This web app enables researchers to upload GPAQ values and download predicted
values which are calibrated to more accurately represent what would have been
recorded via ActiGraph. Data must be uploaded as a text file; various delimiters
may be used. Any rows with missing values will be removed. Visualizations
are provided, and the calibrated values can be downloaded as part of the original
The calibration model was constructed using data collected by the Active Ottumwa
project (https://www.public-health.uiowa.edu/prc/active-ottumwa/), a community-based
research project by the University of Iowa Prevention Research Center, funded by the
Centers for Disease Control and Prevention. A number of linear and non-linear
relationships between GPAQ scores and corresponding ActiGraph data were investigated.
AIC was used to select the best model from a training set, and the resulting calibration
model was validated on a testing set from the same population as well as a testing set
on a different population. Please see the following paper for more details
Metcalf, K., Baquero, B., Laroche, H., Coronado Garcia, M., Francis, S., Janz, K., and Sewell,
D.K. (2017+),"Calibration of the Global Physical Activity Questionnaire to Accelerometry
Measured Physical Activity and Sedentary Behavior in a Random Sample of Rural Iowans,"
If this web app is used, we request that the above work be cited.
How the App Works
1. Use the "Upload File" tab to upload your data in text format. Comma, tab, or
semicolon delimited files accepted. Your uploaded data will be shown for you to confirm
that it has been read in correctly.
2. The "Predictions" tab allows users to download the calibrated data. First, use the drop
down menus to match the required variables. If you have ActiGraph data with which you
would like to compare the predictions, select the appropriate box. To download the
predictions, select the appropriate button at the bottom of the page.
3. Visualizations are also provided on the "Predictions" tab. The first plot is a
Bland-Altman plot, giving the GPAQ values minus the calibrated values vs. the average
of the GPAQ and calibrated values. The second plot (only when ActiGraph data is present)
shows the ActiGraph values vs. both the GPAQ and calibrated values. Each observation
thus corresponds to a pair of points which are connected by a gray segment. The diagonal
black line is given by y=x, and is where we desire the calibrated values to fall.
4. If ActiGraph data is present, ratios of the mean squared predictive errors (MSPE) are given,
where values less than one imply the calibrated values contain less error than the GPAQ
values. For example, if you get a MSPE ratio of 0.12 for the sedentary physical activity your can
say that calibrated sedentary data reduced the error of your sedentary GPAQ data by 88%.
This research was supported by Cooperative Agreement Number 1-U48DP001902-01 from the Centers
for Disease Control and Prevention. The findings and conclusions in this report are those of the
authors and do not necessarily represent the official position of the Centers for Disease Control
Any questions or problems should be sent to Daniel Sewell at daniel-sewell AT uiowa DOT edu
Upload the file that contains the age and self-reported
values of sedentary, moderate, and vigorous physical activity
of each participant. Once your file is uploaded, the first 6
participants will be displayed in the white space next to the
In the following drop down menus please select the name of the column that corresponds
with the data values. Example: if your moderate physical activity column is named GPAQ_MOD
then select that name in the drop down menu asking for the GPAQ Moderate Data Column.
A common error that appears in the app is
'ERROR: non-numeric argument to binary operator'. When this error appears, double
check that the column names you selected in the drop down menus does not correspond
with date data.