Powered Tilt/Recline Systems: Why and How Are They Used?
Bibliographic record
Abstract
Prolonged static sitting can lead to discomfort, pain, pressure sores, spinal curvatures, and loss of functional independence. In order to counteract these harmful effects, adjustable tilt and/or recline systems are often prescribed. Considering the current context of assistive technology service delivery and budget cuts, it is essential to have a better knowledge of the use of these technical aids and user's satisfaction with them. The purpose of this study was to characterize the use of powered tilt and recline systems. A questionnaire was developed for this purpose, and 40 subjects were interviewed at home. They were asked to identify, from a list of 25 objectives, the reasons for which they used their repositioning system and to rank these reasons in order of importance. For each objective, they were also asked to identify the frequency and range of use as well as their satisfaction level with their system. Results revealed that 97.5% of the subjects were using their powered tilt and recline system everyday, and their satisfaction was high. The main objectives for using this type of assistive technology were to increase comfort and to promote rest. Although mainly descriptive, results are of clinical relevance and can be helpful when selecting wheelchairs.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".