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| http://dx.doi.org/10.3389/fpsyg.2013.00972 | DOI Listing |
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Futures of gastric cancer: The fundamental level of prevention in health promotion using casual layered analysis.
Heliyon
November 2024
Health Management and Economics Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
Gastric cancer is the leading cause of cancer mortality among men and the second leading cause among women in Iran. Given the high incidence and mortality rates of this disease in the country, a deeper investigation into its effective causes is essential. One effective approach to uncovering the unknowns related to gastric cancer is the application of critical-deconstructive future-thinking tools, particularly Causal Layer Analysis (CLA).
View Article and Find Full Text PDFNudging recommendation algorithms increases news consumption and diversity on YouTube.
PNAS Nexus
December 2024
Department of Communication, University of California, Davis, USA.
Recommendation algorithms profoundly shape users' attention and information consumption on social media platforms. This study introduces a computational intervention aimed at mitigating two key biases in algorithms by influencing the recommendation process. We tackle , or algorithms creating narrow nonnews and entertainment information diets, and , or algorithms directing the more strongly partisan users to like-minded content.
View Article and Find Full Text PDFImproving the management of hospital waiting lists by using nudges in letters: A Randomised controlled trial.
Soc Sci Med
November 2024
Leeds Trinity University, England, United Kingdom.
Article Synopsis
- The study aimed to reduce the rate at which patients do not respond to validation letters sent by hospitals, using a redesigned letter that included "nudges" as an intervention.
- A total of 2,855 participants were divided into a control group receiving the standard letter and an intervention group receiving the new version.
- Results showed that the intervention group had a significantly lower non-response rate (19.24%) compared to the control group (23.97%), leading to improved patient compliance with the validation process, which has now been adopted by public hospitals in Ireland.
Choice architecture promotes sustainable choices in online food-delivery apps.
PNAS Nexus
October 2024
El-Erian Institute of Behavioural Economics and Policy, Judge Business School, University of Cambridge, Trumpington Street, Cambridge CB2 1AG, United Kingdom.
Greenhouse gas emissions from the food system constitute about one-third of the global total, hence mitigation in this sphere of human activity is a vital goal for research and policy. This study empirically tests the effectiveness of different interventions to reduce the carbon footprint of food choices made on food-delivery apps, using an incentive-compatible online randomized controlled trial with 4,008 participants. The experiment utilized an interactive web platform that mimics popular online food-delivery platforms (such as Just Eat) and included three treatment conditions: a sign-posted meat tax, a carbon-footprint label, and a choice-architecture intervention that changed the order of the menu so that the lowest carbon-impact restaurants and dishes were presented first.
View Article and Find Full Text PDFConsidering information-sharing motives to reduce misinformation.
Curr Opin Psychol
October 2024
Affective Brain Lab, Department of Experimental Psychology, University College London, London, UK; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA. Electronic address:
Misinformation has risen in recent years, negatively affecting domains ranging from politics to health. To curb the spread of misinformation it is useful to consider why, how, and when people decide to share information. Here we suggest that information-sharing decisions are value-based choices, in which sharers strive to maximize rewards and minimize losses to themselves and/or others.
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