Promotion and implementation effectiveness of World Health Organization's Caregiver Skills Training program in Taiwan
Bibliographic record
Abstract
The World Health Organization (WHO) developed the Caregiver Skills Training for Families of Children with Developmental Delays and Disabilities (CST) with support from Autism Speaks to address the resource gaps and worldwide needs for interventions for children with developmental disorders or delays, especially those with autism spectrum disorder (ASD), and their families. Evidence has indicated that parent-mediated interventions benefit both caregivers and children by strengthening caregivers' knowledge and confidence and children's social communication skills and behavioral regulation. The CST-Taiwan team began the prepilot field trial in 2017 and developed the project to serve families in various locations. This study (1) delineated the adaptations and promotion of CST-Taiwan; (2) determined the program's effectiveness in the promotional stage, in terms of caregiver and child outcomes, and (3) examined the maintenance of its effects. The materials, delivery, and facilitator training procedure of the original CST were adapted to Taiwan. The quantitative data indicated that CST-Taiwan is a promising program, it positively affected caregiver knowledge and confidence and reduced the severity of the children's autistic symptoms. The 3-month follow-up results suggested that the effects persisted. Thus, CST-Taiwan, and its promotional strategies are feasible and effective.
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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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".