Depression: The Complexity of Self‐Report Measures1
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
This study investigated the state‐trait distinction of the Beck Depression Inventory (BDI) and the complexity of this and three other self‐report depression inventories (Carroll Depression Scale‐Revised [CDS‐R] and the State‐Depression [S‐Dep] and Trait‐Depression [T‐Dep] subscales of the Self‐Analysis Questionnaire). In Study l, participants (170 men, 275 women) were administered the BDI, the S‐Dep, and the T‐Dep. Correlation analysis supported higher relationships between the BDI and T‐Dep for women but not for men. Regression results showed T‐Dep to be a better predictor of the BDI than S‐Dep for both men and women. Four factors were extracted through factor analysis: Cognitive‐Affective, Dysthymic, Euthymic, and Physiological. Study 2 investigated the BDI, T‐Dep, S‐Dep, and CDS‐R in a subsample (95 men, 122 women) of participants. Factor analysis yielded factors similar to those in Study I. Results indicated that clinicians and researchers should be knowledgeable about the aspects of depression that self‐report inventories assess before making conclusions based on one particular measure.
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.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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