Evidence of validity and reliability of the adaptive functioning scale for intellectual disability (EFA-DI)
Bibliographic record
Abstract
Intellectual disability (ID) is a developmental disorder characterized by deficits in intellectual functioning and adaptive behavior. The fifth edition of the Diagnostic and statistical manual of mental disorders (DSM-5) defines adaptive functioning as a severity measure of ID. The availability of tests in the international context to assess this construct has increased in recent years. In Brazil, however, non-systematic assessment of adaptive functioning, such as through observation and interviews, still predominates. The Escala de Funcionamento Adaptativo para Deficiência Intelectual EFA-DI [Adaptive Functioning Scale for Intellectual Disabilities] is a new instrument developed in Brazil to assess the adaptive functioning of 7- to 15-year-old children and support the diagnosis of ID. This study's objectives were to investigate evidence of validity related to the EFA-DI's internal structure, criterion validity, and reliability. The psychometric analyses involved two statistical modeling types, confirmatory factor analysis (CFA) and item response theory analysis (IRT). These results highlight the EFA-DI scale's strong psychometric properties and support its use as a parental report measure of young children's adaptive functioning. Future studies will be conducted to develop norms of interpretation for the EFA-DI. This study is expected to contribute to the fields of psychological assessment and child development in Brazil.
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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 | 0.022 | 0.068 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".