MAPPING SEDENTARY BEHAVIOUR USING WEARABLE DEVICES AND DIARIES IN OLDER ADULTS WITH FRAILTY: A FEASIBILITY STUDY
Bibliographic record
Abstract
Abstract Older adults with frailty are sedentary. Prior interventions to reduce sedentary time in older adults have not been successful as there is little research about context (posture, location, purpose, social environment). There is limited evidence on feasible measures to assess context of sedentary behaviour in older adults. Our aim was to determine feasibility of measuring context of sedentary behaviour in older adults with frailty using objective and self-report measures. We defined “feasibility process” using recruitment (20 participants within two-months), retention (85%), and refusal (20%) rates and “feasibility resource” if the measures capture context and can be linked (e.g., sitting-kitchen-eating-alone), and are all participants willing to use the measures. Context was assessed using a wearable sensor for posture, indoor positioning system [IPS] for location, and electronic or hard-copy diary for purpose and social-context over three days in winter and spring. We approached 80 individuals, and 58 expressed interest; of the 58, 37 did not enroll due to lack of interest or medical mistrust (64% refusal). We recruited 21 older adults (72±7.3 years, 13 females, 13 frail) within two months and experienced two dropouts (90% retention). The measures captured one domain of context, but the hard copy was not completed with detail making it challenging to link with the other devices. Not all participants were willing to use the wearable devices or electronic diary; but we linked the measures of those who did. Future studies will need to determine the most feasible and valid method to assess the context of sedentary behaviour.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".