Comparison of Paper and Computer-Based Questionnaire Modes for Measuring Health Outcomes in Patients Undergoing Total Hip Arthroplasty
Bibliographic record
Abstract
BACKGROUND: Health status questionnaires are important, especially with the growing interest in outcome studies. However, these questionnaires continue to be administered in their original paper format. We hypothesized that total hip arthroplasty outcome data derived with computer-based questionnaires do not differ significantly from those derived with established paper-based formats. METHODS: From January 2006 to January 2007, the clinic schedules of four attending arthroplasty surgeons were screened weekly to identify patients who could potentially be included in the study. Charts were reviewed for subjects who were scheduled for or had received primary total hip arthroplasty. Patients were recruited during their office visit or when they attended a preoperative educational class, and five health status questionnaires (the Harris hip score, WOMAC [Western Ontario and McMaster Universities Osteoarthritis Index], SF-36 [Short Form-36], EQ-5D [EuroQol-5D], and UCLA [University of California at Los Angeles] activity score) were administered in three formats: paper, touch screen, and web-based. Repeated-measures analysis of variance and Pearson correlations were used to compare the questionnaire modes for the Harris hip score (normally distributed data), and the Friedman test and Spearman correlations were used to compare the modes for the other health status scores (non-normally distributed data). The study was designed with 90% power for detecting 10% differences between modes in the entire series of sixty-one patients and with 82% and 87% power in preoperative and postoperative subgroups, respectively. RESULTS: The mean age was sixty-three years, with thirty-seven male and twenty-four female patients in the study. Forty-seven hips (77%) had osteoarthritis as the primary diagnosis. No significant differences were detected, for any of the five health outcome systems, among the paper, touch screen, and web-based modes, and there were highly significant correlations among all questionnaire modes in the entire series of patients and in the preoperative and postoperative subgroups (p < 0.001). CONCLUSIONS: The scores obtained with the paper, touch screen, and web-based modes of the five questionnaires demonstrated excellent agreement. Thus, touch screen and web-based formats can be used to collect and track patient outcome data. Use of electronic formats of these questionnaires will facilitate a more efficient and reliable data collection process.
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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 | 0.010 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".