Measuring Health-related Quality of Life in Teens With and Without Depression
Bibliographic record
Abstract
PURPOSE: To provide empirical evidence on the performance of common measures in assessing health-related quality of life (HRQL) in depressed and nondepressed youth. These measures can be used in research trials, cost-effectiveness studies, and to help develop policy for treating youth depression. BACKGROUND: Depression is one of the most common mental disorders among adolescents, with a chronic, episodic course marked by considerable impairment. Data on HRQL for teens with depression could more fully demonstrate the burden of depression and help to evaluate the comparative effectiveness of teen depression services, which in turn can be used to inform public and clinical policies. METHODS: We collected data on depression and HRQL from 392 depressed and nondepressed teens aged 13-17. RESULTS: Generic mental health, disease-specific, and generic preference-based measures of HRQL all do a reasonable job of distinguishing teens with and without depression and between teens with differing levels of depression. Generic mental health and disease-specific measures provide valuable information on burden of disease and perform well. For the purpose of economic evaluation, the HUI-3 and EQ-5D perform somewhat better than other preference-based measures. These results can aid future research on teens with depression by helping to guide which HRQL instruments are most useful in this population and can help to quantify the burden of depression in teens for policy and clinical planning.
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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 | 0.000 |
| 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 | 0.000 |
| 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".