Depression screening and mental health outcomes in children and adolescents: a systematic review protocol
Bibliographic record
Abstract
BACKGROUND: Depression is an important cause of disability among children and adolescents. Depression screening is one possible method for managing depression, and screening programs have been initiated in some school and medical settings. However, in 2005, the Canadian Task Force on Preventive Health Care and the United Kingdom National Institute of Clinical Excellence did not recommend depression screening among children and adolescents. By contrast, in 2009, the United States Preventive Services Task Force recommended that all adolescents, but not younger children, be screened for depression in medical settings with integrated depression management services, although no trials of screening were identified. The objectives of this systematic review are to evaluate in children and adolescents the accuracy of depression screening tools; depression treatment efficacy; whether depression screening improves depression outcomes; and potential harms related to depression interventions and screening. METHODS/DESIGN: Data sources will include the bibliographic databases MEDLINE, Cochrane CENTRAL, PsycINFO, EMBASE, LILACS and Web of Science, supplemented by reference harvesting of eligible articles, relevant systematic reviews, relevant guidelines and recommendations, and selected journals, and by searches for unpublished studies. Eligible studies will report data for children and adolescents aged 6 to 18 years. Eligible diagnostic accuracy studies must compare a depression screening tool to a validated diagnostic interview for major depressive disorder and report diagnostic accuracy data. Eligible treatment studies must be randomized controlled trials of pharmacological, psychotherapeutic, or other depression treatments commonly available for children and adolescents in pediatric, primary-care, and family medicine settings. Eligible screening studies must be randomized controlled trials that compare depression outcomes between children or adolescents who underwent depression screening versus those who did not. Studies of harms will include randomized controlled trials and observational studies that evaluate harms from depression screening or treatment. Two investigators will independently review titles and abstracts, followed by full article review. Disagreements will be resolved by consensus. Two investigators will independently extract the data, with discrepancies resolved via consensus. DISCUSSION: The proposed systematic review will determine whether there is sufficient evidence of benefits in excess of harms and costs to support screening for depression in childhood and adolescence.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| 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".