Abstract
BackgroundMeasuring physical activity and sedentary behavior accurately remains a challenge. When describing the uncertainty of mean values or when making group comparisons, minimising Standard Error of the Mean (SEM) is important. The sample size and the number of repeated observations within each subject influence the size of the SEM. In this study we have investigated how different combinations of sample sizes and repeated observations influence the magnitude of the SEM.MethodsA convenience sample were asked to wear an accelerometer for 28 consecutive days. Based on the within and between subject variances the SEM for the different combinations of sample sizes and number of monitored days was calculated.ResultsFifty subjects (67% women, mean ± SD age 41 ± 19 years) were included. The analyses showed, independent of which intensity level of physical activity or how measurement protocol was designed, that the largest reductions in SEM was seen as the sample size were increased. The same magnitude in reductions to SEM was not seen for increasing the number of repeated measurement days within each subject.ConclusionThe most effective way of reducing the SEM is to have a large sample size rather than a long observation period within each individual. Even though the importance of reducing the SEM to increase the power of detecting differences between groups is well-known it is seldom considered when developing appropriate protocols for accelerometer based research. Therefore the results presented herein serves to highlight this fact and have the potential to stimulate debate and challenge current best practice recommendations of accelerometer based physical activity research.
Highlights
Measuring physical activity and sedentary behavior accurately remains a challenge
The participants were approached by e-mail. They were sent information regarding the nature of the study and what was expected of them. If they were interested in participating in the study they were asked to reply to the email
None of the observed differences between the datasets in the mean level of physical activity at the different intensities was significantly different from each other (ANOVA, p > 0.05)
Summary
Measuring physical activity and sedentary behavior accurately remains a challenge. When describing the uncertainty of mean values or when making group comparisons, minimising Standard Error of the Mean (SEM) is important. One of the most important factors included in such a protocol is the number of days that a subject should be monitored as this cannot be changed afterwards. This is central since the number of repeated observations will influence on the measurement error and in extension on the outcome. [16,17,18,19]) These studies show relatively consistently that 3–5 days of repeated observations is sufficient to achieve reliability coefficients of around 0.7, and have served as a basis for current guides on best practices in accelerometer based physical activity research which recommend a 7-day measurement period to have some margin to compensate for days during which the accelerometer was not worn [1,2,3,4]. In nutritional epidemiology, which shares many of the measurement problems with physical activity research, four levels of measurement (Fig. 1) relating to different types of research questions have been described [21]
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