Improving access to assessments of early motor development in local languages: polish adaptation of the Early Motor Questionnaire
Bibliographic record
Abstract
A child's motor development progresses very dynamically. It is crucial to develop freely available parent-report measures of motor development that can be easily used globally to measure motor skills and identify children in need of interventions. This paper presents the adaptation and validation of the Early Motor Questionnaire, which consists of gross motor (GM), fine motor (FM), and perception-action integration (PA) subscales, to the Polish language (EMQ-PL). Study 1 (online, cross-sectional, N = 640) assessed psychometric properties of the EMQ-PL and its value in identifying children referred to physiotherapy. Results reveal excellent psychometric properties of the EMQ-PL and differences in GM and total age-independent scores between children that were and were not referred for physiotherapy. Study 2 (in-person assessment, longitudinal, N = 100) showed high correlations of GM and total scores with Alberta Infant Motor Scale. CONCLUSION: Overall, the EMQ can be easily adapted to local languages and has the potential for use as a screening tool in global health contexts. WHAT IS KNOWN: • Parent-report questionnaires - especially those available free of charge - can potentially improve the rapid assessment of motor skills in young children worldwide. • Translation, adaptation and validation of freely available parent-report measures of motor development to local languages are important for local populations. WHAT IS NEW: • Early Motor Questionnaire can be easily adapted to local languages and has the potential for use as a screening tool in global health contexts. • The polish version of the Early Motor Questionnaire has excellent psychometric properties and highly correlates with infants' age and Alberta Infant Motor Scale scores.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".