Early accounts of judgmental anchoring attribute the effect to a deliberate, but insufficient, adjustment process; more recent theories point to automatic, priming-based processes as the underlying cause. In this article we introduce a novel anchor assessment manipulation and a decompositional analysis of the standard anchoring effect to determine the extent to which anchoring is driven by automatic versus deliberate processes. Prior to providing a target estimate, participants indicated whether the target was greater or less than the anchor, or whether the anchor would make a good or bad target estimate. Contrary to predictions of priming-based accounts, the decomposition of the anchoring effect revealed that participants generally provided estimates consistent with their prior assessment; in particular, anchoring was eliminated when participants considered the anchor to be a bad target estimate. These findings challenge the view of anchoring as an inevitable bias of numerical judgment and indicate that people have significant control over how they manage numerical information in judgments under uncertainty. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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PLoS One
January 2025
Centre for Agri-Environmental Research, School of Agriculture, Policy and Development, University of Reading, Reading, England, United Kingdom.
Pressures on honey bee health have substantially increased both colony mortality and beekeepers' costs for hive management across Europe. Although technological advances could offer cost-effective solutions to these challenges, there is little research into the incentives and barriers to technological adoption by beekeepers in Europe. Our study is the first to investigate beekeepers' willingness to adopt the Bee Health Card, a molecular diagnostic tool developed within the PoshBee EU project which can rapidly assess bee health by monitoring molecular changes in bees.
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January 2025
Department of Mathematics and Statistics, University of Energy and Natural Resources, Sunyani, Ghana.
Access to clean and efficient cooking fuel is crucial for promoting good health, safeguarding the environment, and driving economic growth. Despite efforts to promote the adoption of cleaner alternatives, traditional solid fuels such as charcoal and firewood remain prevalent in Ghana. In this study, we utilized a statistical mechanical model as a framework to explore the statistical relationship between socio-economic factors such as educational attainment, wealth status, place of residence, and cooking fuel choices.
View Article and Find Full Text PDFPsychiatr Q
January 2025
Educational psychology, The Hashemite University, Queen Rania Faculty for Childhood, Early Childhood Department, Zarqa, Jordan.
The current paper aimed to estimate the network structure of general psychopathology (internalizing and externalizing symptoms/disorders) among 239 gifted children in Jordan. This cross-sectional study with a convenience sampling method was conducted between September 2023 and October 2024 among gifted children aged 7-12. The Child Behavior Checklist (CBCL) was employed to assess six symptom clusters: conduct problems, attention-deficit/hyperactivity disorder (ADHD), and oppositional defiant problems as externalizing symptoms, and affective problems, anxiety issues, and somatic complaints as internalizing symptoms.
View Article and Find Full Text PDFJ Epidemiol Glob Health
January 2025
Special Infectious Agents Unit-BSL3, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, 21589, Saudi Arabia.
Human papillomavirus (HPV), a common sexually transmitted infection, includes over 200 types, some linked to genital warts and various cancers, including cervical, anal, penile, and oropharyngeal cancers. In Saudi Arabia, an estimated 10.7 million women aged 15 years and older are at risk of HPV-related cervical cancer.
View Article and Find Full Text PDFBrief Bioinform
November 2024
School of Artificial Intelligence, Jilin University, 3003 Qianjin Street, 130012 Changchun, China.
Accurate identification of causal genes for cancer prognosis is critical for estimating disease progression and guiding treatment interventions. In this study, we propose CPCG (Cancer Prognosis's Causal Gene), a two-stage framework identifying gene sets causally associated with patient prognosis across diverse cancer types using transcriptomic data. Initially, an ensemble approach models gene expression's impact on survival with parametric and semiparametric hazard models.
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