Self-Discrepancies and Eating Disorder Symptoms
Bibliographic record
Abstract
Self-discrepancies refer to perceived gaps between one’s actual self (characteristics one believes they currently possess), ideal self (attributes one aspires to have), and ought self (attributes one feels obligated to possess). Large actual-ideal and actual-ought self-discrepancies have been consistently associated with increased eating pathology. However, the potential role of the feared self—representing undesired personal characteristics — and the link between actual-feared self-discrepancies and eating pathology remains underexplored. Further, recent evidence suggests that approach and avoidance motivational orientations (e.g., reflecting sensitivity to reward and punishment) independently contribute to eating disorder (ED) symptoms and, importantly, may also interact with self-discrepancies to exacerbate ED symptom severity. As such, the present study examined the relationship between actual-ideal and actual-feared self-discrepancies and ED symptoms while also investigating approach and avoidance temperaments as potential moderators. Undergraduate participants (N = 89) completed an online questionnaire battery assessing these constructs. As hypothesized, actual-feared self-discrepancy was significantly associated with both avoidance temperament and ED symptoms. In contrast to previous research, neither actual-ideal self-discrepancy nor approach temperament was significantly associated with ED symptoms. Moderation analyses were non-significant. Taken together, preliminary findings suggest that actual-feared self-discrepancies may be relevant to eating pathology, warranting further investigation into causal pathways and intervention strategies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".