0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessThis article describes four key quality control and data reduction issues that researchers should consider when using accelerometry to measure physical activity: monitor reliability, spurious data, monitor wear time, and number of valid days required for analysis.Exploratory analyses were conducted on an unweighted subsample (n=987) of the accelerometry data from the Canadian Health Measures Survey. Participants were asked to wear an accelerometer for 7 consecutive days. Calibration, reliability, biological plausibility and compliance issues were explored using descriptive statistics.Ongoing calibration is an effective method for identifying malfunctioning accelerometers. The percentage of files deemed viable for analysis depends on participant compliance, the allowable interruption period chosen and the minimum wear-time-per-day criterion. A 60-minute allowable interruption period and 10-hours-per-day wear time criteria resulted in 95% of the subsample having at least 1 valid day, and 84% having at least 4 valid days.Before the derivation of physical activity outcomes, accelerometry data should undergo standardized quality control and data reduction procedures to prevent mis-representation of the results. Incomplete accelerometry data should be handled carefully, and strategies to improve compliance in the field are warranted.
Rachel C. Colley, Sarah Connor Gorber, Mark S. Tremblay (2010). Quality control and data reduction procedures for accelerometry-derived measures of physical activity.. PubMed, 21(1), pp. 63-9
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2010
Authors
3
Datasets
0
Total Files
0
Language
English
Journal
PubMed
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access