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https://www.readbyqxmd.com/read/29325409/all-health-partnerships-great-and-small-comparing-mandated-with-emergent-health-partnerships-comment-on-evaluating-global-health-partnerships-a-case-study-of-a-gavi-hpv-vaccine-application-process-in-uganda
#1
Elaine Green, Dan Ritman, Graeme Chisholm
The plurality of healthcare providers and funders in low- and middle-income countries (LMICs) has given rise to an era in which health partnerships are becoming the norm in international development. Whether mandated or emergent, three common drivers are essential for ensuring successful health partnerships: trust; a diverse and inclusive network; and a clear governance structure. Mandated and emergent health partnerships operate as very different models and at different scales. However, there is potential for sharing and learning between these types of partnerships...
June 11, 2017: International Journal of Health Policy and Management
https://www.readbyqxmd.com/read/29317007/growing-health-partnerships-in-rural-and-remote-communities-what-drives-the-joint-efforts-of-primary-schools-and-universities-in-maintaining-service-learning-partnerships
#2
Sue Kirby, Fabian P Held, Debra Jones, David Lyle
Aim This study explored the partnership between universities and local primary schools to deliver a classroom-based paediatric communication impairment service provided by undergraduate speech pathology students. It aimed to understand how partnerships work to facilitate programme replication. BACKGROUND: The partners included universities sending students on rural clinical placement, local host academic units and primary schools who worked together to provide paediatric speech and language services in primary schools in three sites in Australia...
January 10, 2018: Primary Health Care Research & Development
https://www.readbyqxmd.com/read/29306372/twitter-journal-clubs-and-continuing-professional-development-an-analysis-of-a-medradjclub-tweet-chat
#3
A Bolderston, J Watson, N Woznitza, A Westerink, L Di Prospero, G Currie, C Beardmore, J Hewis
INTRODUCTION: Online Twitter journal clubs are a recent and popular innovation with the potential to increase research awareness and inform practice. The medical radiation sciences' MedRadJournalClub (MJRC) is a Twitter-based event that attracts a global group of participants at the monthly chats. An analysis of a recent MedRadJournalClub discussion evaluated the perceived benefits and limitations of medical radiation practitioners participating in an online journal club. METHODS: The February 2017 chat used for analysis was based on the Journal of Medical Imaging and Radiation Sciences article by Currie et al...
February 2018: Radiography
https://www.readbyqxmd.com/read/29273572/facebook-groups-as-a-powerful-and-dynamic-tool-in-medical-education-mixed-method-study
#4
Leo Nicolai, Moritz Schmidbauer, Maximilian Gradel, Sabine Ferch, Sofía Antón, Boj Hoppe, Tanja Pander, Philip von der Borch, Severin Pinilla, Martin Fischer, Konstantinos Dimitriadis
BACKGROUND: Social networking sites, in particular Facebook, are not only predominant in students' social life but are to varying degrees interwoven with the medical curriculum. Particularly, Facebook groups have been identified for their potential in higher education. However, there is a paucity of data on user types, content, and dynamics of study-related Facebook groups. OBJECTIVE: The aim of this study was to identify the role of study-related Facebook group use, characterize medical students that use or avoid using Facebook groups (demographics, participation pattern, and motivation), and analyze student posting behavior, covered topics, dynamics, and limitations in Facebook groups with regards to educational usage...
December 22, 2017: Journal of Medical Internet Research
https://www.readbyqxmd.com/read/29244814/forecasting-influenza-like-illness-dynamics-for-military-populations-using-neural-networks-and-social-media
#5
Svitlana Volkova, Ellyn Ayton, Katherine Porterfield, Courtney D Corley
This work is the first to take advantage of recurrent neural networks to predict influenza-like illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of historical ILI data and the state-of-the-art machine learning models, we build and evaluate the predictive power of neural network architectures based on Long Short Term Memory (LSTMs) units capable of nowcasting (predicting in "real-time") and forecasting (predicting the future) ILI dynamics in the 2011 - 2014 influenza seasons...
2017: PloS One
https://www.readbyqxmd.com/read/29222076/adverse-drug-event-discovery-using-biomedical-literature-a-big-data-neural-network-adventure
#6
Ahmad P Tafti, Jonathan Badger, Eric LaRose, Ehsan Shirzadi, Andrea Mahnke, John Mayer, Zhan Ye, David Page, Peggy Peissig
BACKGROUND: The study of adverse drug events (ADEs) is a tenured topic in medical literature. In recent years, increasing numbers of scientific articles and health-related social media posts have been generated and shared daily, albeit with very limited use for ADE study and with little known about the content with respect to ADEs. OBJECTIVE: The aim of this study was to develop a big data analytics strategy that mines the content of scientific articles and health-related Web-based social media to detect and identify ADEs...
December 8, 2017: JMIR Medical Informatics
https://www.readbyqxmd.com/read/29208026/operationalizing-mhealth-to-improve-patient-care-a-qualitative-implementation-science-evaluation-of-the-weltel-texting-intervention-in-canada-and-kenya
#7
Kevin Louis Bardosh, Melanie Murray, Antony M Khaemba, Kirsten Smillie, Richard Lester
BACKGROUND: Mobile health (mHealth) applications have proliferated across the globe with much enthusiasm, although few have reached scale and shown public health impact. In this study, we explored how different contextual factors influenced the implementation, effectiveness and potential for scale-up of WelTel, an easy-to-use and evidence-based mHealth intervention. WelTel uses two-way SMS communication to improve patient adherence to medication and engagement in care, and has been developed and tested in Canada and Kenya...
December 6, 2017: Globalization and Health
https://www.readbyqxmd.com/read/29197929/transdiagnostic-symptom-clusters-and-associations-with-brain-behavior-and-daily-function-in-mood-anxiety-and-trauma-disorders
#8
Katherine A Grisanzio, Andrea N Goldstein-Piekarski, Michelle Yuyun Wang, Abdullah P Rashed Ahmed, Zoe Samara, Leanne M Williams
Importance: The symptoms that define mood, anxiety, and trauma disorders are highly overlapping across disorders and heterogeneous within disorders. It is unknown whether coherent subtypes exist that span multiple diagnoses and are expressed functionally (in underlying cognition and brain function) and clinically (in daily function). The identification of cohesive subtypes would help disentangle the symptom overlap in our current diagnoses and serve as a tool for tailoring treatment choices...
December 3, 2017: JAMA Psychiatry
https://www.readbyqxmd.com/read/29174946/fluoxetine-not-donepezil-reverses-anhedonia-cognitive-dysfunctions-and-hippocampal-proteome-changes-during-repeated-social-defeat-exposure
#9
M G Gottschalk, P Mortas, M Haman, S Ozcan, B Biemans, S Bahn
While anhedonia is considered a core symptom of major depressive disorder (MDD), less attention has been paid to cognitive dysfunctions. We evaluated the behavioural and molecular effects of a selective serotonin re-uptake inhibitor (SSRI, fluoxetine) and an acetylcholinesterase inhibitor (AChEI, donepezil) on emotional-cognitive endophenotypes of depression and the hippocampal proteome. A chronic social defeat (SD) procedure was followed up by "reminder" sessions of direct and indirect SD. Anhedonia-related behaviour was assessed longitudinally by intracranial self-stimulation (ICSS)...
November 23, 2017: European Neuropsychopharmacology: the Journal of the European College of Neuropsychopharmacology
https://www.readbyqxmd.com/read/29165084/advances-on-automatic-speech-analysis-for-early-detection-of-alzheimer-disease-a-non-linear-multi-task-approach
#10
Karmele Lopez-de-Ipina, Unai Martinez-de-Lizarduy, Pilar M Calvo, Jiri Mekyska, Blanca Beitia, Nora Barroso, Ainara Estanga, Milkel Tainta, Mirian Ecay-Torres
OBJECTIVE: Nowadays proper detection of cognitive impairment has become a challenge for the scientific community. Alzheimer's Disease (AD), the most common cause of dementia, has a high prevalence that is increasing at a fast pace towards epidemic level. In the not-so-distant future this fact could have a dramatic social and economic impact. In this scenario, an early and accurate diagnosis of AD could help to decrease its effects on patients, relatives and society. Over the last decades there have been useful advances not only in classic assessment techniques, but also in novel non-invasive screening methodologies...
2018: Current Alzheimer Research
https://www.readbyqxmd.com/read/29154409/sensitive-topics-missing-data-and-refusal-in-social-network-studies-an-ethical-examination
#11
Erin Rose Ellison, Regina Day Langhout
We describe our ethics-driven process of addressing missing data within a social network study about accountability for racism, classism, sexism, heterosexism, cis-sexism, ableism, and other forms of oppression among social justice union organizers. During data collection, some would-be participants did not return emails and others explicitly refused to engage in the research. All refusals came from women of color. We faced an ethical dilemma: Should we continue to seek participation from those who had not yet responded, with the hopes of recruiting more women of color from within the network so their perspectives would not be tokenized? Or, should we stop asking those who had been contacted multiple times, which would compromise the social network data and analysis? We delineate ways in which current discussions of the ethics of social network studies fell short, given our framework and our community psychology (CP) values...
November 20, 2017: American Journal of Community Psychology
https://www.readbyqxmd.com/read/29151574/machine-learning-meets-complex-networks-via-coalescent-embedding-in-the-hyperbolic-space
#12
Alessandro Muscoloni, Josephine Maria Thomas, Sara Ciucci, Ginestra Bianconi, Carlo Vittorio Cannistraci
Physicists recently observed that realistic complex networks emerge as discrete samples from a continuous hyperbolic geometry enclosed in a circle: the radius represents the node centrality and the angular displacement between two nodes resembles their topological proximity. The hyperbolic circle aims to become a universal space of representation and analysis of many real networks. Yet, inferring the angular coordinates to map a real network back to its latent geometry remains a challenging inverse problem...
November 20, 2017: Nature Communications
https://www.readbyqxmd.com/read/29119693/the-neural-representation-of-social-status-in-the-extended-face-processing-network
#13
Jessica E Koski, Jessica A Collins, Ingrid R Olson
Social status is a salient cue that shapes our judgment and memory for other people and ultimately guides our social interactions. Despite the pervasive influence of status on social behavior, how information about the status of others is represented in the brain remains unclear. Here, we tested the hypothesis that social-status information is embedded in our neural representations of other individuals. Participants learned to associate faces with names, job titles that that varied in associated status, and explicit markers of reputational status (star ratings)...
November 9, 2017: European Journal of Neuroscience
https://www.readbyqxmd.com/read/29084280/maximum-entropy-methods-for-extracting-the-learned-features-of-deep-neural-networks
#14
Alex Finnegan, Jun S Song
New architectures of multilayer artificial neural networks and new methods for training them are rapidly revolutionizing the application of machine learning in diverse fields, including business, social science, physical sciences, and biology. Interpreting deep neural networks, however, currently remains elusive, and a critical challenge lies in understanding which meaningful features a network is actually learning. We present a general method for interpreting deep neural networks and extracting network-learned features from input data...
October 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/29067872/selective-neural-sensitivity-to-familial-threat-in-adolescents-with-weak-family-bonds
#15
Paul B Sharp, Wendy Heller, Eva H Telzer
Familial stressors, such as weak familial connectedness, are associated with the development of maladaptive threat processing, yet little is known regarding how weak familial bonds impinge on biological mechanisms of threat processing. The present study leveraged multivoxel pattern analysis of fMRI data to compare the neural encoding of familial and nonfamilial threatening and non-threatening stimuli in adolescents who endorsed varying levels of connectedness to their families. Adolescents (N=22, Mage= 14.38 years) reporting lower family connectedness one year earlier showed elevated sensitivity to familial threat, but not to nonfamilial threat in a neural network associated with threat processing, comprising left and right amygdala, and right inferior and middle temporal gyri...
October 25, 2017: Social Neuroscience
https://www.readbyqxmd.com/read/29061891/the-conceptual-foundations-of-network-based-diffusion-analysis-choosing-networks-and-interpreting-results
#16
Will Hoppitt
Network-based diffusion analysis (NBDA) is a statistical technique for detecting the social transmission of behavioural innovations in groups of animals, including humans. The strength of social transmission is inferred from the extent to which the diffusion (spread) of the innovation follows a social network. NBDA can have two goals: (a) to establish whether social transmission is occurring and how strong its effects are; and/or (b) to establish the typical pathways of information transfer. The technique has been used in a range of taxa, including primates, cetaceans, birds and fish, using a range of different types of network...
December 5, 2017: Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
https://www.readbyqxmd.com/read/29052021/a-new-approach-to-predict-user-mobility-using-semantic-analysis-and-machine-learning
#17
Roshan Fernandes, Rio D'Souza G L
Mobility prediction is a technique in which the future location of a user is identified in a given network. Mobility prediction provides solutions to many day-to-day life problems. It helps in seamless handovers in wireless networks to provide better location based services and to recalculate paths in Mobile Ad hoc Networks (MANET). In the present study, a framework is presented which predicts user mobility in presence and absence of mobility history. Naïve Bayesian classification algorithm and Markov Model are used to predict user future location when user mobility history is available...
October 19, 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/29017620/familial-aggregation-of-matrics-consensus-cognitive-battery-scores-in-a-large-sample-of-outpatients-with-schizophrenia-and-their-unaffected-relatives
#18
A Mucci, S Galderisi, M F Green, K Nuechterlein, P Rucci, D Gibertoni, A Rossi, P Rocca, A Bertolino, P Bucci, G Hellemann, M Spisto, D Palumbo, E Aguglia, G Amodeo, M Amore, A Bellomo, R Brugnoli, B Carpiniello, L Dell'Osso, F Di Fabio, M di Giannantonio, G Di Lorenzo, C Marchesi, P Monteleone, C Montemagni, L Oldani, R Romano, R Roncone, P Stratta, E Tenconi, A Vita, P Zeppegno, M Maj
BACKGROUND: The increased use of the MATRICS Consensus Cognitive Battery (MCCB) to investigate cognitive dysfunctions in schizophrenia fostered interest in its sensitivity in the context of family studies. As various measures of the same cognitive domains may have different power to distinguish between unaffected relatives of patients and controls, the relative sensitivity of MCCB tests for relative-control differences has to be established. We compared MCCB scores of 852 outpatients with schizophrenia (SCZ) with those of 342 unaffected relatives (REL) and a normative Italian sample of 774 healthy subjects (HCS)...
October 11, 2017: Psychological Medicine
https://www.readbyqxmd.com/read/28989752/cultural-investment-and-urban-socio-economic-development-a-geosocial-network-approach
#19
Xiao Zhou, Desislava Hristova, Anastasios Noulas, Cecilia Mascolo, Max Sklar
Being able to assess the impact of government-led investment onto socio-economic indicators in cities has long been an important target of urban planning. However, owing to the lack of large-scale data with a fine spatio-temporal resolution, there have been limitations in terms of how planners can track the impact and measure the effectiveness of cultural investment in small urban areas. Taking advantage of nearly 4 million transition records for 3 years in London from a popular location-based social network service, Foursquare, we study how the socio-economic impact of government cultural expenditure can be detected and predicted...
September 2017: Royal Society Open Science
https://www.readbyqxmd.com/read/28968847/multidimensional-neuroanatomical-subtyping-of-autism-spectrum-disorder
#20
Seok-Jun Hong, Sofie L Valk, Adriana Di Martino, Michael P Milham, Boris C Bernhardt
Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders with multiple biological etiologies and highly variable symptoms. Using a novel analytical framework that integrates cortex-wide MRI markers of vertical (i.e., thickness, tissue contrast) and horizontal (i.e., surface area, geodesic distance) cortical organization, we could show that a large multi-centric cohort of individuals with ASD falls into 3 distinctive anatomical subtypes (ASD-I: cortical thickening, increased surface area, tissue blurring; ASD-II: cortical thinning, decreased distance; ASD-III: increased distance)...
September 14, 2017: Cerebral Cortex
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