ALEXITHYMIA, BURDEN AND EMOTIONAL STATE IN ALS’ CAREGIVERS
Bibliographic record
Abstract
Introduction: Living with a progressively disease such as Amyotrophic lateral sclerosis (ALS) has a strong impact on the people affected and on their relatives, who have to tackle the demanding duties of caring for and assisting them (Tramonti et al., 2014). Although an extensive literature documents the levels of distress among caregivers of patients with progressive illness, less attention has been directed to determinants of caregiver mood and emotional regulation (Rabkin et al., 2009). In particular, there are not studies that assess the role of alexithymia in ALS. We evaluated the relationship between alexithymia and burden, and psychopatological symptoms in ALS’caregivers. Methods: 17 ALS’caregivers were tested with the following instruments: Toronto Alexithymia Scale-20 (TAS20); Hospital Anxiety and Depression Scale (HADS); Caregiver Burden Inventory (CBI). Results: 9 (53%) caregivers suffered from alexithymia (M=58; SD=6.2), while 8 individuals (47%) were not alexithymic (M=41.25; SD=8.31). We showed a positive correlation between total alexithymia score (TAS20-Tot) and depression (HADS-D; ρ= 0.575, p<0.01) and emotional burden (CBI-E; ρ=0.581, p<0.01). We found positive associations between TAS20 Difficulty Identifying Feelings subscale (TAS20-DIF) and anxiety (HADS-A; ρ=0.505, p<0.05), and HADS-D (ρ=0.679, p<0.05), and CBI-E (ρ=0.672, p<0.01). TAS20 Difficulty Describing Feelings subscale (TAS20-DDF) correlated with HADS-D (ρ=0.508, p<0.05) and CBI-E (ρ=0.747, p<0.01). TAS20 Externally-Oriented Thinking subscale (TAS20-EOT) did not show any significant correlation. Conclusions: Our results in ALS’ caregivers confirm previous evidence of a relationship between alexithymia and depression symptoms in other severe disabling diseases. Difficulty in identifying and describing own and others feelings could increase caregivers’emotional negative state and burden. It could lead to ineffective emotional responding and it could be a risk factor for care-related stress.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.025 |
| Science and technology studies | 0.002 | 0.037 |
| Scholarly communication | 0.018 | 0.075 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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; both teacher heads agree on what is shown here.
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".