Most women with anorexia nervosa report less eating pathology on days when they are more self‐compassionate than usual
Bibliographic record
Abstract
OBJECTIVE: Individuals with eating disorders who have lower trait levels of self-compassion have more severe eating pathology. This study examined the extent to which levels of self-compassion fluctuate day-to-day in individuals with anorexia nervosa (AN) and whether these fluctuations contribute to their eating pathology. METHOD: For 2 weeks, 33 women with typical (75%) and atypical AN reported on their daily eating pathology and self-compassion. RESULTS: Nearly half the variance in participants' self-compassion scores occurred at the within-persons daily level. Multilevel modeling revealed that on days when participants were more self-compassionate than usual, their eating pathology was lower. However, this effect was moderated by participants' mean self-compassion level over the 2 weeks. Specifically, daily self-compassion was negatively related to eating pathology among individuals with average and higher mean self-compassion levels but was not related to eating pathology among those with lower levels. DISCUSSION: One-time self-reports of self-compassion in individuals with AN may overlook the substantial within-person variability in their self-compassion levels. For most individuals with AN, responding to distressing daily experiences with more compassion than usual should be associated with decreased eating pathology. More work is needed to understand how individuals lower in dispositional self-compassion can benefit from these upward fluctuations.
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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 | 0.000 | 0.000 |
| 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) | 0.003 | 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".