Relating coping, fear of uncertainty and alexithymia with psychological distress: The mediator role of experiential avoidance
Bibliographic record
Abstract
Abstract\n\nThe present study tests the mediating role of experiential avoidance (EA;\n\nHayes, Wilson, Gifford, Follette, & Strosahl, 1996) to account for the\n\nrelations of avoidant coping, fear of uncertainty, and alexithymia with\n\nnegative psychological outcomes. Participants were 177 adults (51 males\n\nand 126 females; mean age = 34.5). Measures of EA (Acceptance and\n\nAction Questionnaire, AAQ), avoidant coping (Brief COPE scale), fear of\n\nuncertainty (Temperament and Character Inventory), alexithymia (Toronto\n\nAlexithymia Scale), and psychological outcomes (Behavior and Symptom\n\nIdentification Scale) were obtained from standardized, self-administered\n\nquestionnaires. Regression analyses were performed to test for mediation\n\nmodels. Results show that the effect of avoidant coping and fear of\n\nuncertainty on emotional distress and other negative outcomes decreases\n\nwhen controlling avoidance scores, whereas the latter predicts\n\npsychological outcomes. Findings suggest that EA may represent a\n\ngeneralized mechanism through which both avoidant coping and fear of\n\nuncertainty take on psychological significance. Results did not support,\n\nhowever, the mediating role of EA for explaining the relations between\n\nalexithymia and psychological outcomes.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".