Development and psychometric properties of a novel depression measure
Bibliographic record
Abstract
The Filgueiras Depression Inventory is proposed as a new instrument, created specifi cally for the Brazilian culture, for screening of Major Depressive Episodes according to the categories of the DSM-V. Two studies were conducted for this purpose. Study's 1 sample consisted of 326 undergraduate psychology students. Single words or expressions were asked to represent overall depressive symptoms. The most cited formed the fi rst version of the Filgueiras Depression Inventory. Study 2 reported the psychometric properties of this new scale. The sample consisted of 471 volunteers recruited on the Internet and 238 volunteers undergraduate students. Factor analyses, convergent and discriminant validity and other Classical Test Theory indices revealed results consistent to expectations in the present study. Andrich's Rating Scale Modeling was used as an Item Response Theory method of analysis. The overall psychometric properties of the Filgueiras Depression Inventory were shown to be good, and this study supports the effectiveness of this scale as a new instrument that measures depressive episodes in the Brazil.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".