Mothers’ and Fathers’ Interactions With Children With Motor Delays
Bibliographic record
Abstract
OBJECTIVE: In early intervention programs, parents are often asked to teach their child new skills. As fathers are increasingly involved in intervention, clinicians need more information on fathers' unique interactive style. This pilot study compared mothers' and fathers' parent-child interactions during a teaching episode to identify similarities and differences in order to better understand parents' strengths. METHODS: The Nursing Child Assessment Teaching Scale was used to observe 10 mothers and 10 fathers interacting with their 10- to 28-month-old children in their homes. The children were receiving early intervention for a motor delay. The Caregiver Scores (parent's contribution to the interaction) of mothers and others were compared using paired t tests. RESULTS: Mothers had more optimal interactions as indicated by significantly higher Caregiver scores than fathers, t (9) = 3.83, p = .004. The subscales with statistically significant differences were Caregiver Contingency and Cognitive Growth Fostering. Children's scores when they interacted with their mothers or fathers did not differ. CONCLUSION: When observing fathers teaching their child new skills, therapists should remember that fathers of children with motor delays (and typically developing children) may use a more task-oriented communication style with less consideration of the child's actions than do mothers.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".