Toward a comprehensive evaluation of the impact of electronic aids to daily living: evaluation of consumer satisfaction
Bibliographic record
Abstract
PURPOSE: It is generally accepted that electronic aids to daily living (EADLs) play an important role in the lives of many people with severe disabilities by providing the means to access and control devices for daily living activities. Despite this, little proof exists to support the contention that consumers are satisfied with relevant aspects of these assistive devices. The purpose of this study was to explore consumer satisfaction with EADLs and investigate the value that people with degenerative neuromuscular conditions place on these technologies. METHOD: Interviews were conducted with 40 EADL users and non-users to compare their views about these devices and their daily life experiences. Users were interviewed twice, six months apart, to establish the stability of their views and experiences with EADLs. The Functional Independence Measure (FIM instrument), the personal profile and Quebec User Evaluation of Satisfaction with assistive Technology (QUEST) were administered to determine functional levels of participants, gather personal data pertinent to the study of device utility and explore user satisfaction with EADLs. RESULTS: Results suggest that overall consumers were quite satisfied with their EADLs and that this was relatively stable over time. However, some consumers expressed concerns regarding the cost of these technologies and their associated services. Both users and non-users rated EADLs similarly in relation to relative degree of importance ascribed to them. CONCLUSIONS: Combining the QUEST with outcome measurement tools that explore other important dimensions such as the effect on quality of life and psychosocial impact will help service providers to justify the costs associated with the prescription of sophisticated, costly assistive devices such as EADLs.
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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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".