Comparison of commonly used orthopaedic outcome measures using palm‐top computers and paper surveys
Bibliographic record
Abstract
INTRODUCTION: Measuring patient-perceived outcomes following orthopaedic procedures have become an important component of clinical research and patient care. General and disease-specific outcomes measures have been developed and applied in orthopaedics to assess the patients' perceived health status. Unfortunately, paper-based, self-administered instruments remain inefficient for collecting data because of: (a) missing data (b) respondent error, and (c) the costs to administer and enter data. OBJECTIVE: To study the comparability of palm-top computer devices and paper-pencil self-administered questionnaires in the collection of health-related quality of life (HRQL) information from patients. METHODS: The comparability of administering HRQL questionnaires using palm-top computer and traditional paper-based forms was tested in a sample of 96 patients with complaints of hip and/or knee pain. Each patient completed mailed versions of the Medical Outcomes Study (MOS), 36-item Health Survey (SF-36), and Western Ontario and McMasters University Arthritis Index (WOMAC) three weeks prior to presenting to clinic. At the clinic they were asked to complete the same outcomes measures using the palm-top computer or a paper-and-pencil version. ANALYSIS: In the analysis, scale distributions, floor and ceiling effects, internal consistency and retest reliability of scales were compared across the two data collection methods. Because the baseline characteristics of the groups were not strictly comparable according to age, the data were analyzed for the entire sample and stratified according to age. RESULTS: Few statistically significant differences were found for the means, variances and intra-class correlation coefficients between the methods of administration. While the scale distribution between the two methods was comparable, the internal consistency of the scales was dissimilar. CONCLUSIONS: Administration of HRQL questionnaires using portable palm-top computer devices has the potential advantage of decreased cost and convenience. These data lend some support for the comparability of palm-top computers and paper surveys for outcomes measures widely used in the field of orthopaedic surgery. The present study identified the lack of reliability across modes of administration that requires further study in a randomized comparability trial. These mode effects are important for orthopaedic surgeons to appreciate before implementing innovative data-capture technologies in their practices.
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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 | 0.029 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| 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) | 0.002 | 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".