Feasibility testing of smart tablet questionnaires compared to paper questionnaires in an amputee rehabilitation clinic
Bibliographic record
Abstract
BACKGROUND: Capturing the variability that exists among patients attending an amputee clinic using standardized paper-based questionnaires is time-consuming and may not be practical for routine clinical use. Electronic questionnaires are a potential solution; however, the benefits are dependent on the feasibility and acceptance of this mode of data collection among patients. OBJECTIVE: To determine the feasibility and patient preference/comfort in using a tablet-based questionnaire for data collection in an outpatient amputee rehabilitation clinic compared to a traditional paper-based questionnaire. STUDY DESIGN: Observational study. METHODS: In all, 48 patients with major extremity amputations completed both tablet and paper questionnaires related to their amputation and prosthetic use. Both trials were timed; patients then completed a semi-structured questionnaire about their experience. RESULTS: In all, 20.5% of patients needed hands-on assistance completing the paper questionnaire compared to 20.8% for the tablet. The majority of participants (52.1%) indicated a preference for the tablet questionnaire; 64.6% of patients felt the tablet collected a more complete and accurate representation of their status and needs. In all, 70.8% of participants described themselves as comfortable using the tablet. CONCLUSION: Despite comorbidities, patients with amputations demonstrated excellent acceptance of the electronic tablet-based questionnaire. Tablet questionnaires have significant potential advantages over paper questionnaires and should be further explored. Clinical relevance A custom electronic questionnaire was found to be beneficial for routine clinic use and was well received by patients in an amputee rehabilitation clinic. Development of such questionnaires can provide an efficient mechanism to collect meaningful data that can be used for individual patient care and program quality improvement initiatives.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".