An Investigation of the Factor Structure of the Beck Depression Inventory‐II in Anorexia Nervosa
Bibliographic record
Abstract
Symptoms of depression frequently co-occur with eating disorders and have been associated with negative outcomes. Self-report measures such as the Beck Depression Inventory-II (BDI-II) are commonly used to assess for the presence of depressive symptoms in eating disorders, but the instrument's factor structure in this population has not been examined. The purposes of this study were to explore the factor structure of the BDI-II in a sample of individuals (N = 437) with anorexia nervosa undergoing inpatient treatment and to examine changes in depressive symptoms on each of the identified factors following a course of treatment for anorexia nervosa in order to provide evidence supporting the construct validity of the measure. Exploratory factor analysis revealed that a three-factor model reflected the best fit for the data. Confirmatory factor analysis was used to validate this model against competing models and the three-factor model exhibited strong model fit characteristics. BDI-II scores were significantly reduced on all three factors following inpatient treatment, which supported the construct validity of the scale. The BDI-II appears to be reliable in this population, and the factor structure identified through this analysis may offer predictive utility for identifying individuals who may have more difficulty achieving weight restoration in the context of inpatient treatment. Copyright © 2014 John Wiley & Sons, Ltd and Eating Disorders Association.
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".