keyword
https://read.qxmd.com/read/31944934/meta-modal-information-flow-a-method-for-capturing-multimodal-modular-disconnectivity-in-schizophrenia
#21
Haleh Falakshahi, Steven Potkin, Adrian Preda, Hooman Rokham, Jing Sui, Jessica A Turner, Sergey Plis, Vince D Calhoun, Victor Manuel Vergara, Jingyu Liu, Daniel H Mathalon, Judith M Ford, James Voyvodic, Bryon Mueller, Aysenil Belger, Sarah McEwen
OBJECTIVE: Multimodal measurements of the same phenomena provide complementary information and highlight different perspectives, albeit each with their own limitations. A focus on a single modality may lead to incorrect inferences, which is especially important when a studied phenomenon is a disease. In this paper, we introduce a method that takes advantage of multimodal data in addressing the hypotheses of disconnectivity and dysfunction within schizophrenia (SZ). METHODS: We start with estimating and visualizing links within and among extracted multimodal data features using a Gaussian graphical model (GGM)...
January 7, 2020: IEEE Transactions on Bio-medical Engineering
https://read.qxmd.com/read/31940347/clinical-state-tracking-in-serious-mental-illness-through-computational-analysis-of-speech
#22
Armen C Arevian, Daniel Bone, Nikolaos Malandrakis, Victor R Martinez, Kenneth B Wells, David J Miklowitz, Shrikanth Narayanan
Individuals with serious mental illness experience changes in their clinical states over time that are difficult to assess and that result in increased disease burden and care utilization. It is not known if features derived from speech can serve as a transdiagnostic marker of these clinical states. This study evaluates the feasibility of collecting speech samples from people with serious mental illness and explores the potential utility for tracking changes in clinical state over time. Patients (n = 47) were recruited from a community-based mental health clinic with diagnoses of bipolar disorder, major depressive disorder, schizophrenia or schizoaffective disorder...
2020: PloS One
https://read.qxmd.com/read/31685674/pushing-the-boundaries-of-psychiatric-neuroimaging-to-ground-diagnosis-in-biology
#23
EDITORIAL
Manish Saggar, Lucina Q Uddin
To accurately detect, track progression of, and develop novel treatments for mental illnesses, a diagnostic framework is needed that is grounded in biological features. Here we present the case for utilizing personalized neuroimaging, computational modeling, standardized computing, and ecologically valid neuroimaging to anchor psychiatric nosology in biology. Significance Statement There is a growing recognition that the boundaries of human neuroimaging data acquisition and analysis must be pushed to ground psychiatric diagnosis in biology...
November 4, 2019: ENeuro
https://read.qxmd.com/read/31661518/applying-corrigan-s-progressive-model-of-self-stigma-to-people-with-depression
#24
Nele Cornelia Göpfert, Steffen Conrad von Heydendorff, Harald Dreßing, Josef Bailer
BACKGROUND: The progressive model of self-stigma describes four stages of internalizing stereotypes of mental illness: stereotype awareness, personal agreement, self-concurrence, and harm to self (i.e., self-esteem). Successive stages are postulated to be the most highly related. Endorsement is presumed to decrease by stage. The model has been supported in most but not all elements in various studies. The procedural character has not yet been investigated in one integrative model. The aim of this study was to test the progressive model of self-stigma in three respects: I) successive stages have the strongest associations, II) endorsements decrease with each stage, and III) the procedural character can be represented by one serial mediation model...
2019: PloS One
https://read.qxmd.com/read/31549461/cognitive-behavioural-family-intervention-cbfi-for-people-diagnosed-with-severe-mental-illness-and-their-families-a-systematic-review-and-meta-analysis-of-randomised-controlled-trials
#25
REVIEW
Chak Fai Ma, Sherry Kit Wa Chan, Wai Tong Chien, Daniel Bressington, Esther Yee Wai Mui, Edwin Ho Ming Lee, Eric Yu Hai Chen
INTRODUCTION: Cognitive behavioural family intervention (CBFI) may be an effective brief psychosocial intervention for people diagnosed with severe mental illness (SMI) and their families. No systematic review has summarised the effectiveness of CBFI. AIM: This review aimed to systematically examine the trial evidence of the effectiveness of CBFI versus treatment as usual (TAU) on improving the outcomes of people diagnosed with SMI and their families. METHOD: Eligible randomised controlled trials were identified from nine databases...
September 24, 2019: Journal of Psychiatric and Mental Health Nursing
https://read.qxmd.com/read/31409311/prevalence-of-risky-alcohol-use-behavior-and-associated-factors-in-pregnant-antenatal-care-attendees-in-debre-berhan-ethiopia-2018
#26
Abate Dargie Wubetu, Surafel Habte, Kefyalew Dagne
BACKGROUND: National Institute of alcohol and alcoholism define Problem/risky use of alcohol as drinking in a way that can negatively impact our health and life, but the body is not physically dependent on the substance. Risky alcohol use behavior is harmful to both the fetus and the mother such as maternal alcohol intoxication and alcohol use disorder, abortion, stillbirth, low birth weight, and prematurity. This study is aimed to assess the prevalence of risky alcohol use for both the mother and the fetus during pregnancy among mothers who have used alcohol at least once in the current pregnancy...
August 13, 2019: BMC Psychiatry
https://read.qxmd.com/read/31370266/the-global-prevalence-of-anxiety-among-medical-students-a-meta-analysis
#27
REVIEW
Travis Tian-Ci Quek, Wilson Wai-San Tam, Bach X Tran, Min Zhang, Zhisong Zhang, Cyrus Su-Hui Ho, And Roger Chun-Man Ho
: Anxiety, although as common and arguably as debilitating as depression, has garnered less attention, and is often undetected and undertreated in the general population. Similarly, anxiety among medical students warrants greater attention due to its significant implications. We aimed to study the global prevalence of anxiety among medical students and the associated factors predisposing medical students to anxiety. In February 2019, we carried out a systematic search for cross-sectional studies that examined the prevalence of anxiety among medical students...
July 31, 2019: International Journal of Environmental Research and Public Health
https://read.qxmd.com/read/31262697/real-time-estimation-of-electric-fields-induced-by-transcranial-magnetic-stimulation-with-deep-neural-networks
#28
Tatsuya Yokota, Toyohiro Maki, Tatsuya Nagata, Takenobu Murakami, Yoshikazu Ugawa, Ilkka Laakso, Akimasa Hirata, Hidekata Hontani
BACKGROUND: Transcranial magnetic stimulation (TMS) plays an important role in treatment of mental and neurological illnesses, and neurosurgery. However, it is difficult to target specific brain regions accurately because the complex anatomy of the brain substantially affects the shape and strength of the electric fields induced by the TMS coil. A volume conductor model can be used for determining the accurate electric fields; however, the construction of subject-specific anatomical head structures is time-consuming...
June 17, 2019: Brain Stimulation
https://read.qxmd.com/read/31139099/trajectories-of-dynamic-risk-factors-as-predictors-of-violence-and-criminality-in-patients-discharged-from-mental-health-services-a-longitudinal-study-using-growth-mixture-modeling
#29
Mélissa Beaudoin, Stéphane Potvin, Laura Dellazizzo, Mimosa Luigi, Charles-Edouard Giguère, Alexandre Dumais
Background: Individuals with severe mental illnesses are at greater risk of offenses and violence, though the relationship remains unclear due to the interplay of static and dynamic risk factors. Static factors have generally been emphasized, leaving little room for temporal changes in risk. Hence, this longitudinal study aims to identify subgroups of psychiatric populations at risk of violence and criminality by taking into account the dynamic changes of symptomatology and substance use. Method: A total of 825 patients from the MacArthur Violence Risk Assessment Study having completed five postdischarge follow-ups were analyzed...
2019: Frontiers in Psychiatry
https://read.qxmd.com/read/31051434/state-representation-in-mental-illness
#30
REVIEW
Angela Radulescu, Yael Niv
Reinforcement learning theory provides a powerful set of computational ideas for modeling human learning and decision making. Reinforcement learning algorithms rely on state representations that enable efficient behavior by focusing only on aspects relevant to the task at hand. Forming such representations often requires selective attention to the sensory environment, and recalling memories of relevant past experiences. A striking range of psychiatric disorders, including bipolar disorder and schizophrenia, involve changes in these cognitive processes...
April 30, 2019: Current Opinion in Neurobiology
https://read.qxmd.com/read/31029196/computational-modeling-in-pediatric-mental-health
#31
EDITORIAL
Joel Stoddard, Matt Jones
Computational modeling has recently become of great interest to mental health clinicians as a tool for discovering the nature of pathophysiology and for clinical assessment, prediction, and treatment. Computational psychiatry is a term used to describe the application of computational modeling to behavioral and mental health problems. The National Institute of Mental Health (NIMH) has taken an interest in computational modeling, suggesting applications of interest, such as understanding the neural basis of mental illness, discovering new treatments, and predicting treatment response...
May 2019: Journal of the American Academy of Child and Adolescent Psychiatry
https://read.qxmd.com/read/30999271/machine-learning-and-big-data-in-psychiatry-toward-clinical-applications
#32
REVIEW
Robb B Rutledge, Adam M Chekroud, Quentin Jm Huys
Psychiatry is a medical field concerned with the treatment of mental illness. Psychiatric disorders broadly relate to higher functions of the brain, and as such are richly intertwined with social, cultural, and experiential factors. This makes them exquisitely complex phenomena that depend on and interact with a large number of variables. Computational psychiatry provides two ways of approaching this complexity. Theory-driven computational approaches employ mechanistic models to make explicit hypotheses at multiple levels of analysis...
April 2019: Current Opinion in Neurobiology
https://read.qxmd.com/read/30987923/the-abiding-relevance-of-mouse-models-of-rare-mutations-to-psychiatric-neuroscience-and-therapeutics
#33
Joseph A Gogos, Gregg Crabtree, Anastasia Diamantopoulou
Studies using powerful family-based designs aided by large scale case-control studies, have been instrumental in cracking the genetic complexity of the disease, identifying rare and highly penetrant risk mutations and providing a handle on experimentally tractable model systems. Mouse models of rare mutations, paired with analysis of homologous cognitive and sensory processing deficits and state-of-the-art neuroscience methods to manipulate and record neuronal activity have started providing unprecedented insights into pathogenic mechanisms and building the foundation of a new biological framework for understanding mental illness...
April 12, 2019: Schizophrenia Research
https://read.qxmd.com/read/30979917/predictive-big-data-analytics-using-the-uk-biobank-data
#34
Yiwang Zhou, Lu Zhao, Nina Zhou, Yi Zhao, Simeone Marino, Tuo Wang, Hanbo Sun, Arthur W Toga, Ivo D Dinov
The UK Biobank is a rich national health resource that provides enormous opportunities for international researchers to examine, model, and analyze census-like multisource healthcare data. The archive presents several challenges related to aggregation and harmonization of complex data elements, feature heterogeneity and salience, and health analytics. Using 7,614 imaging, clinical, and phenotypic features of 9,914 subjects we performed deep computed phenotyping using unsupervised clustering and derived two distinct sub-cohorts...
April 12, 2019: Scientific Reports
https://read.qxmd.com/read/30975539/smoking-cessation-for-people-with-severe-mental-illness-scimitar-a-pragmatic-randomised-controlled-trial
#35
RANDOMIZED CONTROLLED TRIAL
Simon Gilbody, Emily Peckham, Della Bailey, Catherine Arundel, Paul Heron, Suzanne Crosland, Caroline Fairhurst, Catherine Hewitt, Jinshuo Li, Steve Parrott, Tim Bradshaw, Michelle Horspool, Elizabeth Hughes, Tom Hughes, Suzy Ker, Moira Leahy, Tayla McCloud, David Osborn, Joe Reilly, Thomas Steare, Emma Ballantyne, Polly Bidwell, Sue Bonner, Diane Brennan, Tracy Callen, Alex Carey, Charlotte Colbeck, Debbie Coton, Emma Donaldson, Kimberley Evans, Hannah Herlihy, Wajid Khan, Lizwi Nyathi, Elizabeth Nyamadzawo, Helen Oldknow, Peter Phiri, Shanaya Rathod, Jamie Rea, Crystal-Bella Romain-Hooper, Kaye Smith, Alison Stribling, Carinna Vickers
BACKGROUND: People with severe mental illnesses such as schizophrenia are three times more likely to smoke than the wider population, contributing to widening health inequalities. Smoking remains the largest modifiable risk factor for this health inequality, but people with severe mental illness have not historically engaged with smoking cessation services. We aimed to test the effectiveness of a combined behavioural and pharmacological smoking cessation intervention targeted specifically at people with severe mental illness...
May 2019: Lancet Psychiatry
https://read.qxmd.com/read/30956137/depressive-symptoms-predict-characteristics-of-online-social-networks
#36
Sonya Negriff
PURPOSE: There is a substantial body of literature that examines depression or well-being as outcomes of social media use, but there are fewer studies that seek to understand how mental health may lead to different patterns of online interactions. The purpose of the present study was to examine how depressive symptoms may predict subsequent structural characteristics of the online social network. METHODS: Data came from Time 3 and Time 5 of a longitudinal study on the effects of maltreatment on adolescent development...
April 4, 2019: Journal of Adolescent Health
https://read.qxmd.com/read/30935485/quantitative-system-pharmacology-qsp-an-integrative-framework-for-paradigm-change-in-the-treatment-of-the-first-episode-schizophrenia
#37
F Gaillard-Bigot, X-Y Zendjidjian, F Kheloufi, C Casse-Perrot, R Guilhaumou, J Micallef, E Fakra, J-M Azorin, O Blin
Despite the lack of progress in the curative treatment of mental illness, especially schizophrenia, the accumulation of neuroscience data over the past decade suggests the re-conceptualization of schizophrenia. With the advent of new biomarkers and cognitive tools, new neuroscience technologies such as functional dynamic connectivity and the identification of subtle clinical features; it is now possible to detect early stages at risk or prodromes of a first psychotic episode. Current concepts reconceptualizes schizophrenia as a neurodevelopmental disorder at early onset, with polygenic risk and only symptomatic treatment for positive symptoms at this time...
December 2018: L'Encéphale
https://read.qxmd.com/read/30919476/commentary-building-the-developmental-foundations-of-developmental-computational-psychiatry-reflections-on-hauser-et-al-2019
#38
Katherine E Kabotyanski, Michael D Mayer, Mahalia Prater Fahey, Leah H Somerville
There is a growing interest in applying the conceptual and analytical frameworks of computational psychiatry to developmental populations. This is motivated by appreciation that psychiatric illness needs to be understood from a neurodevelopmental perspective. The target article by Hauser and colleagues highlights progress in applying the computational psychiatry perspectives to identifying the developmental mechanisms of mental illness. We share the enthusiasm and optimism for this venture, while recognizing the substantial theoretical and pragmatic challenges associated with applying computational frameworks to developing populations...
April 2019: Journal of Child Psychology and Psychiatry, and Allied Disciplines
https://read.qxmd.com/read/30900075/measuring-situation-awareness-and-team-effectiveness-in-pediatric-acute-care-by-using-the-situation-global-assessment-technique
#39
Ester Coolen, Jos Draaisma, Jan Loeffen
Situation awareness (SA) is an important human factor and necessary for effective teamwork and patient safety. Human patient simulation (HPS) with video feedback allows for a safe environment where health care professionals can develop both technical and teamwork skills. It is, however, very difficult to observe and measure SA directly. The Situation Global Assessment Technique (SAGAT) was developed by Endsley to measure SA during real-time simulation. Our objective was to measure SA among team members during simulation of acute pediatric care scenarios on the medical ward and its relationship with team effectiveness...
June 2019: European Journal of Pediatrics
https://read.qxmd.com/read/30863072/bipolar-spectrum-disorders-and-associated-factors-among-adults-attending-an-antiretroviral-therapy-clinic-in-gedeo-zone-health-centers-southern-ethiopia
#40
Zelalem Belayneh, Wagaye Alemu, Birhanie Mekuriaw, Zegeye Abebe
Background: Bipolar spectrum disorders (BPSDs) are more common among HIV-positive individuals than the general population. Although BPSDs have very diverse and devastating consequences (immune suppression, cognitive impairment and poor medication adherence), little is known about BPSDs among HIV-positive individuals in Ethiopia. Therefore, this study was aimed to assess the prevalence and associated factors of BPSDs among adults attending antiretroviral therapy (ART) clinics in Gedeo zone health centers, southern Ethiopia...
2019: Neuropsychiatric Disease and Treatment
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