Notes

Cognitive ailments within people with continual renal system ailment: specificities of scientific examination.
ecreased the spread of COVID-19 in South Korea and differentially affected cluster infections of SARS-CoV-2.
Chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) in adolescents is common and disabling. Teenagers in the United Kingdom are more likely to recover if they access specialist care, but most do not have access to a local specialist CFS/ME service. see more Delivering treatment remotely via the internet could improve access to treatment.

This study aims to assess (1) the feasibility of recruitment and retention into a trial of internet-delivered specialist treatment for adolescents with CFS/ME and (2) the acceptability of trial processes and 2 web-based treatments (to inform continuation to full trial).

This study is an internal pilot for the initial 12 months of a full randomized controlled trial (RCT), with integrated qualitative methods (analysis of recruitment consultations and participant and clinician interviews). Recruitment and treatment were delivered remotely from a specialist pediatric CFS/ME treatment service within a hospital in South West United Kingdom. Adolescents (aged 11-17 years) from 851; http//www.isrctn.com/ISRCTN18020851.

RR2-10.1186/s13063-018-2500-3.
RR2-10.1186/s13063-018-2500-3.
Populations are aging at an alarming rate in many countries around the world. There has been not only a decrease in the number of births and an increase in the percentage of older people, but also an increase in the number of people living alone. There is growing demand for specialist medical care and daily care with the number of people who can act as caregivers reducing. The use of assistive robots can, at least partially, solve these problems.

The purpose of this study was to examine the opinions of future health care professionals (medical and nursing students) regarding the use of assistive robots in the care of older people.

The study was conducted with a group of 178 students from Poznan University of Medical Sciences, Poznań, Poland (110 nursing students and 68 medical students), using the Users' Needs, Requirements, and Abilities Questionnaire.

The participants of this study believed that assistive robots should, first of all, remind older people to take medication regularly, ensure their safbots, which can have an impact on their acceptance by older adults. In the future, medical professionals could help their patients to choose the right robots (and necessary functions) that are best suited to their needs. However, this would require expanding the curriculum to include the issues of gerontechnology.
Our study revealed a generally positive attitude of future doctors and nurses toward assistive robots, which can have an impact on their acceptance by older adults. In the future, medical professionals could help their patients to choose the right robots (and necessary functions) that are best suited to their needs. However, this would require expanding the curriculum to include the issues of gerontechnology.
Internet-administered cognitive behavioral therapy (ICBT) has been demonstrated to be an effective intervention for adults with depression and/or anxiety and is recommended in national guidelines for provision within Swedish primary care. However, the number and type of organizations that have implemented ICBT within primary care in Sweden is currently unclear. Further, there is a lack of knowledge concerning barriers and facilitators to ICBT implementation.

The two primary objectives were to identify and describe primary care organizations providing ICBT in Sweden and compare decision makers' (ie, directors of primary care organizations) views on barriers and facilitators to implementation of ICBT among ICBT implementers (ie, organizations that offered ICBT) and nonimplementers (ie, organizations that did not offer ICBT).

An online survey based on a checklist for identifying barriers and facilitators to implementation was developed and made accessible to decision makers from all primary care organizatithe implementation of ICBT.
High alcohol consumption poses risks to individual health and society. Previous alcohol interventions have mainly focused on high-risk consumers or young adults in school-based settings. Since the majority of the adult population is in the workforce, the workplace can be considered a favorable arena for implementing interventions.

This protocol describes a project aimed at increasing knowledge of the effectiveness of combining the implementation of an organizational alcohol policy with skills training for managers as a workplace alcohol prevention program, by evaluating the intervention and exploring managers' perceptions of the intervention.

Organizations with at least 100 employees were invited to take part in the project. A total of 11 organizations (744 managers and 11,761 employees) were included in the project. Data are collected through self-administered online surveys at baseline, 12 months, and 24 months. The primary outcome is managers' inclination to initiate an early alcohol intervention (egaining among managers, compared to the usual practices in the workplace. The results from this study can contribute to increased knowledge about alcohol interventions and future prevention programs in the workplace.

ISRCTN17250048; http//www.isrctn.com/ISRCTN17250048.

DERR1-10.2196/17145.
DERR1-10.2196/17145.
Twitter presents a valuable and relevant social media platform to study the prevalence of information and sentiment on vaping that may be useful for public health surveillance. Machine learning classifiers that identify vaping-relevant tweets and characterize sentiments in them can underpin a Twitter-based vaping surveillance system. Compared with traditional machine learning classifiers that are reliant on annotations that are expensive to obtain, deep learning classifiers offer the advantage of requiring fewer annotated tweets by leveraging the large numbers of readily available unannotated tweets.

This study aims to derive and evaluate traditional and deep learning classifiers that can identify tweets relevant to vaping, tweets of a commercial nature, and tweets with provape sentiments.

We continuously collected tweets that matched vaping-related keywords over 2 months from August 2018 to October 2018. From this data set of tweets, a set of 4000 tweets was selected, and each tweet was manually annotated for relevance (vape relevant or not), commercial nature (commercial or not), and sentiment (provape or not).
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