Testing Pediatric Acuity With an iPad: Validation of “Peekaboo Vision” in Malawi and the UK
Why this work is in the frame
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Bibliographic record
Abstract
Purpose: To evaluate two builds of the digital grating acuity test, “Peekaboo Vision” (PV), in young (6–60 months) populations in two hospital settings (Malawi and United Kingdom). Methods: Study 1 evaluated PV in Blantyre, Malawi (N = 58, mean age 33 months); study 2 evaluated an updated build in Glasgow, United Kingdom (N = 60, mean age 44 months). Acuities were tested-retested with PV and Keeler Acuity Cards for Infants (KACI). Bland-Altman techniques were used to compare results and repeatability. Child engagement was compared between groups. Study 2 included test-time comparison. Results: Study 1 (Malawi): The mean difference between PV and KACI was 0.02 logMAR with 95% limits of agreement (LoA) of 0.33 to 0.37 LogMAR. On test-retest, PV demonstrated 95% LoA of −0.283 to 0.198 logMAR with coefficient of repeatability (CR) 0.27. KACI demonstrated 95% LoA of −0.427 to 0.323 logMAR, and larger CR was 0.37. PV evidenced higher engagement scores than KACI (P = 0.0005). Study 2 (UK): The mean difference between PV and KACI was 0.01 logMAR; 95% LoA was −0.413 to 0.437 logMAR. Again, on test-retest, PV had narrower LoA (−0.344 to 0.320 logMAR) and lower CR (0.32) versus KACI, with LoA −0.432 to 0.407 logMAR, CR 0.42. The two tests did not differ in engagement score (P = 0.5). Test time was ∼1 minute shorter for PV (185 vs. 251 s, P = 0.0021). Conclusions: PV gives comparable results to KACI in two pediatric populations in two settings, with benefits in repeatability indices and test duration. Translational Relevance: Leveraging tablet technology extends reliable infant acuity testing to bedside, home, and rural settings, including areas where traditional equipment cannot be financed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it