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Record W2139259794 · doi:10.1155/2014/425897

Video Self-Modeling Is an Effective Intervention for an Adult with Autism

2014· article· en· W2139259794 on OpenAlexaff
Genevieve Hin Ha Tsui, M. D. Rutherford

Bibliographic record

VenueCase Reports in Neurological Medicine · 2014
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsProsocial behaviorAutismIntervention (counseling)Psychological interventionAutism spectrum disorderMedicineDevelopmental psychologyPsychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

With the increases in size and strength that come with adulthood, challenging behaviours among those with autism spectrum disorders (ASD) can become critical. Few studies have explored behavioural interventions in adults with ASD, though recent studies have shown video self-modeling (VSM) to be effective in children with ASD. VSM involves an individual watching videos of himself demonstrating prosocial behaviours, while those behaviours are pointed out and encouraged. In the current study, VSM was used to encourage prosocial behaviours and to reduce problematic behaviour displayed by an adult with ASD. Results reveal a decrease in the tendency to invade others' personal space and make inappropriate loud noises. VSM may be an effective intervention and improve the lives of adults 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 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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.828
Threshold uncertainty score0.690

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.041
GPT teacher head0.344
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 designSimulation or modeling
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

Citations7
Published2014
Admission routes1
Has abstractyes

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