Actigraph data are reliable, with functional reliability increasing with aggregation.

Motion sensor devices such as actigraphs are increasingly used in studies that seek to obtain an objective assessment of activity level. They have many advantages, and are useful additions to research in fields such as sleep assessment, drug efficacy, behavior genetics, and obesity. However, questions still remain over the reliability of data collected using actigraphic assessment. We aimed to apply generalizability theory to actigraph data collected on a large, general-population sample in middle childhood, during 8 cognitive tasks across two body loci, and to examine reliability coefficients on actigraph data aggregated across different numbers of tasks and different numbers of attachment loci. Our analyses show that aggregation greatly increases actigraph data reliability, with reliability coefficients on data collected at one body locus during 1 task (.29) being much lower than that aggregated across data collected on two body loci and during 8 tasks (.66). Further increases in reliability coefficients by aggregating across four loci and 12 tasks were estimated to be modest in prospective analyses, indicating an optimum trade-off between data collection and reliability estimates. We also examined possible instrumental effects on actigraph data and found these to be nonsignificant, further supporting the reliability and validity of actigraph data as a method of activity level assessment.