Optimizing the ability of the Hamilton Depression Rating Scale to discriminate across levels of severity and between antidepressants and placebos
Notice bibliographique
Résumé
Efforts to improve the Hamilton Rating Scale for Depression (HRSD) have included shortening the scale by selecting the best performing items, lengthening the scale by assessing additional symptoms, modifying the format and scoring of existing items, and developing structured interview guides for administration. We defined item performance exclusively in terms of the ability of items to discriminate differences among levels of depressive severity which has not be used to guide any revisions of the HRSD conducted to date. Two techniques derived from item response theory were used to improve the ability of the HRSD to discriminate among individuals with different degrees of depressive severity. Item response curves were used to quantify the ability of items to discriminate among individual differences in depressive severity, on the basis of which the most discriminating items were selected. Maximum likelihood estimates were used to compute an optimal depressive severity score, using all items, but which weighted highly discriminating items more so than items that did not discriminate well. The utility of each method was evaluated by comparing a subset of optimally discriminating items and maximum likelihood estimates of depressive severity to the Maier Philipp subscale of the HRSD, in terms of how well scales discriminate treatment effects. Effect sizes for overall change in depression severity as well as effect sizes differentiating response to treatment versus placebo were evaluated in a sample of 491 patients receiving fluoxetine and 494 patients receiving placebo. Results of analyses identified a new subset of items (IRT-6), selected on the basis of their ability to discriminate among differences in depressive severity, that accounted for more variance in full-scale HRSD scores and was better at detecting change in illness severity than the Maier Philipp subscale of the HRSD. The IRT-6 subscale was equally good as the Maier Philipp subscale in differentiating treatment from placebo response. No evidence supporting the benefits of using maximum likelihood estimates to develop optimally performing subscales was found. Implications of the results are discussed in terms of strategies for optimizing the assessment of change in overall depression severity as well as differentiating treatment response.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».