The Psychometric Characteristics of the Hamilton Depression Inventory
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
In this study, the psychometric properties of the Hamilton Depression Inventory (HDI; Reynolds & Kobak, 1995a) were examined in a sample of 249 undergraduate participants. The HDI exhibited high internal consistency and support for its construct validity was demonstrated by the HDI's patterns of correlations with other measures of depression, anxiety, and depression-relevant cognition. Factor analyses of the full (23-item) and 17-item versions of the HDI each yielded 4 factors, which accounted for 49% and 53% of the variance in participants' responses, respectively. The utility of the HDI's use of multiple-weighted subitems was also assessed by comparing a less complicated scoring system to the standard scoring format. The standard HDI added significantly to the prediction of criterion indexes after controlling for the variance accounted for by the "simplified" HDI. Moreover, the operating characteristics of the standard HDI outperformed the simplified HDI in the prediction of the Beck Depression Inventory-II (Beck, Steer, & Brown, 1996) classification. The results provide strong support for the HDI as a reliable and valid instrument for the assessment of depressive severity
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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 | 0.004 | 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