Understanding the Outcome of Children who Selectively Do not Speak: A Retrospective Approach.
Bibliographic record
Abstract
BACKGROUND: Little is known about the longer-term outcomes of children diagnosed with selective mutism (SM) and/or social anxiety disorder (SAD); two anxiety disorders characterized by difficulties speaking in social situations despite being able to speak in other contexts. OBJECTIVE: This retrospective study aimed to descriptively evaluate the long-term SM and SAD diagnostic and symptom severity outcomes in a clinical youth sample. METHODS: Retrospective follow-up interviews were conducted with 31 parents of children/youth aged four to 14 years previously referred to a specialized anxiety clinic and diagnosed with SM and/or SAD (mean follow-up 4.2 years). Clinician and parent-report measures were used to determine follow-up diagnosis and symptom severity. RESULTS: The majority (71%; n=22) of participants still met criteria for SM and/or SAD. Of these, 11 had SAD only; nine had a comorbid diagnosis of SM and SAD; and two had SM only. At follow-up 42% (n=13) were receiving school supports. Close to half (48%; n=15) of parents continued to express concerns about their child's anxiety. Almost all (90%, n=28) youth had attempted some form of treatment, with group cognitive behavioural therapy (CBT) reported as the most common form of treatment tried (48%, n=15). Almost thirty percent (29%, n=9) reported taking anxiety medications in the past with several (13%, n=4) still on medications at follow-up. CONCLUSION: Study results suggest that symptoms of SM and SAD persist in the longer-term. Further investigation into the differences between diagnostic groups and their long-term treatment outcomes is clearly warranted.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".