Evaluation of a caregiver training program to teach help-seeking behavior to children with autism spectrum disorder
Bibliographic record
Abstract
Alarmingly, nearly half of children with autism spectrum disorder (ASD) engage in behaviour that causes separation from caregivers. More than half of these children go missing for a concerning duration of time and/or enter into dangerous situations. Caregivers often do not feel prepared to address these serious concerns. This study evaluated the effectiveness of behaviour skills training (BST) for teaching caregivers how to also use BST in conjunction with a tactile prompt to teach their children with ASD help-seeking behaviour. Participants included five caregiver-child dyads. Children were diagnosed with ASD and were between the ages of 5-10 years. A non-concurrent multiple probe design across three dyads with a concurrent replication across an additional two dyads was used to evaluate whether the BST procedure increased child safety responses when separated from caregivers in store settings. Child behaviours were measured using a 3-step help-seeking behaviour chain: (1) calling out for their caregiver in a louder than conversational voice, (2) locating a store employee, and (3) informing the employee that they were lost. All children met mastery criteria (a safety response score of 3 across two consecutive trials), and four of the caregivers were able to successfully fade the tactile prompting device in the natural environment. This study contributes to the limited empirical research on caregiver implemented safety training using BST to teach help-seeking behaviour to children with ASD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".