Maximizing the use of practice-based clinical data to track social communication development in autistic preschoolers
Bibliographic record
Abstract
PURPOSE: Evaluating caregiver-delivered programs in clinical settings is necessary to generate practice-based evidence. One challenge of such research is the burden placed on clinicians to complete additional measurement tools. This exploratory study examined the validity of clinical forms already completed as part of the standard delivery of the More Than Words® (MTW) program and explored whether this clinical data would reveal distinct clinical and outcome profiles in real-world contexts. METHOD: The Social Communication Checklist (SCC), a MTW program-specific form completed by the speech-language pathologist, was collected for 36 autistic preschoolers during publicly funded delivery of MTW. We assessed the concurrent validity of autistic preschoolers' social communication stage and skills rated on the SCC pre- and post-program with two of their scores on reliable, validated tools: the Communication Function Classification System (CFCS) and the Focus on the Outcomes of Communication Under Six (FOCUS-34). We also explored autistic preschoolers' communicative participation outcome profiles on the FOCUS-34 with their assigned social communication stages on the SCC. RESULTS: Autistic preschoolers' pre-program social communication stage on the MTW SCC correlated with their pre-program CFCS communication level and FOCUS-34 score. Most children showed positive social communication changes post-program according to the SCC, and two-thirds showed meaningful or possibly meaningful clinical change on the FOCUS-34; however, scores on these measures did not correlate. Autistic preschoolers at different pre-program SCC stages showed distinct communicative participation outcome profiles on the FOCUS-34. CONCLUSION: Program-specific clinical forms like the SCC can be valuable for classifying autistic preschoolers' social communication skills, exploring differences in outcomes, capturing novel outcomes, and generating practice-based evidence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".