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Worldviews Evid Based Nurs
Assistant Professor, Nutrition Program Coordinator, School of Arts and Sciences, Department of Natural Sciences, Lebanese American University, Byblos, Lebanon.
Published: June 2016
Background: The well-documented increases in obesity and unhealthy dietary practices substantiate the need for evidence-based tools that can help people improve their dietary habits. The current spread of mobile phone-embedded cameras offers new opportunities for recording food intake. Moreover, the act of taking pictures of food consumed may enhance visual consciousness of food choice and quantity. The present study aimed to assess the effect of using cell phone pictures to record food intake on energy intake and food choice in college students. The effectiveness and acceptability of cell phone picture-based diet recording also was assessed.
Methods: A repeated measures crossover design was used. One group of participants entered their food intake online during 3 days based on their memory, although a second group recorded their food intake using cell phone pictures as their reference. Participants then crossed over to complete 3 more days of diet recording using the alternate method. Focus groups were conducted to obtain feedback on the effectiveness and acceptability of cell phone picture-based diet recording.
Results: Intake of meat and vegetable servings were significantly higher in the memory period compared with the cell phone period, regardless of the order. Results from the focus group indicated a positive attitude toward the use of cell phone pictures in recording food intake and an increased awareness of food choice and portion size.
Linking Evidence To Action: Cell phone pictures may be an easy, relevant, and accessible method of diet self-monitoring when aiming at dietary changes. Future trials should combine this technique with healthy eating education.
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http://dx.doi.org/10.1111/wvn.12123 | DOI Listing |
Sci Rep
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Department of Biological Sciences, University of Africa, Toru-Orua, Bayelsa State, Nigeria.
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View Article and Find Full Text PDFJAMA Netw Open
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School of Nursing, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
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June 2025
Department of Community Health Sciences, University of Manitoba, Canada.
Advances in modeling the spread of infectious diseases have allowed modellers to relax the homogeneous mixing assumption of traditional compartmental models. The recently introduced synthetic network model, which is an SIRS type model based on a non-linear transmission rate, effectively decouples the underlying population network structure from the epidemiological parameters of disease, and has been shown to produce superior fits to multi-wave epidemics. However, inference from case counts alone is generally problematic due to the partial unidentifiability between probability of person to person transmission and the average number of contacts per individual.
View Article and Find Full Text PDFBMC Infect Dis
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Pharmaceutical Sciences, University of Nigeria, Nsukka, Nigeria.
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