psychology research topics on intelligence

What Is Intelligence In Psychology

Charlotte Ruhl

Research Assistant & 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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Editor-in-Chief for Simply Psychology

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

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

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BSc (Hons) Psychology, MSc Psychology of Education

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On This Page:

Intelligence in psychology refers to the mental capacity to learn from experiences, adapt to new situations, understand and handle abstract concepts, and use knowledge to manipulate one’s environment. It includes skills such as problem-solving, critical thinking, learning quickly, and understanding complex ideas.

Key Takeaways

• Defining and classifying intelligence is extremely complicated. Theories of intelligence range from having one general intelligence (g) to certain primary mental abilities and multiple category-specific intelligences.
• Following the creation of the Binet-Simon scale in the early 1900s, intelligence tests, now referred to as intelligence quotient (IQ) tests, are the most widely-known and used measure for determining an individual’s intelligence.
• Although these tests are generally reliable and valid tools, they have flaws as they lack cultural specificity and can evoke stereotype threats and self-fulfilling prophecies.
• IQ scores are normally distributed , meaning that 95% of the population has IQ scores between 70 and 130. However, some extreme examples exist of people with scores far exceeding 130 or far below 70.

What Is Intelligence?

It might seem useless to define such a simple word. After all, we have all heard this word hundreds of times and probably have a general understanding of its meaning.

However, the concept of intelligence has been a widely debated topic among members of the psychology community for decades.

Intelligence has been defined in many ways: higher level abilities (such as abstract reasoning, mental representation, problem solving, and decision making), the ability to learn, emotional knowledge, creativity, and adaptation to meet the demands of the environment effectively.

Psychologist Robert Sternberg defined intelligence as “the mental abilities necessary for adaptation to, as well as shaping and selection of, any environmental context (1997, p. 1).

History of Intelligence

The study of human intelligence dates back to the late 1800s when Sir Francis Galton (the cousin of Charles Darwin) became one of the first to study intelligence.

Galton was interested in the concept of a gifted individual, so he created a lab to measure reaction times and other physical characteristics to test his hypothesis that intelligence is a general mental ability producing biological evolution (hello, Darwin!).

Galton theorized that because quickness and other physical attributes were evolutionarily advantageous, they would also provide a good indication of general mental ability (Jensen, 1982).

Thus, Galton operationalized intelligence as reaction time.

Operationalization is an important process in research that involves defining an unmeasurable phenomenon (such as intelligence) in measurable terms (such as reaction time), allowing the concept to be studied empirically (Crowthre-Heyck, 2005).

Galton’s study of intelligence in the laboratory setting and his theorization of the heritability of intelligence paved the way for decades of future research and debate in this field.

Theories of Intelligence

Some researchers argue that intelligence is a general ability, whereas others make the assertion that intelligence comprises specific skills and talents. Psychologists contend that intelligence is genetic, or inherited, and others claim that it is largely influenced by the surrounding environment.

As a result, psychologists have developed several contrasting theories of intelligence as well as individual tests that attempt to measure this very concept.

Spearman’s General Intelligence (g)

General intelligence, also known as g factor, refers to a general mental ability that, according to Spearman, underlies multiple specific skills, including verbal, spatial, numerical, and mechanical.

Charles Spearman, an English psychologist, established the two-factor theory of intelligence back in 1904 (Spearman, 1904). To arrive at this theory, Spearman used a technique known as factor analysis.

Factor analysis is a procedure through which the correlation of related variables is evaluated to find an underlying factor that explains this correlation.

In the case of intelligence, Spearman noticed that those who did well in one area of intelligence tests (for example, mathematics) also did well in other areas (such as distinguishing pitch; Kalat, 2014).

In other words, there was a strong correlation between performing well in math and music, and Spearman then attributed this relationship to a central factor, that of general intelligence (g).

Spearman concluded that there is a single g-factor that represents an individual’s general intelligence across multiple abilities and that a second factor, s, refers to an individual’s specific ability in one particular area (Spearman, as cited in Thomson, 1947).

Together, these two main factors compose Spearman’s two-factor theory.

Thurstone’s Primary Mental Abilities

Thurstone (1938) challenged the concept of a g-factor. After analyzing data from 56 different tests of mental abilities, he identified a number of primary mental abilities that comprise intelligence as opposed to one general factor.

The seven primary mental abilities in Thurstone’s model are verbal comprehension, verbal fluency, number facility, spatial visualization, perceptual speed, memory, and inductive reasoning (Thurstone, as cited in Sternberg, 2003).

Although Thurstone did not reject Spearman’s idea of general intelligence altogether, he instead theorized that intelligence consists of both general ability and a number of specific abilities, paving the way for future research that examined the different forms of intelligence.

Gardner’s Multiple Intelligences

Following the work of Thurstone, American psychologist Howard Gardner built off the idea that there are multiple forms of intelligence.

He proposed that there is no single intelligence, but rather distinct, independent multiple intelligences exist, each representing unique skills and talents relevant to a certain category.

Gardner (1983, 1987) initially proposed seven multiple intelligences : linguistic, logical-mathematical, spatial, musical, bodily-kinesthetic, interpersonal, and intrapersonal, and he has since added naturalist intelligence.

Gardner holds that most activities (such as dancing) will involve a combination of these multiple intelligences (such as spatial and bodily-kinesthetic intelligences). He also suggests that these multiple intelligences can help us understand concepts beyond intelligence, such as creativity and leadership .

And although this theory has widely captured the attention of the psychology community and the greater public, it does have its faults.

There have been few empirical studies that actually test this theory, and this theory does not account for other types of intelligence beyond the ones Gardner lists (Sternberg, 2003).

Triarchic Theory of Intelligence

Just two years later, in 1985, Robert Sternberg proposed a three-category theory of intelligence, integrating components that were lacking in Gardner’s theory. This theory is based on the definition of intelligence as the ability to achieve success based on your personal standards and your sociocultural context.

According to the triarchic theory, intelligence has three aspects: analytical, creative, and practical (Sternberg, 1985).

Analytical intelligence , also referred to as componential intelligence, refers to intelligence that is applied to analyze or evaluate problems and arrive at solutions. This is what a traditional IQ test measures.

Creative intelligence is the ability to go beyond what is given to create novel and interesting ideas. This type of intelligence involves imagination, innovation, and problem-solving.

Practical intelligence is the ability that individuals use to solve problems faced in daily life when a person finds the best fit between themselves and the demands of the environment.

Adapting to the demands of the environment involves either utilizing knowledge gained from experience to purposefully change oneself to suit the environment (adaptation), changing the environment to suit oneself (shaping), or finding a new environment in which to work (selection).

Other Types of Intelligence

After examining the popular competing theories of intelligence, it becomes clear that there are many different forms of this seemingly simple concept.

On the one hand, Spearman claims that intelligence is generalizable across many different areas of life, and on the other hand, psychologists such as Thurstone, Gardener, and Sternberg hold that intelligence is like a tree with many different branches, each representing a specific form of intelligence.

To make matters even more interesting, let’s throw a few more types of intelligence into the mix!

Emotional Intelligence

Emotional Intelligence is the “ability to monitor one’s own and other people’s emotions, to discriminate between different emotions and label them appropriately, and to use emotional information to guide thinking and behavior” (Salovey and Mayer, 1990).

Emotional intelligence is important in our everyday lives, seeing as we experience one emotion or another nearly every second of our lives. You may not associate emotions and intelligence with one another, but in reality, they are very related.

Emotional intelligence refers to the ability to recognize the meanings of emotions and to reason and problem-solve on the basis of them (Mayer, Caruso, & Salovey, 1999). The four key components of emotional Intelligence are (i) self-awareness, (ii) self-management, (iii) social awareness, and (iv) relationship management.

In other words, if you are high in emotional intelligence, you can accurately perceive emotions in yourself and others (such as reading facial expressions), use emotions to help facilitate thinking, understand the meaning behind your emotions (why are you feeling this way?), and know how to manage your emotions (Salovey & Mayer, 1990).

Fluid vs. Crystallized Intelligence

Raymond Cattell (1963) first proposed the concepts of fluid and crystallized intelligence and further developed the theory with John Horn.

Fluid intelligence is the ability to problem solve in novel situations without referencing prior knowledge, but rather through the use of logic and abstract thinking. Fluid intelligence can be applied to any novel problem because no specific prior knowledge is required (Cattell, 1963). As you grow older fluid increases and then starts to decrease in the late 20s.

Crystallized intelligence refers to the use of previously-acquired knowledge, such as specific facts learned in school or specific motor skills or muscle memory (Cattell, 1963). As you grow older and accumulate knowledge, crystallized intelligence increases.

The Cattell-Horn (1966) theory of fluid and crystallized intelligence suggests that intelligence is composed of a number of different abilities that interact and work together to produce overall individual intelligence.

For example, if you are taking a hard math test, you rely on your crystallized intelligence to process the numbers and meaning of the questions, but you may use fluid intelligence to work through the novel problem and arrive at the correct solution. It is also possible that fluid intelligence can become crystallized intelligence.

The novel solutions you create when relying on fluid intelligence can, over time, develop into crystallized intelligence after they are incorporated into long-term memory.

This illustrates some of the ways in which different forms of intelligence overlap and interact with one another, revealing its dynamic nature.

Intelligence Testing

Binet-simon scale.

During the early 1900s, the French government enlisted the help of psychologist Alfred Binet to understand which children were going to be slower learners and thus required more assistance in the classroom (Binet et al., 1912).

As a result, he and his colleague, Theodore Simon, began to develop a specific set of questions that focused on areas such as memory and problem-solving skills.

They tested these questions on groups of students aged three to twelve to help standardize the measure (Binet et al., 1912). Binet realized that some children were able to answer advanced questions that their older peers were able to answer.

As a result, he created the concept of mental age, or how well an individual performs intellectually relative to the average performance at that age (Cherry, 2020).

Ultimately, Binet finalized the scale, known as the Binet-Simon scale, that became the basis for the intelligence tests still used today.

The Binet-Simon scale of 1905 comprised 30 items designed to measure judgment, comprehension, and reasoning, which Binet deemed the key characteristics of intelligence.

Stanford-Binet Intelligence Scale

When the Binet-Simon scale made its way over to the United States, Stanford psychologist Lewis Terman adapted the test for American students and published the Stanford-Binet Intelligence Scale in 1916 (Cherry, 2020).

The Stanford-Binet Scale is a contemporary assessment that measures intelligence according to five features of cognitive ability,

including fluid reasoning, knowledge, quantitative reasoning, visual-spatial processing, and working memory. Both verbal and nonverbal responses are measured.

This test used a single number, referred to as the intelligence quotient (IQ), to indicate an individual’s score.

The average score for the test is 100, and any score from 90 to 109 is considered to be in the average intelligence range. Scores from 110 to 119 are considered to be High Average. Superior scores range from 120 to 129 and anything over 130 is considered Very Superior.

To calculate IQ, the student’s mental age is divided by his or her actual (or chronological) age, and this result is multiplied by 100. If your mental age is equal to your chronological age, you will have an IQ of 100, or average. If your mental age is 12, but your chronological age is only 10, you will have an above-average IQ of 120.

WISC and WAIS

Just as theories of intelligence build off one another, intelligence tests do too. After Terman created Stanford-Binet test, American psychologist David Wechsler developed a new tool due to his dissatisfaction with the limitations of the Stanford-Binet test (Cherry, 2020).

Like Thurstone, Gardner, and Sternberg, Wechsler believed intelligence involved many different mental abilities and felt that the Stanford-Binet scale too closely reflected the idea of one general intelligence.

Because of this, Wechsler created the Wechsler Intelligence Scale for Children (WISC) and the Wechsler Adult Intelligence Scale (WAIS) in 1955, with the most up-to-date version being the WAIS-IV (Cherry, 2020).

The Wechsler Intelligence Scale for Children (WISC), developed by David Wechsler, is an IQ test designed to measure intelligence and cognitive ability in children between the ages of 6 and 16. It is currently in its fourth edition (WISC-V) released in 2014 by Pearson.

Above Image: WISC-IV Sample Test Question

The Wechsler Adult Intelligence Scale (WAIS) is an IQ test designed to measure cognitive ability in adults and older adolescents, including

verbal comprehension, perceptual reasoning, working memory, and processing speed.

The latest version of the Wechsler Adult Intelligence Scale (WAIS-IV) was standardized on 2,200 healthy people between the ages of 16 and 90 years (Brooks et al., 2011).

The standardization of a test involves giving it to a large number of people of different ages to compute the average score on the test at each age level.

The overall IQ score combines the test takers’ performance in all four categories (Cherry, 2020). And rather than calculating this number based on mental and chronological age, the WAIS compares the individual’s score to the average score at that level, as calculated by the standardization process.

The Flynn Effect

It is important to regularly standardize an intelligence test because the overall level of intelligence in a population may change over time.

This phenomenon is known as the Flynn effect (named after its discoverer, New Zealand researcher James Flynn) which refers to the observation that scores on intelligence tests worldwide increase from decade to decade (Flynn, 1984).

Aptitude vs. Achievement Tests

Other tests, such as aptitude and achievement tests, are designed to measure intellectual capability. Achievement tests measure what content a student has already learned (such as a unit test in history or a final math exam), whereas an aptitude test measures a student’s potential or ability to learn (Anastasi, 1984).

Although this may sound similar to an IQ test, aptitude tests typically measure abilities in very specific areas.

Criticism of Intelligence Testing

Criticisms have ranged from the claim that IQ tests are biased in favor of white, middle-class people. Negative stereotypes about a person’s ethnicity, gender, or age may cause the person to suffer stereotype threat, a burden of doubt about his or her own abilities, which can create anxiety that result in lower scores.

Reliability and Construct Validity

Although you may be wondering if you take an intelligence test multiple times will you improve your score and whether these tests even measure intelligence in the first place, research provides reassurance that these tests are both very reliable and have high construct validity.

Reliability simply means that they are consistent over time. In other words, if you take a test at two different points in time, there will be very little change in performance or, in the case of intelligence tests, IQ scores.

Although this isn’t a perfect science, and your score might slightly fluctuate when taking the same test on different occasions or different tests at the same age, IQ tests demonstrate relatively high reliability (Tuma & Appelbaum, 1980).

Additionally, intelligence tests also reveal strong construct validity , meaning that they are, in fact, measuring intelligence rather than something else.

Researchers have spent hours on end developing, standardizing, and adapting these tests to best fit the current times. But that is also not to say that these tests are completely flawless.

Research documents errors with the specific scoring of tests and interpretation of the multiple scores (since typically, an individual will receive an overall IQ score accompanied by several category-specific scores), and some studies question the actual validity, reliability, and utility for individual clinical use of these tests (Canivez, 2013).

Additionally, intelligence scores are created to reflect different theories of intelligence, so the interpretations may be heavily based on the theory upon which the test is based (Canivez, 2013).

Cultural Specificity

There are issues with intelligence tests beyond looking at them in a vacuum.  These tests were created by Western psychologists who created such tools to measure euro-centric values.

However, it is important to recognize that the majority of the world’s population does not reside in Europe or North America, and as a result, the cultural specificity of these tests is crucial.

Different cultures hold different values and even have different perceptions of intelligence, so is it fair to have one universal marker of this increasingly complex concept?

For example, a 1992 study found that Kenyan parents defined intelligence as the ability to do without being told what needed to be done around the homestead (Harkness et al., 1992), and, given the American and European emphasis on speed, some Ugandans define intelligent people as being slow in thought and action (Wober, 1974).

Together, these examples illustrate the flexibility of defining intelligence, making capturing this concept in a single test, let alone a single number even more challenging.  And even within the U.S., do perceptions of intelligence differ?

An example is in San Jose, California, where Latino, Asian, and Anglo parents had varying definitions of intelligence.  The teachers’ understanding of intelligence was more similar to that of the Asian and Anglo communities, and this similarity predicted the child’s performance in school (Okagaki & Sternberg, 1993).

That is, students whose families had more similar understandings of intelligence were doing better in the classroom.

Intelligence takes many forms, ranging from country to country and culture to culture.  Although IQ tests might have high reliability and validity, understanding the role of culture is as, if not more, important in forming the bigger picture of an individual’s intelligence.

IQ tests may accurately measure academic intelligence, but more research must be done to discern whether they truly measure practical intelligence or even just general intelligence in all cultures.

Social and Environmental Factors

Another important part of the puzzle to consider is the social and environmental context in which an individual lives and the IQ test-related biases that develop as a result.

These might help explain why some individuals have lower scores than others. For example, the threat of social exclusion can greatly decrease the expression of intelligence.

A 2002 study gave participants an IQ test and a personality inventory, and some were randomly chosen to receive feedback from the inventory indicating that they were “the sort of people who would end up alone in life” (Baumeister et al., 2002).

After a second test, those who were told they would be loveless and friendless in the future answered significantly fewer questions than they did on the earlier test.

These findings can translate into the real world where not only the threat of social exclusion can decrease the expression of intelligence but also a perceived threat to physical safety.

In other words, a child’s poor academic performance can be attributed to the disadvantaged, potentially unsafe communities in which they grow up.

Stereotype Threat

Stereotype threat is a phenomenon in which people feel at risk of conforming to stereotypes about their social group. Negative stereotypes can also create anxiety that results in lower scores.

In one study, Black and White college students were given part of the verbal section from the Graduate Record Exam (GRE), but in the stereotype threat condition, they told students the test diagnosed intellectual ability, thus potentially making the stereotype that Blacks are less intelligent than Whites salient.

The results of this study revealed that in the stereotype threat condition, Blacks performed worse than Whites, but in the no stereotype threat condition, Blacks and Whites performed equally well (Steele & Aronson, 1995).

And even just recording your race can also result in worsened performance. Stereotype threat is a real threat and can be detrimental to an individual’s performance on these tests.

Self-Fulfilling Prophecy

Stereotype threat is closely related to the concept of a self-fulfilling prophecy in which an individual’s expectations about another person can result in the other person acting in ways that conform to that very expectation.

In one experiment, students in a California elementary school were given an IQ test, after which their teachers were given the names of students who would become “intellectual bloomers” that year based on the results of the test (Rosenthal & Jacobson, 1968).

At the end of the study, the students were tested again with the same IQ test, and those labeled as “intellectual bloomers” significantly increased their scores.

This illustrates that teachers may subconsciously behave in ways that encourage the success of certain students, thus influencing their achievement (Rosenthal & Jacobson, 1968), and provides another example of small variables that can play a role in an individual’s intelligence score and the development of their intelligence.

This is all to say that it is important to consider the less visible factors that play a role in determining someone’s intelligence. While an IQ score has many benefits in measuring intelligence, it is critical to consider that just because someone has a lower score does not necessarily mean they are lower in intelligence.

There are many factors that can worsen performance on these tests, and the tests themselves might not even be accurately measuring the very concept they are intended to.

Extremes of Intelligence

IQ scores are generally normally distributed (Moore et al., 2013). That is, roughly 95% of the population has IQ scores between 70 and 130. But what about the other 5%?

Individuals who fall outside this range represent the extremes of intelligence.

Those who have an IQ above 130 are considered to be gifted (Lally & French, 2018), such as Christopher Langan, an American horse rancher, who has an IQ score around 200 (Gladwell, 2008).

Those individuals who have scores below 70 do so because of an intellectual disability marked by substantial developmental delays, including motor, cognitive, and speech delays (De Light, 2012).

Some of the time, these disabilities are the product of genetic mutations.

Down syndrome, for example, resulting from extra genetic material from or a complete extra copy of the 21st chromosome, is a common genetic cause of an intellectual disability (Breslin, 2014). As such, many individuals with Down Syndrome have below-average IQ scores (Breslin, 2014).

Savant syndrome is another example of extreme intelligence. Despite having significant mental disabilities, these individuals demonstrate certain abilities in some fields that are far above average, such as incredible memorization, rapid mathematical or calendar calculation ability, or advanced musical talent (Treffert, 2009).

The fact that these individuals who may be lacking in certain areas such as social interaction and communication make up for it in other remarkable areas further illustrates the complexity of intelligence and what this concept means today, as well as how we must consider all individuals when determining how to perceive, measure, and recognize intelligence in our society.

Intelligence Today

Today, intelligence is generally understood as the ability to understand and adapt to the environment by using inherited abilities and learned knowledge.

Many new intelligence tests have arisen, such as the University of California Matrix Reasoning Task (Pahor et al., 2019), that can be taken online and in very little time, and new methods of scoring these tests have been developed too (Sansone et al., 2014).

Admission into university and graduate schools relies on specific aptitude and achievement tests, such as the SAT, ACT, and the LSAT – these tests have become a huge part of our lives.

Humans are incredibly intelligent beings and rely on our intellectual abilities daily. Although intelligence can be defined and measured in countless ways, our overall intelligence as a species makes us incredibly unique and has allowed us to thrive for generations on end.

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Human intelligence and brain networks

Inteligencia humana y redes cerebrales, intelligence humaine et réseaux cérébraux, roberto colom.

Universidad Autónoma de Madrid, Spain

Sherif Karama

McGill University, Montreal, Quebec, Canada

Rex E. Jung

The MIND Research Network, Albuquerque, New Mexico, USA

Richard J. Haier

University of California, Irvine, California, USA

Intelligence can be defined as a general mental ability for reasoning, problem solving, and learning. Because of its general nature, intelligence integrates cognitive functions such as perception, attention, memory, language, or planning. On the basis of this definition, intelligence can be reliably measured by standardized tests with obtained scores predicting several broad social outcomes such as educational achievement, job performance, health, and longevity. A detailed understanding of the brain mechanisms underlying this general mental ability could provide significant individual and societal benefits. Structural and functional neuroimaging studies have generally supported a frontoparietal network relevant for intelligence. This same network has also been found to underlie cognitive functions related to perception, short-term memory storage, and language. The distributed nature of this network and its involvement in a wide range of cognitive functions fits well with the integrative nature of intelligence. A new key phase of research is beginning to investigate how functional networks relate to structural networks, with emphasis on how distributed brain areas communicate with each other.

La inteligencia se puede definir como una capacidad mental general para razonar, resolver problemas y aprender. Dada su naturaleza general, la inteligencia integra funciones cognitivas como perceptión, atención, memoria, lenguaje o planificatión. De acuerdo con esta definitión la inteligencia se puede medir confiablemente mediante pruebas estandarizadas en que los puntajes obtenidos predicen algunas repercusiones sociales generales como éxito educacional, rendimiento laboral, salud y longevidad. Una comprensión detallada de los mecanismos cerebrales a la base de esta capacidad mental general podría entregar significativos beneficios individuales y sociales. Los estudios de neuroimágenes estructurales y funcionales en general le han dado soporte a una red frontoparietal como relevante para la inteligencia. Esta misma red se ha encontrado a la base de las funciones cognitivas relacionadas con la perceptión, el almacenamiento de la memoria de corto plazo y el lenguaje. La forma en que se distribuye esta red y su participatión en una amplia gama de funciones cognitivas se ajusta bien con la característica integradora de la inteligencia. Se está iniciando una nueva fase clave de la investigatión para estudiar cómo se relacionan las redes funcionales con las redes estructurales, con un énfasis en cómo las áreas cerebrales dispersas se comunican unas con otras.

L'intelligence peut se définir comme une capacité mentale générale de raisonnement, de résolution de problèmes et d'apprentissage. Sa nature généraliste lui permet d'intégrer des fonctions cognitives comme la perception, l'attention, la mémoire, le langage ou l'organisation. Selon cette définition, l'intelligence peut être mesurée de façon fiable par des tests standardisés dont les scores prédisent plusieurs données sociales importantes comme le niveau d'éducation, la performance professionnelle, la santé et la longévité. Une compréhension précise des mécanismes cérébraux sous-tendant cette aptitude mentale générale pourrait bénéficier de façon significative à l'individu et à la société. Des études de neuro-imagerie structurale et fonctionnelle sont dans l'ensemble en faveur d'un réseau frontopariétal pour l'intelligence. Ce même réseau est également à la base des fonctions cognitives liées à la perception, à la mémorisation à court terme et au langage. La nature multifocale de ce réseau et son implication dans de nombreuses fonctions cognitives cadre bien avec la démarche d'ensemble de l'intelligence. Une nouvelle phase clé de la recherche commence à s'intéresser aux rapports entre les réseaux fonctionnels et les réseaux structuraux, en insistant sur la façon dont les différentes aires cérébrales communiquent entre elles.

Human intelligence: definition, measurement, and structure

Reasoning, problem solving, and learning are crucial facets of human intelligence. People can reason about virtually any issue, and many problems may be solved. Simple and highly complex behavioral repertoires can be learned throughout the lifespan. Importantly, there are widespread individual differences in the ability to reason, solve problems, and learn which lead to human differences in the general ability to cope with challenging situations. These differences: (i) become more salient as the cognitive complexity of the situation becomes greater 1 - 3 ; (ii) are stable over time 4 ; and (iii) are partially mediated by genetic factors. 5

Various definitions of intelligence tend to converge around similar notions designed to capture the essence of this psychological factor. Jensen 6 notes Carl Bereiter's definition of intelligence: “what you use when you don't know what to do” (p 111). After their extensive survey, Snyderman and Rothman 7 underscored reasoning, problem solving, and learning as crucial for intelligence. The “mainstream science on intelligence” report coordinated by Gottfredson 8 highlights reasoning, planning, solving problems, thinking abstractly, comprehending complex ideas, learning quickly, and learning from experience. The American Psychological Association (APA) report on intelligence acknowledges that “individuals differ from one another in their ability to understand complex ideas, to adapt effectively to the environment, to learn from experience, to engage in various forms of reasoning, to overcome obstacles by taking thought” (p 77). 9

Humans perceive the environment, attend to relevant stimuli, memorize episodic and semantic information, communicate, and so forth. However, these activities must be integrated in some way for: (i) adapting our behavior to the environment; (ii) selecting the most appropriate contexts; or (iii) changing the world when adaptation and selection are not an option. 10 In our view, the integration of cognitive functions and abilities is dependent on the very general mental ability we call “general intelligence” or g for short. This integration is consistent with g as ability 11 or as an emergent property of the brain. 12

Any cognitive ability refers to variations in performance on some defined class of mental or cognitive tasks ( Figure 1 ). Abilities reflect observable differences in individuals' performance on certain tests or tasks. However, this performance involves the synthesis of a variety of abilities: “spatial ability,” for instance, can be regarded as an inexact concept that has no formal scientific meaning unless it refers to the structure of abilities that compose it. The problem of defining (and measuring) intelligence is the problem of defining the constructs that underlie it and of specifying their structure. 13 - 15

For more than a century, psychologists have developed hundreds of tests for the standardized measurement of intelligence with varying degrees of reliability and validity 16 The resulting measures allowed for the organization of taxonomies identifying minor and major cognitive abilities. J. B. Carroll, 17 , 18 for example, proposed a threestratum theory of intelligence after the extensive reanalysis of more than 400 datasets with thousands of subjects from almost 20 different countries around the world. Figure 2 . shows a simplified depiction of the taxonomy of cognitive abilities.

This survey of factor analytic studies supports the view that intelligence has a hierarchical structure (ie, like a pyramid). There is strong evidence for a factor representing general intelligence (g) located at the apex of the hierarchy (stratum III). This g factor provides an index of the level of difficulty that an individual can handle in performing induction, reasoning, visualization, or language comprehension tests. At a lower order in the hierarchy (stratum II), several broad ability factors are distinguished: fluid intelligence, crystallized intelligence, general memory, visual perception, auditory perception, retrieval, or cognitive speed. Lastly, stratum I is based on specific abilities, such as induction, lexical knowledge, associative memory, spatial relations, general sound discrimination, or ideational fluency.

Factor analytic surveys reveal two main findings: (i) the g factor constitutes more than half of the total common factor variance in a cognitive test or task in samples representative of the population; and (ii) various specific cognitive abilities can be identified, including the cognitive domains of language, memory, and learning, visual perception, information processing, knowledge and so forth, indicating certain generalizations of abilities; actually, there are more than 60 specific or narrow abilities. Available test batteries (a good example would be the Wechsler Adult Intelligence Scale - WAIS) measure g in addition to several cognitive abilities and specific skills. We know how to separate these influences over cognitive performance by means of statistical analyses. There are some measures which are highly g-loaded (eg, the Vocabulary subtest of the WAIS), while others are less g-loaded (eg, the Digit Symbol Subtest of the WAIS). ( Figure 3 ). shows how gray matter correlates become more prominent with increased g loadings of the intelligence measures. Moreover, the same measure can load differently on general and specific cognitive factors/abilities depending on the sample analyzed. 19 , 20

Human intelligence and the brain

Exploring the relationships between human intelligence and the brain requires a careful consideration of the structure of human intelligence. As evident from above, when researchers state that they are measuring intelligence by means of the Standard Progressive Matrices Test (SPM - as another example) they are telling an imprecise story because the SPM measures g plus spatial and reasoning abilities plus SPM specificity. The exact combination of these “ingredients” for the analyzed sample must be computed before saying something clear about the measured performance. This requires that studies use a battery of tests rather than just one test. Although this was not usually done for the early functional imaging studies of intelligence, 21 - 25 it is now more common. 26 - 29 Results from the older and the newer studies, however, point to the importance of both whole brain and specific brain networks.

Brain size and human intelligence

Wickett et al 30 state:

“There is no longer any doubt that a larger brain predicts greater intelligence. Several research teams, using differing scan protocols, populations, and cognitive measures, have all shown that IQ and brain volume correlate at about the 0.40 level ( ...) obviously replication of this effect is no longer required. What is required now is a more fine-grained analysis of why it is that a larger brain predicts greater intelligence, and what it is about intelligence that is most directly related to brain volume” (p 1096, emphasis added).

The meta-analysis by McDaniel 31 studied the relationship between in vivo brain volume and intelligence. Thirty-seven samples comprising a total of 1530 participants were considered simultaneously. These were the main findings: (i) the average correlation is 0.33; (ii) subsets of the 37 studies that allow partitioning by gender revealed that the correlation is higher for females (0.40) than for males (0.34); and (iii) the correlation does not change across age (0.33). The report concludes that these results resolve a 169-year-old debate: it is clear that intelligence and brain volumes are positively related.

Going one step further, several studies measured the volume of regions of interest (ROIs) showing the most significant correlations (controlling for total brain volumes) in frontal, parietal, and temporal brain regions, along with the hippocampus and the cerebellum. 32 , 33 Nevertheless, regional correlations are moderate (ranging from 0.25 to 0.50) which implies that measures of total or local brain size are far from telling the whole story.

From this perspective, gray and white matter must be distinguished. In keeping with this, voxel-by-voxel (a voxel is a volume element analogous to a pixel) analyses also showed specific areas where the amount of gray and white matter was correlated with intelligence scores. 24 , 25 The amount of gray matter is considered to reflect number and density of neuronal bodies and dendritic arborization, whereas the amount of white matter is considered to capture number and thickness of axons and their degree of myelination. Gray matter could support information processing capacity, while white matter might support the efficient flow of information in the brain. Available reports are consistent with the statement that both gray and white matter volumes are positively related to intelligence, but that the latter relationship is somewhat greater (unweighted mean correlation values =.27 and .31 respectively). 34 It is noteworthy that new studies using diffusion tensor imaging (DTI), which is the best method to date for assessing white matter, have reported DTI correlations with intelligence scores (see white matter section below).

A distributed brain network for human intelligence

Jung and Haier 35 reviewed 37 structural and functional neuroimaging studies published between 1988 and 2007. Based on the commonalities found in their analysis, they proposed the Parieto-Frontal Integration Theory (PFIT), identifying several brain areas distributed across the brain. These P-FIT regions support distinguishable information processing stages ( Figure 4 ).

This is a summary of the proposed stages.

• Occipital and temporal areas process sensory information in the first processing stage: the extrastriate cortex (Brodmann areas - BAs - 18 and 19) and the fusiform gyrus (BA 37), involved with recognition, imagery and elaboration of visual inputs, as well as Wernicke's area (BA 22) for analysis and elaboration of syntax of auditory information.
• Integration and abstraction of the sensory information by parietal BAs 39 (angular gyrus), 40 (supramarginal gyrus), and 7 (superior parietal lobule) correspond to the second processing stage.
• The parietal areas interact with the frontal lobes in the third processing stage and this interaction underlies problem solving, evaluation, and hypothesis testing. Frontal BAs 6, 9, 10, 45, 46, and 47 are underscored by the model.
• The anterior cingulate (BA 32) is implicated for response selection and inhibition of alternative responses, once the best solution is determined in the previous stage.

White matter, especially the arcuate fasciculus, is thought to play a critical role in reliable communication of information across the brain processing units. Nevertheless, note that the “Geschwind area” (underlying the angular gyrus) within the arcuate fasciculus may be even more important than the entire track. 36

Frontal, parietal, temporal, and occipital areas are depicted in Figure 4. However, Jung and Haier 35 suggest that not all these areas are equally necessary in all individuals for intelligence. Discrete brain regions of the dorsolateral prefrontal cortex (BAs 9, 45, 46, and 47) and the parietal cortex (BAs 7 and 40) could be considered most important for human intelligence.

A frontoparietal network may be relevant for intelligence, but also for working memory. 37 A study by Gray et al 38 tested whether fluid or reasoning ability (Gf) was mediated by neural mechanisms supporting working memory. Sixty participants performed verbal and nonverbal working memory tasks. They had to indicate if a current item matched the item they saw 3 items previously (3-back). Brain activity was measured by event-related functional magnetic resonance imaging (fMRI). The demand for working memory varied across trials. Results showed that: (i) participants scoring higher on the Progressive Matrices Test (a measure related to fluid g - Gf) were more accurate in the 3-back task; and (ii) only lateral prefrontal and parietal regions mediated the correlation between Gf and 3-back performance.

These fMRI results are consistent with the voxel-based morphometry (VBM) study reported by Colom et al (N = 48). 39 In agreement with the well established fact that the g factor and working memory capacity are very highly correlated, 40 - 45 these researchers predicted that g and working memory would share significant common neural networks. Therefore, using a VBM approach they quantified the overlap in brain areas where regional gray matter was correlated with measures of general intelligence and working memory, finding a common neuroanatomic framework supported by frontal gray matter regions belonging to BA 10 and by the right inferior parietal lobule (BA 40). Of note, this study also showed: (i) more gray matter recruitment for the more cognitively complex tasks (= more highly g loaded); and (ii) the complex span task (backward digit span) showed more gray matter overlap with the general factor of intelligence than the simple span task (forward digit span, ( Figure 5 ). These results were interpreted after the theory proposed by Cowan, 46 namely that parietal regions support “capacity limitations,” whereas frontal areas underlie the “control of attention.”

A similar commonality between intelligence and working memory was found in animal studies. Matzel and Kolata 47 reviewed several reports in which performance of laboratory mice was measured in a variety of attention and learning tasks. These are their most prominent conclusions:

• The “positive manifold” (eg, scores on cognitive tasks of various kinds are positively correlated) found in humans also applied to mice
• Storage and processing components of working memory accounted for the strong relationship between this cognitive function and g
• Networks involved in working memory overlap with those relevant for intelligence. These findings support an evolutionary conservation process of the structure and determinants of intelligence beyond humans. 48

Giftedness has been also investigated with related findings. Lee et al 49 used an fMRI approach to investigate the neural bases of superior intelligence. Eighteen gifted and 18 nongifted adolescents were analyzed. They solved reasoning problems, having high (complex) and low (simple) loadings on g. Increased bilateral frontoparietal activations (lateral prefrontal, anterior cingulate, and posterior parietal cortices) were found for both groups, but the gifted subjects showed greater activations in the posterior parietal cortex. Furthermore, activations in BAs 7 and 40 (superior and intraparietal cortices) correlated with intelligence differences. Therefore, high intelligence was associated with increased involvement of the frontoparietal network through preferential activation of the posterior parietal regions.

Gläscher et al 28 investigated the neural substrates of g in 241 patients with focal brain damage, using voxel-based lesion-symptom mapping. Statistically significant associations between g and damage within a distributed network in frontal and parietal brain regions were found. Further, damage of white matter association tracts in frontopolar areas was also shown to be associated with differences in g. They concluded that g draws on connections between regions integrating verbal, visuospatial, working memory, and executive processes.

Going one step further, Gläscher et al 28 asked whether or not there was a neural region whose damage uniquely impacts g beyond subtests contributing to the general score. They examined this question by analyzing the nonoverlap between a disjunction of subtests and the reported lesion pattern for g. A single region was found in the left frontal pole (BA 10) showing a significant effect unique to g. This result complements the distributed nature of g and suggests a hierarchical control mechanism. This unique area for g may be involved in the allocation of the working memory resources necessary for successful performance on specific cognitive tasks. However, this finding should be placed within context since there are studies showing no decline in intelligence associated with prefrontal lobotomy, presumably including the frontopolar cortex. 35 Therefore, future studies are necessary to determine the specific necessity of the frontal poles to g. The comparison between lesion cohorts and normal cohorts must be done carefully.

The structural studies reported by Colom et al 27 and Karama et al 50 are also consistent with the P-FIT model. In the first study (N =100) the general factor of intelligence was estimated after nine tests measuring reasoning, verbal, and nonverbal intelligence. Their VBM approach revealed several clusters of voxels correlating with individual differences in g scores. The main regions included the dorsolateral prefrontal cortex, Broca's and Wernicke's areas, the somatosensory association cortex, and the visual association cortex. The design matrix in this study controlled for sex, but when total gray matter was controlled for instead of sex, significant correlations were concentrated in frontal and parietal areas only ( Figure 6 ): superior, middle, and frontal gyrus, along with the postcentral gyrus and the superior parietal lobule.

Karama et al 50 used an automated cortical thickness protocol (CIVET51) to analyze a large sample of children and adolescents representative of the population (N=216). The most consistent areas of association between g scores and cortical thickness were found in lateral prefrontal, occipital extrastriate, and parahippocampal areas. Similar to the study reported by Colom et al, 27 Karama et al 50 identified more brain regions related to g than those in the P-FIT model, likely resulting from the synthesizing nature of the P-FIT approach (ie, if all regions implicated in intelligence across all 37 studies were included, they would have numbered in the hundreds) as opposed to the experimental/exploratory approach employed by these studies.

There are three other studies applying a cortical thickness approach (the third will be discussed later). Shaw et al 52 analyzed the trajectory of change in the thickness of the cerebral cortex on a sample of 307 children and adolescents. Intelligence was measured by four subtests from the Wechsler scales (vocabulary, similarities, block design, and matrix reasoning). They found that changes in thickness are more related to intelligence than thickness itself: negative correlations were found in early childhood, whereas the correlation was positive in late adolescence (these positive correlations were identified in frontal BAs 4, 6, 8, 10, 11, and 44-46, in parietal BAs 1-3, 5, 39, 40, in temporal BAs 21, 37, and in occipital BAs 17, 18, and 19). Further, intelligence differences were associated with the trajectory of cortical development in frontal brain regions. Finally, children with higher scores on intelligence showed more change in estimated cortical thickness along the developmental process.

Narr et al 53 studied a sample of 65 participants. They found positive associations between cortical thickness and intelligence bilaterally in prefrontal BAs 10/11 and 47, as well as in posterior temporal BAs 36/37. These researchers also analyzed males and females separately, finding that males showed correlations in temporaloccipital association cortices, whereas females exhibited correlations in prefrontal and temporal association cortices. These results are not entirely consistent with the parietofrontal framework and emphasize the importance of separate analyses for males and females. 25 , 54 , 55

Functional networks and neurotransmitters

Using an fMRI approach, Bishop et al 56 reported a study based on previous evidence showing that a polymorphism (val158met) in the catechol-O-methyltransferase (COMT) gene regulates catecholaminergic signaling in prefrontal cortex. The val158 allele is associated with higher COMT activity than the met158 allele-therefore, a lesser conten of dopamine. Twenty-two participants, genotyped for the COMT val158met polymorphism, performed verbal and spatial fluid intelligence (Gf) items, classified according to their cognitive complexity, as estimated from the loadings on g (see ref 57). These researchers were particularly interested in the analysis of the frontoparietal network related to fluid intelligence (the lateral prefrontal cortex, the presupplementary motor area/anterior cingulate cortex, and the intraparietal sulcus).

Findings revealed a positive effect of COMT val allele load upon the BOLD signal in regions belonging to this brain network when items showing distinguishable cognitive complexity were compared. This result suggests that the COMT val158met polymorphism impacts on the neural network supporting fluid intelligence. The finding is a demonstration that the effect of single genes can impact blood oxygen level dependent signal as assessed by fMRI. Further evidence linking catecholamine modulation within the identified network may help explain individual differences in the neural response to high levels of cognitive complexity, irrespective of the content domain (verbal or nonverbal).

White matter

The relationship between human intelligence and the integrity of white matter has been much less investigated, although this trend is changing rapidly. Diffusion tensor imaging (DTI) is based on the diffusion of water molecules in the brain and provides information about the size, orientation, and geometry of myelinated axons. DTI can produce measures that include fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RA), and axial diffusivity (AD), which allow for the assessment of myelin and axonal integrity (see Figure 7 ).

DTI is useful for fine-grained deterministic and probabilistic tractography to capture underlying cortical connectivity patterns. This can be used for the quantitative analysis of local and global network properties using graph-theoretical approaches (eg, analysis of small-world properties). 58 , 59

Using DTI, Schmithorst et al 60 analyzed the relationship between intelligence and white matter structure. The sample comprised 47 children and adolescents (age range 5 to 18). White matter structure was studied using fractional anisotropy (FA) and mean diffusivity (MD) indices. These indices were correlated with intelligence scores obtained from the Wechsler scales. These researchers found positive correlations bilaterally for FA in white matter association areas (frontal and parietooccipital areas). These correlations were thought to reflect a positive relationship between fiber organization-density and intelligence.

Also using a DTI approach, Yu et al 61 computed correlations between the integrity of several tracts (corpus callosum, cingulum, uncinate fasciculus, optic radiation, and corticospinal tract) and intelligence. On the basis of their scores on the Wechsler scales, 79 participants were divided in two groups: average and high intelligence. White matter integrity was assessed by fractional anisotropy (FA). The results showed that high intelligence participants display more white matter integrity than average intelligence participants only in the right uncinate fasciculus. Therefore, the right uncinate fasciculus might be an important neural basis for intelligence differences. A sample of 15 participants with mental retardation was also analyzed. These participants were compared with the 79 healthy controls and they showed extensive damage in the integrity of several white matter tracts: corpus callosum, uncinate fasciculus, optic radiation, and corticospinal tract.

Tang et al 62 used both DTI and fMRI during an n-back memory task in 40 young adults who had also completed a battery of intelligence tests. Correlations between the BOLD signal obtained from the n-back task and intelligence were mainly concentrated in the right prefrontal and bilateral parietal cortices. These correlations were negative (the higher the intelligence, the lower the activation during the n-back task) which supports the efficiency model of brain function. Further, white matter tracts connecting these areas also showed correlations to g. Specifically, integrity of interhemispheric connections was positively correlated to some intelligence factors in females but negatively correlated in males.

Chiang et al 63 have reported the first study combining a genetic informative design and a DTI approach for analyzing the relationships between white matter integrity and human intelligence. Intelligence was assessed by the Multidimensional Aptitude Battery, which provides measures of general intelligence, verbal (information, vocabulary, and arithmetic), and nonverbal intelligence (spatial and object assembly). The sample comprised 23 pairs of identical twins and 23 pairs of fraternal twins. White matter integrity, quantified using FA, was used to fit structural equation models (SEM) at each point in the brain. Afterwards three-dimensional maps of heritability were generated. White matter integrity was found to be under significant genetic control in bilateral frontal, bilateral parietal, and left occipital lobes (values ranging from .55 to .85). FA measures were correlated with the estimate of general intelligence and with nonverbal intelligence in the cingulum, optic radiations, superior fronto-occipital fasciculus, internal capsule, the isthmus of the corpus callosum, and the corona radiata. Further, common genetic factors mediated the correlation between intelligence and white matter integrity which suggests a common physiological mechanism and common genetic determination.

Networks for human intelligence

As noted above, gray matter supports information processing capacity and white matter promotes efficient flow of information across the brain. Connections are relevant for intelligence and these connections might be organized in networks. From this perspective, Li et al 64 reported a study testing the hypothesis that high levels of intelligence involve more efficient information transfer in the brain. 21 , 65 , 66 Studying a sample of 79 participants, brain anatomical networks were constructed by means of diffusion tensor tractography. These networks included intrahemispheric and interhemispheric connections. Six white-matter tracts were further constructed: the genu of the corpus callosum, the body of the corpus callosum, the splenium of the corpus callosum, the cingulum, the corticospinal tract, and the inferior fronto-occipital fasciculus. Thereafter, they calculated the topological properties of the networks for every participant. The sample was divided between average and high intelligence according to scores on the Wechsler scales. Higher global efficiencies were revealed for the latter group: higher intelligence was found to display shorter characteristic path length and a higher global efficiency of the networks. This was interpreted as a characteristic of a more efficient parallel information transfer in the brain anatomy. Therefore, the efficiency of brain structural organization could be an important biological basis for human intelligence, as originally proposed by Haier et al. 21 , 66

Song et al 67 analyzed 59 adults for studying the relationships between spontaneous brain activity at rest and individual differences in intelligence. Intelligence was assessed by the Wechsler scales. Using fMRI, the bilateral dorsolateral prefrontal cortices were the seed regions for investigating the correlations across subjects between individual intelligence scores and the strength of the functional connectivity between the seed regions and the remaining brain regions. These researchers found that brain regions in which the strength of the functional connectivity significantly correlated with intelligence scores were distributed in the frontal, parietal, occipital and limbic lobes. Furthermore, functional connectivity within the frontal lobe and between the frontal and posterior brain regions predicted differences in intelligence. These results are consistent with the relevance of a network view for human intelligence.

van den Heuvel et al 68 used resting state fMRI and graph analysis for exploring the presumed organization of the brain network. Functional connections of this brain network were analyzed computing correlations among the spontaneous signals of different brain regions during rest. The sample comprised 19 subjects and intelligence was measured by the Wechsler scales. They found associations between global communication efficiency - more long-distance connections - and scores of intelligence. This was interpreted as suggesting that a difference in the efficiency with which the brain integrates information between brain regions is related to differences in human intelligence. The strongest effects were found in frontal and parietal regions. Furthermore, intelligence differences were not related to the level of local information processing (local neighborhood clustering) and to the total number of functional connections of the brain network.

Beyond these specific studies, the so-called “connectome project” deserves close attention. 69 There is strong agreement regarding the fact that the human brain comprises a wide variety of functional systems. Obtaining brain images during rest shows large-amplitude spontaneous low frequency fluctuations in the fMRI signal. These fluctuations are related across areas sharing functions and the correlations show up as an individual's functional connectome. Biswall et al 69 report findings obtained from 1414 participants from 35 laboratories. Their main results were: (i) there is a universal functional architecture; (ii) there are substantial sex differences and age-related gradients; and (iii) it is possible to establish normative maps for the functional boundaries among identified networks.

Integration of intelligence and cognitive findings

The frontoparietal network is relevant for intelligence, but also for other cognitive functions. 70 Thus, for instance, Wager and Smith 71 reported a meta-analysis of 60 positron-emission tomography (PET) and fMRI studies of working memory. The effect of three content domains (verbal, spatial, and object), three executive functions (updating, temporal order, and manipulation) along with their interactions were analyzed. Brain areas most involved in all these cognitive facets were located in the frontal and parietal lobes: (i) spatial and nonspatial contents were separated in posterior, but not anterior areas; (ii) executive manipulation evoked more frontal activations, but with some exceptions; and (iii) the parietal cortex was always implicated in executive processing. The meta-analysis by Wager, Jonides, and Reading 72 after 31 PET and fMRI studies of shifting attention also highlights this fronto-parietal network (medial prefrontal, superior and inferior parietal, medial parietal, and premotor cortices).

Similarly, Marois and Ivanoff 3 analyzed the capacity limits of information processing in the brain. Three basic limitations for perception, working memory, and action were explicitly considered. Their revision was based mainly on fMRI evidence and these were the basic conclusions: (i) perception and action limitations are related to fronto-parietal brain networks; and (ii) working memory capacity limitations are associated to parieto-ccipital brain networks. The lateral prefrontal cortex may support general target consolidation and response selection, using a flexible coding system for processing relevant information in any given task. In contrast, the lateral parietal cortex might provide support to more specific processing goals. This brain region is more sensitive to perception than to action.

Thus, core cognitive functions (especially working memory) and intelligence share a frontoparietal brain network. If this network is involved for most individuals, it could be possible to predict individual differences in intelligence based on brain data. 74 This was attempted by Choi et al 75 using structural (cortical thickness) and functional magnetic resonance imaging. Their regression model explained 50% of the variance in IQ scores. Even when this figure may be questioned on several grounds, the main approach underscores that brain images might be employed for estimating intelligence levels in some instances using a neurometric approach.

Finally, experimental confirmatory approaches should be welcomed to increase refinement of ongoing research efforts. In this regard, transcranial magnetic stimulation (TMS) may help test hypotheses aimed at determining whether or not specific brain regions are really important for understanding individual differences in human intelligence. TMS induces transient changes in brain activity noninvasively. It does this by producing changes in a magnetic field that, in turn, evoke electric currents in the brain which promote depolarization of cellular membranes. Cognitive neuroscience often relies on a correlation approach, whereas TMS allows studying (almost) causal brain-behavior relationships in higher cognitive functions. 76 , 77 The study reported by Aleman and van't Wout 78 exemplifies this approach using a working memory task (forward and backward digit span). Working memory (and intelligence) performance is partially supported by the dorsolateral prefrontal cortex. Using repetitive TMS (rTMS) - adapted in the Hz band for suppressing cognitive processing - over the right dorsolateral prefrontal cortex, a significant decrease of performance in the forward and backward digit span test was found. Thus, regional suppression (or enhancement) might be produced to experimentally test specific predictions.

Regardless of the use of exploratory (correlation) or confirmatory (experimental) approaches, we do agree with Kennedy 79 : “as with more _eras', it is the underlying technology that makes the era possible [...] new advances in acquisition, analysis, databasing, modeling, and sharing will continue to be necessary.” This is especially true for analyzing human intelligence because this psychological factor is undoubtedly rooted in widely distributed regions in the brain. Frontal and parietal lobes likely comprise crucial processing areas for intelligence, but integrity of hard connections across the entire brain or spontaneous harmonic coactivation among distant regions appear also to be relevant. Creating a comprehensive picture for what can be called “neuro-intelligence” 80 should prove as challenging as it is exciting.

Acknowledgments

RC was partly supported by grant PSI2010-20364 from the Ministerio de Ciencia e Innovación (Spain).

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Theories of Intelligence in Psychology

Learn How to Define and Test Intelligence

• What is Intelligence?
• Foundational Theories

Other Types of Intelligence

Intelligence (iq) testing, frequently asked questions.

Intelligence is one of the most talked-about subjects in psychology , but no standard definition exists. Some researchers have suggested that intelligence is a single, general ability. Other theories of intelligence hold that intelligence encompasses a range of aptitudes, skills, and talents.

How Do We Define Intelligence?

Despite substantial interest in the subject, there still isn't a consensus among experts about the components of intelligence or whether accurate measurements of intelligence are even possible.

Although contemporary definitions of intelligence vary considerably, experts generally agree that intelligence involves mental abilities such as logic, reasoning, problem-solving , and planning. Specifically, current definitions tend to suggest that intelligence is the ability to:

• Learn from experience :   The acquisition , retention, and use of knowledge is an essential component of intelligence.
• Recognize problems : To use knowledge, people first must identify the problems it might address.
• Solve problems :   People must then use what they have learned to come up with solutions to problems.

Research on intelligence plays a significant role in many areas, including educational program funding, job applicant screening, and testing to identify children who need additional academic help.

Main Theories of Intelligence in Psychology

Given the intense interest in the concept of intelligence, some of the field's greatest minds have explored it from numerous angles. Following are some of the major theories of intelligence that have emerged in the last 100 years.

Major Types of Intelligence Theories

• General intelligence
• Primary mental abilities
• Multiple intelligences
• The triarchic approach to intelligence

General Intelligence

British psychologist Charles Spearman (1863–1945) described the concept of general intelligence , or the "g factor." After using factor analysis to examine mental aptitude tests, Spearman concluded that scores on these tests were remarkably similar.

People who performed well on one cognitive test tended to perform well on other tests, while those who scored poorly on one test tended to score poorly on others. He concluded that intelligence is a general cognitive ability that researchers can measure and express numerically.

Primary Mental Abilities

Psychologist Louis L. Thurstone (1887–1955) focused on seven primary mental abilities rather than a single, general ability. These include:

• Associative memory : The ability to memorize and recall
• Numerical ability : The ability to solve mathematical problems
• Perceptual speed : The ability to see differences and similarities among objects
• Reasoning : The ability to find rules
• Spatial visualization : The ability to visualize relationships
• Verbal comprehension : The ability to define and understand words
• Word fluency : The ability to produce words rapidly

Multiple Intelligences

Among more recent ideas about intelligence is Howard Gardner's theory of multiple intelligences . He proposed that traditional IQ testing does not fully and accurately depict a person's abilities. He proposed eight different intelligences based on skills and abilities that are valued in various cultures:

• Bodily-kinesthetic intelligence : The ability to control body movements and handle objects skillfully
• Interpersonal intelligence : The capacity to detect and respond appropriately to the moods, motivations, and desires of others
• Intrapersonal intelligence : The capacity to be self-aware and in tune with inner feelings, values, beliefs, and thinking processes
• Logical-mathematical intelligence : The ability to think conceptually and abstractly, as well as discern logical or numerical patterns
• Musical intelligence : The ability to produce and appreciate rhythm, pitch, and timbre
• Naturalistic intelligence : The ability to recognize and categorize animals, plants, and other objects in nature
• Verbal-linguistic intelligence : Well-developed verbal skills and sensitivity to the sounds, meanings, and rhythms of words
• Visual-spatial intelligence : The capacity to think in images and visualize accurately and abstractly

What Kind of Intelligence Do You Have?

If you'd like to know more about your intelligence style, try our fast and free quiz to learn more about what makes you tick.

The Triarchic Approach to Intelligence

Psychologist Robert Sternberg defined intelligence as "mental activity directed toward purposive adaptation to, selection, and shaping of real-world environments relevant to one's life."

Although he agreed with Gardner that intelligence is much broader than a single, general ability, he suggested that some of Gardner's types of intelligence are better viewed as individual talents. Sternberg proposed the concept of "successful intelligence," which involves three factors:

• Analytical intelligence : The ability to evaluate information and solve problems
• Creative intelligence : The ability to come up with new ideas
• Practical intelligence : The ability to adapt to a changing environment

Of course, there are many other theories on the types of intelligence humans possess.

Fluid vs. Crystallized Intelligence

Psychologist Raymon Cattell, along with his student John Horn, created the theory of fluid vs. crystallized intelligence . Fluid intelligence involves the ability to solve new problems without relying on knowledge from previous experiences.

According to the theory, a person's fluid intelligence declines as they get older. Crystallized intelligence, on the other hand, increases with age—this type of intelligence is based on concrete facts and experiences.

Emotional Intelligence

Emotional intelligence (sometimes called EQ) was initially coined by psychologist Daniel Goleman. It refers to a person's ability to regulate emotions and use their emotions to relate to others. Signs of emotional intelligence include strong self-awareness , empathy , embracing change, and managing emotions in difficult situations.

Efforts to quantify intelligence took a significant leap forward when German psychologist William Stern first coined the term "intelligence quotient" (IQ) in the early 20th century.

Psychologist Alfred Binet developed the very first intelligence tests to help the French government identify schoolchildren who needed extra academic assistance.

Binet was the first to introduce the concept of mental age: a set of abilities that children of a certain age possess.

Since then, intelligence testing has emerged as a widely used tool, which has led to many other tests of skill and aptitude.

However, IQ testing continues to spur debate over its use, cultural biases, influences on intelligence, and even the very way we define intelligence.

How Psychologists and Psychiatrists Measure Intelligence

Experts use a variety of standardized tests to measure intelligence. Some are aptitude tests administered in a group setting, such as the Scholastic Assessment Test (SAT) and the American College Test (ACT). Others are IQ tests given to individuals.

IQ test scores average around 100. Most children with intellectual disabilities (85%) score between 55 and 70. Severe disabilities usually correspond to still lower scores.

The following is a brief history of IQ tests as they were developed:

• Binet-Simon intelligence scale : This was the first IQ test ever made and was developed in 1905 by Alfred Binet and Theodore Simon.
• Stanford-Binet IQ test : This was psychologist Lewis Terman's adaptation of the Binet-Simon test. Scores are based on a person's mental age divided by their chronological age (mental age/chronological age x 100).
• Wechsler Adult Intelligence Scale (WAIS) : This was the first intelligence test for adults, developed by David Wechsler in 1939. It was the first to use standardized normal distribution in scoring and is commonly used today. It is divided into verbal and performance measures. Like most modern tests, it scores on a bell curve.

Other tests that psychologists and psychiatrists use today include the Woodcock-Johnson Tests of Cognitive Abilities, the Kaufman Assessment Battery for Children, the Cognitive Assessment System, and the Differential Ability Scale.

Questions About IQ Testing

The study of the human mind is complex, in part because the most important tool in the effort is the same as the subject itself.

As humans, researchers bring not only their knowledge and expertise but also their biases, experiences, cultural backgrounds, and beliefs to the table; like all scientific experts, they must combat their own humanness to strive for objectivity.

In addition, there's the sheer complexity of the human mind and the challenges of measuring a trait with so many conflicting definitions and nuances. No single standard for intelligence or its quantification exists as yet.

It's no surprise, then, that important questions about intelligence and IQ testing remain unanswered, at least in part. Some of these include:

• Are intelligence tests biased?
• Is intelligence a single ability, or does it involve multiple skills and abilities?
• Is intelligence inherited, or does the environment play a more significant role?
• What do intelligence scores predict, if anything?

To explore these questions, psychologists continue to research the nature, influences, and effects of intelligence. Their ongoing findings resonate across society, from education and the workplace to medical and behavioral diagnostic and therapeutic approaches.

Final Thoughts

Despite considerable debate, no definitive conceptualization of intelligence has emerged in the field of psychology. Today, psychologists often account for the many theoretical viewpoints when discussing intelligence and acknowledge that the debate is ongoing.

Early theories of intelligence focused on logic, problem-solving abilities, and critical thinking skills. In 1920, Edward Thorndike postulated three kinds of intelligence: social, mechanical, and abstract. Building on this, contemporary theories such as that proposed by Harvard psychologist  Howard Gardner tend to break intelligence into separate categories (e.g., emotional, musical, spatial, etc.).

Emotional intelligence (EI or EQ) is the ability to perceive, control, and evaluate emotions. Some researchers suggest that emotional intelligence can be learned and strengthened; others claim it's an inborn characteristic. Generally, EI is measured by self-report and ability tests.

Fluid intelligence is the ability to apply logic and think flexibly. Raymond Cattell defined fluid intelligence as "the ability to perceive relationships independent of previous specific practice or instruction concerning those relationships."

Intelligence develops and changes throughout life, generally peaking in midlife . A study published in  Psychological Science suggested that certain elements of fluid intelligence peak as late as 40.

Jaarsveld S, Lachmann T. Intelligence and creativity in problem solving: The importance of test features in cognition research .  Front Psychol . 2017;8. doi:10.3389/fpsyg.2017.00134

Spearman C. "General intelligence," objectively determined and measured .  The American Journal of Psychology . 1904;15(2):201. doi:10.2307/1412107

Thurstone LL.  Primary Mental Abilities . University of Chicago Press; 1938.

Gardner H. Frames of Mind: The Theory of Multiple Intelligences . Basic Books; 2011.

Sternberg RJ. Beyond IQ: A Triarchic Theory of Human Intelligence . CUP Archive; 1985.

Horn JL, Cattell RB. Refinement and test of the theory of fluid and crystallized general intelligences .  Journal of Educational Psychology . 1966;57(5):253-270. doi:10.1037/h0023816

Ghisletta P, Rabbitt P, Lunn M, Lindenberger U.  Two thirds of the age-based changes in fluid and crystallized intelligence, perceptual speed, and memory in adulthood are shared .  Intelligence . 2012;40(3):260-268. doi:10.1016/j.intell.2012.02.008

Barbey AK.  Network neuroscience theory of human intelligence .  Trends Cogn Sci (Regul Ed) . 2018;22(1):8-20. doi:10.1016/j.tics.2017.10.001

Drigas AS, Papoutsi C.  A new layered model on emotional intelligence . Behav Sci (Basel). 2018;8(5):45. doi:10.3390/bs8050045

Nicolas S, Andrieu B, Croizet JC, Sanitioso RB, Burman JT. Sick? Or slow? On the origins of intelligence as a psychological object .  Intelligence . 2013;41(5):699-711. doi:10.1016/j.intell.2013.08.006

HealthyChildren.org. Children with intellectual disabilities . American Academy of Pediatrics.

Richardson K, Norgate SH. Does IQ really predict job performance?   Applied Developmental Science . 2015;19(3):153-169. doi:10.1080/10888691.2014.983635

Hartshorne JK, Germine LT.  When does cognitive functioning peak? The asynchronous rise and fall of different cognitive abilities across the life span .  Psychol Sci . 2015;26(4):433-443. doi:10.1177/0956797614567339

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

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Human intelligence is, generally speaking, the mental quality that consists of the abilities to learn from experience, adapt to new situations, understand and handle abstract concepts, and use knowledge to control an environment. However, the question of what, exactly, defines human intelligence is contested, particularly among researchers of artificial intelligence , though there is broader agreement that intelligence consists of multiple processes, rather than being a single ability.

There is a long history of efforts to measure human intelligence. Modern theories of measurement can be traced to the French psychologist Alfred Binet and the English scientist Francis Galton , both of whom were researching intelligence during the second half of the 19th century. Standardized intelligence tests became popular during the 20th century, though their shortcomings have been extensively documented.

human intelligence , mental quality that consists of the abilities to learn from experience, adapt to new situations, understand and handle abstract concepts, and use knowledge to manipulate one ’s environment .

Much of the excitement among investigators in the field of intelligence derives from their attempts to determine exactly what intelligence is. Different investigators have emphasized different aspects of intelligence in their definitions. For example, in a 1921 symposium the American psychologists Lewis Terman and Edward L. Thorndike differed over the definition of intelligence, Terman stressing the ability to think abstractly and Thorndike emphasizing learning and the ability to give good responses to questions. More recently, however, psychologists have generally agreed that adaptation to the environment is the key to understanding both what intelligence is and what it does. Such adaptation may occur in a variety of settings: a student in school learns the material he needs to know in order to do well in a course; a physician treating a patient with unfamiliar symptoms learns about the underlying disease; or an artist reworks a painting to convey a more coherent impression. For the most part, adaptation involves making a change in oneself in order to cope more effectively with the environment, but it can also mean changing the environment or finding an entirely new one.

Effective adaptation draws upon a number of cognitive processes, such as perception , learning , memory , reasoning , and problem solving . The main emphasis in a definition of intelligence, then, is that it is not a cognitive or mental process per se but rather a selective combination of these processes that is purposively directed toward effective adaptation. Thus, the physician who learns about a new disease adapts by perceiving material on the disease in medical literature, learning what the material contains, remembering the crucial aspects that are needed to treat the patient, and then utilizing reason to solve the problem of applying the information to the needs of the patient. Intelligence, in total, has come to be regarded not as a single ability but as an effective drawing together of many abilities. This has not always been obvious to investigators of the subject, however; indeed, much of the history of the field revolves around arguments regarding the nature and abilities that constitute intelligence.

Theories of intelligence

Theories of intelligence, as is the case with most scientific theories, have evolved through a succession of models. Four of the most influential paradigms have been psychological measurement , also known as psychometrics; cognitive psychology , which concerns itself with the processes by which the mind functions; cognitivism and contextualism, a combined approach that studies the interaction between the environment and mental processes; and biological science , which considers the neural bases of intelligence. What follows is a discussion of developments within these four areas.

Intelligence

IQ, Giftedness

Reviewed by Psychology Today Staff

Reading a road map upside-down, excelling at chess, and generating synonyms for "brilliant" may seem like three different skills. But each is thought to be a measurable indicator of general intelligence or "g," a construct that includes problem-solving ability, spatial manipulation, and language acquisition that is relatively stable across a person's lifetime.

IQ—or intelligence quotient—is the standard most widely used to assess general intelligence. IQ tests seek to measures a variety of intellectual skills that include verbal, non-verbal and spatial. Any person from any walk of life can be highly intelligent, and scoring high on one sub-test tends to correlate with high scores in other tests, though this is not always the case. IQ tests compare a person's performance with that of other people who are the same age—what’s known as a normative sample.

Research has shown that IQ is generally strongly correlated with positive life outcomes, including health and longevity, job performance, and adult income. It is also protective in ways that are not fully understood: People with high IQs seem to be at an advantage in coping with traumatic events—they are less likely to develop full-blown PTSD and more capable of overcoming it when they do—and may experience less rapid decline during the course of Alzheimer's Disease.

• The Roots of Human Intelligence
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There may be. Research suggest that people who are high in the personality trait of openness tended to be more mentally flexible and verbally fluent and more likely to take creative, unconventional approaches to solving problems. Extraverted people were also more likely to score higher on test of verbal fluency because they tended to talk more, and be less concerned about mistakes. And people higher in the trait of conscientiousness tend to perform better on memory tasks because they’re generally better organized and willing to work harder.

No, not even close. This pervasive pop-culture myth—one survey found that 50 percent of science teachers believed it was true—has no basis in reality. We use 100 percent of our brains every day, as is clearly shown by functional magnetic resonance imaging scans. Neurons only make up 10 percent of the cells in our brains but the other 90 percent work full-time, maintaining homeostasis, providing structural support, and removing pathogens. The source of the famous notion is pioneering psychologist William James, who once write that “we are making use of only a small part of our possible mental and physical resources,” and he was right—but our untapped potential has little to do with our brain cells.

No, a larger brain does not make a person more intelligent . Some studies have suggested, for example, that a larger brain may contribute as much as 6 percent boost to one’s intelligence, but this research has come into question, and some experts doubt that a larger brain would bring any advantages because it would necessarily demand greater energy consumption, potentially contributing a drag on a person’s resources. Considering all animals, including humans, there is a theory that the size of a creature’s brain relative the size of their body may confer a higher level of intelligence, though—and human brains constitute up a higher ratio of our body size than do the brains of many other animals.

The theory known as “the Flynn effect” maintains that average IQ scores have and will continue to rise over time, primarily due to changes in our environment—better diet and greater access to education and information, for example. But in recent years, IQ scores appear to declining —one-half to two points per decade—possibly a reflection of a decline in those same environmental factors.

In the early 1980s, Harvard researcher Howard Gardner proposed that, along with IQ, there may be multiple kinds of intelligence that people possess in varying quantities, including visual-spatial, logical-mathematical, and interpersonal (emotional) intelligence. According to this theory, someone high in interpersonal intelligence would likely excel at cooperating within a group, while someone with high levels of logical-mathematical intelligence would have a heightened capacity to understand numbers, patterns, and logic. But while the concept has gained much public attention — and is often used as part of personality or employment tests—many researchers dispute the idea of different intelligences and have criticized Gardner's theory, criteria, and research designs. For example, emotional intelligence cannot be reliably measured through testing as general intelligence can, the critics argue, and so it lacks the power to explain differences between people.

For more, see Emotional Intelligence .

A critical prerequisite for intellectual growth is the idea that one can gain mastery and improve on native ability. While one can indeed improve memory and problem-solving abilities over time via practice or environmental pressure, this does not mean that one is becoming "more" intelligent. IQ scores do not fluctuate markedly over the course of a person's lifetime, and they tend to consistently correlate with other tests, such as the SAT. Many supplements and computer programs are marketed as brain boosters, but there is little long-term evidence to support those claims.

One reason people attend, and stay in, school through high school, college, and beyond, is to become more intelligent. And while additional years of schooling should increase one’s store of general knowledge and career prospects, until recently research had not concluded that formal education also increased one’s IQ. But then a meta-analysis determined that each additional year of schooling appeared to raise IQ by one to five points. Exactly how schooling boosts IQ is not clear, though, nor is whether or how the effect accumulates over many years of education. But experts point to the study as a sign of a more crucial truth: that an individual’s intelligence can change over time.

The right ones seem to be able to. Successful players of games requiring strategy, creativity , and teamwork , research finds, tend to have a higher IQ than others. A similar connection between IQ and gaming success was not found in studies of first-person shooter-type games that rely on hand-eye coordination. But other studies find that playing certain games can actually help boost IQ. Studies that involved popular puzzle-based strategy games, particularly those involving complex, changing environments, led to gains in problem solving, spatial skills, and persistence. Significantly, such results were not found in studies of so-called “brain-training” games marketed as cognitive boosters.

A growing body of research supports the idea that exercise can help boost cognition, especially moderate-to-vigorous aerobic exercise. In one example, researchers found that, for older people, time spent in moderate-to-vigorous cardiovascular exercise was positively correlated with increases in “fluid” intelligence—processing speed, memory, and reasoning. In the same study, sedentary time was correlated with boosts in “crystallized” intelligence, such as vocabulary development. Light physical activity, however, provided little cognitive benefit.

Stimulants like methylphenidate ( Ritalin ) and mixed amphetamine salts ( Adderall ) deliver proven benefits for many people with ADHD. But the question of whether such stimulants could improve cognitive ability is highly controversial. Recent research, however, suggests that the drugs do not deliver any cognitive enhancement—aside from an increase in confidence , interest, and energy in people’s tasks. A boost in optimism when tackling a difficult assignment is not the same as a boost in intelligence, but it can help deliver better results by motivating people to deploy their existing cognitive resources more vigorously.

While most research finds very little difference in the mean IQ between men and women,  men are overrepresented at the tails of the distribution. This means that more men than women have scores that reflect severe retardation, and more men than women score in the profoundly gifted or "genius" range. Research shows that men are a lot more likely than women to overstate their intelligence. In one example, 71 percent of men claimed to be smarter than the average person, compared to just 59 percent of women.

There’s a persistent stereotype that people high in the trait of psychopathy are smarter than most others because they are skilled at both presenting a false façade to potential victims and at manipulating targets into doing what they want those people to do. But research shows that this is not the case. In fact, some studies find, psychopaths are generally less intelligent than others, particularly so when it comes to capabilities like recognizing emotions in others. So why do they seem so intelligent and devious? Researchers suggest that it’s because they constantly target people with schemes, to the point that even if their percentage of success is quite low, they do occasionally rope in a target.

No, but many become obsessed with the idea that they could be. Studies of narcissism have found that a belief in their intellectual superiority is often crucial to their identity . Narcissists of the type known as grandiose are highly likely to believe they are smarter than other people; some place an especially high value on IQ testing. Vulnerable narcissists, on the other hand, who tend to be more introverted, insecure, and neurotic , are not as likely to believe that they are smarter than others, but they are more likely than others to find taking intelligence tests to be highly stressful .

It has long been believed that left-handed people are smarter than right-handers, but research does not support the notion. In fact, a meta-analysis of studies including more than 20,000 people found that right-handers had a slightly higher IQ, on average, than left-handers, but the difference was not significant.

This is emerging as a core philosophical question as AI systems increase in power and humans become more concerned about how many aspects of work, decision-making , and even creative production could eventually be turned over to computer intelligence. But there are some tasks humans perform far better, such as image recognition, and humans can also be seen as more flexible and adaptive learners. Some argue that the human propensity to ask original questions sets us apart from machine intelligence, along with the ability to leverage others people’s intelligence while solving problems together.

The vast majority of people claim that they find intelligence to be among the most desirable traits in a potential romantic partner. As with other favorable traits, though, this appeal most strongly influences initial interest in a new partner. Once people begin dating, other factors like personality and conflict style play important roles in determining whether a couple will stay together. But for a certain group, intelligence is their primary erotic turn-on . Some research suggests that these individuals, known as sapiosexuals , may represent a distinct sexual orientation . Interestingly, whether one finds intelligence to be a turn-on does not seem to be determined by one’s own level of intelligence. But for sapiosexuals, looks and even gender may not be as vital a factor in sexual attraction as intelligence.

Generally, yes. Studies of adolescents found that more intelligent individuals were more well-liked by peers than others—although other research finds that more intelligent people tend to like fewer people than others, and to prefer being with other intelligent people. In the dating pool, smarter people may be at an advantage because others’ preference for being with smart people is strongest at the beginning of relationships.

Generally, it’s an advantage, although some research suggests that the most intelligent people may be at a disadvantage . When people were asked to consider whether they would want to date people in different percentiles of intelligence, the favorability rankings increased steadily from the 50th percentile to the 90th, at which point interest declined. This research is consistent with other findings that even the most appealing traits tend not be desired in the extreme.

In surveys, men and women both claim that they are at least as attracted to intelligence as they are to good looks. In practice, especially for men, that is not always the case. The idea that highly intelligent women may be at a disadvantage in the dating pool , research suggests, is no myth: Men tend to shy away from women who are clearly more intelligent than they are. (Women are less likely to have the same reaction to intelligent men.) Experts suggest that intelligent women avoid dumbing themselves down to attract a partner or going out of their way to support a partner’s ego, as in the end those strategies are likely to lead to unfulfilling relationships.

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61 intriguing psychology research topics to explore

Last updated

11 January 2024

Reviewed by

Brittany Ferri, PhD, OTR/L

Short on time? Get an AI generated summary of this article instead

Psychology is an incredibly diverse, critical, and ever-changing area of study in the medical and health industries. Because of this, it’s a common area of study for students and healthcare professionals.

We’re walking you through picking the perfect topic for your upcoming paper or study. Keep reading for plenty of example topics to pique your interest and curiosity.

• How to choose a psychology research topic

Exploring a psychology-based topic for your research project? You need to pick a specific area of interest to collect compelling data. 

Use these tips to help you narrow down which psychology topics to research:

Focus on a particular area of psychology

The most effective psychological research focuses on a smaller, niche concept or disorder within the scope of a study. 

Psychology is a broad and fascinating area of science, including everything from diagnosed mental health disorders to sports performance mindset assessments. 

This gives you plenty of different avenues to explore. Having a hard time choosing? Check out our list of 61 ideas further down in this article to get started.

Read the latest clinical studies

Once you’ve picked a more niche topic to explore, you need to do your due diligence and explore other research projects on the same topic. 

This practice will help you learn more about your chosen topic, ask more specific questions, and avoid covering existing projects. 

For the best results, we recommend creating a research folder of associated published papers to reference throughout your project. This makes it much easier to cite direct references and find inspiration down the line.

Find a topic you enjoy and ask questions

Once you’ve spent time researching and collecting references for your study, you finally get to explore. 

Whether this research project is for work, school, or just for fun, having a passion for your research will make the project much more enjoyable. (Trust us, there will be times when that is the only thing that keeps you going.) 

Now you’ve decided on the topic, ask more nuanced questions you might want to explore. 

If you can, pick the direction that interests you the most to make the research process much more enjoyable.

• 61 psychology topics to research in 2024

Need some extra help starting your psychology research project on the right foot? Explore our list of 61 cutting-edge, in-demand psychology research topics to use as a starting point for your research journey.

• Psychology research topics for university students

As a university student, it can be hard to pick a research topic that fits the scope of your classes and is still compelling and unique. 

Here are a few exciting topics we recommend exploring for your next assigned research project:

Mental health in post-secondary students

Seeking post-secondary education is a stressful and overwhelming experience for most students, making this topic a great choice to explore for your in-class research paper. 

Examples of post-secondary mental health research topics include:

Student mental health status during exam season

Mental health disorder prevalence based on study major

The impact of chronic school stress on overall quality of life

The impacts of cyberbullying

Cyberbullying can occur at all ages, starting as early as elementary school and carrying through into professional workplaces. 

Examples of cyberbullying-based research topics you can study include:

The impact of cyberbullying on self-esteem

Common reasons people engage in cyberbullying 

Cyberbullying themes and commonly used terms

Cyberbullying habits in children vs. adults

The long-term effects of cyberbullying

• Clinical psychology research topics

If you’re looking to take a more clinical approach to your next project, here are a few topics that involve direct patient assessment for you to consider:

Chronic pain and mental health

Living with chronic pain dramatically impacts every aspect of a person’s life, including their mental and emotional health. 

Here are a few examples of in-demand pain-related psychology research topics:

The connection between diabetic neuropathy and depression

Neurological pain and its connection to mental health disorders

Efficacy of meditation and mindfulness for pain management

The long-term effects of insomnia

Insomnia is where you have difficulty falling or staying asleep. It’s a common health concern that impacts millions of people worldwide. 

This is an excellent topic because insomnia can have a variety of causes, offering many research possibilities. 

Here are a few compelling psychology research topics about insomnia you could investigate:

The prevalence of insomnia based on age, gender, and ethnicity

Insomnia and its impact on workplace productivity

The connection between insomnia and mental health disorders

Efficacy and use of melatonin supplements for insomnia

The risks and benefits of prescription insomnia medications

Lifestyle options for managing insomnia symptoms

The efficacy of mental health treatment options

Management and treatment of mental health conditions is an ever-changing area of study. If you can witness or participate in mental health therapies, this can make a great research project. 

Examples of mental health treatment-related psychology research topics include:

The efficacy of cognitive behavioral therapy (CBT) for patients with severe anxiety

The benefits and drawbacks of group vs. individual therapy sessions

Music therapy for mental health disorders

Electroconvulsive therapy (ECT) for patients with depression 

• Controversial psychology research paper topics

If you are looking to explore a more cutting-edge or modern psychology topic, you can delve into a variety of controversial and topical options:

The impact of social media and digital platforms

Ever since access to internet forums and video games became more commonplace, there’s been growing concern about the impact these digital platforms have on mental health. 

Examples of social media and video game-related psychology research topics include:

The effect of edited images on self-confidence

How social media platforms impact social behavior

Video games and their impact on teenage anger and violence

Digital communication and the rapid spread of misinformation

The development of digital friendships

Psychotropic medications for mental health

In recent years, the interest in using psychoactive medications to treat and manage health conditions has increased despite their inherently controversial nature. 

Examples of psychotropic medication-related research topics include:

The risks and benefits of using psilocybin mushrooms for managing anxiety

The impact of marijuana on early-onset psychosis

Childhood marijuana use and related prevalence of mental health conditions

Ketamine and its use for complex PTSD (C-PTSD) symptom management

The effect of long-term psychedelic use and mental health conditions

• Mental health disorder research topics

As one of the most popular subsections of psychology, studying mental health disorders and how they impact quality of life is an essential and impactful area of research. 

While studies in these areas are common, there’s always room for additional exploration, including the following hot-button topics:

Anxiety and depression disorders

Anxiety and depression are well-known and heavily researched mental health disorders. 

Despite this, we still don’t know many things about these conditions, making them great candidates for psychology research projects:

Social anxiety and its connection to chronic loneliness

C-PTSD symptoms and causes

The development of phobias

Obsessive-compulsive disorder (OCD) behaviors and symptoms

Depression triggers and causes

Self-care tools and resources for depression

The prevalence of anxiety and depression in particular age groups or geographic areas

Bipolar disorder

Bipolar disorder is a complex and multi-faceted area of psychology research. 

Use your research skills to learn more about this condition and its impact by choosing any of the following topics:

Early signs of bipolar disorder

The incidence of bipolar disorder in young adults

The efficacy of existing bipolar treatment options

Bipolar medication side effects

Cognitive behavioral therapy for people with bipolar 

Schizoaffective disorder

Schizoaffective disorder is often stigmatized, and less common mental health disorders are a hotbed for new and exciting research. 

Here are a few examples of interesting research topics related to this mental health disorder:

The prevalence of schizoaffective disorder by certain age groups or geographic locations

Risk factors for developing schizoaffective disorder

The prevalence and content of auditory and visual hallucinations

Alternative therapies for schizoaffective disorder

• Societal and systematic psychology research topics

Modern society’s impact is deeply enmeshed in our mental and emotional health on a personal and community level. 

Here are a few examples of societal and systemic psychology research topics to explore in more detail:

Access to mental health services

While mental health awareness has risen over the past few decades, access to quality mental health treatment and resources is still not equitable. 

This can significantly impact the severity of a person’s mental health symptoms, which can result in worse health outcomes if left untreated. 

Explore this crucial issue and provide information about the need for improved mental health resource access by studying any of the following topics:

Rural vs. urban access to mental health resources

Access to crisis lines by location

Wait times for emergency mental health services

Inequities in mental health access based on income and location

Insurance coverage for mental health services

Systemic racism and mental health

Societal systems and the prevalence of systemic racism heavily impact every aspect of a person’s overall health.

Researching these topics draws attention to existing problems and contributes valuable insights into ways to improve access to care moving forward.

Examples of systemic racism-related psychology research topics include: 

Access to mental health resources based on race

The prevalence of BIPOC mental health therapists in a chosen area

The impact of systemic racism on mental health and self-worth

Racism training for mental health workers

The prevalence of mental health disorders in discriminated groups

LGBTQIA+ mental health concerns

Research about LGBTQIA+ people and their mental health needs is a unique area of study to explore for your next research project. It’s a commonly overlooked and underserved community.

Examples of LGBTQIA+ psychology research topics to consider include:

Mental health supports for queer teens and children

The impact of queer safe spaces on mental health

The prevalence of mental health disorders in the LGBTQIA+ community

The benefits of queer mentorship and found family

Substance misuse in LQBTQIA+ youth and adults

• Collect data and identify trends with Dovetail

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REVIEW article

Cognitive psychology-based artificial intelligence review.

• 1 School of Information Science and Technology, Northwest University, Xi’an, China
• 2 Medical Big Data Research Center, Northwest University, Xi’an, China
• 3 School of Mathematics, Northwest University, Xi’an, China

Most of the current development of artificial intelligence is based on brain cognition, however, this replication of biology cannot simulate the subjective emotional and mental state changes of human beings. Due to the imperfections of existing artificial intelligence, this manuscript summarizes and clarifies that artificial intelligence system combined with cognitive psychology is the research direction of artificial intelligence. It aims to promote the development of artificial intelligence and give computers human advanced cognitive abilities, so that computers can recognize emotions, understand human feelings, and eventually achieve dialog and empathy with humans and other artificial intelligence. This paper emphasizes the development potential and importance of artificial intelligence to understand, possess and discriminate human mental states, and argues its application value with three typical application examples of human–computer interaction: face attraction, affective computing, and music emotion, which is conducive to the further and higher level of artificial intelligence research.

Introduction

At present, in the development of artificial intelligence (AI), the scientific community is mostly based on brain cognition research ( Nadji-Tehrani and Eslami, 2020 ), which is to reproduce the real physiological activities of our human brain through computer software. This replication of the biology of the human brain cannot well simulate the subjective psychological changes ( Zador, 2019 ). For example, in terms of memory, human memory forgetting is non-active, and the more we want to forget the more memorable it becomes, while machine forgetting is an active deletion, which deviates from our psychological expectations. In the process of promoting the progress of artificial intelligence, psychology and its derived philosophy of mind play an important role directly or indirectly, can be considered as one of the fundamental supporting theories of AI. For example: The current reinforcement learning theory in AI is inspired by the behaviorist theory in psychology, i.e., how an organism gradually develops expectations of stimuli in response to rewarding or punishing stimuli given by the environment, resulting in habitual behavior that yields maximum benefit. The current challenges faced by the artificial intelligence community – the emotional response of artificial intelligence machines, decision making in ambiguous states also need to rely on breakthroughs in the corresponding fields of psychology. Psychology and its derived philosophy of mind can be considered as one of the fundamental support theories for artificial intelligence ( Miller, 2019 ). Cognitive psychology is mainly a psychological science that studies the advanced mental processes of human cognition, including the degree of thinking, deciding, reasoning, motivation and emotion. The most important feature that distinguishes humans from machines is that humans process external input by feeding back different attitudes toward things through our already internalized knowledge units about the external world, stimulating different subjective emotional orientations such as satisfaction, dissatisfaction, love, dislike and so on. These labeled emotional traits are generated by human cognitive psychology. By measuring subjective emotional changes, the internal knowledge structure is updated and the artificial intelligence machine is guided to re-learn, so that human attitudes, preferences and other subjective emotional experiences are given in AI ( Kriegeskorte and Douglas, 2018 ; Pradhan et al., 2020 ).

Research on artificial intelligence is still in the developmental stage in terms of simulating human memory, attention, perception, knowledge representation, emotions, intentions, desires, and other aspects ( Shi and Li, 2018 ). As the existing AI is not perfect, the AI system combined with cognitive psychology is the research direction of AI: Promote the development of artificial intelligence, endow the computer with the ability to simulate the advanced cognition of human beings, and carry out learning and thinking, so that computers can recognize emotions, understand human feelings, and finally achieve dialog and empathy with humans and other AI.

In terms of existing research results and methods, artificial intelligence combines new theories and methods such as psychology, brain science and computer science to conduct artificial intelligence machine simulation on people’s psychological activities, reproduce people’s psychology, integrate and promote each other, and jointly create more universal and autonomous artificial intelligence, which can better realize human–computer interaction ( Yang et al., 2018 ) and further improve the level of social intelligence. At the same time, with the development of psychology, the scope of research and the choice of research objects are more extensive and universal, making artificial intelligence products have the conditions for rapid penetration into the field of psychology, resulting in research products such as facial expression-based emotion recognition system, public opinion analysis based on big data analysis technology, intelligent medical image grading or diagnosis, suicide early warning system and intelligent surveillance management system, which in turn promotes the development of psychology and shortens the research cycle of psychology ( Branch, 2019 ).

The review of artificial intelligence based on cognitive psychology at this stage is not comprehensive enough. This manuscript does the following: (a) introduce the current situation and progress of artificial intelligence research on cognitive psychology in recent years; (b) analyze the experimental data on the application examples of cognitive psychology in artificial intelligence; (c) summarize and outlook the related development trend.

Research status

Research related to artificial intelligence in cognitive psychology is trending in recent years. In the mid-1980s, the term “Kansei Engineeirng” was introduced in the Japanese science and technology community ( Ali et al., 2020 ). They interpret sensibility as human psychological characteristics, study people’s perceptual needs with engineering methods, and then conduct in-depth research on people’s perceptual information, and the scope of their research is the human psychological perceptual activities.

Professor Wang Zhiliang of University of Science and Technology Beijing proposed the concept of “artificial psychology” on this basis: The artificial psychological theory is to use the method of information science to realize the more comprehensive content of people’s psychological activities. He broadened the range of psychological characteristics involved in “Kansei Engineeirng,” including low-level psychological activities and high-level processes of psychological activities. It is the reflection of human brain on objective reality, which makes artificial psychology have a new meaning and broader content.

Minsky, one of the founders of artificial intelligence, proposed the theory of “society of mind” in his 1985 monograph “The Society of Mind” ( Auxier, 2006 ), which attempts to combine the approaches of developmental psychology, dynamic psychology and cognitive psychology with the ideas of artificial intelligence and computational theory. Since then, the research on endowing the computer with emotional ability and enabling the computer to understand and express emotions has set off an upsurge in the computer field.

In 1978, deepmind team put forward the theory of mind ( Rabinowitz et al., 2018 ). In a broad sense, it refers to the ability of human beings to understand the psychological state of themselves and others, including expectations, beliefs and intentions, and to predict and explain other people’s behaviors based on this. In 2017, in the case study of deepmind team, the research team selected “shape preference” as the entry point for detecting neural networks. It found that, like human beings, the network’s perception of shape exceeded its preference for color and material, which proved that neural networks also have “shape preference” ( Ritter et al., 2017 ). In 2018, the Deepmind team open sourced the simulation psychology laboratory Psychlab, which uses knowledge in cognitive psychology and other fields to study the behavior of artificial agents in controlled environments, thereby simulating human behavior ( Leibo et al., 2018 ).

In 2020, Taylor incorporated cognitive psychology into the emerging field of explainable artificial intelligence (XAI) with the aim of improving the interpretability, fairness, and transparency of machine learning. Figure 1 shows the evolution of AI in cognitive psychology ( Taylor and Taylor, 2021 ).

Figure 1. The evolution of artificial intelligence in cognitive psychology.

Example of cognitive psychological artificial intelligence applications

Cognitive psychology has been very instructive for the development of AI, and current AI design makes extensive reference to human cognitive models. The process of human mental activity is simulated in various aspects such as attention, encoding, and memory. Cognitive psychological artificial intelligence has been researched in many fields. In this manuscript, we study the basic contents and latest progress of psychology and brain science, and systematically analyze and summarize three typical application scenarios: face attraction, affective computing, and music emotion. These examples guide the learning of AI through the higher mental processes of human cognition, including subjective mental orientations such as thinking and emotion. Artificial intelligence is trained to recognize emotions, understand human feelings, and replicate the human psyche, which in turn accelerates research in cognitive psychology.

Face attraction

Different aesthetic judgments of human faces are one of the most common manifestations of human visual psychology, which is an important source of social emotion generation and plays a role in human social interaction and communication ( Han et al., 2020 ). In daily life, most people think that beauty is a subjective feeling, however, scientists have broken the long-held belief that beauty lacks objectivity and found a high degree of consistency in human perception of facial beauty across race, age, gender, social class, and cultural background. This observation also suggests that face attractiveness reflects to some extent general human psychological commonalities.

SCUT-FBP5500, a database for face attractiveness prediction, was collected and released by the Human–Computer Interaction Laboratory of South China University of Technology. The dataset has 5,500 face frontal photos with different attributes (male/female, age and so on) and different feature labels including face feature point coordinates, face value score (1∼5), face value score distribution and so on. These mental preference features were experimentally used as training data to form mental state embeddings. Then different computer models (AlexNet, ResNet-18, ResNeXt-50) were used for classification, regression and ranking to form a deep learning-based face attractiveness template ( Huang, 2017 ). Evaluate the benchmark according to various measurement indicators, including Pearson correlation coefficient (PC), maximum absolute error (MAE) and root mean square error (RMSE) evaluation model. We used the five-fold method to analyze the performance of the face attractiveness templates under different computer models, and found that the Pearson correlation coefficient was above 0.85, the maximum absolute error was around 0.25, and the root mean square error was between 0.3 and 0.4 ( Liang et al., 2018 ).

Elham Vahdati proposes and evaluates a face facial attractiveness prediction method using facial parts as well as a multi-task learning scheme. First, face attractiveness prediction is performed using a deep convolutional neural network (CNN) pre-trained on a massive face dataset to automatically learn advanced face representations. Next, the deep model is extended to other facial attribute recognition tasks using a multi-task learning scheme to learn the best shared features for three related tasks (such as facial beauty assessment, gender recognition, and race recognition). To further improve the accuracy of the attractiveness computation, specific regions of the face image (such as left eye, nose, and mouth) as well as the entire face are fed into a multi-stream CNN (such as three dual-stream networks). Each dual-stream network uses partial features of the face and the full face as input. Extensive experiments were conducted on the SCUT-FBP5500 benchmark dataset, with a significant improvement in accuracy ( Vahdati and Suen, 2021 ).

Irina Lebedeva, Fangli Ying learned a large number of aesthetic preferences shared by many people during the meta-training process. The model is then used on new individuals with a small sample of rated images in the meta-testing phase. These experiments were conducted on a facial beauty dataset that included faces of different races, genders, and age groups and were scored by hundreds of volunteers with different social and cultural backgrounds. The results show that the proposed method is effective in learning individual beauty preferences from a limited number of annotated images and outperforms existing techniques for predicting facial beauty in terms of quantitative comparisons ( Lebedeva et al., 2022 ).

We summarize the theoretical concepts of artificial intelligence based on cognitive psychology, and do relevant research on this basis. Since the database of face attractiveness needs to be characterized by large samples, diversity and universality, in 2016, we built a Chinese face database containing different ethnicities of different genders. In 2017, considering that the contour structure, geometric features and texture features of faces change with age, in order to study the impact of different face features on the evaluation of face attractiveness under different age groups, we built a middle-aged and elderly face database. In 2018, we used migration learning to migrate the face feature point templates of face recognition to the construction of face attractiveness face templates, and constructed a geometric feature-based face attractiveness evaluation model. In 2019, we established a face database of Chinese males in different eras, and studied the aesthetic characteristics and trends of Chinese males from the perspective of era development. An 81-point face feature point template for face attractiveness analysis was also proposed through feature vector analysis of face image quantification and light model. In 2020, a comprehensive facial attractiveness evaluation system was proposed considering the combined effects of face structure features, facial structure features, and skin texture features on face attractiveness scores, and the experimental results are shown in Table 1 , when these three features are integrated with each other, the Pearson correlation coefficient reached the highest value of 0.806 ( Zhao et al., 2019a , b , c ; Zhao et al., 2020 ).

Table 1. Performance of face attractiveness prediction with different features.

Through years of research at the intersection of artificial intelligence + face attractiveness, it is shown that although it may be difficult to establish a clear, interpretable and accepted set of rules to define face attractiveness. However, it is possible to explore the relationship between ordinary faces and attractive faces, and the qualitative study of face aesthetic preferences can be described quantitatively by artificial intelligence. The results highly fit contemporary aesthetic standards, demonstrating that it is feasible for computers to simulate advanced human cognitive abilities to recognize emotions and understand human feelings, and that the development of artificial intelligence based on cognitive psychology has potential and significance.

Affective computing

Emotion is a psychological state of positive or negative attitude toward external things and objective reality, and can be defined as a group of psychological phenomena expressed in the form of emotions, feelings or passions. Emotions not only refer to human emotions, but also refer to all human sensory, physical, psychological and spiritual feelings. Damasio found in his research that due to the defect of the channel between the cerebral cortex (Cortex: control of logical reasoning) and the limbic system (Limbic System: control of emotion), his “patients” despite having normal or even supernormal rational thinking and logical reasoning. However, their decision-making ability has encountered serious obstacles ( Bechara et al., 2000 ), proving that human intelligence is not only manifested in normal rational thinking and logical reasoning abilities, but also in rich emotional abilities.

More than 40 years ago, Nobel Laureate Herbert Simon emphasized in cognitive psychology that problem solving should incorporate the influence of emotions ( Simon, 1987 ). As one of the founders of artificial intelligence, Professor Marvin Minsky of the Massachusetts Institute of technology of the United States first proposed the ability to make computers have emotion. In his monograph the society of mind, he emphasized that emotion is an indispensable and important ability for machines to achieve intelligence. The concept of affective computing was first introduced by Picard (1995), when she stated that “affective computing is computing that can measure and analyze and influence emotions in response to human outward expressions” ( Picard, 2003 ). This opened up a new field of computer science, with the idea that computers should have emotions and be able to recognize and express them as humans do, thus making human–computer interaction more natural.

As an important means of interpersonal communication, emotion conveys the information of emotional state and explains complex psychological activities and behavioral motives through physiological indicators such as human language text, intonation volume change, facial expression, action posture and brain wave.

In, Ekman (1972) an American professor of psychology, proposed a method for the expression of facial emotions (Facial Motor Coding System FACS) ( Buhari et al., 2020 ). By the combination of different coding and motor units, complex expression changes can be formed on the face. Facial motion coding system FACS can analyze emotions using deep region and multi-label learning (DRML) architecture, using feedforward functions to induce important facial regions, and able to learn weights to capture structural information of the face. The resulting network is end-to-end trainable and converges faster than alternative models with better learning of AU relationships ( Zhao et al., 2016 ). The corresponding emotion computation formula can be derived based on the facial motion encoding, as Table 2 shown.

Table 2. Emotion formula.

In the process of human information interaction, speech is the most common way for people to communicate. As the most basic audiovisual signal, speech cannot only identify different vocalists, but also effectively distinguish different emotional states. International research on emotional speech focuses on the analysis of acoustic features of emotions, such as rhythm, sound source, resonance peaks and spectrum and so on ( Albanie et al., 2018 ). In recent years, deep learning has been widely studied and has many applications in speech emotion computation. Dongdong Li proposed a bidirectional long short-term memory network with directed self-attention (BLSTM-DSA). Long Short Term Memory (LSTM) neural networks can learn long-term dependencies from learned local features. In addition, Bi-directional Long Short-Term Memory(Bi-LSTM) can make the structure more robust through the direction mechanism, and the direction analysis can better identify the hidden emotions in sentences. Also, the autocorrelation of speech frames can be used to deal with the problem of missing information, thus introducing a self-attention mechanism in Speech Emotion Recognition (SER). When evaluated on the Interactive Emotional Binary Motion Capture (IEMOCAP) database and the Berlin Emotional Speech Database (EMO-DB), BLSTM-DSA achieves a recognition rate of over 70% for each algorithm on the speech emotion recognition task ( Li et al., 2021 ).

Human posture often carries emotional information during interaction. Researchers have combined human posture with artificial intelligence to quantitatively assess the external representation of a person’s mental state in the face of different situations through a series of movement and body information capture devices. For example, the intelligent seat is applied to the driver’s seat of the vehicle to dynamically monitor the emotional state of the driver and give timely warnings. Some scientists in Italy also conduct automatic emotional analysis on office staff through a series of posture analysis to design a more comfortable office environment.

Electroencephalographic(EEG) is a graph obtained by amplifying and recording the spontaneous biological potential of the brain from the scalp through precise electronic instruments. It has been widely used in the field of emotion recognition. The DEAP dataset used to study human emotional states ( Luo et al., 2020 ), recording EEG and peripheral physiological signals from 32 participants watching 40 one-minute long music video clips. Participants rated each video according to arousal, potency, like/dislike, dominance, and familiarity. Correlations between EEG signal frequencies and participants’ ratings were investigated by emotional label retrieval, and decision fusion was performed on classification results from different modalities. The experiments obtained an average recognition rate of up to 84.2% and up to 98% by identifying a single emotional state, while for two, three and four emotions, the average recognition rate was up to 90.2, 84.2, and 80.9%, respectively. Table 3 shows the validated classification accuracy of the DEAP dataset based on different recognition models ( Khateeb et al., 2021 ).

Table 3. Classification accuracy of deap dataset based on different recognition models.

Our research group has also carried out relevant research on multimodal affective computing, and has a patent for automatic diagnosis of depression based on speech and facial expression: By combining facial gesture features, we propose a new double dictionary idea with gesture robustness. In 2016, feature extraction and evaluation of depressed speech were performed, and in the following year, we proposed to use the change of expression of depressed patients as one of the evaluation indicators to determine whether they suffer from depression as well. Figures 2 and 3 shows the data.

Figure 2. Speech emotion recognition rate.

Figure 3. Face facial emotion recognition rate.

In 2018, a new automatic depression assistant discrimination algorithm integrating speech and facial expression was proposed. Firstly, the signal enhancement was performed for depressed speech; the fundamental frequency and the first three resonance peaks features were extracted by the inverse spectral method, and the energy, short-time average amplitude and Mel-Frequency Ceptral Coefficients(MFCC) features were extracted; the speech recognition model and the facial expression recognition model were established to assist in judging whether a person has depression; finally, the Adaboost algorithm based on back propagation(BP) neural network was proposed and validated in a practical situation for an automatic depression-assisted detection system. As Table 4 shown, the recognition rate of the depression detection algorithm based on fused speech and facial emotion reached 81.14%. The development of artificial intelligence provides a more objective judgment basis for the diagnosis of depression in psychological medical health, which has cutting-edge and application value ( Zhao et al., 2019d ).

Table 4. The integration of voice and facial expression recognition rate.

Affective computing is a combination of computational science with physiology science, psychological science, cognitive science and other disciplines. Based on the common cognition and knowledge structure of human on different emotional expressions, it studies the emotions in the process of human-human interaction and human–computer interaction, and guides the design of artificial intelligence with emotion recognition and feedback functions, understands human emotional intentions and makes appropriate responses to achieve human–computer emotional interaction.

Music emotion

Extensive research on musical emotions suggests that music can trigger emotional activity in listeners. Scientists believe that when a person is in a beautiful and pleasant musical environment, the body secretes an active substance that is beneficial to health and helps eliminate psychological factors that cause tension, anxiety, depression and other adverse psychological states ( Rahman et al., 2021 ). People’s preference for different kinds of music is not without rules, after psychological cognition and data test, there is a precise music signal α value can measure the ear-pleasant degree. The closer the music signal α is to the value 1, the better it sounds. The value of α also can be obtained by artificial intelligence ( Banerjee et al., 2016 ). This shows that people’s psychological state toward music can be judged by machines, and further research can be based on this law to simulate good-sounding music in line with public aesthetics and realize the interaction between emotions and machines.

As Figure 4 , a team of researchers from the University of Reading and the University of Plymouth in the UK developed and evaluated an affective brain-computer music interface (aBCMI) for detecting a user’s current emotional state and attempting to modulate it by playing music generated by a music composition system based on specific emotional goals.

Figure 4. The proposed affective brain-computer music interface (aBCMI). The system consists of five key elements: (A) . The user of the system (B) . The user’s physiological signal acquisition module (including the electroencephalogram (EEG), electrocardiogram (ECG) and respiration rate) (C) . An emotional state detection system for identifying a current emotional state that a user is experiencing (D) . A case-based reasoning system that determines how a user moves from his current emotional state to a new target emotional state (E) . The music generator is used to play music for the user. The case-based reasoning system identifies the most appropriate emotional trajectory and moves them to the target emotional state.

The affective state detection method achieved statistically significant online single-trial classification accuracy in classifying user potency in seven-eighths of participants and in classifying user arousal in three-eighths of participants. The mean accuracy for affective state detection was 53.96% (chemotaxis) and 53.80% (arousal) ( Daly et al., 2016 ). The experimental data also demonstrate that the aBCMI system is able to detect the emotional states of most of the participants and generate music based on their emotional states to achieve “happy” and “calm” mental states. By visualizing abstract mental states, extracting features from changes in emotional states, and quantifying different emotions in different musical environments, the aBCMI system can effectively characterize and provide feedback to regulate current emotional states, realizing the combination of psychology and artificial intelligence.

Musical emotion regulation aims to record physiological indicators from users with a signal acquisition component in order to capture the cognitive and physiological processes associated with their current affective state. Features are extracted from the physiological signals that most likely correspond to changes in the user’s affective state. Then the case-based reasoning system is used to determine the best method to transfer them to the target emotional state, so as to move the user to the target emotional state.

Dapeng Li and Xiaoguang Liu have also combined incremental music teaching methods to assist therapy. The combination of contextual teaching and artificial intelligence attention theory makes the assisted treatment system more targeted. The design of treatment content more fully takes into account the patient’s actual situation. When designing the music teaching-assisted treatment context, the physician will fully consider various factors of the patient, from the perspective of mobilizing the patient’s interest in the music learning work, to achieve the full activity of brain neurons and more fully access the pathological information around the lesion to promote autoimmunity and subsequent treatment ( Li and Liu, 2022 ).

The evocation of musical emotions is based on functional connections between sensory, emotional and cognitive areas of the brain, including subcortical reward networks common to humans and other animals, such as the nucleus accumbens, amygdala and dopaminergic systems, as well as the evolutionary end of the cerebral cortex with complex cognitive functions. Musical emotions regulate the activity of almost all limbic and paralimbic structures of the brain. Music can induce different emotions, and we can also use music emotions to guide the development of artificial intelligence. Further research is expected in such fields as music generation, education, medical treatment and so on.

Summary and outlook

Through systematic analysis and application examples, this manuscript points out that the artificial intelligence system combined with cognitive psychology is the development direction of artificial intelligence: to promote the development of artificial intelligence, to give computers the ability to simulate human’s advanced cognition, and to learn and think, so that computers can recognize emotions and understand human feelings, and finally realize dialog and empathy with human beings and other artificial intelligence. Artificial intelligence with human psychological cognition cannot only simulate the rational thinking of “brain,” but also reproduce the perceptual thinking of “heart,” and can realize the emotional interaction between people and machines, machines and machines, similar to human communication.

Nowadays, the theory of artificial intelligence based on cognitive psychology also has imperfections: due to the differences in race, region and growth environment, the evaluation criteria for each subject are not completely consistent, and the random sampling difference is even greater Moreover, mental activities are generally ambiguous and chaotic.

The future interdisciplinary combination of AI and psychology will focus on the following aspects: big data medical, human–computer interaction, brain-computer interface, general artificial intelligence and so on. Through the combination of cognitive science in psychology and AI, breakthroughs in many aspects will be achieved based on multimodal data and extraction of high-dimensional data. The two accomplish each other, complementing each other and developing together.

This manuscript provides a research direction for the development of artificial intelligence to simulate machines with human emotions and to realize human–computer interaction. It has the characteristics of cutting-edge science, which is not only of great theoretical significance, but also has good development potential and application prospects. It is hoped that it can provide research basis for follow-up researchers.

Author contributions

JZ formulated the research manuscript idea, provided substantial edits to the manuscript and final draft, and aided in the interpretation of the manuscript. MW wrote the main body of the manuscript, participated in revisions, and submitted the final manuscript. LZ contributed to the formulation of the research manuscript idea, provided substantial edits to the manuscript and the final draft, and aided in the interpretation of the manuscript. XW and JJ participated in the conception of the idea and revised the manuscript. All authors contributed to the article and approved the submitted version.

This work was supported by National Natural Science Foundation of China: 12071369 and Key Research and Development Program of Shaanxi (No. 2019ZDLSF02-09-02).

Conflict of interest

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

Publisher’s note

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

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Keywords : cognitive psychology, artificial intelligence, cognitive theory, behavioral science, human–computer interaction

Citation: Zhao J, Wu M, Zhou L, Wang X and Jia J (2022) Cognitive psychology-based artificial intelligence review. Front. Neurosci. 16:1024316. doi: 10.3389/fnins.2022.1024316

Received: 21 August 2022; Accepted: 13 September 2022; Published: 06 October 2022.

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Copyright © 2022 Zhao, Wu, Zhou, Wang and Jia. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jian Jia, [email protected]

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

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Home » 500+ Psychology Research Topic Ideas

500+ Psychology Research Topic Ideas

Table of Contents

Psychology is a vast field that encompasses a wide range of topics and research areas. From the study of cognition and behavior to the exploration of mental health disorders, there are countless avenues for researchers to explore within this field. Whether you are a college student, graduate student, or professional in the field of psychology, selecting a research topic can be a daunting task. To help guide your research endeavors, we have compiled a list of 500+ unique psychology research topic ideas across various subfields of psychology. These research topics range from the study of abnormal psychology and cognitive psychology to military psychology and education. With this extensive list, we hope to provide you with inspiration and ideas to jumpstart your research journey.

Psychology Research Topic Ideas

Psychology Research Topic Ideas are as follows:

• The effects of social media on self-esteem in adolescents
• The role of parenting styles in shaping children’s personality development
• The impact of mindfulness meditation on stress reduction in adults
• The influence of music on mood and emotional regulation
• The effects of sleep deprivation on cognitive functioning
• The relationship between personality traits and job satisfaction
• The effects of physical exercise on mental health
• The role of culture in shaping social identity and behavior
• The impact of peer pressure on decision-making in adolescents
• The effects of childhood trauma on adult attachment styles
• The influence of personality on romantic relationships
• The effects of bullying on mental health in children and adolescents
• The role of cognitive-behavioral therapy in treating anxiety disorders
• The impact of positive psychology interventions on well-being
• The effects of social support on coping with stress
• The relationship between emotional intelligence and academic achievement
• The effects of technology use on cognitive functioning
• The influence of gender roles on social behavior
• The effects of pet ownership on mental health
• The role of attachment styles in parent-child relationships
• The impact of social comparison on body dissatisfaction in women
• The effects of mindfulness-based stress reduction on chronic pain management
• The relationship between personality disorders and criminal behavior
• The effects of stereotype threat on academic performance
• The influence of self-esteem on romantic relationships
• The effects of environmental factors on cognitive development in children
• The role of resilience in coping with trauma
• The effects of gaming on cognitive functioning and addiction
• The impact of mindfulness interventions on workplace productivity
• The relationship between social support and physical health.
• The relationship between self-compassion and mental health
• The impact of cognitive biases on decision-making
• The role of attachment styles in romantic relationships
• The effects of social isolation on mental health
• The influence of cultural values on parenting practices
• The relationship between social media use and body image dissatisfaction
• The effects of childhood obesity on mental health and well-being
• The impact of mindfulness-based interventions on addiction recovery
• The role of personality in predicting job performance and success
• The effects of sleep quality on academic achievement
• The influence of social identity on intergroup conflict
• The effects of nature exposure on stress reduction
• The impact of meditation on empathy and compassion
• The role of emotion regulation in coping with chronic illness
• The effects of gratitude interventions on well-being and life satisfaction
• The relationship between personality traits and leadership effectiveness
• The impact of trauma on brain development in children
• The role of social norms in shaping behavior
• The effects of mindfulness interventions on eating disorders
• The influence of cultural factors on mental health stigma
• The effects of emotional intelligence on workplace relationships and team effectiveness
• The relationship between self-esteem and academic achievement
• The impact of exercise on cognitive aging and dementia prevention
• The role of empathy in moral decision-making
• The effects of social comparison on academic motivation
• The influence of cultural factors on the perception of mental illness
• The effects of childhood bullying on long-term mental health outcomes
• The role of personality in romantic partner selection and satisfaction
• The impact of parental divorce on children’s emotional and behavioral outcomes
• The relationship between personality traits and coping strategies in stressful situations.
• The impact of personality disorders on interpersonal relationships
• The effects of mindfulness interventions on workplace stress and burnout
• The role of emotional intelligence in romantic relationships
• The effects of cultural factors on the development of eating disorders
• The relationship between attachment styles and emotional regulation
• The impact of early childhood education on cognitive development
• The effects of exposure to violence on mental health outcomes
• The role of motivation in academic achievement and success
• The influence of culture on the perception of intelligence and academic achievement
• The effects of technology use on social skills and communication
• The relationship between self-esteem and social anxiety
• The impact of trauma on memory processing and recall
• The role of parental involvement in academic achievement
• The effects of exercise on mental health outcomes in older adults
• The influence of cultural factors on romantic attraction and mate selection
• The effects of mindfulness interventions on depression and anxiety
• The relationship between personality traits and substance abuse
• The impact of environmental factors on child development
• The role of motivation in workplace productivity and job satisfaction
• The effects of social media use on sleep quality and quantity
• The influence of cultural factors on the perception and treatment of addiction
• The effects of cognitive-behavioral therapy on social anxiety disorder
• The relationship between personality traits and risk-taking behavior
• The impact of prenatal stress on child development and behavior
• The role of emotional intelligence in leadership effectiveness
• The effects of meditation on attention and focus
• The influence of cultural factors on mental health treatment-seeking behavior
• The effects of traumatic events on personal growth and resilience
• The relationship between personality traits and creativity
• The impact of mindfulness interventions on emotion dysregulation in children and adolescents.
• The effects of social comparison on body dissatisfaction
• The impact of parental stress on child behavior and development
• The role of mindfulness in stress management during pregnancy
• The effects of cultural factors on the development of social anxiety disorder
• The relationship between personality traits and procrastination
• The impact of trauma on addiction and substance abuse
• The role of culture in shaping attitudes towards mental health treatment
• The effects of exercise on self-esteem and body image
• The influence of personality traits on the development of eating disorders
• The relationship between childhood trauma and adult mental health outcomes
• The impact of meditation on academic performance and focus
• The role of culture in shaping attitudes towards body image and appearance
• The effects of mindfulness interventions on chronic pain management
• The relationship between personality traits and moral decision-making
• The impact of early childhood attachment on romantic relationships
• The role of culture in shaping attitudes towards sexuality and sexual behavior
• The effects of social support on mental health outcomes in older adults
• The influence of personality traits on the development of obsessive-compulsive disorder
• The relationship between childhood bullying and adult mental health outcomes
• The impact of cognitive-behavioral therapy on panic disorder
• The role of culture in shaping attitudes towards substance use and addiction
• The effects of mindfulness interventions on insomnia and sleep quality
• The relationship between personality traits and social comparison behavior
• The impact of parental divorce on romantic relationship outcomes
• The role of culture in shaping attitudes towards aging and age-related changes
• The effects of social support on stress management in college students
• The influence of personality traits on the development of anxiety disorders
• The relationship between childhood trauma and romantic relationship outcomes
• The impact of cognitive-behavioral therapy on social anxiety disorder
• The role of culture in shaping attitudes towards masculinity and femininity
• The effects of mindfulness interventions on work-related stress
• The relationship between personality traits and forgiveness
• The impact of peer pressure on adolescent substance abuse
• The role of culture in shaping attitudes towards mental health stigma
• The effects of social support on stress management in healthcare workers
• The influence of personality traits on the development of depression
• The relationship between childhood trauma and substance abuse
• The impact of cognitive-behavioral therapy on depression
• The role of culture in shaping attitudes towards body modification and cosmetic surgery
• The effects of mindfulness interventions on emotional regulation in adolescents.
• The effects of social media on self-esteem and body image in adolescent girls
• The impact of parental emotional neglect on adult mental health outcomes
• The role of culture in shaping attitudes towards gender and sexual orientation identity
• The effects of cognitive-behavioral therapy on post-traumatic stress disorder
• The relationship between personality traits and attachment styles in romantic relationships
• The impact of social support on mental health outcomes in individuals with chronic illness
• The role of culture in shaping attitudes towards disability and ableism
• The effects of mindfulness interventions on emotional eating and food addiction
• The influence of personality traits on the development of borderline personality disorder
• The relationship between childhood adversity and adult mental health outcomes
• The impact of cognitive-behavioral therapy on generalized anxiety disorder
• The role of culture in shaping attitudes towards aging and dementia
• The effects of social support on mental health outcomes in individuals with chronic pain
• The relationship between personality traits and coping strategies in response to stress
• The impact of maternal mental health on child behavior and development
• The role of culture in shaping attitudes towards mental health in the workplace
• The effects of mindfulness interventions on stress and burnout in healthcare professionals
• The influence of personality traits on the development of narcissistic personality disorder
• The relationship between childhood trauma and sleep disorders
• The impact of cognitive-behavioral therapy on bipolar disorder
• The role of culture in shaping attitudes towards diversity and inclusion
• The effects of social support on mental health outcomes in refugees and immigrants
• The relationship between personality traits and empathy
• The impact of social comparison on academic performance and motivation
• The role of culture in shaping attitudes towards mental health in the military
• The effects of mindfulness interventions on addiction recovery and relapse prevention
• The influence of personality traits on the development of antisocial personality disorder
• The relationship between childhood trauma and borderline personality disorder
• The impact of cognitive-behavioral therapy on social skills and communication in autism spectrum disorder
• The role of culture in shaping attitudes towards mental health in the LGBTQ+ community
• The effects of social support on mental health outcomes in individuals with substance use disorder
• The relationship between personality traits and creativity in the arts and sciences
• The impact of early childhood exposure to violence on adult mental health outcomes
• The role of culture in shaping attitudes towards mental health and aging in rural communities
• The effects of mindfulness interventions on self-compassion and self-care
• The influence of personality traits on the development of schizophrenia
• The relationship between childhood trauma and dissociative identity disorder
• The impact of cognitive-behavioral therapy on social anxiety in children and adolescents
• The role of culture in shaping attitudes towards mental health and spirituality
• The effects of social support on mental health outcomes in individuals with chronic stress.
• The impact of personality traits on job performance and satisfaction
• The relationship between childhood trauma and attention-deficit/hyperactivity disorder (ADHD)
• The effects of exposure therapy on phobias and anxiety disorders
• The role of culture in shaping attitudes towards mental health in minority communities
• The effects of social support on mental health outcomes in caregivers of individuals with chronic illness or disability
• The relationship between cognitive flexibility and problem-solving abilities
• The impact of psychoeducation on stigma reduction towards mental illness
• The role of culture in shaping attitudes towards mental health and substance use in college students
• The effects of mindfulness interventions on academic performance and stress in college students
• The influence of personality traits on the development of obsessive-compulsive disorder (OCD)
• The relationship between childhood trauma and depression in adulthood
• The impact of cognitive-behavioral therapy on depression and anxiety in cancer patients
• The role of culture in shaping attitudes towards mental health and body image in men
• The effects of social support on mental health outcomes in individuals with chronic fatigue syndrome
• The relationship between resilience and post-traumatic growth
• The impact of music therapy on mental health outcomes in individuals with schizophrenia
• The role of culture in shaping attitudes towards mental health and motherhood
• The effects of mindfulness interventions on emotional regulation and mood disorders in adolescents
• The influence of personality traits on the development of hoarding disorder
• The relationship between childhood trauma and substance use disorder in adulthood
• The impact of cognitive-behavioral therapy on insomnia and sleep disorders
• The role of culture in shaping attitudes towards mental health and masculinity
• The effects of social support on mental health outcomes in individuals with chronic migraines
• The relationship between emotional intelligence and leadership effectiveness
• The impact of group therapy on social skills and communication in individuals with autism spectrum disorder
• The role of culture in shaping attitudes towards mental health and aging in urban communities
• The effects of mindfulness interventions on compassion and empathy in healthcare professionals
• The influence of personality traits on the development of postpartum depression
• The relationship between childhood trauma and bipolar disorder in adulthood
• The impact of cognitive-behavioral therapy on self-esteem and body image in individuals with eating disorders
• The role of culture in shaping attitudes towards mental health and family dynamics in immigrant families
• The effects of social support on mental health outcomes in individuals with chronic gastrointestinal disorders
• The relationship between personality traits and self-compassion
• The impact of play therapy on social-emotional development in children with autism spectrum disorder
• The role of culture in shaping attitudes towards mental health and aging in LGBTQ+ communities
• The effects of mindfulness interventions on anxiety and depression in individuals with chronic pain
• The relationship between childhood trauma and borderline personality disorder symptoms in adolescence
• The impact of cognitive-behavioral therapy on obsessive-compulsive disorder symptoms in children and adolescents.
• The effects of physical exercise on mood and anxiety in older adults
• The relationship between childhood trauma and attachment styles in romantic relationships
• The impact of cognitive-behavioral therapy on body dysmorphic disorder symptoms
• The role of culture in shaping attitudes towards mental health and spirituality in indigenous communities
• The relationship between personality traits and risky behavior in adolescence
• The influence of parental bonding on the development of borderline personality disorder in young adults
• The impact of mindfulness interventions on stress and burnout in healthcare professionals
• The role of culture in shaping attitudes towards mental health and disability in rural communities
• The effects of psychotherapy on self-compassion in individuals with depression
• The relationship between childhood trauma and dissociative symptoms in adulthood
• The impact of cognitive-behavioral therapy on social anxiety disorder in individuals with autism spectrum disorder
• The role of culture in shaping attitudes towards mental health and help-seeking behaviors in Asian American communities
• The effects of social support on mental health outcomes in individuals with chronic obstructive pulmonary disease (COPD)
• The influence of family functioning on the development of substance use disorders in adolescents
• The impact of expressive writing on emotional processing in individuals with post-traumatic stress disorder (PTSD)
• The effects of mindfulness interventions on self-compassion and emotional regulation in survivors of domestic violence
• The relationship between childhood trauma and disordered eating behaviors in young adults
• The impact of cognitive-behavioral therapy on panic disorder symptoms in individuals with irritable bowel syndrome (IBS)
• The role of culture in shaping attitudes towards mental health and community support in refugee populations
• The effects of social support on mental health outcomes in individuals with chronic kidney disease (CKD)
• The relationship between personality traits and romantic relationship satisfaction
• The influence of childhood attachment on the development of post-traumatic stress disorder in adulthood
• The impact of group therapy on social skills and self-esteem in individuals with social anxiety disorder
• The role of culture in shaping attitudes towards mental health and faith-based support in African American communities
• The effects of mindfulness interventions on emotion regulation and coping skills in individuals with borderline personality disorder
• The relationship between childhood trauma and anxiety sensitivity in adulthood
• The impact of cognitive-behavioral therapy on health anxiety symptoms in individuals with chronic illnesses
• The role of culture in shaping attitudes towards mental health and social stigma in Hispanic/Latino communities
• The effects of social support on mental health outcomes in individuals with chronic hepatitis C
• The relationship between personality traits and decision-making processes
• The influence of parent-child communication on the development of eating disorders in adolescents
• The impact of cognitive-behavioral therapy on gambling disorder symptoms
• The role of culture in shaping attitudes towards mental health and access to care in rural communities
• The effects of mindfulness interventions on self-compassion and emotional regulation in individuals with bipolar disorder
• The relationship between childhood trauma and rumination in adulthood
• The impact of group therapy on self-esteem and assertiveness in individuals with avoidant personality disorder
• The role of culture in shaping attitudes towards mental health and community resources in Native American populations.
• The effects of sleep deprivation on cognitive performance and decision-making
• The relationship between personality traits and addiction susceptibility
• The impact of cognitive-behavioral therapy on hoarding disorder symptoms
• The role of culture in shaping attitudes towards mental health and spirituality in Hispanic/Latino communities
• The effects of social support on mental health outcomes in individuals with multiple sclerosis
• The relationship between childhood trauma and emotional regulation in adulthood
• The influence of social media on body image and self-esteem in adolescents
• The impact of mindfulness interventions on impulsivity and self-control in individuals with attention deficit hyperactivity disorder (ADHD)
• The role of culture in shaping attitudes towards mental health and help-seeking behaviors in LGBTQ+ communities
• The effects of cognitive training on cognitive performance and brain structure in older adults
• The relationship between personality traits and risk-taking behaviors in college students
• The impact of family therapy on communication and conflict resolution in families with a history of domestic violence
• The role of culture in shaping attitudes towards mental health and community resources in Asian American communities
• The relationship between childhood trauma and interpersonal functioning in adulthood
• The influence of cultural identity on mental health outcomes in immigrant populations
• The impact of cognitive-behavioral therapy on eating disorder symptoms in individuals with type 1 diabetes
• The role of culture in shaping attitudes towards mental health and stigma in Arab American communities
• The effects of mindfulness interventions on self-compassion and emotional regulation in individuals with obsessive-compulsive disorder (OCD)
• The relationship between childhood trauma and attachment styles in adulthood friendships
• The impact of expressive writing on stress and immune function in caregivers of individuals with dementia
• The role of culture in shaping attitudes towards mental health and community resources in rural Native American communities
• The effects of social support on mental health outcomes in individuals with chronic pain and depression
• The relationship between personality traits and emotional intelligence
• The influence of parental warmth and discipline on the development of anxiety disorders in children
• The impact of cognitive-behavioral therapy on postpartum depression symptoms
• The role of culture in shaping attitudes towards mental health and access to care in South Asian communities
• The effects of mindfulness interventions on self-compassion and emotional regulation in individuals with borderline personality disorder
• The relationship between childhood trauma and resilience in adulthood
• The impact of group therapy on social anxiety and loneliness in individuals with hearing loss
• The role of culture in shaping attitudes towards mental health and community support in Pacific Islander communities
• The effects of social support on mental health outcomes in individuals with chronic obstructive pulmonary disease (COPD) and depression
• The relationship between personality traits and leadership styles
• The influence of peer relationships on the development of depressive symptoms in adolescents
• The impact of cognitive-behavioral therapy on body image and self-esteem in individuals with gender dysphoria
• The role of culture in shaping attitudes towards mental health and community resources in Middle Eastern communities
• The effects of mindfulness interventions on self-compassion and emotional regulation in individuals with post-traumatic stress disorder (PTSD) and addiction
• The relationship between childhood trauma and substance use disorders in adulthood
• The impact of group therapy on emotion regulation and self-esteem in individuals with personality disorders
• The role of culture in shaping attitudes towards mental health and community resources in immigrant and refugee communities.
• Sure, here are 40 more psychology research topic ideas:
• The effects of meditation on creativity and divergent thinking
• The relationship between personality traits and career satisfaction
• The impact of cognitive-behavioral therapy on sleep disturbances in individuals with post-traumatic stress disorder (PTSD)
• The role of culture in shaping attitudes towards mental health and help-seeking behaviors in Black communities
• The effects of social support on mental health outcomes in individuals with traumatic brain injury (TBI)
• The relationship between childhood trauma and attachment styles in romantic relationships in adulthood
• The influence of social norms on substance use behaviors in college students
• The impact of cognitive-behavioral therapy on social anxiety symptoms in individuals with autism spectrum disorder (ASD)
• The role of culture in shaping attitudes towards mental health and community resources in Indigenous communities
• The effects of mindfulness interventions on self-compassion and emotional regulation in individuals with chronic pain
• The impact of group therapy on emotion regulation and social connectedness in individuals with eating disorders
• The role of culture in shaping attitudes towards mental health and community resources in African immigrant communities
• The effects of social support on mental health outcomes in individuals with spinal cord injuries (SCI)
• The relationship between childhood trauma and the development of eating disorders in adulthood
• The influence of social identity on stereotype threat and academic performance in college students
• The impact of cognitive-behavioral therapy on obsessive-compulsive disorder (OCD) symptoms in individuals with Parkinson’s disease
• The role of culture in shaping attitudes towards mental health and help-seeking behaviors in Southeast Asian communities
• The effects of mindfulness interventions on self-compassion and emotional regulation in individuals with chronic obstructive pulmonary disease (COPD)
• The relationship between personality traits and coping strategies in individuals with chronic pain
• The impact of group therapy on emotion regulation and social support in individuals with borderline personality disorder
• The role of culture in shaping attitudes towards mental health and community resources in Muslim communities
• The effects of social support on mental health outcomes in individuals with chronic kidney disease (CKD) and depression
• The relationship between childhood trauma and emotional intelligence in adulthood
• The influence of attachment styles on romantic relationship satisfaction in adults
• The impact of cognitive-behavioral therapy on social anxiety symptoms in individuals with social communication disorder (SCD)
• The role of culture in shaping attitudes towards mental health and community resources in refugee communities
• The effects of mindfulness interventions on self-compassion and emotional regulation in individuals with substance use disorders
• The relationship between personality traits and resilience in individuals with chronic illnesses
• The impact of group therapy on emotion regulation and social skills in individuals with attention deficit hyperactivity disorder (ADHD)
• The role of culture in shaping attitudes towards mental health and community resources in Caribbean communities
• The effects of social support on mental health outcomes in individuals with fibromyalgia and depression
• The influence of social comparison on body dissatisfaction and eating disorder behaviors in adolescents
• The impact of cognitive-behavioral therapy on depression symptoms in individuals with chronic fatigue syndrome (CFS)
• The role of culture in shaping attitudes towards mental health and community resources in Native Hawaiian communities
• The relationship between personality traits and coping strategies in individuals with traumatic brain injuries (TBI)
• The impact of group therapy on social anxiety symptoms in individuals with intellectual disabilities
• The role of social comparison in body image dissatisfaction and disordered eating behaviors in men
• The effects of parental attachment on romantic relationships in adulthood
• The impact of cognitive-behavioral therapy on anxiety symptoms in individuals with multiple sclerosis (MS)
• The relationship between cultural values and parenting practices in Latino families
• The effects of social support on mental health outcomes in individuals with chronic obstructive pulmonary disease (COPD) and anxiety
• The role of social norms in shaping attitudes towards mental health and help-seeking behaviors in South Asian communities
• The influence of personality traits on academic achievement in college students
• The impact of cognitive-behavioral therapy on depression symptoms in individuals with rheumatoid arthritis (RA)
• The relationship between attachment styles and romantic relationship satisfaction in same-sex couples
• The effects of mindfulness interventions on self-compassion and emotional regulation in individuals with schizophrenia
• The role of culture in shaping attitudes towards mental health and community resources in Arab communities
• The effects of social support on mental health outcomes in individuals with chronic pain and anxiety
• The relationship between childhood adversity and substance use disorders in adulthood
• The impact of cognitive-behavioral therapy on anxiety symptoms in individuals with attention deficit hyperactivity disorder (ADHD)
• The role of cultural beliefs about mental illness and stigma in Latino communities
• The effects of social identity on stereotype threat and academic achievement in minority college students
• The relationship between personality traits and coping strategies in caregivers of individuals with dementia
• The impact of group therapy on depression symptoms in individuals with traumatic brain injuries (TBI)
• The role of culture in shaping attitudes towards mental health and community resources in LGBTQ+ communities
• The relationship between attachment styles and romantic relationship satisfaction in individuals with chronic illnesses
• The influence of personality traits on stress and coping in police officers
• The impact of cognitive-behavioral therapy on anxiety symptoms in individuals with chronic kidney disease (CKD)
• The role of cultural beliefs about mental illness and stigma in Asian communities
• The effects of social support on mental health outcomes in individuals with irritable bowel syndrome (IBS) and depression
• The relationship between childhood trauma and interpersonal relationships in adulthood
• The impact of group therapy on anxiety symptoms in individuals with social phobia
• The role of culture in shaping attitudes towards mental health and community resources in Native American communities
• The effects of mindfulness interventions on self-compassion and emotional regulation in individuals with postpartum depression
• The relationship between personality traits and burnout in healthcare professionals
• The impact of cognitive-behavioral therapy on anxiety symptoms in individuals with chronic pain and fibromyalgia
• The role of cultural beliefs about mental illness and stigma in African American communities
• The effects of social support on mental health outcomes in individuals with inflammatory bowel disease (IBD) and anxiety
• The relationship between childhood trauma and emotional regulation in adolescence
• The influence of personality traits on well-being and life satisfaction in older adults
• The impact of group therapy on depression symptoms in individuals with borderline personality disorder
• The role of culture in shaping attitudes towards mental health and community resources in Hispanic/Latino communities
• The effects of mindfulness interventions on self-compassion and emotional regulation in individuals with post-traumatic stress disorder (PTSD)
• The relationship between attachment styles and emotional regulation in individuals with substance use disorders

Psychology Research Topic Ideas College Students

• The effects of virtual reality exposure therapy on anxiety and phobias among college students
• The relationship between attachment styles and romantic relationship satisfaction among college students
• The impact of social norms on substance use among college students
• The effects of cultural identity on mental health and academic achievement among college students
• The role of self-compassion in reducing burnout among college students
• The relationship between social media use and FOMO (fear of missing out) among college students
• The impact of environmental factors on mental health and well-being among college students
• The effects of self-esteem on social anxiety and social skills among college students
• The role of positive psychology interventions in promoting well-being and academic success among college students
• The relationship between gender identity and mental health outcomes among college students
• The impact of parental communication on mental health and academic performance among college students
• The effects of cognitive-behavioral therapy on PTSD symptoms among college students
• The relationship between personality traits and academic procrastination among college students
• The role of humor in reducing stress and promoting well-being among college students
• The impact of social identity on academic motivation and achievement among college students
• The effects of mindfulness-based stress reduction on academic performance and mental health among college students
• The relationship between academic stress and substance use among college students
• The role of cultural competence in promoting diversity and inclusion on college campuses
• The impact of emotional intelligence on academic success and career readiness among college students
• The effects of peer mentoring programs on academic motivation and success among college students
• The relationship between exercise and cognitive functioning in college students
• The role of optimism in promoting resilience and well-being among college students
• The impact of music therapy on anxiety and depression among college students
• The effects of exposure to nature on mental health and well-being among college students
• The relationship between parental involvement and emotional regulation among college students
• The role of forgiveness in promoting well-being and interpersonal relationships among college students
• The impact of social comparison on body image and self-esteem among college students
• The effects of attachment styles on coping with stress among college students
• The relationship between academic self-efficacy and academic performance among college students
• The role of grit in promoting academic perseverance and achievement among college students
• The impact of COVID-19 on mental health and well-being among college students
• The effects of peer pressure on substance use and risky behaviors among college students
• The relationship between social support and academic engagement among college students
• The role of cognitive biases in promoting or hindering academic success among college students
• The impact of physical activity on mental health and well-being among college students
• The effects of mindfulness-based interventions on academic motivation and success among college students
• The relationship between perfectionism and academic burnout among college students
• The role of parental support in promoting academic resilience and success among college students with disabilities
• The impact of diversity education on promoting empathy and reducing prejudice among college students
• The effects of assertiveness training on communication skills and interpersonal relationships among college students.

Graduate Psychology Research Topic Ideas

• The impact of mindfulness-based interventions on reducing symptoms of anxiety and depression in clinical populations
• The role of self-compassion in promoting emotional well-being among adults with chronic illness
• The effects of cognitive-behavioral therapy on PTSD symptoms in military veterans
• The relationship between sleep quality and cognitive functioning in aging populations
• The impact of positive psychology interventions on well-being and resilience among individuals with chronic pain
• The role of emotion regulation in reducing symptoms of borderline personality disorder
• The effects of virtual reality exposure therapy on social anxiety in individuals with autism spectrum disorder
• The relationship between executive functioning and academic achievement in children with ADHD
• The impact of family-based interventions on reducing symptoms of substance use disorders among adolescents
• The role of mindfulness in promoting emotional regulation and stress management in healthcare professionals
• The effects of cognitive remediation therapy on cognitive functioning in individuals with schizophrenia
• The relationship between attachment styles and therapeutic alliance in psychotherapy
• The impact of cultural factors on the manifestation and treatment of eating disorders
• The role of emotion regulation in reducing symptoms of depression and anxiety in postpartum women
• The effects of acceptance and commitment therapy on reducing symptoms of OCD
• The relationship between childhood ADHD and adult executive functioning and academic achievement
• The impact of animal-assisted therapy on reducing symptoms of PTSD in veterans
• The role of social support in promoting resilience and well-being among individuals with chronic illness
• The effects of cognitive remediation therapy on reducing negative symptoms in individuals with schizophrenia
• The relationship between executive functioning and social skills in children with autism spectrum disorder
• The impact of cognitive-behavioral therapy on reducing symptoms of hoarding disorder
• The role of emotion regulation in reducing symptoms of post-traumatic stress disorder
• The effects of mindfulness-based interventions on reducing symptoms of burnout among healthcare professionals
• The relationship between social support and quality of life in individuals with multiple sclerosis
• The impact of cognitive-behavioral therapy on reducing symptoms of generalized anxiety disorder
• The role of mindfulness in promoting well-being and emotional regulation in individuals with chronic pain
• The effects of cognitive remediation therapy on reducing negative symptoms in individuals with bipolar disorder
• The relationship between executive functioning and academic achievement in children with learning disabilities
• The impact of acceptance and commitment therapy on reducing symptoms of social anxiety disorder
• The role of emotion regulation in reducing symptoms of borderline personality disorder in adolescents
• The effects of cognitive-behavioral therapy on reducing symptoms of panic disorder
• The relationship between social support and depression in individuals with HIV/AIDS
• The impact of cognitive remediation therapy on reducing symptoms of ADHD in adults
• The role of mindfulness in promoting well-being and emotional regulation in individuals with depression
• The effects of cognitive-behavioral therapy on reducing symptoms of substance use disorders in individuals with co-occurring PTSD
• The relationship between executive functioning and quality of life in individuals with traumatic brain injury
• The impact of acceptance and commitment therapy on reducing symptoms of obsessive-compulsive disorder
• The role of emotion regulation in reducing symptoms of anxiety and depression in adolescents with chronic illness
• The effects of cognitive remediation therapy on reducing cognitive impairment in individuals with Parkinson’s disease.

Military Psychology Research Topic Ideas

• The impact of military deployment on the mental health and well-being of service members
• The role of resilience in promoting posttraumatic growth among military personnel
• The effects of combat exposure on emotional regulation and decision-making abilities
• The relationship between military leadership styles and team cohesion
• The impact of military culture on help-seeking behaviors among service members with mental health concerns
• The role of perceived social support in promoting resilience among military spouses during deployment
• The effects of military service on identity formation and self-concept
• The relationship between deployment-related stress and marital satisfaction among military couples
• The impact of military sexual trauma on mental health outcomes and treatment seeking behaviors among service members
• The role of mindfulness in reducing symptoms of PTSD among military personnel
• The effects of trauma-focused cognitive-behavioral therapy on reducing symptoms of PTSD among military veterans
• The relationship between military deployment and substance use disorders
• The impact of military deployment on parent-child relationships and child outcomes
• The role of perceived organizational support in promoting job satisfaction and retention among military personnel
• The effects of exposure therapy on reducing combat-related nightmares and sleep disturbances among military personnel
• The relationship between military service and risk-taking behaviors
• The impact of military culture on mental health stigma and treatment seeking behaviors among service members
• The role of positive psychology interventions in promoting resilience and well-being among military personnel and their families
• The effects of virtual reality exposure therapy on reducing symptoms of specific phobias among military personnel
• The relationship between military service and traumatic brain injury
• The impact of deployment on career development and job satisfaction among military personnel
• The role of cognitive appraisal in the stress and coping process among military personnel
• The effects of a peer support program on reducing symptoms of PTSD among military personnel
• The relationship between military service and intimate partner violence perpetration and victimization
• The impact of military deployment on parenting practices and child outcomes among military families
• The role of perceived organizational justice in promoting job satisfaction and retention among military personnel
• The effects of acceptance and commitment therapy on reducing symptoms of depression and anxiety among military personnel
• The relationship between military service and suicidal ideation and behavior
• The impact of military deployment on social support networks and social integration
• The role of perceived unit cohesion in promoting resilience and mental health among military personnel
• The effects of cognitive remediation therapy on improving cognitive functioning and job performance among military personnel with traumatic brain injury
• The relationship between military service and alcohol misuse and addiction
• The impact of military deployment on sibling relationships and family functioning
• The role of perceived leadership support in promoting job satisfaction and retention among military personnel
• The effects of exposure therapy on reducing symptoms of phobic avoidance among military personnel
• The relationship between military service and eating disorders
• The impact of military deployment on community reintegration and social support among veterans
• The role of perceived control in the stress and coping process among military personnel
• The effects of a mindfulness-based intervention on reducing symptoms of depression and anxiety among military spouses during deployment
• The relationship between military service and personality disorders.

Psychology Research Topic Ideas in Education

• The effects of mindfulness practices on student well-being and academic performance
• The impact of classroom diversity on student attitudes and academic achievement
• The role of parent-teacher communication in promoting student success
• The effects of differentiated instruction on student engagement and academic achievement
• The relationship between school climate and student mental health outcomes
• The impact of technology integration on student learning outcomes
• The role of teacher-student relationships in promoting student engagement and academic success
• The effects of social-emotional learning programs on student behavior and academic performance
• The relationship between academic self-concept and academic achievement
• The impact of peer tutoring on student academic performance
• The role of motivation in promoting student academic success
• The effects of educational gaming on student engagement and academic achievement
• The relationship between parental involvement and student academic achievement
• The impact of teacher expectations on student academic performance
• The role of goal-setting in promoting student academic success
• The effects of growth mindset interventions on student motivation and academic achievement
• The relationship between teacher burnout and student academic outcomes
• The impact of teacher diversity on student attitudes and academic achievement
• The role of classroom management in promoting student engagement and academic success
• The effects of student-centered learning on student academic performance
• The relationship between teacher empathy and student academic outcomes
• The impact of school-based mental health services on student mental health outcomes and academic achievement
• The role of parental involvement in homework on student academic success
• The effects of project-based learning on student engagement and academic achievement
• The relationship between student motivation and academic achievement in STEM fields
• The impact of teacher professional development on student academic outcomes
• The role of teacher feedback in promoting student academic success
• The effects of cooperative learning on student engagement and academic achievement
• The relationship between classroom climate and student academic outcomes
• The impact of restorative justice practices on student behavior and academic achievement
• The role of teacher support in promoting student academic success
• The effects of flipped classrooms on student engagement and academic achievement
• The relationship between teacher autonomy and student academic outcomes
• The impact of teacher collaboration on student academic performance
• The role of metacognition in promoting student academic success
• The effects of active learning on student engagement and academic achievement
• The relationship between student engagement and academic achievement in language learning
• The impact of teacher coaching on student academic outcomes
• The role of self-regulated learning in promoting student academic success
• The effects of outdoor learning on student engagement and academic achievement.

Cognitive Psychology Research Topic Ideas

• The role of attention in perception and memory
• The effect of sleep deprivation on cognitive functioning
• The relationship between creativity and cognitive flexibility
• The cognitive processes involved in decision-making
• The impact of stress on cognitive performance
• The role of working memory in problem-solving
• The cognitive factors involved in language acquisition
• The relationship between attention and executive functions
• The effect of aging on cognitive abilities
• The role of attention in visual perception
• The cognitive processes involved in learning and memory
• The impact of technology on cognitive development
• The relationship between cognition and emotion
• The effect of anxiety on cognitive performance
• The cognitive processes involved in attentional control
• The role of executive functions in decision-making
• The effect of mindfulness practices on cognitive functioning
• The relationship between language and cognition
• The cognitive processes involved in reading comprehension
• The impact of nutrition on cognitive development
• The role of working memory in language processing
• The effect of exercise on cognitive performance
• The cognitive processes involved in mental rotation tasks
• The relationship between cognitive load and learning
• The effect of multitasking on cognitive performance
• The cognitive processes involved in problem-solving
• The role of executive functions in goal-directed behavior
• The impact of cognitive training on cognitive abilities
• The relationship between attention and perception
• The effect of music on cognitive performance
• The cognitive processes involved in decision-making under uncertainty
• The role of cognitive control in self-regulation
• The impact of bilingualism on cognitive development
• The relationship between cognitive biases and decision-making
• The effect of caffeine on cognitive performance
• The cognitive processes involved in face recognition
• The role of cognitive dissonance in attitude change
• The impact of mindfulness-based interventions on cognitive functioning
• The relationship between cognitive styles and problem-solving
• The cognitive processes involved in mental imagery.

Forensic Psychology Research Topic Ideas

• The impact of childhood trauma on criminal behavior
• The effectiveness of forensic psychological evaluations in court proceedings
• The role of mental illness in criminal behavior
• The effect of substance abuse on criminal behavior
• The impact of eyewitness testimony on legal outcomes
• The role of psychopathy in criminal behavior
• The effectiveness of restorative justice practices
• The relationship between socioeconomic status and criminal behavior
• The effect of media coverage on public perceptions of crime
• The impact of prison environment on offender rehabilitation
• The role of the insanity defense in criminal cases
• The effectiveness of sex offender treatment programs
• The relationship between domestic violence and homicide
• The effect of legal representation on trial outcomes
• The impact of juvenile delinquency prevention programs
• The role of cultural factors in criminal behavior
• The effectiveness of parole and probation programs
• The relationship between mental illness and violence
• The effect of polygraph testing on legal outcomes
• The impact of criminal profiling on law enforcement investigations
• The role of victim impact statements in sentencing
• The effectiveness of correctional education programs
• The relationship between childhood attachment styles and criminal behavior
• The effect of cognitive biases in legal decision-making
• The impact of witness identification procedures on accuracy
• The role of forensic hypnosis in criminal investigations
• The effectiveness of drug court programs
• The relationship between alcohol use and criminal behavior
• The effect of societal stereotypes on criminal sentencing
• The impact of prison overcrowding on offender rehabilitation
• The role of cultural competence in forensic assessments
• The effectiveness of diversion programs for juvenile offenders
• The relationship between trauma and criminal behavior in women
• The effect of plea bargaining on legal outcomes
• The impact of social support on offender rehabilitation
• The role of forensic psychology in counterterrorism efforts
• The effectiveness of offender reentry programs
• The relationship between intellectual disability and criminal behavior
• The effect of forensic testimony on jury decision-making.

Abnormal psychology research topic ideas

• The effects of childhood trauma on the development of anxiety disorders
• The relationship between depression and sleep disturbances
• The effectiveness of psychotherapy for borderline personality disorder
• The impact of social media on body image and eating disorders
• The role of genetics in the development of schizophrenia
• The effect of early intervention on the progression of psychosis
• The impact of stigma on help-seeking behaviors for mental health disorders
• The relationship between substance use disorders and mental health
• The effect of exercise on symptoms of depression and anxiety
• The impact of trauma-focused cognitive behavioral therapy on post-traumatic stress disorder
• The role of attachment styles in the development of personality disorders
• The effectiveness of cognitive remediation therapy for schizophrenia
• The relationship between childhood ADHD and the development of anxiety disorders
• The effect of mindfulness meditation on symptoms of depression and anxiety
• The impact of cultural factors on the diagnosis and treatment of mental health disorders
• The role of neuroplasticity in the treatment of addiction
• The effectiveness of exposure therapy for specific phobias
• The effect of stress on the development of mental health disorders
• The impact of sleep disturbances on the onset of bipolar disorder
• The role of trauma in the development of dissociative disorders
• The effectiveness of cognitive behavioral therapy for insomnia
• The relationship between childhood abuse and the development of borderline personality disorder
• The effect of peer support on the recovery of individuals with mental health disorders
• The impact of cultural differences on the presentation of mental health symptoms
• The role of cognitive biases in the maintenance of anxiety disorders
• The effectiveness of dialectical behavior therapy for borderline personality disorder
• The relationship between early life stressors and the development of depression
• The effect of nutrition on mental health
• The impact of virtual reality exposure therapy on phobia treatment
• The role of genetics in the development of mood disorders
• The effectiveness of acceptance and commitment therapy for anxiety disorders
• The relationship between childhood trauma and the development of dissociative identity disorder
• The effect of stigma on treatment outcomes for individuals with mental health disorders
• The impact of childhood adversity on the development of personality disorders
• The role of emotional regulation in the treatment of borderline personality disorder
• The effectiveness of psychodynamic therapy for depression
• The relationship between sleep disturbances and the development of anxiety disorders
• The effect of stigma on mental health professionals’ treatment decisions
• The impact of cultural factors on the expression of bipolar disorder symptoms.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Exploring 200+ Psychology Topics to Research: Unlocking the Depths of the Mind

The world of psychology is as vast as the human mind itself. Delving into the intricate workings of the human psyche can be both fascinating. For students, academics, or anyone with a curious mind, choosing the right psychology topics to research is paramount. In this blog, we’ll navigate through the labyrinth of psychology topics, helping you find your way to a captivating and meaningful research endeavor.

How To Select Psychology Topics To Research?

Table of Contents

• Follow Your Interests: Start with what you love. What aspects of human behavior or the mind fascinate you the most? It’s much easier to research something you’re passionate about.
• Consider Relevance: Think about how your chosen topic fits into your academic or career goals. Does it relate to what you’re studying or the job you want? If it does, great!
• Balance the Scope: Don’t pick a topic that’s too broad or too narrow. Find that sweet spot in the middle. You want a topic that’s focused enough to research effectively but not so narrow that there’s no existing information.
• Explore Different Areas: Research the various branches of psychology, like cognitive, social, clinical, developmental, or biological psychology. See which one resonates with you the most.
• Seek Advice: Talk to your professors, mentors, or peers. They can provide guidance and suggestions based on your interests and goals.

200+ Popular Psychology Topics To Research: Category Wise

40+ cognitive psychology topics.

• The role of working memory in problem-solving.
• Cognitive effects of sleep deprivation.
• Neural basis of attention and focus.
• Influence of language on cognitive development.
• Decision-making biases in economic behavior.
• The psychology of learning and memory.
• The impact of stress on cognitive performance.
• Cognitive decline in aging populations.
• Emotion and memory recall.
• False memories and eyewitness testimony.
• Cognitive processes in creativity.
• Cognitive aspects of decision-making in healthcare.
• The psychology of expertise and skill acquisition.
• Cognitive factors in reading comprehension.
• The role of schemas in information processing.
• Cognitive development in infants.
• Cognitive rehabilitation after brain injury.
• Attention-deficit/hyperactivity disorder (ADHD) and executive functions.
• Neural mechanisms of perception and visual attention.
• The psychology of problem-solving in artificial intelligence.
• Cognitive aspects of mathematical reasoning.
• Neural plasticity and cognitive recovery.
• Cognitive load and its impact on learning.
• Memory consolidation during sleep.
• Attentional disorders and their impact on cognitive functioning.
• The influence of music on cognitive processes.
• Cognitive development in bilingual individuals.
• Cognitive aspects of decision-making in criminal behavior.
• Neural correlates of cognitive control.
• The psychology of cognitive biases in politics.
• Cognitive effects of mindfulness meditation.
• The part working memory plays in academic success.
• Cognitive processes in language acquisition.
• Cognitive factors in problem gambling behavior.
• The psychology of cognitive development in children with autism.
• Cognitive aspects of spatial navigation.
• Memory distortions and the courtroom.
• Neural basis of cognitive dissonance.
• Cognitive aspects of social perception.
• Cognitive rehabilitation in Alzheimer’s disease.

40+ Social Psychology Research Topics

• The impact of social media on self-esteem.
• Groupthink and decision-making.
• Stereotype threat in academic settings.
• Bystander effect in emergencies.
• Cross-cultural perspectives on conformity.
• Online dating and self-presentation.
• The psychology of social influence.
• The role of empathy in prosocial behavior.
• Social identity and intergroup relations.
• Aggression and video game exposure.
• Prejudice and discrimination in modern society.
• The influence of social norms on behavior.
• Attitudes and attitude change.
• Social support and mental health.
• Obedience to authority figures.
• Social comparison and self-concept.
• The psychology of attraction and relationships.
• The bystander intervention model.
• Body image and social media.
• Political polarization and social psychology.
• The psychology of fake news and misinformation.
• Emotional contagion and social interactions.
• Stereotyping in the workplace.
• Consequences of cyberbullying.
• The impact of group dynamics on creativity.
• Gender roles and socialization.
• The role of humor in social interactions.
• Social factors in decision-making and risk-taking.
• Altruism and volunteerism.
• The psychology of leadership and authority.
• Social exclusion and its effects on individuals.
• The relationship between religion and prosocial behavior.
• Social influence in marketing and advertising.
• Online activism and social change.
• The psychology of online communities and forums.
• Attachment styles and adult relationships.
• Social perceptions of beauty and attractiveness.
• Social isolation’s negative consequences on mental health.
• The psychology of public speaking anxiety.
• The role of forgiveness in interpersonal relationships.

40+ Clinical Psychology Research Topics

• Effects of childhood trauma on mental health in adults.
• Efficacy of virtual therapy for treating anxiety disorders.
• Exploring the genetics of schizophrenia.
• Effects of mindfulness meditation on depression.
• Cultural factors in the diagnosis of eating disorders.
• Examining the link between sleep disorders and mood disorders.
• Assessing the effectiveness of group therapy for substance abuse.
• The role of attachment in borderline personality disorder.
• Investigating the stigma surrounding mental illness.
• Treating PTSD in veterans through exposure therapy.
• Neurobiological basis of obsessive-compulsive disorder (OCD).
• Parent-child relationships and their impact on conduct disorder.
• Gender differences in the prevalence of depression.
• Cognitive-behavioral therapy for social anxiety disorder.
• Psychopharmacology and treatment-resistant depression.
• The psychology of self-harm and self-injury.
• Internet addiction and its connection to mental health.
• Assessing the efficacy of art therapy for PTSD.
• Personality disorders and their impact on interpersonal relationships.
• Evaluating the effectiveness of dialectical behavior therapy (DBT) in treating borderline personality disorder.
• Factors contributing to the rise in adolescent depression.
• Exploring the link between childhood abuse and dissociative identity disorder.
• Cross-cultural perspectives on the diagnosis of ADHD.
• The role of serotonin in mood disorders.
• Mindfulness-based stress reduction in chronic pain management.
• Impact of family dynamics on eating disorders in adolescents.
• Examining the long-term effects of child neglect on adult mental health.
• Psychosocial factors in the development of schizophrenia.
• Gender dysphoria and psychological well-being.
• The psychology of resilience in cancer patients.
• Attachment styles and their influence on adult relationships.
• Virtual reality exposure therapy for phobias.
• Exploring the effectiveness of equine therapy for trauma survivors.
• Autism spectrum disorders and early intervention.
• Body image dissatisfaction and its link to eating disorders.
• The psychological impact of chronic illness.
• Cognitive rehabilitation in traumatic brain injury.
• Sleep disorders in children and their impact on academic performance.
• The role of social support in recovery from substance abuse.
• Neuropsychological assessment in Alzheimer’s disease diagnosis.

40+ Developmental Psychology Research Topics

• The impact of parental divorce on child development.
• Adolescents’ self-identity and social media.
• Long-term effects of early childhood attachment on adult relationships.
• Gender identity development in children.
• The influence of birth order on personality development.
• The role of genetics in language development.
• Autism spectrum disorder interventions for toddlers.
• Adolescent peer pressure and substance abuse.
• The impact of bullying on psychological development.
• Sibling rivalry and its long-term effects.
• Parenting styles and their influence on children’s behavior.
• The development of moral reasoning in children.
• Influence of cultural factors on child development.
• Attachment theory and foster care outcomes.
• The impact of technology on cognitive development in children.
• Children’s understanding of death and grief.
• Cognitive development in bilingual children.
• The role of play in early childhood development.
• Attachment disorders and interventions in adopted children.
• The development of emotional intelligence in adolescents.
• The impact of poverty on child development.
• The relationship between nutrition and cognitive development.
• Bullying prevention and intervention programs in schools.
• The role of grandparents in child development.
• Developmental aspects of sibling relationships.
• Child prodigies and their psychological development.
• Gender stereotypes and their influence on children’s aspirations.
• The effects of early education on academic success.
• Cognitive development in children with learning disabilities.
• The impact of divorce on young adults’ romantic relationships.
• Parent-child communication about sex education.
• Adolescents’ body image and its influence on self-esteem.
• Influence of peer relationships on early social development.
• The role of extracurricular activities in adolescent development.
• Long-term outcomes for children in same-sex parent families.
• Cognitive development in children with ADHD.
• The effects of early exposure to screens on cognitive development.
• The role of attachment in adolescent mental health.
• Identity development in multicultural children.

40+ Biological Psychology Research Topics

• The neural basis of addiction and substance abuse.
• The role of genetics in personality traits.
• Effects of sleep deprivation on cognitive function.
• Exploring the gut-brain connection and its impact on mental health.
• Neural mechanisms of stress and its long-term effects.
• The relationship between brain structure and intelligence.
• The impact of exercise on brain health and cognition.
• Neurobiological factors in eating disorders.
• Neural pathways involved in fear and anxiety.
• The influence of hormones on behavior and mood.
• Neuroplasticity and its implications for recovery after brain injuries.
• The biology of memory and amnesia.
• Understanding the neurological basis of schizophrenia.
• The role of neurotransmitters in depression.
• The impact of aging on brain structure and function.
• Neural mechanisms underlying aggression and violence.
• Brain imaging techniques and their applications in research.
• The effects of prenatal exposure to toxins on brain development.
• Neurological aspects of autism spectrum disorders.
• Brain changes associated with post-traumatic stress disorder (PTSD).
• The genetics of Alzheimer’s disease.
• Neurobiology of consciousness and altered states of consciousness.
• The role of the amygdala in emotional processing.
• Neural mechanisms of sexual attraction and orientation.
• The impact of nutrition on brain development and function.
• Brain regions involved in decision-making and impulsivity.
• Neurological factors in Tourette’s syndrome.
• The biology of reward and motivation.
• Neural correlates of empathy and social cognition.
• Genetic predisposition to addiction.
• The influence of hormones on maternal behavior.
• The neurological basis of attention-deficit/hyperactivity disorder (ADHD).
• Adolescent brain development and the effects on behavior.
• The prefrontal cortex’s function in executive tasks.
• Linguistic disorders and language neuroscience.
• Neuroinflammation’s effects on mental health.
• Mechanisms in the brain that affect sensory perception.
• Neurological and genetic influences on bipolar disorder.
• The impact of persistent pain on brain development and function.
• The endocannabinoid system’s function in controlling mood.

Research Methodology for Psychology Topics

Understanding various research methodologies is key to conducting a successful study. Whether you opt for experimental designs, surveys, case studies, or sophisticated data analysis, each method offers unique insights. Choose the methodology that aligns with your research questions and objectives, ensuring a robust and reliable study.

Resources for Psychology Research

In the digital age, a wealth of resources for psychology topics to research is at your fingertips. Utilize academic journals, databases, books, and online courses to enhance your understanding. 

Engage with professional organizations and attend conferences to stay updated with the latest research trends and network with fellow enthusiasts.

Tips for Successful Psychology Topics for Research

• Choose a Fascinating Topic: Select a research topic that genuinely interests you. Your passion and curiosity will drive your motivation and engagement throughout the research process.
• Narrow Your Focus: Refine your research question to ensure it’s specific and manageable. A focused question will lead to more meaningful and in-depth findings.
• Conduct a Thorough Literature Review: Familiarize yourself with existing research in your chosen area. This helps you build on prior knowledge and identify gaps in the literature.
• Hypothesize and Predict: Develop clear hypotheses and predictions for your study. This sets the direction for your research and provides a framework for data collection and analysis.
• Choose the Right Research Method: Select the research method that best suits your research question, whether it’s experiments, surveys, interviews, or case studies.
• Ethical Considerations: Prioritize ethical guidelines in your research, including obtaining informed consent, ensuring confidentiality, and avoiding harm to participants.
• Sample Selection: Carefully choose your sample to make sure it’s representative of the population you’re studying. Consider factors like age, gender, and cultural diversity.
• Data Collection: Collect data systematically and ensure its accuracy and reliability. Use well-established measurement tools when applicable.
• Data Analysis: Employ appropriate statistical techniques to analyze your data. Make use of software like SPSS or R for thorough analysis.
• Interpret Results Objectively: Avoid confirmation bias and interpret your results objectively, even if they don’t align with your initial hypotheses.
• Discuss Limitations: Acknowledge the limitations of your study in your research paper. This demonstrates your awareness of potential weaknesses and strengthens your research’s credibility.
• Contribute to the Field: Highlight the significance of your research and how it contributes to the broader field of psychology. What does it add to existing knowledge?
• Write Clearly and Concisely: Communicate your findings in a clear, concise, and well-structured manner. Use APA or other relevant style guides for formatting.
• Peer Review: Seek feedback from colleagues, mentors, or professors. Peer review can help identify blind spots and improve the quality of your work.
• Stay Organized: Maintain detailed records of your research process, including notes, data, and references. Organization is key to successful research.
• Time Management: Plan your research timeline carefully, allocating sufficient time for each stage, from literature review to data collection and analysis.
• Persevere: Research often involves setbacks and challenges. Stay persistent, adapt when necessary, and remain dedicated to your research goals.
• Publish and Share: Consider presenting your research at conferences and seek opportunities for publication in academic journals . Sharing your findings contributes to the advancement of the field.
• Stay Informed: Keep up with the latest research trends and developments in psychology. Attend conferences and join professional organizations to stay connected with the academic community.
• Collaborate: Don’t hesitate to collaborate with other researchers, as teamwork can lead to valuable insights and more significant research outcomes.

Choosing the psychology topics to research is akin to embarking on an adventure into the depths of the human mind. Each topic holds the potential to unravel mysteries, challenge assumptions, and make a meaningful impact on individuals and society. 

As you venture into this realm, remember that your curiosity and dedication are your greatest assets. Embrace the journey, learn from every step, and let your research contribute to the ever-expanding tapestry of psychological knowledge. Happy researching!

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119 Intelligence Research Topics & Essay Examples

📝 intelligence research papers examples, 👍 good intelligence essay topics to write about, 🏆 best intelligence essay titles, 🎓 simple research topics about intelligence, ❓ intelligence research questions.

• The Wechsler Intelligence Scales Psychology essay sample: The Wechsler Intelligence Scales are used to gauge the rational functioning of grown and children. This work ratify the nature of the WISC-III Functional Distractibility factor.
• Emotional Intelligence: Why and How to Enhance It? Psychology essay sample: High emotional intelligence level enables a person to form meaningful relationships and lead to success in life spheres such as work and education.
• Experiential Hospitality and Emotional Intelligence Psychology essay sample: This work gives an example of given a guest an experiential stay and outlines the importance of emotional intelligence for hospitality managers using literature sources.
• Emotional Intelligence Analysis Psychology essay sample: Individuals with a higher level of EQ have a better chance of navigating through social complexities and making decisions that are in line with the existing environment.
• Crystallized Intelligence and Psychometrics: Definition Psychology essay sample: Crystallized Intelligence describes the accumulation of skills acquired over a specific duration. Psychometrics refers to the methods applied in the design of psychological tests.
• Childhood Experience Connected to Adult Intelligence Psychology essay sample: Our feelings and thoughts in childhood shape our personality because personal growth always occurs gradually and under the influence of many factors.
• Emotional Intelligence: Annotated Bibliography Psychology essay sample: This paper reviews such articles as “Emotional Intelligence: Theory, Finding, and Implications”, “A review and critique of emotional intelligence measures,” and others.
• Emotional Intelligence and Its Components Psychology essay sample: Emotional intelligence is a person’s ability to understand their emotions and handle them well. This ability consists of four components.
• Determinants of Intelligence and Creativity Psychology essay sample: Researchers have demonstrated that both the environment and heredity have a collaborative influence on intelligence.
• Emotional Intelligence (EQ) in the Workplace Psychology essay sample: High EQ contributes to better professional cooperation since this ability allowed me to identify whether it was suitable to ask a person for a favor or it was better to give support.
• Emotional Intelligence: Theories and Experiments Psychology essay sample: This paper describes models and theories for defining and describing emotional intelligence, experiments in this area, and proving hypotheses.
• Intelligence Measurement Theories by Gardner and Sternberg Psychology essay sample: Gardner included difficult-to-measure types in his theory (kinesthetic, musical, naturalistic), while Stenberg chose criteria that can be tested in traditional forms of tasks.
• Reflection on the Emotional Intelligence Psychology essay sample: Emotional intelligence is one of the most important and necessary qualities in the modern world. People who hold ruling positions and manage a team especially need this skill.
• Primal Leadership With Emotional Intelligence Psychology essay sample: Emotional intelligence is vital particularly in management and leadership because it helps ease the management of one’s emotions, and that of a group of individuals.
• Emotional Intelligence: Description and Quiz Results Psychology essay sample: Emotional intelligence influences numerous dissimilar facets of one’s everyday undertakings, for instance, how one acts and the mode of one’s interrelations with others.
• Practical and Emotional Intelligence: Application and Examples Psychology essay sample: Lay people term practical intelligence as street smart, which is different from book smart, a term used to refer to emotional intelligence.
• Emotional Intelligence Findings Psychology essay sample: The paper explains what emotional responses look like and their importance when interacting in social settings, and how can we be “in check” with our emotions.
• Intelligence Testing in Clinical Psychology Psychology essay sample: Intelligence is an integral component with regard to human undertakings in social settings. It facilitates survival in various situations that characterize contemporary society.
• IQ (Intelligence Quotient) Tests Do Not Reflect Intelligence Psychology essay sample: IQ (Intelligence Quotient) tests scores should be estimated carefully and held several times to adequately measure children’s abilities.
• The Importance of Emotional Intelligence Psychology essay sample: Effective leaders have one characteristic in common: strong emotional intelligence. Intelligence quotient and hard skills, such as technical expertise and analytical knowledge.
• Intelligence: Defining, Measuring, and Testing Psychology essay sample: This essay provides insight into various controversies, pros, and cons of the approaches to defining and measuring intelligence.
• Social and Emotional Intelligence Psychology essay sample: This paper will examine the characteristics of social and emotional intelligence to determine the impact on leadership skills.
• Emotional Intelligence and Personal Development Plan Psychology essay sample: It is crucial to pay attention to emotional intelligence and its development in order to improve performance in the workplace. For this aim, multiple assessments were elaborated.
• Fundamentals of Psychology: The Intelligence Test Psychology essay sample: The intelligence test was to be used as a specialized tool that would recognize children needing technical assistance.
• Emotional Intelligence and the "Three Good Things" Psychology essay sample: One of the main components of emotional intelligence is knowing one's weaknesses and strengths and co-existing with them calmly and managing emotions.
• Emotional Intelligence and Its Importance Psychology essay sample: This essay will discuss and examine the concept of emotional intelligence and its personal and social importance, and its correlation with the achievement of personal goals.
• Theories of Intelligence in Transformative Learning Psychology essay sample: Intelligence, as a concept, has become a topic for many debates providing ground for new ideas in psychology. The very notion of intelligence is a point of controversy.
• The Role of the Emotional Intelligence in the Communication Psychology essay sample: The paper aims to discuss the role of the emotional intelligence in the communication, team building, and relationship building.
• The Development of Emotional Intelligence Psychology essay sample: The development of emotional intelligence is an important part of each person's self-development, which should be paid maximum attention to.
• Wechsler Intelligence Scale for Children Instrument Assessment Psychology essay sample: The Wechsler Intelligence Scale for Children (WISC) is a test that is designed to evaluate intelligence in children of different ages.
• Emotional Intelligence and Leadership Psychology essay sample: Emotional Intelligence (EI) is the ability to have compassion, sympathy, and emotional participation for members who are involved in an organization.
• Thinking and Intelligence in Psychological Science Psychology essay sample: In psychological science, based on the doctrine of the active nature of the human psyche, thinking and intellect occupy an essential place.
• “The Minnesota Twin Family Study” and “Genetic Study of Genius” Psychology essay sample: This paper analyzes studies “The Minnesota Twin Family Study” about differences between the monozygotic twin reared apart and “Genetic Study of Genius” about high IQ students.
• Researching of Emotional Intelligence Psychology essay sample: Emotional intelligence is the reverse side of rational intelligence, the ability of a person to manage their emotions, understand the feelings and intentions of others.
• The Relationship Between Intelligence and Creativity Psychology essay sample: This essay explores various arguments that explain the correlation between intelligence and creativity by drawing evidence from related studies.
• Cross-Sectional and Longitudinal Research Methods Psychology essay sample: The current paper describes the most commonly used methods of developmental research. They are cross-sectional and longitudinal designs.
• Mental Testing as Cornerstone of Applied Psychology Psychology essay sample: Mental testing was invented in the 19th century as a reaction to the development of compulsory primary education, which required the assessment of children's cognitive abilities.
• Piaget’s Theory of Cognitive Development Psychology essay sample: Piaget's theory of cognitive development refers to ways in which human intelligence undergoes growth and development.
• Children Born During Pandemic Have Lower IQs Psychology essay sample: “Children Born During Pandemic Have Lower IQs, US Study Finds” reveals findings of a study on children's cognitive development and intelligence quotient (IQ).
• Team-Building Across Cultures: Literature Review Psychology essay sample: This paper analyzes team building across cultures, the major challenges and positive factors in cross-cultural team-building and reflect on specific approaches to leadership.
• Chapters 9 and 10 of Psychology by Myers & DeWall Psychology essay sample: Since the mind makes snap judgments according to preexisting concepts and prototypes, it is also prone to errors.
• Problem-Solving, Decision-Making, and Intelligence Psychology essay sample: Problem-solving, creativity, decision-making, and intelligence are overlapping constructs, often indistinguishable even for scholars.
• The Nature of Human Intelligence Psychology essay sample: The ability to think, learn from experience, solve issues, and adjust to new circumstances is known as intelligence.
• Artificial Intelligence, Expert Systems and Robotics
• Self-Concept, Personality and Emotional Intelligence in Primary Education
• Academic Performance and Fluid Intelligence
• Artificial Intelligence and Blockchain Used in Accounting
• Intelligence and Adapting for Graduate School
• Ascertaining Critical Variables Using Artificial Intelligence Tools
• The Useful of Artificial Intelligence in Nursing Technologies can make nursing practice more efficient, but technologies with human reasoning are even more helpful, which is why nurses need artificial intelligence applications.
• Artificial Intelligence: The Branch of Compute
• Intelligence Child Development
• Emotional Intelligence Reflection Paper: The Importance of EI in Nursing Leadership Read this essay to learn about emotional intelligence in nursing and find a reflection on personal EI.
• Android Applications With Artificial Intelligence
• Intelligence and Its Relationship to Human Cognition
• Auditory and Visual Intelligence Development Evolution
• Banks, Financial Services and Artificial Intelligence
• The Emotional Intelligence of Adolescents and Their Risk-Taking Behavior
• Understanding People and Organisations Intelligence
• The Process of Formation of Intelligence
• General Intelligence and Specific Abilities Psychology
• Development of Language Skills and Intelligence
• Howard Gardner’s Theory and Types of Intelligence
• Cognitive Ability and Intelligence
• Government Size, Intelligence and Life Satisfaction
• Leadership Styles and Emotional Intelligence in Educators
• Cognitive Intelligence for Effective Leadership
• Crimes: The Role of People With High, Average, and Low Intelligence
• Cultural Intelligence and Intercultural Competency
• Heritability and Malleability of Intelligence
• Digital Intelligence and Digital Marketing Effectiveness
• Grade Point Average and Intelligence Quotient
• The Connection of Intelligence With Narcissism and Achievement Motivation
• Dolphin Intelligence and Interaction With Humans
• The Value of Art for Intelligence and Communication
• Economic Factors and Impact on Intelligence and Growth
• Education, Academic Intelligence, and Personal Experience
• Academic Definition and History of Emotional Intelligence
• Environmental Factors That Affect Intelligence
• The Role of Metacognitive and Cognitive Cultural Intelligence
• Active Empathic Listening and Emotional Intelligence
• The Relationship Between Theories of Intelligence and Beliefs About Brain Development
• Factors Determining the Level of Intelligence in Human Beings
• Gap Between Intelligence and Emotion
• History and Testing Measures of Intelligence Theory
• Connection of Personality With Self-Assessment of Intelligence
• Intelligence and How Can We Tell a Person Is Intelligent
• Link Between Depression and Intelligence
• Memory Processes Thinking and Language Intelligence
• Can Robots Have Human Intelligence?
• How Did Different Psychologists Define Intelligence?
• How Can You Measure Your Current Emotional Intelligence?
• What Is Gardner’s Theory of Multiple Intelligences?
• Does Intelligence Affect Confidence?
• Can Personality and Level of Intelligence Be Changed?
• Does Physical Exercise Increase People’s Intelligence?
• What Are the Ethical Problems of Artificial Intelligence?
• Does the Writing Process Improve Verbal Intelligence?
• How Does Music Affect Intelligence?
• Does the Intelligence Test Measure What It Claims to Measure?
• How Cultures Affect Perceptions of Intelligence?
• Does Intelligence Boost Happiness?
• Can Animals Demonstrate Intelligence?
• Does Birth Order Have an Effect on Intelligence?
• How Does Autism Affect Intelligence?
• Does Being Talented Affect a Child ‘s Intelligence?
• Is the Internet Lowering Human Intelligence and “Making Us Stupid”?
• What Are the Main Traditions of Measuring Intelligence?
• Does Intelligence Affect Interpersonal Communication?
• What Are the Styles of Creative Intelligence?
• Can Personality and Intelligence Be Inherited?
• Can Cultural Intelligence Affect Employees Innovative Behavior?
• What Are the Arguments “For” and “Against” Artificial Intelligence?
• Can Artificial Intelligence Lead to a More Sustainable Society?
• Does Intelligence Quotient Determine Success?
• Can Artificial Intelligence Become Smarter Than Humans?
• Can Group Intelligence Help Entrepreneurs Find Better Opportunities?
• What Is Intelligence Quotient?
• Can Beauty and Intelligence Be Related?

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Impacts of generative artificial intelligence in higher education: research trends and students’ perceptions.

1. Introduction

2. materials and methods.

• “Generative Artificial Intelligence” or “Generative AI” or “Gen AI”, AND;
• “Higher Education” or “University” or “College” or “Post-secondary”, AND;
• “Impact” or “Effect” or “Influence”.
• Q1— Does GenAI have more positive or negative effects on higher education? Options (to choose one): 1. It has more negative effects than positives; 2. It has more positive effects than negative; 3. There is a balance between positive and negative effects; 4. Don’t know.
• Q2— Identify the main positive effect of Gen AI in an academic context . Open-ended question.
• Q3— Identify the main negative effect of Gen AI in an academic context . Open-ended question.

3.1. Impacts of Gen AI in HE: Research Trends

3.1.1. he with gen ai, the key role that pedagogy must play, new ways to enhance the design and implementation of teaching and learning activities.

• Firstly, prompting in teaching should be prioritized as it plays a crucial role in developing students’ abilities. By providing appropriate prompts, educators can effectively guide students toward achieving their learning objectives.
• Secondly, configuring reverse prompting within the capabilities of Gen AI chatbots can greatly assist students in monitoring their learning progress. This feature empowers students to take ownership of their education and fosters a sense of responsibility.
• Furthermore, it is essential to embed digital literacy in all teaching and learning activities that aim to leverage the potential of the new Gen AI assistants. By equipping students with the necessary skills to navigate and critically evaluate digital resources, educators can ensure that they are prepared for the digital age.

The Student’s Role in the Learning Experience

The key teacher’s role in the teaching and learning experience, 3.1.2. assessment in gen ai/chatgpt times, the need for new assessment procedures, 3.1.3. new challenges to academic integrity policies, new meanings and frontiers of misconduct, personal data usurpation and cheating, 3.2. students’ perceptions about the impacts of gen ai in he.

• “It harms the learning process”: ▪ “What is generated by Gen AI has errors”; ▪ “Generates dependence and encourages laziness”; ▪ “Decreases active effort and involvement in the learning/critical thinking process”.

4. Discussion

• Training: providing training for both students and teachers on effectively using and integrating Gen AI technologies into teaching and learning practices.
• Ethical use and risk management: developing policies and guidelines for ethical use and risk management associated with Gen AI technologies.
• Incorporating AI without replacing humans: incorporating AI technologies as supplementary tools to assist teachers and students rather than replacements for human interaction.
• Continuously enhancing holistic competencies: encouraging the use of AI technologies to enhance specific skills, such as digital competence and time management, while ensuring that students continue to develop vital transferable skills.
• Fostering a transparent AI environment: promoting an environment in which students and teachers can openly discuss the benefits and concerns associated with using AI technologies.
• Data privacy and security: ensuring data privacy and security using AI technologies.
• The dynamics of technological support to align with the most suitable Gen AI resources;
• The training policy to ensure that teachers, students, and academic staff are properly trained to utilize the potential of Gen AI and its tools;
• Security and data protection policies;
• Quality and ethical action policies.

5. Conclusions

• Database constraints: the analysis is based on existing publications in SCOPUS and the Web of Science, potentially omitting relevant research from other sources.
• Inclusion criteria: due to the early stage of scientific production on this topic, all publications were included in the analysis, rather than focusing solely on articles from highly indexed journals and/or with a high number of citations as recommended by bibliometric and systematic review best practices.
• Dynamic landscape: the rate of publications on Gen AI has been rapidly increasing and diversifying in 2024, highlighting the need for ongoing analysis to track trends and changes in scientific thinking.

Author Contributions

Institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Share and Cite

Saúde, S.; Barros, J.P.; Almeida, I. Impacts of Generative Artificial Intelligence in Higher Education: Research Trends and Students’ Perceptions. Soc. Sci. 2024 , 13 , 410. https://doi.org/10.3390/socsci13080410

Saúde S, Barros JP, Almeida I. Impacts of Generative Artificial Intelligence in Higher Education: Research Trends and Students’ Perceptions. Social Sciences . 2024; 13(8):410. https://doi.org/10.3390/socsci13080410

Saúde, Sandra, João Paulo Barros, and Inês Almeida. 2024. "Impacts of Generative Artificial Intelligence in Higher Education: Research Trends and Students’ Perceptions" Social Sciences 13, no. 8: 410. https://doi.org/10.3390/socsci13080410

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NIH Guidance on Artificial Intelligence (AI) in Research – August 2024

The National Institutes of Health (NIH) has recently released a webpage on Artificial Intelligence (AI) in Research: Policy Considerations and Guidance (external link) , aimed to “guide stakeholders across the biomedical and behavioral research ecosystem.”

This NIH guidance provides “policies, best practices, and regulations,” specifically addressing the following topics:

• Research Participant Protections
• Data Management and Sharing
• Health Information Privacy
• Licensing, Intellectual Property, & Technology Transfer
• Peer Review
• Biosecurity and Biosafety

The Office of Research Compliance recommends this resource to researchers involved in the use of AI in research, particularly those conducting NIH-supported research.