Autism Spectrum Social Stories In Schools Trial 2 (ASSSIST2): study protocol for a randomised controlled trial analysing clinical and cost-effectiveness of Social Stories™ in primary schools
Bibliographic record
Abstract
BACKGROUND: Interventions designed to support children with a diagnosis of Autism Spectrum Conditions (ASC) can be time consuming, needing involvement of outside experts. Social Stories™ are a highly personalised intervention aiming to give children with ASC social information or describing an otherwise difficult situation or skill. This can be delivered daily by staff in education settings. Studies examining Social Story™ use have yielded mostly positive results but have largely been single case studies with a lack of randomised controlled trials (RCTs). Despite this numerous schools are utilising Social Stories™, and a fully powered RCT is timely. METHODS: A multi-site pragmatic cluster RCT comparing care as usual with Social Stories™ and care as usual. This study will recruit 278 participants (aged 4-11) with a clinical diagnosis of ASC, currently attending primary school in the North of England. Approximately 278 school based staff will be recruited to provide school based information about participating children with approximately 140 recruited to deliver the intervention. The study will be cluster randomised by school. Potential participants will be screened for eligibility prior to giving informed consent. Follow up data will be collected at 6 weeks and 6 months post randomisation and will assess changes in participants' social responsiveness, goal based outcomes, social and emotional health. The primary outcome measure is the Social Responsiveness Scale Second Edition (SRS-2) completed by school based staff at 6 months. Approvals have been obtained from the University of York's Research Governance Committee, Research Ethics Committee and the Health Research Authority. Study results will be submitted for publication in peer-reviewed journals and disseminated to participating families, educational staff, local authority representatives, community groups and Patient and Participant Involvement representatives. Suggestions will be made to NICE about treatment evidence dependent on findings. DISCUSSION: This study addresses a much used but currently under researched intervention and results will inform school based support for primary school children with a diagnosis of ASC. TRIAL REGISTRATION: The trial is registered on the ISRCTN registry (registration number: ISRCTN11634810). The trial was retrospectively registered on 23rd April 2019.
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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 | 0.046 | 0.041 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.096 | 0.016 |
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".