Psychometric Properties and Diagnostic Utility of the 11-Item Kutcher Adolescent Depression Scale (KADS-11) in Persian Samples
Bibliographic record
Abstract
The goal of this study was to examine the psychometric properties of Kutcher Adolescent Depression Scale (KADS- 11-item version) in Persian population. After translation and back translation of KADS and conducting a pilot evaluation, two major studies were conducted to answer four main psychometric questions. In the study 1, applying KADS-11 in 277 university students revealed a KADS-11 reliability of 0.88 that KADS-11 can determine two major factors including a Core Depressive Symptomatic factor and a Suicidal-Physical factor. Both factors have satisfactory internal consistency as well as all 11 items of KADS. Its reliability was 0.79 in pilot study and 0.88 in study 1. Using Zung Self-Rating Depressive Scale to obtain convergent validity, the study 1 revealed that both scales have high correlations in all parts. In the second study, 63 depressed patients from Shahid Dr. Lavasani Hospital and 40 normal individuals were selected to examine whether KADS has enough power to discriminate depressed individuals from non-depressed individuals. The analysis of data showed that the scale has enough power to differentiate depressed groups from non-depressed groups t (101) = 3.316, P <0.001. This sensitivity was proved for both factors, which extracted from varimax rotation in study 1.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".