Re‐visiting the ‘mysterious myth of attention deficit’: A systematic review of the recent evidence
Bibliographic record
Abstract
Based on the inclusive and methodologically rigorous framework provided by Ed Zigler's developmental approach, we previously challenged what we called, 'the mysterious myth of attention deficit', the fallacy of attention as a universal deficit among persons with intellectual disability (ID). In this latest update, we conducted a systematic review of studies of essential components of attention among persons with ID published in the interim since the last iteration of the mysterious myth narrative was submitted for publication approximately a decade ago. We searched the databases PubMed and PsycINFO for English-language peer-reviewed studies published from 1 January 2011 through 5 February 2021. In keeping with the developmental approach, the two essential methodological criteria were that the groups of persons with ID were aetiologically homogeneous and that the comparisons with persons with average IQs (or with available norms) were based on an appropriate index of developmental level, or mental age. Stringent use of these criteria for inclusion served to control for bias in article selection. Articles were then categorised based on aetiological group studied and component of visual attention. Based on these criteria, 18 articles were selected for inclusion out of the 2837 that were identified. The included studies involved 547 participants: 201 participants with Down syndrome, 214 participants with Williams syndrome and 132 participants with fragile X syndrome. The findings from these articles call attention to the complexities and nuances in understanding attentional functioning across homogeneous aetiological groups and highlight that functioning must be considered in relation to aetiology; factors associated with the individual, such as developmental level, motivation, styles and biases; and factors associated with both the task, such as context, focus, social and emotional implications, and levels of environmental complexity.
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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 | 0.061 | 0.200 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.005 |
| Bibliometrics | 0.026 | 0.022 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| 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".