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Jon-Patrick Allem, Emilio Ferrara
No abstract text is available yet for this article.
August 9, 2016: Journal of Medical Internet Research
David J Lorenz, Diego Nieto-Lugilde, Jessica L Blois, Matthew C Fitzpatrick, John W Williams
Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0...
2016: Scientific Data
Ramona Ludolph, Ahmed Allam, Peter J Schulz
BACKGROUND: One of people's major motives for going online is the search for health-related information. Most consumers start their search with a general search engine but are unaware of the fact that its sorting and ranking criteria do not mirror information quality. This misconception can lead to distorted search outcomes, especially when the information processing is characterized by heuristic principles and resulting cognitive biases instead of a systematic elaboration. As vaccination opponents are vocal on the Web, the chance of encountering their non‒evidence-based views on immunization is high...
2016: Journal of Medical Internet Research
Veronica X Yan, Elizabeth Ligon Bjork, Robert A Bjork
Interleaving exemplars of to-be-learned categories-rather than blocking exemplars by category-typically enhances inductive learning. Learners, however, tend to believe the opposite, even after their own performance has benefited from interleaving. In Experiments 1 and 2, the authors examined the influence of 2 factors that they hypothesized contribute to the illusion that blocking enhances inductive learning: Namely, that (a) blocking creates a sense of fluent extraction during study of the features defining a given category, and (b) learners come to the experimental task with a pre-existing belief that blocking instruction by topic is superior to intermixing topics...
July 2016: Journal of Experimental Psychology. General
Kaylee van Geene, Esther de Groot, Carmen Erkelens, Dorien Zwart
INTRODUCTION: Bias in diagnostic reasoning can potentially lead to severe consequences. We explored how to design an experiential learning workshop in a general practice clerkship to raise awareness on bias. METHOD: A group of 12 students was split into two groups. Both groups 'diagnosed' two patients in two case studies. Only one group, without them knowing, were given a case including salient distracting features. The whole group discussed the influence of these distractors...
June 2016: Perspectives on Medical Education
Nathan Herdener, Christopher D Wickens, Benjamin A Clegg, C A P Smith
OBJECTIVE: The aim of this study was to understand factors that influence the prediction of uncertain spatial trajectories (e.g., the future path of a hurricane or ship) and the role of human overconfidence in such prediction. BACKGROUND: Research has indicated that human prediction of uncertain trajectories is difficult and may well be subject to overconfidence in the accuracy of forecasts as is found in event prediction, a finding that indicates that humans insufficiently appreciate the contributions of variance in nature to their predictions...
September 2016: Human Factors
Sharon Stemple Hinchman, Amy Funk, Christina DeBiase, Cathryn Frere
PURPOSE: The purpose of this study was to determine the extent of ultrasonic scaling instrumentation instruction in dental hygiene programs in the U.S. Currently, there is no publication available defining a consensus of instruction for ultrasonic instrumentation. METHODS: Exempt status was received from the West Virginia University Institutional Review Board. A survey was developed with dental hygiene administrators and faculty, based on assumptions and a list of questions to be answered...
April 2016: Journal of Dental Hygiene: JDH
Victoria A Shaffer, Elizabeth S Focella, Laura D Scherer, Brian J Zikmund-Fisher
OBJECTIVE: To determine whether representative experience narratives (describing a range of possible experiences) or targeted experience narratives (targeting the direction of forecasting bias) can reduce affective forecasting errors, or errors in predictions of experiences. METHODS: In Study 1, participants (N=366) were surveyed about their experiences with 10 common medical events. Those who had never experienced the event provided ratings of predicted discomfort and those who had experienced the event provided ratings of actual discomfort...
October 2016: Patient Education and Counseling
Keng Sheng Chew, Steven J Durning, Jeroen Jg van Merriënboer
INTRODUCTION: Metacognition is a cognitive debiasing strategy that clinicians can use to deliberately detach themselves from the immediate context of a clinical decision, in order to reflect upon the thinking process engaged. However, the use of cognitive debiasing strategies is often most needed in occasions where the clinician cannot afford the time to do so. A mnemonic checklist known as the TWED checklist (where T = Threat, W = What else, E = Evidence and D = Disposition influence) was recently created to facilitate metacognition...
January 15, 2016: Singapore Medical Journal
Melissa M Jenkins, Eric A Youngstrom
OBJECTIVE: This study examined the efficacy of a new cognitive debiasing intervention in reducing decision-making errors in the assessment of pediatric bipolar disorder (PBD). METHOD: The study was a randomized controlled trial using case vignette methodology. Participants were 137 mental health professionals working in different regions of the United States (M = 8.6 ± 7.5 years of experience). Participants were randomly assigned to a (a) brief overview of PBD (control condition), or (b) the same brief overview plus a cognitive debiasing intervention (treatment condition) that educated participants about common cognitive pitfalls (e...
April 2016: Journal of Consulting and Clinical Psychology
Honglei Zhuang, Aditya Parameswaran, Dan Roth, Jiawei Han
Crowdsourcing is the de-facto standard for gathering annotated data. While, in theory, data annotation tasks are assumed to be attempted by workers independently, in practice, data annotation tasks are often grouped into batches to be presented and annotated by workers together, in order to save on the time or cost overhead of providing instructions or necessary background. Thus, even though independence is usually assumed between annotations on data items within the same batch, in most cases, a worker's judgment on a data item can still be affected by other data items within the batch, leading to additional errors in collected labels...
August 2015: KDD: Proceedings
Balazs Aczel, Bence Bago, Aba Szollosi, Andrei Foldes, Bence Lukacs
The aim of this study was to initiate the exploration of debiasing methods applicable in real-life settings for achieving lasting improvement in decision making competence regarding multiple decision biases. Here, we tested the potentials of the analogical encoding method for decision debiasing. The advantage of this method is that it can foster the transfer from learning abstract principles to improving behavioral performance. For the purpose of the study, we devised an analogical debiasing technique for 10 biases (covariation detection, insensitivity to sample size, base rate neglect, regression to the mean, outcome bias, sunk cost fallacy, framing effect, anchoring bias, overconfidence bias, planning fallacy) and assessed the susceptibility of the participants (N = 154) to these biases before and 4 weeks after the training...
2015: Frontiers in Psychology
Joram van Driel, Roy Cox, Michael X Cohen
BACKGROUND: Cross-frequency coupling methods allow for the identification of non-linear interactions across frequency bands, which are thought to reflect a fundamental principle of how electrophysiological brain activity is temporally orchestrated. In this paper we uncover a heretofore unknown source of bias in a commonly used method that quantifies cross-frequency coupling (phase-amplitude-coupling, or PAC). NEW METHOD: We demonstrate that non-uniform phase angle distributions--a phenomenon that can readily occur in real data--can under some circumstances produce statistical errors and uninterpretable results when using PAC...
October 30, 2015: Journal of Neuroscience Methods
Gabriella Eriksson, Christopher J D Patten, Ola Svenson, Lars Eriksson
The time saving bias predicts that the time saved when increasing speed from a high speed is overestimated, and underestimated when increasing speed from a slow speed. In a questionnaire, time saving judgements were investigated when information of estimated time to arrival was provided. In an active driving task, an alternative meter indicating the inverted speed was used to debias judgements. The simulated task was to first drive a distance at a given speed, and then drive the same distance again at the speed the driver judged was required to gain exactly 3 min in travel time compared with the first drive...
2015: Ergonomics
Boris Schauerte, Rainer Stiefelhagen
In recent years it has become apparent that a Gaussian center bias can serve as an important prior for visual saliency detection, which has been demonstrated for predicting human eye fixations and salient object detection. Tseng et al. have shown that the photographer's tendency to place interesting objects in the center is a likely cause for the center bias of eye fixations. We investigate the influence of the photographer's center bias on salient object detection, extending our previous work. We show that the centroid locations of salient objects in photographs of Achanta and Liu's data set in fact correlate strongly with a Gaussian model...
2015: PloS One
Panlong Wu, Xingxiu Li, Jianshou Kong, Jiale Liu
To solve the problem of tracking maneuvering airborne targets in the presence of clutter, an improved interacting multiple model probability data association algorithm (IMMPDA-MDCM) using radar/IR sensors fusion is proposed. Under the architecture of the proposed algorithm, the radar/IR centralized fusion tracking scheme of IMMPDA-MDCM is designed to guarantee the observability of the target state. The interacting multiple model (IMM) deals with the model switching. The modified debiased converted measurement (MDCM) filter accounts for non-linearity in the dynamic system models, and reduces the effect of measurement noise on the covariance effectively...
2015: Sensors
Pat Croskerry
No abstract text is available yet for this article.
July 2015: Medical Education
Andrew R Smith, Paul D Windschitl
The biasing influence of anchors on numerical estimates is well established, but the relationship between knowledge level and the susceptibility to anchoring effects is less clear. In two studies, we addressed the potential mitigating effects of having knowledge in a domain on vulnerability to anchoring effects in that domain. Of critical interest was a distinction between two forms of knowledge-metric and mapping knowledge. In Study 1, participants who had studied question-relevant information-that is, high-knowledge participants-were less influenced by anchors than were participants who had studied irrelevant information...
October 2015: Memory & Cognition
Thanh-Tung Nguyen, Joshua Zhexue Huang, Thuy Thi Nguyen
Random forests (RFs) have been widely used as a powerful classification method. However, with the randomization in both bagging samples and feature selection, the trees in the forest tend to select uninformative features for node splitting. This makes RFs have poor accuracy when working with high-dimensional data. Besides that, RFs have bias in the feature selection process where multivalued features are favored. Aiming at debiasing feature selection in RFs, we propose a new RF algorithm, called xRF, to select good features in learning RFs for high-dimensional data...
2015: TheScientificWorldJournal
Gilberto Montibeller, Detlof von Winterfeldt
Behavioral decision research has demonstrated that judgments and decisions of ordinary people and experts are subject to numerous biases. Decision and risk analysis were designed to improve judgments and decisions and to overcome many of these biases. However, when eliciting model components and parameters from decisionmakers or experts, analysts often face the very biases they are trying to help overcome. When these inputs are biased they can seriously reduce the quality of the model and resulting analysis...
July 2015: Risk Analysis: An Official Publication of the Society for Risk Analysis
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