The development and evaluation of a novel computer program to assess previous-day dietary and physical activity behaviours in school children: The Synchronised Nutrition and Activity Program TM (SNAP TM )

• Published in: British journal of nutrition 2008-06, Vol.99 (6), p.1266-1274
• Main Authors: Moore, Helen J., Ells, Louisa J., McLure, Sally A., Crooks, Sean, Cumbor, David, Summerbell, Carolyn D., Batterham, Alan M.
• Format: Article
• Language: English
• ISSN: 0007-1145; 1475-2662
• DOI: 10.1017/S0007114507862428

Self-report recall questionnaires used to measure physical activity and dietary intake in children can be labour intensive and monotonous and tend to focus on either dietary intake or physical activity. The web-based software, Synchronised Nutrition and Activity Program TM (SNAP TM ), was developed to produce a novel, simple, quick and engaging method of assessing energy balance-related behaviours at a population level, combining principles from new and existing 24 h recall methodologies, set within a user-friendly interface. Dietary intake was measured using counts for twenty-one food groups and physical activity levels were measured in min of moderate to vigorous physical activity (MVPA). A combination of the mean difference between methods, type II regression and non-parametric limits of agreement techniques were used to examine the accuracy and precision of SNAP TM . Method comparison analyses demonstrated a good agreement for both dietary intake and physical activity behaviours. For dietary variables, accuracy of SNAP TM (mean difference) was within ± 1 count for the majority of food groups. The proportion of the sample with between-method agreement within ± 1 count ranged from 0·40 to 0·99. For min of MVPA, there was no substantial fixed or proportional bias, and a mean difference between methods (SNAP TM – accelerometry) of − 9 min. SNAP TM provides a quick, accurate, low-burden, cost-effective and engaging method of assessing energy balance behaviours at a population level. Tools such as SNAP TM , which exploit the popularity, privacy and engagement of the computer interface, and linkages with other datasets, could make a substantial contribution to future public health monitoring and research.