Parent‐mediated intervention in infants with an elevated likelihood for autism reduces dwell time during a gaze‐following task
Bibliographic record
Abstract
Cognitive markers may in theory be more sensitive to the effects of intervention than overt behavioral measures. The current study tests the impact of the Intervention with the British Autism Study of Infant Siblings-Video Interaction for Promoting Positive Parenting (iBASIS-VIPP) on an eye-tracking measure of social attention: dwell time to the referred object in a gaze following task. The original two-site, two-arm, assessor-blinded randomized controlled trial (RCT) of this intervention to increase parental awareness, and responsiveness to their infant, was run with infants who have an elevated familial likelihood for autism (EL). Fifty-four EL infants (28 iBASIS-VIPP intervention, 26 no intervention) were enrolled, and the intervention took place between 9 months (baseline) and 15 months (endpoint), with gaze following behavior measured at 15 months. Secondary intention to treat (ITT) analysis showed that the intervention was associated with significantly reduced dwell time to the referent of another person's gaze (β = -0.32, SE = 0.14, p = 0.03) at 15-month treatment endpoint. Given the established link between gaze following and language, the results are considered in the context of a previously reported, non-significant and transient trend toward lower language scores at the treatment endpoint (Green et al. (2015) The Lancet Psychiatry, 2(2), 133-140). Future intervention trials should aim to include experimental cognitive measures, alongside behavioral measures, to investigate mechanisms associated with intervention effects.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".