Factors Affecting Self-Image in Patients with a Diagnosis of Eating Disorders on the Basis of a Cluster Analysis
Bibliographic record
Abstract
The aim of this study was to assess the relationship between self-image in eating disorders and age, duration and severity of the disorder, comorbidity, depressiveness and self-evaluation of eating problems. The results of the Offer self-image questionnaire for adolescents (QSIA) were compared in four groups: anorexia nervosa restrictive subtype (ANR, n: 47), anorexia nervosa binge/purge subtype (ANBP, n: 16), bulimia nervosa (BUL, n: 34) and eating disorders NOS (EDNOS, n: 19). The control group was age matched female pupils (NOR, n = 76). The Kruskal-Wallis test revealed significant differences between the age of patients from the ANR (16.34, SD 1.58) and BUL (17.56, SD 0.96) groups (p = .008). The self-image of schoolgirls from the NOR group was on most scales significantly better than the self-image of girls from clinical groups. On four scales differences between the (better) self-image in the ANR group and that in the BUL group were observed. Next, a cluster analysis using a generalised k-means algorithm with v-fold cross validation of QSIA questionnaire results was conducted in the group of clinical eating disorders (ANR, ANBP, and BUL). Three clusters were obtained. The first was characterized by very good self-image (above the average for the general population), the second by poor self-image and the third by negative self-image. Severity of depressiveness measured using the Beck Depression Inventory turned out to be the only factor which differentiated the clusters of self-image in eating disorders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 teacher head, 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".