Users’ Satisfaction with an Assistive Device and Quality of Life: A preliminary study on lower limb prosthetics
Bibliographic record
Abstract
Quality of life refers to the individual perception of each person regarding their objectives, expectations and achievements, according to their stage of life and contexts of material, physical, emotional and social conditions. Assistive Technology devices can improve the individual’s performance in many domains related to daily activities, which are linked to independence and social participation. The user’s satisfaction is an important factor for the successful use of assistive devices. This study aimed to analyze the correlation between the quality of life and the users’ satisfaction with their lower limb prostheses. Eleven individuals aged between 20 and 54 years participated in the study. All participants were interviewed by telephone responding to the Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0) and the World Health Organization Quality of Life (WHOQOL-BREF), both in its Brazilian version. The highest frequency of positive responses (“very satisfied” or “quite satisfied”) were found in the professional service (90%), efficacy (81.8%) and weight (81.8%), while durability (27.3%), repairs and technical assistance (27.3%) and follow-up service (27.3%) were the factors with highest frequencies of dissatisfaction (responses of “not satisfied at all” or “not very satisfied”) in the QUEST 2.0. Participants indicated comfort (27.3%), durability (21.2%) and safety (21.2%) as the most important aspects for satisfaction with their prostheses. When it comes to the quality of life in the WHOQOL-BREF, the mean of the participants' scores was 74.2%, with similar scores for the domains of physical health (75.6±12.8), psychological (80.7±9.4), social relationships (74.2±15.1) and environment (66.5±16.2). This study contributed to the comprehension of the main factors of the assistive device and service that influence the satisfaction of prostheses’ users, and the correlation with their quality of life. Improvements are still needed in some aspects in lower limb prostheses in order to better meet the users’ needs.
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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 | 0.000 |
| 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 | 0.001 |
| 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".