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Record W4246745018 · doi:10.1177/1054773806295235

Screening and Assessing Adolescent Asthmatics for Anxiety Disorders

2007· article· en· W4246745018 on OpenAlexaff
Terry M. A. Davis, Daniel Hogg

Bibliographic record

VenueClinical Nursing Research · 2007
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsCollege & Association of Registered Nurses of AlbertaUniversity of Alberta
Fundersnot available
KeywordsAnxietyTrait anxietyPsychiatryClinical psychologyPopulationMedicineAsthmaAnxiety disorderTraitPsychologyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

The purpose of this study was to evaluate a strategy designed to permit early detection of anxiety disorders in adolescent asthmatics. Adolescents with asthma ( N = 53) were screened for anxiety disorders using the Trait subscale of the State-Trait Anxiety Inventory for Children [STAI-C (Trait)] and the Multidimensional Anxiety Scale for Children (MASC). Adolescents and their parents were individually evaluated by a nurse trained in the administration of the Anxiety Disorders Interview Schedule-IV: Parent and Child Versions (ADIS-IV: P&C). Of the participants, 21 (40%) met the diagnostic criteria for one or more anxiety disorders. The STAI-C (Trait) was more effective than the MASC in screening adolescents for risk of coexisting anxiety disorders. Nurses trained to administer the ADIS-IV: P&C diagnosed anxiety disorders with a high degree of accuracy. These results have important implications for resolving the problem of unrecognized and untreated anxiety disorders in the adolescent asthmatic population.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.183
GPT teacher head0.542
Teacher spread0.359 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations22
Published2007
Admission routes1
Has abstractyes

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