Creative Artistic Achievement Is Related to Lower Levels of Alexithymia
Bibliographic record
Abstract
Alexithymia is characterized by deficits in the ability to identify, differentiate, and describe emotions—abilities that are of importance for social interactions, well-being, and, consequently, also for health. The aim of this study was to investigate whether achievements in cultural activities are associated with alexithymia. Participants from the Swedish Twin Registry were 2,279 men and 3,152 women in the ages 27 to 54. Cultural achievement was measured with the Creative Achievement Questionnaire (CAQ) in which participants estimate their achievement in the domains writing, music, visual arts, theater, and dance on a 7-point scale. Alexithymia was measured with the Toronto Alexithymia Score (TAS 20). In sex separated, age, and education-adjusted multivariate analyses, nonpractitioners, amateurs, and professionals in the 5 different CAQ domains were compared with regard to alexithymia scores. For both men and women, achievement in writing and music contributed statistically and independently of one another to a low alexithymia score. In addition, achievement in visual arts contributed independently to low alexithymia score in men and achievement in theatre to low alexithymia score in women. Total creative achievement was calculated as a sum score across domains, and the distribution divided into tertile groups. These groups were compared with regard to alexithymia scores. Large tertile differences were found in both sexes. The results show differences between modalities and cumulative effects of multiple creative achievements.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".