). 39, 644–647.

Profetto-Mcgrath, J. (2005). Critical thinking and evidence-based practice. J. Prof. Nurs. 21, 364–371. doi: 10.1016/j.profnurs.2005.10.002

Ren, X., Tong, Y., Peng, P., and Wang, T. (2020). Critical thinking predicts academic performance beyond general cognitive ability: evidence from adults and children. Intelligence 82:101487. doi: 10.1016/j.intell.2020.101487

Sanja, M., and Krstivoje, S. (2015). Developing critical thinking in elementary mathematics education through a suitable selection of content and overall student performance. Proc. Soc. Behav. Sci. 180, 653–659. doi: 10.1016/j.sbspro.2015.02.174

Stupple, E., Maratos, F. A., Elander, J., Hunt, T. E., and Aubeeluck, A. V. (2017). Development of the critical thinking toolkit (critt): a measure of student attitudes and beliefs about critical thinking. Think. Skills Creat. 23, 91–100. doi: 10.1016/j.tsc.2016.11.007

Suliman, W. A., and Halabi, J. (2007). Critical thinking, self-esteem, and state anxiety of nursing students. Nurse Educ. Today. 27, 162–168. doi: 10.1016/j.nedt.2006.04.008

Ugwuozor, F. O., Otu, M. S., and Mbaji, I. N. (2021). Critical thinking intervention for stress reduction among undergraduates in the Nigerian Universities. Medicine 100:25030. doi: 10.1097/MD.0000000000025030

Velotti, P., Garofalo, C., Petrocchi, C., Cavallo, F., Popolo, R., and Dimaggio, G. (2016). Alexithymia, emotion dysregulation, impulsivity and aggression: a multiple mediation model. Psychiatry Res. 237, 296–303. doi: 10.1016/j.psychres.2016.01.025

Wang, K., Shi, H. S., Geng, F. L., Zou, L. Q., Tan, S. P., Wang, Y., et al. (2016). Cross-cultural validation of the depression anxiety stress scale−21 in China. Psychol. Assess. 28:e88. doi: 10.1037/pas0000207

West, R. F., Toplak, M. E., and Stanovich, K. E. (2008). Heuristics and biases as measures of critical thinking: associations with cognitive ability and thinking dispositions. J. Educ. Psychol. 100, 930–941. doi: 10.1037/a0012842

Yoshida, T., Ichikawa, T., Ishikawa, T., and Hori, M. (1998). Mental health of visually and hearing impaired students from the viewpoint of the University Personality Inventory. Psychiatry Clin. Neurosci. 52, 413–418.

Yoshinori, S., and Marcus, G. (2013). The dual effects of critical thinking disposition on worry. PLoS ONE 8:e79714. doi: 10.1371/journal.pone.007971

Zhang, J., Lanza, S., Zhang, M., and Su, B. (2015). Structure of the University personality inventory for chinese college students. Psychol. Rep. 116, 821–839. doi: 10.2466/08.02.PR0.116k26w3

Keywords: mental health, critical thinking ability, critical thinking disposition, impulsivity, depression

Citation: Liu Z, Li S, Shang S and Ren X (2021) How Do Critical Thinking Ability and Critical Thinking Disposition Relate to the Mental Health of University Students? Front. Psychol. 12:704229. doi: 10.3389/fpsyg.2021.704229

Received: 04 May 2021; Accepted: 21 July 2021; Published: 19 August 2021.

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Copyright © 2021 Liu, Li, Shang and Ren. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Xuezhu Ren, renxz@hust.edu.cn

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Critical Thinking, Clinical Decision Making, and the Interpersonal Relationship

CHAPTER 5 CRITICAL THINKING, CLINICAL DECISION MAKING, AND THE INTERPERSONAL RELATIONSHIP Angie S. Chesser CHAPTER CONTENTS Critical Thinking and Clinical Decision Making The Nursing Process Implications for Psychiatric-Mental Health Nursing EXPECTED LEARNING OUTCOMES After completing this chapter, the student will be able to:    1.    Identify the basic concepts involved in critical thinking    2.    Correlate critical thinking with clinical decision making    3.    Describe the framework for critical thinking    4.    Describe how the nursing process is related to critical thinking and clinical decision making    5.    Correlate the stages of the nursing process with Peplau’s phases of the interpersonal relationship KEY TERMS Critical thinking Critical Thinking Indicators™ (CTIs™) Dispositions Nursing process Psychoeducational intervention   P sychiatric-mental health nursing care is practiced in multiple settings across the health care continuum. Patients of all ages in need of psychiatric-mental health nursing care can be found in hospitals, community agencies, and residential settings. Across all these settings and age groups, psychiatric-mental health nurses integrate critical thinking skills for clinical decision making throughout the interpersonal relationship. Critical thinking and clinical decision making are crucial elements to ensure that the patient’s needs are assessed, relevant problems are identified, and therapeutic nursing interventions are planned, implemented, and evaluated (Wilkinson,2011). Clinical decision making based on critical thinking is similar across all clinical settings. One unique dimension of critical thinking in psychiatric-mental health nursing is the importance of the interpersonal relationship as a major healing factor in delivering psychiatric nursing care. This chapter focuses on how psychiatric nurses integrate the concepts of critical thinking, clinical decision making, and the nursing process within the interpersonal relationship to address patient needs and delivery of nursing care. Throughout this textbook, a recurring special feature, “How Would You Respond?” is used to promote the development of critical thinking and clinical decision-making skills.   CRITICAL THINKING AND CLINICAL DECISION MAKING CRITICAL THINKING refers to a purposeful method of reasoning that is systematic, reflective, rational, and outcome oriented. It is an important part of psychiatric-mental health nursing and the interpersonal relationship. Through the use of critical thinking, psychiatric-mental health nurses make clinical decisions that translate into an appropriate plan of care for the patient (Harding & Snyder, 2015). Critical thinking correlated with clinical decision making does not refer to thinking that is judgmental, negative, or dismissive about a given strategy, plan, or subject under consideration. Rather, it is a conscious, organized activity that requires development over time through consistent effort, practice, and experience. Critical thinking is dynamic, not static, and ever-evolving based on the circumstances of the individualized situation. Numerous definitions have been developed about critical thinking and how it applies to nursing practice. Scheffer and Rubenfeld (2000), in a consensus statement, described critical thinking in nursing as           an essential component of professional accountability and quality nursing care. Critical thinkers in nursing exhibit these habits of mind: confidence, contextual perspective, creativity, flexibility, inquisitiveness, intellectual integrity, intuition, open mindedness, perseverance and reflection. Critical thinkers in nursing practice the cognitive skills of analyzing, applying standards, discrimination, information seeking, logical reasoning, predicting, and transforming knowledge. (p. 357) This consensus statement indicates that critical thinking is a positive skill set used by nurses to plan patient care.   Critical thinking is a purposeful method of reasoning that is systematic, reflective, rational, organized, and outcome oriented. Effort, practice, and experience are necessary to develop critical thinking. Domains of Critical Thinking Four specific domains have been identified as essential to critical thinking (Paul, 1993). These domains include the following:      Elements of Thought— The basic building blocks of thinking, such as purpose (what one hopes to accomplish), question or problem at issue, points of view or frame of reference, empirical dimension (evidence, data, or information), concepts and ideas, assumptions, and implications and consequences.      Abilities— The skills essential to higher order thinking, such as evaluating the credibility, analyzing arguments, clarifying meanings, generating possible solutions, and developing criteria for evaluation.      Affective Dimensions— The attitudes, dispositions, passions, and traits of mind essential to higher order thinking in real settings, such as thinking independently, being fair minded, developing insight, intellectual humility, intellectual courage, perseverance, and developing confidence in reasoning and intellectual curiosity.      Intellectual Standards— The standards used to critique higher-order thinking, such as clarity, specificity, consistency, preciseness, significance, accuracy, and fairness (Paul, 1993). Elements Necessary for Critical Thinking Critical thinking requires practice, effort, and experience. It involves the use of cognitive skills and working through DISPOSITIONS , the way a person approaches life and living (Facione, 2010). Boxes 5-1 and 5-2 highlight the cognitive skills and dispositions important for critical thinking. In addition to these cognitive skills and dispositions, evidence-based research has identified specific behaviors that demonstrate the knowledge, characteristics, and skills needed to promote critical thinking for clinical decision making. These behaviors are termed CRITICAL THINKING INDICATORS™ (CTIs ™ ; Alfaro-LeFevre, 2010). The two major categories of CTIs address knowledge and intellectual skills and competencies. Knowledge indicators involve:      Clarifying nursing versus medical information, normal and abnormal function including factors that affect normal function, rationales for interventions, policies and procedures, standards, laws and practice acts that are applicable to the situation, ethical and legal principles, and available information resources      Demonstrating focused nursing assessment skills and related technical skills, and clarifying personal values, beliefs, and needs, including how one’s self may differ from others’ preferences and organizational mission and values. Intellectual skills and competencies involve:      Application of standards, principles, laws, and ethics      Systematic and comprehensive assessment      Detection of bias and determination of information credibility   BOX 5-1: COGNITIVE SKILLS ASSOCIATED WITH CRITICAL THINKING INTERPRETATION •    Comprehension and expression of the meaning or significance of wide-ranging experiences, situations, data, events, and beliefs •    Ability to categorize, decode, and clarify the meaning and significance of the information ANALYSIS •    Identification of intended and inferred relationships •    Examination of ideas •    Detection and analysis of arguments EVALUATION •    Assessment of credibility •    Assessment of logical strength of actual or intended inferential relationships INFERENCE •    Ability to draw reasonable conclusions, conjectures, and hypotheses •    Ability to arrive at consequences based on data evidence, beliefs, opinions, and descriptions •    Evidence queries, alternative conjectures, and conclusion drawing EXPLANATION •    Presentation of coherent, logical, and rational reasoning •    Description of methods and results, justification of procedures, proposal and defense of one’s explanations or points of view, and presentation of full, well-reasoned arguments for seeking the best understanding SELF-REGULATION •    Ability to self-consciously monitor one’s cognitive activities, elements used in activities, and results obtained •    Self-examination and self-correction Adapted from Facione (2010).   BOX 5-2: DISPOSITIONS ASSOCIATED WITH CRITICAL THINKING •    Independent thinking •    Inquisitiveness toward a wide range of issues •    Concern to be and remain well informed •    Self-confidence in own abilities •    Open mindedness, fair mindedness •    Flexibility for alternatives and other options •    Honesty related to one’s own biases, prejudices, and stereotypes •    Intellectual courage: willingness to reconsider and revise views when change is necessary •    Creativity or “thinking outside the box” Adapted from Facione (2010).        Identification of assumptions and inconsistencies      Development of reasonable conclusions based on evidence      Determination of individual outcomes with a focus on results      Risk management; priority setting      Effective communication      Individualization of interventions Nurses also need to possess personal CTIs that support the critical thinking characteristics. These personal CTIs reflect the nurse’s behaviors, attitudes, and qualities that are associated with critical thinking.   The four domains of critical thinking are elements of thought, abilities, affective dimensions, and intellectual standards. Critical thinking involves the use of cognitive skills and working through dispositions or the way a person approaches life and living. Framework for Critical Thinking and Clinical Decision Making The question is, “How is critical thinking related to clinical decision making in psychiatric-mental health nursing?” First, critical thinking is a skill set involving cognitive skills and dispositions. It is a framework that structures psychiatric-mental health nurse’s clinical decision making for psychiatric-mental health patients and their needs throughout the interpersonal relationship. One way that psychiatric-mental health nurses use critical thinking as a framework for clinical decision making is to answer a structured series of questions either through individual reflection or in consultation with other nurses. Facione (2010) developed the “IDEALS” approach to assist psychiatric-mental health nurses in making therapeutic clinical decisions. This framework includes “Six Questions for Effective Thinking and Problem Solving” ( Box 5-3 ). Reflecting on and answering these questions can promote critical thinking involving cognitive skills and dispositions when a psychiatric-mental health nurse is engaged in the interpersonal relationship and faces a clinical problem in delivering care. One example of psychiatric-mental health nurses using critical thinking skills to solve patient care problems may include situations that involve the need to alter a noneffective plan of care after a nurse–patient interaction. Another example may occur when the nurse requests clinical supervision to better understand how personal feelings may be influencing the nurse–patient relationship. A third example may be when a nurse participates in a case conference related to developing a more consistent approach to a patient’s needs. Thus, when issues arise for a patient or within the interpersonal relationship, the psychiatric-mental health nurse’s critical thinking skills can help find the answer to the question, “What should I say or do now to meet this patient’s needs?”   The psychiatric-mental health nurse uses critical thinking skills to find the answer to the question about what to do or say to meet the patient’s needs.   BOX 5-3: SIX QUESTIONS FOR EFFECTIVE THINKING AND PROBLEM SOLVING: “IDEALS” I dentify the problem: “What’s the real question we’re facing here?” D efine the context: “What are the facts and circumstances that frame this problem?” E numerate choices: “What are our most plausible three or four options?” A nalyze options: “What is our best course of action, all things considered?” L ist reasons explicitly: “Exactly why are we making this choice rather than another?” S elf-correct: “Okay, let’s look at it again. What did we miss?” Adapted from Facione (2010).   THE NURSING PROCESS The NURSING PROCESS is a systematic method of problem solving that provides the nurse with a logical, organized framework from which to deliver nursing care. It is an ongoing, complex, cyclical process that requires the nurse to continually collect data, critically analyze it, and incorporate it into the patient’s treatment plan (Fortinash & Holoday Worret, 2008). Thus, the nursing process integrates critical thinking skills and clinical decision making. According to the American Nurses Association and The International Society of Psychiatric Mental Health Nurses (2014):           the six Standards of Practice describe a competent level of psychiatric-mental health nursing care as demonstrated by the critical thinking model known as the nursing process …. The nursing process encompasses all significant actions taken by registered nurses, and forms the foundation of the nurse’s decision making. The nursing process used in this text includes four key stages: assessment, planning/diagnosing, implementation, and evaluation (APIE). Nurses use the nursing process to deliver safe, effective therapeutic nursing care regardless of the setting. The challenge for psychiatric-mental health nurses is to integrate the specialized focus of their work with patients—the therapeutic use of self within the interpersonal relationship—with their nursing process skills. The integration of Peplau’s four-phase interpersonal model with the four-step nursing process model challenges the nurse to use critical thinking skills to provide care for psychiatric-mental health patients. Both the nursing process and the interpersonal relationship reflect a problem-solving approach to providing care. Their integration is important because it is the foundation for sound clinical decision making in psychiatric-mental health nursing. The Nursing Process and the Interpersonal Relationship Recall from Chapter 2 that Peplau identified four phases of the interpersonal relationship: orientation, identification, exploitation, and resolution. These phases closely parallel the stages of the nursing process. Figure 5-1 depicts the correlations among critical thinking, clinical decision making, the interpersonal relationship, and the nursing process.   Both the nursing process and the interpersonal relationship reflect a problem-solving approach to providing care. Psychiatricmental health nurses integrate the nursing process and the interpersonal relationship for sound clinical decision making in psychiatricmental health nursing. Assessment The first stage of the nursing process is assessment, which involves the collection of patient data through a patient history and physical assessment. For the psychiatric-mental health patient, a mental status examination and psychosocial assessment are essential components. The nurse obtains additional information from the patient’s medical record as well as from his or her own knowledge of relevant and current literature. This data collection process is ongoing, with the nurse continuously updating and validating the information. Peplau’s orientation and identification phases correspond to the assessment phase of the nursing process. In some clinical situations, a psychiatric-mental health nurse will have information about the patient before meeting him or her. This information may come from a variety of sources. The nurse may have information from a nursing report, another professional, records from other agencies, the patient’s significant others, or a patient having filled out an assessment questionnaire before the meeting. At other times, a psychiatric-mental health nurse may need to respond to a patient’s needs without any previous clinical history, such as in a crisis situation. The nurse uses observation skills to gather clinical information that can guide nursing interventions in the orientation and identification phases of such a relationship. A nurse might encounter a psychiatric patient in a hospital unit day room after an angry outburst in which the patient threatens to harm himself or herself. Although the nurse may have only minimal background information on the patient, the nurse can gather data based on the patient’s current emotional and behavioral status, which will guide the assessment and planning of care. Peplau also felt that the nurse should not explicitly focus on his or her own individual behavior or the client’s individual behavior; rather, the combined experience of the interaction should be interpreted (D’Antonio, Beeber, Sills, & Naegle, 2014). Figure 5-1 Interrelationship among critical thinking, clinical decision making, the interpersonal relationship, and the nursing process. Information about a patient’s prior clinical history is important because it can influence the orientation and identification phases when the nurse and the patient interact. When reviewing a patient’s clinical history, a psychiatric-mental health nurse needs to mobilize therapeutic use of self-skills to analyze and monitor his or her own reactions to the information and how it might help or hinder the establishment of a therapeutic relationship. Information that a psychiatric-mental health nurse has before meeting the patient, whether it is historical in nature or immediately in the here and now, can trigger a range of reactions for the nurse. The psychiatric nurse needs to develop self-awareness about how either a stereotypically biased reaction (e.g., questioning how any mother could attempt to harm her newborn) or a personal reaction (such as a nurse who works in substance abuse recovery reacting negatively to a patient’s suicide attempt during a relapse) can impede the development of a therapeutic relationship before it even begins. How Would You Respond? 5-1 provides a practical example for the therapeutic use of self during the assessment stage and orientation phase. The assessment stage begins when the patient and nurse meet, often for the first time. According to Peplau (1952), the orientation and identification phases begin when the nurse and the patient meet together and begin to structure a relationship that can therapeutically address the patient’s needs. Whether this is an encounter where the nurse meets the patient for the first time or the patient is known to the nurse from a previous therapeutic relationship and has now returned for further help, the assessment stage and the orientation and identification phases set the stage for how the nursing process and interpersonal relationship will unfold. Anxiety for both the nurse and the patient is common during this time because each has preconceptions about the other as well as uncertainty about how and if help can be provided. The nurse collects biopsychosocial clinical assessment data using the formats specific to the setting, for example, the hospital unit, emergency department, community agency, residential setting, or home health care setting. This clinical assessment occurs within the nurse–patient relationship. The psychiatric-mental health nurse works to build a trusting alliance with the patient so that the patient will share his or her perceptions about why this meeting is occurring and what his or her needs are. Using critical thinking skills, the nurse and the patient identify the problem and define the context, thereby providing the basis for determining future strategies to address the problems.  

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Critical Thinking Questions

Discuss why thoughts, feelings, or behaviors that are merely atypical or unusual would not necessarily signify the presence of a psychological disorder. Provide an example.

Describe the DSM-5. What is it, what kind of information does it contain, and why is it important to the study and treatment of psychological disorders?

The International Classification of Diseases (ICD) and the DSM differ in various ways. What are some of the differences in these two classification systems?

Why is the perspective one uses in explaining a psychological disorder important?

Describe how cognitive theories of the etiology of anxiety disorders differ from learning theories.

Discuss the common elements of each of the three disorders covered in this section: obsessive-compulsive disorder, body dysmorphic disorder, and hoarding disorder.

List some of the risk factors associated with the development of PTSD following a traumatic event.

Describe several of the factors associated with suicide.

Why is research following individuals who show prodromal symptoms of schizophrenia so important?

The prevalence of most psychological disorders has increased since the 1980s. However, as discussed in this section, scientific publications regarding dissociative amnesia peaked in the mid-1990s but then declined steeply through 2003. In addition, no fictional or nonfictional description of individuals showing dissociative amnesia following a trauma exists prior to 1800. How would you explain this phenomenon?

Imagine that a child has a genetic vulnerability to antisocial personality disorder. How might this child’s environment shape the likelihood of developing this personality disorder?

Compare the factors that are important in the development of ADHD with those that are important in the development of autism spectrum disorder.

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How Do Critical Thinking Ability and Critical Thinking Disposition Relate to the Mental Health of University Students?

Affiliation.

• 1 School of Education, Huazhong University of Science and Technology, Wuhan, China.
• PMID: 34489809
• PMCID: PMC8416899
• DOI: 10.3389/fpsyg.2021.704229

Theories of psychotherapy suggest that human mental problems associate with deficiencies in critical thinking. However, it currently remains unclear whether both critical thinking skill and critical thinking disposition relate to individual differences in mental health. This study explored whether and how the critical thinking ability and critical thinking disposition of university students associate with individual differences in mental health in considering impulsivity that has been revealed to be closely related to both critical thinking and mental health. Regression and structural equation modeling analyses based on a Chinese university student sample ( N = 314, 198 females, M age = 18.65) revealed that critical thinking skill and disposition explained a unique variance of mental health after controlling for impulsivity. Furthermore, the relationship between critical thinking and mental health was mediated by motor impulsivity (acting on the spur of the moment) and non-planning impulsivity (making decisions without careful forethought). These findings provide a preliminary account of how human critical thinking associate with mental health. Practically, developing mental health promotion programs for university students is suggested to pay special attention to cultivating their critical thinking dispositions and enhancing their control over impulsive behavior.

Keywords: critical thinking ability; critical thinking disposition; depression; impulsivity; mental health.

Copyright © 2021 Liu, Li, Shang and Ren.

Critical Thinking in Mental Health

So what is critical thinking? Basically it is just thinking about the evidence before you and measuring the likelihood of it being true or false, or partly true or partly false. There is even a Foundation and Center for Critical Thinking , a Critical Thinking Company , and a massive amount of websites with “official” definitions.

Critical thinking is discussed in academics at all educational levels, although because of varying definitions some don’t support the concept. In general, however, being able to critically think about new information is a good skill, especially as we get more and more inundated with information in our world.

When I am teaching my students about critical thinking I always focus on it as it relates to the mental health of their future clients. There is so much information out there that gets presented to mental health professionals as truth that if we aren’t good at critical thinking we could be putting our patients at risk. I have seen it before, where a therapist tries a “new” approach to treatment that is later discovered to be problematic.

I share this because as I finish up my first month of blogging for this site I realized that as much as I enjoy sharing new research, it is important to note that research is ever changing in the mental health world, and all new ideas and information needs to be approached with caution.

If you needed to see a therapist I would advocate you ask about treatment modalities, especially if specific techniques are being used. For example, sometimes I just let my client talk because that is what they need – I don’t consider that a modality itself. But if I felt that client would benefit from specific forms of cognitive-behavioral therapy I would share specific information about it, so they could look into it further if they wanted. Not all therapists think like I do though. So protect yourself – be a critical thinker when seeking therapy to ensure techniques used are based on actual evidence. It is the only way I would seek therapy.

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Critical Thinking: The Secret to Better Mental Health

In the bustling and ever-evolving world we live in, mental health has become a predominant area of focus for many individuals. its importance cannot be overstated. one of the key strategies to enhance mental health is through critical thinking, a cognitive process that encourages us to analyse and evaluate our thoughts, actions and experiences. .

Here we will delve into the intriguing relationship between critical thinking and mental health, elucidating how the former can significantly contribute to the betterment of the latter.

Understanding Critical Thinking

Critical thinking is the intellectually disciplined process of actively and skilfully conceptualising, applying, analysing, synthesising, and/or evaluating information gathered from, or generated by, observation, experience, reflection, reasoning, or communication, as a guide to belief and action. It is an essential skill that allows us to make informed decisions, solve problems, and develop a balanced perspective of the world around us.

The Intersection of Critical Thinking and Mental Health

Now, how does critical thinking intersect with mental health? Our mental health is significantly influenced by our thoughts, perceptions and interpretations of experiences. Through critical thinking, we can evaluate these thoughts and perceptions objectively, differentiating between reality and cognitive distortions, thus leading to better mental health.

When we develop a habit of thinking critically, we become more adept at recognising negative thought patterns such as catastrophising (predicting the worst-case scenario), overgeneralising (seeing a single negative event as a never-ending pattern of defeat), and mind-reading (assuming you know what others are thinking). This recognition is the first step in combating these patterns, paving the way for more positive and constructive thoughts.

Critical Thinking as a Tool for Emotional Regulation

Emotional regulation is a fundamental aspect of mental health, and here too, critical thinking plays a pivotal role. It equips us with the ability to identify, assess, and manage our emotions effectively. It promotes emotional intelligence and helps us to understand and regulate our emotional responses to situations.

For instance, when faced with a situation that induces anger, a critical thinker can reflect on why the situation has elicited this response, identify any irrational thoughts, and then reframe their perspective to reduce the intensity of the emotion. By doing so, one can maintain emotional balance, thereby promoting better mental health.

Building Resilience with Critical Thinking

Resilience, the capacity to recover quickly from difficulties, is another essential facet of good mental health. Critical thinkers are often more resilient as they can objectively analyse setbacks or challenges, learn from their experiences and devise strategies to overcome similar obstacles in the future. By maintaining an open mind and viewing challenges as opportunities for growth, individuals can significantly enhance their mental resilience, contributing to improved mental health.

Promoting Mental Health Through Improved Decision Making

Good decision-making skills are integral to mental health. People who regularly practice critical thinking are better equipped to make thoughtful, informed decisions. They are less likely to make impulsive choices that could potentially harm their mental well-being. Instead, they can assess the potential outcomes of their decisions and choose the path that is most beneficial for their mental health.

In summary, critical thinking is a powerful tool for bolstering mental health. It allows us to combat negative thought patterns, regulate emotions, enhance resilience, and improve decision-making skills. It is, indeed, the secret to better mental health.

To unlock the benefits of critical thinking, it is important to practice it regularly, and consider seeking the guidance of a professional counsellor or therapist, who can provide strategies and techniques to enhance this skill. As we continue to navigate the complexities of life, nurturing our critical thinking skills will enable us to maintain and improve our mental health, leading to a more balanced, fulfilling life.

At times, life can be overwhelming and leave us feeling lost, anxious, or depressed. Counselling can provide the support and guidance needed to navigate difficult times and achieve mental well-being. We offer a safe and confidential space to explore your thoughts, feelings, and concerns. We believe that everyone deserves access to quality mental health care, and we strive to provide an inclusive and non-judgmental environment for all. 

If you are struggling with mental health issues or feeling overwhelmed, we invite you to reach out to us for support. We are here to listen, guide, and empower you towards a healthier and happier life. Don't let mental health challenges hold you back from living your best life. Contact us today to schedule an appointment and take the first step towards better mental health.

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Exploring the Role of Critical Health Literacy in Addressing the Social Determinants of Health

National Academies of Sciences, Engineering, and Medicine; Health and Medicine Division; Board on Population Health and Public Health Practice; Roundtable on Health Literacy ; Editors: Kelly McHugh , Rapporteur and Rose Marie Martinez , Rapporteur.

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On January 27, 2021, the Roundtable on Health Literacy of the Health and Medicine Division of the National Academies of Sciences, Engineering, and Medicine held a virtual public workshop titled The Role of Critical Health Literacy in Addressing the Social Determinants of Health. The workshop's Statement of Task can be found in Box 1 . The planning committee's role was limited to planning the workshop and the Proceedings of a Workshop was prepared by the workshop rapporteurs as a factual summary of what occurred at the workshop. Statements, recommendations, and opinions expressed are those of individual presenters and participants, and are not necessarily endorsed or verified by the National Academies, and they should not be construed as reflecting any group consensus.

Statement of Task.

To begin the virtual workshop, Lawrence Smith, member of the Roundtable on Health Literacy, executive vice president and physician in chief at Northwell Health, and dean of the Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, welcomed attendees. Smith introduced the moderators for the panels: Olayinka Shiyanbola, associate professor in the Social and Administrative Sciences Division in the School of Pharmacy at the University of Wisconsin–Madison; Amanda J. Wilson, chief of the Office of Engagement and Training at the National Library of Medicine; and Gem Daus, health policy analyst in the Office of Health Equity at the Health Resources and Services Administration in the U.S. Department of Health and Human Services and adjunct professor in Asian American studies at the University of Maryland, College Park.

The following sections of the Proceedings of a Workshop—in Brief present summaries of each of the workshop's three presentations. The presentations examined the concept of critical health literacy, what critical health literacy can look like in action, and how it may be used in research and evaluation. The final section of the proceedings provides a summary of the panel discussion, facilitated by Shiyanbola, during which the panelists together explored facilitators, barriers, and future directions for the implementation of critical health literacy interventions.

• APPLYING THE CRITICAL HEALTH LITERACY FRAMEWORK TO ACHIEVE HEALTH EQUITY

Shiyanbola introduced the first speaker, Linn Gould, executive director of Just Health Action (JHA) in Seattle, Washington. 1 Gould developed and teaches a critical health literacy curriculum that can be used to take action on the social determinants of health (SDOH) to achieve health equity. 2

Gould began her presentation by first acknowledging that she lives and works on the traditional lands of the first people of Seattle and offered her gratitude to the Duwamish Tribe, past and present. Gould continued by presenting JHA's SDOH model (see Figure 1 ), which is the basis for its work on critical health literacy. The first three layers of the model are adapted from Dahlgren and Whitehead's (1991) SDOH model and the outer layer incorporates what Jones et al. (2009) refer to as the SDOH equity. This type of model is often referred to as the onion model.

The model of social determinants of health used by Just Health Action. SOURCES: Gould presentation, January 27, 2021; adapted from Dahlgren and Whitehead, 1991; Jones et al., 2009.

Gould then shifted her discussion to the three levels of health literacy—functional, interactive, and critical ( Nutbeam, 2000 ). She used safe sex as an example to describe each level. Functional literacy would entail providing individuals with facts about having safe sex. Interactive health literacy would be reached when people have learned how to communicate about having safe sex and are able to problem solve and independently make decisions about safe sex. Critical health literacy, which is not taught much in the United States today, she said, is about an individual's understanding of the SDOH and their ability to take action at both the individual and the community level ( Mogford et al., 2011 ). In the safe sex example, critical health literacy would come into play when a safe sex problem is identified in the community (e.g., high levels of sexually transmitted infections or unplanned pregnancies), and the question is asked: How can the community take action on the problem?

Gould then described a tree metaphor (pictured in Figure 2 ; Mogford et al., 2011 ) that is used in the curriculum and training that JHA developed to explain the critical health literacy framework to students and community members. The roots of the tree represent knowledge about equity, the SDOH, and health as a human right. In addition to the tree, the diagram includes a “compass” element. This dimension of the curriculum assists participants in finding a sense of direction as change agents, and exploring how participants want to be activists. An activist response to a problem, Gould explained, critically questions why the problem exists in the community and develops strategies to reduce or eliminate the problem on a structural level. Next, in order to move in the direction they identified in the compass stage, community members learn about tools and skills to take action; these are represented by the fruits of the tree. In the tree metaphor, the final stage of the process is represented by a bird flying away with a seed to take action and grow in the community.

Just Health Action's (JHA's) model for operationalizing the Critical Health Literacy (CHL) framework. This tree model is used to explain the framework to students and community members. SOURCES: Gould presentation, January 27, 2021. Concept from Mogford (more...)

JHA operationalizes the critical health literacy framework through several kinds of interventions. In any project that JHA engages in with a community, each stage of the framework (knowledge, compass, tools, and action) is incorporated. Gould also underscored that each intervention must be requested by the community, and that JHA does not enter a community without invitation. One type of intervention through which JHA operationalizes the critical health literacy framework is participatory action research. Together, the community and JHA conduct health impact assessments or cumulative health impact analyses. In the latter analyses, factors that contribute to negative health are considered together, rather than in isolation, to create a better assessment of a community's cumulative health impacts and associated health risks. Additionally, JHA operationalizes the critical health literacy framework through a number of educational activities that are, again, invited by the community. These activities might include co-curriculum development, co-teaching, and co-facilitation with community members.

Having laid out the basic framework that underlies JHA's work, Gould moved into describing critical health literacy projects undertaken by and with the Duwamish Valley community. She first noted that she collaborates with many organizations but her most important partner is the Duwamish River Cleanup Coalition, an alliance of 10 nonprofit organizations. 3 She went on to describe the two communities with which the partnership has conducted critical health literacy and power-building activities: South Park and Georgetown in South Seattle's Duwamish Valley. Gould explained that both communities, relative to other Seattle areas, have pronounced health inequities that compromise community health. For example, individuals living in the zip code that includes these communities (98108) have a life expectancy that is 13 years lower than that of individuals living in more affluent Laurelhurst (zip code 98105; Gould and Cummings, 2013 ). As additional context, Gould noted that the residents live adjacent to the Lower Duwamish Waterway Superfund Site. In the past, the Duwamish River had many meanders into a large estuary but in 1909, the Army Corps of Engineers straightened the river for industrial use. The valley represents 80 percent of Seattle's industrial land base, but the river and surrounding area is heavily contaminated. She also noted that, though the industry in the Duwamish Valley supplies about 80 percent of the area's family wage jobs, residents of the South Park and Georgetown communities do not necessarily have access to those jobs. Although the two communities face substantial health inequities, they have assets too; they are incredibly resilient areas, Gould said.

Gould said she often receives questions on how power building or empowerment and critical health literacy interact. During her presentation—and in discussion with Shiyanbola afterward—she emphasized that the concepts are inextricably linked; she noted that Nutbeam (1998) , who originated the concept, says that empowerment cannot be achieved unless critical health literacy is developed and action is taken on the SDOH. To this end, JHA created a power-building model for its work in the Duwamish Valley (see Figure 3 ). This figure illustrates how the pieces of the critical health literacy framework come together, combined with power building, to enable community action, with the ultimate goal of achieving health equity. She highlighted that empowerment is recognized both as part of the process and as an outcome.

Just Health Action's (JHA's) power-building model. This is used to guide its critical health literacy interventions, with the end goal of achieving health equity. NOTE: CBPR = community-based participatory research.

For the knowledge portion of the power-building model, JHA works with the communities to understand the SDOH through root-cause analysis exercises and storytelling. Community members also participate in root-cause analyses, an exercise used to understand the upstream, political determinants of health and to identify strategies to address those upstream factors.

In the compass and reflection portion of the work, JHA and community members conduct power analysis and advocacy mapping exercises. She described a health mapping exercise where youth and/or community members use pictures to depict the conditions that make a community healthy or unhealthy. This health mapping exercise contributes to decision making on the action areas that the community targets to improve health.

To build skills and capacity, Gould explained, JHA teaches whatever the community wants or needs. In terms of power building or empowerment, the goals are to understand and tackle inequitable distributions of power, improve daily living conditions, create health-promoting public policy, and conduct community action for health. Other exercises help community members define what equity means for the community and to design their own definitions for individual empowerment and community empowerment. They can measure their own progress on an empowerment pathway.

Gould provided a number of examples of community actions undertaken using the power-building model (see Figure 3 ). She described work with the Duwamish River Cleanup Coalition's Clean Air Program. 4 This program has been in existence for several years, but was relaunched last year with a new model. A broad range of community clean air partners (government agencies, universities, nonprofit organizations, and community members) participates in the program. She explained that community members conducted a root-cause exercise of asthma to identify what action strategies could be taken. Based on the analysis, they identified poor indoor air quality in rental housing as a cause of asthma and poor landlord maintenance of housing units as a cause of the cause (or “root cause”). This understanding enabled community members to identify a policy action: advocacy to get landlords to improve housing conditions. One of the most interesting observations noted with this exercise, she said, was that the policy actions identified by the community members were much more upstream than those selected by other types of partners who underwent the same exercise.

Another action taken by community members is community science—what academicians refer to as community-based participatory research (CBPR). For example, as part of the Duwamish Valley Clean Air Program, community youth collected moss and analyzed metals in the samples in order to identify the source of air pollution in the Duwamish Valley. Throughout the process, Gould explained, the partnership's intent is for the community to maintain ownership of the data and all other aspects of their work.

Gould ended her presentation with a brief summary of ongoing policy work around the Port of Seattle. She explained that, recently, the Port of Seattle admitted that it had been a partial contributor to the negative environmental and economic impacts in the Duwamish Valley over the past 100 years. For more than 3 years, JHA worked with the Port of Seattle Community Action Team, comprising about five members from Georgetown and five community members from South Park, to develop trust and to eventually co-write a policy resolution. Community members conducted policy advocacy and provided public testimony at the Port of Seattle meetings. On December 10, 2019, the Port of Seattle passed Resolution 3767, the Duwamish Valley Community Benefits Commitment Program. It was an exciting day for the Duwamish Valley, Gould said. 5

• CRITICAL HEALTH LITERACY AND COMMUNITY-BASED PARTICIPATORY RESEARCH

Wilson introduced the next speaker, Vanessa Simonds, associate professor at Montana State University. Simonds began her presentation by explaining that she conducts research in partnership with the Crow (or Apsáalooke) community in Montana. The research focuses on environmental health issues and uses the concept of critical health literacy to drive research activities, implementation, and evaluation efforts.

The community with which they work is an Indigenous, rural community. Like many other rural, low-income communities, this community faces a triple threat of a higher risk for exposure to chemicals or pathogens, a lack of access to resources to address and mitigate those exposures, and health literacy barriers (see Figure 4 ). Health literacy barriers, Simonds elaborated, arise when information on risks and resources is not communicated to the community in a way that aligns with the level of literacy skills in the community.

The “triple threat” for water insecurity risk. The community in which Simonds and the Crow community conduct their research faces health inequities including higher risk of exposure to chemicals or pathogens, a lack of access to resources (more...)

The environmental health problems that the Crow community is addressing, Simonds explained, are water insecurity and water safety. In the United States, rural tribal households are less likely to have access to safe water than non-tribal homes. Similar to other rural communities across the United States, many rural tribal residents rely on home wells as their primary water source. But home wells may be contaminated; for example, studies have documented uranium and arsenic contamination in wells on Navajo tribal lands. 6 Well testing in Crow communities has also found that some homes have unsafe, contaminated well water ( LaVeaux et al., 2018 ).

In addition to the problem of contaminated home well water, tribal members have raised concerns about the general deterioration of local water sources. Community members are losing access to safe and free water for basic household needs as river water quality declines. Water contamination and insecurity is troubling for all communities they affect, but for Crow people there are additional and significant dimensions to these problems, Simonds noted. First, the Crow people have a deep spiritual connection and relationship to water; water is deeply embedded within Crow cultural practices ( Martin et al., 2021 ). Additionally, complex tribal jurisdictional issues, paired with a lack of financial resources in the community, make it difficult for the community to address water contamination ( Simonds et al., 2019b ).

Simonds shared that the research team found that the health literacy framework (as described in Nutbeam, 2008 ) is compatible with CBPR to address environmental health issues ( LaVeaux et al., 2018 ; see Figure 5 ). In other words, CBPR can be used to undertake interventions around the three components of environmental health literacy: functional literacy, interactive literacy, and critical literacy. To achieve functional literacy, the CBPR research team worked with the community to design information that is clear, based on community language rather than jargon, and culturally relevant. For example, because water is very important to Crow people ( Martin et al., 2021 ), Simonds said it would be inappropriate to advise community members not to drink river water as part of a tribal ceremony, even though it may not be entirely safe. Once functional literacy is achieved, the CBPR research team and community co-created interventions around interactive literacy (where members act on and share the information they receive). Finally, by applying environmental critical health literacy, the CBPR team and the community worked together to achieve community-level change ( LaVeaux et al., 2018 ).

Combining the health literacy framework with community-based participatory research. SOURCE: Simonds presentation, January 27, 2021.

Simonds next shifted to provide more specifics on how the research team integrated the environmental health literacy framework into its CBPR approach in order to promote critical health literacy among community adults. An important first step in CBPR research, she said, is to consider the skill level of community members and to identify which skills they believe need to be developed. She noted that in 2004, tribal members began to identify water quality and the impact poor water quality can have on human health as a community problem. These community members reached out to and developed a partnership with researchers so that they could work to understand and document the contaminants in local water sources.

Two challenges that proved to be critical were building trust between researchers and the community, and considering how the researchers could best provide data and information back to the community ( LaVeaux et al., 2018 ). In the question-and-answer session that followed the presentation, Simonds reflected that the keys to building trust had been time and consistency. She highlighted the importance of the fact that the research team continued “showing up and doing what we said we would do.” With respect to the second challenge of communicating information back to the community, tribal members and the researchers determined that the co-creation of information materials would be the best method for communicating their findings ( LaVeaux et al., 2018 ). They found that home visits served as another effective method for informing community members. Trusted members of the Crow Environmental Health Steering Committee, a group formed to address water issues, conducted the home visits.

In 2014, the tribal leadership invited Simonds and her team to assist in furthering critical health literacy around water insecurity. A community–academic partnership, Guardians of the Living Water, a project founded by the Crow Environmental Health Steering Committee, served as the vehicle for increasing environmental health literacy among youth (fifth- and sixth-grade students) and their families. Simonds explained that the goal of the project was to address water insecurity holistically by educating youth about water quality science, the cultural significance of water sources, and the Crow values of respecting rivers and springs. The project initiated new partnerships with the local public school, the college, and community members to pursue the goal of enhancing critical health literacy in youth and inspiring them to be agents of change. The project hosted summer camps and after-school activities for youth to learn about the relationship between water-related environmental issues and human health, and supported activities for youth to apply their knowledge and conduct dissemination tasks ( Milakovich et al., 2018 ; Simonds et al., 2019a ).

Simonds explained that the team employed the same health literacy framework used with the adult community members to achieve functional, interactive, and critical health literacy with the youth. With respect to functional literacy, an existing curriculum conveyed the basics on the science of water quality, and Crow elders engaged in storytelling with the youth to integrate cultural knowledge about the importance of water to the Crow people ( LaVeaux et al., 2018 ).

The next step, according to Simonds, was to help the youth apply that knowledge and demonstrate interactive health literacy. Similar to activities conducted by the Crow Environmental Health Steering Committee, the youth chose to apply what they learned through water testing. They identified specific water sources of interest to them and conducted the tests themselves ( Milakovich et al., 2018 ; see Figure 6 ).

Youth in the Crow community conducting water testing. Through this activity, they are practicing interactive health literacy. SOURCE: Simonds presentation, January 27, 2021.

Another dimension of the project that supported functional and interactive health literacy was the use of a cross-mentoring model. Under the model, Simonds explained, tribal college or tribal high school students who had achieved functional health literacy served as mentors to middle school students. They assisted the younger students in developing their own questions and research, thinking about applying what they learned, and conducting water testing. In this way, older youth also demonstrated interactive health literacy.

Simonds shared that a number of questions arose with respect to developing critical health literacy among youth. These included “What is it that youth can do about this issue? How can they address water insecurity? What are the steps they can take? What do they need to learn so that they can act?” Students brainstormed a number of ideas, including adopting areas where trash tended to accumulate. They set out, monitored, and cared for trash cans in these areas in order to discourage trash dumping. The youth also thought up research questions related to water testing, including comparing water quality at different sites and determining how best to protect the water springs over time. Finally, the youth chose to develop a movie to educate others about what they had been learning (interactive health literacy). Indigenous filmmakers assisted the youth in creating the film, which ultimately received an award at an Indigenous film festival.

Simonds then commented on the success of their work in achieving its main goal: to develop youth as change agents through the application of critical health literacy. She reported that the research team conducted surveys and interviews with participants, parents, and the larger community in order to evaluate change. She noted that the youth talked about their increased sense of environmental responsibility, actions they had taken, and actions they wanted to take in the future ( Milakovich et al., 2018 ; Simonds et al., 2019a ). Photovoice, a qualitative method utilized in CBPR, was also part of the evaluation. Youth used photography and stories associated with their photographs as a medium to share their new knowledge and inform and educate the community. Simonds noted that the youth's experience led to the development of a new logic model (see Figure 7 ) that tells the story of how the project works to integrate Indigenous science and Western science, and to transmit that knowledge through youth to the broader community.

The project logic model for Guardians of the Living Water. It represents the transfer of Western science knowledge and Crow elder knowledge to the Montana State University partners, tribal and high school interns, then onto fifth- and sixth-graders, and (more...)

Simonds next reflected on lessons learned from the CBPR project. The overarching takeaway is that CBPR and critical health literacy can be beneficial in addressing the SDOH. The first lesson she offered is that environmental health issues related to water insecurity are complex and need to draw on science literacy, health literacy, and legal literacy. Second, she observed that the complexity of the issues necessitates cross collaboration, especially between community and academic–scientific partners. Scientists and academicians can provide guidance on what to research and how to address the identified problems; community partners can help researchers make their research more impactful and more effective. The third lesson relates to balancing what she describes as the need to provide youth with guidance versus the need to direct youth to be change agents. Ultimately, Simonds believes that youth need to be in charge of the ideas and the process. The fourth lesson Simonds stressed is the importance of integrating Indigenous knowledge and culture with Western science.

• IMPLEMENTING CRITICAL HEALTH LITERACY TO BUILD RESILIENCY

Daus introduced the final panelist, Gabriel Maldonado. Maldonado is founder and chief executive officer of TruEvolution, a community-based organization that advocates for health equity and racial justice to advance the quality of life and human dignity of LGBTQ+ people. The organization also provides HIV, mental health, and housing services.

Maldonado opened by providing some background to his presentation, titled Leading with Resiliency. He explained that his lived experiences as a member of the LGBTQ+ community, an individual living with HIV, and a former resident of an urban community of low socioeconomic status, led him to focus much of his work on stigma as an SDOH, and the role it plays in creating health disparities and health inequities. He noted that the organization he directs witnesses the impact of stigma on the health of the clients it serves, and it recognizes the role critical health literacy can play in promoting resiliency and addressing stigma in community settings.

Stigma has been identified as an SDOH, as it has been demonstrated to impact health outcomes and risks for a variety of conditions ( Craig et al., 2017 ; Hatzenbuehler et al., 2013 , 2014 ; Turan et al., 2017 ). Maldonado went on to describe the concept of stigma and how it operates in society. He explained that stigma broadly refers to assumptions made about a group of people, and how those assumptions affect the experiences of individuals. He said that stigma consists of three pieces. Stereotypes are characteristics generally assumed about a group of people. These stereotypes can lead to prejudice, when people assume that those stereotypes about a group are valid and confirmed. This, in turn, results in discrimination, which occurs when actions are taken based on those stereotypes and prejudices. These actions, he said, manifest in stigmatizing assumptions, stigmatizing experiences, and stigmatizing systems that affect individuals. As an example, he noted that systemic racism and systemic bias and prejudice exist in the health care system toward individuals with HIV. The systemic racism and bias often begin when individuals in positions of power, who hold stereotypes about people with HIV, create discriminatory experiences for the people they serve.

He went on to describe three types of stigma: community, institutional, and self- or internalized stigma. During this discussion, Maldonado provided examples of the mechanisms through which stigma can act as an SDOH and deepen health inequities. Community stigma refers to stigma that is encountered among family and friends, in the workplace, and in faith spaces. Faith spaces, he emphasized, may need special consideration. He shared that that there is a precarious relationship between the LBGTQ+ community and religious and faith spaces. On one hand, it is important to acknowledge that Black and Brown communities have found faith places to be spaces of safety and refuge, which can be beneficial for health. However, the Black and Brown LGBTQ+ communities have also experienced very real traumatizing effects of stigma perpetrated in faith spaces, he said.

He then discussed institutional stigma, which is the stigma encountered in a range of places that provide needed resources, such as the health care system, clinics, schools, universities, and the legal system. He emphasized the special situation of the large number of marginalized young people who are involved in the criminal justice system. Members of the LGBTQ+ community and individuals living with HIV, who already experience marginalization, encounter additional marginalization while in prison or jail. Such institutional stigma may act as an SDOH because it may prevent these individuals from accessing needed medications and services to address co-occurring conditions such as mental health problems and trauma, he said.

Last, Maldonado explained internalized stigma, held toward the self. This form of stigma is often characterized by sexual shaming, guilt, depression, retraumatization, avoidance, unprocessed anger and sadness, and fatalism. Fatalism, he said, finds its way into the souls of clients; internalized stigma acts as an SDOH because it affects their ability to engage in services, disclose information, trust, and be willing to go to multiple agencies to seek services.

Having established that stigma operates as an SDOH, Maldonado then transitioned to describe how critical health literacy could be used to address internalized stigma. Specifically, critical health literacy interventions can be used to build resiliency, which Maldonado said is the key to empowering individuals to combat stigma. Maldonado used the framework for resilience described by Harper et al. (2014) . Maldonado explained that building resiliency requires an individual to engage in health-promoting cognitive processing (functional health literacy), enact healthy behavioral practices or choices, enlist social support from others (interactive health literacy), and empower other young LGBTQ+ individuals (critical health literacy). Empowering the client to have a perspective beyond themselves is important, he said. Otherwise, the focus might remain on the tragedy and trauma of the individual's life experiences, rather than on what is possible.

Maldonado suggested that critical health literacy could be used to help build resiliency and combat stigma, as illustrated through the previous examples. Maldonado said his understanding of critical health literacy is based on a definition by Sykes et al. (2013) . It describes critical health literacy as “a set of characteristics of advanced personal skills, health knowledge, information skills, effective interaction between service providers and users, informed decision making and empowerment, including political action.” The potential consequences of critical health literacy, under this definition, are “improving health outcomes, creating more effective use of health services, and reducing inequalities in health” ( Sykes et al., 2013 ).

Maldonado offered eight suggestions to implement health literacy in health agencies and institutions (see Box 2 ). He suggested that the interventions described can help build toward critical health literacy, in part by improving functional and interactive health literacy in a community. These steps toward critical health literacy may also be regarded as, ultimately, steps toward building resiliency and combatting stigma.

Implementing Health Literacy in Health Agencies and Institutions.

After the presentation, Daus led a brief discussion. He asked Maldonado what data his service organization collects in order to identify what social determinants may be affecting clients. In reply, Maldonado explained that because providers at community-based organizations interact with clients every day they are able to provide crucial insight. For example, at his organization, check-ins and screenings are conducted regularly; this form of data allows the providers to identify themes and obstacles across clients (e.g., transportation barriers to accessing care). Those conversations, in turn, inform what social determinants the organization might target in the future. The interventions identified to address these SDOH could include approaches based in critical health literacy.

Following the final presentation, Shiyanbola facilitated a discussion with all of the panelists. Beginning with a question submitted by a member of the public, she asked what advice the speakers would give to health departments seeking to promote critical health literacy around the COVID-19 vaccine. Maldonado responded first to this question, and emphasized the importance of empowering and building the infrastructure of community-based organizations. Simonds concurred. She stressed that the Crow reservation and other tribal nonprofits have played a crucial role in delivering needed resources (such as food and masks) to the community during the COVID-19 pandemic. Gould shared that South King County has faced large disparities in the COVID-19 crisis, and that, though it took some time, she feels that the health departments have recognized a need to redirect their messaging and address the most impacted communities.

The next question came from roundtable member Wilson. Noting that all of the webinar's presentations shared the theme of working with youth, she asked the panelists whether there are certain populations, like youth, that are more amenable to critical health literacy projects than others. Simonds responded first, immediately explaining that the impetus for focusing on youth came from the urging of her partners in the Crow community. The community leaders felt that the youth would be the most effective change agents. In light of the fact that many of the partnership's leaders are elders, they felt it would also help sustain the work in future generations. Simonds added that it has proven to be a fruitful approach. Additionally, Gould noted that in immigrant communities, youth are an important audience for critical health literacy because they often have the highest levels of English fluency and are able to communicate information to other members of their communities.

Roundtable member Daus then asked the panelists about their experiences working with those who have had the opportunity to receive a professional education, such as nurses or doctors, and how they receive these concepts of health literacy. Gould responded that in her personal experiences teaching these concepts at medical schools and health departments, she has found that nurses have often been the most receptive to concepts of the SDOH and health equity. On the other hand, she states that she has encountered more resistance in her experiences with medical schools, where some individuals expressed that these concepts were “for social workers.” She suggested that community clinics tend to be more open to critical health literacy. Maldonado shared that he has felt encouraged that newer medical schools seem to be incorporating the SDOH, community health, and equity into their work. As an example, he noted that the University of California, Riverside, incorporated a commitment to these concepts as part of its entrance process and loan forgiveness programs.

In response to Shiyanbola's question about what the future looks like for health literacy in the space of the SDOH, Maldonado responded that it is unavoidable, and that “we are at the door.” He argued that the COVID-19 pandemic has revealed to the public that inaction around factors such as congregate housing and mental health has created a strain on the U.S. health care system. He suggested that continued avoidance of these topics by institutions is likely to result in poor health outcomes in the future. Gould stated that she envisions the end of poverty. She underscored the importance of “root-cause” exercises, such as those used in JHA's program, as a tool to help individuals understand the upstream policies that might affect change. She also expressed that focusing on individual behavioral change amounts to victim blaming. Simonds concurred with the statements of the other two panelists, and added that, when it comes to research, community partners want researchers to take action (as critical health literacy requires) rather than simply measuring and leaving.

In response to Simonds's comment, Wilson asked what researchers and scientists need to learn in order to effectively engage in CBPR. Simonds noted that her research team benefited from the fact that the Crow community was experienced in communicating its priorities to researchers. Additionally, the community had existing advisory boards that would consider researchers' proposals or that would initiate proposals themselves and bring them to researchers. She again underscored the importance of building trust between the research team and the community and said that researchers should maintain flexibility to pivot their approach if the community feels that it is not working.

Daus, sharing a question from the webinar chat, asked the panelists how they navigate balancing the important work of building resiliency with maintaining a focus on a systemic approach to the SDOH. In particular, he asked how they avoid reinforcing the narrative that individuals are responsible for disparate outcomes. Maldonado responded by noting that these are not mutually exclusive. Institutions and providers, he suggested, should focus on reducing the burdens placed on clients. At the same time, he clarified, it may be necessary to figure out how an individual with marginalized identities can navigate and overcome the barriers that they encounter on a day-to-day basis. He provided an example of working with an individual who has just relapsed during their recovery process with methamphetamine. His approach in that moment, he said, is to work with the client to identify what tools and resiliency they may need to be able to recover in that moment.

Shiyanbola then asked the panelists to turn to the challenges they have encountered in creating community-level, systemic change through critical health literacy work. Simonds shared that her team has encountered many challenges in its work around water insecurity in tribal communities. For instance, she shared that it can be difficult to navigate the overlapping jurisdictions of state and tribal entities. In the short term, her team addressed these challenges by focusing on well water testing, which goes unregulated by the government. The tribal colleges, she added, have responded by creating more courses related to water quality, as a longer-term solution to the gaps faced in these rural communities.

While Smith noted that trust is likely the biggest barrier to effective interventions in critical health literacy, he asked if the panelists have encountered misinformation, whether intentionally or unintentionally spread, as another barrier. He also asked how they approach addressing misinformation. In response, Gould noted that contamination and its causes can be complex, and that sometimes genuine confusion can result in the spreading of misinformation. She reiterated that addressing misinformation goes back to building trust. She shared a story about the impact that a meeting between U.S. Fish & Wildlife enforcement officers and community health advocates had on decreasing misinformation around fishing practices. Maldonado agreed that misinformation, and the unlearning of that misinformation, often present a serious challenge.

Lastly, the panelists responded to a question from Wilson, who asked what resources they recommend for people seeking to understand the difference between critical health literacy and health literacy. Maldonado stressed the importance of beginning with understanding the SDOH; if someone understands basic health literacy, and understands the SDOH, he suggested it is easier to bridge the gap. Gould noted that she and her team have shared educational materials on the JHA website and have published an article that can serve as a useful jumping off point ( Mogford et al., 2011 ). ◆◆◆

• Craig GM, Daftary A, Engel N, O'Driscoll S, Ioannaki A. Tuberculosis stigma as a social determinant of health: A systematic mapping review of research in low incidence countries. International Journal of Infectious Diseases. 2017; 56 :90–100. 10.1016/j. ijid.2016.10.011. [ PubMed : 27810521 ]
• Credo J, Torkelson J, Rock T, Ingram JC. Quantification of elemental contaminants in unregulated water across Western Navajo Nation. International Journal of Environmental Research and Public Health. 2019; 16 (15):2727. 10.3390/ijerph16152727. [ PMC free article : PMC6696199 ] [ PubMed : 31370179 ]
• Dahlgren G, Whitehead M. Policies and strategies to promote social equity in health. Background document to WHO—Strategy paper for Europe. Stockholm, Sweden: Stockholm Institute for Futures Studies; 1991.
• Gould L, Cummings B. Duwamish Valley cumulative health impacts analysis. Seattle, WA: Just Health Action and Duwamish River Cleanup Coalition/Technical Advisory Group; 2013.
• Harper GW, Bruce D, Hosek SG, Fernandez MI, Rood BA. the Adolescent Medicine Trials Network for HIV/AIDS Interventions. Resilience processes demonstrated by young gay and bisexual men living with HIV: Implications for intervention. AIDS Patient Care and STDs. 2014; 28 (12):666–676. 10.1089/apc.2013.0330. [ PMC free article : PMC4250951 ] [ PubMed : 25329778 ]
• Hatzenbuehler ML, Phelan JC, Link BG. Stigma as a fundamental cause of population health inequalities. American Journal of Public Health. 2013; 103 (5):813–821. 10.2105/AJPH.2012.301069. [ PMC free article : PMC3682466 ] [ PubMed : 23488505 ]
• Hatzenbuehler ML, Bellatorre A, Lee Y, Finch BK, Muennig P, Fiscella K. Structural stigma and all-cause mortality in sexual minority populations. Social Science and Medicine. 2014; 103 :33–41. 10.1016/j.socscimed.2013.06.005. [ PMC free article : PMC3818511 ] [ PubMed : 23830012 ]
• Hoover J, Gonzales M, Shuey C, Barney Y, Lewis J. Elevated arsenic and uranium concentrations in unregulated water sources on the Navajo Nation, USA. Exposure and Health. 2017; 9 (2):113–124. 10.1007/s12403-016-0226-6. [ PMC free article : PMC5425493 ] [ PubMed : 28553666 ]
• Jones CP, Jones CY, Perry GS, Barclay G, Jones CA. Addressing the social determinants of children's health. Journal of Health Care for the Poor and Underserved. 2009; 20 (4 Suppl):1–12. 10.1353/hpu.0.0228. [ PubMed : 20168027 ]
• LaVeaux D, Simonds VW, Picket V, Cummins J, Calkins E. Developing a curriculum for change: Water and environmental health literacy in a Native American community. Progress in Community Health Partnerships. 2018; 12 (4):441–449. [ PMC free article : PMC6375303 ] [ PubMed : 30739898 ]
• Martin C, Simonds VW, Young SL, Doyle J, Lefthand M, Eggers MJ. Our relationship to water and experience of water insecurity among Apsáalooke (Crow Indian) people, Montana. International Journal of Environmental Research and Public Health. 2021; 18 (2):582. 10.3390/ijerph18020582. [ PMC free article : PMC7827827 ] [ PubMed : 33445579 ]
• Milakovich J, Simonds VW, Held S, Picket V, LaVeaux D, Cummins J, Martin C, Kelting-Gibson L. Children as agents of change: Parent perceptions of child-driven environmental health communication in the Crow community. Journal of Health Disparities Research and Practice. 2018; 11 (3):115–127. [ PMC free article : PMC6430107 ] [ PubMed : 30906673 ]
• Mogford E, Gould L, DeVoght A. Teaching critical health literacy in the U.S. as a means to action on the social determinants of health. Health Promotion International. 2011; 26 (1):4–13. 10.1093/heapro/daq049. [ PMC free article : PMC3218635 ] [ PubMed : 20729240 ]
• Nutbeam D. Health Promotion Glossary. Health Promotion International. 1998; 13 (4):349–364. 10.1093/heapro/13.4.349.
• Nutbeam D. Health literacy as a public health goal: A challenge for contemporary health education and communication strategies into the 21st century. Health Promotion International. 2000; 15 (3):259–267. 10.1093/heapro/15.3.259.
• Nutbeam D. The evolving concept of health literacy. Social Science & Medicine. 2008; 67 (12):2072–2078. 10.1016/j.socs-cimed.2008.09.050. [ PubMed : 18952344 ]
• Simonds VW, Kim FL, LaVeaux D, Pickett V, Milakovich J, Cummins J. Guardians of the living water: Using a health literacy framework to evaluate a child as change agent intervention. Health Education Behavior. 2019a; 46 (2):349–359. 10.1177/1090198118798676. [ PMC free article : PMC6417982 ] [ PubMed : 30215276 ]
• Simonds VW, Margetts M, Rudd RE. Expanding environmental health literacy—a focus on water quality and tribal lands. Journal of Health Communication. 2019b; 24 (3):236–243. 10.1080/10810730.2019.1597948. [ PMC free article : PMC6510619 ] [ PubMed : 30998127 ]
• Sykes S, Wills J, Rowlands G, Popple K. Understanding critical health literacy: A concept analysis. BMC Public Health. 2013; 13 (1):150. 10.1186/1471-2458-13-150. [ PMC free article : PMC3583748 ] [ PubMed : 23419015 ]
• Turan B, Hatcher AM, Weiser SD, Johnson MO, Rice WS, Turan JM. Framing mechanisms linking HIV-related stigma, adherence to treatment, and health outcomes. American Journal of Public Health. 2017; 107 (6):863–869. 10.2105/ajph.2017.303744. [ PMC free article : PMC5425866 ] [ PubMed : 28426316 ]

See http: ​//justhealthaction.org (accessed April 13, 2021).

See http: ​//justhealthaction ​.org/resources/jha-curriculum-material (accessed April 13, 2021).

See https://www ​.duwamishcleanup.org (accessed April 13, 2021).

See https://www ​.duwamishcleanup ​.org/clean-air-project-link (accessed April 13, 2021).

See https://www ​.duwamishcleanup ​.org/port-of-seattle-community-equity (accessed April 13, 2021).

For example, Credo et al. (2019) and Hoover et al. (2017) .

This Proceedings of a Workshop—in Brief was prepared by Rose Marie Martinez and Kelly McHugh as a factual summary of what occurred at the workshop. The statements made are those of the rapporteurs or individual workshop participants and do not necessarily represent the views of all workshop participants; the planning committee; or the National Academies of Sciences, Engineering, and Medicine.

*The National Academies of Sciences, Engineering, and Medicine's planning committees are solely responsible for organizing the workshop, identifying topics, and choosing speakers. The responsibility for the published Proceedings of a Workshop—in Brief rests with the rapporteurs and the institution. The members of the planning committee were Annlouise Assaf, Pfizer Worldwide Medical and Safety; Gem Daus, Health Resources and Services Administration; Laurie Myers, Merck Sharp & Dohme Corp.; Olayinka O. Shiyanbola, University of Wisconsin–Madison School of Pharmacy; and Amanda J. Wilson, National Library of Medicine.

To ensure that it meets institutional standards for quality and objectivity, this Proceedings of a Workshop—in Brief was reviewed by Ruth Parker, Emory University School of Medicine; Christopher R. Trudeau, University of Arkansas at Little Rock William H. Bowen School of Law; and Amanda J. Wilson, National Library of Medicine. Hugh Tilson, University of North Carolina Gillings School of Global Public Health, served as the review coordinator.

For additional information regarding the workshop, visit www.nationalacademies.org/HealthLiteracyRT .

Health and Medicine Division

The national academies of sciences • engineering • medicine.

The nation turns to the National Academies of Sciences, Engineering, and Medicine for independent, objective advice on issues that affect people's lives worldwide. www.nationalacademies.org

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National Academies of Sciences, Engineering, and Medicine. 2021. Exploring the role of critical health literacy in addressing the social determinants of health: Proceedings of a workshop—in brief. Washington, DC: The National Academies Press. https://doi.org/10.17226/26214 .

• Cite this Page National Academies of Sciences, Engineering, and Medicine; Health and Medicine Division; Board on Population Health and Public Health Practice; Roundtable on Health Literacy; McHugh K, Martinez RM, editors. Exploring the Role of Critical Health Literacy in Addressing the Social Determinants of Health: Proceedings of a Workshop—in Brief. Washington (DC): National Academies Press (US); 2021 Jun 16. doi: 10.17226/26214
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Critical Thinking Therapy for Mental Health and Self-Actualization through The Cultivation Of Intellectual and Ethical Character as Well as One’s Creative Potential

We now offer counseling in Critical Thinking Therapy as well as instruction in Critical Thinking Therapy for Therapists. Critical Thinking Therapy uses the explicit concepts in critical thinking to help clients (or you) gain command of your emotional life, achieve emotional well-being and realize all of which you are capable as a unique individual. Critical Thinking Therapy is based in the assumption that to gain command of your life requires, first and foremost, gaining command of the thinking that is commanding your life. Contact Ms. Lisa Sabend at [email protected] for more information.

Moreover, Dr. Linda Elder is currently authoring a book with the working title Critical Thinking Therapy . This is currently expected to release in 2022.

Drawbacks of Conventional Mental Health Therapies

Critical thinking refers to reasoning (thinking) that adheres to standards of excellence (criteria for thinking). It entails the ability to explicitly take one’s thinking apart and examine each part for quality through intellectual standards (such as clarity, accuracy, relevance, breadth, depth, logicalness, fairness, significance, and sufficiency). It includes fairmindedness, since critical thinkers will always strive to consider relevant viewpoints in good faith. The cultivation of fairminded critical thinking necessitates working toward the embodiment of intellectual virtues such as intellectual empathy, intellectual humility, intellectual integrity, intellectual courage, confidence in reason, and intellectual autonomy. Critical thinking implies understanding one’s own native egocentric and sociocentric tendencies, and actively combatting these tendencies throughout daily life. Critical thinking also entails understanding the intimate relationship between thinking, feelings, and desires. And it involves a creative dimension that enables people to improve their thinking and the quality of their lives, to contribute to the development of human ideas and practices, and to achieve self-fulfillment and self-actualization.

It is clear that therapists typically neither use nor impart a comprehensive, explicit conception of critical thinking in their work with clients because they are rarely, if ever, taught such a conception. They may themselves think critically to some degree on any number of topics. But they will be limited by their overall lack of knowledge of critical thinking theory when attempting to advance critical thinking in the therapeutic setting (assuming they are even making such an attempt).

Characteristics of Mentally Healthy Persons

This leads to the fundamental question, how do counselors decide on the therapies they use? More specifically, what standards do they use to determine which to accept and which to reject?

To be mentally healthy in our complex and commonly pathological world requires a relatively high level of command of one’s own reasoning and of how that reasoning leads to one’s own actions. In therapy involving adults and adolescents, the therapists’ emphasis on reasoning should be primary, and focus specifically on clients taking full command of their reasoning using the tools of critical thinking. In the case of child therapy, the emphasis should still be on the reasoning of the clients themselves (in this case the children), but must also include a focus on the reasoning of the adults caring for the children, since the problem often lies with the parents’ reasoning or the reasoning of both parents and children, as well as others in the family with influence or power over the child.

Mentally healthy people who rely on explicit tools of criticality are able to consistently and accurately assess their own reasoning as well the reasoning of relevant others in their lives, the reasoning of politicians, writers, great thinkers, indeed anyone they choose and in any context they choose. Again, to assess reasoning, they routinely use intellectual standards that come to us through critical thinking – standards such as clarity, accuracy, relevance, significance, logicalness, depth, breadth, sufficiency, justifiability, and fairness.

In addition to learning the fundamentals of critical thinking theory as it relates to therapy or self-therapy, there are a number of important domains of human thought within which most all of us should learn to reason, if we are to enjoy the highest degrees of mental health, or what has been termed self-actualization or self-realization.   Clients should come to appreciate 1) the tools of criticality we all need to function in a complex world, 2) the pathologies and neuroses of human thought to which all humans fall prey as well as those to which they particularly fall prey, and 3) the domains of life especially important to them, as individuals, in achieving self-realization

How Critical Thinking Therapy is Different

Consequently, in addition to teaching clients explicit tools of critical thinking, Critical Thinking Therapists are able, through their own developed critical thinking skills, to effectively pull together and employ the best therapeutic approaches that have come to us through such fields as psychology, philosophy, sociology and anthropology. In developing or using the tools of critical thinking, they do not ignore the best ideas on mental health that have already been worked through by important thinkers from the past, but instead Critical Thinking Therapists appropriate and build on these ideas. In other words, they do not rely on any individual school of psychological or social thought, but instead pull together the best ideas from any field of thought relevant to the mental health of their clients (for instance art or music therapy).

In closing, through Critical Thinking Therapy, clinicians are able to directly use explicit tools of critical thinking to help clients intervene in pathological or neurotic thinking. Clients themselves are encouraged to internalize and use the tools of critical thinking as a central part of becoming mentally well. Further, through a robust conception of critical thinking, therapist and clients alike can learn to effectively assess all existing therapeutic techniques which purport to improve one’s mental health.

To inquire further about Critical Thinking Therapy and how we can bring it to your mental health journey, or to your practice if you are a therapist, please contact Ms. Lisa Sabend at [email protected] for more information.

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Research Article

How our longitudinal employment patterns might shape our health as we approach middle adulthood—US NLSY79 cohort

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Silver School of Social Work, New York University, New York, NY, United States of America

• Wen-Jui Han

• Published: April 3, 2024
• https://doi.org/10.1371/journal.pone.0300245
• Reader Comments

Recent labor market transformations brought on by digital and technological advances, together with the rise of the service economy since the 1980s, have subjected more workers to precarious conditions, such as irregular work hours and low or unpredictable wages, threatening their economic well-being and health. This study advances our understanding of the critical role employment plays in our health by examining how employment patterns throughout our working lives, based on work schedules, may shape our health at age 50, paying particular attention to the moderating role of social position. The National Longitudinal Survey of Youth-1979 (NLSY79), which has collected 30+ years of longitudinal information, was used to examine how employment patterns starting at ages 22 (n ≈ 7,336) might be associated with sleep hours and quality, physical and mental functions, and the likelihood of reporting poor health and depressive symptoms at age 50. Sequence analysis found five dominant employment patterns between ages 22 and 49: “mostly not working” (10%), “early standard hours before transitioning into mostly variable hours” (12%), “early standard hours before transitioning into volatile schedules” (early ST-volatile, 17%), “mostly standard hours with some variable hours” (35%), and “stable standard hours” (26%). The multiple regression analyses indicate that having the “early ST-volatile” schedule pattern between ages 22 and 49 was consistently, significantly associated with the poorest health, including the fewest hours of sleep per day, the lowest sleep quality, the lowest physical and mental functions, and the highest likelihood of reporting poor health and depressive symptoms at age 50. In addition, social position plays a significant role in these adverse health consequences. For example, whereas non-Hispanic White women reported the most hours of sleep and non-Hispanic Black men reported the fewest, the opposite was true for sleep quality. In addition, non-Hispanic Black men with less than a high school education had the highest likelihood of reporting poor health at age 50 if they engaged in an employment pattern of “early ST-volatile” between ages 22 and 49. In comparison, non-Hispanic White men with a college degree or above education had the lowest likelihood of reporting poor health if they engaged in an employment pattern of stable standard hours. This analysis underscores the critical role of employment patterns in shaping our daily routines, which matter to sleep and physical and mental health as we approach middle adulthood. Notably, the groups with relatively disadvantaged social positions are also likely to be subject to nonstandard work schedules, including non-Hispanic Blacks and people with low education; hence, they were more likely than others to shoulder the harmful links between nonstandard work schedules and sleep and health, worsening their probability of maintaining and nurturing their health as they approach middle adulthood.

Citation: Han W-J (2024) How our longitudinal employment patterns might shape our health as we approach middle adulthood—US NLSY79 cohort. PLoS ONE 19(4): e0300245. https://doi.org/10.1371/journal.pone.0300245

Editor: Emiko Usui, Hitosubashi University, JAPAN

Received: April 6, 2023; Accepted: February 23, 2024; Published: April 3, 2024

Copyright: © 2024 Wen-Jui Han. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data set used for this study, NLSY79, is publicly available at https://www.bls.gov/nls/nlsy79/using-and-understanding-data/home.htm .

Funding: The author received no specific funding for this work.

Competing interests: The author has declared that no competing interests exist.

Introduction

Since the 1980s, the rise of the technological and digital age has transformed how people around the globe live and work, carrying significant consequences for our overall well-being [ 1 ]. For instance, innovations in medicine and public health have increased life expectancy in the United States from 48 years in 1900 to 76 years in 2000 [ 2 ]. However, since the 1990s, health improvements might have been blunted by the increased prevalence of precarious employment [ 3 ]. Precarious jobs are defined as those with poor working conditions and weak power relations, including low wages, unpredictable or unstable hours, few or no benefits, and weak or no bargaining power. One of the essential indicators of a precarious job is working outside of traditional 9:00 to 5:00 hours, such as during early mornings, evenings, or nights, or having irregular hours (e.g., rotating, split, or unpredictable hours). Such work patterns are sometimes called nonstandard work schedules [ 4 ] or shiftwork [ 5 ]. Prior research has found that these jobs have physically exhausted and emotionally drained U.S. workers [ 3 ]. Recently, the COVID-19 crisis has heightened existing inequalities, as people engaging in shiftwork (ironically labeled “essential” work) experience greater exposure to infection and higher death tolls [ 6 ].

Approximately one-third of the workforce globally has a work schedule considered nonstandard or shiftwork [ 7 ]. Dr. Harriet Presser [ 8 ] was among the first to extensively document this labor force transformation. Her seminal works provide insights into not only the prevalence of such work schedules but also their potential implications for the well-being of individuals and their families [ 4 , 8 ]. Subsequent studies have demonstrated that nonstandard work schedules dictate when we can sleep, with implications for our sleep quality and overall physical and mental health [ 5 ]. Studies using samples from different occupations (e.g., nurses, truck drivers) [ 9 , 10 ] and countries (e.g., Canada, European countries, Singapore, South Korea, and the United States) [ 1 , 5 , 11 – 13 ] have consistently documented significantly worse health outcomes, including shorter sleep and a lower quality of sleep, among those with nonstandard work schedules compared to their counterparts. A growing line of scholarship has also documented well-established adverse associations between nonstandard work schedules, particularly night shifts, and a higher likelihood of poor physical health (e.g., cardiovascular disease) and mental health (e.g., anxiety, depression) [ 1 , 5 , 8 ].

Missing from the extant scholarship are longer term longitudinal studies using a life-course perspective with sequence analysis to examine how work schedule patterns might be associated with our sleep and health as we approach middle adulthood [ 14 ]. This study extends our knowledge by using the National Longitudinal Study of Youth-1979, a nationally representative sample of about 7,000 people in the U.S. over 30 years, from ages 22 to 50. I focus on work schedule patterns in the United States throughout individuals’ working lives to underscore the critical role of employment in our daily experience and thus our health. This study also fills a literature gap by paying attention to how such a link might differ by social position, as reflected by race-ethnicity, gender, and education. This study, therefore, provides new insights into factors shaping our well-being on a global scale given that nonstandard work schedules are increasingly becoming a global phenomenon [ 15 ].

Life-course approach using a cumulative advantage and disadvantage (CAD) lens

This study builds on the life-course perspective [ 16 , 17 ] to conceptualize the association between employment throughout adulthood and sleep and health at age 50. Specifically, firstly, drawing on a fundamental principle of the life-course perspective—that human development and aging are lifelong processes, with the appreciation that the past shapes the future—this study uses longitudinal data to conceptualize and empirically examine how work patterns during one’s working life between ages 22 and 49 may shape sleep and physical and mental health at age 50. Importantly, our health is shaped by daily events occurring to and around us but may not manifest their effects until years later. Hence, studying working lives over substantial periods allows one to identify and investigate long-term associations between changes in our employment concerning work schedules and our health. For example, we can never be certain that no association between employment patterns and our sleep and health exists merely based on short-term null effects. Building upon this principle, this study answers the following research question: How might lifetime work trajectories shape future health outcomes? Secondly, drawing on the principle of timing—that the health consequences of event transitions and patterns vary according to their timing in a person’s life—this study uses longitudinal data spanning more than 30 years of an individual’s life to understand how transitions between work schedules over time may shape sleep and health at age 50. By examining work trajectories, this study, thus, pays attention to the paths of changes in individuals’ employment patterns and transitions that might shape their health, taking a long view of the life course. Building upon this principle, this study also answers the following research question: How might transitions between schedules (for example, daytime hours to evening or night hours) be associated with our sleep (hours and quality) and our future physical and mental health? Overall, examining the constraints imposed by employment patterns, particularly work schedules, with a life-course lens allows us to understand how favorable work conditions from early adulthood to old age contribute to better health in an individual’s lifetime, with significant implications for the well-being of future generations.

Furthermore, I pay special attention to how the links between employment patterns throughout one’s working life and sleep health at age 50 might vary by social position, identified in this study through race-ethnicity, gender, and education. I adopt the cumulative advantage and disadvantage (CAD) framework [ 18 , 19 ], which assumes our social positions (e.g., race, ethnicity, gender) interact with macro systems and institutions (e.g., employment) to shape our opportunities and constraints throughout our lifetime, influencing our health by generating increasing disparities in resources between those who have and those who have not [ 16 , 18 , 19 ]. Importantly, some work schedules (e.g., daytime hours) are more likely than others (e.g., irregular hours) to benefit our sleep and health [ 1 , 5 ]. By considering social position in this investigation, I shed light on the prevalent health disparities among different social position groups that might partly result from work schedule patterns over time.

Health consequences of work schedules

Since the late 1990s, studies using both US and non-US samples have examined the links between work schedules and social, psychological, and physical well-being of individuals [ 1 , 8 , 20 ] and family members, including children [ 4 , 21 , 22 ]. These studies have largely found weak to moderate adverse associations between working nonstandard hours and the well-being of workers and their families, particularly when such a schedule was chosen involuntarily (e.g., a job requirement). One of the immediate adverse health consequences is a decline in the amount and quality of sleep for workers with nonstandard hours because these schedules (e.g., night shifts) counter our circadian rhythm, which is critical for maintaining and sustaining good health [ 5 ]. Health issues stemming from severe sleep deprivation and low sleep quality due to nonstandard work schedules have been labeled Shift Work Sleep Disorder (SWSD) by academics and experts in the medical field [ 5 ]. People with SWSD tend to report the following symptoms: trouble sleeping, excessive sleepiness, and tiredness. These symptoms compromise one’s overall physical and mental functions, leading to poor general health [ 5 ]. Regarding other health consequences, one study showed that 38% of people working an 8-hour night shift had a BMI ≥30 versus 26% of people working an 8-hour day shift ( p < .05) [ 23 ]. Another study found that people with nonstandard work schedules are also 42% more likely to suffer from depressive symptoms than those with standard schedules [ 24 ].

Our understanding of the links between work schedules and sleep and health has also been refined through increasingly sophisticated data, including from small cross-sectional samples [ 12 , 25 ], nationally representative samples [ 1 , 26 ], and panel data [ 27 , 28 ]. For example, using two-year longitudinal data on approximately 1,500 Norweigan nurses, Waage and colleagues found that nurses working night hours the prior year were more likely to report acute sleepiness or insomnia related to shiftwork in the current year [ 27 ]. Importantly, those who stopped working night shifts were more likely to report a reduction in excessive sleepiness and less insomnia. A recent study using panel data from 2002 to 2018 in Germany found that individuals who perceived their work as involving nonstandard work schedules, high job insecurity, and low social rights were more likely to have poorer physical and mental health than their counterparts, and chronic exposure to or transitioning into such work might predict poorer health than otherwise [ 28 ]. This study builds on this emerging literature to advance our knowledge by using sequence analysis to document the changes in work trajectories and then examining how those changes/trajectories might be associated with sleep and health.

The importance of social position.

Another line of studies has shown that social position shapes our likelihood of having jobs requiring nonstandard work schedules [ 3 , 8 ]. For example, Presser extensively documented that in the United States, young workers, Blacks, and people with a high school or lower education are particularly subject to working nonstandard schedules [ 8 ]. In addition, whereas men are more likely than women to have nonstandard schedules, the distribution can vary greatly by occupation. Nurses are a prime example of a female-dominated occupation requiring nonstandard work schedules, particularly night shifts. A substantial line of scholarship has documented that, compared to their counterparts, female workers with nonstandard work schedules, particularly night shifts, have substantially higher odds of experiencing sleep disturbance and fatigue [ 26 ], stroke [ 29 ], and breast cancer [ 30 ]. In addition, studies have shown that both shift work and being an African American independently increase the odds of having high blood pressure [ 31 ]. A growing body of evidence has also found that people of racial-ethnic minority groups are more likely to get insufficient or low-quality sleep. Adverse sleep issues, such as insomnia, may also help account for increasing health disparities, such as higher rates of cardiovascular disease among racial-ethnic minority groups [ 32 ]. The higher share of African Americans with jobs requiring nonstandard schedules than their counterparts does not help and may indeed further intensify the high prevalence of sleep issues among people of color.

Hence, employment carries long-lasting implications for the social, psychological, physical, and economic well-being of workers and their families, with significant implications for inequality across generations, a central CAD tenet. The rise in precarious jobs, particularly among those in relatively disadvantaged social positions, motivates the need to investigate whether engaging in nonstandard work schedules over time may translate into long-term health consequences. A previous study [ 33 ] using the same data as the current analysis found that individuals in various social positions such as men, Blacks, and people with low educational attainment (e.g., high school or less) were more likely to have ever worked nonstandard hours between ages 18 and 39 than were their corresponding counterparts. Importantly, compared to men, women were more likely to have either never or always had nonstandard work schedules by age 39. This finding reflects the reality that women-dominated occupations often require nonstandard hours (e.g., nurses, home health aides).

The present study

The field has established a decent set of scholarship on the associations between work schedules and sleep and health, including the consequences for family and child well-being. The implication is thus clear. People in the U.S. and around the world are increasingly subject to nonstandard work schedules, creating work-induced health disparities [ 1 , 3 , 4 , 12 ]. However, we have yet to understand how employment patterns over the life-course may shape our health as we approach middle adulthood. Furthermore, a long line of extant research has shown how some social positions may act as vulnerabilities, putting people on a disadvantaged trajectory throughout their lifetime [ 3 , 17 , 20 ]. Hence, drawing upon the CAD framework, this study pays attention to three markers representing social position—race-ethnicity, gender, and education—to highlight how the intersectionality between employment and social position may accumulate advantages and disadvantages throughout a lifetime, manifested in our sleep behaviors and general health. By using a nationally representative sample of youths aged 14–22 in 1979 in the United States, this analysis addresses this evidence gap by building upon the life-course and CAD lens to answer the following research questions: how might lifetime work trajectories (between ages 22 and 49) be associated with health outcomes as we approach middle adulthood (at age 50), and how might such an association differ due to the intersectionality between work and social position? Notably, the longitudinal data used in this analysis allow researchers to track employment patterns during a period when working nonstandard hours was on the rise [ 7 , 12 ].

Materials and methods

This study used the National Longitudinal Survey of Youth-1979 (NLSY79), which comprises a nationally representative sample of Americans between the ages of 14 and 22 in 1979 (N = 12,686). NLSY79 interviewed respondents every year until 1994 and biennially thereafter. The current analysis excludes two discontinued oversamples: non-Black non-Hispanic disadvantaged youths, discontinued in 1990 (n = 1,643), and military youth, discontinued in 1984 (n = 1,280). A total of 9,763 respondents served as the starting point after excluding these two discontinued oversamples. The response rates of NLSY79 have been remarkably high, ranging from 96% in the early survey years to about 77% in recent years [ 34 , 35 ]. The NYLS79 is well suited to this study due to its rich data on longitudinal sociodemographic characteristics (e.g., education, marriage, number of children) and work schedules.

I use outcome measures at age 50 and begin the sample at age 22. I chose age 50 for two primary reasons. First, as this study was built upon a life-course lens, focusing on age 50 allowed me to examine employment patterns over an extended period of time, from ages 22 to 49. Second, NLSY79 collects health outcomes in the health modules at ages 40, 50, and 60. By 2018 (the most updated data as of this analysis), most participants had reached age 50 but only a small proportion (10%) had reached age 60. Therefore, using age 50 meant the sample comprised the majority of the participants. I also had two primary reasons for selecting age 22 as the starting point for the employment patterns. First, NLSY79 did not collect information on ages 14–18 for those who were 19–22 in 1979, the first interview year. Second, more than 30% of the NLSY79 participants were in college between ages 18 and 22. During this period, their jobs, if they had one, were more likely to be temporary or part time [ 33 ]. Therefore, age 22 is a plausible beginning point for establishing a career for many participants, particularly the college graduates in the sample.

Participants

The final analysis excluded participants who were missing information on the sleep outcome at age 50 (n = 2,052) or on employment between ages 22 and 49 (n = 6). Furthermore, approximately 5% of cases (n = 369) were missing information on sociodemographic characteristics (e.g., from < 0.01% on education to about 4% on parental education). The final analyzed samples after these exclusions were 7,336 for the dependent variable of sleep quality, 7,324 for average sleep hours per day over a week, 7,334 for general health status, 7,262 for physical and mental functions, and 7,271 for depression symptoms. Following previous research, missing values for the dependent variables were not imputed to avoid measurement noise [ 36 ]. The pattern of missing values on these dependent variables suggests that the older participants (e.g., 19 or older in 1979) were more likely than the younger participants to have missing values on the dependent variables. This missing pattern suggests a positive selection bias; younger or healthier participants more likely to remain in the longitudinal study. No other significant differences in sociodemographic variables were found between those with and without missing outcome measures.

Hours . As part of the age 50+ health modules, the NLSY79 asked how many hours of sleep the participant typically gets at night on a weekday, and a separate question asked about the weekend. Using both questions, I created a new variable to represent the average number of hours a participant gets per day across a 7-day week. As a robustness check, the analysis was also run using three individual variables as the outcomes: average number of hours of sleep on a weekday, average number of hours of sleep on the weekend, and average number of hours of sleep per day across a 7-day week. The results were similar to those presented here. Note that information about sleep was not collected before the participants turned 50.

Quality . As part of age 50+ health modules, participants were asked how frequently they had experienced the following four issues over the last month: “have trouble falling asleep,” “wake up and have trouble falling back asleep,” “wake up too early and have trouble falling back asleep,” and “feel unrested during the day despite the amount of sleep.” Respondents answered using a 4-point Likert scale ranging from “almost always (4+ times per week)” to “rarely or never (once a month or less).” These four questions are commonly used in studies examining sleep quality or disturbance [ 37 ]. A standardized score with a mean of 0 and a standard deviation of 1 was created from these four questions with excellent reliability (α = 0.84). The higher the score, the better the sleep quality was.

Poor health.

The NLSY79 collects information on general health status by asking participants to assess their general health, ranging from excellent (1) to poor (5). I created a dichotomous variable that received a value of 1 if the participant reported having either “poor” or “fair” health, and 0 otherwise.

SF12 physical and mental health.

The NLSY79 adopted the 12-Item Short-Form Health Survey (SF-12 v1) to rate self-reported mental and physical health. The NLSY79 administered this scale as part of the 50+ health modules to those who had turned 50 since their last interview. These data were collected between the interview years of 2008 and 2016. Specifically, the respondents were asked 12 questions about the past 4 weeks, including whether pain had interfered with normal work, whether their health had limited their moderate activities, and their frequency of feeling downhearted or blue. The possible responses, given the nature of the question, include a 3-point Likert scale (not limited at all, limited a little, limited a lot) and a 5-point Likert scale (ranging from “all the time” to “none of the time”). This study used the global scores representing physical and mental functions created by the NLSY79, following the scoring established by Ware, Kosinski, and Keller [ 38 ]. The SF-12 has been shown to have good reliability (e.g., 0.89) and validity [ 38 ] and can detect active and recent depressive disorders [ 39 ]. NLSY79 standardized the scores to have a mean of 50 and a standard deviation of 10; a score of 50 corresponds to the U.S. average, and a one-point difference is one-tenth of a standard deviation [ 40 ]. Previous research has shown that the NLSY79 sample tends to have a higher-than-average score on SF-12 mental function and just about the average score on SF-12 physical function [ 40 ]. The higher the score, the better the function is.

Depressive symptoms.

As part of the age 50+ health modules, NLSY79 used seven items from the Center for Epidemiologic Studies Depression Scale (CES-D) [ 41 ] to collect data on respondents’ depressive symptoms [ 42 ]. Respondents were asked how they felt during the past week through prompts such as “I felt depressed” and “I felt lonely," with possible responses on a scale of 0 (rarely/none of the time/1 day) to 3 (most/all of the time/5–7 days). The NLSY79 created a total CES-D score (ranging from 0 to 21) by summing the responses of all seven questions. A higher score indicates more depressive symptoms. The scale score was coded as missing if one item was missing. Compared to the original 20-item CES-D, this short form has similar or higher reliability and validity [ 43 ]. Prior studies have found a score of 8 or greater to have acceptable specificity and modest sensitivity with the standard CES-D cutoff score of 16 [ 43 ]; this study thus used this cutoff score to identify individuals with symptoms putting them at clinical risk of depression.

Work schedules.

At every survey year, the NLSY79 asked participants about their work schedules. This study followed NLSY’s definitions and responses to create five work statuses. Specifically, a “standard” work schedule was defined as work beginning at 6 a.m. or later and ending by 6 p.m., “evenings” as work beginning at 2 p.m. or later and ending by midnight, “nights” as work beginning at 9 p.m. or later and ending by 8 a.m., and “variable” if the participant had either split or rotating shift or irregular hours. “Not working” was used when participants answered “not working at any job.” These five work statuses were used in the sequence analysis to arrive at possible clusters describing individuals’ employment patterns and trajectories.

Social position.

This study used three indicators to define social position independent of employment patterns: gender, race-ethnicity, and education. The choice of these three indicators is to avoid reverse causality. For example, low-income status during adulthood tends to be highly associated with working nonstandard hours. However, nonstandard work schedules could lead to low-income status instead of vice versa. In this case, low-income status might be better conceptualized as a mediator instead of a moderator in the association between employment and health. The year 1979 was used as the data point to identify gender as either woman or man (as the reference group). In 1979, separate questions were asked about race and ethnicity. These two pieces of information were used to define four racial-ethnic groups: non-Hispanic White (reference group; Whites hereafter), non-Hispanic Black (Blacks hereafter), Hispanic, and others. Participants’ highest educational degree completed by age 23 was used to determine educational achievement with four dichotomous groups: less than a high school degree (<12 years of schooling), a high school degree (12 years of schooling, reference group), some college (13–15 years of schooling), and college or higher (16+ years of schooling).

Sociodemographic characteristics.

A rich set of sociodemographic characteristics was considered in all analyses to address the potential unobserved heterogeneity between participants and selection bias that might explain the associations between employment patterns and sleep and health [ 1 , 8 ]. These variables include age in 1979; background characteristics at age 14, including not living with both biological parents, parental education (i.e., less than high school, high school as the reference group, some college, or college or higher), and living location (suburban, rural, versus urban); region of residence at age 22 (Northeast, Midwest, West, versus South); any health issues that limited the ability to work by age 22; being a parent by age 22; ever experiencing poverty before age 23; ever receiving welfare before age 23; the number of years living in poverty between ages 22 and 49; the number of years receiving welfare between ages 22 and 49; number of marriages by age 49; number of children by age 49; average weekly working hours between ages 22 and 49; and occupations between ages 22 and 49. I defined poverty as family income at 100% of or under the federal poverty threshold. Welfare receipt was defined as receiving any assistance, including low-income cash transfers (e.g., AFDC or TANF), food assistance (e.g., food stamps or SNAP), or supplemental security income (SSI). Of note, to avoid reverse causality, I did not control for annual wages or income given the high correlation between these two variables and the type of work; instead, education, experiences with poverty and welfare receipt, and occupations were considered as proxies for resources available and accessible to respondents.

I created three dichotomous variables to measure average weekly working hours with a value of 1 and 0 otherwise to categorize participants as having (1) “mostly or only full-time hours” if they worked 35+ hours a week for at least half of the survey years (i.e., proportion of 0.50–0.99) between 22 and 49 (the reference group), (2) “mostly or only part-time hours” if they worked fewer than 35 hours a week for at least half of the survey years between 22 and 49, or (3) “mixed” if the participants worked about an equal share of survey years at full- and part-time hours between 22 and 49. Similarly, data on occupation were collected at each interview between ages 22 and 49. I created five occupational categories: mostly professional/managerial, mostly sales-related, mostly service-related (the reference group), mostly other occupations, and mixed. I used dichotomous variables to classify each participant’s primary occupation between 22 and 49. A person was considered mostly professional/managerial if they worked at least half the survey years between ages 22 and 49 in such an occupation. The “mixed” occupation category comprised participants who worked about an equal share of the survey years in at least two of the five occupation categories between 22 and 49.

Data analysis.

Stata v.15 was used to perform the analyses in two steps. I first used sequence analysis to identify work schedule patterns between ages 22 and 49. I then conducted multiple regression analyses to examine the association between work schedule patterns (found in the sequence analysis) and the following health outcomes: sleep hours and quality, having poor health, SF-12 physical and mental functions, and having depressive symptoms.

When using a life-course perspective and focusing on the principles of lifespan development and timing, a sequence analysis is a well-suited statistical tool to chronologically classify the transitions between work schedule statuses over time [ 44 ]. To document the changes or transitions chronologically, this analysis used each year between the ages of 22 and 49 as the time axis, and the five work schedule statuses as the state or categorical variable tracked over time. I followed two steps to portray the work schedule trajectories over the working years (i.e., sequences) and then cluster the trajectories into groups. First, I calculated the similarity and dissimilarity between sequences using an optimal matching algorithm by setting the “costs” of turning one sequence into another [ 45 , 46 ]. Following the sequence analysis literature, I set the insertion and deletion costs to be 1 and used the Needleman-Wunsch algorithm to calculate the substitution costs based on the transition rates between work schedule categories; when the transition is rare, the substitution cost is higher [ 47 , 48 ]. I conducted additional sensitivity analyses using alternative theoretical-driven substitution (such as 2, 3, or other theoretically driven cost structures) to ensure the cluster solutions are not sensitive to cost-setting decisions [ 49 ]. The results affirm that they are not.

The next step was to cluster similar sequences into a finite number of groups using Ward’s hierarchical fusion algorithm [ 45 ]. The stopping rules based on the Calinski and Harabasz pseudo-F index and the Duda-Hart index, as well as the conceptual meaning of clusters, were used to determine the ideal number of clusters [ 50 ]. Fig 1 presents the five sequence cluster solutions obtained, and S1 Table presents these diagnostic tests.

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In the second step of the analysis, I used ordinary least squares (OLS) models to examine the associations between employment patterns and sleep hours and quality and SF-12 physical and mental functions, and I used logistic regression models to assess the associations between employment patterns and the likelihood of reporting poor health and having depressive symptoms (CES-D score > = 8). I then conducted post-estimations based on each multiple regression model to assess whether the regression estimates for the dependent variables were statistically significantly different between the five employment patterns. Next, I conducted interaction analyses to evaluate whether the associations between employment patterns and sleep and health might vary by social position. I conducted separate analyses by interacting the employment patterns with the following social position markers one at a time: race-ethnicity, gender, and education.

Due to the overwhelming number of combinations of employment patterns and the three social position markers, for brevity and for illustrative purposes, based on the interaction analyses, Figs 2 – 7 plot the predicted estimates of the number of sleep hours, sleep quality, poor health, SF-12 physical function, SF-12 mental function, and depressive symptoms against the work schedule patterns and the joint characteristics of race-ethnicity, gender, and education. The predicted probabilities in Figs 2 – 7 were produced by using the “margins” command in Stata based on the multivariate regression analyses. Of note, results for Hispanics were similar to but weaker than those comparing non-Hispanic Whites and non-Hispanic Blacks. Results for "Other" respondents were insignificant, primarily due to extremely small sample sizes. Therefore, the comparison between racial-ethnic groups in the Results section focuses on the Black–White differences.

Note: ST: standard hours; VH: variable hours; NW: not working. The box plot displays the 95% confidence interval of each predicted estimate.

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Descriptive picture

Table 1 displays all analyzed variables for the total sample (n = 7,336) and by employment cluster patterns between ages 22 and 49. Table 1 also presents the results of bivariate statistical tests to gauge differences between employment patterns in regard to sociodemographic characteristics. The focal independent variable in this analysis is employment patterns between ages 22 and 49. Fig 1 presents the distribution plot of the sequence analysis clusters of employment patterns between ages 22 and 49. About 60% of the NLSY79 participants had employment patterns involving mostly standard hours (ST) throughout their working years: 35% worked "mostly ST with some variable hours (VH)," and 26% worked "stable ST." A decent share of participants (17%) had an employment pattern characterized as working standard hours early in their careers (20s) but transitioning into a variety of work schedules (during their early 30s). This group is labeled "early ST-volatile." Another 12% of respondents had a similar employment pattern of working standard hours during their early working years but switched into mainly variable hours (labeled "early ST-mostly VH"). Finally, About 11% of respondents had an employment pattern characterized as "mostly not working (NW)."

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Table 1 also shows sociodemographic characteristics of the sample. NLSY79 contains slightly more women than men. Approximately half of the participants were non-Hispanic White, with another third identified as non-Hispanic Black, 19% as Hispanic, and about 1% as some other racial group. The majority were U.S.-born. In addition, at age 14, more than 70% of the NLSY79 respondents had parents with a high school degree or less, one-third were not living with both biological parents, and almost 80% lived in urban areas. Nearly 10% of these young adults reported health issues that limited work capacity by age 22. By age 23, for about 20% of these young adults, less than high school was their highest educational attainment, 43% had a high school degree, 23% had some college, and 14% had a college or above education. Roughly 30% of the participants were married at age 22, and about 29% had become parents by age 22. Finally, before age 23, about 44% of the participants had experienced poverty, and about 21% had received welfare assistance.

Furthermore, between ages 22 and 49, participants experienced an average of one marriage and had an average of two children. In addition, participants spent an average of two to three years experiencing poverty and received welfare assistance for an average of over two years. More than three-fourths of the participants mainly worked full-time (i.e., 35 or more hours per week). About a quarter of the participants mostly worked in professional/managerial occupations, more than one-third had primarily service-related occupations, and another 30% had jobs primarily in occupations other than professional/managerial, sales-, or service-related.

Regarding the outcome variables considered in this analysis, the average number of sleep hours per day on a weekday was 6.62 (SD = 1.41) and 7.21 (SD = 1.64) on the weekend; combined, across a 7-day week, participants slept an average of 6.92 hours (SD = 1.39). The average sleep quality of the analyzed sample was at the mean value. About 20% of the participants reported their general health status was either fair or poor. The average SF-12 physical function was 49.28 (SD = 10.14), slightly below the national average, and the average SF-12 mental function was 52.96 (SD = 8.81), slightly above the national average. These findings are consistent with the NLSY79’s reported statistics [ 34 ]. Approximately 17% of the respondents reported having depressive symptoms (CES-D scores > = 8) at age 50.

The bivariate statistical analyses shown in Table 1 suggest that people with employment patterns of “stable ST” had comparatively advantaged characteristics in terms of being non-Hispanic White, having a college or above education by age 23, being less likely to have been exposed to poverty or welfare assistance by age 22, and having a lower-than-average percentage of health issues limiting their ability to work. The next groups with somewhat advantaged sociodemographic characteristics were participants with an employment pattern of either “early ST-mostly VH” or “mostly ST with some VH;” the notable differences between these two groups were the former being more likely to be a man and non-Hispanic White and the latter being more likely to be a female and Hispanic. In contrast, being a man, being non-Hispanic Black, and having a high school degree were more likely to be associated with the “early ST-volatile” employment pattern. Of importance, participants with an employment pattern of “mostly NW” tended to have somewhat disadvantaged sociodemographic backgrounds. For instance, they were likely to be either non-Hispanic Black or Hispanic, to have less than a high school education, to have health issues limiting work, to have become parents by age 22, to have been exposed to poverty or welfare by age 22, and to experience more years of poverty and welfare assistance after age 22. Given these differences in sociodemographic backgrounds for the employment patterns, it is not surprising to find that, generally, people with the “stable ST” employment pattern between ages 22 and 49 had the most favorable sleep and health outcomes, and that people with the “mostly NW” employment pattern had the worst sleep and health outcomes. Those with the “early ST-volatile” employment pattern had the second-worst sleep and health outcomes.

Multiple regression estimates of work schedule patterns on sleep and health

Tables 2 and 3 report multiple regression estimates of employment patterns on sleep and health outcomes, with Table 2 reporting the hours and quality of sleep (OLS regression) along with the likelihood of self-reporting poor health (logistic regression) and Table 3 reporting SF-12 physical and mental functions (OLS regression) along with the likelihood of self-reporting depressive symptoms (logistic regression). All sociodemographic characteristics detailed in the Measures section were considered in all analyses. On the whole, results in Tables 2 and 3 indicate that employment patterns matter to sleep and health. Specifically, compared to the pattern of mostly stable standard hours (“stable ST”), having an employment pattern of working standard hours during early career years (age 20s) but transitioning into volatile schedules after age 30 (“early ST-volatile”) was statistically significantly associated with fewer hours of sleep per day, lower quality of sleep, a higher likelihood of self-reporting poor health at age 50, lower scores on SF-12 physical and mental functions, and a higher likelihood of having depressive symptoms. Compared to the “stable ST” pattern, people with an employment pattern of working mostly standard hours but with some variable hours (“mostly ST with some VH”) also had significantly worse sleep and health outcomes, except for a nonsignificant effect on SF-12 mental function. People with an employment pattern of having standard hours during their 20s but transitioning into mostly variable hours after age 30 (“early ST-mostly VH”) had significantly fewer hours of sleep per day and significantly lower SF-12 physical function scores than those with the “stable ST” pattern. Lastly, people with an employment pattern of mostly not working (“mostly NW”) reported a significantly higher likelihood of poor health and significantly lower SF-12 physical function than those with the “stable ST” pattern. In addition, post-estimation Wald test results (not shown, available upon request) indicate that individuals with the “early ST-volatile” employment pattern (1) slept significantly fewer hours (b = -0.24 vs. b = -0.10, χ 2 = 7.42, p < .01), reported significantly lower SF-12 physical function (b = -1.42 vs. b = -0.62, χ 2 = 5.53, p < .05), and were more likely to report poor health (b = 0.45 vs. b = 0.18, χ 2 = 9.08, p < .01) than those with the “mostly ST with some VH” pattern and (2) were more likely to report poor health than those with the “early ST-mostly VH” pattern (b = 0.45 vs. b = 0.08, χ 2 = 9.39, p < .01). Furthermore, individuals with the employment pattern of “early ST-mostly VH” had significantly fewer hours of sleep per day during the week compared to those with the “mostly ST with some VH” pattern (b = -0.23 vs. b = -0.10, χ 2 = 6.28, p < .01). The post-estimation Wald tests detected no other statistically significant differences among employment patterns.

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As expected, age, gender, race-ethnicity, education, marital status, health issues limiting work capacity, years of receiving welfare or living in poverty, number of marriages and children, weekly working hours, and occupations were by and large significantly associated with hours and quality of sleep and other health outcomes. However, gender and race-ethnicity did not make a difference in the likelihood of self-reporting poor health. Specifically, people occupying vulnerable social positions (e.g., women, less than a high school education, previously married, having health limitations, multiple marriages, more experiences of poverty and welfare, not having full-time work status) tended to report lower sleep quality and lower SF-12 physical and mental functions, and were more likely to self-report poor health and having depressive symptoms. Note that, compared to men, women reported significantly more hours of sleep but substantially lower sleep quality. Moreover, compared to non-Hispanic White peers, non-Hispanic Black respondents reported considerably fewer hours of sleep yet better sleep quality.

For ease of interpretation, Table 4 presents the predicted estimates of how sleep and health outcomes might vary by employment patterns based on the results reported in Tables 2 and 3 . Across all outcomes, among those employed, individuals engaged in the “early ST-volatile” pattern between 22 and 49 had fewer (if not the fewest) hours of sleep (6.80 hrs/day), the lowest quality of sleep (-0.02), the highest likelihood of self-reporting poor health (0.23), the lowest SF-12 physical and mental functions scores (48.62 and 52.45), and the highest likelihood of having depressive symptoms (0.19). In contrast, individuals engaged in the “stable ST” pattern had the best outcomes, followed by those with the pattern of “mostly ST with some VH.”

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Variations in links between employment patterns and outcomes by social position

Prior research suggests that social position influences employment patterns, with vital implications for our health [ 3 , 5 , 6 , 17 , 18 ]. Figs 2 – 7 display the predicted estimates of the six outcomes by intersecting employment patterns, gender, race, and education. S2 – S7 Tables present the predicted estimates in detail. Several findings are worth highlighting. First, education serves an important cushion for better sleep (hours and quality) and health outcomes regardless of employment pattern, race, or gender. Second, the significantly poorer sleep and health outcomes observed in Tables 2 and 3 were concentrated among people with vulnerable positions, such as females, racial minorities (with some exceptions detailed below), and those with less than a college degree. For example, Black males with the “early ST-mostly VH” employment pattern slept the least regardless of education; their average sleep hours were 6.39, 6.44, 6.44, and 6.50, respectively, for less than a high school degree, high school, some college, and college and above. On the other spectrum are White females, who tended to have the most sleep hours, particularly if they had the employment pattern of stable standard hours (7.14, 7.19, 7.19, and 7.25 for the educational groups of less than a high school degree to college or above) ( Fig 2 and S2 Table ).

In contrast with the sleep hours results, Black males reported the best and White females the worst sleep quality. These findings are particularly true for those with either the “early ST-volatile” or the “mostly ST with some VH” employment pattern regardless of educational attainment ( Fig 3 and S3 Table ).

The health outcomes also varied by employment pattern and social position. In general, “early ST-volatile” reported the poorest health outcomes across all educational groups and all racial/ethnic and gender pairings. Specifically, across all education categories, Black females who had the "early ST-volatile" employment pattern reported the highest likelihood of having poor health among all groups examined. Despite White males in the “early ST-volatile” group also reporting a high likelihood of having poor health, the difference in the likelihood of reporting poor health between Black females (.34) and White males (.27) with this employment pattern is about .07 among those with less than a high school education ( Fig 4 and S4 Table ). In addition, Black females with the “early ST-volatile” employment pattern had the lowest SF-12 physical function score, whereas males, regardless of race, reported the highest SF-12 physical function ( Fig 5 and S5 Table ). In regard to SF-12 mental function, Black males and females generally reported better scores than White males and females. In addition, White females with the “early ST-volatile” employment pattern reported the lowest SF-12 mental function; this is particularly true if they had a less than high school education ( Fig 6 and S6 Table ).

Similar to the SF-12 mental health results, Black males and females generally reported a lower likelihood of having depressive symptoms than their White counterparts. In addition, White females with the “early ST-volatile” employment pattern reported the highest likelihood of having depressive symptoms, particularly among those with less than a high school education ( Fig 7 and S7 Table ). The difference in the likelihood of having depressive symptoms between this group and White males in the highest education group with the “stable ST” employment patterns is striking: .32 versus .07.

Discussion and conclusion

Since the 1980s, our employment has been shaped by global technological and digital advances, together with the rise and dominance of the service economy. These changes have produced undesirable health consequences, including disrupting our sleep routines, an aspect of our daily life critical to nurturing our health. Decades of research has established that sleep, both duration and quality, matters to our health [ 5 ]. This paper contributes two crucial insights to advance our knowledge of how work may have become a vulnerability for our sleep and health. Specifically, nonstandard work schedules, a central indicator of precarious employment, have become a widespread job characteristic in the increasingly unequal and globalized labor market [ 3 , 15 ]. Moreover, the strains and harm caused by the recent devastating public health crisis (the COVID-19 pandemic) were disproportionately carried by those without resources and those with precarious jobs [ 51 ], particularly in the United States [ 6 ]. This study thus examines the extent to which having a nonstandard work schedule throughout one’s working life in the United States might make a difference in both sleep hours and quality and health outcomes. I paid particular attention to the relationship between employment patterns, sleep, and health outcomes among the groups most likely to be subject to working nonstandard hours. Below I highlight a few significant findings.

Using a nationally representative, longitudinal sample of U.S. individuals interviewed since 1979, this study finds that employment patterns over our working lives matter to our sleep and health, consistent with prior research [ 1 , 5 , 12 , 52 ]. Importantly, this study approaches this issue from a life-course perspective, examining how employment patterns over our working lives might be linked to our sleep and health by shaping our daily routines. My empirical results suggest that individuals engaged in volatile work schedule patterns—a combination of evening, night, and variable hours—could anticipate sleeping significantly fewer hours per day, getting lower sleep quality, perceiving lower SF-12 physical and mental functions, and reporting a higher likelihood of poor health and depressive symptoms at age 50 than people working regular daytime hours. In fact, any employment pattern involving nonstandard hours (such as evening, night, or variable hours) for most of one’s working years may be associated with adverse sleep and health outcomes. These results suggest that a job requiring constant changes between daytime, evenings, nights, and irregular hours could significantly interfere with daily routines, affecting when a person sleeps, eats, and socializes with family members and friends. Furthermore, night shifts require a waking state during night hours when our bodies need rest, disrupting our circadian rhythm and thus sleep routines, including sleep quality. The lack of (good quality) sleep, physical fatigue, and emotional exhaustion stemming from a volatile employment pattern exemplifies how our work has made us vulnerable to an unhealthy life. Indeed, in regard to the SF-12 physical and mental function scores and the likelihood of having depressive symptoms, the effect sizes associated with the “early ST-volatile” employment pattern were similar to, if not larger than, having less than a high school education (see Table 3 ). This adverse health consequence of nonstandard work schedule patterns is alarming given that the extant research has shown that getting an inadequate amount of sleep and having poor sleep quality can have myriad short- and long-term health consequences, ranging from somatic issues and increased stress responsivity, which can lead to increased anxiety and depression [ 53 ], to a high prevalence of hypertension, obesity, and stroke [ 5 ].

The picture becomes grimmer if we further disentangle these links by social position. For example, as shown in Table 1 , Blacks were more likely than their White peers to have an employment pattern of starting with standard hours but soon transitioning into volatile schedules for most of their working years. Importantly, the intersectionality between employment patterns and social position only underscores the substantial health disparities between those with resources and those without: those without disproportionately shoulder the adverse consequences of employment patterns characterized by volatility, confirming that advantages and disadvantages produced by our work can accumulate throughout a lifetime, with powerful implications for our health and well-being. The empirical evidence reported here shows that White females with a college or above education who had an employment pattern of stable standard-hour schedules (“stable-ST”) got on average six more hours of sleep a week ((7.25–6.39) x 7) than Black males with less than a high school degree who worked variable hours for most of their working years (“early ST-mostly VH”). Even within the group with less than a high school education, White females with the “stable-ST” employment pattern got on average five more hours of sleep a week ((7.14–6.39) x 7) than Black males with the “early ST-mostly VH” employment pattern. Similarly, the likelihood of reporting poor health was .09 among White males with a college or above education and an employment pattern of stable standard hours versus .34 (the highest likelihood) among Black females with a less than high school education and the “early ST-volatile” employment pattern. The former also reported significantly better SF-12 physical function than the latter, with an effect size of five-tenths of one standard deviation (51.61–46.44 = 5.17) (see S5 Table ).

However, the opposite is true regarding gender differences in sleep quality and mental health. Specifically, females generally reported more hours of sleep but also poorer sleep quality than their male counterparts, which is consistent with the established scholarship in this area [ 54 , 55 ]. Studies have examined whether gender differences in sleep quality might be related to biological (e.g., genetics) and sociological (e.g., family responsibilities, work) factors [ 54 ]. The extant research suggests that family responsibilities and work characteristics are the most important factors explaining why women experience sleep disorders more than men [ 54 ]. Specifically, among those who work nonstandard schedules, women are more likely to have sleep disorders than men [ 54 ]. In line with the literature, my analyses show that (see S3 Table ) White and Black females with less than a high school degree who had volatile employment patterns between ages 22 and 49 reported a sleep quality of -.29 and -.12, respectively. In contrast, the corresponding estimates were -.10 and .05 for White and Black males with that same educational level and employment pattern. As the sleep quality variable is a standardized score with a mean of 0 and a standard deviation of 1, the differences between White women and Black men amount to a one-third of a standard deviation (e.g., -.29 –(.05) / 1 = .34) among those with less than a high school degree and the employment pattern of “early ST-volatile.” Further, when comparing White and Black males with a college degree and the “stable ST” employment pattern, the corresponding estimates were .18 and .25. The difference between White females with a less than a high school degree and an employment pattern of “early ST-volatile” and Black males with a college or above education and a “stable ST” employment pattern is even larger, amounting to slightly over half of a standard deviation (e.g., -.29 –(.25) / 1 = .54). These differences are considered medium to large effect sizes [ 55 , 56 ].

In regard to mental health, extant studies have shown that males are less likely to report mental health symptoms than females, a finding echoed in my analysis. Prior research indicates that although males and females were equally likely to experience emotional stress, males were less likely than females to express stress in ways that are measured through items in the SF-12 or CES-D instruments [ 57 ]. In addition, studies have found that females are more likely than males to report mild-moderate depression, but males report severe depression and suicidal thoughts more often than females [ 58 ]. Because the measures used in this study assess mild to moderate depressive symptoms, my findings that females reported poorer mental functions and a higher likelihood of having at-risk depressive symptoms than males are in line with previous empirical evidence. Furthermore, prior research has indicated that gender differences in symptom phenotypes (e.g., atypical symptoms in male depression) or in coping style (e.g., males tend not to seek help) are mechanisms that might explain why studies tend to observe a higher incidence of depression among females than males [ 58 ].

In contrast, and importantly, the racial differences in sleep hours and quality, and in health outcomes found in my analyses are nuanced and far from straightforward. Although Black males and, to a lesser extent, Black females tended to report similar physical and mental health as their White counterparts, the contrasts are striking when looking at sleep-related results. Specifically, Black males reported the fewest hours of sleep yet the best sleep quality, whereas White females tended to report more sleep hours but much poorer sleep quality. Although the extant research suggests that Blacks tend to sleep fewer hours (e.g., < 7 hrs) and have poorer sleep quality than their White counterparts, the Black–White disparities in sleep quality previously documented are somewhat mixed [ 59 ]. For example, studies that use objective measurements to assess sleep quality tend to confirm the Black–White disparities in sleep quality [ 59 ]. However, the results are less definitive when a subjective measure such as self-reports are used [ 59 ], which is how sleep quality was collected in the NLSY79. Prior studies have also shown that the Black–White disparities in sleep quality might have to do with socioeconomic status or environmental factors (e.g., neighborhood quality) [ 59 – 61 ]. In other words, the Black–White disparities in sleep quality might disappear once we consider these factors. Indeed, the raw data of this analysis indicated that Blacks in the NLSY79 sample reported the lowest sleep quality among all respondents, but this disparity disappeared in the multiple regression analysis when a rich set of sociodemographic characteristics were considered, including their work schedule trajectories.

Although beyond the scope of this paper, the scholarship on the “black–white health paradox” might also corroborate my findings that the Black respondents tended to report better sleep quality and similar if not better physical and mental functions despite shorter sleep duration [ 62 ]. Social stress theory, and related approaches, would predict that racial minority groups in the United States like Black Americans should be more likely than their White peers to develop poor physical and mental health due to discrimination-related experiences, in line with the core assumption of CAD [ 63 ]. However, prior studies using self-reported data (the same method as used with the NLSY79) have documented that Blacks display similar physical health and better mental health than their White counterparts [ 64 , 65 ]. Researchers have posited that experiencing discrimination, hardship, and stresses may increase resilience in the face of challenges [ 63 , 65 ]. If so, nonstandard work schedules, considered a disadvantage, might not directly translate into poor health for Blacks. However, caution is warranted when making any sweeping generalizations based on my results. After all, the predicted estimates shown in S3 Table suggest that Black males and females with less than a high school degree and a volatile employment pattern for most of their working lives had a high, if not the highest, likelihood of reporting poor health (.29 and .34, respectively) among all respondents. This association between perceived poor health and the joint forces of work and social position warrants attention in future research and policy advocacy endeavors.

Limitations

As with all observational studies, the current study has several limitations. First, the NLSY79 provided work schedule information annually until 1994 and biennially thereafter. For some, work schedules may have changed from month to month, let alone during the two-year windows, limiting my ability to depict more precise employment patterns over time. Thus, the present results may underestimate the true association between employment patterns and outcomes. However, the longitudinal approach has the advantage of reducing measurement noise. Specifically, longitudinal data allow more accuracy than cross-sectional data in recognizing, for example, individuals who have repeatedly reported nonstandard work schedules over the years versus those who might have only worked such a schedule a few times over 30 years.

Second, our daily routines and health are closely related to the type and amount of resources we can access; income and wages are the primary means of securing such resources. Ideally, the true association between employment patterns and sleep and health would be obtained after considering income and wages. However, the high correlation between employment and income and wages creates concerns about reverse causality. After all, our type of work determines how much income we can bring home. To address this potential reverse-causality issue, I controlled for the following variables likely to shape the type of work one may access at the start of their career and thus the wages and income they might bring home: the educational levels of the respondents and their parents and whether they had ever experienced poverty and/or received welfare before age 22. Nonetheless, our knowledge will benefit from a closer examination of how wages and income might play a critical role in the association between employment patterns and our sleep and health. For example, although it is beyond the scope of this analysis, future research might pursue this research question by utilizing a structural equation model to establish a proper temporal order between employment patterns (e.g., between ages 22 and 40), wages and income (e.g., between ages 41 and 49), and health outcomes (e.g., at age 50) to avoid reverse-causality issues. In this study, I did not adopt a structural equation modeling as specified above because my primary aim was to build upon a life-course lens to document the respondents’ work schedule trajectories using as many working years as possible (i.e., between ages 22 and 49 vs. between ages 22 and 39). Similarly, due to the data at hand, this analysis could not consider the number of hours respondents spent on household chores, which plays an important role not only in how many hours we can sleep but also in our physical and mental health. For example, women generally spend more time doing household work than men do despite potentially having the same number of working hours. These differences in household chores influence the number of hours a woman versus a man has for sleep and can impact their physical and emotional energy levels.

Third, individuals may switch from evening/night hours to standard daytime hours due to worsening health stemming from working nonstandard hours. If so, the estimates of the links between employment patterns and the sleep and health outcomes might be underestimated in this analysis. The sequence analysis adopted in this paper does not sufficiently answer such research questions. Although it is beyond the scope of this paper, future research might use other appropriate statistical analyses (e.g., latent transition analysis) to examine this crucial dynamic nature between employment patterns and sleep and health over time. Similarly, fixed-effect models might help answer research questions about how changes in employment patterns may shape changes in sleep and health over time. Such analyses would require at least three data points of health outcomes. This analysis relies on the 2018 NLSY79 data release, at which point only two such data points were available for the majority of its sample, as only about 10% of the respondents had reached age 60 to have three data points of health outcomes. In addition, the NLSY79 collected the sleep information analyzed here only in the health module at ages 50 and 60, thus limiting the ability to conduct the more sophisticated statistical analyses needed to answer more dynamic research questions.

Fourth, despite the sequence analysis accurately documenting the sequential changes in work trajectories, the analyses presented here at best represent associations instead of causation. While an experimental design study might allow one to detect a causal relationship between employment and sleep and health, randomly assigning individuals to different employment and various work schedule patterns would be neither feasible nor ethical. Hence, relying on quality longitudinal data with proper and sophisticated statistical analysis (e.g., fixed-effect modeling, instrumental variable) would allow us one step closer to causation.

Fifth, most of the NLSY79 health variables are self-reported, which likely influenced the outcomes identified here. Knowing how individuals perceive their sleep quality and health outcomes is critical as subjective perceptions significantly affect our well-being. However, the extant research using objective measurement tools consistently confirms a Black–White disparity in sleep quality and health outcomes, highlighting the importance of triangulating information to increase confidence in the findings.

Sixth, sample attrition is unavoidable with longitudinal data and could have affected some results. The positive selection bias associated with sample attrition might also bias the true association between employment patterns and sleep and health outcomes.

Seventh, although I used a separate racial-ethnic group named “other” that included Asian and other ethnicities, the estimates suffer from extremely small sample sizes, prohibiting me from drawing definitive interpretations about this group. This limitation warrants attention in future efforts to collect nationally representative data. Despite these limitations, the NLSY79 is the only dataset containing work schedule information for a nationally representative sample in the U.S. over three decades during a period when nonstandard work schedules were increasingly becoming prevalent throughout the country.

This study uses a life-course lens to shed much-needed light on how our employment patterns might shape our sleep and health as we approach middle adulthood. Employment is a crucial factor in the process of producing and accumulating resources and risks throughout our lives. Of importance, precarious employment has become increasingly typical in the globalized and polarized labor market, and nonstandard work schedules are a critical feature of precarious jobs. Examining employment patterns and work schedules through a longitudinal lens thus provides a deeper appreciation of how the impact of nonstandard work schedules might manifest through advantages and disadvantages accumulated throughout one’s working life. This approach also underscores that the health burden might be disproportionately shouldered by workers in vulnerable social positions (e.g., females, low education, Blacks). This study’s findings highlight the dual challenges facing workers in vulnerable social positions who have jobs requiring nonstandard work schedules, both of which limit their access to resources that would allow them to achieve decent sleep health and physical and mental health outcomes. This analysis thus calls attention to the reality of how employment as a social system may generate and perpetuate vulnerabilities and inequalities for particular groups over the life course.

Supporting information

S1 table. goodness-of-fit statistics for work arrangements sequence cluster solutions..

https://doi.org/10.1371/journal.pone.0300245.s001

S2 Table. Adjusted predictions of average sleep hours per day/week at age 50 by work schedule patterns, gender, race, and education.

https://doi.org/10.1371/journal.pone.0300245.s002

S3 Table. Adjusted predictions of sleep quality at age 50 by work schedule patterns, gender, race, and education.

https://doi.org/10.1371/journal.pone.0300245.s003

S4 Table. Adjusted predicted probabilities of self-reporting poor health at age 50 by work schedule patterns, gender, race, and education.

https://doi.org/10.1371/journal.pone.0300245.s004

S5 Table. Adjusted predictions of SF-12 physical function at age 50 by work schedule patterns, gender, race, and education.

https://doi.org/10.1371/journal.pone.0300245.s005

S6 Table. Adjusted predictions of SF-12 mental function at age 50 by work schedule patterns, gender, race, and education.

https://doi.org/10.1371/journal.pone.0300245.s006

S7 Table. Adjusted predicted probabilities of self-reporting depressive symptoms at age 50 by work schedule patterns, gender, race, and education.

https://doi.org/10.1371/journal.pone.0300245.s007

• View Article
• PubMed/NCBI
• Google Scholar
• 3. Kalleberg AL. Good Jobs , Bad Jobs : The Rise of Polarized and Precarious Employment Systems in the United States , 1970s to 2000s; Russell Sage Foundation: New York, USA; 2013.
• 8. Presser HB. Working in a 24/7 Economy : Challenges for American Families ; Russell Sage Foundation: New York, USA; 2003.
• 15. Kalleberg AL. Precarious lives : Job insecurity and well-being in rich democracies ; Polity Press, Cambridge, UK; 2018.
• 16. Elder GH, Johnson MK, Crosnoe R. The emergence and development of life course theory. In Mortimer JT, Shanahan MJ, editors. Handbook of the Life Course , Handbooks of Sociology and Social Research ; Boston, MA: Springer; 2003, p. 3–19. https://doi.org/10.1007/978-0-306-48247-2_1
• 21. Enchautegui ME. Nonstandard Work Schedules and the Well-Being of Low-Income Families ; Urban Institute: Washington, DC, USA; 2016. Available from: https://www.urban.org/research/publication/nonstandard-work-schedules-and-well-being-low-income-families
• 32. National Center for Chronic Disease Prevention and Health Promotion. African American health. CDC. 2017 July 3. Available from: https://www.cdc.gov/vitalsigns/aahealth/index.html
• 35. U.S. Bureau of Labor Statistics [Internet]. NLSY79 Data Overview. Available from: https://www.bls.gov/nls/nlsy79.htm
• 38. Ware J, Kosinski M, Keller S. SF-12: How to Score the SF-12 Physical and Mental Health Summary Scales (2nd ed); Boston: The Health Institute, New England Medical Center; 1995.
• 44. Gauthier J-A, Buehlmann F, Blanchard P. Introduction: Sequence analysis in 2014. In Blanchard P, Buehlmann F, Gauthier J-A, editors. Advances in Sequence Analysis : Theory , Method , Applications ; New York: Springer; 2014, p. 1–17.
• 46. MacIndoe H, Abbott A. Sequence analysis and optimal matching techniques for social science data. In Hardy MA, Bryman A. editors. Handbook of Data Analysis ; London, UK: SAGE; 2004, p. 387–406.