Does satisfaction with the manual wheelchair have an impact on the quality of life in spinal cord injury?
Bibliographic record
Abstract
Background: Customised wheelchairs are integral component for comprehensive rehabilitation and community integration for spinal cord injury (SCI) survivors, while inappropriate wheelchairs negatively impact their functional independence, mobility and quality of life (QOL). Keeping this in mind, this study aimed to determine the effects of manual wheelchair users' satisfaction on QOL in SCI. Methods: This cross-sectional study, which included 112 SCI, was conducted at the Paraplegic Centre, Hayatabad, Peshawar, over a period of 6 months using "Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST)" and “World Health Organisation Quality of Life (WHOQOL-BREF)” as study tools. Results: QUEST showed a significant positive correlation with physical health (rs = 0.375; p< 0.001), social relationships (rs=0.234; p = 0.013), and environmental health (rs = 0.462; p<0.001) of QOL except psychological health, and similarly, overall health and overall QOL was positively impacted. Furthermore, overall health and environmental, social relationships, and physical domains of QOL were statistically significantly impacted by the QUEST device and service aspects. Conclusion: A moderate level of satisfaction among participants for both devices and services was observed, which also impacts their physical, environmental, and social domains of QOL. Therefore, steps from the key stakeholders are required to provide satisfactory appropriate wheelchairs to patients so their QOL can be improved.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".