Impacts of COVID-19 on Neuropsychomotor Development From the Perspective of the International Classification of Functioning, Disability and Health in a Case Series of Children Aged 4 to 24 Months Assessed in Land and Aquatic Settings
Bibliographic record
Abstract
Mitigation measures the pandemic caused by the coronavirus disease 2019 (COVID-19) can change neuropsychomotor development (NPMD), diminishing adaptation, learning, and physical and cognitive development skills. Biopsychosocial screening in this scenario requires specific physical therapy assessment for each intervention setting, with validated scales. Hence, the objective of this study was to analyze the consequences of the COVID-19 pandemic on NPMD based on a case series in 4-to-24-month-old children assessed on land and in water. Case series descriptive study, based on physical therapy assessments with the Alberta Infant Motor Scale (AIMS), Developmental Screening Test (Denver II), and Adaptation of the Aquatic Functional Assessment Scale for Babies (AFAS-BABY © ). AIMS classified 8 children as typical NPMD and 5 as suspect NPMD, while Denver II classified 10 children as typical NPMD, 3 as questionable NPMD, and 2 as delayed NPMD. AFAS-BABY © created a qualitative profile, relating it to the land assessments. Thus, the consequences of the COVID-19 pandemic on NPMD were analyzed based on a case series in 4-to-24-month-old children assessed on land and in water.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".