Alexithymia and cognitive impairment
Bibliographic record
Abstract
The term “alexithymia” describes a psychic condition characterized by difficulties in verbalizing affect and \nelaborating fantasies. Some studies have demonstrated that age is strongly associated with alexithymia. \nHowever, the degree to which alexithymia relates to cognitive deficits in patients with conditions such as mild \ncognitive impairment (MCI) is unknown. Therefore, our study examined the degree to which alexithymia is \ngreater in MCI compared to healthy older adults (HC) and also the correlations between alexithymia and \ncognition. Two hundred thirty-eight adults (mean age: 60.5 years; SD: 7.5; age range: 50-88) participated in \nthe study: 131 were HC, while 53 had amnestic MCI (aMCI) and 54 non-amnestic MCI (naMCI). A \ncomprehensive neuropsychological assessment was used to assess cognition, while alexithymia was \nmeasured with the Toronto Alexithymia Scale (TAS-20). ANOVAs showed significant differences in the TAS-20 \nscore (F=6.96, p<.001, η²p=0.06), according to the Group. Indeed, aMCI had a significantly higher total score \n(mean: 46.7; SD: 13.6) than both naMCI (mean: 39.2; SD: 9.6) and HC (mean: 40.2; SD: 11.9). Moreover, TAS 20 score was negatively correlated with general cognition, attention, memory, language, visuospatial abilities, \nand executive functioning. The present study suggests that a cognitive decline may be linked to the inability \nto identify and describe feelings and, above all, fantasize in older adults suffering from amnestic mild cognitive \nimpairment. This may be an important aspect to consider when planning treatments for patients with MCI. \nIndeed, targeting alexithymic facets may be a useful way to prevent or reduce the rate of cognitive decline.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".