Development of the Functional Recovery Index for Ambulatory Surgery and Anesthesia
Bibliographic record
Abstract
BACKGROUND: It is increasingly important to evaluate patients' recovery after ambulatory surgery. The authors developed the Functional Recovery Index (FRI) to assess postdischarge functional recovery for ambulatory surgical patients. METHODS: The scale development involved four phases: item generation, item selection, reliability, and validity testing. A draft questionnaire was tested and revised. Items were selected through testing endorsement frequency, factor analysis, and testing internal consistency. The interrater reliability was calculated. Construct validity was tested by multiple hypotheses on convergent validity, extreme groups, and discriminant validity. Responsiveness was assessed by measuring the FRI postoperatively and comparing minor versus more extensive surgery. The rate of response and the time for completion of the questionnaire were recorded. RESULTS: The final questionnaire had 14 items grouped under 3 factors. Each item was scored from 0 to 10, with 0 = no difficulty and 10 = extreme difficulty with the activity. The 3 factors were summated for a total score. Internal consistency for the 3 factors (pain and social activity, lower limb activity, and general physical activity) was as follows: Cronbach alpha = 0.90, 0.89, and 0.86, respectively. Interrater reliability was 0.99. Convergent validity for FRI versus verbal rating scale pain score was 0.76. Discriminant validity testing showed that the type of surgery was significant and that intermediate (beta = 0.138) and major surgery (beta = 0.337) were associated with higher FRI scores than minor surgery. The time to complete the questionnaires ranged between 4 min 10 s and 4 min 35 s. CONCLUSIONS: The FRI had excellent reliability, good validity, responsiveness, and acceptability, indicating that this questionnaire will be a good instrument for assessing functional recovery of ambulatory surgical patients.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".