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Record W2934102705 · doi:10.1177/0263067219834712

A role-play assessment tool and drama-based social skills intervention for adults with autism or related social communication difficulties

2019· article· en· W2934102705 on OpenAlexaff
Céliane Trudel, Aparna Nadig

Bibliographic record

VenueDramatherapy · 2019
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsNeurotypicalSocial skillsPsychologyAutismIntervention (counseling)Autism spectrum disorderPsychological interventionDevelopmental psychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

This study adds to a small literature on social skills measures and interventions for adults with autism spectrum disorder (ASD) or related social communication difficulties (SCD) without intellectual disability (ID). In study 1, a new multimodal assessment tool, the role-play assessment of social skills (R-PASS), was used to measure real-time application of social skills. The scores of adults with ASD/SCD were marginally lower than those of neurotypical adults, with a large effect size, suggesting that the measure can identify differences between the two groups. Therefore, the R-PASS shows potential as an objective tool to assess dynamic and naturalistic social skills. In Study 2, a pre–post single-group design study, we measured the effectiveness of a drama-based social skills intervention for seven participants who self-identified as having ASD/SCD. The R-PASS was used by external raters blind to diagnosis and intervention status to compare the performance of intervention participants to that of neurotypical adults. R-PASS scores suggested substantial improvement of social skills in the majority of participants post-intervention. Furthermore, relatives’ and participants’ perception of their social communication and self-regulation skills improved from pre- to post-intervention. These results suggest that the intervention may have helped the participants improve their social skills.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.637
Threshold uncertainty score0.650

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.315
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2019
Admission routes1
Has abstractyes

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