Reliability and Validity of the Power-Mobility Community Driving Assessment
Bibliographic record
Abstract
The Power-Mobility Community Driving Assessment (PCDA) is a performance-based measure designed to assess driving performance of individuals using power wheelchairs or scooters in community environments. This article reports the results of pilot testing and an evaluation of the assessment's reliability and validity. Pilot testing was conducted with a random selection of Canadian occupational therapists working in the area of mobility. Although the response rate was very low, feedback confirmed the utility of the measure and contributed to one substantive scoring revision. Reliability and validity testing was conducted with a sample of 34 drivers. Internal consistency results were positive. Interrater reliability was fair to high but limited by the lack of variability in the scores. Construct validity hypotheses were tested on the relationships between PCDA scores and vision, perception, cognition, and environmental accessibility. Results indicated no relationships between the PCDA and perceptual and cognitive function and only a weak trend for a relationship with environmental accessibility. Concurrent validity was established: PCDA scores were positively associated with the judgments of therapists familiar with the driving performance of participants. In summary, the PCDA has moderate to good reliability, and content and concurrent validity results were found. More research is needed, particularly on the underlying constructs of successful driving performance. At this point, rehabilitation professionals and their clients are urged to use this assessment to establish driving performance rather than relying on assessments of perception, cognition, or environmental accessibility to predetermine whether someone will receive power mobility. Clinicians may find this a useful tool to identify where clients are able to drive safely in community settings, to identify specific learning needs, and, through those, to promote independent living for drivers of power-mobility devices.
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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 | 0.020 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".