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Record W2081635417 · doi:10.1080/15374416.2010.517172

Diagnostic Instability of<i>DSM–IV</i>ADHD Subtypes: Effects of Informant Source, Instrumentation, and Methods for Combining Symptom Reports

2010· article· en· W2081635417 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Clinical Child & Adolescent Psychology · 2010
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsRating scalePsychologyClinical psychologyAttention deficit hyperactivity disorderPsychiatryScale (ratio)NeuropsychiatryDevelopmental psychology

Abstract

fetched live from OpenAlex

Using data from 123 children (aged 6-12 years) referred consecutively to a pediatric neuropsychiatry clinic by community physicians for assessment of Attention-Deficit/Hyperactivity Disorder (ADHD) and related problems, we investigated the effects of informant (parent, teacher), tool (interview, rating scale), and method for combining symptom reports ("and," "or" algorithms), on the diagnosis of ADHD and its subtypes. Results indicated that as many as 50% of cases were reclassified from one subtype to another, depending on whether information was derived from one or two informants, a semistructured clinical interview and/or rating scale, and the algorithm used to combine informant reports. We conclude that the diagnosis of DSM-IV ADHD subtypes is capricious in that it is influenced by clinicians' decisions regarding informants, instrumentation, and method for aggregating information across informants and instruments.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.039
GPT teacher head0.463
Teacher spread0.424 · 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