Efficacy of Therapeutic Listening® Quickshifts in Children with Sensory Processing Difficulties
Bibliographic record
Abstract
Few empirical studies provide evidence for the effectiveness of Therapeutic Listening - Quickshifts (TL-Q). However, anecdotally, therapists and clients report TL-Q produces consistent positive results as an intervention for children with learning and developmental problems. In this study, the researchers examined the effectiveness of TL-Q intervention for five children with sensory processing difficulties to improve participation and function in (1) self-regulation and arousal, (2) activities of daily living (ADLs), (3) social/emotional skills, and (4) sensorimotor skills. Over the course of an 8-week prospective study, the researchers conducted a pre-test, post-test, prospective case study. During the intervention period, occupational therapist with TL-Q expertise chose the specific musical track depending on the needs of each child. Outcome measures included: Canadian Occupational Performance Measure, Sensory Processing Measure, Clinical Observations of Motor Performance, Beery-Buktenica Test of Visual Motor Integration and parent journals. Results showed an overall positive increase in quantitative scores and through qualitative reports. Most notably, in the areas of social interaction and sensorimotor skills. This study provided evidence for the support of TL-Q in the clinical setting and developed an effective protocol for future research.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".