Physical mobility limitations in adults with intellectual disabilities: a systematic review
Bibliographic record
Abstract
BACKGROUND: Mobility limitations increase with age in the general population. Despite a growing population of older adults with intellectual disabilities (ID), mobility is rarely studied in the ID literature. The specific aim of this study was to identify and summarise primary literature investigating mobility limitations in adults with ID. METHODS: This study was a systematic review of the epidemiological literature (incidence and prevalence) of mobility limitations among adults with ID. Four electronic databases were searched from January 1980 to May 2007 for publications according to predefined inclusion/exclusion criteria. Additional sources were consulted. Two reviewers extracted data from each of the included articles. RESULTS: Thirty-two publications representing 31 studies were ultimately included. In general, studies did not focus on mobility but were conducted for other purposes. All studies were conducted in industrialised countries. Only one study used a longitudinal design; the remainders were cross-sectional. Few investigators reported on the representativeness of the sample or the validity of the measurement tool. Study samples differed substantially and investigators used numerous definitions of mobility limiting comparability between studies. CONCLUSIONS: There is a need for increased research on mobility limitations among adults with ID, particularly longitudinal research. Researchers investigating mobility limitations should use validated measurement tools and offer detailed descriptions of the study sample and how it compares with an identifiable population.
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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 | 0.004 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.009 | 0.010 |
| 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) | 0.004 | 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".