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      Smart Device-Based Notifications to Promote Healthy Behavior Related to Childhood Obesity and Overweight

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          Abstract

          Obesity is one of the most serious public health challenges of the 21st century and it is a threat to the life of people according to World Health Organization. In this scenario, family environment is important to establish healthy habits which help to reduce levels of obesity and control overweight in children. However, little efforts have been focused on helping parents to promote and have healthy lifestyles. In this paper, we present two smart device-based notification prototypes to promote healthy behavior with the aim of avoiding childhood overweight and obesity. The first prototype helps parents to follow a healthy snack routine, based on a nutritionist suggestion. Using a fridge magnet, parents receive graphical reminders of which snacks they and their children should consume. The second prototype provides a graphical reminder that prevents parents from forgetting the required equipment to practice sports. Prototypes were evaluated by nine nutritionists from three countries (Costa Rica, Mexico and Spain). Evaluations were based on anticipation of use and the ergonomics of human–system interaction according to the ISO 9241-210. Results show that the system is considered useful. Even though they might not be willing to use the system, they would recommend it to their patients. Based on the ISO 9241-210 the best ranked features were the system’s comprehensibility, the perceived effectiveness and clarity. The worst ranked features were the system’s suitability for learning and its discriminability.

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          Most cited references 34

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          Parent-child feeding strategies and their relationships to child eating and weight status.

          Parental feeding styles may promote overeating or overweight in children. A comprehensive literature review was undertaken to summarize the associations between parental feeding styles and child eating and weight status. Twenty-two studies were identified. We systematically coded study attributes and outcomes and tested for patterns of association. Nineteen studies (86%) reported at least one significant association between parental feeding style and child outcome, although study methodology and results varied considerably. Studies measuring parental feeding restriction, as opposed to general feeding control or another feeding domain, were more likely to report positive associations with child eating and weight status. Certain associations differed by gender and by outcome measurement (e.g., rate of eating as opposed to total energy intake). Parental feeding restriction, but no other feeding domain, was associated with increased child eating and weight status. Longitudinal studies are needed to test underlying causal pathways, including bidirectional causal models, and to substantiate findings in the presence of other obesity risk factors.
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            Myths, presumptions, and facts about obesity.

            Many beliefs about obesity persist in the absence of supporting scientific evidence (presumptions); some persist despite contradicting evidence (myths). The promulgation of unsupported beliefs may yield poorly informed policy decisions, inaccurate clinical and public health recommendations, and an unproductive allocation of research resources and may divert attention away from useful, evidence-based information. Using Internet searches of popular media and scientific literature, we identified, reviewed, and classified obesity-related myths and presumptions. We also examined facts that are well supported by evidence, with an emphasis on those that have practical implications for public health, policy, or clinical recommendations. We identified seven obesity-related myths concerning the effects of small sustained increases in energy intake or expenditure, establishment of realistic goals for weight loss, rapid weight loss, weight-loss readiness, physical-education classes, breast-feeding, and energy expended during sexual activity. We also identified six presumptions about the purported effects of regularly eating breakfast, early childhood experiences, eating fruits and vegetables, weight cycling, snacking, and the built (i.e., human-made) environment. Finally, we identified nine evidence-supported facts that are relevant for the formulation of sound public health, policy, or clinical recommendations. False and scientifically unsupported beliefs about obesity are pervasive in both scientific literature and the popular press. (Funded by the National Institutes of Health.).
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              Meal frequency and timing in health and disease.

              Although major research efforts have focused on how specific components of foodstuffs affect health, relatively little is known about a more fundamental aspect of diet, the frequency and circadian timing of meals, and potential benefits of intermittent periods with no or very low energy intakes. The most common eating pattern in modern societies, three meals plus snacks every day, is abnormal from an evolutionary perspective. Emerging findings from studies of animal models and human subjects suggest that intermittent energy restriction periods of as little as 16 h can improve health indicators and counteract disease processes. The mechanisms involve a metabolic shift to fat metabolism and ketone production, and stimulation of adaptive cellular stress responses that prevent and repair molecular damage. As data on the optimal frequency and timing of meals crystalizes, it will be critical to develop strategies to incorporate those eating patterns into health care policy and practice, and the lifestyles of the population.
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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                18 January 2018
                January 2018
                : 18
                : 1
                Affiliations
                [1 ]Research Center for Communication and Information Technologies (CITIC), University of Costa Rica, San José 11501, Costa Rica; joseantonio.brenes@ 123456ucr.ac.cr (J.A.B.); luis.guerrero@ 123456ecci.ucr.ac.cr (L.A.G.)
                [2 ]MAmI Research Lab, University of Castilla-La Mancha, 13071 Ciudad Real, Spain; ivan.gdiaz@ 123456uclm.es (I.G.); jesus.fontecha@ 123456uclm.es (J.F.); jose.bravo@ 123456uclm.es (J.B.)
                [3 ]Faculty of Engineering, Architecture and Design, Autonomous University of Baja California, Ensenada 21100, Mexico; ejimenez@ 123456uabc.edu.mx
                Author notes
                [* ]Correspondence: gustavo.lopez_h@ 123456ucr.ac.cr ; Tel.: +506-2511-8030
                Article
                sensors-18-00271
                10.3390/s18010271
                5795366
                29346302
                © 2018 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                Categories
                Article

                Biomedical engineering

                ubiquitous computing, health, human-centered computing

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