Alexithymia and Cancer-Related Fatigue: A Controlled Cross-Sectional Study
Bibliographic record
Abstract
AIMS AND BACKGROUND: The study aims to investigate the alexithymia construct in patients with a recent or longtime diagnosis of cancer as well as in healthy people, and whether alexithymia and fatigue are linked in the mentioned groups. METHODS: A first group, diagnosed less than 3 months previously (n = 63), and a second group whose cancer diagnosis dated back more than 30 months (n = 53), matched for sex, age, educational level and cancer site were assessed. Matched healthy controls (n = 50) were also evaluated. Alexithymia was assessed with the Toronto Alexithymia Scale-20, while fatigue was assessed with the Brief Fatigue Inventory. RESULTS: Alexithymia scores were higher in the recently diagnosed group than in the group with a longtime cancer diagnosis (t = 2.18, P < 0.05). Both groups had higher scores than controls (t = 4.3, P < 0.001; t = 2.01, P < 0.05). Alexithymic subjects were 45.6% in the recently diagnosed and 21.4% in the longtime diagnosed group (Chi(2) = 6.3, P < 0.05) and 18% in controls. Fatigue was more severe in patients with a longtime diagnosis compared with recently diagnosed patients (t = 7.079, P = 0.000). A weak but significant association between fatigue and alexithymia was found in recently diagnosed patients (r = 0.27.2; P < 0.05). CONCLUSIONS: Our study confirms that alexithymia scores are higher in cancer patients than in controls. The study suggests that alexithymia could be considered a dynamic reaction to illness in recently diagnosed patients, declining during subsequent phases. High fatigue rates in patients with a longtime diagnosis of cancer underline the role of the long course of illness in the perception of fatigue. The association between fatigue and alexithymia was weak in the recently diagnosed group and not significant in patients with a longtime diagnosis, in whom fatigue was an important complaint.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".