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Record W2063887971 · doi:10.1136/ebmh.5.2.58

2 of 3 dimensional rating scales were useful for discriminating anxiety and depression in adolescents

2002· letter· en· W2063887971 on OpenAlexaff
Katharina Manassis

Bibliographic record

VenueEvidence-Based Mental Health · 2002
Typeletter
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsRating scalePercentileDepression (economics)AnxietyMedicinePsychologyPsychiatryPediatricsDevelopmental psychologyMathematicsStatistics

Abstract

fetched live from OpenAlex

Dierker LC, Albano AM, Clarke GN , et al. Screening for anxiety and depression in early adolescence. J Am Acad Child Adolesc Psychiatry2001 Aug; 40 : 929 –36 [OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] QUESTION: In grade 9 adolescents, what is the diagnostic and discriminative accuracy of 3 dimensional rating scales for detecting anxiety and depressive disorders? Blinded comparison of 3 rating scales with a DSM-IV diagnosis. 5 high schools in Portland, Oregon; Louisville, Kentucky; and Philadelphia, Pennsylvania, USA. 632 adolescents (mean age 14 y, 55% girls) who were in grade 9. Participation was offered to those who scored above the 80th percentile on ≥1 of 3 rating scales (25% agreed) and a random sample of adolescents who scored below the 80th percentile (75% agreed). 72 adolescents received the rating scales and the diagnostic standard. The 3 rating scales were the Center for Epidemiologic Studies—Depression Scale (CES-D), the Revised Children's Manifest Anxiety Scale (RCMAS), and the Multidimensional … [1]: {openurl}?query=rft.jtitle%253DJournal%2Bof%2Bthe%2BAmerican%2BAcademy%2Bof%2BChild%2Band%2BAdolescent%2BPsychiatry%26rft.stitle%253DJ%2BAm%2BAcad%2BChild%2BAdolesc%2BPsychiatry%26rft.aulast%253DDierker%26rft.auinit1%253DL.%2BC.%26rft.volume%253D40%26rft.issue%253D8%26rft.spage%253D929%26rft.epage%253D936%26rft.atitle%253DScreening%2Bfor%2Banxiety%2Band%2Bdepression%2Bin%2Bearly%2Badolescence.%26rft_id%253Dinfo%253Adoi%252F10.1097%252F00004583-200108000-00015%26rft_id%253Dinfo%253Apmid%252F11501693%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1097/00004583-200108000-00015&link_type=DOI [3]: /lookup/external-ref?access_num=11501693&link_type=MED&atom=%2Febmental%2F5%2F2%2F58.atom [4]: /lookup/external-ref?access_num=000169985800016&link_type=ISI

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.060
GPT teacher head0.335
Teacher spread0.275 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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