Actical Accelerometer Sedentary Activity Thresholds for Adults
Bibliographic record
Abstract
BACKGROUND: Actical accelerometer thresholds have been derived to enable objective measurement of time spent performing sedentary activity in children and adolescents, but not adults. Thus, the purpose of this study was to determine Actical accelerometer sedentary activity thresholds for adults. METHODS: Data were available from 3187 participants aged 6 to 79 years from a preliminary partial dataset of the Canadian Health Measures Survey, who wore an Actical for 7 days. Step count data were used to evaluate the use of 50, 100, and 800 counts per min (cpm) as sedentary activity thresholds. Minutes when no steps were recorded were considered minutes of sedentary activity. RESULTS: The use of higher cpm thresholds resulted in a greater percentage of sedentary minutes being correctly classified as sedentary. The percentage of minutes that were incorrectly classified as sedentary was substantially higher when using a threshold of 800 cpm compared with 50 or 100 cpm. Results were similar for children, adolescents, and adults. CONCLUSIONS: These findings suggest that a threshold of 100 cpm is appropriate for classifying sedentary activity of adults when using the Actical. As such, wear periods with minutes registering less than 100 cpm would be classified as time spent performing sedentary activity.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".