Powered Mobility for Middle-Aged and Older Adults
Bibliographic record
Abstract
OBJECTIVE: To identify the outcomes of power mobility devices for middle-aged and older adult users, and to critically appraise the research evidence. DESIGN: Systematic review of primary source studies involving adults aged 50 and over using power mobility devices (1996-2007). Articles were (i) mapped to the Taxonomy of Assistive Technology Device Outcomes, which describes categories of impact of assistive devices from the vantages of effectiveness, social significance, and subjective well-being; and (ii) appraised using the Grading of Recommendations, Assessment, Development, and Evaluation criteria. RESULTS: This review retained 19 studies and identified 52 different categories of impacts of power mobility devices spanning the three vantages of the taxonomy. The coverage of outcome dimensions was not as extensive for adults age 50 and over as it was for mixed-age groups. Most of the research designs were assigned very low evidence grades. Three studies were low to moderate in quality of evidence, among which one was a randomized trial. CONCLUSIONS: A vast array of potential impacts of powered mobility devices have been described in the last decade. The level of quality of this evidence is improving, but most of these studies were not designed to verify causal relationships, and this is largely responsible for the absence of unequivocal evidence for directly attributing benefits to devices themselves and for quantifying relationships between power mobility device intervention and outcome. To raise the level of evidence about power mobility device interventions in older adults, studies are needed that use prospective designs, better-defined user groups, and well-grounded conceptual frameworks for measuring interventions and outcomes.
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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 | 0.008 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".