The use of artificial intelligence and virtual reality in doctor-patient risk communication: A scoping review

Bibliometric and visualization analysis of risk management in the doctor-patient relationship: A systematic quantitative literature review

OBJECTIVES

This paper analyzed the research on risk management in the doctor-patient relationship (DPR) based on a systematic quantitative literature review approach using bibliometric software. It aims to uncover potential information about current research and predict future research hotspots and trends.

METHODS

We conducted a comprehensive search for relevant publications in the Scopus database and the Web of Science Core Collection database from January 1, 2000 to December 31, 2023. We analyzed the data using CiteSpace 6.2.R2 and VOSviewer 1.6.19 software to examine the annual number of publications, countries/regions, journals, citations, authors, and keywords in the field.

RESULTS

A total of 553 articles and reviews that met the criteria were included in this study. There is an overall upward trend in the number of publications issued; in terms of countries/regions, the United States and the United Kingdom are the largest contributors; Patient Education and Counseling is the most productive journal (17); Physician communication and patient adherence to treatment: a meta-analysis is the most cited article (1637); the field has not yet to form a stable and obvious core team; the analysis of high-frequency keywords revealed four main research directions: the causes of DPR risks, coping strategies, measurement tools, and research related to people prone to doctor-patient risk characteristics; the causes of DPR risks, coping strategies, measurement tools, and research related to people prone to doctor-patient risk characteristics; the keyword burst analysis revealed several shifts in the research hotspots for risk management in the DPR, suggesting that chronic disease management, is a future research direction for the continued development of risk management in the DPR.

CONCLUSIONS

The visualization analysis of risk management literature in the DPR using CiteSpace and VOSviewer software provides insights into the current research status and highlights future research directions.

Immersive Innovations: Exploring the Diverse Applications of Virtual Reality (VR) in Healthcare

Virtual reality (VR) has experienced a remarkable evolution over recent decades, evolving from its initial applications in specific military domains to becoming a ubiquitous and easily accessible technology. This thorough review delves into the intricate domain of VR within healthcare, seeking to offer a comprehensive understanding of its historical evolution, theoretical foundations, and current adoption status. The examination explores the advantages of VR in enhancing the educational experience for medical students, with a particular focus on skill acquisition and retention. Within this exploration, the review dissects the applications of VR across diverse medical disciplines, highlighting its role in surgical training and anatomy/physiology education. While navigating the expansive landscape of VR, the review addresses challenges related to technology and pedagogy, providing insights into overcoming technical hurdles and seamlessly integrating VR into healthcare practices. Additionally, the review looks ahead to future directions and emerging trends, examining the potential impact of technological advancements and innovative applications in healthcare. This review illuminates the transformative potential of VR as a tool poised to revolutionize healthcare practices.

Virtual reality applications in pediatric surgery

Virtual reality modeling (VRM) is a 3-dimensional (3D) simulation. It is a powerful tool and has multiple uses and applications in pediatric surgery. Patient-specific 2-dimensional imaging can be used to generate a virtual reality model, which can improve anatomical perception and understanding, and can aid in preoperative planning for complex operations. VRM can also be used for realistic training and simulation. It has also proven effective in distraction for pediatric patients experiencing pain and/or anxiety. We detail the technical requirements and process required for VRM generation, the applications, and future directions.

What Is Medical Extended Reality? A Taxonomy Defining the Current Breadth and Depth of an Evolving Field

Medical extended reality (MXR) has emerged as a dynamic field at the intersection of health care and immersive technology, encompassing virtual, augmented, and mixed reality applications across a wide range of medical disciplines. Despite its rapid growth and recognition by regulatory bodies, the field lacks a standardized taxonomy to categorize its diverse research and applications. This American Medical Extended Reality Association guideline, authored by the editorial board of the Journal of Medical Extended Reality, introduces a comprehensive taxonomy for MXR, developed through a multidisciplinary and international collaboration of experts. The guideline seeks to standardize terminology, categorize existing work, and provide a structured framework for future research and development in MXR. An international and multidisciplinary panel of experts was convened, selected based on publication track record, contributions to MXR, and other objective measures. Through an iterative process, the panel identified primary and secondary topics in MXR. These topics were refined over several rounds of review, leading to the final taxonomy. The taxonomy comprises 13 primary topics that jointly expand into 180 secondary topics, demonstrating the field's breadth and depth. At the core of the taxonomy are five overarching domains: (1) technological integration and innovation; (2) design, development, and deployment; (3) clinical and therapeutic applications; (4) education, training, and communication; and (5) ethical, regulatory, and socioeconomic considerations. The developed taxonomy offers a framework for categorizing the diverse research and applications within MXR. It may serve as a foundational tool for researchers, clinicians, funders, academic publishers, and regulators, facilitating clearer communication and categorization in this rapidly evolving field. As MXR continues to grow, this taxonomy will be instrumental in guiding its development and ensuring a cohesive understanding of its multifaceted nature.

The Multidomain Metaverse Cancer Care Digital Platform: Development and Usability Study

BACKGROUND

As cancer treatment methods have diversified and the importance of self-management, which lowers the dependence rate on direct hospital visits, has increased, effective cancer care education and management for health professionals and patients have become necessary. The metaverse is in the spotlight as a means of digital health that allows users to engage in cancer care education and management beyond physical constraints. However, it is difficult to find a multipurpose medical metaverse that can not only be used in the field but also complements current cancer care.

OBJECTIVE

This study aimed to develop an integrated metaverse cancer care platform, Dr. Meta, and examine its usability.

METHODS

We conducted a multicenter, cross-sectional survey between November and December 2021. A descriptive analysis was performed to examine users' experiences with Dr. Meta. In addition, a supplementary open-ended question was used to ask users for their suggestions and improvements regarding the platform.

RESULTS

Responses from 70 Korean participants (male: n=19, 27% and female: n=51, 73%) were analyzed. More than half (n=37, 54%) of the participants were satisfied with Dr. Meta; they responded that it was an interesting and immersive platform (n=50, 72%). Less than half perceived no discomfort when using Dr. Meta (n=34, 49%) and no difficulty in wearing and operating the device (n=30, 43%). Furthermore, more than half (n=50, 72%) of the participants reported that Dr. Meta would help provide non-face-to-face and noncontact services. More than half also wanted to continue using this platform in the future (n=41, 59%) and recommended it to others (n=42, 60%).

CONCLUSIONS

We developed a multidomain metaverse cancer care platform that can support both health professionals and patients in non-face-to-face cancer care. The platform was uniquely disseminated and implemented in multiple regional hospitals and showed the potential to perform successful cancer care.

The Influence of Individualized Three-Dimensional Holographic Models on Patients' Knowledge Qualified for Intervention in the Treatment of Peripheral Arterial Disease (PAD)

We sought to determine the role of the patient-specific, three-dimensional (3D) holographic vascular model in patient medical knowledge and its influence on obtaining a more conscious informed consent process for percutaneous balloon angioplasty (PTA). Patients with peripheral arterial disease who had been scheduled for PTA were enrolled in the study. Information regarding the primary disease, planned procedure, and informed consent was recorded in typical fashion. Subsequently, the disease and procedure details were presented to the patient, showing the patients their individual model. A patient and medical supervisor equipped with mixed reality headsets could both simultaneously manipulate the hologram using gestures. The holographic 3D model had been created on a scale of 1:1 based on computed tomography scans. The patient's knowledge was tested by the completion of a questionnaire before and after the interaction in a mixed reality environment. Seventy-nine patients manipulated arterial holograms in mixed reality head-mounted devices. Before the 3D holographic artery model interaction, the mean ± standard deviation score of the knowledge test was 2.95 ± 1.21 points. After the presentation, the score had increased to 4.39 ± 0.82, with a statistically significant difference (p = 0.0000) between the two scores. Using a Likert scale from 1 to 5, the patients had scored the use of the 3D holographic model at 3.90 points regarding its usefulness in comprehending their medical condition; at 4.04 points regarding the evaluation of the holograms as helpful in understanding the course of surgery; and rated the model at 1.99 points in reducing procedure-related stress. Using a nominal scale (know or don't know), the patients had self-assessed their knowledge of the procedure before and after the 3D model presentation, with a score of 6.29 ± 2.01 and 8.39 ± 1.54, respectively. The study group tolerated the use of head-mounted devices. Only one patient had nausea and dizziness, while four patients experienced transient eye pain. The 3D holographic arterial model aided in the understanding of patients' knowledge regarding the disease and procedure, making the informed consent process more conscious. The holograms improved the patient's self-consciousness. Mixed reality headset-related complications were rare and within acceptable rates.

Injured Avatars: The Impact of Embodied Anatomies and Virtual Injuries on Well-Being and Performance

Human cognition relies on embodiment as a fundamental mechanism. Virtual avatars allow users to experience the adaptation, control, and perceptual illusion of alternative bodies. Although virtual bodies have medical applications in motor rehabilitation and therapeutic interventions, their potential for learning anatomy and medical communication remains underexplored. For learners and patients, anatomy, procedures, and medical imaging can be abstract and difficult to grasp. Experiencing anatomies, injuries, and treatments virtually through one's own body could be a valuable tool for fostering understanding. This work investigates the impact of avatars displaying anatomy and injuries suitable for such medical simulations. We ran a user study utilizing a skeleton avatar and virtual injuries, comparing to a healthy human avatar as a baseline. We evaluate the influence on embodiment, well-being, and presence with self-report questionnaires, as well as motor performance via an arm movement task. Our results show that while both anatomical representation and injuries increase feelings of eeriness, there are no negative effects on embodiment, well-being, presence, or motor performance. These findings suggest that virtual representations of anatomy and injuries are suitable for medical visualizations targeting learning or communication without significantly affecting users' mental state or physical control within the simulation.

Artificial Intelligence Supporting the Training of Communication Skills in the Education of Health Care Professions: Scoping Review

BACKGROUND

Communication is a crucial element of every health care profession, rendering communication skills training in all health care professions as being of great importance. Technological advances such as artificial intelligence (AI) and particularly machine learning (ML) may support this cause: it may provide students with an opportunity for easily accessible and readily available communication training.

OBJECTIVE

This scoping review aimed to summarize the status quo regarding the use of AI or ML in the acquisition of communication skills in academic health care professions.

METHODS

We conducted a comprehensive literature search across the PubMed, Scopus, Cochrane Library, Web of Science Core Collection, and CINAHL databases to identify articles that covered the use of AI or ML in communication skills training of undergraduate students pursuing health care profession education. Using an inductive approach, the included studies were organized into distinct categories. The specific characteristics of the studies, methods and techniques used by AI or ML applications, and main outcomes of the studies were evaluated. Furthermore, supporting and hindering factors in the use of AI and ML for communication skills training of health care professionals were outlined.

RESULTS

The titles and abstracts of 385 studies were identified, of which 29 (7.5%) underwent full-text review. Of the 29 studies, based on the inclusion and exclusion criteria, 12 (3.1%) were included. The studies were organized into 3 distinct categories: studies using AI and ML for text analysis and information extraction, studies using AI and ML and virtual reality, and studies using AI and ML and the simulation of virtual patients, each within the academic training of the communication skills of health care professionals. Within these thematic domains, AI was also used for the provision of feedback. The motivation of the involved agents played a major role in the implementation process. Reported barriers to the use of AI and ML in communication skills training revolved around the lack of authenticity and limited natural flow of language exhibited by the AI- and ML-based virtual patient systems. Furthermore, the use of educational AI- and ML-based systems in communication skills training for health care professionals is currently limited to only a few cases, topics, and clinical domains.

CONCLUSIONS

The use of AI and ML in communication skills training for health care professionals is clearly a growing and promising field with a potential to render training more cost-effective and less time-consuming. Furthermore, it may serve learners as an individualized and readily available exercise method. However, in most cases, the outlined applications and technical solutions are limited in terms of access, possible scenarios, the natural flow of a conversation, and authenticity. These issues still stand in the way of any widespread implementation ambitions.

Methodological innovations to strengthen evidence-based serious illness communication

BACKGROUND/OBJECTIVE

A growing population of those affected by serious illness, prognostic uncertainty, patient diversity, and healthcare digitalization pose challenges for the future of serious illness communication. Yet, there is paucity of evidence to support serious illness communication behaviors among clinicians. Herein, we propose three methodological innovations to advance the basic science of serious illness communication.

RESULTS

First, advanced computation techniques - e.g. machine-learning techniques and natural language processing - offer the possibility to measure the characteristics and complex patterns of audible serious illness communication in large datasets. Second, immersive technologies - e.g., virtual- and augmented reality - allow for experimentally manipulating and testing the effects of specific communication strategies, and interactional and environmental aspects of serious illness communication. Third, digital-health technologies - e.g., shared notes and videoconferences - can be used to unobtrusively observe and manipulate communication, and compare in-person to digitally-mediated communication elements and effects. Immersive and digital health technologies allow integration of physiological measurement (e.g. synchrony or gaze) that may advance our understanding of patient experience.

CONCLUSION/PRACTICE IMPLICATIONS

New technologies and measurement approaches, while imperfect, will help advance our understanding of the epidemiology and quality of serious illness communication in an evolving healthcare environment.

Artificial Intelligence in Surgical Learning

(1) Background: Artificial Intelligence (AI) is transforming healthcare on all levels. While AI shows immense potential, the clinical implementation is lagging. We present a concise review of AI in surgical learning; (2) Methods: A non-systematic review of AI in surgical learning of the literature in English is provided; (3) Results: AI shows utility for all components of surgical competence within surgical learning. AI presents with great potential within robotic surgery specifically (4) Conclusions: Technology will evolve in ways currently unimaginable, presenting us with novel applications of AI and derivatives thereof. Surgeons must be open to new modes of learning to be able to implement all evidence-based applications of AI in the future. Systematic analyses of AI in surgical learning are needed.

Virtual reality for healthcare: A scoping review of commercially available applications for head-mounted displays

Objective

This scoping review aimed to describe the scope of commercially available virtual reality (VR) healthcare applications for mainstream head-mounted displays (HMD)s.

Methods

A search was conducted during late April and early May 2022 over five major VR app stores using "health," "healthcare," "medicine," and "medical" as keywords. Apps were screened based on their title and description sections. Metadata collected included: title, description, release date, price (free or paid), multilingual support, VR app store availability, and HMD support.

Results

The search yielded 1995 apps, out of which 60 met the inclusion criteria. The analysis showed that the number of healthcare VR apps has been steadily increasing since 2016, but no developer has released more than two apps so far. Most of the reviewed apps can run on HTC Vive, Oculus Quest, and Valve Index. Thirty-four (56.7%) apps had a free version, and 12 (20%) apps were multilingual, i.e., supported languages other than English. The reviewed apps fell into eight major themes: life science education (3D anatomy, physiology and pathology, biochemistry, and genetics); rehabilitation (physical, mental, and phobia therapy); public health training (safety, life-saving skills, and management); medical training (surgical and patient simulators); role-playing as a patient; 3D medical imagery viewing; children's health; and online health communities.

Conclusions

Although commercial healthcare VR is still in its early phases, end-users can already access a broad range of healthcare VR apps on mainstream HMDs. Further research is needed to assess the usefulness and usability of existing apps.

Artificial Intelligence in Public Health: Current Trends and Future Possibilities

Artificial intelligence (AI) is a discipline that studies whether and how intelligent computer systems that can simulate the capacity and behaviour of human thought can be created [...]