Understanding the task demands for powered wheelchair driving: a think-aloud task analysis
Bibliographic record
Abstract
BACKGROUND: Powered wheelchair use promotes participation in individuals with limited mobility, however training is required for safe and effective use. There is limited evidence on the task demands of powered wheelchair use to inform an evidence-based skills training programme. OBJECTIVE: To conduct a systematic exploration of the task demands of indoor powered wheelchair use to identify frequently used skills, abilities, and knowledge. METHODS: = 5). Participants completed seven indoor driving tasks while speaking aloud (concurrent think aloud) and subsequently engaged in a structured qualitative interview to discuss skills, abilities, and knowledge used across each of the seven tasks (retrospective think aloud). We used directed content analysis to map the skills and abilities to the ICF framework and conventional content analysis to develop thematic areas of knowledge used while operating a powered wheelchair. RESULTS: One-hundred and ten (110) distinct skills and abilities were identified and mapped to the ICF; 80 in the Body Structures and Functions domain, and 30 in the Activities and Participation domain. Approximately 50% of skills and abilities were mental functions. Four thematic knowledge domains were identified: knowledge of self, environment, wheelchair, and task. CONCLUSION: Powered wheelchair use is complex and requires a variety of skills and abilities from all areas of human functioning, in addition to a wide range of knowledge. Training programmes should address a range of areas of skill development.IMPLICATIONS FOR REHABILITATIONPowered wheelchair use is a complex skill; training should develop skills from all.Domains of the ICF, including mental and physical functions.A range of knowledge is used while operating a powered wheelchair; training programs.Should include the development and application of necessary knowledge.Clinicians may consider a range of factors when assessing suitability for powered.Wheelchair user, however should acknowledge that while the range of skills idenotified.May be useful, they may not be critical for success in powered wheelchair use.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".