Our science

Personomist rests on the idea that people are complex and that this deserves respect. No person can be placed in a personality "type", even though pseudoscientific solutions do so. For many scientific purposes it is enough to describe people only by abstract dimensions such as the Big Five. But building a psychological profile that is recognisable and useful for a real person takes more.

A unique 100D model for each person

Personomist builds a unique profile of each person's personality from about a hundred traits. You can think of it as a high-resolution 100D psychological model. In the next steps, a person's model is compared with other models that help discover their personality from different angles.

5 broad traits
30 traits
100 narrow traits
Described by five broad traits, a person can remain a stranger; described by narrow ones, they become someone you recognise (Henry and Mõttus, 2025a).

To compute the Big Five, for example, we compare a person's personality model with the models of extraversion, conscientiousness and the other Big Five traits. To describe the Wellbeing landscape, we compare it with the models of stress resilience, ability to concentrate and ability to relax. To place a person in the career landscape, we compare their model with the models of people in more than 120 jobs. And so on: the same model can be used for a great many comparisons.

Extraversioncomparison groupStress resilienceSoodla et al., 2025how far alongSales manager83,828 peopleA habityour goalYour modelcomparison group
Your model is a point; each comparison looks at it from one direction. The point does not move; only the direction changes. Each direction carries a tag saying where that model comes from. A simplified picture of a much larger space.

How the model is built

  1. We ask about 100 questions about typical ways of behaving, thinking and feeling. Each question is about a different nuance of personality.
  2. We neutralise the answers for gender and age, so that a person is compared with people of the same age and gender. For this we use associations found in the data of about 14,000 people, each of whom was also described with the same questions by someone who knows them well.
  3. We analyse the patterns in the answers with a psychological model pre-trained on a large sample of people. It finds a suitable compromise between the person's own answer and what their other answers, given other people's data, predict about the same trait. Each answer thus becomes, together with contributions from many other answers, a feature of its own in our 100D model. The average person's value on each feature is 0, and people typically differ from it by about one unit. In the comparison group, this step raised the agreement between self-descriptions and other people's descriptions by more than 30% on average.
  4. This is the person's basic psychological model, which can be used flexibly to draw other conclusions.
  5. From other people's data we have built a model of each Big Five trait, of more than 120 jobs, of the Wellbeing landscape's traits and of much else. A person's basic model can be compared with these models, giving a similarity and showing exactly which features raise that similarity and which lower it.

How we show the Big Five and other scores

Five levels
Each Big Five trait is a score with an average of 0. It comes from comparing a person's basic model with the Big Five model. We show results on a scale of 1 to 5, so that each level is expected to hold about a fifth of people (the levels are cut at −0.85, −0.25, 0.25 and 0.85 standard deviations). We avoid showing more precise results, to keep small differences from being over-interpreted: small fluctuations are often only the situation or measurement noise.
Sub-traits
For each Big Five trait we show up to 12 sub-traits that characterise it best, ordered by how strongly they show up in you. So you see how your extraversion or conscientiousness score comes about. Two people with exactly the same score can get there through different sub-traits: our results show how it is expressed uniquely in you.
Interesting profiles
We also estimate how evenly each score is formed (consistency): whether all the signs point to one value of the score, or the traits underlying it show up differently in a person. When some sub-traits are high and others low, the trait cannot be summed up well by one number. When consistency is below 40%, we mark the trait "Interesting" and open its sub-traits straight away, to draw attention to it.
1≈ 20%2≈ 20%3≈ 20%4≈ 20%5≈ 20%−0.85−0.250.250.85
The level cut-offs in standard deviations, and the approximate share of people at each level.

What does "90% similarity" mean?

Personomist uses a very large database on what sets the people in each job apart from people in other jobs. Your similarity to each job shows how strongly your personality traits point the same way. At 50% your personality model leans neither towards it nor away. At 90% it clearly points the job's way. The percentage roughly follows percentiles: 90% means your model points the job's way more strongly than about 90% of people do.

We show the range 5–95%, because 0 and 100% would suggest a complete (dis)similarity this kind of estimate does not give. It does not take skills, education or work experience into account. Note that the results are descriptive: how similar you are to the people in that job in what sets them apart from others. They do not say which work you should do or what is right for you. There are a great many other reasons why people do one job or another.

5%points away50%leans neither way95%points the job's waySales manager · 90%
A sample result. Each job shows how many people its model rests on.

Personomist gets to know you better and better

The first time you answer, you already get a useful profile, but it can be made better still.

  • If you answer again a few days or a couple of weeks later, the quality of the information improves and the model becomes more stable and reliable. Answers given within 30 days are taken together. Psychologists call this improving reliability.
  • Adding information from other sources reduces systematic biases, related for example to a person's self-perception or to how they understand the questions. It also opens the chance to see yourself through others' eyes, which no approach based only on a person's own information can offer.
  • Personality is not fixed, so it is worth building a new model of yourself in future and comparing it with the earlier one.
  • The personality profile can be extended with the results of other questionnaires, on wellbeing, interests and, in future, other things.

Users who have saved their results can fill in the questionnaires repeatedly, either to make the results more reliable or to follow changes. You can also invite other people to answer the questions about you. Their answers are combined, and results are shown only once at least two people have answered. Then Others' view opens, and the Combined view, which synthesises everyone's information and is usually the most accurate. In the Combined view your self-description carries the same weight as each description by someone else.

Your viewOthers' view3 descriptionsCombinedLow extraversionHigh extraversion
One trait in three views. Combined sits where equal weights put it: your description once, each other person's description once.

Each result is the model's prediction about you. Read it against your own experience and look for examples in your life.

In more depth

What the results are calculated from

  • Traits and the Big Five14,000 people

    Basis: the comparison group, about 14,000 people from the Estonian Biobank's personality data (Arumäe et al., 2025). The Big Five give a bird's-eye view: five broad dimensions from 60 of the traits, as in Anni, Vainik and Mõttus (2025). We call neuroticism Emotionality.

  • Wellbeing landscape16,226 people

    Ability to concentrate, Ability to relax and Stress resilience, estimated from personality using associations found in the data of 16,226 Estonian Biobank participants (Soodla et al., 2025). These scores bring together combinations of stable tendencies that go with different levels of wellbeing, so they describe the psychological landscape behind wellbeing. How work has been going for you over the last 30 days is what the work wellbeing questionnaire shows, and in future a questionnaire on the different sides of general wellbeing.

  • Jobs83,828 people

    Personomist compares your personality model with the models of 128 jobs. They rest on 83,828 people working in those jobs: Estonian job means (Anni, Vainik and Mõttus, 2025) and the public data of the whichjob.me app, from which people who have stayed in their job and are satisfied with it were taken. Each job shows how many people its model rests on.

  • Work rolesAI ratings

    Work-role models rated on the same traits by several AI models. They are not based on data from people.

  • Free timeUniversity of Tartu

    University of Tartu research data on what people with different personalities do in their free time. About 2,000 people took part, describing more than 5,000 free-time activities. We will soon add at least as much data again.

  • Recommendationsyour goal

    The habit recommendations were written by clinical psychologists to match your personality profile. A recommendation weighs where you are now and how far that is from how you want to be, which you describe in the ideal-self questionnaire; until you do, your model is compared with what is generally considered desirable.

  • Work wellbeingBAT-23

    The Burnout Assessment Tool, an internationally used questionnaire grounded in research literature. The questions are about wellbeing at work over the last 30 days and are brought together into five scores. The scores' risk-level cut-offs currently come from the BAT manual and rest on a sample of 1,403 people in Flanders, but we plan to make them more thorough. The results are not diagnoses. Work wellbeing recommendations come with the result, written by a work psychologist to match the pattern of your answers.

  • ComingUniversity of Tartu

    A non-clinical wellbeing questionnaire, with norms from University of Tartu research.

Who is behind it

Personomist's science comes from the personality and wellbeing research group at the University of Tartu's Institute of Psychology. The team includes clinical psychologists. The research and development were co-funded by the European Union (ASTRA+ measure).

The team and funders

For scientists

Narrow traits. Narrow traits carry content independent of the broad traits, which is stable over time and recognised in the same way by other people (Mõttus et al., 2017). The questions come from the 100 nuances item pool (Henry and Mõttus, 2025b).

Scoring. The value expected from gender and age (with a quadratic term), estimated by regression in the comparison group, is subtracted from the raw answers. Each trait is then predicted from the others with an elastic net model (α = 0.5); the trait's own answer has weight 1 before variance normalisation. Self-descriptions and descriptions by others have separate models. Finally, scores are standardised to the comparison group's mean and spread. Ages outside 20 to 70 take the nearest end; where gender is unknown or "Other", the average of women and men is used.

What this buys, and what it costs. In the comparison group, the correlation between self-descriptions and acquaintances' descriptions was computed for each trait. It rose for every trait, by 32% on average on the Fisher z scale, most where agreement was lowest to begin with. Each trait is measured by one question, so each detail on its own is less certain than a broad trait's score. Using the other answers reduces random error. The price is that a trait on which you genuinely differ from closely related traits also moves a little towards them, the more so the more strongly the other traits predict it.

The Big Five. Five varimax-rotated principal components of 60 traits, estimated in the comparison group as in Anni, Vainik and Mõttus (2025); congruence with the paper's loadings is 0.97–0.99.

Wellbeing landscape. The weights start from Soodla et al. (2025): 16,226 Biobank participants described themselves and were also described by people close to them, and the study's associations are converted into score weights through the correlations among the traits in the comparison group.

Jobs. The two sources are combined per job, weighted by sample size; jobs resting on fewer than 25 people are left out. Job models rest on 65 traits and are standardised twice: each trait across jobs, and each job across its traits. Similarity is a directional projection of the person's model on the job's model, displayed as 50 + 45 · tanh(projection), rounded to 5 within 5–95%. It roughly follows percentiles and compresses the extremes.

References

  1. Anni, K., Vainik, U., & Mõttus, R. (2025). Personality profiles of 263 occupations. Journal of Applied Psychology, 110(4), 481–511. doi:10.1037/apl0001249
  2. Arumäe, K., Vaht, M., Realo, A., Ausmees, L., Allik, J., Henry, S., Estonian Biobank Research Team, Puusepp, M., Lind, S., Hallik, I., Alavere, H., Metspalu, A., Palta, P., Esko, T., Mõttus, R., & Vainik, U. (2025). Cohort profiles: Personality measurements at the Estonian Biobank of the Estonian Genome Center, University of Tartu. Personality Science, 6. doi:10.1177/27000710251377954
  3. Henry, S., & Mõttus, R. (2025a). More nuanced assessments improve predictive and explanatory accuracy. Current Opinion in Psychology, 65, 102074. doi:10.1016/j.copsyc.2025.102074
  4. Henry, S., & Mõttus, R. (2025b). The 100 Nuances of Personality: Development of a comprehensive, non-redundant personality item pool. PsyArXiv. doi:10.31234/osf.io/zgwna_v2
  5. Mõttus, R., Kandler, C., Bleidorn, W., Riemann, R., & McCrae, R. R. (2017). Personality traits below facets: The consensual validity, longitudinal stability, heritability, and utility of personality nuances. Journal of Personality and Social Psychology, 112(3), 474–490.
  6. Schaufeli, W. B., De Witte, H., & Desart, S. (2020). Manual Burnout Assessment Tool (BAT), version 2.0. KU Leuven.
  7. Soodla, H. L., Lehto, K., Kõiv, K., Vainik, U., Akkermann, K., & Mõttus, R. (2025). Assessing the overlap of personality traits and internalizing psychopathology using multi-informant data: Two sides of the same coin? Journal of Psychopathology and Clinical Science, 134(4), 400–413. doi:10.1037/abn0000967

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