Evidence-based medicine has been regarded as a prerequisite for ensuring health care quality. The increase in health care professionals' adoption of web-based medical information and the lack of awareness of alternative access to evidence-based online resources suggest the need for an investigation of their information-searching behaviors of using evidence-based online medical databases.

Health authorities recommend educating diabetic patients and their families and initiating measures aimed at improving self-management, promoting a positive behavior change, and reducing the risk of complications. Social media could provide valid channel to intervene in and deliver diabetes education. However, it is not well known whether the use of these channels in such interventions can help improve the patients' outcomes.

GPS alarms aim to support users in independent activities. Previous systematic reviews have reported a lack of clear evidence of the effectiveness of GPS alarms for the health and welfare of users and their families and for social care provision. As GPS devices are currently being implemented in social care, it is important to investigate whether the evidence of their clinical effectiveness remains insufficient. Standardized evidence frameworks have been developed to ensure that new technologies are clinically effective and offer economic value. The frameworks for analyzing existing evidence of the clinical effectiveness of GPS devices can be used to identify the risks associated with their implementation and demonstrate key aspects of successful piloting or implementation.

User-friendly information at the point of care should be well structured, rapidly accessible, and comprehensive. Also, this information should be trustworthy, as it will be used by health care practitioners to practice evidence-based medicine. Therefore, a standard, validated tool to evaluate the trustworthiness of such point-of-care information resources is needed.

Internet-based intervention platforms may improve access to mental health care for women with perinatal depression (PND). Though the majority of platforms in the market lack an evidence base, a small number of them are supported by research evidence.

The GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach is a system for transparent evaluation of the certainty of evidence used in clinical practice guidelines and systematic reviews. GRADE is a key part of evidence-based medicine (EBM) training of health care professionals.

User-friendly information at the point of care for health care professionals should be well structured, rapidly accessible, comprehensive, and trustworthy. The reliability of information and the associated methodological process must be clear. There is no standard tool to evaluate the trustworthiness of such point-of-care (POC) information.

Existing research postulates a variety of components that show an impact on utilization of technology-mediated mental health information systems (MHIS) and treatment outcome. Although researchers assessed the effect of isolated design elements on the results of Web-based interventions and the associations between symptom reduction and use of components across computer and mobile phone platforms, there remains uncertainty with regard to which components of technology-mediated interventions for mental health exert the greatest therapeutic gain. Until now, no studies have presented results on the therapeutic benefit associated with specific service components of technology-mediated MHIS for depression.

Artificial intelligence (AI)-based technologies develop rapidly and have myriad applications in medicine and health care. However, there is a lack of comprehensive reporting on the productivity, workflow, topics, and research landscape of AI in this field.

The application of artificial intelligence (AI) in the delivery of health care is a promising area, and guidelines, consensus statements, and standards on AI regarding various topics have been developed.

Syncope evaluation and management is associated with testing overuse and unnecessary hospitalizations. The 2017 American College of Cardiology/American Heart Association (ACC/AHA) Syncope Guideline aims to standardize clinical practice and reduce unnecessary services. The use of clinical decision support (CDS) tools offers the potential to successfully implement evidence-based clinical guidelines. However, CDS tools that provide an evidence-based differential diagnosis (DDx) of syncope at the point of care are currently lacking.

Since the mid-2010s, use of conversational artificial intelligence (AI; chatbots) in health care has expanded significantly, especially in the context of increased burdens on health systems and restrictions on in-person consultations with health care providers during the COVID-19 pandemic. One emerging use for conversational AI is to capture evolving questions and communicate information about vaccines and vaccination.

Health professions education has undergone major changes with the advent and adoption of digital technologies worldwide.

Primary care is known to be one of the most complex health care settings because of the high number of theoretically possible diagnoses. Therefore, the process of clinical decision-making in primary care includes complex analytical and nonanalytical factors such as gut feelings and dealing with uncertainties. Artificial intelligence is also mandated to offer support in finding valid diagnoses. Nevertheless, to translate some aspects of what occurs during a consultation into a machine-based diagnostic algorithm, the probabilities for the underlying diagnoses (odds ratios) need to be determined.

Social media platforms are increasingly used by registered dietitians (RDs) to improve knowledge translation and exchange in nutrition. However, a thorough understanding of social media in dietetic practice is lacking.

Chronic kidney disease (CKD) poses a major challenge to public health. In CKD patients, adequate disease self-management has been shown to improve both proximal and distal outcomes. Currently, electronic health (eHealth) interventions are increasingly used to optimize patients' self-management skills.

Telemedicine is defined by three characteristics: (1) using information and communication technologies, (2) covering a geographical distance, and (3) involving professionals who deliver care directly to a patient or a group of patients. It is said to improve chronic care management and self-management in patients with chronic diseases. However, currently available guidelines for the care of patients with diabetes, hypertension, or dyslipidemia do not include evidence-based guidance on which components of telemedicine are most effective for which patient populations.

Accumulating evidence suggests the COVID-19 pandemic has negative effects on public mental health. Digital interventions that have been developed and evaluated in recent years may be used to mitigate the negative consequences of the pandemic. However, evidence-based recommendations on the use of existing telemedicine and internet-based (eHealth) and app-based mobile health (mHealth) interventions are lacking.

Patients with orthopedic conditions frequently use the internet to find health information. Patient education that is distributed online may form an easily accessible, time- and cost-effective alternative to education delivered through traditional channels such as one-on-one consultations or booklets. However, no systematic evidence for the comparative effectiveness of Web-based educational interventions exists.

Screening is an effective primary prevention strategy in health care, as it enables the early detection of diseases. However, the uptake of such screening remains low. Different delivery methods for screening have been developed and found to be effective in increasing the uptake of screening, including the use of web-based apps. Studies have shown that web-based apps for screening are effective in increasing the uptake of health screening among the general population. However, not much is known about the effective implementation of such web-based apps in the real-world setting. Implementation strategies are theory-based methods or techniques used to enhance the adoption, implementation, and sustainability of evidence-based interventions. Implementation strategies are important, as they allow us to understand how to implement an evidence-based intervention. Therefore, a scoping review to identify the various implementation strategies for web-based apps for screening is warranted.