The Ability of Outcome Questionnaires to Capture Patient Concerns Following Ankle Reconstruction
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to compare questions from outcome questionnaires with items generated by preoperative and postoperative ankle reconstruction patients (using the open-ended questions of self-reported Patient-Specific Index [PASI]) to determine whether existing questionnaires address patients' concerns. METHODS: Patients (n = 142) completed the PASI. Questions from 6 standardized questionnaires (American Academy of Orthopaedic Surgeons Foot and Ankle Questionnaire [AAOS], patient-reported portion of the American Orthopaedic Foot and Ankle Society Clinical Rating System Ankle-Hindfoot Scale [AOFAS], Foot Function Index [FFI], Lower Extremity Functional Scale [LEFS], Short Musculoskeletal Function Assessment [SMFA], Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC]) and PASI were matched by 3 reviewers to corresponding categories in the International Classification of Functioning, Disability and Health (ICF). Standardized questionnaires were then compared with the patient responses produced by the PASI. RESULTS: Patients identified 690 items corresponding to 45 ICF categories. Most PASI concepts fell into Activities and Participation (60.3%) and Body Functions (29.0%) components, including the categories "walking" (19.1%), "pain" (16.5%), and "recreation and leisure" (15.4%); 237 items were identified in questionnaires and linked to 39 ICF categories. Core issues in questionnaires ("pain," "walking," "stairs") were important concerns for patients, but other key patient concerns ("swelling," "recreation and leisure," "sports") were seldom included in questionnaires. CONCLUSION: No single questionnaire captured all patient concerns, and standardized questionnaires differed largely in content. This analysis may help guide development of a more comprehensive instrument for evaluating outcomes following ankle reconstruction. CLINICAL RELEVANCE: When choosing an outcome questionnaire, clinicians and researchers should consider the targeted outcome because no one questionnaire captures the full patient experience.
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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 | 0.021 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".