A considerable number of adults with dementia live in residential aged care facilities, where loneliness and boredom are common. Computer-based and electronic technologies have advanced significantly and there is potential for such technologies to improve engagement of residents with dementia. However, the nature and extent of the evidence supporting the use of these technologies is unclear.

The aim of this study was to investigate the use of computer-based and electronic technologies for enhancing meaningful engagement of adults with dementia living in residential aged care.

A scoping review was conducted. Nine databases were searched from 2008-2018. Included studies were summarized, compared and synthesized according to technology type.

Twenty studies were included. Most studies were conducted in Australia (n = 7) and Europe (n = 8). Study designs were quantitative (n = 12), mixed methods (n = 5), descriptive (n = 2) or qualitative (n = 1). Studies aimed to investigate interaction, engagement, behaviors or quality of life (n = 14), to examine the feasibility of technologies (n = 3), or had both aims (n = 3). Technology type fell into two categories: robotics (n = 14) and multi-media computer programs (n = 6). Across both technology types, there were conflicting results in relation to positive impact on meaningful engagement. Studies only investigated the doing, belonging and connecting aspects of meaningful engagement. Additionally, there was a lack of consistency across studies in how activity, interaction and engagement were measured.

The role and potential of new technologies to enhance meaningful engagement for those with dementia should focus on creating human-to-human interactions while taking individual preference and person-centered principles into account.

Assistive technology is advocated as a key solution to the need for support among people living with dementia. There is growing awareness of the benefits of user involvement in the design and test of these technologies and the need to identifying applicable and effective methods for implementation. The aim of this review was to explore and synthesize research addressing assistive technology designed to be used by people with dementia for self-management. Further research aims were to explore if and how user involvement, dissemination, and adoption of assistive technology were addressed.

Electronic databases were searched using specified search terms. Key publications and grey literature sources were hand-searched. Materials published until year end 2018 were included. The results were summarized according to the research aims.

Eleven papers derived from eight studies were included. The studies presented data from prototype design and testing, and the review showed great variation in study scope, design, and methodology. User involvement varied from extensive involvement to no user involvement. Methods for adoption also varied widely and only targeted prototype testing. None of the studies addressed dissemination.

The results of this review underline the need for well-designed high-quality research into all the aspects that are essential to deliver applicable, effective, and sustainable assistive technology to support self-management of people with dementia. There is a need for evidence-based methods to promote and qualify user involvement, dissemination, and adoption. The results also point to the need for standardized outcome measures and standards for conducting and reporting research to improve its quality and impact.

Brain health diplomacy aims to influence the global policy environment for brain health (i.e. dementia, depression, and other mind/brain disorders) and bridges the disciplines of global brain health, international affairs, management, law, and economics. Determinants of brain health include educational attainment, diet, access to health care, physical activity, social support, and environmental exposures, as well as chronic brain disorders and treatment. Global challenges associated with these determinants include large-scale conflicts and consequent mass migration, chemical contaminants, air quality, socioeconomic status, climate change, and global population aging. Given the rapidly advancing technological innovations impacting brain health, it is paramount to optimize the benefits and mitigate the drawbacks of such technologies.

We propose a working model of Brain health INnovation Diplomacy (BIND).

We prepared a selective review using literature searches of studies pertaining to brain health technological innovation and diplomacy.

BIND aims to improve global brain health outcomes by leveraging technological innovation, entrepreneurship, and innovation diplomacy. It acknowledges the key role that technology, entrepreneurship, and digitization play and will increasingly play in the future of brain health for individuals and societies alike. It strengthens the positive role of novel solutions, recognizes and works to manage both real and potential risks of digital platforms. It is recognition of the political, ethical, cultural, and economic influences that brain health technological innovation and entrepreneurship can have.

By creating a framework for BIND, we can use this to ensure a systematic model for the use of technology to optimize brain health.

To investigate the effect of a social robot intervention on depression, loneliness, and quality of life of older adults in long-term care (LTC) and to explore participants’ experiences and perceptions after the intervention.

A mixed-methods approach consisting of a single group, before and after quasi-experimental design, and individual interview.

Twenty older adults with depression from four LTC facilities in Taiwan were recruited.

Each participant participated in 8 weeks of observation and 8 weeks of intervention. In the observation stage, participants received usual care or activities without any research intervention. In the intervention stage, each participant was given a Paro (Personal Assistive RobOt) to keep for 24 hours, 7 days a week.

The Geriatric Depression Scale, the UCLA Loneliness Scale Version 3, and the World Health Organization Quality of Life Questionnaire for older adults were administered at four time points. Individual qualitative interviews with thematic analysis followed.

A repeated multivariate analysis of variance and Friedmanʼs test showed no significant changes during the observation stage between T1 and T2 for depression and quality of life (p >.5). For the intervention stage, statistically significant changes in decreasing depression and loneliness and improving quality of life over time were identified. Three themes emerged from the interviews: (i) humanizing Paro through referring to personal experiences and engagement; (ii) increased social interaction with other people; and (iii) companionship resulting in improved mental well-being.

There were significant improvements in mental well-being in using Paro. Further research may help us to understand the advantages of using a Paro intervention as depression therapy.

The ultimate goal of artificial intelligence (AI) is to develop technologies that are best able to serve humanity. This will require advancements that go beyond the basic components of general intelligence. The term “intelligence” does not best represent the technological needs of advancing society, because it is “wisdom”, rather than intelligence, that is associated with greater well-being, happiness, health, and perhaps even longevity of the individual and the society. Thus, the future need in technology is for artificial wisdom (AW).

We examine the constructs of human intelligence and human wisdom in terms of their basic components, neurobiology, and relationship to aging, based on published empirical literature. We review the development of AI as inspired and driven by the model of human intelligence, and consider possible governing principles for AW that would enable humans to develop computers which can operationally utilize wise principles and result in wise acts. We review relevant examples of current efforts to develop such wise technologies.

AW systems will be based on developmental models of the neurobiology of human wisdom. These AW systems need to be able to a) learn from experience and self-correct; b) exhibit compassionate, unbiased, and ethical behaviors; and c) discern human emotions and help the human users to regulate their emotions and make wise decisions.

A close collaboration among computer scientists, neuroscientists, mental health experts, and ethicists is necessary for developing AW technologies, which will emulate the qualities of wise humans and thus serve the greatest benefit to humanity. Just as human intelligence and AI have helped further the understanding and usefulness of each other, human wisdom and AW can aid in promoting each other’s growth