Measuring the psychosocial impact of mobility assistive products with elderly people: Findings from Italian surveys
Bibliographic record
Abstract
Purpose. In 2014 and 2015 the authors surveyed two samples of 79 and 65 users who had obtained mobility assistive devices from the National Health Service in Italy. The first sample was composed of powered wheelchair users, 71% of them being over 65 years old [1]. The second sample included users of seven different mobility assistive devices: powered wheelchairs, tilting manual wheelchairs, manual wheelchairs with seating system, tracked and wheeled stair-climbing devices, trans-femoral and trans-tibial lower limb prostheses); 42% of them were over 65 years old. Follow-up interviews were conducted in order to collect information about usage, effectiveness, usefulness and economic impact of their assistive device. Method. The instruments used in the interviews, which were conducted at the users’ homes, included an introductory questionnaire and other widely known assessment instruments, one of them being the PIADS (Psychosocial Impact of Assistive Devices Scale) [2], [3]. Results & Discussion. In both samples elderly people (those aged 65 or more) answered the PIADS items in greater numbers than those under 65. Some difficulties in answering the PIADS questions were noticed, which seem to be related to the kind of assistive device rather than to the age of the interviewed person. In the 2015 survey the number of subjects who did not answer the whole PIADS questionnaire was greater among users of assistive devices maneuvered by caregivers (tilting wheelchairs, manual wheelchairs with seating system, tracked and wheeled stair-climbing devices) than among users of devices providing full independence (powered wheelchairs, trans-femoral and trans-tibial lower limb prostheses). Another noteworthy finding is that, although all average scores obtained in the PIADS subscales were positive (about +1 in both samples), for elderly people the scores were a bit lower than those obtained from younger users. This does not occur for electronic wheelchairs users, whose scores don't differ in relation to the age of the interviewed subjects. Building on experience gained during these and previous studies, in the next two years a battery of outcome measurement instruments will be prepared to be used in clinical practice. References. 1. Salatino C, Andrich R, Converti RM, Saruggia M. An observational study of powered wheelchair pro-vision in Italy. Assistive technology 28(1) (2015) 41-52. 2. Andrich R, Pedroni F, Vanni G. Psychosocial Impact of Assistive Devices: Italian localization of the PIADS instrument. In: Craddock G et al (eds), Assistive technology: Shaping the future (AAATE 2003). Amsterdam: IOS Press (2003) 917–921. 3. Jutai J, Day H. Psychosocial Impact of Assistive Devices Scale (PIADS). Technology and Disability 14(3) (2002) 107–111.
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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 | 0.002 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".