Stroop Effect

The Stroop Effect is a famous psychology experiment first studied by J.R. Stroop in the 1930s. It shows that people find it easier to name the color of a word when the word matches the color it’s printed in. For example, the word “red” written in red ink.

But when the word and the ink color don’t match – like the word “red” written in green ink – it takes longer to say the correct color.

This happens because reading words is automatic, and it interferes with the task of naming the ink color. Researchers often study this effect using a test called the Stroop Color-Word Interference Test.

Key Takeaways

  • Experiment: In the classic Stroop task, participants are asked to name the color of the ink a word is printed in, not the word itself. Accuracy and speed are measured to observe how conflict affects attention.
  • How It Works: The effect occurs because reading is automatic, while identifying ink color requires more mental effort. This mismatch creates cognitive interference and delays reaction time.
  • Applications: The Stroop task is widely used to study attention, self-control, and brain function. It also has clinical relevance in assessing conditions like ADHD or brain injury.
  • Implications: The Stroop Effect highlights the limits of mental control and the brain’s tendency to prioritize familiar, automatic tasks.
stroop test
The Stroop test measures the interference between reading and naming the ink color of words, highlighting the conflict between automatic and controlled cognitive processes.

The First Stroop Experiment

The Stroop Effect was first published in 1935 by American psychologist John Ridley Stroop.

Although discoveries of this phenomenon date back to the 19th century, Stroop’s three experiments formally demonstrated how automatic reading can interfere with color naming.

Aims

Stroop set out to answer two key questions:

  • Does it take longer to name the color of a word when the word and ink color don’t match? For example, is it harder to say “blue” when the word “red” is printed in blue ink?

  • Can practice reduce this interference? In other words, can people improve their ability to ignore the word and focus only on the ink color with training?


Experiment 1: Word Reading

  • Participants: 70 undergraduates.

  • Task: Read aloud a list of color words (e.g., “green”), ignoring the ink color.

  • Control Condition: The same words were printed in black ink, with no color interference.

  • Incongruent Condition: Participants read aloud color words printed in mismatched (incongruent) ink colors.

  • Purpose: To test whether the color of the ink interferes with the ability to read the word.

  • Finding: The presence of conflicting ink color had minimal effect on reading speed.

  • Result: Participants took only 2.3 seconds longer to read 100 words on the incongruent cards compared to the control (a 5.6% increase), which Stroop reported as “far from significant.”


Experiment 2: Color Naming

  • Participants: 100 undergraduates.

  • Task: Participants named the ink color of color words, ignoring the word itself.
  • Control Condition: Participants named the color of solid colored squares, printed in the same colours and order as the experimental cards.

  • Incongruent Condition: The words were color names that did not match their ink color (e.g., the word “RED” printed in blue ink).

  • Purpose: To test whether the meaning of the word interferes with naming the ink color.

  • Finding: Naming the ink color was significantly slower when the word spelled a different color than the ink. Over 99% of trials in the incongruent condition took longer than the corresponding control trials.

  • Result: Participants took an average of 47 seconds longer to name 100 ink colors in the incongruent condition—a 74.3% increase in time compared to the control.


Experiment 3: Effects of Practice upon Interference

  • Participants: 32 undergraduates.

  • Task: Participants practiced naming the ink colors of incongruent color words for 8 consecutive days to examine whether practice reduced interference.

  • Control Stimuli: Stroop replaced solid color squares with swastikas (卍) — a neutral symbol that better resembled printed words in visual complexity and allowed more accurate color matching between the control and experimental cards.

Finding 1: Reduced Interference in Color Naming

  • Observation: With daily practice, participants became faster at naming the ink colors of incongruent words.

  • Result: The time to name 50 color words dropped from 49.6 seconds (Day 1) to 32.8 seconds (Day 8), indicating reduced Stroop interference due to practice.

Finding 2: Temporary Interference in Word Reading (Reverse Stroop Effect)

  • Observation: Practice in color naming introduced interference into a previously automatic process—word reading.

  • Result: After 8 days of color-naming practice, word reading times for incongruent stimuli increased from 19.4 seconds (pre-test) to 34.8 seconds (post-test). However, this interference quickly faded—dropping to 22.0 seconds in a second post-test conducted shortly afterward.


Conclusion

Stroop concluded that reading words is a more automatic and practiced skill than naming ink colors.

Because reading happens automatically, it’s difficult to suppress—even when we’re trying to focus on something else.

  • The brain associates written words with a specific, well-learned response: to read.

  • Colors, on the other hand, can be linked to a variety of responses: to name, to describe, or simply to notice.

  • This mismatch in experience creates a conflict in the brain when the word and ink color don’t match—leading to slower reaction times.

Stroop’s research showed how automatic thinking can interfere with controlled thinking, making his work foundational in the study of attention, cognitive control, and executive function.

Modern Computer Version

In today’s computer-based versions of the Stroop task, the colours red, blue, green, and yellow are most commonly used.

These colours and their matching words (like the word “red” in red ink) are used because they are easy to recognise and are part of many people’s everyday vocabulary.


Why Use These Specific Colours?

Researchers use red, blue, green, and yellow for a few important reasons:

  • Easy to tell apart: These colours are very different from each other, so it’s unlikely that someone will confuse them.

  • Well-known words: Most people are familiar with these colour names, which makes the task easier to understand.

  • Balanced design: With four colours, you can make:

    • 12 mismatched (incongruent) combinations – like the word “green” printed in red ink.

    • 4 matched (congruent) combinations – like the word “green” in green ink.

    In a typical experiment, each mismatched combination might be shown 2 or 3 times, making 24–36 trials.

    Matched combinations are fewer, so they may be shown more often to balance things out.

How Trials Are Organised

Trials are usually shown in a random order. But researchers often make sure the same colour or word doesn’t appear twice in a row. This helps avoid patterns that might make the task easier or harder.

Independent Variable (IV):

Whether the word and ink color were congruent (matched) or incongruent (mismatched).

  • Congruent: The word and ink color match. The word “green” written in green ink.  Congruent trials are fewer in number, and some researchers exclude them to avoid participants switching to reading strategies.
  • Incongruent: The word and ink color do not match. The word “green” written in red ink. This creates interference, making it slower and harder to name the ink color.

Dependent Variable (DV):

The main thing being measured is reaction time—how long it takes (in milliseconds) for someone to name the ink colour.

This helps researchers understand how different types of stimuli (congruent, incongruent, or neutral) affect mental processing speed.


What About Control Conditions?

Control for Colour Naming

To measure baseline performance, researchers use neutral items that aren’t real words. These might include:

  • A string of symbols like “*****” or “xxxxx”

  • Random letters like “wwww” (same length as “blue”)

  • Made-up words or words that aren’t colours

These items are printed in colour, and participants are asked to name the colour of the ink.

Because the string isn’t a word, it doesn’t trigger automatic reading—so it gives a clearer measure of how fast someone can name a colour without interference.

Researchers are careful not to use strings that might accidentally remind someone of a real colour (like a word starting with “g,” which could suggest “green”).

Control for Word Reading

To get a baseline for how fast someone can read colour words, researchers use the same colour words, but print them in black ink (e.g., the word “blue” in black).

Participants are simply asked to read the word, with no conflicting colour to process.


How Do People Respond?

Participants can respond in two main ways:

1. Speaking aloud (vocal response)

  • The participant says the name of the ink colour out loud.

  • This method usually leads to faster responses and shows stronger Stroop effects.

  • It closely reflects real-time cognitive interference but requires a voice detection system (e.g., a microphone or voice key).

2. Pressing keys (manual response)

  • Each colour is matched with a keyboard key (e.g., red = “z”, green = “x”).

  • The participant presses the correct key based on the ink colour.

  • This method is a bit slower but is useful when testing large groups or recording accuracy.

Before starting the task, participants usually complete a few practice rounds to get used to the instructions and key mappings.

How the Stroop Effect Works

The Stroop Effect occurs because our brains are wired to prioritize faster, more automatic processes – like reading – over slower, more controlled ones – like naming colors.

1. Relative speed of processing theory:

This theory easily explains why reading the word interferes with naming the ink color, but naming the color doesn’t interfere with reading the word.

That’s because reading happens much faster than color naming, so it takes over more easily.

Interference happens because your brain gets ready to say the word before it finishes figuring out the color.

Since both the word and the color are competing to be spoken, and your brain can only respond to one at a time, this slows you down—especially when the word and color don’t match.

Limitation

While this theory explains why reading the word often interferes with saying the ink color, it doesn’t work in every situation.

Researchers have tried to test the idea by showing the color slightly before the word, hoping that this “head start” would help people focus on the color first.

But in many cases, the interference still happens, even with the extra time.

This suggests that the problem isn’t just about speed—something else must be going on. So, while the theory is helpful, it can’t fully explain why the Stroop effect occurs in all situations.

2. Automaticity theory:

This theory says that reading is an automatic process—it’s fast, happens without thinking, and doesn’t need much attention.

In contrast, saying the color of the ink is not automatic and takes more focus and mental effort.

Because reading happens so quickly and automatically, it can be hard to ignore the word, even when you’re supposed to say the color instead.

This automatic reading gets in the way and causes interference.

This idea also helps explain why reading affects color naming, but color naming doesn’t affect reading as much.

Psychologist Daniel Kahneman (2011) explained this tension using the System 1 vs. System 2 framework:

  • System 1: Fast, automatic thinking (like reading).

  • System 2: Slow, deliberate thinking (like overriding your instinct to read and instead name the ink color).

In a Stroop task, System 1 tends to dominate, and System 2 must work harder to override the automatic response.

Limitation

The theory originally claimed that automatic processes (like reading) can’t be controlled by attention. But newer research shows that’s not completely true.

For example, when researchers change how often the word and color match, or give people helpful cues, the Stroop interference can become weaker.

This means even automatic processes can be influenced by how we focus or shift attention.

So while the automaticity theory explains a lot about the Stroop effect, it doesn’t fully capture how flexible the brain can be when dealing with conflicting information.

3. Parallel distributed processing (PDP) theory:

How does the Parallel Distributed Processing (PDP) model offer a more comprehensive explanation of the Stroop Effect?

The PDP model, proposed by Cohen, Dunbar, and McClelland (1990), gives a more complete explanation of the Stroop effect by focusing on how practice and attention strengthen mental pathways over time.

Instead of saying a process is either “automatic” or “controlled,” this model says automaticity exists on a spectrum, depending on how much we’ve practiced a task.

Key features

1. Strength of Processing

The PDP model says it’s not just speed that matters, but the strength of a pathway in the brain. Think of these pathways like well-worn roads:

  • Reading is a strong pathway because we’ve practiced it all our lives.

  • Color naming is weaker because we use it less often.

Because reading is stronger, it wins the race to the brain’s response system, leading to interference in tasks like the Stroop test.

2. Practice Builds Stronger Pathways

As we practice a task, our brains strengthen the neural connections involved. Over time, these tasks become faster and feel more automatic. For example:

  • If you practice naming made-up shapes over and over, that task can eventually become automatic.

  • In some experiments, those practiced shape names started to interfere with color naming—just like real words do.

This shows that automaticity isn’t fixed—it grows with training and repetition.

3. Automaticity Is a Continuum, Not Either/Or

Older theories said a task is either automatic (fast, effortless) or controlled (slow, effortful). But the PDP model says it’s more like a scale:

  • Tasks can become more automatic with practice.

  • Some tasks are partly automatic but still influenced by attention.

For example, even word reading (which feels automatic) can be weakened or controlled if we focus hard enough or change the task conditions (like showing more incongruent trials).

4. Direct vs. Indirect Pathways

The PDP model also talks about two kinds of processing routes in the brain:

  • Direct pathways: These are fast and automatic, built through lots of practice. Word reading usually uses this route.

  • Indirect pathways: These are slower and used for tasks we’re not yet fluent in. They require more effort, attention, and possibly step-by-step thinking.

As you practice, tasks can move from indirect to direct, becoming faster and more automatic over time.

Why the PDP Model Is Better Than Older Theories

Limitations of Earlier Theories:

  • Speed-of-processing theory explains why faster processes interfere with slower ones, but it can’t explain why interference still happens even if the slower task gets a head start.

  • Automaticity theory claims that automatic processes are completely uncontrollable, but research shows attention can reduce their influence.

What the PDP Model Adds:

  • Shows that practice and learning are key to how automatic a task becomes.

  • Explains how attention can adjust the strength of interference.

  • Describes processing as continuous and flexible, not all-or-nothing.

  • Accounts for both interference and facilitation (when matching word and color helps instead of hurts).

Additional Research

John Ridley Stroop helped lay the groundwork for future research in this field.

Numerous studies have tried to identify the specific brain regions responsible for this phenomenon, identifying two key regions: the anterior cingulate cortex (ACC) and dorsolateral prefrontal cortex (DLFPC).

Both MRI and fMRI scans show activity in the ACC and DLPFC while completing the Stroop test or related tasks (Milham et al., 2003).

The DLPFC assists with memory and executive functioning, and its role during the task are to activate color perception and inhibit word encoding. The ACC is responsible for selecting the appropriate response and properly allocating attentional resources (Banich et al., 2000).

Countless studies that repeatedly test the Stroop effect reveal a few key recurring findings (van Maanen et al., 2009):

  1. Semantic interference: Naming the ink color of neutral stimuli (where the color is only shown in blocks, not as a written word) is faster than incongruent stimuli (where the word differs from its printed color).
  2. Semantic facilitation: Naming the ink of congruent stimuli (where the word and its printed color are in agreement) is faster than for neutral stimuli.
  3. Stroop asynchrony: The previous two findings disappear when reading the word, not naming the color, is the task at hand – supporting the claim that it is much more automatic to read words than to name colors.

Other experiments have slightly modified the original Stroop test paradigm to provide additional findings.

One study found that participants were slower to name the color of emotion words as opposed to neutral words (Larsen et al., 2006).

Another experiment examined the differences between participants with panic disorder and OCD. Even with using threat words as stimuli, they found that there was no difference among panic disorder, OCD, and neutral participants’ ability to process colors (Kampman et al., 2002).

A third experiment investigated the relationship between duration and numerosity processing instead of word and color processing.

Participants were shown two series of dots in succession and asked either (1) which series contained more dots or (2) which series lasted longer from the appearance of the first to the last dots of the series.

The incongruency occurred when fewer dots were shown on the screen for longer, and a congruent series was marked by a series with more dots that lasted longer.

The researchers found that numerical cues interfered with duration processing. That is, when fewer dots were shown for longer, it was harder for participants to figure out which set of dots appeared on the screen for longer (Dormal et al., 2006).

Thus, there is a difference between the processing of numerosity and duration. Together, these experiments illustrate not only all of the doors of research that Stroop’s initial work opened but also shed light on all of the intricate processing associations that occur in our brains.

Other Uses and Versions

The purpose of the Stroop task is to measure interference that occurs in the brain. The initial paradigm has since been adopted in several different ways to measure other forms of interference (such as duration and numerosity, as mentioned earlier).

Additional variations measure interference between picture and word processing, direction and word processing, digit and numerosity processing, and central vs. peripheral letter identification (MacLeod, 2015).

The below figure provides illustrations for these four variations:

stroop picture word  experiment

The Stroop task is also used as a mechanism for measuring selective attention, processing speed, and cognitive flexibility (Howieson et al., 2004).

The Stroop task has also been utilized to study populations with brain damage or mental disorders, such as dementia, depression, or ADHD (Lansbergen et al., 2007; Spreen & Strauss, 1998).

For individuals with depression, an emotional Stroop task (where negative words, such as “grief,” “violence,” and “pain,” are used in conjunction with more neutral words, such as “clock,” “door,” and “shoe”) has been developed.

Research reveals that individuals who struggle with depression are more likely to say the color of a negative word slower than that of a neutral word (Frings et al., 2010).

The versatility of the Stroop task paradigm lends itself to be useful in a wide variety of fields within psychology.

What was once a test that only examined the relationship between word and color processing has since been expanded to investigate additional processing interferences and to contribute to the fields of psychopathology and brain damage.

The development of the Stroop task not only provides novel insights into the ways in which our brain mechanisms operate but also sheds light on the power of psychology to expand and build on past research methods as we continue to uncover more and more about ourselves.

Critical Evaluation

1. The Stroop task is highly replicable and reliable.

 One of the main strengths of the Stroop effect is that it has been replicated many times across different studies, settings, and populations.

Because the task is simple, standardised, and easy to administer, researchers consistently find similar interference effects.

For example, MacLeod (1991) reviewed over 400 studies and found the Stroop effect to be one of the most robust and reliable findings in cognitive psychology.

This high reliability strengthens the validity of the Stroop effect as a measure of attention and interference.

It also makes the Stroop task a valuable tool for both research and clinical assessments of executive function, such as in individuals with brain damage or attention disorders.


2. The Stroop task has strong internal validity.

The task is carefully controlled, with clear independent (congruent vs. incongruent stimuli) and dependent variables (reaction time).

Because participants are typically tested individually under similar conditions, extraneous variables are reduced.

This allows researchers to draw strong conclusions about cause and effect—specifically, that incongruent word-colour pairings lead to longer reaction times due to cognitive interference.

The strong internal validity allows psychologists to make confident claims about the mechanisms of selective attention and automaticity.

However, this level of control may come at the cost of real-world relevance, limiting how well the results generalise beyond the lab.


3. The Stroop task lacks ecological validity.

While the Stroop task is useful in understanding attention in a laboratory setting, it does not reflect how we typically use attention in everyday life.

Naming colours of printed words is an artificial task that doesn’t closely resemble real-world challenges, where distractions are often more complex or emotional in nature.

As a result, findings from Stroop studies may not fully generalise to real-life situations that require managing competing demands—like driving while listening to the radio or focusing on work in a noisy environment.

This limits how applicable the findings are outside experimental settings.


4. The task assumes reading is automatic, but this varies by individual.

The classic Stroop effect is based on the assumption that word reading is an automatic process for all participants.

However, this may not hold true for individuals with lower reading proficiency, such as children, non-native speakers, or people with dyslexia.

In these cases, reading may not be more automatic than colour naming.

This raises concerns about the generalisability of the findings.

If reading is not automatic for a given group, then the Stroop effect may not appear, or may look very different, which limits the universality of the conclusions drawn from Stroop studies.


5. The Stroop task can be adapted for diverse research and clinical applications.

One strength of the Stroop effect is its adaptability.

Researchers have developed variations such as the Emotional Stroop, which uses emotionally charged words to measure attentional biases in anxiety or depression, and the Numerical Stroop, which compares the size of numbers and their numerical value.

These adaptations extend the task beyond colour-word interference to explore broader cognitive processes.

These flexible applications make the Stroop paradigm a valuable diagnostic and research tool, particularly in clinical psychology and neuroscience.

However, care must be taken when interpreting results, as the meaning of “interference” may differ across task versions.


6. The theoretical explanations for the Stroop effect remain debated.

While several models—such as the speed-of-processing theory, automaticity theory, and parallel distributed processing (PDP) model—have been proposed to explain the Stroop effect, none fully capture all aspects of the phenomenon.

For instance, the automaticity theory struggles to explain why attentional strategies can reduce interference, and the speed-of-processing model fails when the timing of stimuli is manipulated.

These theoretical limitations suggest that our understanding of cognitive interference is still incomplete.

Researchers must be cautious when drawing conclusions about mental processes based solely on Stroop performance, as multiple mechanisms may be involved.

FAQs

1. How is the Stroop Effect used in clinical psychology or brain injury assessment?

The Stroop task is widely used in neuropsychological assessments to evaluate executive functions, particularly inhibitory control and selective attention.

Patients with frontal lobe damage, ADHD, schizophrenia, or dementia often show greater interference on Stroop tasks, suggesting impaired cognitive control mechanisms.

Clinicians use variations like the Color-Word Interference Test (part of the D-KEFS battery) to assess how well a person can manage competing information, which is critical for diagnosing issues related to brain injury or neurological conditions

2. What does the Emotional Stroop task reveal about anxiety and depression?

The Emotional Stroop task uses emotionally charged words (e.g., “death,” “failure”) instead of neutral color words.

People with anxiety disorders often take longer to name the ink color of threat-related words, indicating attentional bias toward emotionally salient stimuli.

Similarly, individuals with depression may show slower reaction times to negative or self-referential words.

This suggests that emotional interference reflects underlying mood-related cognitive biases, making the Emotional Stroop a useful tool in clinical and research settings.

3. How does practice change performance in the Stroop task over time?

According to the Parallel Distributed Processing (PDP) model, performance in the Stroop task improves with repeated practice.

As people practice a task (like naming the color of shapes or unfamiliar stimuli), their brains develop stronger processing pathways, making the task faster and more automatic.

With enough training, even a new task can begin to interfere with other tasks—just like word reading does in the classic Stroop effect. This shows that automaticity is learned, not fixed, and evolves over time with repeated exposure

4. Can the Stroop Effect be reduced or trained away?

Yes, research shows that interference in the Stroop task can be reduced through strategic attentional control, feedback, and practice.

For example, changing the proportion of congruent vs. incongruent trials or using cues can help participants shift attention away from reading and improve performance.

Over time, with consistent training, individuals can learn to suppress automatic word reading more effectively, reducing the Stroop interference.

However, even with practice, the effect is not fully eliminated, especially in highly literate adults.

5. Are there cultural or language differences in the Stroop Effect?

Yes, language proficiency, orthography, and reading experience can influence Stroop interference.

For instance, bilingual individuals may show different interference patterns depending on which language is used and their fluency.

Languages with non-alphabetic scripts (like Chinese or Japanese) may also engage different cognitive processes during reading, which can affect how automatic reading is—and therefore how strong the Stroop effect appears.

Additionally, cultural differences in reading instruction and exposure may impact how quickly reading becomes automatic, especially in children or second-language learners.

References

Banich, M. T., Milham, M. P., Atchley, R., Cohen, N. J., Webb, A., Wszalek, T., … & Magin, R. (2000). fMRI studies of Stroop tasks reveal unique roles of anterior and posterior brain systems in attentional selection. Journal of cognitive neuroscience, 12 (6), 988-1000.

Cohen, J. D., Dunbar, K., & McClelland, J. L. (1990). On the control of automatic processes: a parallel distributed processing account of the Stroop effect . Psychological Review, 97 (3), 332.

Dishon-Berkovits, M., & Algom, D. (2000). The Stroop effect: It is not the robust phenomenon that you have thought it to beMemory & Cognition28, 1437-1449.

Dormal, V., Seron, X., & Pesenti, M. (2006). Numerosity-duration interference: A Stroop experiment. Acta psychologica, 121 (2), 109-124.

Frings, C., Englert, J., Wentura, D., & Bermeitinger, C. (2010). Decomposing the emotional Stroop effect. Quarterly journal of experimental psychology, 63 (1), 42-49.

Howieson, D. B., Lezak, M. D., & Loring, D. W. (2004). Orientation and attention. Neuropsychological assessment, 365-367.

Kahneman, D. (2011). Thinking, fast and slow. Macmillan.

Kampman, M., Keijsers, G. P., Verbraak, M. J., Näring, G., & Hoogduin, C. A. (2002). The emotional Stroop: a comparison of panic disorder patients, obsessive–compulsive patients, and normal controls, in two experiments. Journal of anxiety disorders, 16 (4), 425-441.

Lansbergen, M. M., Kenemans, J. L., & Van Engeland, H. (2007). Stroop interference and attention-deficit/hyperactivity disorder: a review and meta-analysis. Neuropsychology, 21 (2), 251.

Larsen, R. J., Mercer, K. A., & Balota, D. A. (2006). Lexical characteristics of words used in emotional Stroop experiments. Emotion, 6 (1), 62.

MacLeod, C. M. (1991). Half a century of research on the Stroop effect: an integrative review. Psychological bulletin, 109 (2), 163.

MacLeod, C. M. (2015). The stroop effect. Encyclopedia of Color Science and Technology.

McMahon, M. (2013). What Is the Stroop Effect. Retrieved November, 11.

Milham, M. P., Banich, M. T., Claus, E. D., & Cohen, N. J. (2003). Practice-related effects demonstrate complementary roles of anterior cingulate and prefrontal cortices in attentional control. Neuroimage, 18 (2), 483-493.

Monahan, J. S. (2001). Coloring single Stroop elements: Reducing automaticity or slowing color processing? . The Journal of general psychology, 128 (1), 98-112.

Sahinoglu B, Dogan G. (2016). Event-Related Potentials and the Stroop Effect. Eurasian J Med, 48(1), 53‐57.

Spreen, O., & Strauss, E. (1998). A compendium of neuropsychological tests: Administration, norms, and commentary. Oxford University Press.

Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of experimental psychology, 18 (6), 643.

van Maanen, L., van Rijn, H., & Borst, J. P. (2009). Stroop and picture—word interference are two sides of the same coin. Psychonomic bulletin & review, 16 (6), 987-999.

Further information

Saul McLeod, PhD

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

Editor-in-Chief for Simply Psychology

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


Charlotte Ruhl

Psychology Graduate

BA (Hons) Psychology, Harvard University

Charlotte Ruhl, a psychology graduate from Harvard College, boasts over six years of research experience in clinical and social psychology. During her tenure at Harvard, she contributed to the Decision Science Lab, administering numerous studies in behavioral economics and social psychology.

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