Bibliographic record
Abstract
Purpose: The purpose of this descriptive correlation study was to examine the correlations among body mass index, paternal and maternal parenting, alexithymia, depression, and abnormal eating behaviors, and to determine asso-ciated risk factors for Korean women college students. Methods: Data were collected from 270 women college stu-dents in S city, Korea. They were asked to fill out the Korean version of the Eating Attitude Test, Parental Bonding Instrument, Toronto Alexithymia Scale, and Center for Epidemiological Studies Depression Scale. The collected data were analyzed using t-test, ANOVA, Scheffe test, Pearson`s correlation coefficient, and hierarchial regression analysis. Results: College students` abnormal eating behaviors were significantly associated with body mass index, paternal and maternal parenting, alexithymia, and depression. Hierarchical regression analysis found the most im-portant predictors of abnormal eating behaviors were body mass index and depression, which explained 15% of the variance in abnormal eating behaviors. Conclusion: These results suggest that women college students with over-weight and higher levels of depression are vulnerable to disordered eating behavior. Management of obesity and depressive mood could be effective interventions to prevent disordered eating behavior.
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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".