Notes

Pacemaker employ for the reflex-mediated syncope: 40-year experience with a solitary paediatric establishment.
mall number of participants in this study, the findings demonstrate the potential of the app and support a fully powered trial to evaluate the empowering effect of the mobile health app. More data will be gathered with an improved version of the app in the second phase involving a larger study sample.
Despite the very small number of participants in this study, the findings demonstrate the potential of the app and support a fully powered trial to evaluate the empowering effect of the mobile health app. More data will be gathered with an improved version of the app in the second phase involving a larger study sample.
Smartphones and mobile applications have seen a surge in popularity in recent years, a pattern that has also been reflected in the health care system. Despite increased reliance among clinicians however, limited research has been conducted on the uptake and impact of smartphone usage in medical practice, especially outside the Western world.

This study aimed to identify the usage of smartphones and medical apps by doctors in the clinical setting in 2 culturally distinct countries King Hamad University Hospital (KHUH), Bahrain and Queen Mary Hospital (QMH), Hong Kong.

A cross-sectional, comparative study was conducted where doctors in both hospitals were asked to take part in a 15-item online survey. The questions were categorized into the following groups demographics of the study population, ownership and main use of smartphones, number and names of medical apps currently owned, rating usage of smartphones for medical purposes, time spent on a smartphone related to clinical use, clinical reliance on smsionals in attaining their information from accurate sources and also regulate a system to monitor the usage of mobile devices within hospitals to prevent a breach of patient privacy and confidentiality.
Aedes aegypti is a vector for the transmission of diseases such as dengue fever, chikungunya, Zika fever, and yellow fever. In 2016, over 1 million cases of these diseases were reported in Brazil, which is an alarming public health issue. One of the ways of controlling this disease is by inspecting and neutralizing the places where A. aegypti lays its eggs. The Ministry of Planning, Development, and Administration of Brazil maintains the inspection statistics.

We propose a multi-criteria analysis to create an index for A. Pyridostatin clinical trial aegypti inspections reported through the Ministry of Planning, Development, and Administration system of Brazil.

Based on the repository from urban cleaning services combined with data on inspections conducted by government agencies in several Brazilian cities and municipalities, we selected and combined metrics, which we further ranked using the analytic hierarchy process methodology. We also developed risk maps based on the analytic hierarchy process ranking of the A. aegypti breeding sites.

Based on our analysis and the available data, the priority for inspections should consider the number of sick people (weight 0.350), medical evaluations (weight 0.239), inspections (weight 0.201), mosquito breeding sites (weight 0.126), and days of absence from work (weight 0.096).

The proposed index could aid public health practitioners in preventing the appearance of new A. aegypti breeding sites. This information technology application can help solve such public health challenges.
The proposed index could aid public health practitioners in preventing the appearance of new A. aegypti breeding sites. This information technology application can help solve such public health challenges.
The study of doctor-patient-computer interactions is a key research area for examining doctor-patient relationships; however, studying these interactions is costly and obtrusive as researchers usually set up complex mechanisms or intrude on consultations to collect, then manually analyze the data.

We aimed to facilitate human-computer and human-human interaction research in clinics by providing a computational ethnography tool an unobtrusive automatic classifier of screen gaze and dialogue combinations in doctor-patient-computer interactions.

The classifier's input is video taken by doctors using their computers' internal camera and microphone. By estimating the key points of the doctor's face and the presence of voice activity, we estimate the type of interaction that is taking place. The classification output of each video segment is 1 of 4 interaction classes (1) screen gaze and dialogue, wherein the doctor is gazing at the computer screen while conversing with the patient; (2) dialogue, wherein the answering questions related to screen gaze and dialogue in doctor-patient-computer interactions.
In clinical diagnostic interviews, mental health professionals (MHPs) implement a care practice that involves asking open questions (eg, "What do you want from your life?" "What have you tried before to bring change in your life?") while listening empathetically to patients. link2 During these interviews, MHPs attempted to build a trusting human-centered relationship while collecting data necessary for professional medical and psychiatric care. link3 Often, because of the social stigma of mental health disorders, patient discomfort in discussing their presenting problem may add additional complexities and nuances to the language they use, that is, hidden signals among noisy content. Therefore, a focused, well-formed, and elaborative summary of clinical interviews is critical to MHPs in making informed decisions by enabling a more profound exploration of a patient's behavior, especially when it endangers life.

The aim of this study is to propose an unsupervised, knowledge-infused abstractive summarization (KiAS) approe outside of normally scheduled clinical appointments. This study shows promise in generating semantically relevant summaries that will help MHPs make informed decisions about patient status.
The use of wearable biosensor devices for monitoring and coaching in forensic psychiatric settings yields high expectations for improved self-regulation of emotions and behavior in clients and staff members. More so, if clients have mild intellectual disabilities (IQ 50-85), they might benefit from these biosensors as they are easy to use in everyday life, which ensures that clients can practice with the devices in multiple stress and arousal-inducing situations. However, research on (continuous) use and acceptance of biosensors in forensic psychiatry for clients with mild intellectual disabilities and their caretakers is scarce. Although wearable biosensors show promise for health care, recent research showed that the acceptance and continuous use of wearable devices in consumers is not as was anticipated, probably due to low expectations.

The main goal of this study was to investigate the associations between and determinants of the expectation of usability, the actual experienced usability, and the int cognitive capacity to increase usability, acceptance, and continuous use.
Accounting for how end users engage with technologies is imperative for designing an efficacious mobile behavioral intervention.

This mixed methods analysis examined the translational potential of user-centered design and basic behavioral science to inform the design of a new mobile intervention for obesity and binge eating.

A total of 22 adults (7/22, 32% non-Hispanic White; 8/22, 36% male) with self-reported obesity and recurrent binge eating (≥12 episodes in 3 months) who were interested in losing weight and reducing binge eating completed a prototyping design activity over 1 week. Leveraging evidence from behavioral economics on choice architecture, participants chose treatment strategies from 20 options (aligned with treatment targets composing a theoretical model of the relation between binge eating and weight) to demonstrate which strategies and treatment targets are relevant to end users. The process by which participants selected and implemented strategies and their change in outcomes were analscience yielded design insights to incorporate personalization through user choice with guidance, which may enhance engagement with and potential efficacy of digital health interventions.
Data-driven medical health information processing has become a new development trend in obstetrics. Electronic medical records (EMRs) are the basis of evidence-based medicine and an important information source for intelligent diagnosis. To obtain diagnostic results, doctors combine clinical experience and medical knowledge in their diagnosis process. External medical knowledge provides strong support for diagnosis. Therefore, it is worth studying how to make full use of EMRs and medical knowledge in intelligent diagnosis.

This study aims to improve the performance of intelligent diagnosis in EMRs by combining medical knowledge.

As an EMR usually contains multiple types of diagnostic results, the intelligent diagnosis can be treated as a multilabel classification task. We propose a novel neural network knowledge-aware hierarchical diagnosis model (KHDM) in which Chinese obstetric EMRs and external medical knowledge can be synchronously and effectively used for intelligent diagnostics. In KHDM, EMRs and atly improve the accuracy of diagnosis.
Identification of the essential components of the quality of the data collection process is the starting point for designing effective data quality management strategies for public health information systems. An inductive analysis of the global literature on the quality of the public health data collection process has led to the formation of a preliminary 4D component framework, that is, data collection management, data collection personnel, data collection system, and data collection environment. It is necessary to empirically validate the framework for its use in future research and practice.

This study aims to obtain empirical evidence to confirm the components of the framework and, if needed, to further develop this framework.

Expert elicitation was used to evaluate the preliminary framework in the context of the Chinese National HIV/AIDS Comprehensive Response Information Management System. The research processes included the development of an interview guide and data collection form, data collectier validation of psychometric properties and item reduction.
This expert elicitation study validated and improved the 4D framework. The framework can be useful in developing a questionnaire survey instrument for measuring the quality of the public health data collection process after validation of psychometric properties and item reduction.
Older adults are increasingly accessing information and communicating using patient-facing portals available through their providers' electronic health record (EHR). Most theories of technology acceptance and use suggest that patients' overall satisfaction with care should be independent of their chosen level of portal engagement. However, achieving expected benefits of portal use depends on demonstrated support from providers to meet these expectations. This is especially true among older adults, who may require more guidance. However, little is known about whether misalignment of expectations around technology-facilitated care is associated with lower perceptions of care quality.

The aims of this study were to analyze whether older adults' assessment of primary care quality differs across levels of patient portal engagement and whether perceptions of how well their provider uses the EHR to support care moderates this relationship.

We conducted a cross-sectional survey analysis of 158 older adults over the age of 65 (average age 71.
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