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James MacKillop

Bio: James MacKillop is an academic researcher from McMaster University. The author has contributed to research in topics: Medicine & Impulsivity. The author has an hindex of 66, co-authored 339 publications receiving 14376 citations. Previous affiliations of James MacKillop include Washington University in St. Louis & University of California, San Diego.
Topics: Medicine, Impulsivity, Cannabis, Craving, Addiction


Papers
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Journal ArticleDOI
TL;DR: These results provide strong evidence of greater DRD in individuals exhibiting addictive behavior in general and particularly in individuals who meet criteria for an addictive disorder.
Abstract: Rationale Delayed reward discounting (DRD) is a behavioral economic index of impulsivity and numerous studies have examined DRD in relation to addictive behavior. To synthesize the findings across the literature, the current review is a meta-analysis of studies comparing DRD between criterion groups exhibiting addictive behavior and control groups.

821 citations

Journal ArticleDOI
TL;DR: The overall goal of this review is to present a new understanding of substance use disorders as viewed by recent advances in behavioral economics.
Abstract: The field of behavioral economics has made important inroads into the understanding of substance use disorders through the concept of reinforcer pathology. Reinforcer pathology refers to the joint effects of (a) the persistently high valuation of a reinforcer, broadly defined to include tangible commodities and experiences, and/or (b) the excessive preference for the immediate acquisition or consumption of a commodity despite long-term negative outcomes. From this perspective, reinforcer pathology results from the recursive interactions of endogenous person-level variables and exogenous environment-level factors. The current review describes the basic principles of behavioral economics that are central to reinforcer pathology, the processes that engender reinforcer pathology, and the approaches and procedures that can repair reinforcement pathologies. The overall goal of this review is to present a new understanding of substance use disorders as viewed by recent advances in behavioral economics.

464 citations

Journal ArticleDOI
TL;DR: The largest genome-wide association study to date of DSM-IV-diagnosed AD found loci associated with AD and characterized the relationship between AD and other psychiatric and behavioral outcomes, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.
Abstract: Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case-control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n = 46,568; African, n = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; P = 9.8 × 10-13) and African ancestries (rs2066702; P = 2.2 × 10-9). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit-hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.

434 citations

Journal ArticleDOI
TL;DR: In this article, the authors further validated the Mindful attention and awareness scale (MAAS) in a large university sample and found that no gender differences in MAAS performance were evident, but the factor structure was not confirmed in the subsample of men.
Abstract: Mindfulness is an increasingly prominent construct in health research but its study has been impeded by a lack of well-validated measures. The Mindful Attention and Awareness Scale (MAAS; Brown and Ryan, Journal of Personality and Social Psychology, 84:822–848, 2003) is a promising measure and the goal of the present study was to further validate the MAAS in a large university sample (n = 711). Confirmatory factor analysis supported the unidimensional factor structure of the MAAS in the overall sample. No gender differences in MAAS performance were evident, but the factor structure was not confirmed in the subsample of men, apparently due to power limitations. No categorical differences were evident based on experience with meditation, and MAAS performance was not significantly associated with experience with meditation. These findings are interpreted as broadly supporting the MAAS as a valid measure of mindfulness, but suggesting that novice-level experience with meditation should not be presumed to be associated with greater mindfulness.

397 citations

Journal ArticleDOI
Richard Karlsson Linnér1, Richard Karlsson Linnér2, Pietro Biroli3, Edward Kong4, S. Fleur W. Meddens2, S. Fleur W. Meddens1, Robbee Wedow, Mark Alan Fontana5, Mark Alan Fontana6, Maël Lebreton7, Stephen P. Tino8, Abdel Abdellaoui2, Anke R. Hammerschlag2, Michel G. Nivard2, Aysu Okbay2, Cornelius A. Rietveld1, Pascal Timshel9, Pascal Timshel10, Maciej Trzaskowski11, Ronald de Vlaming2, Ronald de Vlaming1, Christian L. Zund3, Yanchun Bao12, Laura Buzdugan13, Laura Buzdugan3, Ann H. Caplin, Chia-Yen Chen4, Chia-Yen Chen14, Peter Eibich15, Peter Eibich16, Peter Eibich17, Pierre Fontanillas, Juan R. González18, Peter K. Joshi19, Ville Karhunen20, Aaron Kleinman, Remy Z. Levin21, Christina M. Lill22, Gerardus A. Meddens, Gerard Muntané23, Gerard Muntané18, Sandra Sanchez-Roige21, Frank J. A. van Rooij1, Erdogan Taskesen2, Yang Wu11, Futao Zhang11, Adam Auton, Jason D. Boardman24, David W. Clark19, Andrew Conlin20, Conor C. Dolan2, Urs Fischbacher25, Patrick J. F. Groenen1, Kathleen Mullan Harris26, Gregor Hasler27, Albert Hofman1, Albert Hofman4, Mohammad Arfan Ikram1, Sonia Jain21, Robert Karlsson28, Ronald C. Kessler4, Maarten Kooyman, James MacKillop29, James MacKillop30, Minna Männikkö20, Carlos Morcillo-Suarez18, Matthew B. McQueen24, Klaus M. Schmidt31, Melissa C. Smart12, Matthias Sutter17, Matthias Sutter32, Matthias Sutter33, Roy Thurik1, André G. Uitterlinden1, Jon White34, Harriet de Wit35, Jian Yang11, Lars Bertram22, Lars Bertram36, Dorret I. Boomsma2, Tõnu Esko37, Ernst Fehr3, David A. Hinds, Magnus Johannesson38, Meena Kumari12, David Laibson4, Patrik K. E. Magnusson28, Michelle N. Meyer39, Arcadi Navarro18, Arcadi Navarro40, Abraham A. Palmer21, Tune H. Pers9, Tune H. Pers10, Danielle Posthuma2, Daniel Schunk41, Murray B. Stein21, Rauli Svento20, Henning Tiemeier1, Paul R. H. J. Timmers19, Patrick Turley4, Patrick Turley14, Patrick Turley42, Robert J. Ursano43, Gert G. Wagner17, Gert G. Wagner16, James F. Wilson44, James F. Wilson19, Jacob Gratten45, Jacob Gratten11, James J. Lee46, David Cesarini47, Daniel J. Benjamin48, Daniel J. Benjamin42, Philipp Koellinger16, Philipp Koellinger2, Jonathan P. Beauchamp8 
TL;DR: This paper found evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of their other GWAS, and general risk-tolerance is genetically correlated with a range of risky behaviors.
Abstract: Humans vary substantially in their willingness to take risks. In a combined sample of over 1 million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. Across all GWAS, we identified hundreds of associated loci, including 99 loci associated with general risk tolerance. We report evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is genetically correlated ([Formula: see text] ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near SNPs associated with general risk tolerance are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We found no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.

395 citations


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01 Jan 2016
TL;DR: The using multivariate statistics is universally compatible with any devices to read, allowing you to get the most less latency time to download any of the authors' books like this one.
Abstract: Thank you for downloading using multivariate statistics. As you may know, people have look hundreds times for their favorite novels like this using multivariate statistics, but end up in infectious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they juggled with some harmful bugs inside their laptop. using multivariate statistics is available in our digital library an online access to it is set as public so you can download it instantly. Our books collection saves in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the using multivariate statistics is universally compatible with any devices to read.

14,604 citations

Journal ArticleDOI
TL;DR: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols used xiii 1.
Abstract: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

14,171 citations

Journal Article
TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

9,847 citations

Journal ArticleDOI
TL;DR: It is shown that the average statistical power of studies in the neurosciences is very low, and the consequences include overestimates of effect size and low reproducibility of results.
Abstract: A study with low statistical power has a reduced chance of detecting a true effect, but it is less well appreciated that low power also reduces the likelihood that a statistically significant result reflects a true effect. Here, we show that the average statistical power of studies in the neurosciences is very low. The consequences of this include overestimates of effect size and low reproducibility of results. There are also ethical dimensions to this problem, as unreliable research is inefficient and wasteful. Improving reproducibility in neuroscience is a key priority and requires attention to well-established but often ignored methodological principles.

5,683 citations