The ups and downs of self‐criticism and disordered eating: Complementing Paranjothy and Wade's (2024) analysis by considering both trait and state perspectives
Bibliographic record
Abstract
Paranjothy and Wade's (2024) meta-review reveals that individuals higher in the personality trait of self-criticism consistently experience more disordered eating than those lower in the trait. The clinical implications of this meta-review are important in that they suggest current theoretical models and clinical practices in the field of eating disorders should incorporate a greater focus on self-criticism. Building on this exciting contribution, we highlight conceptual, practical, and empirical reasons why the field would benefit from supplementing this research on trait self-criticism with investigations of state self-criticism. We review research showing that self-criticism levels vary not only between individuals, with some people chronically more self-critical than others, but also within a person, with a given individual enacting relatively more self-criticism during some moments and days than others. We then present emerging research showing that these periods of higher-than-usual self-criticism are associated with more disordered eating. Thus, we emphasize the need to explore the factors that give rise to self-critical states in daily life, and review preliminary findings on this topic. We highlight the ways in which research on within-person variations in self-criticism can complement research on trait self-criticism to advance case formulation, prevention, and treatment in the field of eating disorders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.025 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.014 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".