Psychometric properties of the Alberta Infant Motor Scale and culturally adapted or translated versions when used for infant populations internationally: A systematic review
Bibliographic record
Abstract
AIM: To systematically review the psychometric properties of the Alberta Infant Motor Scale (AIMS) when used for infant populations internationally, defined as infants not living in Canada, where the normative sample was established. METHOD: Seven databases were searched for studies that informed the psychometric properties of the AIMS and culturally adapted or translated versions in non-Canadian infant cohorts. RESULTS: Forty-nine studies reported results from 11 663 infants representing 22 countries. Country-specific versions of the AIMS are available for Brazilian, Polish, Serbian, Spanish, and Thai infant cohorts. Country-specific norms were introduced for Brazilian, Dutch, Polish, and Thai cohorts. The original Canadian norms were appropriate for Brazilian, Greek, and Turkish cohorts. Across countries, the validity, reliability, and responsiveness of the AIMS was generally sufficient, except for predictive validity. Sufficient structural validity was found in one study, responsiveness in one study, discriminant validity in four of four studies, concurrent validity in 14 of 16 studies, reliability in 26 of 26 studies, and predictive validity in only eight of 13 studies. INTERPRETATION: The use of the AIMS with validated versions and norms is recommended. The AIMS or country-specific versions should be used with caution if norms have not been validated within the specific cultural context.
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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 | 0.012 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".