Alexithymia and emotional reactions to odors
Bibliographic record
Abstract
Alexithymia is a psychological construct characterized by deficits in processing emotional stimuli. However, little is known about the processing of odours in alexithymia, even though there is extensive proof that emotion and olfaction are closely linked. The present study is aimed at investigating how alexithymic individuals process emotions conveyed by odors. Emotional responses to unpleasant, neutral odors and clean air were collected through self-report ratings and psychophysiological measures in a sample of 62 healthy participants with high (HA), medium (MA) and low (LA) levels of alexithymia. Moreover, participants performed tests on odors identification and threshold and completed questionnaires assessing olfactory imagery and awareness. Two main results have been found: first, HA and MA groups showed altered physiological responses to odors, compared to LA, while no differences among the groups were observed in odor ratings; and second, affective and cognitive alexithymia components were differently associated with the performance on olfactory tests, skin conductance response to odors, reaction times in the rating task, and scores on olfactory questionnaires. We conclude that alexithymia is characterized by altered physiological reactions to olfactory stimuli; moreover, we stress the importance of evaluating the different alexithymia components since they affect emotional stimuli processing in different ways.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".