Study of alexithymia among people with low distress tolerance compared to non-clinical sample
Bibliographic record
Abstract
Background: Alexithymia is a personality construct described as an asymptomatic clinical disability to identify and describe individual feelings. Individuals with alexithymia have difficulties regarding distress tolerance. The present research aimed at studying alexithymia among people with low distress tolerance in comparison to non-clinical sample. Methods: The study population consisted of all male employees working for General Education Office of Kermanshah Province, Iran. A total of 300 individuals from among these employees were selected based on Morgan table using multistep clustering method. Demographic data questionnaire, Toronto alexithymia scale, and distress tolerance questionnaire were used for data collection. Results: Mean (SD) score for tolerance, attracting, Assessment and Regulation were 7.3 (2.74), 8.4 (3.20), 16.8 (4.99), and 6.7 (2.63), respectively, in the normal group and 22.54 (6.07), 17 (4.28), 30.67 (6.65), and 30.50 (74.6) in the group with low distress tolerance. independent t-test showed that low distress tolerance group had significantly higher score regarding tolerance, absorption, evaluation, and regulation in comparison with the normal group (P<0.001). Conclusion: Findings of the present study can help psychologists and counsellors to pay more attention in alexithymia among people with Low Distress Tolerance to help them for better adaptability and confrontation ability against life difficulties such as distress, and ultimately for better health.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".