Identifying affective personality profiles: A latent profile analysis of the Affective Neuroscience Personality Scales
Bibliographic record
Abstract
Based on evolutionary theory, a recent model in affective neuroscience delineated six emotional brain systems at the core of human personality: SEEKING, CARING, PLAYFULNESS, FEAR, ANGER, SADNESS. The Affective Neuroscience Personality Scales (ANPS) assess their functioning. Using a person-centred approach of the ANPS, this study: (i) examined the existence of latent personality profiles, (ii) studied their gender invariance, (iii) assessed their longitudinal (4 years) stability, and (iv) explored how they relate to several intrapersonal, interpersonal, and emotion regulation skills. Latent Profile Analysis in 2 samples (Canadian, longitudinal, N = 520; French, cross-sectional, N = 830) found that, qualitatively, 3 profiles characterized both populations and genders, with one distinction for the second profile where the French women endorsed slightly higher and lower scores for, respectively, the negative and positive emotions. Whilst not being quantitatively similar across genders, the personality profiles remained consistent across time in the longitudinal sample. Associations between profiles and intrapersonal (e.g. depression), interpersonal (e.g. empathy), and emotion regulation skills measures (e.g. emotional intelligence) offered concurrent validity evidence. This person centred approach to ANPS offers a holistic and parsimonious way to study affective personality dimensions. It opens promising avenues for future studies on the predictive value of ANPS profiles, and for personality-targeted interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".