Language and communication in children with complex tourette syndrome: Insights from five mixed methods case studies
Bibliographic record
Abstract
PURPOSE: This study aimed to understand and describe language skills and day-to-day communication in five children with complex Tourette syndrome. METHOD: We conducted five scaffolded mixed methods case studies. Psychosocial functioning and language skills were measured using standardised tests. We collected information about day-to-day communication using communication log books and semi-structured qualitative interviews. Communication was considered using the bioecological model with a focus on microstructure' contexts (i.e. school, home, and peer interaction). RESULT: All children had accessed school accommodations, extra services, or alternative education options. While some parents highlighted school successes, others described significant challenges in finding a fitting school environment for their child. Managing family interaction in the home required parents to be thoughtful and proactive in their planning. Parents strategised to keep the home environment calm and productive, adopted attitudes of acceptance and understanding, and accessed outside tools and supports. In some cases, parents provided social coaching and created intentional social experiences so their child could be successful; in other cases, children were thriving socially without need for parental intervention. CONCLUSION: The communication profiles and parent-reported experiences of children with complex Tourette syndrome are diverse. Interventions and accommodations need to be individualised to optimise language development and day-to-day communication.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".