Participation in intellectual disability research: a review of 20 years of studies
Bibliographic record
Abstract
BACKGROUND: Researchers have noted difficulties in attracting adequate numbers of participants with intellectual disabilities (ID) to their studies. METHODS: This study was a review of participation by adults with ID in research conducted in South Eastern Ontario over a 20-year period (1987-2006). Original research studies were identified by local investigators and then reviewed for inclusion and exclusion criteria. The report of each study was then reviewed by three reviewers and key information was extracted. The extent of study participation was calculated using three methods and compared along with key design characteristics. RESULTS: Nine studies met all inclusion/exclusion criteria and provided sufficient data to calculate participation. Among the studies there was a variety of purposes, research designs and recruitment strategies. Using the participant/approached calculation, participation varied between 41.8% and 100%. Higher participation was observed in studies where investigators had direct access to participants, the data collection was non-invasive and consent was required from substitute decision-makers only. There was no clear trend of increasing or decreasing participation over time. CONCLUSIONS: Researchers seeking the participation of adults with ID in their studies must incorporate factors influencing participation into study designs to ensure robust results and effective use of research resources.
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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 | 0.019 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.017 | 0.024 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".