Everyday technology use among people with Parkinson’s disease
Bibliographic record
Abstract
Objectives To explore the relevance of and ability to use everyday technology (ET) among people with Parkinson’s Disease (PD) and to explore associations between ET use and global cognition and motor ability.Materials and Methods Cross-sectional data was collected from 34 people with PD using the Short Everyday Technology Use Questionnaire+ (S-ETUQ+), the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale and the Montreal Cognitive Assessment (MoCA).Results Out of 41 ETs in the S-ETUQ+, the mean number perceived as relevant was 27.5 (min-max 19–35, SD 3.6). A good ability to use ET was reported where many ETs had a challenge measure below participants’ ability to use them. A strong positive correlation between the ability to use ET and global cognition (MoCA) (r = .676, p = <0.01) was shown.Conclusions ET use has become integrated into everyday life and is important for participation. This study showed a high relevance of and good ability to use ET and a correlation between ET use and global cognition among people with mild-moderate PD. Evaluation and support to use ET in PD are important for maintaining independence and participation, especially among those with cognitive decline.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".