Each day, adolescents and young adults (AYAs) choose to engage in behaviors that impact their current and future health. Behavioral economics represents an innovative lens through which to explore decision-making among AYAs. Behavioral economics outlines a diverse set of phenomena that influence decision-making and can be leveraged to develop interventions that may support behavior change. Up to this point, behavioral economic interventions have predominantly been studied in adults. This article provides an integrative review of how behavioral economic phenomena can be leveraged to motivate health-related behavior change among AYAs. We contextualize these phenomena in the physical and social environments unique to AYAs and the neurodevelopmental changes they undergo, highlighting opportunities to intervene in AYA-specific contexts. Our review of the literature suggests behavioral economic phenomena leveraging social choice are particularly promising for AYA health. Behavioral economic interventions that take advantage of AYA learning and development have the potential to positively impact youth health and well-being over the lifespan.
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http://dx.doi.org/10.1016/j.jadohealth.2020.10.007 | DOI Listing |
Sci Rep
December 2024
Department of Physics, Sakarya University, Sakarya, Turkey.
Environmental problems have increased the need for sustainable agricultural practices that conserve water and energy. Carob, an eco-friendly crop with multiple health benefits, holds the potential for economic evaluation. This study investigates the carob molasses extraction process, focusing on the influence of temperature and water quantity on the diffusion coefficient.
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December 2024
School of Economics and Management, Taiyuan Normal University, Taiyuan, 030619, China.
An investigation of the evolutionary characteristics and internal driving mechanisms of territorial space since the reform and opening up is essential. The study will guide the orderly development and rational layout of territorial space, as well as achievement transformation and high-quality development in Shanxi Province. We used land use data from 1980 to 2020, which was divided into four periods, to examine the changes in production-living-ecological spatial pattern in Shanxi Province.
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December 2024
Health Systems and Health Economics, School of Public Health, Curtin University, Bentley, Perth, Australia.
Background: Women's preferences for time allocation reveal how they would like to prioritise market work, family life, and other competing activities. Whilst preferences may not always directly translate to behaviour, they are an important determinant of intention to act.
Objective: We present the first study to apply a discrete choice experiment (DCE) to investigate time allocation preferences among women diagnosed with breast cancer and women without a cancer diagnosis.
Sci Rep
December 2024
Department of Surgery, Transplantation and Gastroenterology, Semmelweis University, Budapest, 1082, Hungary.
Human alveolar echinococcosis (HAE), which is caused by the larval stage of the Echinococcus multilocularis tapeworm, is an increasing healthcare issue in Hungary. Among the 40 known cases in the country, 25 were detected in the last five years. Our study aimed to reveal the geographically underlying risk factors associated potentially with these cases.
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December 2024
College of Geography and Environment, Shandong Normal University, Jinan, 250358, China.
The urban agglomeration represents the predominant form of new urbanisation, yet the evolution of its internal spatial structure exhibits pronounced spatial and temporal heterogeneity. This study concentrates on the Bohai Rim urban agglomeration, one of three major urban agglomerations in China, which has received comparatively limited research attention but has also undergone substantial urbanisation. Therefore, we reassessed and explored the spatial-temporal evolution of the spatial structure of urban expansion using Exploratory Spatiotemporal Data Analysis (ESTDA), and summarized the driving mechanisms using Geographically and Temporally Weighted Regression (GTWR).
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