Older adults’ satisfaction of wearing consumer-level activity monitors
Bibliographic record
Abstract
There is a growing body of evidence to suggest that consumer-level activity monitors are a valid means of measuring physical activity in older adults. Understanding whether older adults are satisfied with wearing these activity monitors is an important step to ensuring that devices can be successfully implemented in clinical and research settings. Twenty-five older adults (mean age = 72.5 years, standard deviation = 4.9) wore two consumer-level activity monitors (Misfit Shine and Fitbit Charge HR) for seven consecutive days. After the week, participants were asked for their views and satisfaction of wearing each device, measured in part by the Quebec User Evaluation of Satisfaction with assistive Technology. Participants were generally satisfied with most aspects of the devices, though they were significantly more satisfied with the Misfit Shine. Participants were critical about their ability to adjust the fit of both the Misfit Shine and Fitbit Charge HR. Interestingly, the perceived satisfaction with the device was not associated with participants' consideration of wearing the device again. Future research needs to consider whether the design of consumer-level activity monitors are best suited for 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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".