Assessment of the MyWellness Key accelerometer in people with type 2 diabetes
Bibliographic record
Abstract
Accelerometers are designed to measure physical activity (PA) objectively. The MyWellness Key (MWK) accelerometer has been validated primarily in younger, normal-weight populations. The aims of this study were to examine the accuracy of the MWK against directly measured lab-based exercise and free-living PA in people with type 2 diabetes, many of whom are older and overweight or obese. Thirty-five participants with type 2 diabetes completed the protocol, which included a laboratory-based session and a free-living phase. In the laboratory visit, participants completed a structured treadmill protocol wearing MWKs on each hip (all subjects) and bra cup (women only). The speed where each MWK switched from recording light- to moderate-intensity activity was determined for each MWK worn. In the free-living phase, participants wore the MWK for all waking hours for 2 weeks, and recorded exercise in PA diaries immediately after each exercise session. The mean cut-points between low ("Free") and moderate ("Play") intensity for the right and left waist-worn MWKs were 4.1 ± 0.5 km/h and 5.0 ± 0.9 km/h for the bra-mounted MWK; ideal cut-point would be 4.0 km/h. In the free-living phase, the Spearman correlation between PA according to PA diary and the waist-worn MWK was 0.81 (95% confidence interval (CI): 0.76, 0.85; P < 0.001), but only 0.66 (95% CI: 0.53, 0.77; P < 0.001) when on the bra. In conclusion, the waist-worn MWK measured PA volume accurately, and was acceptably accurate at discriminating between low- and moderate-intensity PA in people with type 2 diabetes. The MWK underestimated PA volume and intensity when worn on a bra.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".