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4 Associations Between Glycemia and Cognitive Performance in Adults with Type 1 Diabetes (T1D) using Continuous Glucose Monitoring (CGM) and Ecological Momentary Assessment (EMA)
- Olivia H Wang, Miranda Zuniga-Kennedy, Luciana Mascarenhas Fonseca, Michael Cleveland, Zoe W. Hawks, Lanee Jung, Jane D. Bulger, Elizabeth Grinspoon, Shifali Singh, Martin Sliwinski, Alandra Verdejo, Ruth S. Weinstock, Laura Germine, Naomi Chaytor
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 792-793
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Objective:
Despite associations between hypoglycemia and cognitive performance using cross-sectional and experimental methods (e.g., Insulin clamp studies), few studies have evaluated this relationship in a naturalistic setting. This pilot study utilizes an EMA study design in adults with T1D to examine the impact of hypoglycemia and hyperglycemia, measured using CGM, on cognitive performance, measured via ambulatory assessment.
Participants and Methods:Twenty adults with T1D (mean age 38.9 years, range 26-67; 55% female; 55% bachelor’s degree or higher; mean HbA1c = 8.3%, range 5.4% - 12.5%), were recruited from the Joslin Diabetes Center at SUNY Upstate Medical University. A blinded Dexcom G6 CGM was worn during everyday activities while completing 3-6 daily EMAs using personal smartphones. EMAs were delivered between 9 am and 9 pm, for 15 days. EMAs included 3 brief cognitive tests developed by testmybrain.org and validated for brief mobile administration (Gradual Onset CPT d-prime, Digit Symbol Matching median reaction time, Multiple Object Tracking percent accuracy) and self-reported momentary negative affect. Day-level average scores were calculated for the cognitive and negative affect measures. Hypoglycemia and hyperglycemia were defined as the percentage of time spent with a sensor glucose value <70 mg/dL or > 180 mg/dL, respectively. Daytime (8 am to 9 pm) and nighttime (9 pm to 8 am) glycemic excursions were calculated separately. Multilevel models estimated the between- and within-person association between the night prior to, or the same day, time spent in hypoglycemia or hyperglycemia and cognitive performance (each cognitive test was modeled separately). To evaluate the effect of between-person differences, person-level variables were calculated as the mean across the study and grand-mean centered. To evaluate the effect of within-person fluctuations, day-level variables were calculated as deviations from these person-level means.
Results:Within-person fluctuations in nighttime hypoglycemia were associated with daytime processing speed. Specifically, participants who spent a higher percentage of time in hypoglycemia than their average percentage the night prior to assessment performed slower than their average performance on the processing speed test (Digit Symbol Matching median reaction time, b = 94.16, p = 0.042), while same day variation in hypoglycemia was not associated with variation in Digit Symbol Matching performance. This association remained significant (b = 97.46, p = 0.037) after controlling for within-person and between-person effects of negative affect. There were no significant within-person associations between time spent in hyperglycemia and Digit Symbol Matching, nor day/night hypoglycemia or hyperglycemia and Gradual Onset CPT or Multiple Object Tracking.
Conclusions:Our findings from this EMA study suggest that when individuals with T1D experience more time in hypoglycemia at night (compared to their average), they have slower processing speed the following day, while same day hypoglycemia and hyperglycemia does not similarly impact processing speed performance. These results showcase the power of intensive longitudinal designs using ambulatory cognitive assessment to uncover novel determinants of cognitive variation in real world settings that have direct clinical applications for optimizing cognitive performance. Future research with larger samples is needed to replicate these findings.
Pro-inflammatory markers are associated with response to sequential pharmacotherapy in major depressive disorder: a CAN-BIND-1 report
- M. Ishrat Husain, Jane A. Foster, Brittany L. Mason, Sheng Chen, Haoyu Zhao, Wei Wang, Susan Rotzinger, Sakina Rizvi, Keith Ho, Raymond Lam, Glenda MacQueen, Roumen Milev, Benicio N. Frey, Daniel Müller, Gustavo Turecki, Manish Jha, Madhukar Trivedi, Sidney H. Kennedy
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- Journal:
- CNS Spectrums / Volume 28 / Issue 6 / December 2023
- Published online by Cambridge University Press:
- 23 May 2023, pp. 739-746
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Objective
There is limited literature on associations between inflammatory tone and response to sequential pharmacotherapies in major depressive disorder (MDD).
MethodsIn a 16-week open-label clinical trial, 211 participants with MDD were treated with escitalopram 10–20 mg daily for 8 weeks. Responders continued escitalopram while non-responders received adjunctive aripiprazole 2–10 mg daily for 8 weeks. Plasma levels of pro-inflammatory markers—C-reactive protein, interleukin (IL)-1β, IL-6, IL-17, interferon-gamma (IFN)-Γ, tumor necrosis factor (TNF)-α, and Chemokine C–C motif ligand-2 (CCL-2)—measured at baseline, and after 2, 8 and 16 weeks were included in logistic regression analyzes to assess associations between inflammatory markers and treatment response.
ResultsPre-treatment IFN-Γ and CCL-2 levels were significantly associated with a lower of odds of response to escitalopram at 8 weeks. Increases in CCL-2 levels from weeks 8 to 16 in escitalopram non-responders were significantly associated with higher odds of non-response to adjunctive aripiprazole at week 16.
ConclusionHigher pre-treatment levels of IFN-Γ and CCL-2 were associated with non-response to escitalopram. Increasing levels of these pro-inflammatory markers may be associated with non-response to adjunctive aripiprazole. These findings require validation in independent clinical populations.
Prediction of depression treatment outcome from multimodal data: a CAN-BIND-1 report
- Mehri Sajjadian, Rudolf Uher, Keith Ho, Stefanie Hassel, Roumen Milev, Benicio N. Frey, Faranak Farzan, Pierre Blier, Jane A. Foster, Sagar V. Parikh, Daniel J. Müller, Susan Rotzinger, Claudio N. Soares, Gustavo Turecki, Valerie H. Taylor, Raymond W. Lam, Stephen C. Strother, Sidney H. Kennedy
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- Journal:
- Psychological Medicine / Volume 53 / Issue 12 / September 2023
- Published online by Cambridge University Press:
- 25 August 2022, pp. 5374-5384
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Background
Prediction of treatment outcomes is a key step in improving the treatment of major depressive disorder (MDD). The Canadian Biomarker Integration Network in Depression (CAN-BIND) aims to predict antidepressant treatment outcomes through analyses of clinical assessment, neuroimaging, and blood biomarkers.
MethodsIn the CAN-BIND-1 dataset of 192 adults with MDD and outcomes of treatment with escitalopram, we applied machine learning models in a nested cross-validation framework. Across 210 analyses, we examined combinations of predictive variables from three modalities, measured at baseline and after 2 weeks of treatment, and five machine learning methods with and without feature selection. To optimize the predictors-to-observations ratio, we followed a tiered approach with 134 and 1152 variables in tier 1 and tier 2 respectively.
ResultsA combination of baseline tier 1 clinical, neuroimaging, and molecular variables predicted response with a mean balanced accuracy of 0.57 (best model mean 0.62) compared to 0.54 (best model mean 0.61) in single modality models. Adding week 2 predictors improved the prediction of response to a mean balanced accuracy of 0.59 (best model mean 0.66). Adding tier 2 features did not improve prediction.
ConclusionsA combination of clinical, neuroimaging, and molecular data improves the prediction of treatment outcomes over single modality measurement. The addition of measurements from the early stages of treatment adds precision. Present results are limited by lack of external validation. To achieve clinically meaningful prediction, the multimodal measurement should be scaled up to larger samples and the robustness of prediction tested in an external validation dataset.
Children in foster care with symptoms of reactive attachment disorder: feasibility randomised controlled trial of a modified video-feedback parenting intervention
- Paula Oliveira, Lydia Barge, Eloise Stevens, Sarah Byford, James Shearer, Ruan Spies, Julie Comyn, Kirsty Langley, Paul Ramchandani, Barry Wright, Matt Woolgar, Eilis Kennedy, Stephen Scott, Jane Barlow, Danya Glaser, Rob Senior, Peter Fonagy, Pasco Fearon
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- Journal:
- BJPsych Open / Volume 8 / Issue 4 / July 2022
- Published online by Cambridge University Press:
- 18 July 2022, e134
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Background
Looked-after children are at risk of suboptimal attachment patterns and reactive attachment disorder (RAD). However, access to interventions varies widely, and there are no evidence-based interventions for RAD.
AimsTo modify an existing parenting intervention for children with RAD in the UK foster care setting, and test the feasibility of conducting a randomised controlled trial (RCT) of the modified intervention.
MethodThe intervention was modified with expert input and tested on a case series. A feasibility and pilot RCT compared the new intervention with usual care. Foster carers and children in their care aged ≤6 years were recruited across nine local authorities, with 1:1 allocation and blind post-treatment assessments. The modified intervention was delivered in-home by trained mental health professionals over 4–6 months. Children were assessed for RAD symptoms, attachment quality and emotional/behavioural difficulties, and foster carers were assessed for sensitivity and stress.
ResultsMinimal changes to the intervention programme were necessary, and focused on improving its suitability for the UK foster care context. Recruitment was challenging, and remained below target despite modifications to the protocol and the inclusion of additional sites. Thirty families were recruited to the RCT; 15 were allocated to each group. Most other feasibility outcomes were favourable, particularly high numbers of data and treatment completeness. The revised intervention was positively received by practitioners and foster carers.
ConclusionsA large-scale trial may be feasible, but only if recruitment barriers can be overcome. Dedicated resources to support recruitment within local authorities and wider inclusion criteria are recommended.
Machine learning in the prediction of depression treatment outcomes: a systematic review and meta-analysis
- Mehri Sajjadian, Raymond W. Lam, Roumen Milev, Susan Rotzinger, Benicio N. Frey, Claudio N. Soares, Sagar V. Parikh, Jane A. Foster, Gustavo Turecki, Daniel J. Müller, Stephen C. Strother, Faranak Farzan, Sidney H. Kennedy, Rudolf Uher
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- Journal:
- Psychological Medicine / Volume 51 / Issue 16 / December 2021
- Published online by Cambridge University Press:
- 12 October 2021, pp. 2742-2751
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Background
Multiple treatments are effective for major depressive disorder (MDD), but the outcomes of each treatment vary broadly among individuals. Accurate prediction of outcomes is needed to help select a treatment that is likely to work for a given person. We aim to examine the performance of machine learning methods in delivering replicable predictions of treatment outcomes.
MethodsOf 7732 non-duplicate records identified through literature search, we retained 59 eligible reports and extracted data on sample, treatment, predictors, machine learning method, and treatment outcome prediction. A minimum sample size of 100 and an adequate validation method were used to identify adequate-quality studies. The effects of study features on prediction accuracy were tested with mixed-effects models. Fifty-four of the studies provided accuracy estimates or other estimates that allowed calculation of balanced accuracy of predicting outcomes of treatment.
ResultsEight adequate-quality studies reported a mean accuracy of 0.63 [95% confidence interval (CI) 0.56–0.71], which was significantly lower than a mean accuracy of 0.75 (95% CI 0.72–0.78) in the other 46 studies. Among the adequate-quality studies, accuracies were higher when predicting treatment resistance (0.69) and lower when predicting remission (0.60) or response (0.56). The choice of machine learning method, feature selection, and the ratio of features to individuals were not associated with reported accuracy.
ConclusionsThe negative relationship between study quality and prediction accuracy, combined with a lack of independent replication, invites caution when evaluating the potential of machine learning applications for personalizing the treatment of depression.
The mustatils: cult and monumentality in Neolithic north-western Arabia
- Hugh Thomas, Melissa A. Kennedy, Matthew Dalton, Jane McMahon, David Boyer, Rebecca Repper
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North-western Arabia is marked by thousands of prehistoric stone structures. Of these, the monumental, rectilinear type known as mustatils has received only limited attention. Recent fieldwork in AlUla and Khaybar Counties, Saudi Arabia, demonstrates that these monuments are architecturally more complex than previously supposed, featuring chambers, entranceways and orthostats. These structures can now be interpreted as ritual installations dating back to the late sixth millennium BC, with recent excavations revealing the earliest evidence for a cattle cult in the Arabian Peninsula. As such, mustatils are amongst the earliest stone monuments in Arabia and globally one of the oldest monumental building traditions yet identified.
Contributors
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- By Mitchell Aboulafia, Frederick Adams, Marilyn McCord Adams, Robert M. Adams, Laird Addis, James W. Allard, David Allison, William P. Alston, Karl Ameriks, C. Anthony Anderson, David Leech Anderson, Lanier Anderson, Roger Ariew, David Armstrong, Denis G. Arnold, E. J. Ashworth, Margaret Atherton, Robin Attfield, Bruce Aune, Edward Wilson Averill, Jody Azzouni, Kent Bach, Andrew Bailey, Lynne Rudder Baker, Thomas R. Baldwin, Jon Barwise, George Bealer, William Bechtel, Lawrence C. Becker, Mark A. Bedau, Ernst Behler, José A. Benardete, Ermanno Bencivenga, Jan Berg, Michael Bergmann, Robert L. Bernasconi, Sven Bernecker, Bernard Berofsky, Rod Bertolet, Charles J. Beyer, Christian Beyer, Joseph Bien, Joseph Bien, Peg Birmingham, Ivan Boh, James Bohman, Daniel Bonevac, Laurence BonJour, William J. Bouwsma, Raymond D. Bradley, Myles Brand, Richard B. Brandt, Michael E. Bratman, Stephen E. Braude, Daniel Breazeale, Angela Breitenbach, Jason Bridges, David O. Brink, Gordon G. Brittan, Justin Broackes, Dan W. Brock, Aaron Bronfman, Jeffrey E. Brower, Bartosz Brozek, Anthony Brueckner, Jeffrey Bub, Lara Buchak, Otavio Bueno, Ann E. Bumpus, Robert W. Burch, John Burgess, Arthur W. Burks, Panayot Butchvarov, Robert E. Butts, Marina Bykova, Patrick Byrne, David Carr, Noël Carroll, Edward S. Casey, Victor Caston, Victor Caston, Albert Casullo, Robert L. Causey, Alan K. L. Chan, Ruth Chang, Deen K. Chatterjee, Andrew Chignell, Roderick M. Chisholm, Kelly J. Clark, E. J. Coffman, Robin Collins, Brian P. Copenhaver, John Corcoran, John Cottingham, Roger Crisp, Frederick J. Crosson, Antonio S. Cua, Phillip D. Cummins, Martin Curd, Adam Cureton, Andrew Cutrofello, Stephen Darwall, Paul Sheldon Davies, Wayne A. Davis, Timothy Joseph Day, Claudio de Almeida, Mario De Caro, Mario De Caro, John Deigh, C. F. Delaney, Daniel C. Dennett, Michael R. DePaul, Michael Detlefsen, Daniel Trent Devereux, Philip E. Devine, John M. Dillon, Martin C. Dillon, Robert DiSalle, Mary Domski, Alan Donagan, Paul Draper, Fred Dretske, Mircea Dumitru, Wilhelm Dupré, Gerald Dworkin, John Earman, Ellery Eells, Catherine Z. Elgin, Berent Enç, Ronald P. Endicott, Edward Erwin, John Etchemendy, C. Stephen Evans, Susan L. Feagin, Solomon Feferman, Richard Feldman, Arthur Fine, Maurice A. Finocchiaro, William FitzPatrick, Richard E. Flathman, Gvozden Flego, Richard Foley, Graeme Forbes, Rainer Forst, Malcolm R. Forster, Daniel Fouke, Patrick Francken, Samuel Freeman, Elizabeth Fricker, Miranda Fricker, Michael Friedman, Michael Fuerstein, Richard A. Fumerton, Alan Gabbey, Pieranna Garavaso, Daniel Garber, Jorge L. A. Garcia, Robert K. Garcia, Don Garrett, Philip Gasper, Gerald Gaus, Berys Gaut, Bernard Gert, Roger F. Gibson, Cody Gilmore, Carl Ginet, Alan H. Goldman, Alvin I. Goldman, Alfonso Gömez-Lobo, Lenn E. Goodman, Robert M. Gordon, Stefan Gosepath, Jorge J. E. Gracia, Daniel W. Graham, George A. Graham, Peter J. Graham, Richard E. Grandy, I. Grattan-Guinness, John Greco, Philip T. Grier, Nicholas Griffin, Nicholas Griffin, David A. Griffiths, Paul J. Griffiths, Stephen R. Grimm, Charles L. Griswold, Charles B. Guignon, Pete A. Y. Gunter, Dimitri Gutas, Gary Gutting, Paul Guyer, Kwame Gyekye, Oscar A. Haac, Raul Hakli, Raul Hakli, Michael Hallett, Edward C. Halper, Jean Hampton, R. James Hankinson, K. R. Hanley, Russell Hardin, Robert M. Harnish, William Harper, David Harrah, Kevin Hart, Ali Hasan, William Hasker, John Haugeland, Roger Hausheer, William Heald, Peter Heath, Richard Heck, John F. Heil, Vincent F. Hendricks, Stephen Hetherington, Francis Heylighen, Kathleen Marie Higgins, Risto Hilpinen, Harold T. Hodes, Joshua Hoffman, Alan Holland, Robert L. Holmes, Richard Holton, Brad W. Hooker, Terence E. Horgan, Tamara Horowitz, Paul Horwich, Vittorio Hösle, Paul Hoβfeld, Daniel Howard-Snyder, Frances Howard-Snyder, Anne Hudson, Deal W. Hudson, Carl A. Huffman, David L. Hull, Patricia Huntington, Thomas Hurka, Paul Hurley, Rosalind Hursthouse, Guillermo Hurtado, Ronald E. Hustwit, Sarah Hutton, Jonathan Jenkins Ichikawa, Harry A. Ide, David Ingram, Philip J. Ivanhoe, Alfred L. Ivry, Frank Jackson, Dale Jacquette, Joseph Jedwab, Richard Jeffrey, David Alan Johnson, Edward Johnson, Mark D. Jordan, Richard Joyce, Hwa Yol Jung, Robert Hillary Kane, Tomis Kapitan, Jacquelyn Ann K. Kegley, James A. Keller, Ralph Kennedy, Sergei Khoruzhii, Jaegwon Kim, Yersu Kim, Nathan L. King, Patricia Kitcher, Peter D. Klein, E. D. Klemke, Virginia Klenk, George L. Kline, Christian Klotz, Simo Knuuttila, Joseph J. Kockelmans, Konstantin Kolenda, Sebastian Tomasz Kołodziejczyk, Isaac Kramnick, Richard Kraut, Fred Kroon, Manfred Kuehn, Steven T. Kuhn, Henry E. Kyburg, John Lachs, Jennifer Lackey, Stephen E. Lahey, Andrea Lavazza, Thomas H. Leahey, Joo Heung Lee, Keith Lehrer, Dorothy Leland, Noah M. Lemos, Ernest LePore, Sarah-Jane Leslie, Isaac Levi, Andrew Levine, Alan E. Lewis, Daniel E. Little, Shu-hsien Liu, Shu-hsien Liu, Alan K. L. Chan, Brian Loar, Lawrence B. Lombard, John Longeway, Dominic McIver Lopes, Michael J. Loux, E. J. Lowe, Steven Luper, Eugene C. Luschei, William G. Lycan, David Lyons, David Macarthur, Danielle Macbeth, Scott MacDonald, Jacob L. Mackey, Louis H. Mackey, Penelope Mackie, Edward H. Madden, Penelope Maddy, G. B. Madison, Bernd Magnus, Pekka Mäkelä, Rudolf A. Makkreel, David Manley, William E. Mann (W.E.M.), Vladimir Marchenkov, Peter Markie, Jean-Pierre Marquis, Ausonio Marras, Mike W. Martin, A. P. Martinich, William L. McBride, David McCabe, Storrs McCall, Hugh J. McCann, Robert N. McCauley, John J. McDermott, Sarah McGrath, Ralph McInerny, Daniel J. McKaughan, Thomas McKay, Michael McKinsey, Brian P. McLaughlin, Ernan McMullin, Anthonie Meijers, Jack W. Meiland, William Jason Melanson, Alfred R. Mele, Joseph R. Mendola, Christopher Menzel, Michael J. Meyer, Christian B. Miller, David W. Miller, Peter Millican, Robert N. Minor, Phillip Mitsis, James A. Montmarquet, Michael S. Moore, Tim Moore, Benjamin Morison, Donald R. Morrison, Stephen J. Morse, Paul K. Moser, Alexander P. D. Mourelatos, Ian Mueller, James Bernard Murphy, Mark C. Murphy, Steven Nadler, Jan Narveson, Alan Nelson, Jerome Neu, Samuel Newlands, Kai Nielsen, Ilkka Niiniluoto, Carlos G. Noreña, Calvin G. Normore, David Fate Norton, Nikolaj Nottelmann, Donald Nute, David S. Oderberg, Steve Odin, Michael O’Rourke, Willard G. Oxtoby, Heinz Paetzold, George S. Pappas, Anthony J. Parel, Lydia Patton, R. P. Peerenboom, Francis Jeffry Pelletier, Adriaan T. Peperzak, Derk Pereboom, Jaroslav Peregrin, Glen Pettigrove, Philip Pettit, Edmund L. Pincoffs, Andrew Pinsent, Robert B. Pippin, Alvin Plantinga, Louis P. Pojman, Richard H. Popkin, John F. Post, Carl J. Posy, William J. Prior, Richard Purtill, Michael Quante, Philip L. Quinn, Philip L. Quinn, Elizabeth S. Radcliffe, Diana Raffman, Gerard Raulet, Stephen L. Read, Andrews Reath, Andrew Reisner, Nicholas Rescher, Henry S. Richardson, Robert C. Richardson, Thomas Ricketts, Wayne D. Riggs, Mark Roberts, Robert C. Roberts, Luke Robinson, Alexander Rosenberg, Gary Rosenkranz, Bernice Glatzer Rosenthal, Adina L. Roskies, William L. Rowe, T. M. Rudavsky, Michael Ruse, Bruce Russell, Lilly-Marlene Russow, Dan Ryder, R. M. Sainsbury, Joseph Salerno, Nathan Salmon, Wesley C. Salmon, Constantine Sandis, David H. Sanford, Marco Santambrogio, David Sapire, Ruth A. Saunders, Geoffrey Sayre-McCord, Charles Sayward, James P. Scanlan, Richard Schacht, Tamar Schapiro, Frederick F. Schmitt, Jerome B. Schneewind, Calvin O. Schrag, Alan D. Schrift, George F. Schumm, Jean-Loup Seban, David N. Sedley, Kenneth Seeskin, Krister Segerberg, Charlene Haddock Seigfried, Dennis M. Senchuk, James F. Sennett, William Lad Sessions, Stewart Shapiro, Tommie Shelby, Donald W. Sherburne, Christopher Shields, Roger A. Shiner, Sydney Shoemaker, Robert K. Shope, Kwong-loi Shun, Wilfried Sieg, A. John Simmons, Robert L. Simon, Marcus G. Singer, Georgette Sinkler, Walter Sinnott-Armstrong, Matti T. Sintonen, Lawrence Sklar, Brian Skyrms, Robert C. Sleigh, Michael Anthony Slote, Hans Sluga, Barry Smith, Michael Smith, Robin Smith, Robert Sokolowski, Robert C. Solomon, Marta Soniewicka, Philip Soper, Ernest Sosa, Nicholas Southwood, Paul Vincent Spade, T. L. S. Sprigge, Eric O. Springsted, George J. Stack, Rebecca Stangl, Jason Stanley, Florian Steinberger, Sören Stenlund, Christopher Stephens, James P. Sterba, Josef Stern, Matthias Steup, M. A. Stewart, Leopold Stubenberg, Edith Dudley Sulla, Frederick Suppe, Jere Paul Surber, David George Sussman, Sigrún Svavarsdóttir, Zeno G. Swijtink, Richard Swinburne, Charles C. Taliaferro, Robert B. Talisse, John Tasioulas, Paul Teller, Larry S. Temkin, Mark Textor, H. S. Thayer, Peter Thielke, Alan Thomas, Amie L. Thomasson, Katherine Thomson-Jones, Joshua C. Thurow, Vzalerie Tiberius, Terrence N. Tice, Paul Tidman, Mark C. Timmons, William Tolhurst, James E. Tomberlin, Rosemarie Tong, Lawrence Torcello, Kelly Trogdon, J. D. Trout, Robert E. Tully, Raimo Tuomela, John Turri, Martin M. Tweedale, Thomas Uebel, Jennifer Uleman, James Van Cleve, Harry van der Linden, Peter van Inwagen, Bryan W. Van Norden, René van Woudenberg, Donald Phillip Verene, Samantha Vice, Thomas Vinci, Donald Wayne Viney, Barbara Von Eckardt, Peter B. M. Vranas, Steven J. Wagner, William J. Wainwright, Paul E. Walker, Robert E. Wall, Craig Walton, Douglas Walton, Eric Watkins, Richard A. Watson, Michael V. Wedin, Rudolph H. Weingartner, Paul Weirich, Paul J. Weithman, Carl Wellman, Howard Wettstein, Samuel C. Wheeler, Stephen A. White, Jennifer Whiting, Edward R. Wierenga, Michael Williams, Fred Wilson, W. Kent Wilson, Kenneth P. Winkler, John F. Wippel, Jan Woleński, Allan B. Wolter, Nicholas P. Wolterstorff, Rega Wood, W. Jay Wood, Paul Woodruff, Alison Wylie, Gideon Yaffe, Takashi Yagisawa, Yutaka Yamamoto, Keith E. Yandell, Xiaomei Yang, Dean Zimmerman, Günter Zoller, Catherine Zuckert, Michael Zuckert, Jack A. Zupko (J.A.Z.)
- Edited by Robert Audi, University of Notre Dame, Indiana
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- The Cambridge Dictionary of Philosophy
- Published online:
- 05 August 2015
- Print publication:
- 27 April 2015, pp ix-xxx
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- By Michael H. Allen, Leora Amira, Victoria Arango, David W. Ayer, Helene Bach, Christopher R. Bailey, Ross J. Baldessarini, Kelsey Ball, Alan L. Berman, Marian E. Betz, Emily A. Biggs, R. Warwick Blood, Kathleen T. Brady, David A. Brent, Jeffrey A. Bridge, Gregory K. Brown, Anat Brunstein Klomek, A. Jacqueline Buchanan, Michelle J. Chandley, Tim Coffey, Jessica Coker, Yeates Conwell, Scott J. Crow, Collin L. Davidson, Yogesh Dwivedi, Stacey Espaillat, Jan Fawcett, Steven J. Garlow, Robert D. Gibbons, Catherine R. Glenn, Deborah Goebert, Erica Goldstein, Tina R. Goldstein, Madelyn S. Gould, Kelly L. Green, Alison M. Greene, Philip D. Harvey, Robert M. A. Hirschfeld, Donna Holland Barnes, Andres M. Kanner, Gary J. Kennedy, Stephen H. Koslow, Benoit Labonté, Alison M. Lake, William B. Lawson, Steve Leifman, Adam Lesser, Timothy W. Lineberry, Amanda L. McMillan, Herbert Y. Meltzer, Michael Craig Miller, Michael J. Miller, James A. Naifeh, Katharine J. Nelson, Charles B. Nemeroff, Alexander Neumeister, Matthew K. Nock, Jennifer H. Olson-Madden, Gregory A. Ordway, Michael W. Otto, Ghanshyam N. Pandey, Giampaolo Perna, Jane Pirkis, Kelly Posner, Anne Rohs, Pedro Ruiz, Molly Ryan, Alan F. Schatzberg, S. Charles Schulz, M. Katherine Shear, Morton M. Silverman, April R. Smith, Marcus Sokolowski, Barbara Stanley, Zachary N. Stowe, Sarah A. Struthers, Leonardo Tondo, Gustavo Turecki, Robert J. Ursano, Kimberly Van Orden, Anne C. Ward, Danuta Wasserman, Jerzy Wasserman, Melinda K. Westlund, Tracy K. Witte, Kseniya Yershova, Alexandra Zagoloff, Sidney Zisook
- Edited by Stephen H. Koslow, University of Miami, Pedro Ruiz, University of Miami, Charles B. Nemeroff, University of Miami
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- A Concise Guide to Understanding Suicide
- Published online:
- 05 October 2014
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- 18 September 2014, pp vii-x
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- By Mina Alikani, Renate Barber, Christian Becker, Jane Chan, Tim Child, Jacques Cohen, Lorraine Corfield, Kevin Coward, Jo Craig, Janet Currie, Farah El-Sadi, Kornelia Ewald, Elpida Fragouli, Joaquin Gadea, Richard Gardner, Gustavo German, Ingrid Granne, Andy Greenfield, Tracey Griffiths, Geraldine Hartshorne, William V. Holt, Aysha Itani, Paul R V Johnson, Celine Jones, Junaid Kashir, Stephen Kennedy, James Lawford Davies, Janelle Luk, Enda McVeigh, Janis Meek, Jane M. Morrell, Anas Nader, John Parrington, Pasquale Patrizio, Caroline Ross, Autumn Rowan-Hull, Ian Sargent, Bianka Seres, Alison Shaw, Shankar Srinivas, Alan R Thornhill, Karen Turner, Nicolas Vulliemoz, Tomoko Watanabe, Dagan Wells, Suzannah A Williams
- Edited by Kevin Coward, Dagan Wells
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- Textbook of Clinical Embryology
- Published online:
- 05 November 2013
- Print publication:
- 31 October 2013, pp vii-x
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Locating the Dust in A Star Debris Discs
- Mark Booth, Grant Kennedy, Bruce Sibthorpe, Brenda C. Matthews, Mark C. Wyatt, Gaspard Duchêne, J. J. Kavelaars, David Rodriguez, Jane S. Greaves, Alice Koning, Laura Vican, George H. Rieke, Kate Y. L. Su, Amaya Moro-Martín, Paul Kalas
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- Journal:
- Proceedings of the International Astronomical Union / Volume 8 / Issue S299 / June 2013
- Published online by Cambridge University Press:
- 06 January 2014, pp. 330-331
- Print publication:
- June 2013
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Using photometry at just two wavelengths it is possible to fit a blackbody to the spectrum of infrared excess that is the signature of a debris disc. From this the location of the dust can be inferred. However, it is well known that dust in debris discs is not a perfect blackbody. By resolving debris discs we can find the actual location of the dust and compare this to that inferred from the blackbody fit. Using the Herschel Space Observatory we resolved many systems as part of the DEBRIS survey. Here we discuss a sample of 9 discs surrounding A stars and find that the discs are actually located between 1 and 2.5 times further from their star than predicted by blackbody fits to the spectral energy distribution (SED). The variation in this ratio is due to differences in stellar luminosities, location of the dust, size distribution and composition of the dust.
Genes, Environments, and Developmental Research: Methods for a Multi-Site Study of Early Substance Abuse
- E. Jane Costello, Lindon Eaves, Patrick Sullivan, Martin Kennedy, Kevin Conway, Daniel E. Adkins, A. Angold, Shaunna L. Clark, Alaattin Erkanli, Joseph L. McClay, William Copeland, Hermine H. Maes, Youfang Liu, Ashwin A. Patkar, Judy Silberg, Edwin van den Oord
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- Journal:
- Twin Research and Human Genetics / Volume 16 / Issue 2 / April 2013
- Published online by Cambridge University Press:
- 06 March 2013, pp. 505-515
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The importance of including developmental and environmental measures in genetic studies of human pathology is widely acknowledged, but few empirical studies have been published. Barriers include the need for longitudinal studies that cover relevant developmental stages and for samples large enough to deal with the challenge of testing gene–environment–development interaction. A solution to some of these problems is to bring together existing data sets that have the necessary characteristics. As part of the National Institute on Drug Abuse-funded Gene-Environment-Development Initiative, our goal is to identify exactly which genes, which environments, and which developmental transitions together predict the development of drug use and misuse. Four data sets were used of which common characteristics include (1) general population samples, including males and females; (2) repeated measures across adolescence and young adulthood; (3) assessment of nicotine, alcohol, and cannabis use and addiction; (4) measures of family and environmental risk; and (5) consent for genotyping DNA from blood or saliva. After quality controls, 2,962 individuals provided over 15,000 total observations. In the first gene–environment analyses, of alcohol misuse and stressful life events, some significant gene–environment and gene–development effects were identified. We conclude that in some circumstances, already collected data sets can be combined for gene–environment and gene–development analyses. This greatly reduces the cost and time needed for this type of research. However, care must be taken to ensure careful matching across studies and variables.
Suicide and other causes of mortality in bipolar disorder: a longitudinal study
- RINA DUTTA, JANE BOYDELL, NOEL KENNEDY, JIM VAN OS, PAUL FEARON, ROBIN M. MURRAY
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- Journal:
- Psychological Medicine / Volume 37 / Issue 6 / June 2007
- Published online by Cambridge University Press:
- 12 March 2007, pp. 839-847
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Background. The high risk of suicide in bipolar disorder is well recognized, but may have been overestimated. There is conflicting evidence about deaths from other causes and little known about risk factors for suicide. We aimed to estimate suicide and mortality rates in a cohort of bipolar patients and to identify risk factors for suicide.
Method. All patients who presented for the first time with a DSM-IV diagnosis of bipolar I disorder in a defined area of southeast London over a 35-year period (1965–1999) were identified. Mortality rates were compared with those of the 1991 England and Wales population, indirectly standardized for age and gender. Univariate and multivariate analyses were used to test potential risk factors for suicide.
Results. Of the 239 patients in the cohort, 235 (98·3%) were traced. Forty-two died during the 4422 person-years of follow-up, eight from suicide. The standardized mortality ratio (SMR) for suicide was 9·77 [95% confidence interval (CI) 4·22–19·24], which, although significantly elevated compared to the general population, represented a lower case fatality than expected from previous literature. Deaths from all other causes were not excessive for the age groups studied in this cohort. Alcohol abuse [hazard ratio (HR) 6·81, 95% CI 1·69–27·36, p=0·007] and deterioration from pre-morbid level of functioning up to a year after onset (HR 5·20, 95% CI 1·24–21·89, p=0·024) were associated with increased risk of suicide.
Conclusions. Suicide is significantly increased in unselected bipolar patients but actual case fatality is not as high as previously claimed. A history of alcohol abuse and deterioration in function predict suicide in bipolar disorder.
An interdisciplinary workshop to improve palliative care: Advanced heart failure— Clinical guidelines and healing words
- JANE G. ZAPKA, WINNIE HENNESSY, YAN LIN, LISA JOHNSON, DIANE KENNEDY, SARAH J. GOODLIN
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- Journal:
- Palliative & Supportive Care / Volume 4 / Issue 1 / March 2006
- Published online by Cambridge University Press:
- 29 June 2006, pp. 37-46
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Objective: Effective communication is recognized as an essential process to providing quality care, including palliative and end-of-life care. Discussion of prognosis and support needs of patients with heart failure is particularly challenging given the nature of the condition and care across several settings. The objective was to design, implement, and evaluate an interdisciplinary workshop aimed at improving attitudes and skills related to communication with patients and family, health team communication and documentation, and assessment of physical and emotional symptoms.
Methods: A pretest, delayed posttest evaluation design was used to evaluate two 4-h workshops offered to nurses, social workers, and other nonphysician clinicians.
Results: Although baseline reports of skills were high for the participants, significant improvement was noted for objectives emphasized in the workshop.
Significance of results: This project demonstrated the feasibility of designing, marketing a brief workshop, and positively impacting communication and documentation skills.
11 - Globalisation, Trade Unionism and Solidarity: Further Reflections on the Liverpool Dock Lockout
- from Part III - Social Dimensions
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- By Jane Kennedy, University of Liverpool, Michael Lavalette, University of Liverpool
- Edited by Ronaldo Munck
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- Book:
- Labour and Globalisation
- Published by:
- Liverpool University Press
- Published online:
- 04 July 2017
- Print publication:
- 01 February 2003, pp 206-226
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Summary
On 25 September 1995, 20 workers employed by the Torside stevedoring company in Liverpool were instructed to work overtime under conditions which broke existing contractual arrangements held between Torside Ltd, the Mersey Docks and Harbour Company (MDHC) and the Transport and General Workers’ Union (TGWU). In response the men decided, at the end of their normal shift, to return to the canteen and attempt to contact their shop steward. The first five men to reach the canteen were met by the managing director of Torside, who sacked them for leaving the ship. When the others arrived they were told to return to the ship without their colleagues or face dismissal. They refused to return without their workmates and were sacked. On the following morning the shop stewards arranged a meeting to review the situation. The managing director of Torside appeared at the meeting and sacked the entire Torside workforce. Over the next few days the conflict spread through the port as the Torsiders picketed out the dock workforce. First, men from Nelson Freight were picketed out – and then sacked for joining the strike. Then, on 28 September, a picket was placed on the gates of Seaforth docks – the main entry point for 325 MDHC-employed dockers. The Seaforth workforce refused to cross the line, which meant that dockers across the whole complex were out on strike. Instead of entering into negotiations MDHC chose to sack the entire workforce and recruit a casual, non-union labour force via Drake International, a London-based employment agency. In the space of four days, 500 workers had lost their jobs. When the TGWU tried to negotiate a return to work, MDHC informed them that there would be jobs for a small minority, on new casual contracts and no union recognition, but the majority would never work at the complex again. The dispute had turned into a fully fledged union-busting lockout.
These dramatic events started the Liverpool docks lockout that was to continue for the next 28 months, eventually ending in defeat for the dockers in January 1998. The story of the lockout has been told elsewhere and it is not our intention to repeat much of that history here (see Lavalette and Kennedy, 1996; 1997; 1998; Kennedy and Lavalette, 1997; Castree, 1999; Barker and Lavalette, 2001).
Household Capital Formation and Financing, 1897–1962. By F. Thomas Juster. National Bureau of Economic Research; Columbia University Press, New York, distributor, 1966. Pp. xiv, 146. $6.00.
- Jane Kennedy
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- Journal:
- The Journal of Economic History / Volume 27 / Issue 3 / September 1967
- Published online by Cambridge University Press:
- 03 February 2011, pp. 414-415
- Print publication:
- September 1967
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