Outcomes of population based language promotion for slow to talk toddlers at ages 2 and 3 years: Let's Learn Language cluster randomised controlled trial
Bibliographic record
Abstract
OBJECTIVE: To determine the benefits of a low intensity parent-toddler language promotion programme delivered to toddlers identified as slow to talk on screening in universal services. DESIGN: Cluster randomised trial nested in a population based survey. SETTING: Three local government areas in Melbourne, Australia. PARTICIPANTS: Parents attending 12 month well child checks over a six month period completed a baseline questionnaire. At 18 months, children at or below the 20th centile on an expressive vocabulary checklist entered the trial. INTERVENTION: Maternal and child health centres (clusters) were randomly allocated to intervention (modified "You Make the Difference" programme over six weekly sessions) or control ("usual care") arms. MAIN OUTCOME MEASURES: The primary outcome was expressive language (Preschool Language Scale-4) at 2 and 3 years; secondary outcomes were receptive language at 2 and 3 years, vocabulary checklist raw score at 2 and 3 years, Expressive Vocabulary Test at 3 years, and Child Behavior Checklist/1.5-5 raw score at 2 and 3 years. RESULTS: 1217 parents completed the baseline survey; 1138 (93.5%) completed the 18 month checklist, when 301 (26.4%) children had vocabulary scores at or below the 20th centile and were randomised (158 intervention, 143 control). 115 (73%) intervention parents attended at least one session (mean 4.5 sessions), and most reported high satisfaction with the programme. Interim outcomes at age 2 years were similar in the two groups. Similarly, at age 3 years, adjusted mean differences (intervention-control) were -2.4 (95% confidence interval -6.2 to 1.4; P=0.21) for expressive language; -0.3 (-4.2 to 3.7; P=0.90) for receptive language; 4.1 (-2.3 to 10.6; P=0.21) for vocabulary checklist; -0.5 (-4.4 to 3.4; P=0.80) for Expressive Vocabulary Test; -0.1 (-1.6 to 1.4; P=0.86) for externalising behaviour problems; and -0.1 (-1.3 to 1.2; P=0. 92) for internalising behaviour problems. CONCLUSION: This community based programme targeting slow to talk toddlers was feasible and acceptable, but little evidence was found that it improved language or behaviour either immediately or at age 3 years. TRIAL REGISTRATION: Current Controlled Trials ISRCTN20953675.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".