Why Your Insight Card Has Adjectives, Not a Personality Type

6 min read

Personality is one of the most studied topics in psychology. For over a century, researchers have asked the same underlying question: What is the best way to describe the differences between people? Is personality a set of distinct types that people belong to — or a collection of continuous dimensions along which everyone varies?

Modern psychology has a clear answer. Personality is dimensional, not categorical. People are not boxes to be sorted into; they are patterns of scores on continuous traits. Lobe is built around this principle, and your Insight Card reflects it directly.

What the evidence shows

To test whether a psychological variable is truly categorical or continuous, researchers use a statistical approach called taxometric analysis, developed by Paul Meehl and colleagues (Meehl, 1995; Meehl & Yonce, 1994; Waller & Meehl, 1998). The method examines patterns in the data and asks: Does the evidence suggest discrete groups, or a continuum?

The largest review of this research, published in Psychological Medicine, analyzed 177 taxometric studies covering 533,377 participants across personality, mood, anxiety, eating, and personality disorders (Haslam, Holland, & Kuppens, 2012). The authors estimated that only about 14% of these constructs are genuinely categorical. The other 86% — including normal personality — are best described as continuous dimensions.

This is why modern personality research has converged on dimensional models. The Big Five, and the six-factor HEXACO model that Lobe uses both describe personality as continuous traits with strong predictive validity for real-world outcomes such as job performance, relationship satisfaction, and well-being (e.g., Ashton & Lee, 2007; Saucier & Srivastava, 2015). The clinical world is moving in the same direction: the DSM-5 introduced a dimensional model as an alternative to categorical personality disorder diagnoses, and the ICD-11 has replaced most categorical personality disorder types with a dimensional trait model (Widiger & Trull, 2007; Bach & First, 2018).

The limits of category-based descriptions

Type-based personality systems describe people using labels — four letters, a number, a color, a name. These labels are easy to remember and fun to share, which is part of why they remain popular.

The challenge with this approach is not that it is useless, but that it loses most of the information in the data. If a trait is continuous, and the system uses a cut-off to sort people into two categories, then two people very close to the cut-off — one just above, one just below — end up in different boxes despite being nearly identical. Meanwhile, two people in the same box can be very different if one is near the cut-off and the other is at the extreme.

This is one reason why the retest stability of categorical labels tends to be lower than that of the underlying continuous scores. Small changes in how someone answers near a category boundary can flip their label, even though their actual personality has not meaningfully changed (Pittenger, 2005). If personality were truly discrete, the label would be stable. The fact that it often is not tells us something about the nature of what is being measured.

Dimensional descriptions avoid this problem. Instead of a label, they give a position on each of several traits — and that position reflects the actual data, with as much detail as the measurement allows.

How Lobe’s Insight Card works

Your Insight Card is a shareable summary of your personality. It shows three things:

- A decorative abstract figure — purely aesthetic, chosen to make each card visually distinct.

- An adjective sentence — three adjectives drawn from your highest-scoring HEXACO factor, and two from your lowest-scoring factor.

- Your name and Lobe ID.

For example, if your highest factor is Openness to Experience and your lowest is Extraversion, your card might read:

"Curious, innovative, and creative — and reflective and independent."

If your highest is Agreeableness and your lowest is Honesty-Humility:

"Patient, tolerant, and forgiving — and bold and ambitious."

The adjectives come from the HEXACO Adjective Scales, a validated psychometric measure developed by Romano, Costantini, Richetin, and Perugini (2023). Both poles of every trait are framed in neutral or positive terms, so low Extraversion is described as reflective and independent rather than with negative language. Both sides of every trait describe real tendencies.

Two users with different scores get different adjectives. No one is sorted into a box. The description comes directly from the data.

What this means for you

A dimensional description changes the experience in four concrete ways.

It is specific to you. The adjective sentence draws from your highest and lowest scoring factors — so the description reflects your actual profile, not a category you've been sorted into.

It updates as you change. Personality evolves across the lifespan (Roberts, Walton, & Viechtbauer, 2006). If you retake the test and your profile shifts, your card shifts with it. The description always reflects who you are now, not who you were when you first tested.

Both sides are real. Every trait has two poles, and both describe genuine tendencies. Being reflective is not the absence of being sociable — it is a different strength. Your card shows adjectives from both your highest and your lowest factors because both are part of you.

It describes rather than prescribes. A label becomes an identity to live up to. An adjective sentence is just a description — something the data says about you, not something you have to perform. The card is there to reflect who you are, not to tell you who to be.

Why is the figure random?

The abstract figure on your card is decorative and unrelated to your personality scores. We considered designing symbols that represented each factor, but symbols would start to function as visual categories — badges that feel like identities. The figure is there for visual appeal – the substance lies in the adjectives.

A description, not a category

The science of personality has moved toward dimensions for good reason. Continuous traits capture more of what is actually there, update as people change, and predict real-world outcomes better than labels do. Lobe takes that evidence seriously. Your Insight Card describes you using adjectives that come from your data — specific to you, grounded in research, and honest about both sides of every trait.

That is the idea behind the card. Everything else is just decoration.

Key takeaways

- A large meta-analysis of 533,377 participants across 177 taxometric studies found that approximately 86% of psychological constructs — including normal personality — are best described as continuous dimensions rather than discrete categories (Haslam et al., 2012).

- Lobe’s Insight Card describes users with a sentence of adjectives drawn directly from their actual HEXACO scores, using the validated HEXACO Adjective Scales (Romano et al., 2023).

- The description updates when the user’s profile changes, both poles of every trait are framed positively, and no user is sorted into a fixed category.

- The decorative figure on the card is random and purely aesthetic — the substance lives in the adjectives.

References

Ashton, M. C., & Lee, K. (2007). Empirical, theoretical, and practical advantages of the HEXACO model of personality structure. Personality and Social Psychology Review, 11(2), 150–166.

Bach, B., & First, M. B. (2018). Application of the ICD-11 classification of personality disorders. BMC Psychiatry, 18, 351.

Haslam, N., Holland, E., & Kuppens, P. (2012). Categories versus dimensions in personality and psychopathology: A quantitative review of taxometric research. Psychological Medicine, 42(5), 903–920.

Meehl, P. E. (1995). Bootstraps taxometrics: Solving the classification problem in psychopathology. American Psychologist, 50(4), 266–275.

Meehl, P. E., & Yonce, L. J. (1994). Taxometric analysis: I. Detecting taxonicity with two quantitative indicators using means above and below a sliding cut (MAMBAC procedure). Psychological Reports, 74(3), 1059–1274.

Pittenger, D. J. (2005). Cautionary comments regarding the Myers-Briggs Type Indicator. Consulting Psychology Journal: Practice and Research, 57(3), 210–221.

Roberts, B. W., Walton, K. E., & Viechtbauer, W. (2006). Patterns of mean-level change in personality traits across the life course: A meta-analysis of longitudinal studies. Psychological Bulletin, 132(1), 1–25.

Romano, D., Costantini, G., Richetin, J., & Perugini, M. (2023). The HEXACO Adjective Scales and its psychometric properties. Assessment, 30(8), 2510–2532.

Saucier, G., & Srivastava, S. (2015). What makes a good structural model of personality? Evaluating the Big Five and alternatives. In M. Mikulincer & P. R. Shaver (Eds.), APA Handbook of Personality and Social Psychology (Vol. 4, pp. 283–305).

Waller, N. G., & Meehl, P. E. (1998). Multivariate taxometric procedures: Distinguishing types from continua. Sage Publications.

Widiger, T. A., & Trull, T. J. (2007). Plate tectonics in the classification of personality disorder: Shifting to a dimensional model. American Psychologist, 62(2), 71–83.