Qualitative experiences of new motorised mobility scooter users relevant to their scooter skills: a secondary analysis
Bibliographic record
Abstract
Objective To explore the experiences of new motorised mobility scooter users from the perspectives of the assessment and training of scooter skills.Design Descriptive secondary analysis of qualitative data.Setting Community.Participants 20 New users of motorised mobility scooters.Interventions Not applicable.Main outcome measures Directed qualitative analysis of up to four semi-structured interviews over the course of the first year of scooter use, to identify themes and sub-themes that could inform recommendations regarding assessment and training protocols.Results We identified two themes. The first related to potential new content. As one example of the sub-themes, there were many excerpts that dealt with the use of skills in various combinations and permutations that were used to carry out activities during everyday life and participate in society. These excerpts suggested the importance of training skills in combination to facilitate skill transfer (or generalizability). The second theme is related to enhancements of existing content. As one example of the sub-themes, there were several excerpts that dealt with scooter security. These excerpts led to the recommendation that removing and inserting the scooter key should be added to the assessment criteria for the “turns power on and off” skill of the Wheelchair Skills Test (WST) and its questionnaire version (WST-Q).Conclusions The experiences of scooter users over the first year of receiving a scooter appear to be relevant to the assessment and training of scooter skills and suggest themes for further study. Clinical trial registration number: NCT02696213 IMPLICATIONS FOR REHABILITATIONThe experiences of new scooter users are highly relevant to the assessment and training of scooter skills.These experiences suggest both potential new content and enhancements of existing content to the Wheelchair Skills Program Manual.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".