Validity of the Alberta Infants Motor Scale in Norwegian infants aged 6–9 months through comparison with Canadian and Dutch scores
Bibliographic record
Abstract
Introduction: The Alberta Infant Motor Scale (AIMS) is widely used to assess infant motor development but has shown limited cross-cultural validity in various populations. The distribution of the original AIMS scores has not been cross-culturally validated for Norwegian infants. This study aimed to evaluate the applicability of the Canadian AIMS norm reference for Norwegian infants aged 6-9 months and compare their percentile rankings with the Canadian and Dutch norms. Methods: In this cross-sectional study, AIMS scores from a sample of 189 Norwegian infants aged 6-9 months were compared to the Canadian and Dutch norms. Total raw scores from the Canadian norms were compared to those of the Norwegian sample, and the percentiles of the Canadian and Dutch sample were compared to tentative Norwegian percentiles. Results: < 0.001), with 81% scoring at or below the 50th percentile and 18% falling at or below cut-off indicating possible motor delay. Using the Dutch norms, 20% of the Norwegian sample scored at or below the 50th percentile, while only 1% scored at or below the cut-off. A comparison of the percentile ranks showed that Canadian norms had the highest ranks for all age groups, followed by the Norwegian sample and subsequently the Dutch norms. The observed difference is considered clinically significant. Conclusion: Neither Canadian nor Dutch AIMS norms are valid for Norwegian infants due to the Canadian norms being too stringent and the Dutch norms being too lenient. A thorough cross-cultural validation for infants 0-18 months to establish Norwegian-specific AIMS norms is recommended.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".