Focused attention, heart rate deceleration, and cognitive development in preterm and full‐term infants
Bibliographic record
Abstract
The majority of children who are born very preterm escape major impairment, yet more subtle cognitive and attention problems are very common in this population. Previous research has linked infant focused attention during exploratory play to later cognition in children born full-term and preterm. Infant focused attention can be indexed by sustained decreases in heart rate (HR). However there are no preterm studies that have jointly examined infant behavioral attention and concurrent HR response during exploratory play in relation to developing cognition. We recruited preterm infants free from neonatal conditions associated with major adverse outcomes, and further excluded infants with developmental delay (Bayley Mental Development Index [MDI < 70]) at 8 months corrected age (CA). During infant exploratory play at 8 months CA, focused attention and concurrent HR response were compared in 83 preterm infants (born 23-32 weeks gestational age [GA]) who escaped major impairment to 46 full-term infants. Focused attention and HR response were then examined in relation to Bayley MDI, after adjusting for neonatal risk. MDI did not differ by group, yet full-term infants displayed higher global focused attention ratings. Among the extremely preterm infants born <29 weeks, fewer days on mechanical ventilation, mean longest focus, and greater HR deceleration during focused attention episodes, accounted for 49% of adjusted variance in predicting concurrent MDI. There were no significant associations for later-born gestational age (29-32 weeks) or full-term infants. Among extremely preterm infants who escape major impairment, our findings suggest unique relationships between focused attention, HR deceleration, and developing cognition.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".