DOCSLIB.ORG

Toward an Affective Science of Resource Allocation: Psychological, Affective, and Neural Factors in Resource Allocation Decisions

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Toward an Affective Science of Resource Allocation: Psychological, Affective, and Neural Factors in Resource Allocation Decisions Toward an Affective Science of Resource Allocation: Psychological, Affective, and Neural Factors in Resource Allocation Decisions by Brian D. Vickers A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Psychology) in the University of Michigan 2015 Doctoral Committee: Associate Professor Stephanie D. Preston, Co-Chair Professor Rachael D. Seidler, Co-Chair Distinguished Professor Phoebe C. Ellsworth Assistant Professor Scott Rick Professor J. Frank Yates “These, then, are some of the basic principles of ecology—interdependence, recycling, partnership, flexibility, diversity, and, as a consequence of all those, sustainability... the survival of humanity will depend on our ecological literacy, on our ability to understand these principles of ecology and live accordingly.” Fritjof Capra, The Systems View of Life © Brian D. Vickers 2015 Dedication To Savanna ii Acknowledgements I want to thank my committee for all of their support and feedback, especially Stephanie, who has helped me develop intellectually and as a person over these years in Ann Arbor. Between the numerous rounds of data collection and analysis strategies it is easy to get off track but you have all helped me find my way. Thank you. This work would not be possible without the contributions from graduate students in my labs, especially Alicia Hofelich, Dan Porter, and Stephanie Carpenter. Without their support, feedback, and suggestions this dissertation would not have been completed. Thank you also to Daniel Weissman for his numerous methodological and statistical suggestions regarding fMRI studies, Rich Gonzalez for the way he shaped my approach to understanding patterns in data, and the whole Cognition and Cognitive Neuroscience area for their feedback on these projects at various stages. I would also like to thank the army of research assistants I have built over the years: Dave Chester, Lisa Blaskowski, Ben Sanford, Kendall Arslanian, Jamie Cohen, Chis Cannon, Nitin Gandi, Eitan Newmark, Courtney Hsing, Chris Vasileff, Michael Shen, Colleen McNamee, Belinda Chen, Chris Shu, Valerie Laird, Arthur Wandzel, and Hammad Kahn. A very special thank you goes out to my family and my girlfriend, Savanna. Your unconditional love and support have helped me persist through the difficult times when stress was overwhelming and I had a hard time finding motivation. Thank you also to my friends and the Dopamine Machine intramural sports team, who have provided welcome conversations, distractions, and fun escapes when I needed them. iii My final thank you goes to caffeine. Without you academia probably would not function, and I know my dissertation would not have been completed without you. iv Table of Contents Dedication ...................................................................................................................................... ii Acknowledgements ...................................................................................................................... iii List of Figures .............................................................................................................................. vii List of Tables ................................................................................................................................ ix Abstract .......................................................................................................................................... x Chapter 1: General Introduction ................................................................................................ 1 Decision Making and Preference Construction ....................................................................... 2 Affect and Appraisals ........................................................................................................................ 3 Affect and Decision Making ............................................................................................................. 5 Integral Emotions and Decision Making .............................................................................................. 6 Incidental Emotions and Decision Making ......................................................................................... 8 General Theories of Carryover Effects ................................................................................................. 8 The Current Research .................................................................................................................... 10 References .......................................................................................................................................... 14 Chapter 2: Affective Influences on the Drive to Acquire: Uncertainty and Sadness Increase Consumption, but Uncertain-Sadness Does Not ...................................................................... 16 Abstract ............................................................................................................................................... 16 Introduction ...................................................................................................................................... 17 Study 1 ................................................................................................................................................. 20 Methods ........................................................................................................................................................... 20 Procedure ....................................................................................................................................................... 20 Analysis ........................................................................................................................................................... 23 Results.............................................................................................................................................................. 24 Discussion ...................................................................................................................................................... 26 Study 2 ................................................................................................................................................. 27 Methods ........................................................................................................................................................... 28 Procedure ....................................................................................................................................................... 29 Results.............................................................................................................................................................. 29 Discussion ...................................................................................................................................................... 33 General Discussion .......................................................................................................................... 35 References .......................................................................................................................................... 38 Appendix 2A. Item Ratings. .......................................................................................................... 40 Appendix 2B. Emotion Induction Stories from Study 2. .................................................... 42 Sad-Certain Story ........................................................................................................................................ 42 Sad-Uncertain Story. .................................................................................................................................. 43 Chapter 3: Why the Attic Overflows: Individual Differences and Psychopathology Predict Material Preferences ................................................................................................................... 44 Abstract ............................................................................................................................................... 44 Introduction ...................................................................................................................................... 45 v Methods ............................................................................................................................................... 47 Participants .................................................................................................................................................... 47 The Relationship to Objects Scale ........................................................................................................ 49 Analysis ........................................................................................................................................................... 49 Results ................................................................................................................................................. 50 Revealing Six Object Factors ................................................................................................................... 50 Qualitative Associations between Item Type and Group ............................................................ 50 Transdiagnostic Approach: Qualitative Associations Across Clinical Diagnoses ............. 53 Discussion
Load more

Recommended publications
  • Tor Wager Diana L
    Tor Wager Diana L. Taylor Distinguished Professor of Psychological and Brain Sciences Dartmouth College Email: [email protected] https://wagerlab.colorado.edu Last Updated: July, 2019 Executive summary ● Appointments: Faculty since 2004, starting as Assistant Professor at Columbia ​ University. Associate Professor in 2009, moved to University of Colorado, Boulder in 2010; Professor since 2014. 2019-Present: Diana L. Taylor Distinguished Professor of Psychological and Brain Sciences at Dartmouth College. ● Publications: 240 publications with >50,000 total citations (Google Scholar), 11 papers ​ cited over 1000 times. H-index = 79. Journals include Science, Nature, New England Journal of Medicine, Nature Neuroscience, Neuron, Nature Methods, PNAS, Psychological Science, PLoS Biology, Trends in Cognitive Sciences, Nature Reviews Neuroscience, Nature Reviews Neurology, Nature Medicine, Journal of Neuroscience. ● Funding: Currently principal investigator on 3 NIH R01s, and co-investigator on other ​ collaborative grants. Past funding sources include NIH, NSF, Army Research Institute, Templeton Foundation, DoD. P.I. on 4 R01s, 1 R21, 1 RC1, 1 NSF. ● Awards: Awards include NSF Graduate Fellowship, MacLean Award from American ​ Psychosomatic Society, Colorado Faculty Research Award, “Rising Star” from American Psychological Society, Cognitive Neuroscience Society Young Investigator Award, Web of Science “Highly Cited Researcher”, Fellow of American Psychological Society. Two patents on research products. ● Outreach: >300 invited talks at universities/international conferences since 2005. ​ Invited talks in Psychology, Neuroscience, Cognitive Science, Psychiatry, Neurology, Anesthesiology, Radiology, Medical Anthropology, Marketing, and others. Media outreach: Featured in New York Times, The Economist, NPR (Science Friday and Radiolab), CBS Evening News, PBS special on healing, BBC, BBC Horizons, Fox News, 60 Minutes, others.
    [Show full text]
  • 1 Automated Face Analysis for Affective Computing Jeffrey F. Cohn & Fernando De La Torre Abstract Facial Expression
    Please do not quote. In press, Handbook of affective computing. New York, NY: Oxford Automated Face Analysis for Affective Computing Jeffrey F. Cohn & Fernando De la Torre Abstract Facial expression communicates emotion, intention, and physical state, and regulates interpersonal behavior. Automated Face Analysis (AFA) for detection, synthesis, and understanding of facial expression is a vital focus of basic research. While open research questions remain, the field has become sufficiently mature to support initial applications in a variety of areas. We review 1) human-observer based approaches to measurement that inform AFA; 2) advances in face detection and tracking, feature extraction, registration, and supervised learning; and 3) applications in action unit and intensity detection, physical pain, psychological distress and depression, detection of deception, interpersonal coordination, expression transfer, and other applications. We consider user-in-the-loop as well as fully automated systems and discuss open questions in basic and applied research. Keywords Automated Face Analysis and Synthesis, Facial Action Coding System (FACS), Continuous Measurement, Emotion, Nonverbal Communication, Synchrony 1. Introduction The face conveys information about a person’s age, sex, background, and identity, what they are feeling, or thinking (Darwin, 1872/1998; Ekman & Rosenberg, 2005). Facial expression regulates face-to-face interactions, indicates reciprocity and interpersonal attraction or repulsion, and enables inter-subjectivity between members of different cultures (Bråten, 2006; Fridlund, 1994; Tronick, 1989). Facial expression reveals comparative evolution, social and emotional development, neurological and psychiatric functioning, and personality processes (Burrows & Cohn, In press; Campos, Barrett, Lamb, Goldsmith, & Stenberg, 1983; Girard, Cohn, Mahoor, Mavadati, & Rosenwald, 2013; Schmidt & Cohn, 2001). Not surprisingly, the face has been of keen interest to behavioral scientists.
    [Show full text]
  • The Future of Emotion Research in the Study of Psychopathology
    Emotion Review Vol. 2, No. 3 (July 2010) 225–228 © 2010 SAGE Publications and The International Society for Research on Emotion The Future of Emotion Research in the Study ISSN 1754-0739 DOI: 10.1177/1754073910361986 of Psychopathology er.sagepub.com Ann M. Kring Department of Psychology, University of California, Berkeley, USA Abstract Research on emotion and psychopathology has blossomed due in part to the translation of affective science theory and methods to the study of diverse disorders. This translational approach has helped the field to hone in more precisely on the nature of emo- tion deficits to identify antecedent causes and maintaining processes, and to develop promising new interventions. The future of emotion research in psychopathology will benefit from three inter-related areas, including an emphasis on emotion difficulties that cut across traditional diagnostic boundaries (i.e., a transdiagnostic approach), the explicit linking of emotion and cognition in behavioral and neuroimaging studies in psychopathology, and continued translation of the latest conceptualizations of emotion to the study of psychopathology. Keywords cognition, emotion, mental illness, psychopathology, transdiagnostic In the past two decades, the number of studies on emotion and Where We Have Been psychopathology has expanded greatly. A search in PsychInfo for peer-reviewed articles containing the most generic of key- Given the ubiquity of emotion-related symptoms in psychopa- words, “emotion” and “mental illness” or “psychopathology”, thology (e.g., anger, anhedonia, anxiety, excited mood, fear, yields 613 peer reviewed articles in just the past 20 years. By flat affect, guilt, irritability, sad mood), most of the early contrast, 441 articles with these keywords are found for the 80 research sought to describe emotion-related disturbances.
    [Show full text]
  • Expert Meeting on Empathy and Compassion
    Expert Meeting on Empathy and Compassion Leveraging Basic Research to Inform Intervention Development September 16–17, 2019 Washington, DC Final March 17, 2020 This meeting summary was prepared by Frances McFarland, Rose Li and Associates, Inc., under contract to the National Institute on Aging of the National Institutes of Health. The views expressed in this document reflect both individual and collective opinions of the meeting participants and not necessarily those of the National Institute on Aging. Review of earlier versions of this meeting summary by the following individuals is gratefully acknowledged: Arielle Baskin- Sommers, Sona Dimidjian, Rebecca Lazeration, Robert Levenson, Rose Li, Abigail Marsh, Joan Monin, Lis Nielsen, Lisa Onken, Nancy Tuvesson, Greg Siegle, Lucas Smalldon, Bethany Stokes Expert Meeting on Empathy and Compassion September 2019 Acronym Definitions AD Alzheimer’s disease ADRD AD and related dementias BBCSS NASEM Board of Behavioral, Cognitive, and Sensory Sciences BSR NIA Division of Behavioral and Social Research bvFTD behavioral variant frontotemporal dementia CBT cognitive behavioral therapy CM compassion meditation LKM lovingkindness meditation NASEM National Academies of Science, Engineering, and Medicine NIA National Institute on Aging RCT randomized controlled trial SOBC Science of Behavior Change Acronym Definitions Page i Expert Meeting on Empathy and Compassion September 2019 Table of Contents Executive Summary ..............................................................................................................
    [Show full text]
  • A Provisional Taxonomy of Subjectively Experienced Positive Emotions
    Affective Science https://doi.org/10.1007/s42761-020-00009-7 RESEARCH ARTICLE A Provisional Taxonomy of Subjectively Experienced Positive Emotions Aaron C. Weidman1 & Jessica L. Tracy1 Received: 3 September 2019 /Accepted: 11 March 2020 # The Society for Affective Science 2020 Abstract Over the past two decades, scholars have conducted studies on the subjective experience of over 30 positive emotional states (see Weidman, Steckler, & Tracy, 2017). Yet, evidence from research on the non-verbal expression and biological correlates of positive emotions suggests that people likely experience far fewer than 30 distinct positive emotions. The present research provided an initial, lexically driven examination of how many, and which, positive emotions cohere as distinct subjective experiences, at both the state and trait levels. Four studies (including two pre-registered replications) using factor and network analyses of 5939 participants’ emotional experiences, elicited through the relived emotions task, found consistent evidence for nine distinct positive emotion states and five distinct traits. At both levels, many frequently studied positive emotions were found to overlap considerably or entirely with other ostensibly distinct states in terms of the subjective components used to describe them, suggesting that researchers currently study more positive emotions than individuals experience distinctively. These find- ings provide the first-ever comprehensive portrait of the taxonomic structure of subjectively experienced positive emotions, with
    [Show full text]
  • Challenges and Opportunities for the Affective Sciences
    Fox et al., Research Agenda for the Affective Sciences 1 Challenges and Opportunities for the Affective Sciences Andrew S. Fox* Department of Psychology and California National Primate Research Center, University of California, Davis, CA USA Regina C. Lapate* Helen Wills Neuroscience Institute, University of California, Berkeley, CA USA Richard J. Davidson Center for Healthy Minds, University of Wisconsin—Madison, Madison, WI USA Alexander J. Shackman* Department of Psychology, Neuroscience and Cognitive Science Program, and Maryland Neuroimaging Center, University of Maryland, College Park, MD USA * contributed equally Word Count: Title (7 words); Main Text (3,909/3,500); References (107) Additional Elements: 1 Figure and 1 Box Abstract: 94 words Keywords: affective neuroscience; biological psychiatry; emotion; individual differences; neuroimaging Address Correspondence to: Andrew S. Fox ([email protected]) –or– Alexander J. Shackman ([email protected]) Fox et al., Research Agenda for the Affective Sciences 2 ABSTRACT (94 words) Emotion is a core feature of the human condition, with profound consequences for health, wealth, and wellbeing. Over the past quarter-century, improved methods for manipulating and measuring different features of emotion have yielded steady advances in our scientific understanding emotional states, traits, and disorders. Yet, it is clear that most of the work remains undone. Here, we highlight key challenges facing the field of affective sciences. Addressing these challenges will provide critical opportunities not just for understanding the mind, but also for increasing the impact of the affective sciences on public health and well-being. Fox et al., Research Agenda for the Affective Sciences 3 INTRODUCTION Emotions play a central role in human experience and there is an abiding interest—among scientists, clinicians, and the public at large—in understanding their nature and determining their impact on health and disease.
    [Show full text]
  • Comparative Analysis of Joy and Awe in Four Cultures Daria B
    James Madison University JMU Scholarly Commons Dissertations The Graduate School Spring 2017 Being and beholding: Comparative analysis of joy and awe in four cultures Daria B. White James Madison University Follow this and additional works at: https://commons.lib.jmu.edu/diss201019 Part of the Counselor Education Commons, and the Multicultural Psychology Commons Recommended Citation White, Daria B., "Being and beholding: Comparative analysis of joy and awe in four cultures" (2017). Dissertations. 150. https://commons.lib.jmu.edu/diss201019/150 This Dissertation is brought to you for free and open access by the The Graduate School at JMU Scholarly Commons. It has been accepted for inclusion in Dissertations by an authorized administrator of JMU Scholarly Commons. For more information, please contact [email protected]. Being and Beholding: Comparative Analysis of Joy and Awe in Four Cultures Daria Borislavova White A dissertation submitted to the Graduate Faculty of JAMES MADISON UNIVERSITY In Partial Fulfillment of the Requirements for the degree of Doctor in Philosophy Department of Graduate Psychology May 2017 FACULTY COMMITTEE: Committee Chair: Dr. Debbie Sturm Committee Members: Dr. Lennis Echterling Dr. Cara Meixner Dedication I dedicate this dissertation to all the wonderful people who shared the most precious “eternal moments” of their lives with me. To all of you, I offer my heartfelt gratitude. I have rejoiced in reading and rereading your stories, living with your memories, learning from you all how to be be-filled and beholding. I write in remembrance of two beloved people who died in 2008 – my brother Ivaylo, whose bear hugs, warmth and sharing nature were a shelter for me, and my friend Mirela, whose pure soul, tinkling laughter and sharp intelligence are irreplaceable.
    [Show full text]
  • Computational Affective Science
    Computational Affective Science Joost Broekens [email protected] Man-Machine Interaction, TU Delft, The Netherlands In the target article, Hudlicka points out very clearly that there are several key challenges in affective computing in general and computational modeling of emotion in particular. The lack of guidelines and the sharing of best-practices as well as failures are some of those challenges. These challenges are very relevant when one is interested in the development of computational models of emotion that are focused on being applied in particular domain, for example games, virtual avatars or social robots [1]. As Hudlicka shows, choices and assumptions have to be made when developing a computational model based on, e.g., an appraisal theory. More often than not, these choices and assumptions are left unaddressed in the final publications, and rarely are the object of experimental investigation, while it is precisely these choices that make the computational model run in the first place (e.g., some representation of a goal is needed, but how is a goal represented in the agent?). Hudlicka provides an impressive overview of the different choices one has to make and the different options one has when computationally modeling emotion. It is therefore interesting to note that for many of these options it is unclear, not due to Hudlicka’s overview but due to the lack of experimental data, why one should pick one or the other if one is interested in grounding the option in emotion psychology. For example, how and when to integrate (mix) emotions is a thorny issue that is far from solved.
    [Show full text]
  • Emotion, Plasticity, Context, and Regulation: Perspectives from Affective Neuroscience
    Psychological Bulletin Copyright 2000 by the American Psychological Association, Inc. 2000, Vol. 126, No. 6, 890-909 0033-2909/00/$5.00 DOI: 10.1037//0033-2909.126.6.890 Emotion, Plasticity, Context, and Regulation: Perspectives From Affective Neuroscience Richard J. Davidson, Daren C. Jackson, and Ned H. Kalin University of Wisconsin--Madison The authors present an overview of the neural bases of emotion. They underscore the role of the prefrontal cortex (PFC) and amygdala in 2 broad approach- and withdrawal-related emotion systems. Components and measures of affective style are identified. Emphasis is given to affective chronometry and a role for the PFC in this process is proposed. Plasticity in the central circuitry of emotion is considered, and implications of data showing experience-induced changes in the hippocampus for understanding psychopathology and stress-related symptoms are discussed. Two key forms of affective plasticity are described--context and regulation. A role for the hippocampus in context-dependent normal and dysfunctional erootional responding is proposed. Finally, implications of these data for understanding the impact on neural circuitry of interventions to promote positive affect and on mecha- nisms that govern health and disease are considered. Biobehavioral scientists are increasingly recognizing the impor- change using both nonpharmacological and pharmacological in- tance of emotion for the fundamental tasks of survival and adap- tervention (Davidson, 1994a). tation (A. R. Damasio, 1994; Ekman & Davidson, 1994; Pinker, In this article, we provide a broad overview of the underlying 1997). Emotion facilitates decision making, has significant influ- biological bases of emotion with a focus on the neural circuitry at ence on learning and memory, and provides the motivation for the human level.
    [Show full text]
  • Preliminary Evidence on the Somatic Marker Hypothesis Applied to Investment Choices
    Preliminary evidence on the Somatic Marker Hypothesis applied to investment choices Article Accepted Version Cantarella, S., Hillenbrand, C., Aldridge-Waddon, L. and Puzzo, I. (2018) Preliminary evidence on the Somatic Marker Hypothesis applied to investment choices. Journal of Neuroscience, Psychology, and Economics, 11 (4). pp. 228- 238. ISSN 1937-321X doi: https://doi.org/10.1037/npe0000097 Available at http://centaur.reading.ac.uk/80454/ It is advisable to refer to the publisher’s version if you intend to cite from the work. See Guidance on citing . To link to this article DOI: http://dx.doi.org/10.1037/npe0000097 Publisher: American Psychological Association All outputs in CentAUR are protected by Intellectual Property Rights law, including copyright law. Copyright and IPR is retained by the creators or other copyright holders. Terms and conditions for use of this material are defined in the End User Agreement . www.reading.ac.uk/centaur CentAUR Central Archive at the University of Reading Reading’s research outputs online The SMH in Investment Choices Preliminary evidence on the Somatic Marker Hypothesis applied to investment choices Simona Cantarella and Carola Hillenbrand University of Reading Luke Aldridge-Waddon University of Bath Ignazio Puzzo City University of London Words count: 5058 Figures: 5 Tables: 1 Manuscript accepted on the 06/08/2018 1 The SMH in Investment Choices Abstract The somatic marker hypothesis (SMH) is one of the more dominant physiological models of human decision making and yet is seldom applied to decision making in financial investment scenarios. This study provides preliminary evidence about the application of the SMH in investment choices using heart rate (HR) and skin conductance response (SCRs) measures.
    [Show full text]
  • Kring-Moran-2008.Pdf
    Schizophrenia Bulletin vol. 34 no. 5 pp. 819–834, 2008 doi:10.1093/schbul/sbn071 Advance Access publication on June 25, 2008 Emotional Response Deficits in Schizophrenia: Insights From Affective Science Ann M. Kring1,2 and Erin K. Moran2 Many factors have contributed to the relatively recent 2Department of Psychology, University of California, Berkeley, CA increaseinresearchonemotioninschizophrenia,butacen- trally important factor has been the development and adoption of methods and theories in basic affective sci- Our understanding of the emotional features of schizophre- ence.Emotionwaslongconsideredtobethe‘‘blacksheep’’ nia has benefited greatly from the adoption of methods and of the family with respect to behaviors that could be em- theory from the field of affective science. This article covers pirically studied, but pioneering work by investigators basic concepts and methods from affective science on the psy- such as Paul Ekman and Carroll Izard in the 1960s paved chological and neural mechanisms contributing to emotions the way for emotion research to become not only well ac- and reviews the ways in which this research has advanced our cepted and integrated into psychology and neuroscience understanding of emotional response deficits in schizophre- but also as a discipline in its own right. Indeed, the explo- nia. We review naturalistic studies and elicitation studies sion of brain imaging techniques has further advanced our that evoke emotion responses among participants, including understanding of how emotion works at the level of the emotion expression, experience, and autonomic physiology. brain, and taken together, we now know a great deal about emotional behavior and its neural underpinnings (see We also consider how these emotion response mea- 4 5 sures correspond to schizophrenia symptoms, and we focus Barrett et al and Wager et al for recent reviews).
    [Show full text]
  • Discrete Emotions Or Dimensions? the Role of Valence Focus And
    COGNITION AND EMOTION, 1998, 12 (4), 579± 599 Discrete Em otions or Dim ensions? The Role of Valence Focus and Arousal Focus Lisa Feldman Barrett Boston College, Massachusetts, USA The present study provides evidence that valence focus and arousal focus are important processes in determining whether a dimensional or a discrete emotion model best captures how people label their affective states. Indivi- duals high in valence focus and low in arousal focus ® t a dimensional model better in that they reported more co-occurrences among like-valenced affec- tive states, whereas those lower in valence focus and higher in arousal focus ® t a discrete model better in that they reported fewer co-occurrences between like-valenced affective states. Taken together, these ® ndings suggest that one static, nomothetic theory may not accurately describe the subjective affective experience of all individuals. INTRODUCTION Most researchers agree that affect has at least two qualities: valence (pleasantness or hedonic value) and arousal (bodily activation). Some theorists emphasise one or the other quality as basic to affective experi- ence (e.g. Duffy, 1941; Lazarus, 1991; Ortony, Clore, & Collins, 1988; Thayer, 1989; Zajonc, 1980). Others incorporate both (e.g. Lang, 1994; Reisenzein, 1994; Russell, 1980; Schacter & Singer, 1962; Schlosberg, 1952). Even some theorists who emphasise basic discrete emotions allow a role for valence and arousal (e.g. Roseman, Spindel, & Jose, 1990; Smith & Ellsworth, 1985). There is evidence that valence and arousal are pan- cultural (Russell, 1991) and present in young children (Russell & Bullock, 1985). Requests for reprints should be sent to Dr Lisa Feldman Barrett, Department of Psychol- ogy, 427 McGuinn Hall, Boston College, Chestnut Hill, MA 02167, USA.
    [Show full text]