The effect of 3D printed assistive technology intervention on the older adults’ independence in activities of daily living: A single-group intervention study
Bibliographic record
Abstract
There is need for innovative approaches in the production of assistive devices. This study aimed to examine the effects of a Three-Dimensional (3D) Printed Assistive Technology Intervention. Twelve older adults (mean age of 67.83 ± 2.72 years) participated in the study. Assistive devices were designed using a 3D printer. The participants completed the Canadian Occupational Performance Measure (COPM), the Functional Independence Measure (FIM), and the Lawton-Brody IADL scale. Also they completed the Visual Analog Scale (VAS) to evaluate their satisfaction with the 3D printed assistive device. The participants’ mean satisfaction score with the assistive devices was found to be 7.00 ± 1.12. After the intervention, significant improvements were observed in the COPM performance subscale (p = 0.016), the FIM motor subscale (p = 0.012), the FIM total score (p = 0.018), and the Lawton-Brody IADL Index (p = 0.024). However, no significant changes were detected in the COPM satisfaction subscale (p = 0.094) or the FIM cognitive subscale (p = 0.069). This study suggest that economically feasible and easily accessible 3D printed assistive devices may serve as an effective alternative to enhance the occupational performance and independence of older adults.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".