Efficacy of Visual–Acoustic Biofeedback Intervention for Residual Rhotic Errors: A Single-Subject Randomization Study
Bibliographic record
Abstract
Purpose: This study documented the efficacy of visual-acoustic biofeedback intervention for residual rhotic errors, relative to a comparison condition involving traditional articulatory treatment. All participants received both treatments in a single-subject experimental design featuring alternating treatments with blocked randomization of sessions to treatment conditions. Method: Seven child and adolescent participants received 20 half-hour sessions of individual treatment over 10 weeks. Within each week, sessions were randomly assigned to feature traditional or biofeedback intervention. Perceptual accuracy of rhotic production was assessed in a blinded, randomized fashion. Each participant's response to the combined treatment package was evaluated by using effect sizes and visual inspection. Differences in the magnitude of response to traditional versus biofeedback intervention were measured with individual randomization tests. Results: Four of 7 participants demonstrated a clinically meaningful response to the combined treatment package. Three of 7 participants showed a statistically significant difference between treatment conditions. In all 3 cases, the magnitude of within-session gains associated with biofeedback exceeded the gains associated with traditional treatment. Conclusions: These results suggest that the inclusion of visual-acoustic biofeedback can enhance the efficacy of intervention for some individuals with residual rhotic errors. Further research is needed to understand which participants represent better or poorer candidates for biofeedback treatment.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".