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Table 3 Comparison of algorithm, visual inspectio n, and logs in the identification of the window of consecutive days of wear

From: Development and application of an automated algorithm to identify a window of consecutive days of accelerometer wear for large-scale studies

 

Total sample n = 169

Sample with logs n = 74

Visual inspection vs. algorithm N (%)

Visual inspection vs. logs N (%)

Algorithm vs. log N (%)

Same number of days in wear window

 Complete agreement

93 (55.0)

50 (67.6)

39 (52.7)

 Wear window shifted by 1 day in one method

46 (27.2)

10 (13.5)

15 (20.3)

 Average difference in hours of wear

0.3 (more in visual inspection)

5.3 (more in visual inspection)

1.5 (more in algorithm)

 Wear window shifted by ≥2 days in one method

2 (1.2)

0 (0)

1 (1.4)

 Average difference in hours of wear

2.2 (more in algorithm)

N/A

4.5 (more in algorithm)

Total, N (%)

141 (83.4)

60 (81.1)

55 (74.3)

Different number of days in wear window

 Differed by 1 day

25 (14.8)

13 (17.6)

19 (25.7)

Method with more days of wear

Visual inspection

Visual inspection

See footnotea

Differed by ≥2 days

3 (1.8)

1 (1.4)

0 (0)

Method with more days of wear

Visual inspection

Visual inspection

N/A

Total, N (%)

28 (16.6)

14 (18.9)

19 (25.7)

  1. aAlgorithm had more days for 9 (12.2%) signals; log had more days for 10 (13.5%) signals.