Alexithymia, Cardiovascular Reactivity, and Symptom Reporting During Blood Donation
Bibliographic record
Abstract
OBJECTIVE: With blood donation serving as a naturalistic stressor and a controlled medical event, the aim of this study was to examine emotional and cardiovascular reactivity, self-report of vasovagal symptoms, and perceived pain as a function of scores on the Toronto Alexithymia Scale (TAS-20). METHOD: Healthy young adult blood donors (N = 610) recruited at mobile blood collection clinics completed the TAS-20, pre- and postdonation measures of anxiety, postdonation measures of pain and vasovagal symptoms, and had their blood pressure and heart rate measured before and after giving blood. RESULTS: Alexithymia score was positively associated with reported anxiety, pain, and vasovagal symptoms. Higher alexithymia was also associated with greater increases in predonation systolic blood pressure in anticipation of blood donation. In general, women and less experienced blood donors reported more vasovagal symptoms than men and more experienced donors, and this corresponded to higher rates of treatment by the nurses, more fainting, and fewer full units of blood obtained. However, despite more reports of vasovagal symptoms by alexithymic donors, alexithymia score was not related to these variables. CONCLUSIONS: The results suggest that individuals with higher alexithymia scores were more anxious in the blood donation setting and more prone to report physical symptoms in the absence of a clear difference in the medical outcome of the blood donation procedure.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".