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United States Department of Agriculture

Agricultural Research Service

Title: BENEFITS OF AGGRESSIVE ACCELEROMETRY DATA COLLECTION?

Authors
item Nelson, Kimberly - BAYLOR COL MED
item Jago, Russell - UNIV BRISTOL
item Missaghian, Mariam - BAYLOR COL MED
item Baranowski, Thomas
item Baranowski, Janice

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: July 13, 2006
Publication Date: July 13, 2006
Citation: Nelson, K., Jago, R., Missaghian, M., Baranowski, T., Baranowski, J. 2006. Benefits of aggressive accelerometry data collection? [abstract]. Fifth Conference of the International Society of Behavioral Nutrition and Physical Activity, July 13-16, 2006, Boston, Massachusetts. p. 252.

Technical Abstract: Purpose: To examine whether the completeness of accelerometer data obtained from elementary and high school students is enhanced when an aggressive data collection approach is employed. Methods: Participants were 149 elementary school (9.9+/-0.4 yrs) and 153 high school (17.7+/-0.4 yrs) students. Participants were asked to wear an accelerometer for a 5-day period. The importance of wearing the monitor for 5 full days (with at least 800 minutes of recorded data per day) was explained at distribution. Some participants who did not have five days of complete data were asked to re-wear the monitor. Analyses concerned completeness of data. Results: Complete data were received from 200 of 302 (66%) participants. The majority of missing days were from Saturday and Sunday (52%). Of the 102 children who did not have complete data, 51 were asked to re-wear their monitor, with 24 (47%) subsequently providing complete data. The number of participants meeting requirements therefore increased from 200 to 224 (12% increase). The number of days with complete data increased from 1268 to 1402 (11% increase). There was considerable variability in the time and effort necessary to obtain complete data. Conclusions: An aggressive approach to accelerometry data collection appears to obtain more complete data with no evidence of demographic bias. Whether the effort is worth the increase in data needs to be more thoroughly addressed. An algorithm identifying children likely to be successful with aggressive collection at low cost will be proposed.

Last Modified: 9/1/2014
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