Coping strategies and the mediating role of Experiential Avoidance
Bibliographic record
Abstract
The present study tests the mediating role of Experiential Avoidance (EA; Hayes et al., 1996) in the relation of specific forms of coping strategies (Self Distraction, Denial, Behavioural Disengagement, and Self Blame) with Depression, Anxiety, and Alexithymia. Participants were 161 subjects recruited from the general population. Measures of EA (Acceptance and Action Questionnaire II, AAQII, Bond et al., submitted), coping strategies (The Brief COPE scale, Carver et al., 1989), Depression and Anxiety (Hospital Anxiety and Depression Scale, HADS, Zigmond & Snaith, 1983), and Alexithymia (Toronto Alexithymia Scale, LSAS-SR; Liebowitz, 1987; Baker et al., 2002) were obtained from standardised, self-administered questionnaires. Regression analyses were performed to test for mediational models. Results showed that coping strategies significantly predicted EA, Depression, Anxiety, and Alexithymia. Moreover, the effect of coping strategies on Depression, Anxiety, and Alexithymia was not significant anymore or was strongly reduced when controlling for EA scores, whereas the latter still predicted Depression, Anxiety, and Alexithymia. Findings suggest that avoidance strategies may represent the mechanism through which Self Distraction, Denial, Behavioural Disengagement, and Self Blame take on psychological significance.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".