Bibliographic record
Abstract
BACKGROUND: Comfort of an orthosis is an important characteristic that is likely to dictate use of and satisfaction with a device. However, instruments to assess only orthosis user comfort do not exist. The Prosthetic Socket Fit Comfort Score, developed previously for prosthesis users, may be adapted to serve this purpose. OBJECTIVES: This study's purpose was to assess the validity and reliability of the Orthosis Comfort Score, a self-report instrument adapted from the Prosthetic Socket Fit Comfort Score. STUDY DESIGN: This is a prospective, observational study designed to establish initial evidence of validity and reliability for an outcome measure that assesses comfort. METHODS: Ankle foot orthosis users completed the Orthosis Comfort Score and two validated patient satisfaction questionnaires. An orthotist documented an assessment of fit. Post-visit Orthosis Comfort Scores were documented after the appointment and 2-4 weeks later. Orthosis Comfort Scores were compared to the patient satisfaction questionnaires, assessment of fit and orthosis use (hours per week). RESULTS: < 0.05). CONCLUSION: This study demonstrates initial evidence for the validity and reliability of the Orthosis Comfort Score in ankle foot orthosis users. CLINICAL RELEVANCE: The Orthosis Comfort Score is a simple patient-reported outcome measure that can be readily incorporated into clinical practice or research study to obtain a rapid assessment of comfort. It can be used to facilitate communication about device fit, evaluate comfort over time and/or assess changes in comfort with a new device.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".