The effect of sung speech on socio-communicative responsiveness in children with autism spectrum disorders
Bibliographic record
Abstract
There is emerging evidence to demonstrate the efficacy of music-based interventions for improving social functioning in children with Autism Spectrum Disorders (ASD). While this evidence lends some support in favor of using song over spoken directives in facilitating engagement and receptive intervention in ASD, there has been little research that has investigated the efficacy of such stimuli on socio-communicative responsiveness measures. Here, we present preliminary results from a pilot study which tested whether sung instruction, as compared to spoken directives, could elicit greater number of socio-communicative behaviors in young children with ASD. Using an adapted single-subject design, three children between the ages of 3 and 4 years, participated in a programme consisting of 18 sessions, of which 9 were delivered with spoken directives and 9 with sung. Sessions were counterbalanced and randomized for three play activities-block matching, picture matching and clay play. All sessions were video-recorded for post-hoc observational coding of three behavioral metrics which included performance, frequency of social gesture and eye contact. Analysis of the videos by two independent raters indicated increased socio-communicative responsiveness in terms of frequency of social gesture as well as eye contact during sung compared to spoken conditions, across all participants. Our findings suggest that sung directives may play a useful role in engaging children with ASD and also serve as an effective interventional medium to enhance socio-communicative responsiveness.
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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 | 0.004 |
| 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 | 0.001 |
| 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".