The structure of the Montgomery–Åsberg depression rating scale over the course of treatment for depression
Bibliographic record
Abstract
The Montgomery-Åsberg Depression Rating Scale (MADRS) is a widely used clinician-rated measure of depressive severity. Empirical support for the factor structure of the MADRS is mixed; further, the comparison of MADRS scores within and between patients requires the demonstration of consistent instrument properties. The objective of the current investigation was to evaluate MADRS factor structure as well as MADRS factorial invariance across time and gender. The MADRS was administered to 821 depressed outpatients participating in a large-scale effectiveness study of combined pharmacotherapy and psychotherapy for depression. Treatment outcome did not differ across treatment groups. Factor structure and invariance was evaluated via confirmatory factor analysis. A four-factor model consisting of Sadness, Negative Thoughts, Detachment and Neurovegetative symptoms demonstrated a good fit to the data. This four-factor structure was invariant across time and gender. A hierarchical model, in which these four factors served as indicators of a general depression factor, was also supported. A limitation of the current study is the lack of comprehensive characterization of patient clinical features; results need to be replicated in more severely depressed or treatment refractory patients. Overall, evidence supported the use of the MADRS total score as well as subscales focused on affective, cognitive, social and somatic aspects of depression in male and female outpatients.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".