Development and validation of Visual Impairment as a Risk for Falls Questionnaire
Bibliographic record
Abstract
Purpose: visual impairment is associated with an increased risk of falls, yet eye care professionals are infrequently members of falls prevention clinics. The aim of this preliminary study was to validate a newly created Visual Impairment as a Risk for Falls Questionnaire intended to be used by those professionals not involved in eye care. Methods: about 53 participants with various visual impairments known to be associated with falls and 33 participants with normal sight were contacted within 4 months of a full oculo-visual assessment and were asked the questions from the current questionnaire pertaining to their visual function. A retrospective file review was undertaken and the sensitivity and specificity of participants' responses were calculated compared to the actual vision impairment based on the findings from their visual assessment. Results: the question regarding ability to read was included to identify people with central vision loss, a risk factor for falling. It was found to have sensitivity of 74% and specificity of 87%. Both sensitivity and specificity improved when participants with cognitive impairment were excluded. The question on recognising facial features gave sensitivity of 73% and specificity of 97% for this subgroup. However, questions related to impairments in stereopsis and peripheral fields were not useful. Conclusion: the study demonstrates that several questions of the new questionnaire are useful; however, further testing with a larger population is needed to fully validate the questionnaire for use by health care professionals.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".