A Validity and Reliability Study of a Chinese Assessment Tool for Persons with Moderate to Severe Intellectual Disabilities
Bibliographic record
Abstract
This study was designed to test the psychometric properties of the Chinese interRAI Intellectual Disability (ID) tool in a Chinese population with learning disabilities in Hong Kong. The Chinese interRAI ID was prepared based on the original interRAI ID which is a standardized, comprehensive instrument and is designed to evaluate the strengths, preferences, and needs of persons with all levels of ID living in various care settings. A sample of 100 people with moderate to severe intellectual disabilities was assessed with the Chinese interRAI ID and its criterion measures. The subscales of the interRAI ID, including the Cognitive Performance Scale, Depression Rating Scale, Aggressive Behavior Scale, Activities of Daily Living Hierarchy Scale, and Instrumental Activities of Daily Living Involvement Scale, had high internal consistency (Cronbach’s α = .66 to .87) and test–retest reliability (r = .96 to .99; κ = .68 to .81). Comparison of the interRAI ID scales with criterion measures supported concurrent and discriminant validity of these scales. The study results provide preliminary support for the Chinese interRAI ID as a reliable and valid tool for assessing Chinese individuals with learning disabilities in Hong Kong.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".