The development and validation of the screening test for the early prediction of school success (STEPSS) : a screen of cognitive functioning in four- and five-year old children with varying health conditions
Bibliographic record
Abstract
The purpose of the present study was to construct and validate a brief screening instrument to support parent(s) and preschool/kindergarten teachers in monitoring and screening for cognitive impairment and/or delay in preschoolers. The target population of interest is all preschoolers at-risk for poor psychosocial and school outcomes due to chronic and acute dysfunction of the central nervous system (CNS). The accessible populations of interest to the present study are pediatric cancer survivors, preschoolers with alcohol related neurodevelopmental disorder (ARND), being preterm low birth weight, and/or diagnosed with various learning disabilities. The past practice of waiting until an at-risk child experienced poor school outcomes before being referred for cognitive assessment toward tailoring an intervention is no longer defensible. For the present study, a 61-item screening instrument (18 memory items, 19 verbal ability items, 15 attention items, and 9 demographic items) was pilot tested with parents, playschool teachers, and kindergarten teachers to rate preschoolers on overt behaviours associated with cognitive functioning. A criterion-referenced framework was used to establish a performance standard and set a cut score based on a sample of 151 normally functioning preschoolers aged 4:0- to 5:11-years. The various empirical and substantive analyses conducted resulted in a revised scale of 28 items (10 memory, 11 verbal ability, and 7 attention) titled, Screening Test for the Early Prediction of School Success (STEPSS). Given the need for a future study to validate the STEPSS with clinical groups of preschoolers, the screening instrument is intended to provide the empirical evidence needed to refer at-risk preschoolers for assessment with more comprehensive cognitive batteries. Constructing and validating the STEPSS is important for two reasons: 1) to fill a gap in the types of instruments available for monitoring and assessing cognitive functioning in at-risk preschool populations; and 2) to alleviate the current delay in targeting interventions for preschoolers because of the practice of depending upon the school system to monitor and identify poor cognitive functioning.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".