22 results
Evaluation of an experiential training program in patient-centered outcomes and comparative effectiveness research for diverse researcher communities and health care organizations
- Dedra S. Buchwald, Megan H. Rogers, Barbara A. Rose, Brian W. Bresnahan, Beth Devine, Linda LeResche, Lonnie A. Nelson, Donald L. Patrick, Danielle C. Lavallee, Michelle M. Garrison, Andrew A. White, Larry G. Kessler
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- Journal:
- Journal of Clinical and Translational Science / Volume 7 / Issue 1 / 2023
- Published online by Cambridge University Press:
- 15 March 2023, e81
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Background/Objective:
The goal of the Patient-Centered Outcomes Research Partnership was to prepare health care professionals and researchers to conduct patient-centered outcomes and comparative effectiveness research (CER). Substantial evidence gaps, heterogeneous health care systems, and decision-making challenges in the USA underscore the need for evidence-based strategies.
Methods:We engaged five community-based health care organizations that serve diverse and underrepresented patient populations from Hawai’i to Minnesota. Each partner nominated two in-house scholars to participate in the 2-year program. The program focused on seven competencies pertinent to patient-centered outcomes and CER. It combined in-person and experiential learning with asynchronous, online education, and created adaptive, pragmatic learning opportunities and a Summer Institute. Metrics included the Clinical Research Appraisal Inventory (CRAI), a tool designed to assess research self-efficacy and clinical research skills across 10 domains.
Results:We trained 31 scholars in 3 cohorts. Mean scores in nine domains of the CRAI improved; greater improvement was observed from the beginning to the midpoint than from the midpoint to conclusion of the program. Across all three cohorts, mean scores on 52 items (100%) increased (p ≤ 0.01), and 91% of scholars reported the program improved their skills moderately/significantly. Satisfaction with the program was high (91%).
Conclusions:Investigators that conduct patient-centered outcomes and CER must know how to collaborate with regional health care systems to identify priorities; pose questions; design, conduct, and disseminate observational and experimental research; and transform knowledge into practical clinical applications. Training programs such as ours can facilitate such collaborations.
A practical risk calculator for suicidal behavior among transitioning U.S. Army soldiers: results from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS)
- Jaclyn C. Kearns, Emily R. Edwards, Erin P. Finley, Joseph C. Geraci, Sarah M. Gildea, Marianne Goodman, Irving Hwang, Chris J. Kennedy, Andrew J. King, Alex Luedtke, Brian P. Marx, Maria V. Petukhova, Nancy A. Sampson, Richard W. Seim, Ian H. Stanley, Murray B. Stein, Robert J. Ursano, Ronald C. Kessler
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- Journal:
- Psychological Medicine / Volume 53 / Issue 15 / November 2023
- Published online by Cambridge University Press:
- 09 March 2023, pp. 7096-7105
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Background
Risk of suicide-related behaviors is elevated among military personnel transitioning to civilian life. An earlier report showed that high-risk U.S. Army soldiers could be identified shortly before this transition with a machine learning model that included predictors from administrative systems, self-report surveys, and geospatial data. Based on this result, a Veterans Affairs and Army initiative was launched to evaluate a suicide-prevention intervention for high-risk transitioning soldiers. To make targeting practical, though, a streamlined model and risk calculator were needed that used only a short series of self-report survey questions.
MethodsWe revised the original model in a sample of n = 8335 observations from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) who participated in one of three Army STARRS 2011–2014 baseline surveys while in service and in one or more subsequent panel surveys (LS1: 2016–2018, LS2: 2018–2019) after leaving service. We trained ensemble machine learning models with constrained numbers of item-level survey predictors in a 70% training sample. The outcome was self-reported post-transition suicide attempts (SA). The models were validated in the 30% test sample.
ResultsTwelve-month post-transition SA prevalence was 1.0% (s.e. = 0.1). The best constrained model, with only 17 predictors, had a test sample ROC-AUC of 0.85 (s.e. = 0.03). The 10–30% of respondents with the highest predicted risk included 44.9–92.5% of 12-month SAs.
ConclusionsAn accurate SA risk calculator based on a short self-report survey can target transitioning soldiers shortly before leaving service for intervention to prevent post-transition SA.
Development of a model to predict antidepressant treatment response for depression among Veterans
- Victor Puac-Polanco, Hannah N. Ziobrowski, Eric L. Ross, Howard Liu, Brett Turner, Ruifeng Cui, Lucinda B. Leung, Robert M. Bossarte, Corey Bryant, Jutta Joormann, Andrew A. Nierenberg, David W. Oslin, Wilfred R. Pigeon, Edward P. Post, Nur Hani Zainal, Alan M. Zaslavsky, Jose R. Zubizarreta, Alex Luedtke, Chris J. Kennedy, Andrea Cipriani, Toshiaki A. Furukawa, Ronald C. Kessler
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- Journal:
- Psychological Medicine / Volume 53 / Issue 11 / August 2023
- Published online by Cambridge University Press:
- 15 July 2022, pp. 5001-5011
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Background
Only a limited number of patients with major depressive disorder (MDD) respond to a first course of antidepressant medication (ADM). We investigated the feasibility of creating a baseline model to determine which of these would be among patients beginning ADM treatment in the US Veterans Health Administration (VHA).
MethodsA 2018–2020 national sample of n = 660 VHA patients receiving ADM treatment for MDD completed an extensive baseline self-report assessment near the beginning of treatment and a 3-month self-report follow-up assessment. Using baseline self-report data along with administrative and geospatial data, an ensemble machine learning method was used to develop a model for 3-month treatment response defined by the Quick Inventory of Depression Symptomatology Self-Report and a modified Sheehan Disability Scale. The model was developed in a 70% training sample and tested in the remaining 30% test sample.
ResultsIn total, 35.7% of patients responded to treatment. The prediction model had an area under the ROC curve (s.e.) of 0.66 (0.04) in the test sample. A strong gradient in probability (s.e.) of treatment response was found across three subsamples of the test sample using training sample thresholds for high [45.6% (5.5)], intermediate [34.5% (7.6)], and low [11.1% (4.9)] probabilities of response. Baseline symptom severity, comorbidity, treatment characteristics (expectations, history, and aspects of current treatment), and protective/resilience factors were the most important predictors.
ConclusionsAlthough these results are promising, parallel models to predict response to alternative treatments based on data collected before initiating treatment would be needed for such models to help guide treatment selection.
Associations of vulnerability to stressful life events with suicide attempts after active duty among high-risk soldiers: results from the Study to Assess Risk and Resilience in Servicemembers-longitudinal study (STARRS-LS)
- Carol Chu, Ian H. Stanley, Brian P. Marx, Andrew J. King, Dawne Vogt, Sarah M. Gildea, Irving H. Hwang, Nancy A. Sampson, Robert O'Brien, Murray B. Stein, Robert J. Ursano, Ronald C. Kessler
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- Journal:
- Psychological Medicine / Volume 53 / Issue 9 / July 2023
- Published online by Cambridge University Press:
- 27 May 2022, pp. 4181-4191
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Background
The transition from military service to civilian life is a high-risk period for suicide attempts (SAs). Although stressful life events (SLEs) faced by transitioning soldiers are thought to be implicated, systematic prospective evidence is lacking.
MethodsParticipants in the Army Study to Assess Risk and Resilience in Servicemembers (STARRS) completed baseline self-report surveys while on active duty in 2011–2014. Two self-report follow-up Longitudinal Surveys (LS1: 2016–2018; LS2: 2018–2019) were subsequently administered to probability subsamples of these baseline respondents. As detailed in a previous report, a SA risk index based on survey, administrative, and geospatial data collected before separation/deactivation identified 15% of the LS respondents who had separated/deactivated as being high-risk for self-reported post-separation/deactivation SAs. The current report presents an investigation of the extent to which self-reported SLEs occurring in the 12 months before each LS survey might have mediated/modified the association between this SA risk index and post-separation/deactivation SAs.
ResultsThe 15% of respondents identified as high-risk had a significantly elevated prevalence of some post-separation/deactivation SLEs. In addition, the associations of some SLEs with SAs were significantly stronger among predicted high-risk than lower-risk respondents. Demographic rate decomposition showed that 59.5% (s.e. = 10.2) of the overall association between the predicted high-risk index and subsequent SAs was linked to these SLEs.
ConclusionsIt might be possible to prevent a substantial proportion of post-separation/deactivation SAs by providing high-risk soldiers with targeted preventive interventions for exposure/vulnerability to commonly occurring SLEs.
Development of a model to predict psychotherapy response for depression among Veterans
- Hannah N. Ziobrowski, Ruifeng Cui, Eric L. Ross, Howard Liu, Victor Puac-Polanco, Brett Turner, Lucinda B. Leung, Robert M. Bossarte, Corey Bryant, Wilfred R. Pigeon, David W. Oslin, Edward P. Post, Alan M. Zaslavsky, Jose R. Zubizarreta, Andrew A. Nierenberg, Alex Luedtke, Chris J. Kennedy, Ronald C. Kessler
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- Journal:
- Psychological Medicine / Volume 53 / Issue 8 / June 2023
- Published online by Cambridge University Press:
- 11 February 2022, pp. 3591-3600
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Background
Fewer than half of patients with major depressive disorder (MDD) respond to psychotherapy. Pre-emptively informing patients of their likelihood of responding could be useful as part of a patient-centered treatment decision-support plan.
MethodsThis prospective observational study examined a national sample of 807 patients beginning psychotherapy for MDD at the Veterans Health Administration. Patients completed a self-report survey at baseline and 3-months follow-up (data collected 2018–2020). We developed a machine learning (ML) model to predict psychotherapy response at 3 months using baseline survey, administrative, and geospatial variables in a 70% training sample. Model performance was then evaluated in the 30% test sample.
Results32.0% of patients responded to treatment after 3 months. The best ML model had an AUC (SE) of 0.652 (0.038) in the test sample. Among the one-third of patients ranked by the model as most likely to respond, 50.0% in the test sample responded to psychotherapy. In comparison, among the remaining two-thirds of patients, <25% responded to psychotherapy. The model selected 43 predictors, of which nearly all were self-report variables.
ConclusionsPatients with MDD could pre-emptively be informed of their likelihood of responding to psychotherapy using a prediction tool based on self-report data. This tool could meaningfully help patients and providers in shared decision-making, although parallel information about the likelihood of responding to alternative treatments would be needed to inform decision-making across multiple treatments.
A history of high-power laser research and development in the United Kingdom
- Part of
- Colin N. Danson, Malcolm White, John R. M. Barr, Thomas Bett, Peter Blyth, David Bowley, Ceri Brenner, Robert J. Collins, Neal Croxford, A. E. Bucker Dangor, Laurence Devereux, Peter E. Dyer, Anthony Dymoke-Bradshaw, Christopher B. Edwards, Paul Ewart, Allister I. Ferguson, John M. Girkin, Denis R. Hall, David C. Hanna, Wayne Harris, David I. Hillier, Christopher J. Hooker, Simon M. Hooker, Nicholas Hopps, Janet Hull, David Hunt, Dino A. Jaroszynski, Mark Kempenaars, Helmut Kessler, Sir Peter L. Knight, Steve Knight, Adrian Knowles, Ciaran L. S. Lewis, Ken S. Lipton, Abby Littlechild, John Littlechild, Peter Maggs, Graeme P. A. Malcolm, OBE, Stuart P. D. Mangles, William Martin, Paul McKenna, Richard O. Moore, Clive Morrison, Zulfikar Najmudin, David Neely, Geoff H. C. New, Michael J. Norman, Ted Paine, Anthony W. Parker, Rory R. Penman, Geoff J. Pert, Chris Pietraszewski, Andrew Randewich, Nadeem H. Rizvi, Nigel Seddon, MBE, Zheng-Ming Sheng, David Slater, Roland A. Smith, Christopher Spindloe, Roy Taylor, Gary Thomas, John W. G. Tisch, Justin S. Wark, Colin Webb, S. Mark Wiggins, Dave Willford, Trevor Winstone
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- Journal:
- High Power Laser Science and Engineering / Volume 9 / 2021
- Published online by Cambridge University Press:
- 27 April 2021, e18
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The first demonstration of laser action in ruby was made in 1960 by T. H. Maiman of Hughes Research Laboratories, USA. Many laboratories worldwide began the search for lasers using different materials, operating at different wavelengths. In the UK, academia, industry and the central laboratories took up the challenge from the earliest days to develop these systems for a broad range of applications. This historical review looks at the contribution the UK has made to the advancement of the technology, the development of systems and components and their exploitation over the last 60 years.
Temporal Progression of Alcohol Dependence Symptoms in the Us Population: Results From the National Comorbidity Survey
- Christopher B. Nelson, Andrew C. Heath, Ronald C. Kessler
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- European Psychiatry / Volume 11 / Issue S4 / 1996
- Published online by Cambridge University Press:
- 16 April 2020, p. 324s
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Posttraumatic stress disorder symptom trajectories within the first year following emergency department admissions: pooled results from the International Consortium to predict PTSD
- Sarah R. Lowe, Andrew Ratanatharathorn, Betty S. Lai, Willem van der Mei, Anna C. Barbano, Richard A. Bryant, Douglas L. Delahanty, Yutaka J. Matsuoka, Miranda Olff, Ulrich Schnyder, Eugene Laska, Karestan C. Koenen, Arieh Y. Shalev, Ronald C. Kessler
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- Journal:
- Psychological Medicine / Volume 51 / Issue 7 / May 2021
- Published online by Cambridge University Press:
- 03 February 2020, pp. 1129-1139
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Background
Research exploring the longitudinal course of posttraumatic stress disorder (PTSD) symptoms has documented four modal trajectories (low, remitting, high, and delayed), with proportions varying across studies. Heterogeneity could be due to differences in trauma types and patient demographic characteristics.
MethodsThis analysis pooled data from six longitudinal studies of adult survivors of civilian-related injuries admitted to general hospital emergency departments (EDs) in six countries (pooled N = 3083). Each study included at least three assessments of the clinician-administered PTSD scale in the first post-trauma year. Latent class growth analysis determined the proportion of participants exhibiting various PTSD symptom trajectories within and across the datasets. Multinomial logistic regression analyses examined demographic characteristics, type of event leading to the injury, and trauma history as predictors of trajectories differentiated by their initial severity and course.
ResultsFive trajectories were found across the datasets: Low (64.5%), Remitting (16.9%), Moderate (6.7%), High (6.5%), and Delayed (5.5%). Female gender, non-white race, prior interpersonal trauma, and assaultive injuries were associated with increased risk for initial PTSD reactions. Female gender and assaultive injuries were associated with risk for membership in the Delayed (v. Low) trajectory, and lower education, prior interpersonal trauma, and assaultive injuries with risk for membership in the High (v. Remitting) trajectory.
ConclusionsThe results suggest that over 30% of civilian-related injury survivors admitted to EDs experience moderate-to-high levels of PTSD symptoms within the first post-trauma year, with those reporting assaultive violence at increased risk of both immediate and longer-term symptoms.
Clinical implications of the proposed ICD-11 PTSD diagnostic criteria
- Anna C. Barbano, Willem F. van der Mei, Richard A. Bryant, Douglas L. Delahanty, Terri A. deRoon-Cassini, Yutaka J. Matsuoka, Miranda Olff, Wei Qi, Andrew Ratanatharathorn, Ulrich Schnyder, Soraya Seedat, Ronald C. Kessler, Karestan C. Koenen, Arieh Y. Shalev
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- Journal:
- Psychological Medicine / Volume 49 / Issue 3 / February 2019
- Published online by Cambridge University Press:
- 14 May 2018, pp. 483-490
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Background
Projected changes to post-traumatic stress disorder (PTSD) diagnostic criteria in the upcoming International Classification of Diseases (ICD)-11 may affect the prevalence and severity of identified cases. This study examined differences in rates, severity, and overlap of diagnoses using ICD-10 and ICD-11 PTSD diagnostic criteria during consecutive assessments of recent survivors of traumatic events.
MethodsThe study sample comprised 3863 survivors of traumatic events, evaluated in 11 longitudinal studies of PTSD. ICD-10 and ICD-11 diagnostic rules were applied to the Clinician-Administered PTSD Scale (CAPS) to derive ICD-10 and ICD-11 diagnoses at different time intervals between trauma occurrence and 15 months.
ResultsThe ICD-11 criteria identified fewer cases than the ICD-10 across assessment intervals (range −47.09% to −57.14%). Over 97% of ICD-11 PTSD cases met concurrent ICD-10 PTSD criteria. PTSD symptom severity of individuals identified by the ICD-11 criteria (CAPS total scores) was 31.38–36.49% higher than those identified by ICD-10 criteria alone. The latter, however, had CAPS scores indicative of moderate PTSD. ICD-11 was associated with similar or higher rates of comorbid mood and anxiety disorders. Individuals identified by either ICD-10 or ICD-11 shortly after traumatic events had similar longitudinal course.
ConclusionsThis study indicates that significantly fewer individuals would be diagnosed with PTSD using the proposed ICD-11 criteria. Though ICD-11 criteria identify more severe cases, those meeting ICD-10 but not ICD-11 criteria remain in the moderate range of PTSD symptoms. Use of ICD-11 criteria will have critical implications for case identification in clinical practice, national reporting, and research.
5 - Bipolar Spectrum Disorder
- from Section II - The Disorders
- Edited by Kate M. Scott, University of Otago, New Zealand, Peter de Jonge, Rijksuniversiteit Groningen, The Netherlands, Dan J. Stein, University of Cape Town, Ronald C. Kessler
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- Mental Disorders Around the World
- Published online:
- 28 December 2017
- Print publication:
- 04 January 2018, pp 57-78
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Impacts of Invasive Plants on Sandhill Crane (Grus canadensis) Roosting Habitat
- Andrew C. Kessler, James W. Merchant, Craig R. Allen, Steven D. Shultz
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- Invasive Plant Science and Management / Volume 4 / Issue 4 / December 2011
- Published online by Cambridge University Press:
- 20 January 2017, pp. 369-377
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Invasive plants continue to spread in riparian ecosystems, causing both ecological and economic damage. This research investigated the impacts of common reed, purple loosestrife, riparian shrubland, and riparian woodlands on the quality and quantity of sandhill crane roosting habitat in the central Platte River, Nebraska, using a discrete choice model. A more detailed investigation of the impacts of common reed on sandhill crane roosting habitat was performed by forecasting a spread or contraction of this invasive plant. The discrete choice model indicates that riparian woodlands had the largest negative impact on sandhill crane roosting habitat. The forecasting results predict that a contraction of common reed could increase sandhill crane habitat availability by 50%, whereas an expansion could reduce the availability by as much as 250%. This suggests that if the distribution of common reed continues to expand in the central Platte River the availability of sandhill crane roosting habitat would likely be greatly reduced.
Contributors
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- By Andrew Adesman, Lenard A. Adler, Samuel Alperin, Kira E. Armstrong, L. Eugene Arnold, Amy F. T. Arnsten, Russell A. Barkley, Craig W. Berridge, Joseph Biederman, F. Xavier Castellanos, Barbara J. Coffey, Alison M. Cohn, C. Keith Conners, Joan M. Daughton, Stephen V. Faraone, John Fayyad, Lisa G. Hahn, Laura Hans, Elizabeth Hurt, Gagan Joshi, Rahil Jummani, Jesse M. Jun, Ronald C. Kessler, Scott Haden Kollins, Kimberly Kovacs, Christopher J. Kratochvil, Beth Krone, Nicholas Lofthouse, Michael J. Manos, Francis Joseph McClernon, Joel E. Morgan, Nicholas R. Morrison, Sonali Nanayakkara, Jeffrey H. Newcorn, Phillip L. Pearl, Juan D. Pedraza, Guy M. L. Perry, Steven R. Pliszka, Jefferson B. Prince, J. Russell Ramsay, Anthony L. Rostain, David M. Shaw, Mary V. Solanto, Mark A. Stein, Jonathan R. Stevens, Brigette S. Vaughan, Margaret Weiss, Roy E. Weiss, Timothy E. Wilens, Janet Wozniak
- Edited by Lenard A. Adler, New York University School of Medicine, Thomas J. Spencer, Timothy E. Wilens
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- Attention-Deficit Hyperactivity Disorder in Adults and Children
- Published online:
- 05 February 2015
- Print publication:
- 08 January 2015, pp vii-x
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- By Alyssa Abo, Faiza Al Talaq, Alexander C. Arroyo, Laura J. Berg, Tony Berger, Lei Chen, Roberto Copetti, Stephanie J. Doniger, Mahmoud Elbarbary, Alaa A. Eldemerdash, Jason W. Fischer, John Christian Fox, Katja Goldflam, Beatrice Hoffmann, Jamie A. Jenkins, David Kessler, Heidi Ladner, Samuel H. F. Lam, Jason A. Levy, Resa E. Lewiss, Andrew S. Liteplo, Jennifer R. Marin, Arun Nagdev, Vicki E. Noble, Daniela Ramirez-Schrempp, Joshua Rempell, Randall T. Rhyne, Antonio Riera, Dana R. Sajed, Fernando Silva, Adam B. Sivitz, Dave Spear, Rebecca L. Vieira
- Edited by Stephanie J. Doniger
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- Pediatric Emergency Critical Care and Ultrasound
- Published online:
- 05 February 2015
- Print publication:
- 24 April 2014, pp x-xii
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- By Leonard A. Adler, Henrik Anckarsäter, L. Eugene Arnold, Philip J. Asherson, Russell Barkley, Joseph Biederman, Andrew D. Blackwell, Jessica Bramham, Thomas E. Brown, Richard Bruggeman, Jan K. Buitelaar, C. Keith Conners, Jonathan H. Dowson, Steve V. Faraone, Christopher Gibbins, Christopher Gillberg, I. Carina Gillberg, Ylva Ginsberg, Laurence L. Greenhill, Julia D. Hunter, Cornelis C. Kan, Ronald C. Kessler, Scott H. Kollins, J. J. Sandra Kooij, Johanna Krause, Jonna Kuntsi, Florence Levy, Stephen P. McDermott, Gráinne McLoughlin, Mitul A. Mehta, Asko Niemela, Eleni Paliokosta, Yannis Paloyelis, Vangelis Pappas, Patricia Quinn, Maria Råstam, Doris Ryffel, David Shaw, Seija Sirviö, Thomas Spencer, Lacramioara Spetie, Siegfried Tuinier, Fiona E. van Dijk, Anne M. D. N. van Lammeren, Wim J. C. Verbeeck, Margaret Weiss, Timothy E. Wilens, Kiriakos Xenitidis
- Edited by Jan K. Buitelaar, Cornelis C. Kan, Philip Asherson, Institute of Psychiatry, London
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- ADHD in Adults
- Published online:
- 04 April 2011
- Print publication:
- 03 March 2011, pp vii-ix
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- By Rose Teteki Abbey, K. C. Abraham, David Tuesday Adamo, LeRoy H. Aden, Efrain Agosto, Victor Aguilan, Gillian T. W. Ahlgren, Charanjit Kaur AjitSingh, Dorothy B E A Akoto, Giuseppe Alberigo, Daniel E. Albrecht, Ruth Albrecht, Daniel O. Aleshire, Urs Altermatt, Anand Amaladass, Michael Amaladoss, James N. Amanze, Lesley G. Anderson, Thomas C. Anderson, Victor Anderson, Hope S. Antone, María Pilar Aquino, Paula Arai, Victorio Araya Guillén, S. Wesley Ariarajah, Ellen T. Armour, Brett Gregory Armstrong, Atsuhiro Asano, Naim Stifan Ateek, Mahmoud Ayoub, John Alembillah Azumah, Mercedes L. García Bachmann, Irena Backus, J. Wayne Baker, Mieke Bal, Lewis V. Baldwin, William Barbieri, António Barbosa da Silva, David Basinger, Bolaji Olukemi Bateye, Oswald Bayer, Daniel H. Bays, Rosalie Beck, Nancy Elizabeth Bedford, Guy-Thomas Bedouelle, Chorbishop Seely Beggiani, Wolfgang Behringer, Christopher M. Bellitto, Byard Bennett, Harold V. Bennett, Teresa Berger, Miguel A. Bernad, Henley Bernard, Alan E. Bernstein, Jon L. Berquist, Johannes Beutler, Ana María Bidegain, Matthew P. Binkewicz, Jennifer Bird, Joseph Blenkinsopp, Dmytro Bondarenko, Paulo Bonfatti, Riet en Pim Bons-Storm, Jessica A. Boon, Marcus J. Borg, Mark Bosco, Peter C. Bouteneff, François Bovon, William D. Bowman, Paul S. Boyer, David Brakke, Richard E. Brantley, Marcus Braybrooke, Ian Breward, Ênio José da Costa Brito, Jewel Spears Brooker, Johannes Brosseder, Nicholas Canfield Read Brown, Robert F. Brown, Pamela K. Brubaker, Walter Brueggemann, Bishop Colin O. Buchanan, Stanley M. Burgess, Amy Nelson Burnett, J. Patout Burns, David B. Burrell, David Buttrick, James P. Byrd, Lavinia Byrne, Gerado Caetano, Marcos Caldas, Alkiviadis Calivas, William J. Callahan, Salvatore Calomino, Euan K. Cameron, William S. Campbell, Marcelo Ayres Camurça, Daniel F. Caner, Paul E. Capetz, Carlos F. Cardoza-Orlandi, Patrick W. Carey, Barbara Carvill, Hal Cauthron, Subhadra Mitra Channa, Mark D. Chapman, James H. Charlesworth, Kenneth R. Chase, Chen Zemin, Luciano Chianeque, Philip Chia Phin Yin, Francisca H. Chimhanda, Daniel Chiquete, John T. Chirban, Soobin Choi, Robert Choquette, Mita Choudhury, Gerald Christianson, John Chryssavgis, Sejong Chun, Esther Chung-Kim, Charles M. A. Clark, Elizabeth A. Clark, Sathianathan Clarke, Fred Cloud, John B. Cobb, W. Owen Cole, John A Coleman, John J. Collins, Sylvia Collins-Mayo, Paul K. Conkin, Beth A. Conklin, Sean Connolly, Demetrios J. Constantelos, Michael A. Conway, Paula M. Cooey, Austin Cooper, Michael L. Cooper-White, Pamela Cooper-White, L. William Countryman, Sérgio Coutinho, Pamela Couture, Shannon Craigo-Snell, James L. Crenshaw, David Crowner, Humberto Horacio Cucchetti, Lawrence S. Cunningham, Elizabeth Mason Currier, Emmanuel Cutrone, Mary L. Daniel, David D. Daniels, Robert Darden, Rolf Darge, Isaiah Dau, Jeffry C. Davis, Jane Dawson, Valentin Dedji, John W. de Gruchy, Paul DeHart, Wendy J. Deichmann Edwards, Miguel A. De La Torre, George E. Demacopoulos, Thomas de Mayo, Leah DeVun, Beatriz de Vasconcellos Dias, Dennis C. Dickerson, John M. Dillon, Luis Miguel Donatello, Igor Dorfmann-Lazarev, Susanna Drake, Jonathan A. Draper, N. Dreher Martin, Otto Dreydoppel, Angelyn Dries, A. J. Droge, Francis X. D'Sa, Marilyn Dunn, Nicole Wilkinson Duran, Rifaat Ebied, Mark J. Edwards, William H. Edwards, Leonard H. Ehrlich, Nancy L. Eiesland, Martin Elbel, J. Harold Ellens, Stephen Ellingson, Marvin M. Ellison, Robert Ellsberg, Jean Bethke Elshtain, Eldon Jay Epp, Peter C. Erb, Tassilo Erhardt, Maria Erling, Noel Leo Erskine, Gillian R. Evans, Virginia Fabella, Michael A. Fahey, Edward Farley, Margaret A. Farley, Wendy Farley, Robert Fastiggi, Seena Fazel, Duncan S. Ferguson, Helwar Figueroa, Paul Corby Finney, Kyriaki Karidoyanes FitzGerald, Thomas E. FitzGerald, John R. Fitzmier, Marie Therese Flanagan, Sabina Flanagan, Claude Flipo, Ronald B. Flowers, Carole Fontaine, David Ford, Mary Ford, Stephanie A. Ford, Jim Forest, William Franke, Robert M. Franklin, Ruth Franzén, Edward H. Friedman, Samuel Frouisou, Lorelei F. Fuchs, Jojo M. Fung, Inger Furseth, Richard R. Gaillardetz, Brandon Gallaher, China Galland, Mark Galli, Ismael García, Tharscisse Gatwa, Jean-Marie Gaudeul, Luis María Gavilanes del Castillo, Pavel L. Gavrilyuk, Volney P. Gay, Metropolitan Athanasios Geevargis, Kondothra M. George, Mary Gerhart, Simon Gikandi, Maurice Gilbert, Michael J. Gillgannon, Verónica Giménez Beliveau, Terryl Givens, Beth Glazier-McDonald, Philip Gleason, Menghun Goh, Brian Golding, Bishop Hilario M. Gomez, Michelle A. Gonzalez, Donald K. Gorrell, Roy Gottfried, Tamara Grdzelidze, Joel B. Green, Niels Henrik Gregersen, Cristina Grenholm, Herbert Griffiths, Eric W. Gritsch, Erich S. Gruen, Christoffer H. Grundmann, Paul H. Gundani, Jon P. Gunnemann, Petre Guran, Vidar L. Haanes, Jeremiah M. Hackett, Getatchew Haile, Douglas John Hall, Nicholas Hammond, Daphne Hampson, Jehu J. Hanciles, Barry Hankins, Jennifer Haraguchi, Stanley S. Harakas, Anthony John Harding, Conrad L. Harkins, J. William Harmless, Marjory Harper, Amir Harrak, Joel F. Harrington, Mark W. Harris, Susan Ashbrook Harvey, Van A. Harvey, R. Chris Hassel, Jione Havea, Daniel Hawk, Diana L. Hayes, Leslie Hayes, Priscilla Hayner, S. Mark Heim, Simo Heininen, Richard P. Heitzenrater, Eila Helander, David Hempton, Scott H. Hendrix, Jan-Olav Henriksen, Gina Hens-Piazza, Carter Heyward, Nicholas J. Higham, David Hilliard, Norman A. Hjelm, Peter C. Hodgson, Arthur Holder, M. Jan Holton, Dwight N. Hopkins, Ronnie Po-chia Hsia, Po-Ho Huang, James Hudnut-Beumler, Jennifer S. Hughes, Leonard M. Hummel, Mary E. Hunt, Laennec Hurbon, Mark Hutchinson, Susan E. Hylen, Mary Beth Ingham, H. Larry Ingle, Dale T. Irvin, Jon Isaak, Paul John Isaak, Ada María Isasi-Díaz, Hans Raun Iversen, Margaret C. 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Yee, Viktor Yelensky, Yeo Khiok-Khng, Gustav K. K. Yeung, Angela Yiu, Amos Yong, Yong Ting Jin, You Bin, Youhanna Nessim Youssef, Eliana Yunes, Robert Michael Zaller, Valarie H. Ziegler, Barbara Brown Zikmund, Joyce Ann Zimmerman, Aurora Zlotnik, Zhuo Xinping
- Edited by Daniel Patte, Vanderbilt University, Tennessee
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- The Cambridge Dictionary of Christianity
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- 05 August 2012
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- 20 September 2010, pp xi-xliv
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Major depression and phobias: the genetic and environmental sources of comorbidity
- Kenneth S. Kendler, Michael C. Neale, Ronald C. Kessler, Andrew C. Heath, Lindon J. Eaves
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- Psychological Medicine / Volume 23 / Issue 2 / May 1993
- Published online by Cambridge University Press:
- 09 July 2009, pp. 361-371
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In a population based sample of 2163 personally interviewed female twins, substantial comorbidity was observed between DSM-III-R defined major depression (MD) and 4 subtypes of phobia: agoraphobia, social phobia, animal phobia and situational phobia. However, the level of comorbidity of MD with agoraphobia was much greater than that found with the other phobic subtypes. We conducted bivariate twin analyses to decompose the genetic and environmental sources of comorbidity between MD and the phobias. Our results suggest that a modest proportion of the genetic vulnerability to MD also influences the risk for all phobic subtypes, with the possible exception of situational phobias. Furthermore, the magnitude of comorbidity resulting from this shared genetic vulnerability is similar across the phobic subtypes. By contrast, the non-familial environmental experiences which predispose to depression substantially increase the vulnerability to agoraphobia, have a modest impact on the risk for social and situational phobias and no effect on the risk for animal phobias. The increased comorbidity between MD and agoraphobia results, nearly entirely, from individual-specific environmental risk factors for MD which also increase the risk for agoraphobia but not for other phobias.
Bulimia nervosa and major depression: a study of common genetic and environmental factors
- Ellen E. Walters, Michael C. Neale, Lindon J. Eaves, Andrew C. Heath, Ronald C. Kessler, Kenneth S. Kendler
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- Psychological Medicine / Volume 22 / Issue 3 / August 1992
- Published online by Cambridge University Press:
- 09 July 2009, pp. 617-622
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A genetic analysis of the co-occurrence of bulimia and major depression (MD) was performed on 1033 female twin pairs obtained from a population based register. Personal interviews were conducted and clinical diagnoses made according to DSM-III-R criteria.
Additive genes, but not family environment, are found to play an important aetiological role in both bulimia and MD. The genetic liabilities of the two disorders are correlated 0·456. While unique environmental factors account for around half of the variation in liability to both bulimia and MD, these risk factors appear to be unrelated, i.e., each disorder has its own set of unique environmental risk factors. Thus, the genetic liability of bulimia and MD is neither highly specific nor entirely nonspecific. There is some genetic correlation between the two disorders as well as some genetic and environmental risk factors unique to each disorder. Limitations and directions for future research are discussed.
Coping: a genetic epidemiological investigation
- Kenneth S. Kendler, Ronald C. Kessler, Andrew C. Heath, Michael C. Neale, Lindon J. Eaves
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- Psychological Medicine / Volume 21 / Issue 2 / May 1991
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- 09 July 2009, pp. 337-346
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This study examines data on self-report coping behaviour, life events and symptoms of anxiety and depression in a general population sample of 827 female twin pairs. Factor analysis identified three almost uncorrelated coping factors: turning to others; problem solving; and denial. Turning to others and problem solving were negatively and denial was positively related to levels of anxiety and depression. Turning to others and problem solving buffered the depressogenic and anxiogenic effects of stressful life events, while denial exacerbated the anxiogenic effects of life events. Structural equation model-fitting indicated that twin resemblance in turning to others and problem solving could be explained entirely by genetic factors with an estimated heritability of 30 and 31%, respectively. For denial, twin resemblance could be best explained by familial–environmental factors accounting for 19% of the total variation. Genes may affect the vulnerability to psychiatric disorders in part by influencing coping behaviour.
Panic disorder in women: a population-based twin study
- Kenneth S. Kendler, Michael C. Neale, Ronald C. Kessler, Andrew C. Heath, Lindon J. Eaves
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- Journal:
- Psychological Medicine / Volume 23 / Issue 2 / May 1993
- Published online by Cambridge University Press:
- 09 July 2009, pp. 397-406
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Previous studies based on probands from clinical samples suggest that panic disorder aggregates strongly in families and may be due to a highly penetrant single major locus. In this study we examine panic disorder as assessed at blind, structured psychiatric interview in 2163 women from a population-based twin registry. DSM-III-R diagnoses were assigned at a narrow and at a broad level both by clinician review and by computer algorithm. The familial aggregation of panic disorder in this sample was only modest. The relatively small number of affected individuals prevented a definitive resolution of competing genetic and non-genetic models of familial transmission. Although there was some inconsistency across diagnostic approaches, most results suggested that the familial aggregation of panic disorder was due largely to genetic factors. Using a multifactorial-threshold model, the best estimates of the heritability of liability ranged from 30 to 40%. From a familial perspective, panic disorder with phobic avoidance appears to represent a more severe form of the syndrome than panic disorder without avoidance. Our results, which suggest that in the general population panic disorder is only a moderately heritable condition, are at variance with results from several previous investigations based on clinically ascertained samples.
The performance of the K6 and K10 screening scales for psychological distress in the Australian National Survey of Mental Health and Well-Being
- T. A. FURUKAWA, R. C. KESSLER, T. SLADE, G. ANDREWS
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- Journal:
- Psychological Medicine / Volume 33 / Issue 2 / February 2003
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- 14 February 2003, pp. 357-362
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Background. Two new screening scales for psychological distress, the K6 and K10, have been developed but their relative efficiency has not been evaluated in comparison with existing scales.
Method. The Australian National Survey of Mental Health and Well-Being, a nationally representative household survey, administered the WHO Composite International Diagnostic Interview (CIDI) to assess 30-day DSM-IV disorders. The K6 and K10 were also administered along with the General Health Questionnaire (GHQ-12), the current de facto standard of mental health screening. Performance of the three screening scales in detecting CIDI/DSM-IV mood and anxiety disorders was assessed by calculating the areas under receiver operating characteristic curves (AUCs). Stratum-Specific Likelihood Ratios (SSLRs) were computed to help produce individual-level predicted probabilities of being a case from screening scale scores in other samples.
Results. The K10 was marginally better than the K6 in screening for CIDI/DSM-IV mood and anxiety disorders (K10 AUC: 0·90, 95%CI: 0·89–0·91 versus K6 AUC: 0·89, 95%CI: 0·88–0·90), while both were significantly better than the GHQ-12 (AUC: 0·80, 95%CI: 0·78–0·82). The SSLRs of the K10 and K6 were more informative in ruling in or out the target disorders than those of the GHQ-12 at both ends of the population spectrum. The K6 was more robust than the K10 to subsample variation.
Conclusions. While the K10 might outperform the K6 in screening for severe disorders, the K6 is preferred in screening for any DSM-IV mood or anxiety disorder because of its brevity and consistency across subsamples. Precision of individual-level prediction is greatly improved by using polychotomous rather than dichotomous classification.