Use of the UFOV to Evaluate and Retrain Visual Attention Skills in Clients With Stroke: A Pilot Study
Bibliographic record
Abstract
OBJECTIVE: The objective of this pilot study was to examine the use of a visual attention analyzer in the evaluation and retraining of useful field of view in clients with stroke. METHOD: Fifty-two clients with stroke referred to a driving evaluation service were evaluated with a visual attention analyzer referred to as the UFOV. The UFOV assesses three aspects of visual attention: processing speed, divided attention, and selective attention. Seven participants were retested to determine the test-retest reliability of the UFOV. Six participated in the development of a training protocol and in a 20-session visual attention retraining program. RESULTS: UFOV scores indicated substantial reduction in visual attention in clients after stroke, with older participants performing the most poorly. Test-retest reliability was moderate (ICC = .70). Mean UFOV scores improved significantly after retraining. CONCLUSION: Although UFOV scores indicated poor visual attention skills in clients with stroke, preliminary information suggests that UFOV scores significantly improve with training.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".