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Record W4322620119 · doi:10.1093/pch/pxac102

Anxiety in children and youth: Part 1—Diagnosis

2023· review· en· W4322620119 on OpenAlexaffabout
Benjamin Klein, Rageen Rajendram, Sophia Hrycko, Aven Poynter, Oliva Ortiz-Alvarez, Natasha Saunders, Debra Andrews

Bibliographic record

VenuePaediatrics & Child Health · 2023
Typereview
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsCanadian Paediatric Society
Fundersnot available
KeywordsAnxietyFeelingPsychiatryMental healthPsychologyClinical psychologyMedicineSocial psychology

Abstract

fetched live from OpenAlex

Anxiety disorders are the most common mental health concerns affecting Canadian children and adolescents. The Canadian Paediatric Society has developed two position statements that summarize current evidence regarding the diagnosis and management of anxiety disorders. Both statements offer evidence-informed guidance to support paediatric health care providers (HCPs) making decisions around the care of children and adolescents with these conditions. The objectives of Part 1, which focuses on assessment and diagnosis, are to: (1) review the epidemiology and clinical characteristics of anxiety disorders and (2) describe a process for assessment of anxiety disorders. Specific topics are reviewed, including prevalence, differential diagnosis, co-occurring conditions, and the process of assessment. Approaches are offered for standardized screening, history-taking, and observation. Associated features and indicators that distinguish anxiety disorders from developmentally appropriate fears, worries, and anxious feelings are considered. Note that when the word 'parent' (singular or plural) is used, it includes any primary caregiver and every configuration of family.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.055
GPT teacher head0.344
Teacher spread0.289 · 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 designNot applicable
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

Citations9
Published2023
Admission routes2
Has abstractyes

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