Phase I trial of a standalone internet social anxiety treatment for adolescents who stutter: iBroadway
Bibliographic record
Abstract
BACKGROUND: iGlebe is a fully automated internet treatment program for adults who stutter that has been shown, in some cases, to reduce anxiety and effectively manage social anxiety disorder for many participants. No such automated internet treatment program exists for adolescents who stutter. AIMS: The present paper reports a Phase I trial of an adolescent version of the adult program: iBroadway. METHODS & PROCEDURES: Participants were 29 adolescents in the age range 12-17 years who were seeking cognitive-behaviour therapy (CBT) for anxiety associated with stuttering. The design was a non-randomized Phase I trial with outcome assessments at pre-treatment and immediately post-treatment after 5 months of access to the program. No contact by a clinical psychologist occurred during participant use of the program. Outcomes were a range of psychological, quality-of-life and stuttering severity measures. OUTCOMES & RESULTS: The compliance rate for the seven iBroadway modules over 5 months was extremely favourable for internet CBT, at 52.4%. There was evidence of treatment effects for (1) the number of DSM-IV mental health diagnoses with the Diagnostic Interview Schedule for Children; (2) the Unhelpful Thoughts and Beliefs About Stuttering scale; (3) the Subjective Units of Distress Scale; and (4) parent-reported speech satisfaction. CONCLUSIONS & IMPLICATIONS: Further development of iBroadway, the adolescent version of iGlebe, with Phase II trialling is 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".