Relationships between Adaptive Behaviours, Personal Factors, and Participation of Young Children
Bibliographic record
Abstract
AIM: To examine the extent to which personal factors (age, socioeconomic grouping, and preterm birth) and adaptive behaviour explain the participation patterns of young children. METHODS: 65 Children 2-5 years old with and without a history of preterm birth and no physical or intellectual disability were selected by convenience sampling from Galway University Hospital, Ireland. Interviews with parents were conducted using the Adaptive Behaviour Assessment System, Second Edition (ABAS-II) and the Assessment of Preschool Children's Participation (APCP). Linear regression models were used to identify associations between the ABAS-II scores, personal factors, and APCP scores for intensity and diversity of participation. RESULTS: Adaptive behaviour explained 21% of variance in intensity of play, 18% in intensity of Skill Development, 7% in intensity of Active Physical Recreation, and 6% in intensity of Social Activities controlling for age, preterm birth, and socioeconomic grouping. Age explained between 1% and 11% of variance in intensity of participation scores. Adapted behaviour (13%), Age (17%), and socioeconomic grouping (5%) explained a significant percentage of variance in diversity of participation controlling for the other variables. CONCLUSIONS: Adaptive behaviour had a unique contribution to children's intensity and diversity of participation, suggesting its importance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".