Silent suffering: understanding and treating children with selective mutism
Bibliographic record
Abstract
Children with selective mutism (SM) restrict speech in some social environments, often resulting in substantial academic and social impairment. Although SM is considered rare, one or more children with SM can be found in most elementary schools. Assessment is performed to confirm the diagnosis, rule out psychological and medical factors that may account for the mutism, ascertain comorbid and exacerbating conditions needing treatment, and develop an intervention plan. Interventions are often multidisciplinary and focus on decreasing anxiety, increasing social speech and ameliorating SM-related impairment. Research is limited, but symptomatic improvement has been demonstrated with behavioral interventions and multimodal treatments that include school and family participation, as well as behavioral methods. Selective serotonin-reuptake inhibitors, especially fluoxetine, have also been found to be efficacious and merit consideration in severe cases. Persistence of some SM or anxiety symptoms despite treatment is common. Further development of treatments targeting specific etiological factors, comparative treatment studies and determination of optimal involvement of families and schools in treatment are needed to improve outcomes for children with SM.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".