Implementation of COPCA: A family-centred early intervention programme in infant physiotherapy
Bibliographic record
Abstract
This thesis provides insight in the application and effect of infant physiotherapy in Switzerland. It focuses on the implementation in daily practice of the family-centred early intervention programme “COPing with and CAring for infants with special needs” (COPCA). COPCA has been developed since the beginning of this century by Tineke Dirks (paediatric physiotherapist) and Mijna Hadders-Algra (developmental neurologist) from the University Medical Center Groningen. They developed COPCA because of lacking evidence on the effectiveness of existing physiotherapeutic programmes on motor development of infants at risk of developmental disorders. COPCA differs from typical physiotherapeutic programmes in two ways (1) by including the whole family as active partners; (2) by offering the infant opportunities to learn through self-produced motor behaviour and trial-and error experiences. The thesis shows, that it is possible to implement COPCA successfully in Switzerland, and that Swiss parents of infants with impaired motor development highly appreciate COPCA. They especially valued its home-based setting, the support from the COPCA coach, and the experience being able to promote their infant’s development by integrating stimulating activities in daily routines. The thesis includes a small randomized controlled trial that demonstrated that COPCA was associated with better motor outcomes in infants with motor impairments. The thesis concludes that COPCA enables parents to promote their infants’ motor development in an autonomous way in their real life environment. The promising results of this thesis should be strengthened through studies evaluating the effect of COPCA in a larger group of infants at risk of motor developmental disorders.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".