An examination of the sensitivity of the six-item Hamilton Rating Scale for Depression in a sample of patients suffering from major depressive disorder.
Bibliographic record
Abstract
OBJECTIVES: To compare the sensitivity of the 6-item Hamilton Rating Scale for Depression (HRSD6) with the more widely used 17-item Hamilton Rating Scale for Depression (HRSD17) in patients suffering from major depressive disorder, with or without melancholia and/or dysthymic disorder. A secondary objective was to compare the sensitivity of the HRSD6 to the Montgomery-Asberg Depression Rating Scale (MADRS). DESIGN: Retrospective analysis of 4 clinical trials that tested antidepressant therapies. SETTING: Outpatient treatment in a major psychiatric hospital. PARTICIPANTS: One hundred and forty-three male and female outpatients meeting the criteria of the DSM-III-R or DSM-IV for major depressive disorder. OUTCOME MEASURES: HRSD17, HRSD6 and MADRS. RESULTS: The HRSD6 correlated strongly with the HRSD17, both at baseline and termination of treatment, and for the subgroups of double depression and melancholia. The HRSD6 was also correlated significantly with the MADRS at both measurement times, and for the subgroups. Paired t-tests with the HRSD6, HRSD17 and MADRS demonstrated equal sensitivity to change over the course of treatment, both in the full sample and in the dysthymic and melancholic subgroups. CONCLUSIONS: The HRSD6 appears to be as sensitive to change over treatment as the HRSD17 and the MADRS. A shorter, less time-consuming measure of depression may have utility in clinical practice and research.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".