A study of a culturally focused psychiatric consultation service for Asian American and Latino American primary care patients with depression

<p>Abstract</p> <p>Background</p> <p>Ethnic minorities with depression are more likely to seek mental health care through primary care providers (PCPs) than mental health specialists. However, both provider and patient-specific challenges exist. PCP-specific challenges include unfamiliarity with depressive symptom profiles in diverse patient populations, limited time to address mental health, and limited referral options for mental health care. Patient-specific challenges include stigma around mental health issues and reluctance to seek mental health treatment. To address these issues, we implemented a multi-component intervention for Asian American and Latino American primary care patients with depression at Massachusetts General Hospital (MGH).</p> <p>Methods/Design</p> <p>We propose a randomized controlled trial to evaluate a culturally appropriate intervention to improve the diagnosis and treatment of depression in our target population. Our goals are to facilitate a) primary care providers' ability to provide appropriate, culturally informed care of depression, and b) patients' knowledge of and resources for receiving treatment for depression. Our two-year long intervention targets Asian American and Latino American adult (18 years of age or older) primary care patients at MGH screening positive for symptoms of depression. All eligible patients in the intervention arm of the study who screen positive will be offered a culturally focused psychiatric (CFP) consultation. Patients will meet with a study clinician and receive toolkits that include psychoeducational booklets, worksheets and community resources. Within two weeks of the initial consultation, patients will attend a follow-up visit with the CFP clinicians. Primary outcomes will determine the feasibility and cost associated with implementation of the service, and evaluate patient and provider satisfaction with the CFP service. Exploratory aims will describe the study population at screening, recruitment, and enrollment and identify which variables influenced patient participation in the program.</p> <p>Discussion</p> <p>The study involves an innovative yet practical intervention that builds on existing resources and strives to improve quality of care for depression for minorities. Additionally, it complements the current movement in psychiatry to enhance the treatment of depression in primary care settings. If found beneficial, the intervention will serve as a model for care of Asian American and Latino American patients.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT01239407">NCT01239407</a></p

Optimizing microsurgical skills with EEG neurofeedback

Background By enabling individuals to self-regulate their brainwave activity in the field of optimal performance in healthy individuals, neurofeedback has been found to improve cognitive and artistic performance. Here we assessed whether two distinct EEG neurofeedback protocols could develop surgical skill, given the important role this skill plays in medicine. Results National Health Service trainee ophthalmic microsurgeons (N = 20) were randomly assigned to either Sensory Motor Rhythm-Theta (SMR) or Alpha-Theta (AT) groups, a randomized subset of which were also part of a wait-list 'no-treatment' control group (N = 8). Neurofeedback groups received eight 30-minute sessions of EEG training. Pre-post assessment included a skills lab surgical procedure with timed measures and expert ratings from video-recordings by consultant surgeons, together with state/trait anxiety self-reports. SMR training demonstrated advantages absent in the control group, with improvements in surgical skill according to 1) the expert ratings: overall technique (d = 0.6, p < 0.03) and suture task (d = 0.9, p < 0.02) (judges' intraclass correlation coefficient = 0.85); and 2) with overall time on task (d = 0.5, p = 0.02), while everyday anxiety (trait) decreased (d = 0.5, p < 0.02). Importantly the decrease in surgical task time was strongly associated with SMR EEG training changes (p < 0.01), especially with continued reduction of theta (4–7 Hz) power. AT training produced marginal improvements in technique and overall performance time, which were accompanied by a standard error indicative of large individual differences. Notwithstanding, successful within session elevation of the theta-alpha ratio correlated positively with improvements in overall technique (r = 0.64, p = 0.047). Conclusion SMR-Theta neurofeedback training provided significant improvement in surgical technique whilst considerably reducing time on task by 26%. There was also evidence that AT training marginally reduced total surgery time, despite suboptimal training efficacies. Overall, the data set provides encouraging evidence of optimised learning of a complex medical specialty via neurofeedback training

Poliomyelitis surveillance report number 18, May 20, 1955

Dr. Edwin Lennette, Virus Laboratory, California Department of Public Health, reports isolation of type 1 virus from the stool of case PSU No. Cal-21. He also reports isolation of type 1 virus from the stool of a third \uc2\ub0th contact of non-paralytic case PSU No. Cal-14. Isolations from 2 other contacts of this case were previously reported.Dr. Werner Henle, Children\ue2\u20ac\u2122s Hospital, Philadelphia, reports isolation of type 1 poliomyelitis virus from Case PSU No. Pa-2. This is the first isolation from a case receiving Wyeth Vaccine. This case had first paralysis at the same site as inoculation.One new case was accepted today from West Virginia. This seven-year-old female developed bulbar signs 26 days after inoculation with Lilly Vaccine. Vaccinated cases total 79 at 12:00 noon 5-20-55 (Table l)

Evolutionary Computation, Optimization and Learning Algorithms for Data Science

A large number of engineering, science and computational problems have yet to be solved in a computationally efficient way. One of the emerging challenges is how evolving technologies grow towards autonomy and intelligent decision making. This leads to collection of large amounts of data from various sensing and measurement technologies, e.g., cameras, smart phones, health sensors, smart electricity meters, and environment sensors. Hence, it is imperative to develop efficient algorithms for generation, analysis, classification, and illustration of data. Meanwhile, data is structured purposefully through different representations, such as large-scale networks and graphs. We focus on data science as a crucial area, specifically focusing on a curse of dimensionality (CoD) which is due to the large amount of generated/sensed/collected data. This motivates researchers to think about optimization and to apply nature-inspired algorithms, such as evolutionary algorithms (EAs) to solve optimization problems. Although these algorithms look un-deterministic, they are robust enough to reach an optimal solution. Researchers do not adopt evolutionary algorithms unless they face a problem which is suffering from placement in local optimal solution, rather than global optimal solution. In this chapter, we first develop a clear and formal definition of the CoD problem, next we focus on feature extraction techniques and categories, then we provide a general overview of meta-heuristic algorithms, its terminology, and desirable properties of evolutionary algorithms

Social Algorithms

This article concerns the review of a special class of swarm intelligence based algorithms for solving optimization problems and these algorithms can be referred to as social algorithms. Social algorithms use multiple agents and the social interactions to design rules for algorithms so as to mimic certain successful characteristics of the social/biological systems such as ants, bees, bats, birds and animals.Comment: Encyclopedia of Complexity and Systems Science, 201

Historical Research Approaches to the Analysis of Internationalisation

Historical research methods and approaches can improve understanding of the most appropriate techniques to confront data and test theories in internationalisation research. A critical analysis of all “texts” (sources), time series analyses, comparative methods across time periods and space, counterfactual analysis and the examination of outliers are shown to have the potential to improve research practices. Examples and applications are shown in these key areas of research with special reference to internationalisation processes. Examination of these methods allows us to see internationalisation processes as a sequenced set of decisions in time and space, path dependent to some extent but subject to managerial discretion. Internationalisation process research can benefit from the use of historical research methods in analysis of sources, production of time-lines, using comparative evidence across time and space and in the examination of feasible alternative choices

Resisting Sleep Pressure:Impact on Resting State Functional Network Connectivity

In today's 24/7 society, sleep restriction is a common phenomenon which leads to increased levels of sleep pressure in daily life. However, the magnitude and extent of impairment of brain functioning due to increased sleep pressure is still not completely understood. Resting state network (RSN) analyses have become increasingly popular because they allow us to investigate brain activity patterns in the absence of a specific task and to identify changes under different levels of vigilance (e.g. due to increased sleep pressure). RSNs are commonly derived from BOLD fMRI signals but studies progressively also employ cerebral blood flow (CBF) signals. To investigate the impact of sleep pressure on RSNs, we examined RSNs of participants under high (19 h awake) and normal (10 h awake) sleep pressure with three imaging modalities (arterial spin labeling, BOLD, pseudo BOLD) while providing confirmation of vigilance states in most conditions. We demonstrated that CBF and pseudo BOLD signals (measured with arterial spin labeling) are suited to derive independent component analysis based RSNs. The spatial map differences of these RSNs were rather small, suggesting a strong biological substrate underlying these networks. Interestingly, increased sleep pressure, namely longer time awake, specifically changed the functional network connectivity (FNC) between RSNs. In summary, all FNCs of the default mode network with any other network or component showed increasing effects as a function of increased 'time awake'. All other FNCs became more anti-correlated with increased 'time awake'. The sensorimotor networks were the only ones who showed a within network change of FNC, namely decreased connectivity as function of 'time awake'. These specific changes of FNC could reflect both compensatory mechanisms aiming to fight sleep as well as a first reduction of consciousness while becoming drowsy. We think that the specific changes observed in functional network connectivity could imply an impairment of information transfer between the affected RSNs

Genetic-based approach for cue phrase selection in dialogue act recognition

Automatic cue phrase selection is a crucial step for designing a dialogue act recognition model using machine learning techniques. The approaches, currently used, are based on specific type of feature selection approaches, called ranking approaches. Despite their computational efficiency for high dimensional domains, they are not optimal with respect to relevance and redundancy. In this paper we propose a genetic-based approach for cue phrase selection which is, essentially, a variable length genetic algorithm developed to cope with the high dimensionality of the domain. We evaluate the performance of the proposed approach against several ranking approaches. Additionally, we assess its performance for the selection of cue phrases enriched by phrase’s type and phrase’s position. The results provide experimental evidences on the ability of the genetic-based approach to handle the drawbacks of the ranking approaches and to exploit cue’s type and cue’s position information to improve the selection. Furthermore, we validate the use of the genetic-based approach for machine learning applications. We use selected sets of cue phrases for building a dynamic Bayesian networks model for dialogue act recognition. The results show its usefulness for machine learning applications

Effectiveness of individualized physiotherapy on pain and functioning compared to a standard exercise protocol in patients presenting with clinical signs of subacromial impingement syndrome. A randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Shoulder impingement syndrome is a common musculoskeletal complaint leading to significant reduction of health and disability. Physiotherapy is often the first choice of treatment although its effectiveness is still under debate. Systematic reviews in this field highlight the need for more high quality trials to investigate the effectiveness of physiotherapy interventions in patients with subacromial impingement syndrome.</p> <p>Methods/Design</p> <p>This randomized controlled trial will investigate the effectiveness of individualized physiotherapy in patients presenting with clinical signs and symptoms of subacromial impingement, involving 90 participants aged 18-75. Participants are recruited from outpatient physiotherapy clinics, general practitioners, and orthopaedic surgeons in Germany. Eligible participants will be randomly allocated to either individualized physiotherapy or to a standard exercise protocol using central randomization.</p> <p>The control group will perform the standard exercise protocol aiming to restore muscular deficits in strength, mobility, and coordination of the rotator cuff and the shoulder girdle muscles to unload the subacromial space during active movements. Participants of the intervention group will perform the standard exercise protocol as a home program, and will additionally be treated with individualized physiotherapy based on clinical examination results, and guided by a decision tree. After the intervention phase both groups will continue their home program for another 7 weeks.</p> <p>Outcome will be measured at 5 weeks and at 3 and 12 months after inclusion using the shoulder pain and disability index and patients' global impression of change, the generic patient-specific scale, the average weekly pain score, and patient satisfaction with treatment. Additionally, the fear avoidance beliefs questionnaire, the pain catastrophizing scale, and patients' expectancies of treatment effect are assessed. Participants' adherence to the protocol, use of additional treatments for the shoulder, direct and indirect costs, and sick leave due to shoulder complaints will be recorded in a shoulder log-book.</p> <p>Discussion</p> <p>To our knowledge this is the first trial comparing individualized physiotherapy based on a defined decision making process to a standardized exercise protocol. Using high-quality methodologies, this trial will add evidence to the limited body of knowledge about the effect of physiotherapy in patients with SIS.</p> <p>Trial registration</p> <p>Current Controlled Trials ISRCTN86900354</p

An update of the Worldwide Integrated Assessment (WIA) on systemic insecticides. Part 2: impacts on organisms and ecosystems

New information on the lethal and sublethal effects of neonicotinoids and fipronil on organisms is presented in this review, complementing the previous WIA in 2015. The high toxicity of these systemic insecticides to invertebrates has been confirmed and expanded to include more species and compounds. Most of the recent research has focused on bees and the sublethal and ecological impacts these insecticides have on pollinators. Toxic effects on other invertebrate taxa also covered predatory and parasitoid natural enemies and aquatic arthropods. Little, while not much new information has been gathered on soil organisms. The impact on marine coastal ecosystems is still largely uncharted. The chronic lethality of neonicotinoids to insects and crustaceans, and the strengthened evidence that these chemicals also impair the immune system and reproduction, highlights the dangers of this particular insecticidal classneonicotinoids and fipronil. , withContinued large scale – mostly prophylactic – use of these persistent organochlorine pesticides has the potential to greatly decreasecompletely eliminate populations of arthropods in both terrestrial and aquatic environments. Sublethal effects on fish, reptiles, frogs, birds and mammals are also reported, showing a better understanding of the mechanisms of toxicity of these insecticides in vertebrates, and their deleterious impacts on growth, reproduction and neurobehaviour of most of the species tested. This review concludes with a summary of impacts on the ecosystem services and functioning, particularly on pollination, soil biota and aquatic invertebrate communities, thus reinforcing the previous WIA conclusions (van der Sluijs et al. 2015)