The validity of patient and physician estimates of walking distance
Bibliographic record
Abstract
OBJECTIVE: To establish the validity of patient and physician estimates of maximum walking distance versus actual measured maximum walking distance. DESIGN: Assessment of concurrent validity (patient and physician estimates were compared with a gold standard measure at the same time). SETTING: University-affiliated rehabilitation department in a tertiary care hospital. SUBJECTS: A sequential sample of 31 patients over the age of 17 referred to the physical medicine and rehabilitation outpatients department between 1 May 2000 and 20 July 2001, who had at least some degree of walking difficulty. INTERVENTIONS: Patients and their physicians were asked to provide estimates of walking distance independently after a regular appointment prior to the patient being escorted along a pre-measured walking course. MAIN OUTCOME MEASURES: Actual distance walked was compared with estimates using Pearson correlation coefficients. RESULTS: Pearson correlation coefficients for patient estimate versus actual was 0.789 (p < or = 0.0001), and mean estimate of patient and physician estimates versus actual was 0.812 (p < or = 0.0001). Physician estimate versus actual and patient estimate versus physician estimate were 0.349 and -0.139 (neither significant). Sixty-seven per cent (20/30) of patients overestimated how far they thought they could walk versus 23% (7.30) of physicians who overestimated. Neither group were found to be 'good' estimators of maximal walking distance. CONCLUSIONS: Neither patients nor physicians provide valid estimates of maximal walking distance. Patients consistently overestimate their maximal walking distance, whereas physicians tend to underestimate. Interestingly, patients' estimates (although over inflated) do correlate well with actual walking distance, while physician estimates are not at all correlated. This study suggests that reliance on self-reported or physician-estimated maximum walking distances (whether for clinical, research or other reasons) is potentially flawed.
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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 | 0.014 | 0.131 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".