Notes

Whole-body moaning physical exercise along with coaching boost regional CBF within moderate cognitive problems along with enhanced intellectual function.
etween engagement with a physical activity digital health intervention and physical activity outcomes. No studies have targeted sedentary behavior outcomes. The findings were consistent across most constructs of engagement; however, the associations were weak.
The findings indicate a weak but consistent positive association between engagement with a physical activity digital health intervention and physical activity outcomes. No studies have targeted sedentary behavior outcomes. The findings were consistent across most constructs of engagement; however, the associations were weak.
The adoption rate of digital health in the health care sector is low in many countries. A facilitating factor for successful implementation and adoption of digital health is acceptance by current and future health care professionals.

This study was conducted to identify factors associated with willingness to use digital health tools in patient care among health care professionals and students.

This was a quantitative cross-sectional survey study conducted among health care professionals and students at a university hospital in Riyadh, Saudi Arabia. A nonprobability convenience sampling procedure was used to recruit participants. Data were collected using a self-completed e-questionnaire that was distributed by email. Chi-square tests, t tests, and logistic regression were used to analyze the data.

We found that 181 out of 218 health care professionals (83.0%; 75.6% [59/78] physicians; 87.1% [122/140] nurses) and 115 out of 154 students (74.7%; 80.0% [76/95] medical students and 66.1% [39/59] nursing se policy makers and hospital managers to implement relevant eHealth interventions within routine health care systems in Saudi Arabia. For successful implementation, digital health education programs should be implemented simultaneously, so that current and future health care professionals are able to develop required positive attitudes as well as practical skills and competencies.
Despite the high prevalence of child sexual offenses and the increasing amounts of available child sexual abuse material, there is a global shortage of preventive interventions focusing on individuals at risk of sexual offending. The web-based app Troubled Desire aims to address this shortage by offering self-assessments and self-management training modules in different languages to individuals with sexual interests in prepubescent and early pubescent children (ie, those with pedophilic and hebephiliac sexual interest, respectively).

The aim of this study was to describe the characteristics of the users of the Troubled Desire app.

The fully completed self-assessment data gathered within the first 30 months of this study from October 25, 2017 to April 25, 2020 were investigated. The main outcome measures were (1) sociodemographic information and (2) sexual interests and sexual behaviors of the users of Troubled Desire.

The self-assessment was completed by 4161 users. User accesses were mainly from Germ relevance of the Troubled Desire app in the prevention of child sexual offending.
Parkinson disease (PD) is a common movement disorder. Patients with PD have multiple gait impairments that result in an increased risk of falls and diminished quality of life. Therefore, gait measurement is important for the management of PD.

We previously developed a smartphone-based dual-task gait assessment that was validated in healthy adults. The aim of this study was to test the validity of this gait assessment in people with PD, and to examine the association between app-derived gait metrics and the clinical and functional characteristics of PD.

Fifty-two participants with clinically diagnosed PD completed assessments of walking, Movement Disorder Society Unified Parkinson Disease Rating Scale III (UPDRS III), Montreal Cognitive Assessment (MoCA), Hamilton Anxiety (HAM-A), and Hamilton Depression (HAM-D) rating scale tests. Participants followed multimedia instructions provided by the app to complete two 20-meter trials each of walking normally (single task) and walking while performing a serial , P=.009). Moreover, those with greater dual-task stride time variability (β=.48, P=.001) or dual-task cost of stride time variability (β=.44, P=.004) exhibited lower MoCA scores.

A smartphone-based gait assessment can be used to provide meaningful metrics of single- and dual-task gait that are associated with disease severity and functional outcomes in individuals with PD.
A smartphone-based gait assessment can be used to provide meaningful metrics of single- and dual-task gait that are associated with disease severity and functional outcomes in individuals with PD.
Patient Priorities Care (PPC) is a model of care that aligns health care recommendations with priorities of older adults who have multiple chronic conditions. Following identification of patient priorities, this information is documented in the patient's electronic health record (EHR).

Our goal is to develop and validate a natural language processing (NLP) model that reliably documents when clinicians identify patient priorities (ie, values, outcome goals, and care preferences) within the EHR as a measure of PPC adoption.

This is a retrospective analysis of unstructured National Veteran Health Administration EHR free-text notes using an NLP model. The data were sourced from 778 patient notes of 658 patients from encounters with 144 social workers in the primary care setting. Each patient's free-text clinical note was reviewed by 2 independent reviewers for the presence of PPC language such as priorities, values, and goals. We developed an NLP model that utilized statistical machine learning approaches. The performance of the NLP model in training and validation with 10-fold cross-validation is reported via accuracy, recall, and precision in comparison to the chart review.

Of 778 notes, 589 (75.7%) were identified as containing PPC language (kappa=0.82, P<.001). The NLP model in the training stage had an accuracy of 0.98 (95% CI 0.98-0.99), a recall of 0.98 (95% CI 0.98-0.99), and precision of 0.98 (95% CI 0.97-1.00). The NLP model in the validation stage had an accuracy of 0.92 (95% CI 0.90-0.94), recall of 0.84 (95% CI 0.79-0.89), and precision of 0.84 (95% CI 0.77-0.91). In contrast, an approach using simple search terms for PPC only had a precision of 0.757.

An automated NLP model can reliably measure with high precision, recall, and accuracy when clinicians document patient priorities as a key step in the adoption of PPC.
An automated NLP model can reliably measure with high precision, recall, and accuracy when clinicians document patient priorities as a key step in the adoption of PPC.
The Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) and Public Health England (PHE) are commencing their 54th season of collaboration at a time when SARS-CoV-2 infections are likely to be cocirculating with the usual winter infections.

The aim of this study is to conduct surveillance of influenza and other monitored respiratory conditions and to report on vaccine uptake and effectiveness using nationally representative surveillance data extracted from primary care computerized medical records systems. We also aim to have general practices collect virology and serology specimens and to participate in trials and other interventional research.

The RCGP RSC network comprises over 1700 general practices in England and Wales. We will extract pseudonymized data twice weekly and are migrating to a system of daily extracts. First, we will collect pseudonymized, routine, coded clinical data for the surveillance of monitored and unexpected conditions; data on vaccine expeloped the capacity and capability of the national primary care surveillance systems and our unique public health institute, the RCGP and University of Oxford collaboration.
The COVID-19 pandemic has been associated with a groundswell of general practices joining our network. It has also created a permissive environment in which we have developed the capacity and capability of the national primary care surveillance systems and our unique public health institute, the RCGP and University of Oxford collaboration.
During the COVID-19 pandemic, people have been encouraged to maintain social distance. selleck products Technology helps people schedule meetings as remote videoconferencing sessions rather than face-to-face interactions. Psychologists are in high demand because of an increase in stress as a result of COVID-19, and videoconferencing provides an opportunity for mental health clinicians to treat current and new referrals. However, shifting treatment from face-to-face to videoconferencing is not simple both psychologists and clients miss in-person information cues, including body language.

This review proposes a new theoretical framework to guide the design of future studies examining the impact of a computer as a mediator of psychologist-client relationships and the influence of videoconferencing on the relationship process.

We conducted a literature review including studies focused on communication and key concepts of the therapeutic relationship and therapeutic alliance.

Studies have reported that clients are generall consider the computer as having an active role in the client-psychologist relationship; thus, it is a third party to the communication that either assists or interferes with the interaction between psychologists and clients.
Public health organizations have begun to use social media to increase awareness of health harm and positively improve health behavior. Little is known about effective strategies to disseminate health education messages digitally and ultimately achieve optimal audience engagement.

This study aims to assess the difference in audience engagement with identical antismoking health messages on three social media sites (Twitter, Facebook, and Instagram) and with a referring link to a tobacco prevention website cited in these messages. We hypothesized that health messages might not receive the same user engagement on these media, although these messages were identical and distributed at the same time.

We measured the effect of health promotion messages on the risk of smoking among users of three social media sites (Twitter, Facebook, and Instagram) and disseminated 1275 health messages between April 19 and July 12, 2017 (85 days). The identical messages were distributed at the same time and as organic (unpaid)g and misinformation on social media.
Our study provides evidence-based insights to guide the design of health promotion efforts on social media. Future studies should examine the platform-specific impact of psycholinguistic message variations on user engagement, include newer sites such as Snapchat and TikTok, and study the correlation between web-based behavior and real-world health behavior change. The need is urgent in light of increased health-related marketing and misinformation on social media.
Diabetes mellitus (DM) is one of the world's greatest health threats with rising prevalence. Global digitalization leads to new digital approaches in diabetes management, such as telemedical interventions. Telemedicine, which is the use of information and communication technologies, may provide medical services over spatial distances to improve clinical patient outcomes by increasing access to diabetes care and medical information.

This study aims to examine whether telemedical interventions effectively improve diabetes control using studies that pooled patients with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM), and whether the benefits are greater in patients diagnosed with T2DM than in those diagnosed with T1DM. We analyzed the primary outcome glycated hemoglobin A
(HbA
) and the secondary outcomes fasting blood glucose (FBG), blood pressure (BP), body weight, BMI, quality of life (QoL), cost, and time saving.

Publications were systematically identified by searching Cochrane Library, MEDLINE via PubMed, Web of Science Core Collection, Embase, and CINAHL databases for studies published between January 2008 and April 2020, considering systematic reviews (SRs), meta-analyses (MAs), randomized controlled trials (RCTs), and clinical trials (CTs).
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