Turkish Translation and Psychometric Properties of the Peabody Developmental Motor Scale-2 in 0–24 Months Turkish At-Risk Infants
Bibliographic record
Abstract
This study was designed to investigate the construct–concurrent validity and reliability of the Turkish version of the Peabody Developmental Motor Scale–2 (PDMS-2) in at-risk infants between 0–24 age in Turkey. In this study, 120 infants (70 males, 50 females) participated in the study (mean corrected age 20.18 ± 22.535 weeks). The PDMS-2 scale consists of two subdimensions, the Fine Motor Quotient (FMQ) and the Gross Motor Quotient (GMQ). Whereas the construct validity was assessed using confirmatory factor analysis, concurrent validity was investigated using the correlation between PDMS-2 and the Alberta Infant Motor Scale and the Hammersmith Infant Neurological Examination with Spearman’s correlation analysis. The PDMS-2 was applied twice for test–retest reliability. Cronbach’s alpha (α) and the intraclass correlation coefficient (ICC) were used for reliability. ICC value was with 95% CI. The overall reliability coefficient of the test was found to be Croncbach’s α = 0.865. TICC values were found (ICC FMQ: 0.998, ICC GMQ: 0.998). Construct validity ( χ 2 /SD = 4.396; root mean square error of approximation = 0.021; goodness-of-fit index = 0.951) and concurrent validity ( r = 0.502–0.771; p < .05) were confirmed as acceptable. The PDMS-2 demonstrated good psychometric properties and can be used as a reliable and valid measure to assess neurodevelopmental aspects of Turkish at-risk infants.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".