Raga-music intervention in verbal autistic children: A randomized controlled pilot study
Bibliographic record
Abstract
Autism spectrum disorder is a multifactorial neurodevelopmental disorder with increasing prevalence worldwide. Given the heterogeneity of autism, it is highly unlikely to have a single effective therapy for autism. Adversities associated with current pharma-therapies in treating autism have prompted the emergence of alternative therapies including variety of behavioral and music interventions. Autistic children, who tend to show a strong preference for music, makes music therapy a promising intervention for autism. Music interventions have shown improved mental and physical health across multiple domains including autism. Previous clinical trials of music therapy versus traditional therapy for autistic children have shown encouraging but mixed results. In that regard, Indian classical music is postulated to exert enhanced benefits due to its melodic uniqueness. Current randomized controlled pilot study evaluated enhanced benefits of Indian classical music-Raga co-treatment added to the conventional standard care in 5-12 years old verbal autistic children. Participants were randomly assigned either to comprehensive standard care (Std) comprised of Applied Behavior Analysis (ABA) and occupational Sensory Integration Therapy (SIT), or to Raga-Music therapy added to the standard care. The comparative effectiveness of Raga-Music therapy add-on was evaluated over 8-weeks of treatment duration, as assessed by primary and secondary outcome measures. The primary outcome measure included the Autism Treatment Evaluation Checklist (ATEC) assessment that evaluated the progression of autism, while the secondary outcome measures included sensory processing assessment using Sensory Profile 2 (SP2) followed by Canadian Occupational Performance Measure (COPM) with satisfaction, before and after the treatment. Raga-Music co-treatment was found to accentuate the benefits of standard treatment in reducing the progression of autism along with improvement in sensory profile of verbal autistic children. Current study supports the notion of Raga-Music as an effective add-on for early intervention autism healthcare program while warranting further investigation.
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 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".