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Comparative predictive validity of the Harris Infant Neuromotor Test and the Alberta Infant Motor Scale

2011· letter· en· W2035047784 on OpenAlexaboutno aff
Marcia F. Williams

Bibliographic record

VenueDevelopmental Medicine & Child Neurology · 2011
Typeletter
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
Fundersnot available
KeywordsAttritionPredictive validityPredictive powerTest (biology)PsychologyScale (ratio)External validityPediatricsMedicineDevelopmental psychologySocial psychology

Abstract

fetched live from OpenAlex

SIR-The paper by Harris et al. 1 describes the Harris Infant Neuromotor Test (HINT), an assessment of infant motor function developed by the first author.The stated purpose of the HINT is 'to differentiate atypical from typical motor development in infants aged 2.5 to 12.5 months.'Hence, this first report of the predictive validity of the HINT deserves careful review.Unfortunately, the article lacks key information, so the reader is unable to evaluate the study procedures, or to determine the clinical validity of the HINT.Demographic and birth characteristics are presented for 144 infants, recruited as a convenience sample of 58-term and 86 at-risk infants.However, the authors report attrition of 21% prior to their primary outcome at 2 years and 50% prior to outcome at 3 years.This implies the predictive validity is actually based on outcome of 114 infants at 2 years and 72 infants at 3 years.But, these participants are not described and the numbers are ambiguous.Tables III and IV indicate that the predictive validity results are based on a sample of 144; the ROC curves in the online supplemental materials indicate 13 missing participants at 2-year outcome.The authors discuss attrition as a limitation but conclude that the 'considerable' attrition in their study was not a problem because the statistically significant findings indicate adequate power.However, they do not address attrition as a source of selection bias which can seriously undermine the validity of an epidemiological study.As stated in the resource cited by the authors, 2 to address attrition in long-term follow-up studies researchers should, 'provide clear, unambiguous information on the flow of subjects through the study ⁄ cohort at each stage.'The article by Harris et al. does not clearly describe the evolution of the study sample, nor of the participants at each end-point.The reference cited further advises researchers to 'provide baseline characteristics for those seen and not seen at follow-up for each intervention group.' 2 Harris et al. do not compare the characteristics of participants who were evaluated to those who were lost to follow-up.This information is required because it is likely

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)0.015
metaresearch head score (Gemma)0.097
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 score0.015
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.097
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.235
Teacher spread0.213 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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