Notes

Functional attribute files with regard to vascular seed types through northeastern United states.
General self- efficacy and internalized stigma emerged as predictors of overall work and social adjustment.

The study has implications for interventions that need to target beliefs about illness in order to maximize help-seeking and reduce treatment gap.
The study has implications for interventions that need to target beliefs about illness in order to maximize help-seeking and reduce treatment gap.Attention deficits have been proven in patients with major depressive disorder (MDD). However, a detailed characterization of attention deficits in MDD was unclear. The aim of current study was to explore the specific deficits of attention in different sub-domains of attention so as to produce an overall picture of contemporary research on this field. We performed a systematic review and meta-analysis of published researches. PubMed, EMBASE, Cochrane Library and review of references were searched up to October 2019. Studies using at least one objective measurement to assess attention performances of MDD patients were included. Effect sizes were calculated using random-effects models for attention outcomes. Publication bias was evaluated using Egger's test. Twenty-three eligible studies including 1371 MDD patients were enrolled in this meta-analysis. Significant deficit of global attention was observed. For the specific outcomes, MDD patients showed significant deficits in psychomotor speed/attention, auditory attention, visuo-spatial attention, sustained visual attention, ranging from small to moderate, but not in selective attention. Larger sample sizes and more detailed subgroup analyses based on features of patients should be conducted to produce a more accurate conclusion.Prominent nursing organizations globally have called for a concerted effort to increase diversity in nursing education. While the number of men in the nursing workforce in the United States has increased slowly over the past five decades, the proportion of men in the profession remains low in comparison to the U.S. population. In response to research indicating a less-than-optimal experience for male nursing students, faculty and students embarked on a collaborative effort to improve the experience of this student population. This paper explores the reasons that men choose to enter nursing as well as the lived experience of men in a baccalaureate prelicensure nursing program in the United States. BAY-1816032 inhibitor The purpose of the study was to determine if progress had been made toward a shared goal of an improved experience for male students. Of the 19 male students who met the inclusion criteria, 13 students agreed to participate in the descriptive phenomenological study. Findings of this study indicate that previous interventions aimed at creating a more welcoming environment for male nursing students at the research site have been moderately successful. Clinically, it is evident that there is still more work left to be done, specifically regarding the maternal-newborn clinical experience.
Anxiety disorders are common and impairing throughout the life course. Propensity to anxiety disorders manifests as distress and avoidance of novel stimuli (called behavioural inhibition) as early as in infancy. Already in preschool children, anxiety disorders impact emotional development and school readiness. Anxiety disorders and behavioural inhibition are prospectively associated with increased risk of mood disorders, substance use, and suicide. Therefore, early targeted prevention and treatment need to be considered. Cognitive-behavioural interventions are effective for anxiety in older age group but their efficacy for preschool children remains to be established.

We searched PsycINFO, PubMed, and Embase until September 19th, 2019 using terms describing anxiety, behavioural inhibition, intervention, and young children. We included studies with young children participating in a cognitive-behavioural intervention for anxiety disorders, anxiety symptoms, or behavioural inhibition. We completed random-effects robust meta-analyses to (1) compare anxiety measures before and after intervention and to (2) compare intervention and control groups.

We identified 43 samples including 2656 participants with a mean age of 5.45 (SD=1.00) years. Anxiety decreased after cognitive-behavioural intervention (standardized mean difference [SMD]=-1.34, 95%CI -1.59 to -1.09, p<0.0001). Anxiety decreased more in children who received intervention than in children in control conditions (SMD=-0.81, 95%CI -1.00 to -0.63, p<0.0001). The difference remained significant after correcting for potential publication bias and outliers (SMD=-0.89, 95% CI -1.13 to -0.66, p<0.0001). The improvement was maintained over follow-up.

Cognitive-behavioural interventions are effective for prevention and treatment of anxiety in young children.
Cognitive-behavioural interventions are effective for prevention and treatment of anxiety in young children.
We have developed and validated a novel EEG-based signal processing approach to distinguish PD and control patients Linear-predictive-coding EEG Algorithm for PD (LEAPD). This method efficiently encodes EEG time series into features that can detect PD in a computationally fast manner amenable to real time applications.

We included a total of 41 PD patients and 41 demographically-matched controls from New Mexico and Iowa. Data for all participants from New Mexico (27 PD patients and 27 controls) were used to evaluate in-sample LEAPD performance, with extensive cross-validation. Participants from Iowa (14 PD patients and 14 controls) were used for out-of-sample tests. Our method utilized data from six EEG leads which were as little as 2min long.

For the in-sample dataset, LEAPD differentiated PD patients from controls with 85.3±0.1% diagnostic accuracy, 93.3±0.5% area under the receiver operating characteristics curve (AUC), 87.9±0.9% sensitivity, and 82.7±1.1% specificity, with multiple cross-validations. After head-to-head comparison with state-of-the-art methods using our dataset, LEAPD showed a 13% increase in accuracy and a 15.5% increase in AUC. When the trained classifier was applied to a distinct out-of-sample dataset, LEAPD showed reliable performance with 85.7% diagnostic accuracy, 85.2% AUC, 85.7% sensitivity, and 85.7% specificity. No statistically significant effect of levodopa-ON and levodopa-OFF sessions were found.

We describe LEAPD, an efficient algorithm that is suitable for real time application and captures spectral EEG features using few parameters and reliably differentiates PD patients from demographically-matched controls.
We describe LEAPD, an efficient algorithm that is suitable for real time application and captures spectral EEG features using few parameters and reliably differentiates PD patients from demographically-matched controls.
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