Computer-Related Assistive Technology: Satisfaction and Experiences Among Users With Disabilities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Many people with disabilities use assistive technology devices (ATDs) for computer access. The specific focus of this exploratory study was (a) to assess the experiences, opinions, and satisfaction levels of 24 individuals with disabilities using computer-related ATDs; (b) to investigate their awareness of health risk factors related to computer usage; and (c) to examine the psychosocial impact of computer-related ATDs on users. Data were collected via telephone interviews with 24 individuals with physical disabilities who had experience using one or more ATDs. The Quebec User Evaluation with Assistive Technology instrument was used to evaluate users' satisfaction with ATDs in a number of dimensions, including their physical attributes. The Psychosocial Impact of Assistive Devices Scale measured the psychosocial impact (i.e., independence, competence, and adequacy) of an ATD on users. Additional questions were posed to gather information about user's opinions and experiences. Training appeared to be an important component for ATD users, many of whom preferred a setting to try out devices rather than group or individual training. Respondents with visual impairments revealed a higher level of adaptability versus those without visual impairments (p = .001). Additional research is needed to develop specific survey items focused on users of computer-related ATDs and the evaluation of the psychosocial impact of ATDs on computer users.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 it