Synchronous telehealth and face‐to‐face administration of the Alberta Infant Motor Scale
Bibliographic record
Abstract
AIM: To determine the agreement between the Alberta Infant Motor Scale (AIMS), when delivered via synchronous telehealth compared with face-to-face administration to assess gross motor development of infants. METHOD: In this prospective cross-sectional study, 123 infants (gestational age: mean 38.8 weeks (SD 1.8); range 31-42 weeks; male n = 65) were assessed at 4 months, 8 months, or 12 months old with two AIMS assessments: face-to-face and via synchronous telehealth. The agreement between the assessments was examined using intraclass correlation coefficient (ICC) and the Bland-Altman method with 95% limits of agreement. RESULTS: Agreement between AIMS assessments administered face-to-face and via synchronous telehealth had an overall ICC of 0.99 (95% confidence interval [CI] 0.98, 0.99) and within age group: 4 months ICC 0.72 (95% CI 0.58, 0.83), 8 months ICC 0.97 (95% CI 0.96, 0.98), and 12 months ICC 0.98 (95% CI 0.96, 0.99). INTERPRETATION: The AIMS assessment delivered via synchronous telehealth shows excellent agreement with face-to-face assessment. Telehealth is a good alternative to face-to-face AIMS assessment, particularly for older 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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".