Automated Vehicles for People With Dementia: A "Tremendous Potential" That "Has Ways to go"-Reports of a Qualitative Study.

BACKGROUND AND OBJECTIVES: The prospect of automated vehicles (AVs) has generated excitement among the public and the research community about their potential to sustain the safe driving of people with dementia. However, no study to date has assessed the views of people with dementia on whether AVs may address their driving challenges. RESEARCH DESIGN AND METHODS: This mixed-methods study included two phases, completed by nine people with dementia. Phase I included questionnaires and individual semistructured interviews on attitudes toward using different types of AVs (i.e., partially or fully automated). Interpretative phenomenological analysis was used to assess participants' underlying reasons for and against AV use. The participants' identified reasons against AV use informed the focus group discussions in Phase II, where participants were asked to reflect on potential means of overcoming their hesitancies regarding AV use. RESULTS: The results showed that people with dementia might place higher levels of trust in fully automated compared to partially automated AVs. In addition, while people with dementia expressed multiple incentives to use AVs (e.g., regaining personal freedom), they also had hesitations about AV use. These hesitancies were based on their perceptions about AVs (e.g., cost), their own abilities (i.e., potential challenges operating an AV), and driving conditions (i.e., risk of driving in adverse weather conditions). DISCUSSION AND IMPLICATIONS: The findings of this study can help promote the research community's appreciation and understanding of the significant potential of AVs for people with dementia while elucidating the potential barriers of AV use by people with dementia.

Can Automated Vehicles Be Useful to Persons Living With Dementia? The Perspectives of Care Partners of People Living With Dementia.

BACKGROUND AND OBJECTIVES: Driving cessation is a complex challenge with significant emotional and health implications for people with dementia, which also affects their family care partners. Automated vehicles (AVs) could potentially be used to delay driving cessation and its adverse consequences for people with dementia and their care partners. Yet, no study to date has investigated whether care partners consider AVs to be potentially useful for people with dementia. RESEARCH DESIGN AND METHODS: This mixed-methods study assessed the views of 20 former or current family care partners of people with dementia on AV use by people with dementia. Specifically, questionnaires and semistructured interviews were used to examine care partners' acceptance of AV use by people with dementia and their views about the potential usefulness of AVs for people with dementia. RESULTS: The results demonstrated that care partners identified possible benefits of AV use by people with dementia such as their anticipated higher social participation. However, care partners also voiced major concerns around AV use by people with dementia and reported significantly lower levels of trust in and perceived safety of AVs if used by the person with dementia in their care compared to themselves. Care partners' concerns about AV use by people with dementia included concerns around the driving of people with dementia that AVs are not designed to address; concerns that are specific to AVs but are not relevant to the nonautomated driving of people with dementia; and concerns that arise from existing challenges around the nonautomated driving of people with dementia but may be exacerbated by AV use. DISCUSSION AND IMPLICATIONS: Findings from this study can inform future designs of AVs that are more accessible and useful for people with dementia.

Artificial Intelligence Education Programs for Health Care Professionals: Scoping Review.

BACKGROUND: As the adoption of artificial intelligence (AI) in health care increases, it will become increasingly crucial to involve health care professionals (HCPs) in developing, validating, and implementing AI-enabled technologies. However, because of a lack of AI literacy, most HCPs are not adequately prepared for this revolution. This is a significant barrier to adopting and implementing AI that will affect patients. In addition, the limited existing AI education programs face barriers to development and implementation at various levels of medical education. OBJECTIVE: With a view to informing future AI education programs for HCPs, this scoping review aims to provide an overview of the types of current or past AI education programs that pertains to the programs' curricular content, modes of delivery, critical implementation factors for education delivery, and outcomes used to assess the programs' effectiveness. METHODS: After the creation of a search strategy and keyword searches, a 2-stage screening process was conducted by 2 independent reviewers to determine study eligibility. When consensus was not reached, the conflict was resolved by consulting a third reviewer. This process consisted of a title and abstract scan and a full-text review. The articles were included if they discussed an actual training program or educational intervention, or a potential training program or educational intervention and the desired content to be covered, focused on AI, and were designed or intended for HCPs (at any stage of their career). RESULTS: Of the 10,094 unique citations scanned, 41 (0.41%) studies relevant to our eligibility criteria were identified. Among the 41 included studies, 10 (24%) described 13 unique programs and 31 (76%) discussed recommended curricular content. The curricular content of the unique programs ranged from AI use, AI interpretation, and cultivating skills to explain results derived from AI algorithms. The curricular topics were categorized into three main domains: cognitive, psychomotor, and affective. CONCLUSIONS: This review provides an overview of the current landscape of AI in medical education and highlights the skills and competencies required by HCPs to effectively use AI in enhancing the quality of care and optimizing patient outcomes. Future education efforts should focus on the development of regulatory strategies, a multidisciplinary approach to curriculum redesign, a competency-based curriculum, and patient-clinician interaction.

Older adults' acceptance of fully automated vehicles: Effects of exposure, driving style, age, and driving conditions.

Automated vehicles are anticipated to have benefits for older adults in maintaining their mobility and autonomy. These anticipated benefits can only be realized if this technology is accepted and thus used by older adults. However, it remains unclear how certain factors affect older adults' acceptance of automated vehicles. This study investigated the extent to which older adults' acceptance of fully automated vehicles are affected by exposure to automated vehicle technology (pre- vs. post-exposure), driving style (manual style relative to automated style), driving conditions (clear, rain, traffic), and age. Thirty-six older adults (M = 73.25, SD = 5.96) completed non-automated (manual) and fully automated driving scenarios under different driving conditions in a high-fidelity driving simulator. The fully automated driving scenarios were designed to be reliably driven by the system in a conservative driving style. Driving conditions included clear daytime, rain, and high-traffic. Pre- and post-exposure to the simulated fully automated driving experience, participants rated their comfort level with fully automated vehicles (FAVs). Additionally, after each driving condition, participants answered a validated questionnaire on their acceptance of the simulated fully automated experience for each respective driving condition. Age and driving style were found to have a significant effect on older adults' acceptance of FAVs, with older age and greater dissimilarity of an individual's manual driving style from the FAV's driving style being associated with lower acceptance. The results suggest that if reliability of fully automated vehicles is ultimately ensured and is demonstrated to the older adults, their acceptance of fully automated vehicles is generally high, particularly if the FAV is operated in a style similar to their own.

Advanced vehicle technologies and road safety: A scoping review of the evidence.

The proliferation of Advanced Vehicle Technologies (AVTs) has generated both excitement and concern among researchers, policymakers, and the general public. An increasing number of driver assistance systems are already available in today's automobiles; many of which are expected to become standard. Therefore, synthesizing the available evidence specific to the safety of AVTs is critical. The goal of this scoping review was to summarize this evidence with a focus on AVTs that require some driver oversight (i.e., Levels 0-3 as per the Society of Automotive Engineers (SAE) levels of automation taxonomy). A scoping review of research literature on AVTs was conducted for studies up to March 2018. Inclusion criteria consisted of: any study with empirical data of AVTs that included male and female drivers aged 16 years and older, healthy people (i.e., without impairments), passenger vehicles, driving simulators and/or large databases with road safety information that could be analyzed for the purpose of examining AVTs (SAE Levels 0-3), as well as measures of driving outcomes. A total of 324 peer-reviewed studies from 25 countries met the inclusion criteria for this review with over half published in the last 5 years. Data was extracted and summarized according to the following categories: measures used to evaluate the effect of AVTs on road safety (objective) and driver perceptions of the technology (subjective), testing environment, and study populations (i.e., driver age). The most commonly reported objective measures were longitudinal control (50 %), reaction time (40 %), and lateral position (23 %). The most common subjective measures were perceptions of trust (27 %), workload (20 %), and satisfaction (17 %). While most studies investigated singular AVTs (237 of 324 studies), the number of studies after 2013 that examined 2 or more AVTs concurrently increased. Studies involved drivers from different age groups (51 %) and were conducted in driving simulators (70 %). Overall, the evidence is generally in favour of AVTs having a positive effect on driving safety, although the nature and design of studies varied widely. Our examination of this evidence highlights the opportunities as well as the challenges involved with investigating AVTs. Ensuring such technologies are congruent with the needs of drivers, particularly younger and older driver age groups, who are known to have a higher crash risk, is critical. With automotive manufacturers keen to adopt the latest AVTs, this scoping review highlights how testing of this technology has been undertaken, with a focus on how new research can be conducted to improve road safety now and in the future.