Scoping review of mobility scooter-related research studies
Bibliographic record
Abstract
Mobility scooters are three- or four-wheeled power mobility devices regularly used by people who have difficulty ambulating. They also differ from power wheelchairs in terms of their driving controls, programmability, seating, and mounting method. Given their growing popularity and anecdotal concerns around their use, a scoping review was undertaken to identify empirical research about mobility scooters and to analyze their study design and purpose. Data sources included MedLINE, Cumulative Index to Nursing and Allied Health Literature, Embase, and PsychINFO. Thirty-two studies met the inclusion criteria. Most studies were descriptive in nature and reported information about scooter users' demographics, scooter-related activities, and accidents. The most common study design was a pre- and postintervention followed by a cross-sectional survey and retrospective review. Despite the increasing use of mobility scooters, surprisingly little scooter-related research has been conducted. Given the nature of most of the research in this area, further empirical evidence is needed to develop a better understanding about the frequency and causes of scooter accidents and the efficacy of interventions to improve users' skills, mobility, and safety.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.091 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.035 | 0.031 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".