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Principles and Methods of Social Research
PRINCIPLES AND METHODS OF SOCIAL RESEARCH Used to train generations of social scientists, this thoroughly updated classic text covers the latest research tech- niques and designs. Applauded for its comprehensive coverage, the breadth and depth of content is unparalleled. Through a multi-methodology approach, the text guides readers toward the design and conduct of social research from the ground up. Explained with applied examples useful to the social, behavioral, educational, and organiza- tional sciences, the methods described are intended to be relevant to contemporary researchers. The underlying logic and mechanics of experimental, quasi-experimental, and nonexperimental research strategies are discussed in detail. Introductory chapters covering topics such as validity and reliability furnish readers with a fi rm understanding of foundational concepts. Chapters dedicated to sampling, interviewing, questionnaire design, stimulus scaling, observational methods, content analysis, implicit measures, dyadic and group methods, and meta- analysis provide coverage of these essential methodologies. The book is noted for its: • Emphasis on understanding the principles that govern the use of a method to facilitate the researcher’s choice of the best technique for a given situation. • Use of the laboratory experiment as a touchstone to describe and evaluate field experiments, correlational designs, quasi experiments, evaluation studies, and survey designs. • Coverage of the ethics of social research, including the power a researcher wields and tips on how to use it responsibly. The new edition features: • A new co-author, Andrew Lac, instrumental in fine-tuning the book’s accessible approach and highlighting the most recent developments at the intersection of design and statistics. • More learning tools, including more explanation of the basic concepts, more research examples, tables, and figures, and the addition of boldfaced terms, chapter conclusions, discussion questions, and a glossary. -
A Task-Based Taxonomy of Cognitive Biases for Information Visualization
A Task-based Taxonomy of Cognitive Biases for Information Visualization Evanthia Dimara, Steven Franconeri, Catherine Plaisant, Anastasia Bezerianos, and Pierre Dragicevic Three kinds of limitations The Computer The Display 2 Three kinds of limitations The Computer The Display The Human 3 Three kinds of limitations: humans • Human vision ️ has limitations • Human reasoning 易 has limitations The Human 4 ️Perceptual bias Magnitude estimation 5 ️Perceptual bias Magnitude estimation Color perception 6 易 Cognitive bias Behaviors when humans consistently behave irrationally Pohl’s criteria distilled: • Are predictable and consistent • People are unaware they’re doing them • Are not misunderstandings 7 Ambiguity effect, Anchoring or focalism, Anthropocentric thinking, Anthropomorphism or personification, Attentional bias, Attribute substitution, Automation bias, Availability heuristic, Availability cascade, Backfire effect, Bandwagon effect, Base rate fallacy or Base rate neglect, Belief bias, Ben Franklin effect, Berkson's paradox, Bias blind spot, Choice-supportive bias, Clustering illusion, Compassion fade, Confirmation bias, Congruence bias, Conjunction fallacy, Conservatism (belief revision), Continued influence effect, Contrast effect, Courtesy bias, Curse of knowledge, Declinism, Decoy effect, Default effect, Denomination effect, Disposition effect, Distinction bias, Dread aversion, Dunning–Kruger effect, Duration neglect, Empathy gap, End-of-history illusion, Endowment effect, Exaggerated expectation, Experimenter's or expectation bias, -
The Lightbulb Paradox: Evidence from Two Randomized Experiments
NBER WORKING PAPER SERIES THE LIGHTBULB PARADOX: EVIDENCE FROM TWO RANDOMIZED EXPERIMENTS Hunt Allcott Dmitry Taubinsky Working Paper 19713 http://www.nber.org/papers/w19713 NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138 December 2013 We are grateful to Raj Chetty, Lucas Davis, Stefano DellaVigna, Mushfiq Mubarak, Sendhil Mullainathan, Emmanuel Saez, Josh Schwartzstein, and other colleagues, as well as seminar audiences at the ASSA Annual Meeting, the Behavioral Economics Annual Meeting, Berkeley, the European Summer Symposium for Economic Theory, Harvard, the NBER Public Economics Meetings, Resources for the Future, Stanford, the Stanford Institute for Theoretical Economics, UCLA, the University of California Energy Institute, and the University of Chicago for constructive feedback. We thank our research assistants - Jeremiah Hair, Nina Yang, and Tiffany Yee - as well as management at the partner company, for their work on the in-store experiment. Thanks to Stefan Subias, Benjamin DiPaola, and Poom Nukulkij at GfK for their work on the TESS experiment. We are grateful to the National Science Foundation and the Sloan Foundation for financial support. Files containing code for replication, the in-store experiment protocol, and audio for the TESS experiment can be downloaded from Hunt Allcott's website. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer- reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications. © 2013 by Hunt Allcott and Dmitry Taubinsky. -
A Neural Network Framework for Cognitive Bias
fpsyg-09-01561 August 31, 2018 Time: 17:34 # 1 HYPOTHESIS AND THEORY published: 03 September 2018 doi: 10.3389/fpsyg.2018.01561 A Neural Network Framework for Cognitive Bias Johan E. Korteling*, Anne-Marie Brouwer and Alexander Toet* TNO Human Factors, Soesterberg, Netherlands Human decision-making shows systematic simplifications and deviations from the tenets of rationality (‘heuristics’) that may lead to suboptimal decisional outcomes (‘cognitive biases’). There are currently three prevailing theoretical perspectives on the origin of heuristics and cognitive biases: a cognitive-psychological, an ecological and an evolutionary perspective. However, these perspectives are mainly descriptive and none of them provides an overall explanatory framework for the underlying mechanisms of cognitive biases. To enhance our understanding of cognitive heuristics and biases we propose a neural network framework for cognitive biases, which explains why our brain systematically tends to default to heuristic (‘Type 1’) decision making. We argue that many cognitive biases arise from intrinsic brain mechanisms that are fundamental for the working of biological neural networks. To substantiate our viewpoint, Edited by: we discern and explain four basic neural network principles: (1) Association, (2) Eldad Yechiam, Technion – Israel Institute Compatibility, (3) Retainment, and (4) Focus. These principles are inherent to (all) neural of Technology, Israel networks which were originally optimized to perform concrete biological, perceptual, Reviewed by: and motor functions. They form the basis for our inclinations to associate and combine Amos Schurr, (unrelated) information, to prioritize information that is compatible with our present Ben-Gurion University of the Negev, Israel state (such as knowledge, opinions, and expectations), to retain given information Edward J. -
Heuristics and Biases the Psychology of Intuitive Judgment. In
P1: FYX/FYX P2: FYX/UKS QC: FCH/UKS T1: FCH CB419-Gilovich CB419-Gilovich-FM May 30, 2002 12:3 HEURISTICS AND BIASES The Psychology of Intuitive Judgment Edited by THOMAS GILOVICH Cornell University DALE GRIFFIN Stanford University DANIEL KAHNEMAN Princeton University iii P1: FYX/FYX P2: FYX/UKS QC: FCH/UKS T1: FCH CB419-Gilovich CB419-Gilovich-FM May 30, 2002 12:3 published by the press syndicate of the university of cambridge The Pitt Building, Trumpington Street, Cambridge, United Kingdom cambridge university press The Edinburgh Building, Cambridge CB2 2RU, UK 40 West 20th Street, New York, NY 10011-4211, USA 477 Williamstown, Port Melbourne, VIC 3207, Australia Ruiz de Alarcon´ 13, 28014, Madrid, Spain Dock House, The Waterfront, Cape Town 8001, South Africa http://www.cambridge.org C Cambridge University Press 2002 This book is in copyright. Subject to statutory exception and to the provisions of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press. First published 2002 Printed in the United States of America Typeface Palatino 9.75/12.5 pt. System LATEX2ε [TB] A catalog record for this book is available from the British Library. Library of Congress Cataloging in Publication data Heuristics and biases : the psychology of intuitive judgment / edited by Thomas Gilovich, Dale Griffin, Daniel Kahneman. p. cm. Includes bibliographical references and index. ISBN 0-521-79260-6 – ISBN 0-521-79679-2 (pbk.) 1. Judgment. 2. Reasoning (Psychology) 3. Critical thinking. I. Gilovich, Thomas. II. Griffin, Dale III. Kahneman, Daniel, 1934– BF447 .H48 2002 153.4 – dc21 2001037860 ISBN 0 521 79260 6 hardback ISBN 0 521 79679 2 paperback iv P1: FYX/FYX P2: FYX/UKS QC: FCH/UKS T1: FCH CB419-Gilovich CB419-Gilovich-FM May 30, 2002 12:3 Contents List of Contributors page xi Preface xv Introduction – Heuristics and Biases: Then and Now 1 Thomas Gilovich and Dale Griffin PART ONE. -
The Threat of Appearing Prejudiced and Race-Based Attentional Biases Jennifer A
PSYCHOLOGICAL SCIENCE Research Report The Threat of Appearing Prejudiced and Race-Based Attentional Biases Jennifer A. Richeson and Sophie Trawalter Department of Psychology and C2S: The Center on Social Disparities and Health at the Institute for Policy Research, Northwestern University ABSTRACT—The current work tested whether external heightened anxiety in anticipation of, as well as during, those motivation to respond without prejudice toward Blacks is interracial interactions that they are unable to avoid (Plant, associated with biased patterns of selective attention that 2004; Plant & Devine, 1998). Research by Amodio has found, reflect a threat response to Black individuals. In a dot- furthermore, that such high-EM individuals automatically probe attentional bias paradigm, White participants with evaluate Black targets more negatively than White targets, as low and high external motivation to respond without revealed by potentiated startle eye-blink amplitudes (Amodio, prejudice toward Blacks (i.e., low-EM and high-EM in- Harmon-Jones, & Devine, 2003), unlike people who are inter- dividuals, respectively) were presented with pairs of White nally motivated to respond in nonprejudiced ways toward and Black male faces that bore either neutral or happy Blacks. Taken together, this work suggests that exposure to facial expressions; on each trial, the faces were displayed Blacks automatically triggers negative affective reactions, in- for either 30 ms or 450 ms. The findings were consistent cluding heightened anxiety, in high-EM individuals. with those of previous research on threat and attention: Although Amodio’s work has begun to explore some of the High-EM participants revealed an attentional bias toward component processes that underlie differences between high- and neutral Black faces presented for 30 ms, but an attentional low-EM individuals’ affective and stereotypical evaluations of bias away from neutral Black faces presented for 450 ms. -
Attentional Bias and Subjective Risk in Hypochondriacal Concern. Polly Beth Hitchcock Louisiana State University and Agricultural & Mechanical College
Louisiana State University LSU Digital Commons LSU Historical Dissertations and Theses Graduate School 1993 Attentional Bias and Subjective Risk in Hypochondriacal Concern. Polly Beth Hitchcock Louisiana State University and Agricultural & Mechanical College Follow this and additional works at: https://digitalcommons.lsu.edu/gradschool_disstheses Recommended Citation Hitchcock, Polly Beth, "Attentional Bias and Subjective Risk in Hypochondriacal Concern." (1993). LSU Historical Dissertations and Theses. 5641. https://digitalcommons.lsu.edu/gradschool_disstheses/5641 This Dissertation is brought to you for free and open access by the Graduate School at LSU Digital Commons. It has been accepted for inclusion in LSU Historical Dissertations and Theses by an authorized administrator of LSU Digital Commons. For more information, please contact [email protected]. INFORMATION TO USERS This manuscript has been reproduced from the microfilm master. UMI films the text directly from the original or copy submitted. Thus, some thesis and dissertation copies are in typewriter face, while others may be from any type of computer printer. The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleedthrough, substandard margins, and improper alignment can adversely affect reproduction. In the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion. Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand corner and continuing from left to right in equal sections with small overlaps. -
Emotional Reasoning and Parent-Based Reasoning in Normal Children
Morren, M., Muris, P., Kindt, M. Emotional reasoning and parent-based reasoning in normal children. Child Psychiatry and Human Development: 35, 2004, nr. 1, p. 3-20 Postprint Version 1.0 Journal website http://www.springerlink.com/content/105587/ Pubmed link http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dop t=Abstract&list_uids=15626322&query_hl=45&itool=pubmed_docsum DOI 10.1023/B:CHUD.0000039317.50547.e3 Address correspondence to M. Morren, Department of Medical, Clinical, and Experimental Psychology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands; e-mail: [email protected]. Emotional Reasoning and Parent-based Reasoning in Normal Children MATTIJN MORREN, MSC; PETER MURIS, PHD; MEREL KINDT, PHD DEPARTMENT OF MEDICAL, CLINICAL AND EXPERIMENTAL PSYCHOLOGY, MAASTRICHT UNIVERSITY, THE NETHERLANDS ABSTRACT: A previous study by Muris, Merckelbach, and Van Spauwen1 demonstrated that children display emotional reasoning irrespective of their anxiety levels. That is, when estimating whether a situation is dangerous, children not only rely on objective danger information but also on their own anxiety-response. The present study further examined emotional reasoning in children aged 7–13 years (N =508). In addition, it was investigated whether children also show parent-based reasoning, which can be defined as the tendency to rely on anxiety-responses that can be observed in parents. Children completed self-report questionnaires of anxiety, depression, and emotional and parent-based reasoning. Evidence was found for both emotional and parent-based reasoning effects. More specifically, children’s danger ratings were not only affected by objective danger information, but also by anxiety-response information in both objective danger and safety stories. -
Redalyc.Effects of State and Trait Anxiety on Selective Attention To
International Journal of Psychological Research ISSN: 2011-2084 [email protected] Universidad de San Buenaventura Colombia Ortega Marín, Jeniffer; Jiménez Solanilla, Karim; Acosta Barreto, Rocio Effects of state and trait anxiety on selective attention to threatening stimuli in a non-clinical sample of school children International Journal of Psychological Research, vol. 8, núm. 1, 2015, pp. 75-89 Universidad de San Buenaventura Medellín, Colombia Available in: http://www.redalyc.org/articulo.oa?id=299033832007 How to cite Complete issue Scientific Information System More information about this article Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Journal's homepage in redalyc.org Non-profit academic project, developed under the open access initiative INT.J.PSYCHOL.RES. 2015; 8 (1): 75-90 Effects of state and trait anxiety on selective attention to threatening stimuli in a non- clinical sample of school children Efectos de la ansiedad estado-rasgo sobre la atención selectiva a estímulos amenazantes en una muestra no clínica de niños escolarizados R e s e a r c h a a a, Jeniffer Ortega Marín , Karim Jiménez Solanilla , and Rocio Acosta Barreto * a Faculty of Psychology, Universidad San Buenaventura,Bogotá, Colombia. ARTICLE INFO ABSTRACT Attentional biases, consisting of a preferential processing of threatening stimuli, have been found in anxious adults as predicted by several cognitive models. However, Article history: studies with non-clinical samples of children have provided mixed results. Therefore, Received: 30-07-2014 the aim of this research was to determine the effects of state and trait anxiety on the Revised: 28-08-2014 selective attention towards threatening stimuli in a non-clinical sample of school Accepted: 10-12-2014 children (age: 8 to 13, n = 110) using the dot-probe task. -
Cognitive Biases in Software Engineering: a Systematic Mapping Study
Cognitive Biases in Software Engineering: A Systematic Mapping Study Rahul Mohanani, Iflaah Salman, Burak Turhan, Member, IEEE, Pilar Rodriguez and Paul Ralph Abstract—One source of software project challenges and failures is the systematic errors introduced by human cognitive biases. Although extensively explored in cognitive psychology, investigations concerning cognitive biases have only recently gained popularity in software engineering research. This paper therefore systematically maps, aggregates and synthesizes the literature on cognitive biases in software engineering to generate a comprehensive body of knowledge, understand state of the art research and provide guidelines for future research and practise. Focusing on bias antecedents, effects and mitigation techniques, we identified 65 articles (published between 1990 and 2016), which investigate 37 cognitive biases. Despite strong and increasing interest, the results reveal a scarcity of research on mitigation techniques and poor theoretical foundations in understanding and interpreting cognitive biases. Although bias-related research has generated many new insights in the software engineering community, specific bias mitigation techniques are still needed for software professionals to overcome the deleterious effects of cognitive biases on their work. Index Terms—Antecedents of cognitive bias. cognitive bias. debiasing, effects of cognitive bias. software engineering, systematic mapping. 1 INTRODUCTION OGNITIVE biases are systematic deviations from op- knowledge. No analogous review of SE research exists. The timal reasoning [1], [2]. In other words, they are re- purpose of this study is therefore as follows: curring errors in thinking, or patterns of bad judgment Purpose: to review, summarize and synthesize the current observable in different people and contexts. A well-known state of software engineering research involving cognitive example is confirmation bias—the tendency to pay more at- biases. -
Infographic I.10
The Digital Health Revolution: Leaving No One Behind The global AI in healthcare market is growing fast, with an expected increase from $4.9 billion in 2020 to $45.2 billion by 2026. There are new solutions introduced every day that address all areas: from clinical care and diagnosis, to remote patient monitoring to EHR support, and beyond. But, AI is still relatively new to the industry, and it can be difficult to determine which solutions can actually make a difference in care delivery and business operations. 59 Jan 2021 % of Americans believe returning Jan-June 2019 to pre-coronavirus life poses a risk to health and well being. 11 41 % % ...expect it will take at least 6 The pandemic has greatly increased the 65 months before things get number of US adults reporting depression % back to normal (updated April and/or anxiety.5 2021).4 Up to of consumers now interested in telehealth going forward. $250B 76 57% of providers view telehealth more of current US healthcare spend % favorably than they did before COVID-19.7 could potentially be virtualized.6 The dramatic increase in of Medicare primary care visits the conducted through 90% $3.5T telehealth has shown longevity, with rates in annual U.S. health expenditures are for people with chronic and mental health conditions. since April 2020 0.1 43.5 leveling off % % Most of these can be prevented by simple around 30%.8 lifestyle changes and regular health screenings9 Feb. 2020 Apr. 2020 OCCAM’S RAZOR • CONJUNCTION FALLACY • DELMORE EFFECT • LAW OF TRIVIALITY • COGNITIVE FLUENCY • BELIEF BIAS • INFORMATION BIAS Digital health ecosystems are transforming• AMBIGUITY BIAS • STATUS medicineQUO BIAS • SOCIAL COMPARISONfrom BIASa rea• DECOYctive EFFECT • REACTANCEdiscipline, • REVERSE PSYCHOLOGY • SYSTEM JUSTIFICATION • BACKFIRE EFFECT • ENDOWMENT EFFECT • PROCESSING DIFFICULTY EFFECT • PSEUDOCERTAINTY EFFECT • DISPOSITION becoming precise, preventive,EFFECT • ZERO-RISK personalized, BIAS • UNIT BIAS • IKEA EFFECT and • LOSS AVERSION participatory. -
Attentional Bias Components in Anxiety and Depression: a Systematic Review
Attentional Bias Components in Anxiety and Depression: A Systematic Review Denise Rogersa, Edel Murphya, Sarah Jane Windersa & Ciara M. Greenea aSchool of Psychology, University College Dublin, Belfield, Dublin 4, Ireland Corresponding author: Associate Professor Ciara M. Greene Email: [email protected] Postal address: School of Psychology, University College Dublin, Belfield, Dublin 4, Ireland Tel: +353 1 7168334 1 Abstract Attentional biases have been identified as a transdiagnostic cognitive process that may underlie a range of psychological disorders. They comprise three measurable and observable components; facilitation (rapid detection of concern-related stimuli), difficulty in disengagement (slower attentional shifting away from concern-related stimuli) and attentional avoidance (allocation of attention away from concern-related stimuli). Attentional biases to negative stimuli are common in anxiety and depression; however, their shared (i.e. transdiagnostic) and distinct components have not yet been systematically investigated. Literature searches were conducted on the PsychINFO, Embase, PubMed and Web of Science databases, yielding 560 articles after duplicates were removed. Articles were subject to abstract and full-text screening against study eligibility criteria. Twenty-five articles were included in the extraction phase. Data regarding population, experimental paradigm and attentional bias components were extracted. Results are suggestive of facilitation as a transdiagnostic attentional process across anxiety, depression and those with co- occurring anxiety and depression. There was strong evidence of avoidance in depression, with weaker evidence in anxiety, while delayed disengagement was observed in anxiety, but not in depression. Critical gaps in the literature were also identified. These findings provide support for the transdisagnostic nature of attentional biases, shedding light on the commonalities observed across diagnostic categories.