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Record W2059207860 · doi:10.1177/0883073813483903

Further Evaluation of the Scoring, Reliability, and Validity of the Hypertonia Assessment Tool (HAT)

2013· article· en· W2059207860 on OpenAlexaff
Shannon Knights, Natasha Datoo, Anne Kawamura, Lauren Switzer, Darcy Fehlings

Bibliographic record

VenueJournal of Child Neurology · 2013
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversity of TorontoQueen's UniversityHolland Bloorview Kids Rehabilitation Hospital
Fundersnot available
KeywordsHypertoniaInter-rater reliabilityCerebral palsyDystoniaPsychologyGold standard (test)Physical medicine and rehabilitationSpasticityPhysical therapyMedicineRating scalePsychiatryDevelopmental psychology

Abstract

fetched live from OpenAlex

We assessed the impact of videotape analysis on scoring of the Hypertonia Assessment Tool (HAT) that discriminates between hypertonia subtypes. The HAT was administered to 28 children with cerebral palsy (mean age 9 years, range 4-17 years, 61% male). HAT examinations were videotaped; scores were assigned before and after videotape review. Neurological examination provided the gold standard diagnosis. Interrater reliability, criterion validity and individual item validation were assessed using prevalence and bias-adjusted kappa (PABAK). Videotape review did not significantly change the HAT item scores or diagnoses. Item validation eliminated 1 dystonia item. Interrater reliability was moderate for dystonia (PABAK = 0.43) and excellent for spasticity and rigidity (PABAK = 0.86-1.0). Criterion validity was substantial for spasticity (PABAK = 0.71), moderate for dystonia (PABAK = 0.43-0.57) and excellent for the absence of rigidity (PABAK = 1.0). The HAT can be administered without videotape review. Dystonia item 1 did not change the HAT hypertonia diagnosis and will be removed from the HAT.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.077
Threshold uncertainty score0.272

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.024
GPT teacher head0.294
Teacher spread0.270 · 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 teacher head, 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

Citations33
Published2013
Admission routes1
Has abstractyes

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