The latent symptom structure of the Beck Depression Inventory–II in outpatients with major depression.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Beck Depression Inventory-II (BDI-II) is a self-report instrument frequently used in clinical and research settings to assess depression severity. Although investigators have examined the factor structure of the BDI-II, a clear consensus on the best fitting model has not yet emerged, resulting in different recommendations regarding how to best score and interpret BDI-II results. In the current investigation, confirmatory factor analysis was used to evaluate previously identified models of the latent symptom structure of depression as assessed by the BDI-II. In contrast to previous investigations, we utilized a reliably diagnosed, homogenous clinical sample, composed only of patients with major depressive disorder (N = 425)--the population for whom this measure of depression severity was originally designed. Two 3-factor models provided a good fit to the data and were further evaluated by means of factor associations with an external, interviewer-rated measure of depression severity. The results contribute to a growing body of evidence for the Ward (2006) model, including a General (G) depression factor, a Somatic (S) factor, and a Cognitive (C) factor. The results also support the use of the BDI-II total scale score. Research settings may wish to model minor factors to remove variance extraneous to depression where possible.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it