The Development of the Multidimensional Social Competence Scale: A Standardized Measure of Social Competence in Autism Spectrum Disorders
Bibliographic record
Abstract
Autism and its related disorders are commonly described as lying along a continuum that ranges in severity and are collectively referred to as autism spectrum disorders (ASDs). Although all individuals with ASD meet the social impairment diagnostic criteria outlined in the DSM-IV-TR, they do not present with the same social difficulties. The variability in the expression and severity of social competence is particularly evident among the group of individuals with "high-functioning" ASD who appear to have difficulty applying their average to above average intelligence in a social context. There is a striking paucity of empirical research investigating individual differences in social functioning among individuals with high-functioning ASD. It is possible that more detailed investigations of social competence have been impeded by the lack of standardized measures available to assess the nature and severity of social impairment. The aim of the current study was to develop and evaluate a parent rating scale capable of assessing individual differences in social competence (i.e. strengths and challenges) among adolescents with ASD: the Multidimensional Social Competence Scale (MSCS). Results from confirmatory factor analyses supported the hypothesized multidimensional factor structure of the MSCS. Seven relatively distinct domains of social competence were identified including social motivation, social inferencing, demonstrating empathic concern, social knowledge, verbal conversation skills, nonverbal sending skills, and emotion regulation. Psychometric evidence provided preliminary support for the reliability and validity of the scale. Possible applications of this promising new parent rating scale in both research and clinical settings are discussed.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".