Scientists Identify Fifteen Key Motives Driving Human Behaviour
Researchers at HSE University and the London School of Hygiene and Tropical Medicine have identified 15 key motives that drive human behaviour. By analysing people's views, preferences, and actions through an evolutionary lens, they demonstrated how these motives intertwine to shape habits and interpersonal relationships. The findings have been published in Personality and Individual Differences.
The question of what motivates human behaviour has long intrigued psychologists. Various approaches are used to assess these underlying motives. The most well-known theory is Abraham Maslow's hierarchy of needs, introduced in the mid-20th century. However, most approaches emphasise the social aspects of motivation while overlooking its evolutionary underpinnings.
A group of researchers at HSE University and the London School of Hygiene and Tropical Medicine proposed analysing human behaviour motives from an evolutionary perspective. In the proposed framework, all motives are viewed as evolutionary adaptations that enhanced early humans' ability to survive in their environment and continue to influence behaviour today. The scientists proceed from the premise that if certain evolutionary mechanisms once triggered specific behaviours, the underlying motives can be identified using standard psychometric techniques.
To accomplish this, the study authors conducted an online survey with over 500 participants who were asked to rate 150 statements concerning their everyday preferences, fears, desires, and social aspirations. The statements were based on previously identified motives from other studies reflecting physical, reproductive, or social needs, such as 'I enjoy going on roller coasters,' 'Eating is less important to me than it seems to be for most people,' and 'I spend a lot of time staying in touch with my friends,' among others.
Using network analysis, the researchers identified stable clusters of motives. The study found that human behaviour is driven by 15 key motives, which can be grouped into five broad categories: environmental (Hoard, Create), physiological (Fear, Disgust, Hunger, Comfort), reproductive (Lust, Attract, Love, Nurture), psychological (Curiosity, Play), and social (Affiliate, Status, Justice).

The researchers also identified functional relationships between motives, contributing to a deeper understanding of motivational structures. For example, Justice has strong ties to Nurture and Curiosity, suggesting that it is a function of both concern for the welfare of others and a need to keep abreast of where anti-social behaviours might be occurring.
Interestingly, the motives of Play and Status emerged as pivotal points of connectivity, interacting extensively with other nodes, suggesting they influence a broad range of related motives. Status appears to be important as it facilitates the attainment of other goals by providing access to resources that enhance the chances of success in life, including attracting a partner. Maintaining status involves hoarding resources, fearing the loss of these resources, and effectively using them in various situations. The motive of play, in turn, helps develop the skills needed to maintain status and adapt to changing circumstances.
'Using network-based psychometric techniques, we were able to observe how motives interrelate. For instance, the motives of Love and Nurture are positioned close to each other in the network, which makes sense from an evolutionary perspective, as caring for offspring enhances their chances of survival. Conversely, the motives of Fear and Curiosity often have opposing effects. Fear keeps us away from danger, but when excessive, it can suppress curiosity, which fosters knowledge and innovation,' explains Albina Gallyamova, Junior Research Fellow at the HSE Centre for Sociocultural Research.
The study also revealed age- and gender-related variations in the significance of different motives. Women tend to show a greater interest in the motives of Nurture and Comfort, while men are more likely to focus on the motives of Status and Attraction. The researchers note that these differences are linked to the traditional roles men and women played in our evolutionary past.
Age also contributes to shaping our priorities. Younger individuals tend to be more focused on Status and Play, while as people age, Fear and concern for Comfort become more prominent. 'These changes reflect different life stages: initially, we strive to secure our place in society, and later, we focus on safety and survival,' adds Gallyamova.
The study findings can be valuable in various fields, ranging from marketing to IT. For example, in advertising, understanding the motives of different social groups allows for more precise and effective communication. Youth focused on Status and Play are more likely to respond to incentives related to prestige and entertainment, while a more mature audience prioritises safety, reliability, and comfort. In the field of AI, understanding evolutionary motives enables a more human-centred approach, offering gamification and social interaction for younger users, while emphasising convenience and simplicity for the older generation. In therapy, understanding the underlying motives can help provide a more accurate response to the client's needs. For example, addressing anxiety can take into account the evolutionary mechanism of avoiding danger and help strike a balance between safety and curiosity.
'Ultimately, understanding the evolutionary motives that drive our behaviour enables us to create solutions that make people's lives more comfortable, safer, and more interesting,' explains Gallyamova.
See also:
'Our Goal Is Not to Determine Which Version Is Correct but to Explore the Variability'
The International Linguistic Convergence Laboratory at the HSE Faculty of Humanities studies the processes of convergence among languages spoken in regions with mixed, multiethnic populations. Research conducted by linguists at HSE University contributes to understanding the history of language development and explores how languages are perceived and used in multilingual environments. George Moroz, head of the laboratory, shares more details in an interview with the HSE News Service.
Slim vs Fat: Overweight Russians Earn Less
Overweight Russians tend to earn significantly less than their slimmer counterparts, with a 10% increase in body mass index (BMI) associated with a 9% decrease in wages. These are the findings made by Anastasiia Deeva, lecturer at the HSE Faculty of Economic Sciences and intern researcher in Laboratory of Economic Research in Public Sector. The article has been published in Voprosy Statistiki.
Scientists Reveal Cognitive Mechanisms Involved in Bipolar Disorder
An international team of researchers including scientists from HSE University has experimentally demonstrated that individuals with bipolar disorder tend to perceive the world as more volatile than it actually is, which often leads them to make irrational decisions. The scientists suggest that their findings could lead to the development of more accurate methods for diagnosing and treating bipolar disorder in the future. The article has been published in Translational Psychiatry.
Scientists Develop AI Tool for Designing Novel Materials
An international team of scientists, including researchers from HSE University, has developed a new generative model called the Wyckoff Transformer (WyFormer) for creating symmetrical crystal structures. The neural network will make it possible to design materials with specified properties for use in semiconductors, solar panels, medical devices, and other high-tech applications. The scientists will present their work at ICML, a leading international conference on machine learning, on July 15 in Vancouver. A preprint of the paper is available on arxiv.org, with the code and data released under an open-source license.
HSE Linguists Study How Bilinguals Use Phrases with Numerals in Russian
Researchers at HSE University analysed over 4,000 examples of Russian spoken by bilinguals for whom Russian is a second language, collected from seven regions of Russia. They found that most non-standard numeral constructions are influenced not only by the speakers’ native languages but also by how frequently these expressions occur in everyday speech. For example, common phrases like 'two hours' or 'five kilometres’ almost always match the standard literary form, while less familiar expressions—especially those involving the numerals two to four or collective forms like dvoe and troe (used for referring to people)—often differ from the norm. The study has been published in Journal of Bilingualism.
Overcoming Baby Duck Syndrome: How Repeated Use Improves Acceptance of Interface Updates
Users often prefer older versions of interfaces due to a cognitive bias known as the baby duck syndrome, where their first experience with an interface becomes the benchmark against which all future updates are judged. However, an experiment conducted by researchers from HSE University produced an encouraging result: simply re-exposing users to the updated interface reduced the bias and improved their overall perception of the new version. The study has been published in Cognitive Processing.
Mathematicians from HSE Campus in Nizhny Novgorod Prove Existence of Robust Chaos in Complex Systems
Researchers from the International Laboratory of Dynamical Systems and Applications at the HSE Campus in Nizhny Novgorod have developed a theory that enables a mathematical proof of robust chaotic dynamics in networks of interacting elements. This research opens up new possibilities for exploring complex dynamical processes in neuroscience, biology, medicine, chemistry, optics, and other fields. The study findings have been accepted for publication in Physical Review Letters, a leading international journal. The findings are available on arXiv.org.
Mathematicians from HSE University–Nizhny Novgorod Solve 57-Year-Old Problem
In 1968, American mathematician Paul Chernoff proposed a theorem that allows for the approximate calculation of operator semigroups, complex but useful mathematical constructions that describe how the states of multiparticle systems change over time. The method is based on a sequence of approximations—steps which make the result increasingly accurate. But until now it was unclear how quickly these steps lead to the result and what exactly influences this speed. This problem has been fully solved for the first time by mathematicians Oleg Galkin and Ivan Remizov from the Nizhny Novgorod campus of HSE University. Their work paves the way for more reliable calculations in various fields of science. The results were published in the Israel Journal of Mathematics (Q1).
Large Language Models No Longer Require Powerful Servers
Scientists from Yandex, HSE University, MIT, KAUST, and ISTA have made a breakthrough in optimising LLMs. Yandex Research, in collaboration with leading science and technology universities, has developed a method for rapidly compressing large language models (LLMs) without compromising quality. Now, a smartphone or laptop is enough to work with LLMs—there's no need for expensive servers or high-powered GPUs.
AI to Enable Accurate Modelling of Data Storage System Performance
Researchers at the HSE Faculty of Computer Science have developed a new approach to modelling data storage systems based on generative machine learning models. This approach makes it possible to accurately predict the key performance characteristics of such systems under various conditions. Results have been published in the IEEE Access journal.