The Depression Inventory Development Workgroup: A Collaborative, Empirically Driven Initiative to Develop a New Assessment Tool for Major Depressive Disorder.
Bibliographic record
Abstract
The Depression Inventory Development project is an initiative of the International Society for CNS Drug Development whose goal is to develop a comprehensive and psychometrically sound measurement tool to be utilized as a primary endpoint in clinical trials for major depressive disorder. Using an iterative process between field testing and psychometric analysis and drawing upon expertise of international researchers in depression, the Depression Inventory Development team has established an empirically driven and collaborative protocol for the creation of items to assess symptoms in major depressive disorder. Depression-relevant symptom clusters were identified based on expert clinical and patient input. In addition, as an aid for symptom identification and item construction, the psychometric properties of existing clinical scales (assessing depression and related indications) were evaluated using blinded datasets from pharmaceutical antidepressant drug trials. A series of field tests in patients with major depressive disorder provided the team with data to inform the iterative process of scale development. We report here an overview of the Depression Inventory Development initiative, including results of the third iteration of items assessing symptoms related to anhedonia, cognition, fatigue, general malaise, motivation, anxiety, negative thinking, pain and appetite. The strategies adopted from the Depression Inventory Development program, as an empirically driven and collaborative process for scale development, have provided the foundation to develop and validate measurement tools in other therapeutic areas as well.
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How this classification was reachedexpand
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".