Accuracy and acceptability of eHealth data collection for an early intensive behavioral intervention program
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Early intensive behavioral intervention (EIBI) is a treatment designed to increase adaptive behavior and decrease maladaptive behaviors for children with autism spectrum disorder (ASD). EIBI service providers typically collect data using pen‐and‐paper. Participants were four service providers employed at a large community‐based EIBI program. Differences in accuracy between collecting discrete‐trial‐teaching (DTT) data and challenging behavior data using pen‐and‐paper and an eHealth electronic data collection (EDC) application were assessed. The social validity of both methods of data collection was also examined. Pen‐and‐paper and EDC were equally accurate, but participants preferred using pen‐and‐paper. Our accuracy findings agreed with previous comparisons of EDC and pen‐and‐paper. Both methods of data collection are viable for an EIBI program; however, social validity considerations will determine the ease of EIBI programs transitioning to using an eHealth tool for data collection.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 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 it