Assessing general cognitive and adaptive abilities in adults with Down syndrome: a systematic review
Bibliographic record
Abstract
BACKGROUND: Measures of general cognitive and adaptive ability in adults with Down syndrome (DS) used by previous studies vary substantially. This review summarises the different ability measures used previously, focusing on tests of intelligence quotient (IQ) and adaptive behaviour (AB), and where possible examines floor effects and differences between DS subpopulations. We aimed to use information regarding existing measures to provide recommendations for individual researchers and the DS research community. RESULTS: Nineteen studies reporting IQ test data met inclusion for this review, with 17 different IQ tests used. Twelve of these IQ tests were used in only one study while five were used in two different studies. Eleven studies reporting AB test data met inclusion for this review, with seven different AB tests used. The only AB scales to be used by more than one study were the Vineland Adaptive Behaviour Scale (VABS; used by three studies) and the Vineland Adaptive Behavior Scale 2nd Edition (VABS-II; used by two studies). A variety of additional factors were identified which make comparison of test scores between studies problematic, including different score types provided between studies (e.g. raw scores compared to age-equivalent scores) and different participant inclusion criteria (e.g. whether individuals with cognitive decline were excluded). Floor effects were common for IQ tests (particularly for standardised test scores). Data exists to suggest that floor effects may be minimised by the use of raw test scores rather than standardised test scores. Raw scores may, therefore, be particularly useful in longitudinal studies to track change in cognitive ability over time. CONCLUSIONS: Studies assessing general ability in adults with DS are likely to benefit from the use of both IQ and AB scales. The DS research community may benefit from the development of reporting standards for IQ and AB data, and from the sharing of raw study data enabling further in-depth investigation of issues highlighted by this review.
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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 | 0.007 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".