EDAI Framework for Integrating Equity, Diversity, and Inclusion Throughout the Lifecycle of AI to Improve Health and Oral Health Care: Qualitative Study.

Background: Recent studies have identified significant gaps in equity, diversity, and inclusion (EDI) considerations within the lifecycle of artificial intelligence (AI), spanning from data collection and problem definition to implementation stages. Despite the recognized need for integrating EDI principles, there is currently no existing guideline or framework to support this integration in the AI lifecycle.

Objective: This study aimed to address this gap by identifying EDI principles and indicators to be integrated into the AI lifecycle.

Outcomes of guidelines from health technology assessment organizations in community-based primary care: a systematic mixed studies review.

Background: Health technology assessment (HTA) organizations generate guidelines to inform healthcare practices toward improved health outcomes. This review sought to identify and classify outcomes of guidelines from HTA organizations within published research.

Methodology: We performed a systematic mixed studies review of empirical studies that (a) referred to a published guideline from an HTA organization and (b) reported an outcome resulting from a guideline.

Perspectives on virtual interviews and emerging technologies integration in family medicine residency programs: a cross-sectional survey study.

Background: During the coronavirus disease of 2019 (COVID-19) pandemic, in-person interviews for the recruitment of family medicine residents shifted to online (virtual) interviews. The purpose of this study was twofold: (1) to gather the ideas about virtual interviews of family medicine applicants (interviewees), and faculty and staff who interviewed these applicants (interviewers), and (2) to describe interviewers' and interviewees' opinions of use of emerging technologies such as artificial intelligence (AI) and virtual reality (VR) in the recruitment process as well as during clinical practice.

Methods: This was a cross-sectional survey study.

Existing Digital Health Technology Index Summary Report for Older Adults Living with Neurocognitive Disorders (Mild and Major) and Their Informal Caregivers: An Environmental Scan.

Digital health has added numerous promising solutions to enhance the health and wellness of people with neurocognitive disorders (NCDs) and their informal caregivers. (1) Background: It is important to obtain a comprehensive view of currently available technologies, their outcomes, and conditions of success to inform recommendations regarding digital health solutions for people with NCDs and their caregivers. This environmental scan was performed to identify the features of existing digital health solutions relevant to the targeted population.

Curriculum Frameworks and Educational Programs in AI for Medical Students, Residents, and Practicing Physicians: Scoping Review.

Background: The successful integration of artificial intelligence (AI) into clinical practice is contingent upon physicians' comprehension of AI principles and its applications. Therefore, it is essential for medical education curricula to incorporate AI topics and concepts, providing future physicians with the foundational knowledge and skills needed. However, there is a knowledge gap in the current understanding and availability of structured AI curriculum frameworks tailored for medical education, which serve as vital guides for instructing and facilitating the learning process.

Primary care physicians' perceptions of artificial intelligence systems in the care of adolescents' mental health.

Background: Given that mental health problems in adolescence may have lifelong impacts, the role of primary care physicians (PCPs) in identifying and managing these issues is important. Artificial Intelligence (AI) may offer solutions to the current challenges involved in mental health care. We therefore explored PCPs' challenges in addressing adolescents' mental health, along with their attitudes towards using AI to assist them in their tasks.

Performance of generative pre-trained transformers (GPTs) in Certification Examination of the College of Family Physicians of Canada.

Introduction: The application of large language models such as generative pre-trained transformers (GPTs) has been promising in medical education, and its performance has been tested for different medical exams. This study aims to assess the performance of GPTs in responding to a set of sample questions of short-answer management problems (SAMPs) from the certification exam of the College of Family Physicians of Canada (CFPC).

Method: Between August 8th and 25th, 2023, we used GPT-3.

Socially Assistive Robots for patients with Alzheimer's Disease: A scoping review.

Background: The most common form of dementia, Alzheimer's Disease (AD), is challenging for both those affected as well as for their care providers, and caregivers. Socially assistive robots (SARs) offer promising supportive care to assist in the complex management associated with AD.

Objectives: To conduct a scoping review of published articles that proposed, discussed, developed or tested SAR for interacting with AD patients.

Strategies to Mitigate Age-Related Bias in Machine Learning: Scoping Review.

Background: Research suggests that digital ageism, that is, age-related bias, is present in the development and deployment of machine learning (ML) models. Despite the recognition of the importance of this problem, there is a lack of research that specifically examines the strategies used to mitigate age-related bias in ML models and the effectiveness of these strategies.

Objective: To address this gap, we conducted a scoping review of mitigation strategies to reduce age-related bias in ML.

Implications of conscious AI in primary healthcare.

The conversation about consciousness of artificial intelligence (AI) is an ongoing topic since 1950s. Despite the numerous applications of AI identified in healthcare and primary healthcare, little is known about how a conscious AI would reshape its use in this domain. While there is a wide range of ideas as to whether AI can or cannot possess consciousness, a prevailing theme in all arguments is uncertainty.

Use of Artificial Intelligence in the Identification and Management of Frailty: A Scoping Review Protocol.

Introduction: Rapid population ageing and associated health issues such as frailty are a growing public health concern. While early identification and management of frailty may limit adverse health outcomes, the complex presentations of frailty pose challenges for clinicians. Artificial intelligence (AI) has emerged as a potential solution to support the early identification and management of frailty.

Artificial Intelligence for Detection of Dementia Using Motion Data: A Scoping Review.

Background: Dementia is a neurodegenerative disease resulting in the loss of cognitive and psychological functions. Artificial intelligence (AI) may help in detection and screening of dementia; however, little is known in this area.

Objectives: The objective of this study was to identify and evaluate AI interventions for detection of dementia using motion data.

Integrating equity, diversity and inclusion throughout the lifecycle of AI within healthcare: a scoping review protocol.

Introduction: Artificial intelligence (AI) has the potential to improve efficiency and quality of care in healthcare settings. The lack of consideration for equity, diversity and inclusion (EDI) in the lifecycle of AI within healthcare settings may intensify social and health inequities, potentially causing harm to under-represented populations. This article describes the protocol for a scoping review of the literature relating to integration of EDI in the AI interventions within healthcare setting.

Application of Artificial intelligence in COVID-19-related geriatric care: A scoping review.

Background: Older adults have been disproportionately affected by the COVID-19 pandemic. This scoping review aimed to summarize the current evidence of artificial intelligence (AI) use in the screening/monitoring, diagnosis, and/or treatment of COVID-19 among older adults.

Method: The review followed the Joanna Briggs Institute and Arksey and O'Malley frameworks.

Curriculum frameworks and educational programs in artificial intelligence for medical students, residents, and practicing physicians: a scoping review protocol.

Objective: The aim of this scoping review is to synthesize knowledge from the literature on curriculum frameworks and current educational programs that focus on the teaching and learning of artificial intelligence (AI) for medical students, residents, and practicing physicians.

Introduction: To advance the implementation of AI in clinical practice, physicians need to have a better understanding of AI and how to use it within clinical practice. Consequently, medical education must introduce AI topics and concepts into the curriculum.

Existing eHealth Solutions for Older Adults Living With Neurocognitive Disorders (Mild and Major) or Dementia and Their Informal Caregivers: Protocol for an Environmental Scan.

Background: Dementia is one of the main public health priorities for current and future societies worldwide. Over the past years, eHealth solutions have added numerous promising solutions to enhance the health and wellness of people living with dementia-related cognitive problems and their primary caregivers. Previous studies have shown that an environmental scan identifies the knowledge-to-action gap meaningfully.

Using incorpoRATE to examine clinician willingness to engage in shared decision making: A study of Family Medicine residents.

Objectives: We evaluated the willingness of Family Medicine residents to engage in SDM, before and after an educational intervention.

Methods: We delivered a lecture and a workshop for residents on implementing SDM in preventive health care. Before the lecture (T1), participants completed a measure of their willingness to engage in SDM.

Application of Artificial Intelligence in Shared Decision Making: Scoping Review.

Background: Artificial intelligence (AI) has shown promising results in various fields of medicine. It has the potential to facilitate shared decision making (SDM). However, there is no comprehensive mapping of how AI may be used for SDM.

User Experience of a Computer-Based Decision Aid for Prenatal Trisomy Screening: Mixed Methods Explanatory Study.

Background: Mobile health tools can support shared decision-making. We developed a computer-based decision aid (DA) to help pregnant women and their partners make informed, value-congruent decisions regarding prenatal screening for trisomy.

Objective: This study aims to assess the usability and usefulness of computer-based DA among pregnant women, clinicians, and policy makers.

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

Objectives: While the development of artificial intelligence (AI) and virtual reality (VR) technologies in medicine has been significant, their application to doctor-patient communication is limited. As communicating risk is a challenging, yet essential, component of shared decision-making (SDM) in surgery, this review aims to explore the current use of AI and VR in doctor-patient surgical risk communication.

Methods: The search strategy was prepared by a medical librarian and run in 7 electronic databases.

Ageism and Artificial Intelligence: Protocol for a Scoping Review.

Background: Artificial intelligence (AI) has emerged as a major driver of technological development in the 21st century, yet little attention has been paid to algorithmic biases toward older adults.

Objective: This paper documents the search strategy and process for a scoping review exploring how age-related bias is encoded or amplified in AI systems as well as the corresponding legal and ethical implications.

Methods: The scoping review follows a 6-stage methodology framework developed by Arksey and O'Malley.

Moving shared decision-making forward in Iran.

Although there have been breakthroughs in patients' rights and informed consent legislation in Iran during the last few years, there is still no policy regarding shared decision-making (SDM). Besides, SDM training and clinical implementation initiatives remain scarce within the country. In this article, we aim to provide an update on the current state of SDM in Iran and discuss future directions.

Exploring the roles of artificial intelligence in surgical education: A scoping review.

Background: Technology-enhanced teaching and learning, including Artificial Intelligence (AI) applications, has started to evolve in surgical education. Hence, the purpose of this scoping review is to explore the current and future roles of AI in surgical education.

Methods: Nine bibliographic databases were searched from January 2010 to January 2021.

Application of Artificial Intelligence in Community-Based Primary Health Care: Systematic Scoping Review and Critical Appraisal.

Background: Research on the integration of artificial intelligence (AI) into community-based primary health care (CBPHC) has highlighted several advantages and disadvantages in practice regarding, for example, facilitating diagnosis and disease management, as well as doubts concerning the unintended harmful effects of this integration. However, there is a lack of evidence about a comprehensive knowledge synthesis that could shed light on AI systems tested or implemented in CBPHC.

Objective: We intended to identify and evaluate published studies that have tested or implemented AI in CBPHC settings.