Health-Related Quality of Life and Prosthetic Satisfaction in Below-Knee Amputees: A Cross-Sectional Study
Bibliographic record
Abstract
A BSTRACT Background: Global patients are the focus of the bulk of studies looking at patient satisfaction and social integration. The major objective is to integrate those people into society because the prevalence of amputation is increasing in India as well. Also, these researchers include a variety of illnesses, such as renal tubular acidosis (RTA), diabetes, vascular disorders, spinal cord damage, and stroke, in their investigations. There are not many studies conducted in India that only consider urban populations. The purpose of the study was to examine factors influencing the quality of life (QOL) and post-acceptance and contentment with one’s body image in patients with unilateral knee amputations. Materials and Methods: A random sampling method was performed to select the subjects. The records of the participants of the study were retrieved from the Chandigarh Welfare Trust Prosthetic Camp, Chandigarh, India, to obtain information on relevant demographic data. Patients were given both questionnaires, that is, Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0) and Community Integration Questionnaire (CIQ), and told about everything, and then, patients gave scores to themselves according to the activities and satisfaction they had with the prosthetic use. Spearman’s correlation test (two-tailed) was used to find the correlation between QUEST 2.0 and CIQ. The correlation between QUEST 2.0 and integration into productive activities (IPA) was also analyzed. A significant level of P ≤ 0.01 was fixed. Result: The correlation between QUEST 2.0 and CIQ is significantly strong or good (r = 1.00, P < 0.001). Home integration and social integration had a high or strong correlation with the QUEST assistive device domain (r = 0.43, P < 0.001) and each other (r = 0.785, P < 0.001). QUEST and productive activities are moderately associated (r = 0.57, P < 0.001). The service sub-domain of QUEST 2.0’s home integration component showed a substantially positive connection (r = 0.38, P < 0.001). It demonstrates that social integration has an overall positive relationship (r = 0.59, P < 0.001) with other factors. Conclusion: In the social life of those who have lost or are missing limbs, prostheses have a social function. By hiding their usage, individuals were able to avoid social stigmatization, which facilitated their social integration and lessened the emotional issues associated with such a disability.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".