Systematization of evaluation instruments for the two first years of life of typical or risk infants according to the ICF model
Bibliographic record
Abstract
ABSTRACT The objective of this study was to identify low-cost instruments of evaluation of neuropsychomotor development (NPMD) of children aged zero to two years, that can be used in the context of daycare and/or clinical environment in early intervention programs, and to systematize these instruments as the biopsychosocial model of the International Classification of Functioning, Disability and Health (ICF). NPMD evaluation instruments with translation or adaptation for Brazil were selected. For this purpose, the ICF domains were chosen triangulating the ICF-CY’s own checklist, the early stimulation core set, and the latest version of the ICF for searching the evaluation instruments in literature. Two physical therapists and a third for discordant items performed the systematization of the selected categories of ICF. The scales that met the criteria were: Alberta Infant Motor Scale (AIMS), Denver II Screening Test, PedIatric Quality of Life Inventory (PedSQl ™), Affordance in the Home Environment for Motor Development-Infant Scale (AHEMD-IS) and Mother-child bond. Even with these scales, there was a need for a complementary anamnesis questionnaire for the infant’s caregiver, data from the Child Health Handbook and a socioeconomic questionnaire from the Brazilian Association of Research Companies for Brazil (ABEP). This systematization is available in the appendix and seeks to facilitate the broader view of the physical therapist or education professional with a biopsychosocial comprehension of the infants, in addition to allowing the early identification of risks and subsidizing actions of promotion and intervention in different contexts.
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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 | 0.015 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".