barriers to problem solving psychology quizlet

7.3 Problem-Solving

Learning objectives.

By the end of this section, you will be able to:

Describe problem solving strategies
Define algorithm and heuristic
Explain some common roadblocks to effective problem solving

People face problems every day—usually, multiple problems throughout the day. Sometimes these problems are straightforward: To double a recipe for pizza dough, for example, all that is required is that each ingredient in the recipe be doubled. Sometimes, however, the problems we encounter are more complex. For example, say you have a work deadline, and you must mail a printed copy of a report to your supervisor by the end of the business day. The report is time-sensitive and must be sent overnight. You finished the report last night, but your printer will not work today. What should you do? First, you need to identify the problem and then apply a strategy for solving the problem.

The study of human and animal problem solving processes has provided much insight toward the understanding of our conscious experience and led to advancements in computer science and artificial intelligence. Essentially much of cognitive science today represents studies of how we consciously and unconsciously make decisions and solve problems. For instance, when encountered with a large amount of information, how do we go about making decisions about the most efficient way of sorting and analyzing all the information in order to find what you are looking for as in visual search paradigms in cognitive psychology. Or in a situation where a piece of machinery is not working properly, how do we go about organizing how to address the issue and understand what the cause of the problem might be. How do we sort the procedures that will be needed and focus attention on what is important in order to solve problems efficiently. Within this section we will discuss some of these issues and examine processes related to human, animal and computer problem solving.

PROBLEM-SOLVING STRATEGIES

When people are presented with a problem—whether it is a complex mathematical problem or a broken printer, how do you solve it? Before finding a solution to the problem, the problem must first be clearly identified. After that, one of many problem solving strategies can be applied, hopefully resulting in a solution.

Problems themselves can be classified into two different categories known as ill-defined and well-defined problems (Schacter, 2009). Ill-defined problems represent issues that do not have clear goals, solution paths, or expected solutions whereas well-defined problems have specific goals, clearly defined solutions, and clear expected solutions. Problem solving often incorporates pragmatics (logical reasoning) and semantics (interpretation of meanings behind the problem), and also in many cases require abstract thinking and creativity in order to find novel solutions. Within psychology, problem solving refers to a motivational drive for reading a definite “goal” from a present situation or condition that is either not moving toward that goal, is distant from it, or requires more complex logical analysis for finding a missing description of conditions or steps toward that goal. Processes relating to problem solving include problem finding also known as problem analysis, problem shaping where the organization of the problem occurs, generating alternative strategies, implementation of attempted solutions, and verification of the selected solution. Various methods of studying problem solving exist within the field of psychology including introspection, behavior analysis and behaviorism, simulation, computer modeling, and experimentation.

A problem-solving strategy is a plan of action used to find a solution. Different strategies have different action plans associated with them (table below). For example, a well-known strategy is trial and error. The old adage, “If at first you don’t succeed, try, try again” describes trial and error. In terms of your broken printer, you could try checking the ink levels, and if that doesn’t work, you could check to make sure the paper tray isn’t jammed. Or maybe the printer isn’t actually connected to your laptop. When using trial and error, you would continue to try different solutions until you solved your problem. Although trial and error is not typically one of the most time-efficient strategies, it is a commonly used one.

Another type of strategy is an algorithm. An algorithm is a problem-solving formula that provides you with step-by-step instructions used to achieve a desired outcome (Kahneman, 2011). You can think of an algorithm as a recipe with highly detailed instructions that produce the same result every time they are performed. Algorithms are used frequently in our everyday lives, especially in computer science. When you run a search on the Internet, search engines like Google use algorithms to decide which entries will appear first in your list of results. Facebook also uses algorithms to decide which posts to display on your newsfeed. Can you identify other situations in which algorithms are used?

A heuristic is another type of problem solving strategy. While an algorithm must be followed exactly to produce a correct result, a heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. A “rule of thumb” is an example of a heuristic. Such a rule saves the person time and energy when making a decision, but despite its time-saving characteristics, it is not always the best method for making a rational decision. Different types of heuristics are used in different types of situations, but the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):

When one is faced with too much information
When the time to make a decision is limited
When the decision to be made is unimportant
When there is access to very little information to use in making the decision
When an appropriate heuristic happens to come to mind in the same moment

Working backwards is a useful heuristic in which you begin solving the problem by focusing on the end result. Consider this example: You live in Washington, D.C. and have been invited to a wedding at 4 PM on Saturday in Philadelphia. Knowing that Interstate 95 tends to back up any day of the week, you need to plan your route and time your departure accordingly. If you want to be at the wedding service by 3:30 PM, and it takes 2.5 hours to get to Philadelphia without traffic, what time should you leave your house? You use the working backwards heuristic to plan the events of your day on a regular basis, probably without even thinking about it.

Another useful heuristic is the practice of accomplishing a large goal or task by breaking it into a series of smaller steps. Students often use this common method to complete a large research project or long essay for school. For example, students typically brainstorm, develop a thesis or main topic, research the chosen topic, organize their information into an outline, write a rough draft, revise and edit the rough draft, develop a final draft, organize the references list, and proofread their work before turning in the project. The large task becomes less overwhelming when it is broken down into a series of small steps.

Further problem solving strategies have been identified (listed below) that incorporate flexible and creative thinking in order to reach solutions efficiently.

Additional Problem Solving Strategies :

Abstraction – refers to solving the problem within a model of the situation before applying it to reality.
Analogy – is using a solution that solves a similar problem.
Brainstorming – refers to collecting an analyzing a large amount of solutions, especially within a group of people, to combine the solutions and developing them until an optimal solution is reached.
Divide and conquer – breaking down large complex problems into smaller more manageable problems.
Hypothesis testing – method used in experimentation where an assumption about what would happen in response to manipulating an independent variable is made, and analysis of the affects of the manipulation are made and compared to the original hypothesis.
Lateral thinking – approaching problems indirectly and creatively by viewing the problem in a new and unusual light.
Means-ends analysis – choosing and analyzing an action at a series of smaller steps to move closer to the goal.
Method of focal objects – putting seemingly non-matching characteristics of different procedures together to make something new that will get you closer to the goal.
Morphological analysis – analyzing the outputs of and interactions of many pieces that together make up a whole system.
Proof – trying to prove that a problem cannot be solved. Where the proof fails becomes the starting point or solving the problem.
Reduction – adapting the problem to be as similar problems where a solution exists.
Research – using existing knowledge or solutions to similar problems to solve the problem.
Root cause analysis – trying to identify the cause of the problem.

The strategies listed above outline a short summary of methods we use in working toward solutions and also demonstrate how the mind works when being faced with barriers preventing goals to be reached.

One example of means-end analysis can be found by using the Tower of Hanoi paradigm . This paradigm can be modeled as a word problems as demonstrated by the Missionary-Cannibal Problem :

Missionary-Cannibal Problem

Three missionaries and three cannibals are on one side of a river and need to cross to the other side. The only means of crossing is a boat, and the boat can only hold two people at a time. Your goal is to devise a set of moves that will transport all six of the people across the river, being in mind the following constraint: The number of cannibals can never exceed the number of missionaries in any location. Remember that someone will have to also row that boat back across each time.

Hint : At one point in your solution, you will have to send more people back to the original side than you just sent to the destination.

The actual Tower of Hanoi problem consists of three rods sitting vertically on a base with a number of disks of different sizes that can slide onto any rod. The puzzle starts with the disks in a neat stack in ascending order of size on one rod, the smallest at the top making a conical shape. The objective of the puzzle is to move the entire stack to another rod obeying the following rules:

1. Only one disk can be moved at a time.
2. Each move consists of taking the upper disk from one of the stacks and placing it on top of another stack or on an empty rod.
3. No disc may be placed on top of a smaller disk.

barriers to problem solving psychology quizlet

Figure 7.02. Steps for solving the Tower of Hanoi in the minimum number of moves when there are 3 disks.

Figure 7.03. Graphical representation of nodes (circles) and moves (lines) of Tower of Hanoi.

The Tower of Hanoi is a frequently used psychological technique to study problem solving and procedure analysis. A variation of the Tower of Hanoi known as the Tower of London has been developed which has been an important tool in the neuropsychological diagnosis of executive function disorders and their treatment.

GESTALT PSYCHOLOGY AND PROBLEM SOLVING

As you may recall from the sensation and perception chapter, Gestalt psychology describes whole patterns, forms and configurations of perception and cognition such as closure, good continuation, and figure-ground. In addition to patterns of perception, Wolfgang Kohler, a German Gestalt psychologist traveled to the Spanish island of Tenerife in order to study animals behavior and problem solving in the anthropoid ape.

As an interesting side note to Kohler’s studies of chimp problem solving, Dr. Ronald Ley, professor of psychology at State University of New York provides evidence in his book A Whisper of Espionage (1990) suggesting that while collecting data for what would later be his book The Mentality of Apes (1925) on Tenerife in the Canary Islands between 1914 and 1920, Kohler was additionally an active spy for the German government alerting Germany to ships that were sailing around the Canary Islands. Ley suggests his investigations in England, Germany and elsewhere in Europe confirm that Kohler had served in the German military by building, maintaining and operating a concealed radio that contributed to Germany’s war effort acting as a strategic outpost in the Canary Islands that could monitor naval military activity approaching the north African coast.

While trapped on the island over the course of World War 1, Kohler applied Gestalt principles to animal perception in order to understand how they solve problems. He recognized that the apes on the islands also perceive relations between stimuli and the environment in Gestalt patterns and understand these patterns as wholes as opposed to pieces that make up a whole. Kohler based his theories of animal intelligence on the ability to understand relations between stimuli, and spent much of his time while trapped on the island investigation what he described as insight , the sudden perception of useful or proper relations. In order to study insight in animals, Kohler would present problems to chimpanzee’s by hanging some banana’s or some kind of food so it was suspended higher than the apes could reach. Within the room, Kohler would arrange a variety of boxes, sticks or other tools the chimpanzees could use by combining in patterns or organizing in a way that would allow them to obtain the food (Kohler & Winter, 1925).

While viewing the chimpanzee’s, Kohler noticed one chimp that was more efficient at solving problems than some of the others. The chimp, named Sultan, was able to use long poles to reach through bars and organize objects in specific patterns to obtain food or other desirables that were originally out of reach. In order to study insight within these chimps, Kohler would remove objects from the room to systematically make the food more difficult to obtain. As the story goes, after removing many of the objects Sultan was used to using to obtain the food, he sat down ad sulked for a while, and then suddenly got up going over to two poles lying on the ground. Without hesitation Sultan put one pole inside the end of the other creating a longer pole that he could use to obtain the food demonstrating an ideal example of what Kohler described as insight. In another situation, Sultan discovered how to stand on a box to reach a banana that was suspended from the rafters illustrating Sultan’s perception of relations and the importance of insight in problem solving.

Grande (another chimp in the group studied by Kohler) builds a three-box structure to reach the bananas, while Sultan watches from the ground. Insight , sometimes referred to as an “Ah-ha” experience, was the term Kohler used for the sudden perception of useful relations among objects during problem solving (Kohler, 1927; Radvansky & Ashcraft, 2013).

Solving puzzles.

Problem-solving abilities can improve with practice. Many people challenge themselves every day with puzzles and other mental exercises to sharpen their problem-solving skills. Sudoku puzzles appear daily in most newspapers. Typically, a sudoku puzzle is a 9×9 grid. The simple sudoku below (see figure) is a 4×4 grid. To solve the puzzle, fill in the empty boxes with a single digit: 1, 2, 3, or 4. Here are the rules: The numbers must total 10 in each bolded box, each row, and each column; however, each digit can only appear once in a bolded box, row, and column. Time yourself as you solve this puzzle and compare your time with a classmate.

How long did it take you to solve this sudoku puzzle? (You can see the answer at the end of this section.)

Here is another popular type of puzzle (figure below) that challenges your spatial reasoning skills. Connect all nine dots with four connecting straight lines without lifting your pencil from the paper:

Did you figure it out? (The answer is at the end of this section.) Once you understand how to crack this puzzle, you won’t forget.

Take a look at the “Puzzling Scales” logic puzzle below (figure below). Sam Loyd, a well-known puzzle master, created and refined countless puzzles throughout his lifetime (Cyclopedia of Puzzles, n.d.).

A puzzle involving a scale is shown. At the top of the figure it reads: “Sam Loyds Puzzling Scales.” The first row of the puzzle shows a balanced scale with 3 blocks and a top on the left and 12 marbles on the right. Below this row it reads: “Since the scales now balance.” The next row of the puzzle shows a balanced scale with just the top on the left, and 1 block and 8 marbles on the right. Below this row it reads: “And balance when arranged this way.” The third row shows an unbalanced scale with the top on the left side, which is much lower than the right side. The right side is empty. Below this row it reads: “Then how many marbles will it require to balance with that top?”

What steps did you take to solve this puzzle? You can read the solution at the end of this section.

Pitfalls to problem solving.

Functional fixedness is a type of mental set where you cannot perceive an object being used for something other than what it was designed for. During the Apollo 13 mission to the moon, NASA engineers at Mission Control had to overcome functional fixedness to save the lives of the astronauts aboard the spacecraft. An explosion in a module of the spacecraft damaged multiple systems. The astronauts were in danger of being poisoned by rising levels of carbon dioxide because of problems with the carbon dioxide filters. The engineers found a way for the astronauts to use spare plastic bags, tape, and air hoses to create a makeshift air filter, which saved the lives of the astronauts.

Researchers have investigated whether functional fixedness is affected by culture. In one experiment, individuals from the Shuar group in Ecuador were asked to use an object for a purpose other than that for which the object was originally intended. For example, the participants were told a story about a bear and a rabbit that were separated by a river and asked to select among various objects, including a spoon, a cup, erasers, and so on, to help the animals. The spoon was the only object long enough to span the imaginary river, but if the spoon was presented in a way that reflected its normal usage, it took participants longer to choose the spoon to solve the problem. (German & Barrett, 2005). The researchers wanted to know if exposure to highly specialized tools, as occurs with individuals in industrialized nations, affects their ability to transcend functional fixedness. It was determined that functional fixedness is experienced in both industrialized and nonindustrialized cultures (German & Barrett, 2005).

In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. Sometimes, however, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the $2,000 home? Why would the realtor show you the run-down houses and the nice house? The realtor may be challenging your anchoring bias. An anchoring bias occurs when you focus on one piece of information when making a decision or solving a problem. In this case, you’re so focused on the amount of money you are willing to spend that you may not recognize what kinds of houses are available at that price point.

The confirmation bias is the tendency to focus on information that confirms your existing beliefs. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Representative bias describes a faulty way of thinking, in which you unintentionally stereotype someone or something; for example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.

Finally, the availability heuristic is a heuristic in which you make a decision based on an example, information, or recent experience that is that readily available to you, even though it may not be the best example to inform your decision . Biases tend to “preserve that which is already established—to maintain our preexisting knowledge, beliefs, attitudes, and hypotheses” (Aronson, 1995; Kahneman, 2011). These biases are summarized in the table below.

Were you able to determine how many marbles are needed to balance the scales in the figure below? You need nine. Were you able to solve the problems in the figures above? Here are the answers.

The first puzzle is a Sudoku grid of 16 squares (4 rows of 4 squares) is shown. Half of the numbers were supplied to start the puzzle and are colored blue, and half have been filled in as the puzzle’s solution and are colored red. The numbers in each row of the grid, left to right, are as follows. Row 1: blue 3, red 1, red 4, blue 2. Row 2: red 2, blue 4, blue 1, red 3. Row 3: red 1, blue 3, blue 2, red 4. Row 4: blue 4, red 2, red 3, blue 1.The second puzzle consists of 9 dots arranged in 3 rows of 3 inside of a square. The solution, four straight lines made without lifting the pencil, is shown in a red line with arrows indicating the direction of movement. In order to solve the puzzle, the lines must extend beyond the borders of the box. The four connecting lines are drawn as follows. Line 1 begins at the top left dot, proceeds through the middle and right dots of the top row, and extends to the right beyond the border of the square. Line 2 extends from the end of line 1, through the right dot of the horizontally centered row, through the middle dot of the bottom row, and beyond the square’s border ending in the space beneath the left dot of the bottom row. Line 3 extends from the end of line 2 upwards through the left dots of the bottom, middle, and top rows. Line 4 extends from the end of line 3 through the middle dot in the middle row and ends at the right dot of the bottom row.

Many different strategies exist for solving problems. Typical strategies include trial and error, applying algorithms, and using heuristics. To solve a large, complicated problem, it often helps to break the problem into smaller steps that can be accomplished individually, leading to an overall solution. Roadblocks to problem solving include a mental set, functional fixedness, and various biases that can cloud decision making skills.

References:

Openstax Psychology text by Kathryn Dumper, William Jenkins, Arlene Lacombe, Marilyn Lovett and Marion Perlmutter licensed under CC BY v4.0. https://openstax.org/details/books/psychology

Review Questions:

1. A specific formula for solving a problem is called ________.

a. an algorithm

b. a heuristic

c. a mental set

d. trial and error

2. Solving the Tower of Hanoi problem tends to utilize a ________ strategy of problem solving.

a. divide and conquer

b. means-end analysis

d. experiment

3. A mental shortcut in the form of a general problem-solving framework is called ________.

4. Which type of bias involves becoming fixated on a single trait of a problem?

a. anchoring bias

b. confirmation bias

c. representative bias

d. availability bias

5. Which type of bias involves relying on a false stereotype to make a decision?

6. Wolfgang Kohler analyzed behavior of chimpanzees by applying Gestalt principles to describe ________.

a. social adjustment

b. student load payment options

c. emotional learning

d. insight learning

7. ________ is a type of mental set where you cannot perceive an object being used for something other than what it was designed for.

a. functional fixedness

c. working memory

Critical Thinking Questions:

1. What is functional fixedness and how can overcoming it help you solve problems?

2. How does an algorithm save you time and energy when solving a problem?

Personal Application Question:

1. Which type of bias do you recognize in your own decision making processes? How has this bias affected how you’ve made decisions in the past and how can you use your awareness of it to improve your decisions making skills in the future?

anchoring bias

availability heuristic

confirmation bias

functional fixedness

hindsight bias

problem-solving strategy

representative bias

trial and error

working backwards

Answers to Exercises

algorithm: problem-solving strategy characterized by a specific set of instructions

anchoring bias: faulty heuristic in which you fixate on a single aspect of a problem to find a solution

availability heuristic: faulty heuristic in which you make a decision based on information readily available to you

confirmation bias: faulty heuristic in which you focus on information that confirms your beliefs

functional fixedness: inability to see an object as useful for any other use other than the one for which it was intended

heuristic: mental shortcut that saves time when solving a problem

hindsight bias: belief that the event just experienced was predictable, even though it really wasn’t

mental set: continually using an old solution to a problem without results

problem-solving strategy: method for solving problems

representative bias: faulty heuristic in which you stereotype someone or something without a valid basis for your judgment

trial and error: problem-solving strategy in which multiple solutions are attempted until the correct one is found

working backwards: heuristic in which you begin to solve a problem by focusing on the end result

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9.5: Pitfalls to Problem Solving

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Learning Objectives

Explain some common roadblocks to effective problem solving

Not all problems are successfully solved, however. What challenges stop us from successfully solving a problem? Albert Einstein once said, “Insanity is doing the same thing over and over again and expecting a different result.” Imagine a person in a room that has four doorways. One doorway that has always been open in the past is now locked. The person, accustomed to exiting the room by that particular doorway, keeps trying to get out through the same doorway even though the other three doorways are open. The person is stuck—but she just needs to go to another doorway, instead of trying to get out through the locked doorway. A mental set is where you persist in approaching a problem in a way that has worked in the past but is clearly not working now. Functional fixedness is a type of mental set where you cannot perceive an object being used for something other than what it was designed for. During the Apollo 13 mission to the moon, NASA engineers at Mission Control had to overcome functional fixedness to save the lives of the astronauts aboard the spacecraft. An explosion in a module of the spacecraft damaged multiple systems. The astronauts were in danger of being poisoned by rising levels of carbon dioxide because of problems with the carbon dioxide filters. The engineers found a way for the astronauts to use spare plastic bags, tape, and air hoses to create a makeshift air filter, which saved the lives of the astronauts.

Figure 1 . In Duncker’s classic study, participants were provided the three objects in the top panel and asked to solve the problem. The solution is shown in the bottom portion.

Link to Learning

Check out this Apollo 13 scene where the group of NASA engineers are given the task of overcoming functional fixedness.

Query $\PageIndex{1}$

Query $\PageIndex{2}$

Query $\PageIndex{3}$

Watch this video from the Big Think to learn more about the confirmation bias.

You can view the transcript for “Confirmation Bias: Your Brain is So Judgmental” here (opens in new window) .

Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Representative bias describes a faulty way of thinking, in which you unintentionally stereotype someone or something; for example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.

Finally, the availability heuristic is a heuristic in which you make a decision based on an example, information, or recent experience that is that readily available to you, even though it may not be the best example to inform your decision . To use a common example, would you guess there are more murders or more suicides in America each year? When asked, most people would guess there are more murders. In truth, there are twice as many suicides as there are murders each year. However, murders seem more common because we hear a lot more about murders on an average day. Unless someone we know or someone famous takes their own life, it does not make the news. Murders, on the other hand, we see in the news every day. This leads to the erroneous assumption that the easier it is to think of instances of something, the more often that thing occurs.

Watch the following video for an example of the availability heuristic.

You can view the transcript for “Availability Heuristic: Are Planes More Dangerous Than Cars?” here (opens in new window) .

Biases tend to “preserve that which is already established—to maintain our preexisting knowledge, beliefs, attitudes, and hypotheses” (Aronson, 1995; Kahneman, 2011). These biases are summarized in Table 2 below.

Learn more about heuristics and common biases through the article, “ 8 Common Thinking Mistakes Our Brains Make Every Day and How to Prevent Them ” by Belle Beth Cooper.

You can also watch this clever music video explaining these and other cognitive biases.

Query $\PageIndex{4}$

Query $\PageIndex{5}$

Query $\PageIndex{6}$

Think It Over

Which type of bias do you recognize in your own decision making processes? How has this bias affected how you’ve made decisions in the past and how can you use your awareness of it to improve your decisions making skills in the future?

anchoring bias: faulty heuristic in which you fixate on a single aspect of a problem to find a solution

availability heuristic: faulty heuristic in which you make a decision based on information readily available to you

confirmation bias: faulty heuristic in which you focus on information that confirms your beliefs

functional fixedness: inability to see an object as useful for any other use other than the one for which it was intended

hindsight bias: belief that the event just experienced was predictable, even though it really wasn’t

mental set: continually using an old solution to a problem without results

representative bias: faulty heuristic in which you stereotype someone or something without a valid basis for your judgment

Licenses and Attributions

CC licensed content, Original

Modification, adaptation, and original content. Provided by : Lumen Learning. License : CC BY: Attribution
Problem Solving. Authored by : OpenStax College. Located at : http://cnx.org/contents/[email protected]:Lk3YnvuC@6/Problem-Solving . License : Public Domain: No Known Copyright . License Terms : Download for free at http://cnx.org/contents/[email protected]
More information on heuristics. Authored by : Dr. Scott Roberts, Dr. Ryan Curtis, Samantha Levy, and Dr. Dylan Selterman. Provided by : University of Maryland. Located at : http://openpsyc.blogspot.com/2014/07/heuristics.html . Project : OpenPSYC. License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike

Identifying Barriers to Problem-Solving in Psychology

Problem-solving is a key aspect of psychology, essential for understanding and overcoming challenges in our daily lives. There are common barriers that can hinder our ability to effectively solve problems. From mental blocks to confirmation bias, these obstacles can impede our progress.

In this article, we will explore the various barriers to problem-solving in psychology, as well as strategies to overcome them. By addressing these challenges head-on, we can unlock the benefits of improved problem-solving skills and mental agility.

Identifying and overcoming barriers to problem-solving in psychology can lead to more effective and efficient solutions.
Some common barriers include mental blocks, confirmation bias, and functional fixedness, which can all limit critical thinking and creativity.
Mindfulness techniques, seeking different perspectives, and collaborating with others can help overcome these barriers and lead to more successful problem-solving.
1 What Is Problem-Solving in Psychology?
2 Why Is Problem-Solving Important in Psychology?
3.1 Mental Blocks
3.2 Confirmation Bias
3.3 Functional Fixedness
3.4 Lack of Creativity
3.5 Emotional Barriers
3.6 Cultural Influences
4.1 Divergent Thinking
4.2 Mindfulness Techniques
4.3 Seeking Different Perspectives
4.4 Challenging Assumptions
4.5 Collaborating with Others
5 What Are the Benefits of Overcoming These Barriers?
6 Frequently Asked Questions

What Is Problem-Solving in Psychology?

Problem-solving in psychology refers to the cognitive processes through which individuals identify and overcome obstacles or challenges to reach a desired goal, drawing on various mental processes and strategies.

In the realm of cognitive psychology, problem-solving is a key area of study that delves into how people use algorithms and heuristics to tackle complex issues. Algorithms are systematic step-by-step procedures that guarantee a solution, whereas heuristics are mental shortcuts or rules of thumb that provide efficient solutions, albeit without certainty. Understanding these mental processes is crucial in exploring how individuals approach different types of problems and make decisions based on their problem-solving strategies.

Why Is Problem-Solving Important in Psychology?

Problem-solving holds significant importance in psychology as it facilitates the discovery of new insights, enhances understanding of complex issues, and fosters effective actions based on informed decisions.

Assumptions play a crucial role in problem-solving processes, influencing how individuals perceive and approach challenges. By challenging these assumptions, individuals can break through mental barriers and explore creative solutions.

Functional fixedness, a cognitive bias where individuals restrict the use of objects to their traditional functions, can hinder problem-solving. Overcoming functional fixedness involves reevaluating the purpose of objects, leading to innovative problem-solving strategies.

Through problem-solving, psychologists uncover underlying patterns in behavior, delve into subconscious motivations, and offer practical interventions to improve mental well-being.

What Are the Common Barriers to Problem-Solving in Psychology?

In psychology, common barriers to problem-solving include mental blocks , confirmation bias , functional fixedness, lack of creativity, emotional barriers, and cultural influences that hinder the application of knowledge and resources to overcome challenges.

Mental blocks refer to the difficulty in generating new ideas or solutions due to preconceived notions or past experiences. Confirmation bias, on the other hand, is the tendency to search for, interpret, or prioritize information that confirms existing beliefs or hypotheses, while disregarding opposing evidence.

Functional fixedness limits problem-solving by constraining individuals to view objects or concepts in their traditional uses, inhibiting creative approaches. Lack of creativity impedes the ability to think outside the box and consider unconventional solutions.

Emotional barriers such as fear, stress, or anxiety can halt progress by clouding judgment and hindering clear decision-making. Cultural influences may introduce unique perspectives or expectations that clash with effective problem-solving strategies, complicating the resolution process.

Mental Blocks

Mental blocks in problem-solving occur when individuals struggle to consider all relevant information, fall into a fixed mental set, or become fixated on irrelevant details, hindering progress and creative solutions.

For instance, irrelevant information can lead to mental blocks by distracting individuals from focusing on the key elements required to solve a problem effectively. This could involve getting caught up in minor details that have no real impact on the overall solution. A fixed mental set, formed by previous experiences or patterns, can limit one’s ability to approach a problem from new perspectives, restricting innovative thinking.

Confirmation Bias

Confirmation bias, a common barrier in problem-solving, leads individuals to seek information that confirms their existing knowledge or assumptions, potentially overlooking contradictory data and hindering objective analysis.

This cognitive bias affects decision-making and problem-solving processes by creating a tendency to favor information that aligns with one’s beliefs, rather than considering all perspectives.

One effective method to mitigate confirmation bias is by actively challenging assumptions through critical thinking.
By questioning the validity of existing beliefs and seeking out diverse viewpoints, individuals can counteract the tendency to only consider information that confirms their preconceptions.
Another strategy is to promote a culture of open-mindedness and encourage constructive debate within teams to foster a more comprehensive evaluation of data.

Functional Fixedness

Functional fixedness restricts problem-solving by limiting individuals to conventional uses of objects, impeding the discovery of innovative solutions and hindering the application of insightful approaches to challenges.

For instance, when faced with a task that requires a candle to be mounted on a wall to provide lighting, someone bound by functional fixedness may struggle to see the potential solution of using the candle wax as an adhesive instead of solely perceiving the candle’s purpose as a light source.

This mental rigidity often leads individuals to overlook unconventional or creative methods, which can stifle their ability to find effective problem-solving strategies.

To combat this cognitive limitation, fostering divergent thinking, encouraging experimentation, and promoting flexibility in approaching tasks can help individuals break free from functional fixedness and unlock their creativity.

Lack of Creativity

A lack of creativity poses a significant barrier to problem-solving, limiting the potential for improvement and hindering flexible thinking required to generate novel solutions and address complex challenges.

When individuals are unable to think outside the box and explore unconventional approaches, they may find themselves stuck in repetitive patterns without breakthroughs.

Flexibility is key to overcoming this hurdle, allowing individuals to adapt their perspectives, pivot when necessary, and consider multiple viewpoints to arrive at innovative solutions.

Encouraging a culture that embraces experimentation, values diverse ideas, and fosters an environment of continuous learning can fuel creativity and push problem-solving capabilities to new heights.

Emotional Barriers

Emotional barriers, such as fear of failure, can impede problem-solving by creating anxiety, reducing risk-taking behavior, and hindering effective collaboration with others, limiting the exploration of innovative solutions.

When individuals are held back by the fear of failure, it often stems from a deep-seated worry about making mistakes or being judged negatively. This fear can lead to hesitation in decision-making processes and reluctance to explore unconventional approaches, ultimately hindering the ability to discover creative solutions. To overcome this obstacle, it is essential to cultivate a positive emotional environment that fosters trust, resilience, and open communication among team members. Encouraging a mindset that embraces failure as a stepping stone to success can enable individuals to take risks, learn from setbacks, and collaborate effectively to overcome challenges.

Cultural Influences

Cultural influences can act as barriers to problem-solving by imposing rigid norms, limiting flexibility in thinking, and hindering effective communication and collaboration among diverse individuals with varying perspectives.

When individuals from different cultural backgrounds come together to solve problems, the ingrained values and beliefs they hold can shape their approaches and methods.

For example, in some cultures, decisiveness and quick decision-making are highly valued, while in others, a consensus-building process is preferred.

Understanding and recognizing these differences is crucial for navigating through the cultural barriers that might arise during collaborative problem-solving.

How Can These Barriers Be Overcome?

These barriers to problem-solving in psychology can be overcome through various strategies such as divergent thinking, mindfulness techniques, seeking different perspectives, challenging assumptions, and collaborating with others to leverage diverse insights and foster critical thinking.

Engaging in divergent thinking , which involves generating multiple solutions or viewpoints for a single issue, can help break away from conventional problem-solving methods. By encouraging a free flow of ideas without immediate judgment, individuals can explore innovative paths that may lead to breakthrough solutions. Actively seeking diverse perspectives from individuals with varied backgrounds, experiences, and expertise can offer fresh insights that challenge existing assumptions and broaden the problem-solving scope. This diversity of viewpoints can spark creativity and unconventional approaches that enhance problem-solving outcomes.

Divergent Thinking

Divergent thinking enhances problem-solving by encouraging creative exploration of multiple solutions, breaking habitual thought patterns, and fostering flexibility in generating innovative ideas to address challenges.

When individuals engage in divergent thinking, they open up their minds to various possibilities and perspectives. Instead of being constrained by conventional norms, a person might ideate freely without limitations. This leads to out-of-the-box solutions that can revolutionize how problems are approached. Divergent thinking sparks creativity by allowing unconventional ideas to surface and flourish.

For example, imagine a team tasked with redesigning a city park. Instead of sticking to traditional layouts, they might brainstorm wild concepts like turning the park into a futuristic playground, a pop-up art gallery space, or a wildlife sanctuary. Such diverse ideas stem from divergent thinking and push boundaries beyond the ordinary.

Mindfulness Techniques

Mindfulness techniques can aid problem-solving by promoting present-moment awareness, reducing cognitive biases, and fostering a habit of continuous learning that enhances adaptability and open-mindedness in addressing challenges.

Engaging in regular mindfulness practices encourages individuals to stay grounded in the current moment, allowing them to detach from preconceived notions and biases that could cloud judgment. By cultivating a non-judgmental attitude towards thoughts and emotions, people develop the capacity to observe situations from a neutral perspective, facilitating clearer decision-making processes. Mindfulness techniques facilitate the development of a growth mindset, where one acknowledges mistakes as opportunities for learning and improvement rather than failures.

Seeking Different Perspectives

Seeking different perspectives in problem-solving involves tapping into diverse resources, engaging in effective communication, and considering alternative viewpoints to broaden understanding and identify innovative solutions to complex issues.

Collaboration among individuals with various backgrounds and experiences can offer fresh insights and approaches to tackling challenges. By fostering an environment where all voices are valued and heard, teams can leverage the collective wisdom and creativity present in diverse perspectives. For example, in the tech industry, companies like Google encourage cross-functional teams to work together, harnessing diverse skill sets to develop groundbreaking technologies.

To incorporate diverse viewpoints, one can implement brainstorming sessions that involve individuals from different departments or disciplines to encourage out-of-the-box thinking. Another effective method is to conduct surveys or focus groups to gather input from a wide range of stakeholders and ensure inclusivity in decision-making processes.

Challenging Assumptions

Challenging assumptions is a key strategy in problem-solving, as it prompts individuals to critically evaluate preconceived notions, gain new insights, and expand their knowledge base to approach challenges from fresh perspectives.

By questioning established beliefs or ways of thinking, individuals open the door to innovative solutions and original perspectives. Stepping outside the boundaries of conventional wisdom enables problem solvers to see beyond limitations and explore uncharted territories. This process not only fosters creativity but also encourages a culture of continuous improvement where learning thrives. Daring to challenge assumptions can unveil hidden opportunities and untapped potential in problem-solving scenarios, leading to breakthroughs and advancements that were previously overlooked.

One effective technique to challenge assumptions is through brainstorming sessions that encourage participants to voice unconventional ideas without judgment.
Additionally, adopting a beginner’s mindset can help in questioning assumptions, as newcomers often bring a fresh perspective unburdened by past biases.

Collaborating with Others

Collaborating with others in problem-solving fosters flexibility, encourages open communication, and leverages collective intelligence to navigate complex challenges, drawing on diverse perspectives and expertise to generate innovative solutions.

Effective collaboration enables individuals to combine strengths and talents, pooling resources to tackle problems that may seem insurmountable when approached individually. By working together, team members can break down barriers and silos that often hinder progress, leading to more efficient problem-solving processes and better outcomes.

Collaboration also promotes a sense of shared purpose and increases overall engagement, as team members feel valued and enableed to contribute their unique perspectives. To foster successful collaboration, it is crucial to establish clear goals, roles, and communication channels, ensuring that everyone is aligned towards a common objective.

What Are the Benefits of Overcoming These Barriers?

Overcoming the barriers to problem-solving in psychology leads to significant benefits such as improved critical thinking skills, enhanced knowledge acquisition, and the ability to address complex issues with greater creativity and adaptability.

By mastering the art of problem-solving, individuals in the field of psychology can also cultivate resilience and perseverance, two essential traits that contribute to personal growth and success.

When confronting and overcoming cognitive obstacles, individuals develop a deeper understanding of their own cognitive processes and behavioral patterns, enabling them to make informed decisions and overcome challenges more effectively.

Continuous learning and adaptability play a pivotal role in problem-solving, allowing psychologists to stay updated with the latest research, techniques, and methodologies that enhance their problem-solving capabilities.

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How Mental Sets Can Prohibit Problem Solving

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

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.

SuHP / Getty Images

A mental set is a tendency to only see solutions that have worked in the past. This type of fixed thinking can make it difficult to come up with solutions and can impede the problem-solving process. For example, that you are trying to solve a math problem in algebra class. The problem seems similar to ones you have worked on previously, so you approach solving it in the same way. Because of your mental set, you may be unable to see a simpler solution that is unique to this problem.

When we are solving problems, we tend to fall back on solutions that have worked in the past. In many cases, this is a useful approach that allows us to quickly come up with answers. In some instances, however, this strategy can make it difficult to think of new ways of solving problems .

Mental sets can lead to rigid thinking and create difficulties in the problem-solving process .

Functional Fixedness

Functional fixedness is a specific type of mental set where people are only able to see solutions that involve using objects in their normal or expected manner. Mental sets are definitely useful at times. By using strategies that have worked before, we are often able to quickly come up with solutions. This can save time and, in many cases, the approach does yield a correct solution.

While in many cases it is beneficial to use our past experiences to solve issues we face, it can also make it difficult to see novel or creative ways of fixing current problems. For example, imagine your vacuum cleaner has stopped working. When it has stopped working in the past, a broken belt was the culprit. Since past experience has taught you the belt is a common issue, you immediately replace the belt again. But, this time the vacuum continues to malfunction.

However, when you ask a friend to come to take a look at the vacuum, they quickly realize one of the hose attachments was not connected, causing the vacuum to lose suction. Because of your mental set, you failed to notice a fairly obvious solution to the problem.

Impact of Past Experiences

In daily life, a mental set may prevent you from solving a relatively minor problem (like figuring out what is wrong with your vacuum cleaner). On a larger scale, mental sets can prevent scientists from discovering answers to real-world problems or make it difficult for a doctor to determine the cause of an illness.

For example, a physician might see a new patient with symptoms similar to certain cases they have seen in the past, so they might diagnose this new patient with the same illness. Because of this mental set, the doctor might overlook symptoms that would actually point to a different illness altogether. Such mental sets can obviously have a dramatic impact on the health of the patient and possible outcomes.

Necka E, Kubik T. How non-experts fail where experts do not: Implications of expertise for resistance to cognitive rigidity . Studia Psychologica . 2012;54(1):3-14.

Valee-Tourangeau F, Euden G, Hearn V. Einstellung defused: Interactivity and mental set . Quarterly Journal of Experimental Psychology . 2011;64(10):1889-1895. doi:10.1080/17470218.2011.605151

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

7.3 Problem Solving

Learning objectives.

By the end of this section, you will be able to:

Describe problem solving strategies
Define algorithm and heuristic
Explain some common roadblocks to effective problem solving and decision making

Problem-Solving Strategies

When you are presented with a problem—whether it is a complex mathematical problem or a broken printer, how do you solve it? Before finding a solution to the problem, the problem must first be clearly identified. After that, one of many problem solving strategies can be applied, hopefully resulting in a solution.

A problem-solving strategy is a plan of action used to find a solution. Different strategies have different action plans associated with them ( Table 7.2 ). For example, a well-known strategy is trial and error . The old adage, “If at first you don’t succeed, try, try again” describes trial and error. In terms of your broken printer, you could try checking the ink levels, and if that doesn’t work, you could check to make sure the paper tray isn’t jammed. Or maybe the printer isn’t actually connected to your laptop. When using trial and error, you would continue to try different solutions until you solved your problem. Although trial and error is not typically one of the most time-efficient strategies, it is a commonly used one.

When one is faced with too much information
When the time to make a decision is limited
When the decision to be made is unimportant
When there is access to very little information to use in making the decision
When an appropriate heuristic happens to come to mind in the same moment

Everyday Connection

Solving puzzles.

Problem-solving abilities can improve with practice. Many people challenge themselves every day with puzzles and other mental exercises to sharpen their problem-solving skills. Sudoku puzzles appear daily in most newspapers. Typically, a sudoku puzzle is a 9×9 grid. The simple sudoku below ( Figure 7.7 ) is a 4×4 grid. To solve the puzzle, fill in the empty boxes with a single digit: 1, 2, 3, or 4. Here are the rules: The numbers must total 10 in each bolded box, each row, and each column; however, each digit can only appear once in a bolded box, row, and column. Time yourself as you solve this puzzle and compare your time with a classmate.

Here is another popular type of puzzle ( Figure 7.8 ) that challenges your spatial reasoning skills. Connect all nine dots with four connecting straight lines without lifting your pencil from the paper:

Take a look at the “Puzzling Scales” logic puzzle below ( Figure 7.9 ). Sam Loyd, a well-known puzzle master, created and refined countless puzzles throughout his lifetime (Cyclopedia of Puzzles, n.d.).

Pitfalls to Problem Solving

Not all problems are successfully solved, however. What challenges stop us from successfully solving a problem? Imagine a person in a room that has four doorways. One doorway that has always been open in the past is now locked. The person, accustomed to exiting the room by that particular doorway, keeps trying to get out through the same doorway even though the other three doorways are open. The person is stuck—but they just need to go to another doorway, instead of trying to get out through the locked doorway. A mental set is where you persist in approaching a problem in a way that has worked in the past but is clearly not working now.

Functional fixedness is a type of mental set where you cannot perceive an object being used for something other than what it was designed for. Duncker (1945) conducted foundational research on functional fixedness. He created an experiment in which participants were given a candle, a book of matches, and a box of thumbtacks. They were instructed to use those items to attach the candle to the wall so that it did not drip wax onto the table below. Participants had to use functional fixedness to overcome the problem ( Figure 7.10 ). During the Apollo 13 mission to the moon, NASA engineers at Mission Control had to overcome functional fixedness to save the lives of the astronauts aboard the spacecraft. An explosion in a module of the spacecraft damaged multiple systems. The astronauts were in danger of being poisoned by rising levels of carbon dioxide because of problems with the carbon dioxide filters. The engineers found a way for the astronauts to use spare plastic bags, tape, and air hoses to create a makeshift air filter, which saved the lives of the astronauts.

Link to Learning

Check out this Apollo 13 scene about NASA engineers overcoming functional fixedness to learn more.

Finally, the availability heuristic is a heuristic in which you make a decision based on an example, information, or recent experience that is that readily available to you, even though it may not be the best example to inform your decision . Biases tend to “preserve that which is already established—to maintain our preexisting knowledge, beliefs, attitudes, and hypotheses” (Aronson, 1995; Kahneman, 2011). These biases are summarized in Table 7.3 .

Watch this teacher-made music video about cognitive biases to learn more.

Were you able to determine how many marbles are needed to balance the scales in Figure 7.9 ? You need nine. Were you able to solve the problems in Figure 7.7 and Figure 7.8 ? Here are the answers ( Figure 7.11 ).

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Want to cite, share, or modify this book? This book uses the Creative Commons Attribution License and you must attribute OpenStax.

Access for free at https://openstax.org/books/psychology-2e/pages/1-introduction

Authors: Rose M. Spielman, William J. Jenkins, Marilyn D. Lovett
Publisher/website: OpenStax
Book title: Psychology 2e
Publication date: Apr 22, 2020
Location: Houston, Texas
Book URL: https://openstax.org/books/psychology-2e/pages/1-introduction
Section URL: https://openstax.org/books/psychology-2e/pages/7-3-problem-solving

© Jan 6, 2024 OpenStax. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution License . The OpenStax name, OpenStax logo, OpenStax book covers, OpenStax CNX name, and OpenStax CNX logo are not subject to the Creative Commons license and may not be reproduced without the prior and express written consent of Rice University.

5 Barriers to Critical Thinking

What holds us back from thinking critically in day-to-day situations.

Posted January 18, 2019 | Reviewed by Davia Sills

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Quite often, discussions of Critical Thinking (CT) revolve around tips for what you or your students should be doing to enhance CT ability. However, it seems that there’s substantially less discussion of what you shouldn’t be doing—that is, barriers to CT.

About a year ago, I posted "5 Tips for Critical Thinking" to this blog, and after thinking about it in terms of what not to do , along with more modern conceptualizations of CT (see Dwyer, 2017), I’ve compiled a list of five major barriers to CT. Of course, these are not the only barriers to CT; rather, they are five that may have the most impact on how one applies CT.

1. Trusting Your Gut

Trust your gut is a piece of advice often thrown around in the context of being in doubt. The concept of using intuitive judgment is actually the last thing you want to be doing if critical thinking is your goal. In the past, intuitive judgment has been described as "the absence of analysis" (Hamm, 1988); and automatic cognitive processing—which generally lacks effort, intention, awareness, or voluntary control—is usually experienced as perceptions or feelings (Kahneman, 2011; Lieberman, 2003).

Given that intuitive judgment operates automatically and cannot be voluntarily "turned off," associated errors and unsupported biases are difficult to prevent, largely because reflective judgment has not been consulted. Even when errors appear obvious in hindsight, they can only be prevented through the careful, self-regulated monitoring and control afforded by reflective judgment. Such errors and flawed reasoning include cognitive biases and logical fallacies .

Going with your gut—experienced as perceptions or feelings—generally leads the thinker to favor perspectives consistent with their own personal biases and experiences or those of their group.

2. Lack of Knowledge

CT skills are key components of what CT is, and in order to conduct it, one must know how to use these skills. Not knowing the skills of CT—analysis, evaluation, and inference (i.e., what they are or how to use them)—is, of course, a major barrier to its application. However, consideration of a lack of knowledge does not end with the knowledge of CT skills.

Let’s say you know what analysis, evaluation, and inference are, as well as how to apply them. The question then becomes: Are you knowledgeable in the topic area you have been asked to apply the CT? If not, intellectual honesty and reflective judgment should be engaged to allow you to consider the nature, limits, and certainty of what knowledge you do have, so that you can evaluate what is required of you to gain the knowledge necessary to make a critically thought-out judgment.

However, the barrier here may not necessarily be a lack of topic knowledge, but perhaps rather believing that you have the requisite knowledge to make a critically thought-out judgment when this is not the case or lacking the willingness to gain additional, relevant topic knowledge.

3. Lack of Willingness

In addition to skills, disposition towards thinking is also key to CT. Disposition towards thinking refers to the extent to which an individual is willing or inclined to perform a given thinking skill, and is essential for understanding how we think and how we can make our thinking better, in both academic settings and everyday circumstances (Norris, 1992; Siegel, 1999; Valenzuela, Nieto, & Saiz, 2011; Dwyer, Hogan & Stewart, 2014).

Dispositions can’t be taught, per se, but they do play a large role in determining whether or not CT will be performed. Simply, it doesn’t matter how skilled one is at analysis, evaluation, and inference—if they’re not willing to think critically, CT is not likely to occur.

4. Misunderstanding of Truth

Truth-seeking is one such disposition towards thinking, which refers to a desire for knowledge; to seek and offer both reasons and objections in an effort to inform and to be well-informed; a willingness to challenge popular beliefs and social norms by asking questions (of oneself and others); to be honest and objective about pursuing the truth, even if the findings do not support one’s self-interest or pre-conceived beliefs or opinions; and to change one’s mind about an idea as a result of the desire for truth (Dwyer, 2017).

Though this is something for which many of us strive or even just assume we do, the truth is that we all succumb to unwarranted assumptions from time to time: that is, beliefs presumed to be true without adequate justification. For example, we might make a judgment based on an unsubstantiated stereotype or a commonsense/belief statement that has no empirical evidence to justify it. When using CT, it’s important to distinguish facts from beliefs and, also, to dig a little deeper by evaluating "facts" with respect to how much empirical support they have to validate them as fact (see " The Dirtiest Word in Critical Thinking: 'Proof' and its Burden ").

Furthermore, sometimes the truth doesn’t suit people, and so, they might choose to ignore it or try and manipulate knowledge or understanding to accommodate their bias . For example, some people may engage in wishful thinking , in which they believe something is true because they wish it to be; some might engage in relativistic thinking , in which, for them, the truth is subjective or just a matter of opinion.

5. Closed-mindedness

In one of my previous posts, I lay out " 5 Tips for Critical Thinking "—one of which is to play Devil’s Advocate , which refers to the "consideration of alternatives." There’s always more than one way to do or think about something—why not engage such consideration?

The willingness to play Devil’s Advocate implies a sensibility consistent with open-mindedness (i.e., an inclination to be cognitively flexible and avoid rigidity in thinking; to tolerate divergent or conflicting views and treat all viewpoints alike, prior to subsequent analysis and evaluation; to detach from one’s own beliefs and consider, seriously, points of view other than one’s own without bias or self-interest; to be open to feedback by accepting positive feedback, and to not reject criticism or constructive feedback without thoughtful consideration; to amend existing knowledge in light of new ideas and experiences; and to explore such new, alternative, or "unusual" ideas).

At the opposite end of the spectrum, closed-mindedness is a significant barrier to CT. By this stage, you have probably identified the inherent nature of bias in our thinking. The first step of CT is always going to be to evaluate this bias. However, one’s bias may be so strong that it leads them to become closed-minded and renders them unwilling to consider any other perspectives.

Another way in which someone might be closed-minded is through having properly researched and critically thought about a topic and then deciding that this perspective will never change, as if their knowledge will never need to adapt. However, critical thinkers know that knowledge can change and adapt. An example I’ve used in the past is quite relevant here—growing up, I was taught that there were nine planets in our solar system; however, based on further research, our knowledge of planets has been amended to now only consider eight of those as planets.

Being open-minded is a valuable disposition, but so is skepticism (i.e., the inclination to challenge ideas; to withhold judgment before engaging all the evidence or when the evidence and reasons are insufficient; to take a position and be able to change position when the evidence and reasons are sufficient; and to look at findings from various perspectives).

However, one can be both open-minded and skeptical. It is closed-mindedness that is the barrier to CT, so please note that closed-mindedness and skepticism are distinct dispositions.

Dwyer, C.P. (2017). Critical thinking: Conceptual perspectives and practical guidelines. UK: Cambridge University Press.

Dwyer, C.P., Hogan, M.J. & Stewart, I. (2014). An integrated critical thinking framework for the 21st century. Thinking Skills & Creativity, 12, 43-52.

Hamm, R. M. (1988). Clinical intuition and clinical analysis: expertise and the cognitive continuum. In J. Dowie & A. Elstein (Eds.), Professional judgment: A reader in clinical decision making, 78–105. Cambridge: Cambridge University Press.

Kahneman, D. (2011). Thinking fast and slow. Penguin: Great Britain.

Lieberman, M. D. (2003). Reflexive and reflective judgment processes: A social cognitive neuroscience approach. Social Judgments: Implicit and Explicit Processes, 5, 44–67.

Norris, S. P. (Ed.). (1992). The generalizability of critical thinking: Multiple perspectives on an educational ideal. New York: Teachers College Press.

Siegel, H. (1999). What (good) are thinking dispositions? Educational Theory, 49, 2, 207–221.

Valenzuela, J., Nieto, A. M., & Saiz, C. (2011). Critical thinking motivational scale: A contribution to the study of relationship between critical thinking and motivation. Journal of Research in Educational Psychology, 9, 2, 823–848.

Christopher Dwyer, Ph.D., is a lecturer at the Technological University of the Shannon in Athlone, Ireland.

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Barriers to Effective Problem Solving

Mcat psychology - chapter 2- section 4 - cognition - intelligence & problem-solving.

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Barriers to Effective Problem Solving – MCAT Psychology

Sample MCAT Question - Barriers to Effective Problem Solving

Which barrier to effective problem solving involves thinking that it is necessary to use all information provided to solve a problem?

a) Irrelevant Information

b) Functional Fixedness

c) Mental Set

d) Unnecessary Constraints

A is correct. The irrelevant information barrier to effective problem solving is the false notion that all information included with the problem is needed to solve the problem. Answer choice B is incorrect because functional fixedness is the tendency to perceive an object only in terms of its most common use. Answer choice C is incorrect because mental set occurs when people continually try to use a problem solving strategy that worked in the past, but may not necessarily be the correct method for the current problem. Answer choice D is incorrect because unnecessary constraints are when individuals assume there are rules that do not exist.

Conciousness-Altering Drugs

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Barriers to Effective Problem Solving for the MCAT

In the MCAT post, we explore four barriers to effective problem solving that are important to know for the Psychological, Social, and Biological Foundations of Behavior section of the MCAT. These four barriers are irrelevant information, functional fixedness, mental set, and unnecessary constraints.

Irrelevant Information

Irrelevant information is information included in a problem that is not related to or required to solve the problem. Irrelevant information is an issue because people generally believe that they need to use all the information provided in a problem to solve it. However, this is often not the case. To solve problems efficiently, it is necessary to determine what information is relevant.

Consider the problem: 30% of residents in Boston have unlisted telephone numbers. If you randomly select 150 names from the Boston telephone directory, how many of these people would you expect to have unlisted phone numbers? In this problem, the information provided is that 30% of residents have unlisted phone numbers, and 150 names are selected from the Boston telephone book. It can be tempting to think that the answer is just 30% of 150 people (45 people). However, this is not correct. The answer to this problem is actually zero because names taken from a telephone directory must have listed numbers. The 30% is a distractor in the problem and is not required to answer the question.

Functional Fixedness

Functional fixedness is the tendency to perceive objects only in terms of their most common uses. For example, in the String Problem depicted in Figure 1 , two strings hang from a ceiling and need to be tied together. However, they are too far apart to allow a person to grab one and walk to the other. On the table is a pair of pliers. Most people can’t determine how to utilize the pliers to tie the two strings together because they think of the pliers as a tool to hold, bend, or compress objects.

The String Problem is an example of arrangement problem solving - MCAT Psychology

However, in the solution depicted in Figure 2, it can be seen that there are other ways to use pliers. The pliers can be connected to the string to make a pendulum and swung back and forth to allow someone holding one string to grab the other. By surpassing functional fixedness and being able to utilize objects in less common ways, problem-solving can be made easier.

The solution to the string problem as an example of arrangement problem solving for the MCAT

A mental set is the collection of problem-solving strategies that have worked for a person in the past. Take the Water Jar Problem as an example, where there are three empty water jars that can hold different volumes of fluids. Jar A can hold 37 cups of water, Jar B can hold 12 cups of water, and Jar C can hold five cups of water. The problem’s task involves filling and emptying the jars as many times as necessary to measure out 10 cups of water. The solution is to fill up Jar A with 37 cups of water. This is poured into Jar B, which removes 12 cups of water and leaves 25 cups of water in Jar A. Jar A is then poured into Jar C to remove five cups of water. This is done three times to remove 15 cups of water, leaving 10 cups of water in Jar A.

In trial two of the Water Jar Problem, Jar A can hold 43 cups of water, Jar B can hold nine cups of water, and Jar C can hold four cups of water. The goal is to measure out 22 cups of water. When presented with this problem, most people want to try the same solution that worked for trial one of the problems, allowing them to solve trial two faster. If Jar A is filled with 43 cups of water and poured into Jar B, nine cups of water will be removed, leaving 34 cups in Jar A. If Jar A is poured into Jar C three times, it will get rid of 12 total cups of water, resulting in 22 cups in Jar A.

Trial three of this problem is solved in the same way, and people solve trial three even quicker than the first two trials. Jar A holds 24 cups of water, Jar B holds four cups of water, and Jar C holds three cups of water. The goal is to measure out 11 cups of water. Jar A is filled with 24 cups of water and poured into Jar B to get rid of four cups of water. The remaining 20 cups of water in Jar A is poured into Jar C three times to get rid of nine total cups of water, resulting in the final goal of 11 cups of water.

In trial four of this problem, Jar A can hold 35 cups of water, Jar B can hold 13 cups of water, and Jar C four cups of water with the final goal of having nine cups of water. This is the easiest of the trials. However, after solving the first three trials, most people have a long, difficult time solving this one. This is because they attempt to solve it with the same strategy that worked for the last three trials, filling Jar A with 35 cups of water, pouring it into Jar B to yield 22 cups of water, and then pouring it into Jar C three times. However, this leaves Jar A with 10 cups of water, which is not the goal volume. The answer is simple and involves filling Jar B with 13 cups of water and pouring four cups out into Jar C to end with nine cups of water. Despite this being the simplest trial, mental set causes many to struggle to solve it.

Unnecessary Constraints

An unnecessary constraint is another barrier to effective problem solving and occurs when individuals assume that there are rules that don’t actually exist. For example, in the problem depicted in Figure 1, nine circles need to be connected using four lines. The unnecessary constraint that most people believe is that there is a barrier around the circles that can’t be crossed. With this unnecessary constraint, drawing four lines to connect the nine circles is impossible. However, without this unnecessary constraint, there are several possible solutions, two of which are depicted, demonstrating how problem-solving can be made easier by removing unnecessary constraints.

To surpass barriers to effective problem solving, such as mental set and unnecessary constraints, it is necessary to think outside of the box and not be restricted to past strategies or constraints that don’t actually exist.

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Barriers To Problem-Solving

Problems are inevitable at work. They could be big problems. Or they could be small problems. Either way, the trick…

Problems are inevitable at work. They could be big problems. Or they could be small problems.

Either way, the trick is to develop strong problem-solving skills. But it isn’t always easy to find a solution to a problem. You often face many unexpected obstacles on the way.

Imagine a client rejects a proposal for a marketing pitch you and your team worked hard on. In such a situation, you might come up with a quick and easy alternative to retain the client, but in the scramble, you may forget to assess its long-term potential.

Such barriers to problem-solving abound at the workplace. You need to be prepared for potential pitfalls that could trip you up. ( Phentermine )

Effective problem-solving in such situations is a handy skill that’ll help you navigate your way through the professional landscape.

You will find some useful tips on how to deal with some common barriers to effective problem-solving in Harappa Education’s Defining Problems course. The course introduces ways in which you can define, identify and deal with problems in a solution-oriented manner.

Contrary to popular belief, problem-solving takes time and patience. This is something we tend to overlook because quick solutions are often rewarded at the workplace where everyone is busy and pressed for time.

When you stop for a moment to think about what went wrong, you’re more likely to come up with a lasting solution. Here are the most common barriers to problem-solving and decision-making in the workplace:

Misdiagnosis

Common barriers to problem-solving include an incorrect diagnosis of the problem. This could be due to preconceived ideas, biases, or judgments. Defining a problem is the hardest step in the process of problem-solving because this is the foundation on which your entire strategy is built. If you’re not careful, you may end up spending all your time, resources and effort on the wrong problem and, eventually, the wrong solution.

Communication Barriers

Thinking that you know better than anyone else or miscommunicating the problem is another one of the barriers to problem-solving. Everyone defines or understands the problem differently. It’s important to communicate with your teammates so that everyone’s on the same page. If you’re unclear about something, acknowledge your limited understanding of the problem. This will save you both time and energy.

Solution Bias

Another common challenge is a solution bias or thinking that one solution is universal and can be applied to multiple problems. If you catch yourself thinking about a problem that you solved in a particular way, you’re already going in the wrong direction. It’s more important for you to focus on the problem at hand than to force-fit a solution from the past that, in all probability, won’t work.

Cognitive Bias

Barriers to problem solving psychology often involve a cognitive bias or the tendency to jump to conclusions. To find a solution as quickly as possible, you might end up with a solution that’s irrelevant to the situation. You have to learn to listen before making a judgment. If you miss a step, for instance, there’s a chance that you’ll end up in an even bigger mess.

Lack Of Empathy

Every problem is in one way or another associated with human emotions, abilities or feelings. If you’re not able to recognize the people who are affected by the problem, you won’t be able to come up with a solution that serves everyone.

How To Circumvent Barriers To Problem-Solving

Some of the ways in which you can tackle common barriers to problem-solving are:

Be open to suggestions and different points of view
Accept that you may not know everything
Be patient and take your time before coming to a conclusion
Approach the owner of the problem and ask the right questions
Avoid shortcuts and ‘cut and dry’ formulas

Navigating your way through the complexities of work-life can be daunting, but it’s not impossible. Harappa’s Defining Problems course equips you with the tools you need to recognize a problem for what it is. Learn more about barriers to effective problem-solving and how to identify or define problems to become a skilled problem-solver. With frameworks such as the Problem Definition Framework, you’ll be able to define problems effectively and find constructive solutions.

Explore topics such as Problem Solving & the 5 Whys Analysis from our Harappa Diaries blog section and develop your skills.

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Worry Impairs the Problem-Solving Process: Results from an Experimental Study

Sandra j. llera.

a Department of Psychology, Towson University, 8000 York Road, Towson, MD 21252.

Michelle G. Newman

b Department of Psychology, The Pennsylvania State University, 140 Moore Building, University Park, PA 16801.

Associated Data

Introduction:.

Many individuals believe that worry helps solve real-life problems. Some researchers also purport that nonpathological worry can aid problem solving. However, this is in contrast to evidence that worry impairs cognitive functioning.

This was the first study to empirically test the effects of a laboratory-based worry induction on problem-solving abilities.

Both high ( n = 96) and low ( n = 89) trait worriers described a current problem in their lives. They were then randomly assigned to contemplate their problem in a worrisome ( n = 60) or objective ( n = 63) manner or to engage in a diaphragmatic breathing task ( n = 62). All participants subsequently generated solutions and then selected their most effective solution. Next, they rated their confidence in the solution’s effectiveness, their likelihood to implement the solution, and their current anxiety/worry. Experimenters uninformed of condition also rated solution effectiveness.

The worry induction led to lower reported confidence in solutions for high trait worry participants, and lower experimenter-rated effectiveness of solutions for all participants, relative to objective thinking. Further, state worry predicted less reported intention to implement solutions, while controlling for trait worry. Finally, worrying about the problem led to more elevated worry and anxiety after solving the problem compared to the other two conditions.

CONCLUSIONS:

Overall, the worry induction impaired problem solving on multiple levels, and this was true for both high and low trait worriers.

Worry is the defining feature of generalized anxiety disorder (GAD; American Psychiatric Association, 2013 ), but it is also a common experience for most individuals. Though many report the belief that worry has benefits for coping with potential threats ( Borkovec & Roemer, 1995 ; Hebert, Dugas, Tulloch, & Holowka, 2014 ), a wide literature documents its negative impact on cognitive, emotional, and behavioral levels. Despite being extensively researched, the effects of worry on some aspects of cognitive functioning and behavioral motivation remain understudied and require further exploration.

Several theories suggest that worry negatively affects cognitive functioning. The Attentional Control Theory ( Eysenck, Derakshan, Santos, & Calvo, 2007 ), posits that worry demands attentional resources that could be allocated to other cognitive capacities and thus creates cognitive impairment. Similarly, Affective Neuroscience theories propose that worry increases cognitive load and interferes with the capacity to ignore task-irrelevant matters ( Beaudreau, MacKay-Brandt, & Reynolds, 2013 ). These theories further posit that because worrisome thoughts are attentionally demanding, additional resources are required to inhibit worry in order to focus attention elsewhere. Thus, worry may interfere with tasks that compete for executive functioning resources.

This perspective has garnered empirical support. High trait worriers performed slower than controls on a number of cognitive and decision-making tasks, in both clinical ( LaFreniere & Newman, 2019 ; Stefanopoulou, Hirsch, Hayes, Adlam, & Coker, 2014 ) and non-clinical ( Tallis, Eysenck, & Mathews, 1991 ) samples. In a meta-analysis of 94 studies, recurrent negative thinking, including trait worry, was associated with impaired ability to discard irrelevant information from working memory ( Zetsche, Bürkner, & Schulze, 2018 ). Additionally, impaired cognitive functioning, such as difficulty concentrating, slowed learning, and delayed decision-making, has been associated with GAD status in both undergraduate ( LaFreniere & Newman, 2019 ; Pawluk & Koerner, 2013 ) and community GAD samples ( Hallion, Steinman, & Kusmierski, 2018 ). Similar to trait-level worry, experimentally manipulated state worry has also been found to reduce working memory ( Rapee, 1993 ; Trezise & Reeve, 2016 ) and attentional control ( Hayes, Hirsch, & Mathews, 2008 ; Stefanopoulou et al., 2014 ). Further, efforts to inhibit state worry depleted working memory and performance on cognitive tasks ( Hallion, Ruscio, & Jha, 2014 ). Thus, both trait and state worry independently have been associated with cognitive impairment.

Similar to evidence of the association between trait/state worry and impaired cognitive functioning, there have been questions as to whether worry impacts problem-solving abilities. D’Zurilla and Goldfried (1971) suggest that effective problem-solving requires five major components. These include: 1) problem orientation (i.e., confidence in and perceived control over the problem-solving process), 2) problem definition and goal identification, 3) generating solutions, 4) decision making, and 5) implementation/verification. Accordingly, impairment at any one of these levels would hinder one’s ability to resolve problems.

On the one hand, many individuals, especially those with GAD symptoms, believe that worry is helpful when solving problems. In fact, such beliefs predicted worry severity levels ( Hebert et al., 2014 ), and were able to distinguish those with GAD from controls ( Borkovec & Roemer, 1995 ). Further, beliefs that worry was helpful in the face of problems, or that persistent thinking was required in order to find the best solution, both predicted trait worry levels ( Kelly & Kelly, 2007 ; Sugiura, 2007 ). In fact, when tested on their ability to solve hypothetical problems in a laboratory setting, anxious participants performed no differently than controls ( Anderson, Goddard, & Powell, 2009 ), and in an unselected student sample these abilities were uncorrelated with trait worry ( Davey, 1994 ).

On the other hand, however, there is reason to believe that the act of worrying and/or trait worry might be associated with impairment in the real world. Negative effects of worry on problem-solving could happen in several ways. Worrying about a problem could increase cognitive load ( Beaudreau, MacKay-Brandt, & Reynolds, 2013 ), interfering with one’s ability to focus on effective solution generation. This could induce lower confidence in one’s abilities to generate effective solutions, leading individuals to stall or avoid decision-making ( D’Zurilla & Goldfried, 1971 ) or to prematurely dismiss possible solutions as likely to be ineffective. Additionally, worry could provoke repetitive rehearsal of the problem and/or focus on potential negative outcomes ( Mathews, 1990 ), thereby interfering with effective solution generation and implementation. Trait worry could also have negative effects. These could include difficulty tolerating the uncertainty inherent in the problem-solving process ( Dugas, Gagnon, Ladouceur, & Freeston, 1998 ), which might be linked to the higher “evidence requirements” seen in chronic worriers when making decisions ( Tallis et al., 1991 ). This, in addition to heightened attentional bias toward threat ( Goodwin, Yiend and Hirsch, 2017 ), could serve to prolong indecision in the face of real-life problems while the worrier attempts to gather more information. Finally, the Contrast Avoidance model of GAD ( Newman & Llera, 2011 ) would suggest that for chronic worriers, reluctance to implement solutions could be due to a fear of getting one’s hopes up only to be confronted with failure (i.e., emotional contrast). In fact, it is possible that multiple factors could work together to impair problem-solving abilities.

In support of impairment related to chronic worry, Davey, Hampton, Farrell, and Davidson (1992) identified a link between harboring a negative attitude toward problems, termed negative problem orientation (NPO), and high trait worry. Since then, NPO has been linked with anxiety and trait worry in both clinical ( Dugas et al., 1998 ; Fergus, Valentiner, Wu, & McGrath, 2015 ; Ladouceur, Blais, Freeston, & Dugas, 1998 ) and non-clinical samples ( Anderson et al., 2009 ; Robichaud & Dugas, 2005 ). Notably, NPO was more robustly associated with trait worry over other anxiety, mood, and obsessive symptoms in a mixed-clinical sample ( Fergus et al., 2015 ). Additional studies found trait worry to be associated with impairment in other aspects of the problem-solving process, such as skills and/or knowledge base. For example, Borkovec (1985) observed that whereas chronic worriers were very good at defining their problems and identifying possible negative outcomes, they often had difficulty implementing solutions. Further, when assessing real-life problem solving based on daily diary and recall data, a mixed anxious-depressed group demonstrated fewer functional cognitions and behaviors, and less effective solutions, than did controls ( Anderson et al., 2009 ).

Although such research on the nature of chronic worriers tends to converge, the extent to which the act of worrying itself impairs problem solving represents a point of contention within the field. Some researchers have argued that worry interferes with successful problem resolution across the board, whereas others contend that this may only apply to pathological worriers (i.e., those for whom worry is excessive and uncontrollable). Mathews (1990) adopted the first stance, arguing that although worry may begin as attempted problem solving, it predominantly leads to the cognitive rehearsal of danger for everyone. Taking the second stance, Davey and colleagues ( Davey, 1994 ; Davey et al., 1992 ) proposed that worry may actually enhance problem solving for many individuals, but that this process can become thwarted for those with high levels of trait worry. The latter argument was based in part on evidence that trait worry was associated with some active coping styles (e.g., information seeking) when controlling for trait anxiety in unselected student samples ( Davey et al., 1992 ). Therefore, Davey and colleagues concluded that for some individuals worry might be an adaptive or constructive approach when confronting a problem.

Nonetheless, an abundance of data shows that worry increases state negative affect and arousal for all individuals (see Newman & Llera, 2011 ; Newman et al., 2019 ; Ottaviani et al., 2016 ), which itself may impact the problem-solving process. For instance, a negative mood induction increased perseveration and catastrophizing on a high-responsibility task ( Startup & Davey, 2003 ), which could have negative implications for problem solving. Furthermore, daily diary studies have found that the intensity of state worry was associated with more anticipation of negative outcomes, greater negative evaluation of solutions to problems, more self-blame, and lower rates of solution selection during worry episodes, in samples including both high and low trait worriers ( Szabó & Lovibond, 2002 , 2006 ). Additionally, state levels of anxious thinking, including worry, were associated with lower problem-solving effectiveness in a community GAD sample ( Pawluk, Koerner, Tallon, & Antony, 2017 ).

In summary, although there is strong evidence to suggest that worry is associated with impairment in problem solving, none of the studies reviewed above experimentally manipulated worry when testing problem-solving abilities. Therefore, it is impossible to determine the extent to which worry itself causally impacted the problem-solving process, as opposed to other characteristics associated with state or trait worry. Interestingly, depressive rumination (a close conceptual relative to worry) has been shown to impact both mood and the problem-solving process across several studies. For example, experimentally induced rumination (versus distraction) led to lower mood in a non-clinical dysphoric sample, and resulted in generating less effective solutions for hypothetical problems, as well as reduced likelihood of implementing solutions for a personal problem ( Lyubomirsky & Nolen-Hoeksema, 1995 ; Lyubomirsky, Tucker, Caldwell, & Berg, 1999 ). The absence of similar research on the effect of worry represents a critical gap in our understanding of this phenomenon.

In this study, we sought to address this gap by testing the effects of experimentally manipulated worry on problem solving using a sample of individuals with both high and low trait worry. In this way, we were able to test whether inducing state worry would hinder problem solving for all participants, thereby supporting Matthews’ (1990) perspective, or if it would enhance problem-solving in low trait worriers and only become problematic at high trait levels, thus supporting Davey and colleagues’ perspective ( Davey, 1994 ; Davey et al., 1992 ). We chose to observe the effects of worrying about a real-life problem, as opposed to a hypothetical problem, in order to increase external validity. As a comparison condition, we chose the problem definition stage of problem solving as outlined in D’Zurilla and Goldfried (1971) . This allowed us to equalize the amount of time spent contemplating the problem, but to channel thinking into styles typical of a worry episode versus thinking in a more objective, emotionally neutral manner. As an additional control condition, a third group engaged in a diaphragmatic breathing task. Immediately afterward, all groups were instructed to brainstorm solutions to their problem and choose the solution they thought would be most successful. We tested a variety of outcomes related to problem solving, including the number of solutions generated, self-reported and experimenter-rated effectiveness of solutions, as well as participant ratings of intention to implement solutions. Further, we assessed state levels of anxiety and worry following the solution-generation phase, to determine the extent to which participants felt calmer once a solution had been identified.

We hypothesized that relative to objective thinking or diaphragmatic breathing instructions, worrying about a problem would lead to 1) generating fewer solutions during brainstorming, 2) generating less effective solutions (based on both participants’ and judge’s ratings), and 3) lower intention to implement solutions. Further, we hypothesized that 4) worrying would lead to lingering anxiety and worry following solution generation, relative to other conditions. We also hypothesized that these effects would be observed for both high and low trait worriers alike.

Research Design and Method

Overall design.

A 2 (Group: High vs. Low Trait Worry) X 3 (Condition: Worry, Think Objectively, Diaphragmatic Breathing) block design was used to determine the effects of worrying about a problem on various outcomes related to problem-solving.

Participants and Measures

The current study recruited 185 volunteers from psychology courses in a public university. Students received class credit as compensation. Participants were largely young adult (M = 20.06 years, SD = 6.47) females (76.8%), with 57.8% identifying as White, 24.3% African American, 7.6% Asian, 6.2% Hispanic/Latinx, 1% American Indian/Pacific Islander, and 8.6% other (e.g., “mixed race”).

Participants were selected based on their scores on the Penn State Worry Questionnaire (PSWQ; Meyer, Miller, Metzger, & Borkovec, 1990 ), a 16-item self-report measure designed to assess the frequency, intensity, and uncontrollability characteristics of trait worry. The PSWQ demonstrates strong internal consistency (Chronbach’s α = .91; Meyer et al., 1990 ) and retest reliability (.74 – .93; Molina & Borkovec, 1994 ). Internal consistency for the current sample was high (α = .95). Participants also completed the Generalized Anxiety Disorder Questionnaire (GAD-Q-IV; Newman et al., 2002 ) to assess for clinical-level GAD symptoms. The GAD-Q-IV is a 9-item self-report questionnaire based on diagnostic criteria for GAD. It demonstrates strong internal consistency (α = .94) and good retest reliability. A cut-score of 5.7 leads to 83% sensitivity and 89% specificity relative to a structured diagnostic interview ( Newman et al., 2002 ). Internal consistency for the current sample was high (α = .91).

Participants were included in the High Trait Worry group (N = 96) if they scored in the upper range on the PSWQ (≥ 60) during a pre-screen. On the day of testing, the High Trait Worry PSWQ score mean was comparable to that found in GAD patient samples (M = 66.68, SD = 9.47; see Startup & Erickson, 2006 ). The High Trait Worry mean on the GAD-Q-IV was also well above the clinical cut-score (M = 8.58, SD = 2.35). Participants were included in the Low Trait Worry group (N = 89) if they scored in the mid-low range on the PSWQ (≤ 45). On the day of testing, scores in this group were comparable to those of nonanxious samples from other studies (M = 41.02, SD = 11.93; see Startup & Erickson, 2006 ). Further, the Low Trait Worry group scored well below the cut-score on the GAD-Q-IV (M = 3.66, SD = 2.82).

This study was approved by the university IRB. Participants were each tested alone in a private room equipped with a computer. All instructions and tasks were completed using the Qualtrics survey platform (Qualtrics, Provo, UT). Participants first provided informed consent, and then completed demographic questions along with the PSWQ and GAD-Q-IV. Next, they completed baseline state measures, comprised of 4 items: worry , anxiety , relaxation , and mood . They were instructed to rate each item based on how they felt right now . The first 3 items were rated on a scale of 0 ( not at all ) to 100 ( extremely ). Mood was rated from 0 ( very negative ) to 100 ( very positive ).

Participants were next instructed to identify a current, real-life problem; specifically, one that was affecting them right now, and for which they had some control over the outcome. The latter requirement was to assist in identifying a problem for which there were possible solutions, as opposed to an uncontrollable issue (e.g., a loved one’s terminal illness). They were then asked to briefly describe their problem by typing it out on the computer.

Next, participants were randomly assigned to either a Worry (WOR; N = 60) or Think Objectively (T-OBJ; N = 63) task, with the remaining third assigned to a Diaphragmatic Breathing (DB; N = 62) task. The primary distinction between WOR and T-OBJ conditions was that participants either worried or did not worry over their problem. To that end, instructions for the WOR task were based on the definition of worry as negatively valanced cognitive activity focused on a threat, along with consideration of potential negative outcomes (i.e., negative emotional and catastrophic thinking; Borkovec, 1985 ; Borkovec, Robinson, Pruzinsky, & DePree, 1983 ). Those in the WOR task were therefore instructed to worry about their problem, with an emphasis on their concerns along with possible negative outcomes and implications (see supplement for full instructions ). To control for the amount of time spent contemplating the problem, but to do so in a non-emotional, non-catastrophic manner, instructions for the T-OBJ task were based on the problem definition stage of problem solving ( D’Zurilla & Goldfried, 1971 ). Participants in the T-OBJ task were instructed to attempt to focus on their problem in a more objective, emotionally neutral manner, such as by breaking it down into smaller components and coming up with ultimate goals. If they found themselves focusing on negative thoughts, participants were instructed to refocus their attention back on the problem itself.

After receiving these instructions, participants in the WOR and T-OBJ conditions were asked to think about their problem for 2 minutes in the specified manner. Those in the DB task were given instructions to engage in diaphragmatic breathing for 2 minutes.

Following this task, and to determine whether the manipulations had their intended effects, all participants again completed state measures of worry , anxiety , relaxation , and mood . This was to ensure that conditions led to three distinct groups: one that had engaged in emotional/catastrophic thinking (WOR), one that had engaged in non-emotional, non-catastrophic thinking (T-OBJ), and one that had engaged in a relaxation-inducing breathing task (DB). As such, distinctions on state levels of worry , anxiety , relaxation , and mood between conditions served as compliance checks for adherence to the manipulations.

Immediately afterward, all participants were asked to generate as many solutions to their problem as they could for 2 minutes, representing the brainstorming stage of problem solving. Solutions were typed out on the computer. Next, they were instructed to reflect on these ideas and choose their “best, most effective” solution, representing the decision-making stage. Once finished, they ranked how confident they felt that this solution would be effective, as well as how likely they were to actually carry it out, on a scale of 0 ( not at all confident/likely ) to 100 ( very confident/likely ). They then provided final ratings of current state worry and anxiety and were debriefed about the study.

Once data collection was complete, a judge uninformed of condition rated participants’ self-identified “best” solutions for their effectiveness on a 7-point scale (1 = not at all effective , to 7 = extremely effective ), identical to that used in similar studies ( Lyubomirsky & Nolen-Hoeksema, 1995 ; Lyubomirsky et al., 1999 ). To determine this score, they rated the likelihood that participants’ solutions would lead to successful resolution of the problem (i.e., maximize positive consequences and minimize negative ones, and not create additional problems; D’Zurilla & Goldfried, 1971 ). For example, if participants listed a solution that would likely improve or resolve the situation (e.g., behavior that would directly enhance their performance in a class, etc.), that was rated as more effective. If their solution was unlikely to improve or resolve the situation, or could potentially exacerbate the issue (e.g., distraction from or avoidance of the problem, etc.), it would be rated as less effective. A second independent judge who was also uninformed of condition rated a random selection of 25% of responses, with evidence of sufficient interrater reliability (ICC = .7). (See Supplemental Materials for an overview of the process used to ensure reliability of judges’ ratings.)

Data Analytic Plan

We first tested whether there were any differences at baseline on measures of state worry , anxiety , relaxation , and mood , using a 2 (Group: High/Low Trait Worry) X 3 (Condition: WOR, T-OBJ, DB) MANOVA. Next, to test that WOR, T-OBJ, and DB tasks had the intended effects, we ran a similar MANOVA but with ratings of state measures of worry , anxiety , relaxation , and mood immediately following the induction as manipulation checks.

To test the 4 main hypotheses, we ran a series of factorial ANOVAs, using Group and Condition as predictors. Outcome variables included 1) the number of solutions participants generated during the brainstorming phase, 2) participant and judge’s ratings of effectiveness of solutions, and 3) ratings of intention to implement solutions. Finally, to determine the presence of any lingering anxiety and worry after participants chose their best solution (4), we ran a MANOVA with Group and Condition as predictors, and state worry and anxiety levels after identifying “best” solutions as outcomes.

In the case of nonsignificant findings, we ran exploratory secondary analyses in the form of hierarchical linear regression models to test if reported state worry levels following the WOR/T-OBJ/DB tasks could predict problem-solving outcomes, while controlling for trait worry. The purpose of these analyses was to determine if the extent to which participants reported actually worrying during the induction would be a better predictor than their assigned condition, while also controlling for the possible influence of trait worry on these outcomes. To do so, we entered PSWQ in the first block of the model, followed by state worry levels in the second block. To address any issues of non-normality, bootstrapping using 1000 samples was applied to all ANOVAs and regressions.

Baseline Measures and Manipulation Check

At baseline, there was a main effect of Group, F (4, 176) = 15.92, p < .001, η 2 p = .27. As expected, the High Trait Worry group reported more baseline worry and anxiety than did the Low Trait Worry group. Further, the Low Trait Worry group reported more baseline relaxation and better mood than did the High Trait Worry group (see Table 1 for means and standard deviations). There was no main effect of Condition; F (8, 354) = 1.55, p = .139, η 2 p = .03; and no Group X Condition interaction; F (8, 354) = 1.07, p = .385, η 2 p = .02; suggesting no significant baseline differences between conditions.

State Measures at Baseline and Post Problem-Thinking Task

Note . Reported raw means with standard deviations in parentheses. WOR/W = worry task, T-OBJ/O = think objectively task, DB = diaphragmatic breathing task, ns = non-significant.

Following the WOR, T-OBJ, and DB tasks, our manipulation check measures showed a main effect of Group, F (4, 176) = 15.07, p < .001, η 2 p = .26. The High Trait Worry group reported significantly more worry and anxiety , lower relaxation , and worse mood than the Low Trait Worry group, regardless of their assigned task. More importantly, however, there was a main effect of Condition; F (8, 354) = 8.75, p < .001, η 2 p = .17; such that WOR led to significantly higher ratings of worry and anxiety than T-OBJ and DB, and T-OBJ led to higher ratings than DB. WOR also led to significantly worse mood than both T-OBJ and DB, which were not significantly different from one-another. Finally, DB led to significantly higher relaxation than both T-OBJ and WOR, and T-OBJ was higher than WOR (see Table 1 ). There was no significant Group X Condition interaction, F (8, 354) = .93, p = .494, η 2 p = .02. As such, data suggest that these tasks operated in the intended way for both High and Low Trait Worry groups.

Main Hypotheses

Number of solutions..

Contrary to predictions, there were no main effects of Group; F (1, 178) = .67, p = .414, η 2 p = .00; or Condition; F (2, 178) = 2.61, p = .076, η 2 p = .03; and no interaction; F (2, 178) = .87, p = .419, η 2 p = .01; on number of solutions generated during the brainstorming period. In a follow-up regression, the first block of the model, consisting of the PSWQ, was not significant; F (1,181) = .17, p = .685; and accounted for only 0.1% of the total variance. Adding state worry levels to the model did not significantly increase predictive value; F (1,180) = 1.52, p = .221; and only accounted for an additional 1.6% of the variance.

Effectiveness of solutions.

In terms of participants’ own ratings of their confidence in solution effectiveness, there was a main effect of Group; F (1, 178) = 9.13, p = .003, η 2 p = .05. Overall, High Trait Worriers reported less confidence in the effectiveness of their solutions (M = 66.73, SD = 22.31) than did Low Trait Worriers (M = 76.25, SD = 23.57), regardless of condition. There was no main effect of Condition; F (2, 178) = 1.01, p = .367, η 2 p = .01; but there was a significant Group X Condition interaction; F (2, 178) = 4.54, p = .012, η 2 p = .05. When divided by Group, High Trait Worriers in the WOR condition rated confidence in their selected solution as significantly lower (M = 57.77, SD = 29.46) than those in T-OBJ (M = 72.97, SD = 15.0; p = .017), and marginally lower than those in DB (M = 68.97, SD = 18.06; p = .076), but this did not reach significance. There were no significant differences between T-OBJ and DB ( p = .347; see Figure 1 ). Low Trait Worriers did not demonstrate significant differences by condition (all p ’s > .05).

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Participant Ratings of Confidence in Effectiveness of Solutions for the High Trait Worry Group

Note. WOR = worry task, T-OBJ = think objectively task, DB = diaphragmatic breathing task, * p < .05.

In terms of judge’s ratings, there was a main effect of Condition; F (2, 177) = 5.08, p = .007, η 2 p = .05. Those in the T-OBJ condition were judged to have generated significantly more effective solutions (M = 5.77, SD = .93) than those in WOR (M = 5.18, SD = 1.19, p = .004) and DB (M = 5.21, SD = 1.38, p = .009), which were not significantly different from each other ( p = .938). Observed differences were modest, but nonetheless significant (see Figure 2 ). There was neither a main effect of Group; F (1, 177) = .14, p = .711, η 2 p = .001; nor an interaction; F (2, 177) = 1.85, p = .161, η 2 p = .02.

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Judge’s Ratings of Effectiveness of Solutions across High and Low Trait Worry Groups

Note. WOR = worry task, T-OBJ = think objectively task, DB = diaphragmatic breathing task, ** p < .01.

Intention to implement solutions.

Contrary to predictions, there were no main effects of Group; F (1, 178) = 3.00, p = .085, η 2 p = .02; Condition; F (2, 178) = .21, p = .814, η 2 p = .00; or an interaction; F (2, 178) = 2.34, p = .10, η 2 p = .03; on participants’ ratings of intention to implement their solutions. A follow-up regression indicated that trait and state worry together significantly predicted intention, accounting for 5.5% of the total variance. When entered first, the PSWQ was a negative predictor of intention ( β = −.158, p = .032), such that higher trait worry predicted less reported intention. Upon adding state worry levels, the model’s predictive value significantly increased (Δ R 2 = .03, p = .017). Higher state worry also predicted less reported intention to implement solutions ( β = −.212, p = .020), but importantly, trait worry was no longer a significant predictor in the full model (see Table 2 ).

Trait and State Worry Predicting Intention to Implement Solutions

Note. Confidence intervals and standard errors are based on 1000 bootstrapped samples. PSWQ = Penn State Worry Questionnaire, Worry = self-reported state worry levels post problem-thinking task,

Worry and anxiety levels after choosing a solution.

There was a main effect of Group; F (2, 178) = 18.17, p < .001, η 2 p = .17. On average, High Trait Worriers reported greater worry (M = 40.53, SD = 26.04) and anxiety (M = 42.80, SD = 25.97) than did Low Trait Worriers (M = 21.91, SD = 26.59; M = 21.12, SD = 25.11, respectively) after generating their solutions, regardless of condition. Consistent with hypotheses, there was also a main effect of Condition; F (4, 358) = 4.27, p = .002, η 2 p = .05. All participants in the WOR condition reported significantly greater worry (M = 40.82, SD = 29.68) and anxiety (M = 41.90, SD = 29.40) following solution generation compared to those in T-OBJ (M = 31.10, SD = 25.55, p = .047; M = 32.11, SD = 27.69, p = .030; respectively) and DB (M = 23.11, SD = 25.80, p = .002; M = 23.42, SD = 23.01, p < .001; respectively). Those in the T-OBJ condition also reported greater anxiety than those in DB ( p = .042), but not greater worry ( p = .071; see Figure 3 ). There was no Group X Condition interaction; F (4, 358) = .87, p = .484, η 2 p = .01.

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Post-Solution Generation State Levels

Note. WOR = worry task, T-OBJ = think objectively task, DB = diaphragmatic breathing task, * p < .05, ** p < .01

Research has long suggested the possibility of a connection between worry and impaired problem solving; yet no prior study has experimentally manipulated worry to test for a causal link. In this study we tested the effects of a controlled worry manipulation on several factors related to the problem-solving process, using both high and low trait worriers. Ultimately, we found that worrying about a real-life problem, relative to attempting to think about the problem objectively or diaphragmatic breathing, led to interference at multiple levels of problem solving. These findings held true at least in part for both high and low trait worriers alike.

Several findings emerged in terms of the effects of trait or state worry on aspects of the problem solving process. Contrary to our expectations, we found no differences for Group or Condition on the number of solutions participants generated when asked to brainstorm ways to solve their problems. This is not to say that all solutions were of equal quality. For example, some participants listed ideas such as, “ignore it until later”, “get some sushi”, and “do nothing”, alongside more effective ideas (e.g., “join a study group”, “make a budget and stick to it”). Listing as many ideas as possible without judgment while in the brainstorming phase is considered beneficial for problem solving ( D’Zurilla & Goldfried, 1971 ). Our data suggested that both trait worry status and condition type neither significantly helped nor hindered brainstorming performance, and that specific negative effects of worry only emerged later in the problem-solving process.

After choosing the “best” of these solutions, however, high trait worriers reported lower confidence in the effectiveness of their chosen solution compared to low trait worriers, regardless of condition. Also, high trait worriers who worried before generating solutions reported significantly lower confidence in their chosen solution than did those instructed to think about their problems more objectively. They also reported marginally lower confidence than those who engaged in a diaphragmatic breathing exercise, though this did not reach significance. This is consistent with prior findings that chronic worriers reported lower confidence in their ability to solve problems relative to nonanxious controls (e.g., Anderson et al., 2009 ; Ladouceur et al., 1998 ); however, this is the first study to demonstrate that in high trait worriers, the specific act of worrying reduced problem-solving confidence. In low trait worriers, on the other hand, worry (vs other conditions) did not lead to a significantly different impact on confidence in their solutions’ effectiveness.

The fact that a prior worry induction only reduced confidence for chronic worriers is more in line with the perspective articulated by Davey and colleagues ( Davey, 1994 ; Davey et al., 1992 ), who argued that factors such as low problem-solving confidence would impair problem solving, but only for pathological worriers. Notably, high trait worriers who were instructed to think objectively reported mean confidence scores that were significantly higher than those instructed to worry. These results imply that instructing chronic worriers to think about their problems in a more objective manner, and to refrain from negative thinking, may counteract such pessimistic beliefs and enhance confidence levels. However, contrary to Davey’s theory, there was no significant benefit of worry on confidence in low trait worriers. Thus, whereas the worry induction impaired confidence in high trait worriers, it neither helped nor hindered confidence in low trait worriers.

As opposed to participants’ subjective ratings of confidence in their solutions’ effectiveness, ratings made by an independent judge reflected our attempts to objectively rate whether the solution would be effective. In this case, a main effect of condition emerged across all participants. According to these ratings, attempting to think objectively about a problem led to a small but significant advantage in coming up with more effective solutions relative to both worrying and diaphragmatic breathing, which were not significantly different. As such, this finding does not represent a unique impairment effect of worry per se , but rather points to the benefits of attempting to contemplate problems in an objective, emotionally-neutral manner. It also indicates that although worrying did not reduce low trait worriers’ confidence in their solution effectiveness, such confidence was not matched by an independent judge.

To further unpack this finding, as a non-worry comparison individuals in the T-OBJ condition were instructed to think about their problem in a less emotional, more constructive way (i.e., breaking it down, focusing on their goals), without falling into negative or catastrophic thinking. We cannot rule out that this may have fueled more solution-focused thinking than worrying. In fact, the very act of focusing on a problem (whether it be catastrophically or objectively), likely made it difficult for participants not to consider various possible solutions during this manipulation period. If, however, those in the T-OBJ condition tended to naturally spend more time generating better solutions, this still supports the conclusion that worry detracts from problem solving, as it suggests that the negative and catastrophic thinking characteristic of worry interferes with more constructive processes and ultimately detracts from coming up with good solutions. It also suggests this can happen for both high and low trait worriers.

Regarding the lack of differences between WOR and DB on experimenter-rated effectiveness, it is important to note that those randomly assigned to the DB condition were not instructed to contemplate their problem at all prior to brainstorming solutions, but rather were instructed to focus attention on their breathing. That they were then able to generate impromptu solutions rated as not different from solutions of those who had actively worried over their problem beforehand, is a notable finding. This suggests that worrying about a problem offered no greater advantage in this context than did a diaphragmatic breathing exercise. It also contradicts the beliefs of many individuals, and especially those of chronic worriers, that worrying is necessary in order to find the best solution to a problem (e.g., Borkovec & Roemer, 1995 ; Hebert et al., 2014 ). Taken together, these findings are more consistent with Mathews’ (1990) proposition that for all individuals, the act of worrying is not actually helpful in terms of finding adequate solutions to problems.

In terms of participants’ reported intention to implement their solutions, there were no significant effects of Group or Condition. A follow-up exploratory regression analysis identified that the extent to which participants worried during their assigned task (irrespective of what that task was) predicted lower reported intention to engage in proactive action. This effect was not simply driven by those with higher trait worry, as state worry predicted ratings of intention when controlling for trait worry, and trait worry was no longer a significant predictor once state worry was entered in the model. This finding provides more clear support for Mathews’ (1990) stance on worry thwarting the problem-solving process, regardless of whether it is experienced at chronic levels or not. This also dovetails with the finding that depressive rumination reduced participants’ reported likelihood to implement solutions to their problems ( Lyubomirsky et al., 1999 ), suggesting that both forms of repetitive negative thinking may discourage engaging in such proactive behaviors. However, it should be noted that this analysis was simply a secondary, and more correlational, exploration of our data, and as such does not allow for more robust causal interpretations.

Finally, we found that for both high and low trait worriers, worrying about one’s problem led to significantly higher reported worry and anxiety levels even after having identified a solution, as compared to thinking objectively about the problem or relaxing. This is consistent with research showing that the negative effects of worry linger over time (e.g., Newman et al., 2019 ; Pieper, Brosschot, van der Leeden, & Thayer, 2010 ), and appears to hold true even after making a decision about the best course of action to ameliorate a problem. Thus, rather than feel a sense of resolution about the issue, with corresponding decreases in worry and anxiety, worrying before choosing a solution may instead lead to lingering feelings of doubt.

Overall, these results provide evidence that engaging in worry is detrimental to problem solving on multiple levels, which apart from reducing confidence in the process, appears to affect both high and low trait worriers alike. One explanation for these findings may be that, consistent with Attentional Control Theory ( Eysenck et al., 2007 ), worrying about a personal problem focused participants’ attention on threatening aspects of the situation (e.g., potential negative outcomes). As such, shifting from worrying into generating and evaluating solutions to the problem, (i.e., threat-related versus goal-directed attention) demanded additional cognitive resources. Attempting to think about the problem objectively, however, is more consistent with goal-directed attention and thus would not have required inhibition. In this way, attempting to think objectively may have allowed for greater access to cognitive resources while problem solving, and possibly more time spent contemplating solutions, relative to worrying. However, we did not measure these effects directly, other than to show that objective thinking facilitated generating more highly rated solution effectiveness than either worry or a breathing exercise.

Another explanation may be that the worry induction both increased cognitive load, and led to greater anxiety and worse mood, and these factors interacted to undermine the problem-solving process. According to Gray’s (1990) neuropsychology theory of emotions, anxiety triggers the behavioral inhibition system, promoting harm-avoidance over approach strategies in the face of a problem. This dovetails with the affect-as-information perspective, which states that affect influences judgment and decision-making ( Clore & Huntsinger, 2007 ). As such, in the context of problem solving, a negative mood may focus attention on potential obstacles to goals or unwanted outcomes, thus leading to pessimistic appraisals of one’s performance (see Schwarz & Skurnik, 2003 ). Our data support this trajectory based on the fact that worry 1) created greater negative affect in the moment, 2) led to sustained worry and anxiety levels even after participants had chosen a solution, 3) decreased confidence in effectiveness of solutions for the high worry group, 4) led to lower judge’s ratings of effectiveness, and 5) predicted less intention to implement solutions for all participants, while controlling for trait worry (though this latter finding was more correlational than causal). In sum, this suggests that worry led to negative cognitive and emotional effects, impairing problem solving at several stages of the process.

Overall, although the worry induction reduced problem-solving confidence only for high trait worriers, it led to a number of additional negative outcomes for all participants. As such, these data provide initial evidence that state worry hinders proactive problem solving across high and low trait worry levels. Moreover, despite the fact that low trait worriers reported a non-significant impact of worry on their confidence in solutions, it still predicted lower judge’s ratings of the solution effectiveness and less willingness to enact them. Therefore, results of this study provide more robust support for Mathews’ (1990) theory, suggesting that worry is a problematic strategy for all persons interested in resolving their problems.

This study has some notable limitations. Because high trait worry participants were not treatment-seeking, this limits our ability to generalize findings to clinically worried individuals. However, previous studies have identified impairment associated with worry in unselected samples (e.g., Hallion et al., 2014 ), as well as in samples of participants diagnosed with GAD (e.g., Pawluk et al., 2017 ). Furthermore, we hypothesized that the worry induction would impair problem solving even at low levels of trait worry, thus it was important to demonstrate that findings were not exclusive to a sample with clinically high levels of trait worry. Future studies should seek to replicate findings in clinical populations before such generalizations can be made. Moreover, because our study population consisted of college students, we cannot generalize findings to non-college student samples. As such these findings merit replication in other samples. On the other hand, our college student sample included adequate representation of racial diversity, with about 42% reflecting non-white groups.

Finally, because we asked participants to think about problems in their own lives, this may have led to some lack of uniformity in the complexity or severity level of problems participants were attempting to solve. For example, pathological worriers may be more likely than nonworriers to worry about even minor things. For this reason, we ensured that there was an equal balance of high and low trait worriers randomly assigned across conditions. Our procedure also directed participants to choose a problem for which they had some control over the outcome (i.e., we directed them to avoid problems for which there were no solutions). This may have also helped to prevent one group from selecting more intractable problems than another. Nonetheless, we cannot rule out the possibility that problem severity varied systematically across conditions leading to the effects we found. Considering that studies of problem solving in real-life settings have been better able to detect worry-related impairment (e.g., Szabó & Lovibond, 2006 ) relative to those using hypothetical problems in an laboratory setting (e.g., Davey, 1994 ), we strove to create a task that was both externally valid and experimentally rigorous. However, future studies may wish to increase uniformity of this variable, while attempting to maintain external validity (such as by balancing participants by the types of problems they report or by ratings of problem severity).

In sum, this was the first study to experimentally manipulate worry immediately prior to problem solving in a controlled laboratory setting, and provides initial evidence that the worry process is detrimental to problem solving in this context. Although many individuals are prone to worry in the face of problems, believe that this is a helpful approach to confronting problems, and often conflate worry with active problem solving (e.g., Kelly & Kelly, 2007 ; Sugiura, 2013 ; Szabó & Lovibond, 2002 ), our findings suggest otherwise. We argue that worry is distinct from adaptive problem solving. Whereas it does direct attention to potential threats, worrying about a problem inhibits the ability to proactively address threats in an optimal way, and instead may repeatedly cycle people through their worst-case scenario fears. Data from this study argue that attempting to take a more objective stance when evaluating a problem, and refraining from catastrophic thinking, represent the most effective problem-solving strategies for both high and low trait worry individuals alike.

Worrying about a personal problem lowered confidence in solutions for high trait worriers.
Thinking objectively about a problem led to more effective solutions than worrying or focused breathing.
State worry predicted less intention to implement solutions, while controlling for trait worry.
Worrying beforehand led to elevated worry and anxiety after solving a personal problem.

Supplementary Material

Acknowledgments.

This study was partially supported by NIMH 1R01MH115128-01A1 to Michelle Newman.

Declarations of interest: none

Sandra Llera: Conceptualization, Methodology, Formal Analysis, Investigation, Writing - Original draft preparation. Michelle G. Newman: Conceptualization, Methodology, Formal Analysis, Writing - Review and editing.

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6 Common Problem Solving Barriers and How Can Managers Beat them?

What is the meaning of barriers to problem solving, what are the 6 barriers to problem solving, examples of barriers to problem solving, how to overcome problem solving barriers at work tips for managers, problem solving barriers faqs.

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Lack of motivation

Lack of knowledge, lack of resources, emotional barriers, cultural and societal barriers, fear of failure.

Lack of motivation: A person who lacks motivation may struggle to complete tasks on time or produce quality work. For example, an employee who is disengaged from their job may procrastinate on essential tasks or show up late to work.
Lack of knowledge : Employees who lack knowledge or training may be unable to perform their duties effectively. For example, a new employee unfamiliar with the company’s software systems may struggle to complete tasks on their computer.
Lack of resources: Employees may be unable to complete their work due to a lack of resources, such as equipment or technology. For example, a graphic designer who doesn’t have access to the latest design software may struggle to produce high-quality designs.
Emotional barriers: Emotional barriers can affect an employee’s ability to perform their job effectively. For example, an employee dealing with a personal issue, such as a divorce, may have trouble focusing on their work and meeting deadlines.
Cultural and societal barriers: Cultural and societal barriers can affect an employee’s ability to work effectively. For example, an employee from a different culture may struggle to communicate effectively with colleagues or may feel uncomfortable in a work environment that is not inclusive.
Fear of failure : Employees who fear failure may avoid taking on new challenges or may not take risks that could benefit the company. For example, an employee afraid of making mistakes may not take on a leadership role or hesitate to make decisions that could impact the company’s bottom line.
Identify and Define the Problem: Define the problem and understand its root cause. This will help you identify the obstacles that are preventing effective problem solving.
C ollaborate and Communicate: Work with others to gather information, generate new ideas, and share perspectives. Effective communication can help overcome misunderstandings and promote creative problem solving.
Use Creative Problem Solving Techniques: Consider using creative problem solving techniques such as brainstorming, mind mapping, or SWOT analysis to explore new ideas and generate innovative solutions.
Embrace Flexibility: Be open to new ideas and approaches. Embracing flexibility can help you overcome fixed mindsets and encourage creativity in problem solving.
Invest in Resources: Ensure that you have access to the necessary resources, such as time, money, or personnel, to effectively solve complex problems.
Emphasize Continuous Learning: Encourage continuous learning and improvement by seeking feedback, evaluating outcomes, and reflecting on the problem solving process. This can help you identify improvement areas and promote a continuous improvement culture.

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Overcoming psychological barriers to good discovery decisions

Affiliation.

1 Tessella Plc, Stanhope Bretby, Burton upon Trent, Staffs, UK. [email protected] <[email protected]>
PMID: 20553956
DOI: 10.1016/j.drudis.2010.05.007

Better individual and team decision-making should enhance R&D performance. Reproducible biases affecting human decision-making, known as cognitive biases, are well understood by psychologists. These threaten objectivity and balance and so are credible causes for continuing unpleasant surprises in Development and high operating costs. For four of the most common and insidious cognitive biases, we consider the risks to R&D decision-making and contrast current practice with use of evidence-based medicine by healthcare practitioners. Feedback on problem-solving performance in simulated environments could be one of the simplest ways to help teams improve their selection of compounds and effective screening sequences. Computational tools that encourage objective consideration of all of the available information might also contribute.

Publication types

Comparative Study
Biomedical Research* / economics
Biomedical Research* / organization & administration
Computational Biology / methods
Decision Making, Organizational*
Decision Support Systems, Management
Drug Discovery*
Efficiency, Organizational / economics
Evidence-Based Medicine / methods
Problem Solving
Psychology, Industrial / methods

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Barriers to Problem Solving
6 Common Problem Solving Barriers and How Can Managers Beat them?
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Problem-Solving in the Workplace Training Course Materials

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ClearSky Logic, Breaking Barriers, Fuelling Innovation and Solving Critical Business Problems!
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COMMENTS

Barriers to Problem-Solving Flashcards
1.) I was fixated on the typical function of coins (i.e., to purchase things) 2.) I was unable of seeing that coins could serve the function I needed. 3.) I was fixated on using a specific tool for a given problem, and failed to consider how other tools/things might help me achieve my aims.
Intro to Psy Final Exam Review
Intro to Psy Final Exam Review - Ch 8 & Ch 9. Identify common barriers to problem solving. P. 274. Click the card to flip 👆. Functional fixedness is the tendency to perceive an item only in terms of its most common use. (ex:using a dime as a screwdriver) Emotional barriers: inhibition and fear of making a fool of oneself, fear of making a ...
6.8: Blocks to Problem Solving
Common obstacles to solving problems. The example also illustrates two common problems that sometimes happen during problem solving. One of these is functional fixedness: a tendency to regard the functions of objects and ideas as fixed (German & Barrett, 2005).Over time, we get so used to one particular purpose for an object that we overlook other uses.
7.3 Problem-Solving
Additional Problem Solving Strategies:. Abstraction - refers to solving the problem within a model of the situation before applying it to reality.; Analogy - is using a solution that solves a similar problem.; Brainstorming - refers to collecting an analyzing a large amount of solutions, especially within a group of people, to combine the solutions and developing them until an optimal ...
9.5: Pitfalls to Problem Solving
Try It. Query 9.5.1 9.5. 1. Query 9.5.2 9.5. 2. Query 9.5.3 9.5. 3. In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. Sometimes, however, we are swayed by biases or by others manipulating a situation.
Problem-Solving Strategies and Obstacles
Problem-solving helps you figure out how to achieve these desires. The problem-solving process involves: Discovery of the problem. Deciding to tackle the issue. Seeking to understand the problem more fully. Researching available options or solutions. Taking action to resolve the issue.
Identifying Barriers to Problem-Solving in Psychology
Identifying and overcoming barriers to problem-solving in psychology can lead to more effective and efficient solutions. Some common barriers include mental blocks, confirmation bias, and functional fixedness, which can all limit critical thinking and creativity. Mindfulness techniques, seeking different perspectives, and collaborating with ...
The Problem-Solving Process
Problem-solving is a mental process that involves discovering, analyzing, and solving problems. The ultimate goal of problem-solving is to overcome obstacles and find a solution that best resolves the issue. The best strategy for solving a problem depends largely on the unique situation. In some cases, people are better off learning everything ...
Mental Set and Seeing Solutions to Problems
SuHP / Getty Images. A mental set is a tendency to only see solutions that have worked in the past. This type of fixed thinking can make it difficult to come up with solutions and can impede the problem-solving process. For example, that you are trying to solve a math problem in algebra class. The problem seems similar to ones you have worked ...
Problem Solving And Decision Making
Barriers to effective problem solving Barriers exist to problem-solving they can be categorized by their features and tasks required to overcome them. The mental set is a barrier to problem-solving. The mental set is an unconscious tendency to approach a problem in a particular way. Our mental sets are shaped by our past experiences and habits.
7.3 Problem Solving
Solving Puzzles. Problem-solving abilities can improve with practice. Many people challenge themselves every day with puzzles and other mental exercises to sharpen their problem-solving skills. Sudoku puzzles appear daily in most newspapers. Typically, a sudoku puzzle is a 9×9 grid. The simple sudoku below is a 4×4 grid. To solve the puzzle ...
5 Barriers to Critical Thinking
Of course, these are not the only barriers to CT; rather, they are five that may have the most impact on how one applies CT. 1. Trusting Your Gut. Trust your gut is a piece of advice often thrown ...
Barriers to Effective Problem Solving
In the MCAT post, we explore four barriers to effective problem solving that are important to know for the Psychological, Social, and Biological Foundations of Behavior section of the MCAT. These four barriers are irrelevant information, functional fixedness, mental set, and unnecessary constraints.
Barriers to Problem Solving
Misdiagnosis. Common barriers to problem-solving include an incorrect diagnosis of the problem. This could be due to preconceived ideas, biases, or judgments. Defining a problem is the hardest step in the process of problem-solving because this is the foundation on which your entire strategy is built. If you're not careful, you may end up ...
The Six Main Barriers Against Problem-Solving And How To ...
Double loop always to make sure that you are not patching over the symptoms but getting to the heart of the matter. 6. Failure to identify the involved parts. Take time to figure out and consult ...
Worry Impairs the Problem-Solving Process: Results from an Experimental
In sum, this suggests that worry led to negative cognitive and emotional effects, impairing problem solving at several stages of the process. Overall, although the worry induction reduced problem-solving confidence only for high trait worriers, it led to a number of additional negative outcomes for all participants.
6 Common Problem Solving Barriers and How Can Managers Beat them
Fear of failure. One of the most common barriers to problem solving is fear of failure. Fear can prevent us from taking risks and trying new things, preventing us from achieving our goals. Overcoming this fear is vital to success. Several ways to reduce or eliminate fear include practice, visualization, and positive self-talk.
Overcoming psychological barriers to good discovery decisions
Reproducible biases affecting human decision-making, known as cognitive biases, are well understood by psychologists. These threaten objectivity and balance and so are credible causes for continuing unpleasant surprises in Development and high operating costs. For four of the most common and insidious cognitive biases, we consider the risks to ...