Self-Compassion as a moderator in the relation between Alexithymia and Emotion Dysregulation
Bibliographic record
Abstract
Alexithymia is a psychological construct characterized by difficulty in identifying and verbally expressing emotion, limited imagination, and externally oriented thinking style. Previous empirical research has supported alexithymia reflecting deficits in emotional regulation, mainly focusing on clinical populations with psychiatric and/or psychosomatic illnesses. In the present study, we will examine the relation between alexithymia and emotional dysregulation with a potential moderating effect of self-compassion in a non-clinical group of adult subjects. Self-compassion is defined as a nonjudgmental noticing of one's suffering, which takes on the form of self-directed empathy and acceptance. While past studies have suggested the efficacy of self-compassion as an emotional regulation technique in individuals with major depressive disorder and anxiety syndrome, there has been limited insight on its influence as a stable personality trait. Alexithymia will be measured using the highly validated Toronto 20-Item Alexithymia Scale, which can be broken down into three subscales: a) Difficulty describing feelings, b) Difficulty identifying feelings, and c) Tendency to orient thinking externally (in which people have difficulty to attend to their internal emotions.) We plan to analyze these individual subscales in relation to our dependent variable, emotion dysregulation. Emotional dysregulation will be measured using the Difficulties in Emotional Regulation Short Form (DER-SF), and self-compassion will be assessed using the Self Compassion Scale (SCS) as developed by Neff. We hope to elucidate, through this study, the pattern of relation between these three phenomena.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".