The integral inventory for depression, a new, self-rated clinimetric instrument for the emotional and painful dimensions in major depressive disorder
Bibliographic record
Abstract
OBJECTIVE: To assess the reliability and validity of the Integral Inventory for Depression (IID) scale using post hoc analyses of data from a multi-country study (ClinicalTrials.gov: NCT00561509) of patients with major depressive disorder (MDD). METHODS: Patients (N = 1629) completed the IID (comprising two separate dimensions for emotional and physically painful symptoms; maximum score of 65) and a reference scale (16-item Quick Inventory of Depressive Symptomatology Self-Report) at baseline and at follow-up (8 and 24 weeks). Physicians rated MDD symptoms using the Clinical Global Impressions of Severity scale at each visit. Inter-item correlation, internal consistency, external validity, factor structure, and exploratory analysis of an optimal severity cut-off point were assessed. RESULTS: The IID displayed two distinct dimensions (i.e. painful and emotional) with little item redundancy and good internal consistency (Cronbach's α > 0.83 at each visit). The IID displayed good external validity (Pearson's correlations coefficients >0.60 at each visit) and statistically significant agreement (McNemar's test; P < 0.001 at follow-up) with the reference scale. Results suggest that a cut-off score of ≤24 had adequate precision (>80%) to identify patients with and without moderate MDD. CONCLUSIONS: Results suggest that the IID may be a reliable and valid tool for assessing emotional and painful symptoms of MDD.
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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 | 0.003 | 0.013 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".