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  • Title: Adapted Sojourn Models to Estimate Activity Intensity in Youth: A Suite of Tools.
    Author: Hibbing PR, Ellingson LD, Dixon PM, Welk GJ.
    Journal: Med Sci Sports Exerc; 2018 Apr; 50(4):846-854. PubMed ID: 29135657.
    Abstract:
    UNLABELLED: The challenges of using physical activity data from accelerometers have been compounded with the recent focus on wrist-worn monitors and raw acceleration (as opposed to activity counts). PURPOSE: This study developed and systematically evaluated a suite of new accelerometer processing models for youth. METHODS: Four adaptations of the Sojourn method were developed using data from a laboratory-based experiment in which youth (N = 54) performed structured activity routines. The adaptations corresponded to all possible pairings of hip or wrist attachment with activity counts (AC) or raw acceleration (RA), and they estimated time in sedentary behavior, light activity, and moderate-to-vigorous physical activity. Criterion validity was assessed using direct observation in an independent free-living sample (N = 27). Monitors were worn on both wrists to evaluate the effect of handedness on accuracy, and status quo methods for each configuration were also evaluated as benchmarks for comparison. Tests of classification accuracy (percent accuracy, κ statistics, and sensitivity and specificity) were used to summarize utility. RESULTS: In the development sample, percent accuracy ranged from 68.5% (wrist-worn AC, κ = 0.42) to 71.6% (hip-worn RA, κ = 0.50). Accuracy was lower in the free-living evaluation, with values ranging from 49.3% (hip-worn RA, κ = 0.25) to 56.7% (hip-worn AC, κ = 0.36). Collectively, the suite predicted moderate-to-vigorous physical activity well, with the models averaging 96.5% sensitivity and 67.5% specificity. However, in terms of overall accuracy, the new models performed similarly to the status quo methods. There were no meaningful differences in performance at either wrist. CONCLUSIONS: The new models offered minimal improvements over existing methods, but a major advantage is that further tuning of the models is possible with continued research.
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