뇌졸중 환자의 편의성과 안전성을 고려한 목욕의자 개발 및 평가
Bibliographic record
Abstract
Objective: The purpose of this study was to develop a bath chair and verify its effectiveness in terms of the convenience and safety of stroke patients. Methods: The subjects were 20 stroke patients admitted to a rehabilitation hospital in a metropolitan city. As a research tool, a bath chair prototype was developed based on a Delphi survey and subjective opinions from the subjects. A Rapid Entire Body Assessment (REBA), questionnaire (usability assessment and open questionnaire), and Korean version of Quebec User Evaluation of Satisfaction Assistive Technology (K-QUEST 2.0) were used as assessment tools. As a statistical analysis, a t-test was conducted before and after applying the bath chair prototype. Results: As the results from before and after using the bath chair prototype indicate, the REBA levels of action regarding the use of bath ware and a showerhead are lowered from ‘high’ to ‘normal’ and ‘low,’ respectively. In addition, in the usability test, convenience was considered to be ‘proper’ and seven other items expressed values of ‘normal’. In addition, the prototype was deemed ‘satisfactory’ in terms of effectiveness, whereas seven other indicators showed a level of ‘normal’. Conclusion: The bath chair developed in this study is expected to not only be effective in improving the convenience and safety of the bathing activity of stroke patients but also to serve as an assistive device to reduce their physical burden.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".