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Record W2898763268 · doi:10.1371/journal.pone.0206800

A psychometric evaluation of the Multidimensional Social Competence Scale (MSCS) for young adults

2018· article· en· W2898763268 on OpenAlexafffund
Dominic A. Trevisan, Donna Tafreshi, Kathleen L. Slaney, Jodi Yager, Grace Iarocci

Bibliographic record

VenuePLoS ONE · 2018
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsSimon Fraser University
FundersSocial Sciences and Humanities Research Council of CanadaMichael Smith Health Research BC
KeywordsSocial competencePsychologyAutismDiscriminant validityDevelopmental psychologySocial skillsAutism spectrum disorderRating scaleConstruct validityCompetence (human resources)ConversationConvergent validityPsychometricsPopulationClinical psychologySocial changeMedicineSocial psychology

Abstract

fetched live from OpenAlex

The current study contributes to previous work on measuring the social phenotype in Autism Spectrum Disorder (ASD) by validating a multidimensional test of social competence developed for use with individuals with and without ASD. The "Multidimensional Social Competence Scale" (MSCS) was previously validated as a parent-rating scale with youth 11-18 years with ASD without intellectual disability and typically developing adolescents of comparable age. The current study presents a validation of a self-report version of the MSCS in a non-clinical young adult population (N = 1178, males = 360, females = 817, age range = 17-25 years). The MSCS consists of seven domains that represent social competence: social motivation, social inferencing, demonstrating empathic concern, social knowledge, verbal conversation skills, nonverbal sending skills, and emotion regulation. These domains are theorized to be indicative of the higher-order construct of social competence. A second higher-order theorization of the MSCS structure posits that 3 of these factors are indicative of social responsiveness, and the remaining 4 factors are indicative of social understanding and emotion regulation. Our findings indicated support for each of the theorized multidimensional factor structures. Reliability, optimal scoring, convergent and discriminant validity of the measure, as well as implications for future research are discussed.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.242
Threshold uncertainty score0.264

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.137
GPT teacher head0.343
Teacher spread0.205 · 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 designBench or experimental
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

Citations58
Published2018
Admission routes2
Has abstractyes

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