PediaTrac V.3.0 protocol: a prospective, longitudinal study of the development and validation of a web-based tool to measure and track infant and toddler development from birth through 18 months
Bibliographic record
Abstract
INTRODUCTION: The need for an efficient, low-cost, comprehensive measure to track infant/toddler development and treatment outcomes is critical, given the importance of early detection and monitoring. This manuscript describes the protocol for the development and testing of a novel measure, PediaTrac, that collects longitudinal, prospective, multidomain data from parents/caregivers to characterise infant/toddler developmental trajectories in term and preterm infants. PediaTrac, a web-based measure, has the potential to become the standard method for monitoring development and detecting risk in infancy and toddlerhood. METHODS AND ANALYSES: V.3.0, a survey tool that queries core domains of early development, including feeding/eating/elimination, sleep, sensorimotor, social/sensory information processing, social/communication/cognition and early relational health. Information also will be obtained about demographic, medical and environmental factors and embedded response bias indices are being developed as part of the measure. Using an approach that systematically measures infant/toddler developmental domains during a schedule that corresponds to well-child visits (newborn, 2, 4, 6, 9, 12, 15, 18 months), we will assess 360 caregiver/term infant dyads and 240 caregiver/preterm infant dyads (gestational age <37 weeks). Parameter estimates of our items and latent traits (eg, sensorimotor) will be estimated by theta using item response theory-graded response modelling. Participants also will complete legacy (ie, established) measures of development and caregiver health and functioning, used to provide evidence for construct (discriminant) validity. Predictive validity will be evaluated by examining relationships between the PediaTrac domains and the legacy measures in the total sample and in a subsample of 100 participants who will undergo a neurodevelopmental assessment at 24 months of age. ETHICS AND DISSEMINATION: This investigation has single Institutional Review Board (IRB) multisite approval from the University of Michigan (IRB HUM00151584). The results will be presented at prominent conferences and published in peer-reviewed scientific journals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.052 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.025 | 0.019 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".