Administering the Lidcombe Program to children who stutter with concomitant disorders: Insights from an exploratory retrospective chart review study
Bibliographic record
Abstract
PURPOSE: Children who stutter (CWS) in clinical settings may present with concomitant disorders (CDs), which can complexify the delivery of the Lidcombe Program (LP). However, there is limited evidence on how CDs influence treatment outcomes in CWS, leaving clinicians with little guidance regarding best practices with these children. This exploratory study, conducted in partnership with a rehabilitation center's clinical team, aims to understand which CDs and suspected CDs speech-language pathologists document when treating CWS with the LP and their relationship to treatment characteristics and outcomes. METHOD: A retrospective chart review was conducted on 47 children diagnosed with developmental stuttering who received the LP between 2016 and 2018. RESULTS: 38 CWS (80.9 %) had either at least one confirmed (59.6 %) or suspected (21.3 %) CD, of which 61.7 % were language-related and 27.6 % attention-related. CWS with diagnosed and suspected CDs had significantly higher stuttering severity rating (SR) scores post-treatment as compared to CWS without CDs (p =.001), although all groups significantly reduced their stuttering. There were high drop-out rates in all groups. CWS with diagnosed and suspected CDs who dropped out had significantly higher SR scores than CWS without CDs who progressed to Stage 2 (p =.011 and p =.014, respectively). CONCLUSION: The LP is effective in improving fluency in both CWS with and without CDs. However, CWS with diagnosed or suspected CDs finished or dropped out of Stage 1 with significantly higher SR scores than CWS without CDs. Future research is needed to confirm these results and investigate the factors underlying the observed differences.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".