Diagnosis and Measurement of Adolescent Depression: A Review of Commonly Utilized Instruments
Bibliographic record
Abstract
We surveyed 160 recent studies of adolescent depression (publication dates ranged from March 1996 to August 2000) and identified 33 different diagnostic and symptom measurement instruments being used by various investigators. We also found that more than one in three of the studies measuring depressive symptom severity in adolescents relied on instruments designed for use with adults. We then reviewed in detail the design features and psychometric properties of the 12 instruments most commonly used in studies of adolescent depression and attempted to characterize their strengths and weaknesses. Our main conclusions are as follows: Too many different instruments are being used by investigators, presumably due to a lack of consensus as to which are the most valid and reliable tools. Instruments designed for use in adults and never validated in adolescent populations are frequently used with no evidence for their developmental sensitivity. Many studies are using instruments that demonstrate substantial weaknesses in validity and/or reliability. The need for a parsimonious, easily administered, valid, and reliable tool(s) to diagnose and measure symptom severity in adolescent depression has not yet been met.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".