Evaluation of alexithymia in individuals with chronic pain in a Mexican population: Alexithymia in a Mexican population
Bibliographic record
Abstract
INTRODUCTION: Alexithymia is the difficulty in identifying and describing feelings. Several studies have suggested that chronic pain can be linked to alexithymia. The aims of this study were to determine the presence of alexithymia in a sample of Mexican individuals who attended public health services, to assess if alexithymia is higher in medically ill individuals with pain than in those without pain, and to determine which alexithymia dimensions are more affected by the presence of pain. METHODS: Demographic and clinical features were evaluated in 250 Mexican outpatients of the General Hospital of Comalcalco, Tabasco. Pain was evaluated using the Visual Analogue Scale for Pain Assessment (VAS-P) and alexithymia was evaluated using the Toronto Alexithymia Scale (TAS-20). RESULTS: 38.8% of the sample was identified with probable/definite alexithymia and up to 61.2% of individuals were currently experiencing pain. Individuals with pain exhibited higher scores in the TAS-20 dimensions: difficulty describing feelings (p = 0.02), difficulty identifying feelings (p < 0.001) and higher total TAS-20 score (p < 0.001). Also, Probable/definite alexithymia was more frequently reported in individuals with pain (49% vs. 21.6%, p < 0.001). CONCLUSIONS: Our results show that a large proportion of individuals who attend public health services in a Mexican population present pain. We also identified that pain could be associated with alexithymia, in particular with a difficulty in describing and identifying feelings. An early identification and treatment of alexithymia could help in reducing the clinical burden of chronic pain in Mexican outpatients.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".