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Record W2019668558 · doi:10.1007/s11920-013-0381-4

Pediatric Depression: An Evidence-Based Update on Treatment Interventions

2013· review· en· W2019668558 on OpenAlexafffund
Amy Cheung, Nicole Kozloff, Diane Sacks

Bibliographic record

VenueCurrent Psychiatry Reports · 2013
Typereview
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
FundersCanadian Institutes of Health ResearchRoyal Bank of Canada
KeywordsReferralDepression (economics)Management of depressionSpecialtyMedicineMental healthPsychological interventionPsychiatryPrimary careFamily medicine

Abstract

fetched live from OpenAlex

Depression is a common condition among children and adolescents, with lasting detrimental effects on health, and social and occupational functioning. Despite being well-positioned to treat depression, primary care providers (PCPs) cite significant barriers. This review aims to summarize recent evidence to provide practical guidance to PCPs on the management of pediatric depression in their practices. Following identification and assessment, PCPs should provide general initial management. Children and adolescents with mild depression can be managed with active support and symptom monitoring, while those with moderate-to-severe depression can be treated with psychotherapy and/or antidepressants, which may involve referral to mental health specialty care. Less is known about the treatment of depression in children under the age of 12 years, who may be candidates for earlier referral to mental health specialty care. PCPs have the potential to improve the recognition and management of depression in young people, having lasting individual and societal benefits.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0050.004
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0030.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0110.002

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.

Opus teacher head0.203
GPT teacher head0.440
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations64
Published2013
Admission routes2
Has abstractyes

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