Protocol for a prospective, school-based standardisation study of a digital social skills assessment tool for children: The Paediatric Evaluation of Emotions, Relationships, and Socialisation (PEERS) study
Bibliographic record
Abstract
Background Humans are by nature a social species, with much of human experience spent in social interaction. Unsurprisingly, social functioning is crucial to well-being and quality of life across the lifespan. While early intervention for social problems appears promising, our ability to identify the specific impairments underlying their social problems (eg, social communication) is restricted by a dearth of accurate, ecologically valid and comprehensive child-direct assessment tools. Current tools are largely limited to parent and teacher ratings scales, which may identify social dysfunction, but not its underlying cause, or adult-based experimental tools, which lack age-appropriate norms. The present study describes the development and standardisation of Paediatric Evaluation of Emotions, Relationships, and Socialisation ( PEERS®), an iPad-based social skills assessment tool. Methods The PEERS project is a cross-sectional study involving two groups: (1) a normative group, recruited from early childhood, primary and secondary schools across metropolitan and regional Victoria, Australia; and (2) a clinical group, ascertained from outpatient services at The Royal Children’s Hospital Melbourne (RCH). The project aims to establish normative data for PEERS®, a novel and comprehensive app-delivered child-direct measure of social skills for children and youth. The project involves recruiting and assessing 1000 children aged 4.0–17.11 years. Assessments consist of an intellectual screen, PEERS® subtests, and PEERS-Q, a self-report questionnaire of social skills. Parents and teachers also complete questionnaires relating to participants’ social skills. Main analyses will comprise regression-based continuous norming, factor analysis and psychometric analysis of PEERS® and PEERS-Q. Ethics and dissemination Ethics approval has been obtained through the RCH Human Research Ethics Committee (34046), the Victorian Government Department of Education and Early Childhood Development (002318), and Catholic Education Melbourne (2166). Findings will be disseminated through international conferences and peer-reviewed journals. Following standardisation of PEERS®, the tool will be made commercially available.
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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 | 0.045 | 0.039 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.044 | 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".