Artificial intelligence in elderly healthcare: A scoping review

Use of artificial intelligence to support quality of life of people with dementia: A scoping review

BACKGROUND

Dementia has an impact on the quality of life (QoL) of people with dementia. Tailored services are crucial for improving their QoL. Advances in artificial intelligence (AI) offer opportunities for personalised care, potentially delaying institutionalisation and enhancing QoL. However, AI's specific role in approaches to support QoL for people with dementia remains unclear. This scoping review aims to synthesise the scientific evidence and grey literature on how AI can support the QoL of people with dementia.

METHOD

Following Joanna Briggs Institute guidelines, we searched PubMed, Scopus, ACM Digital Library, and Google Scholar in January 2024. Studies on AI, QoL (using Lawton's four-domain QoL definition), and people with dementia across various care settings were included. Two reviewers conducted a two-stage screening, and a narrative synthesis identified common themes arising from the individual studies to address the research question.

RESULTS

The search yielded 5.467 studies, after screening, thirty studies were included. Three AI categories were identified: monitoring systems, social robots, and AI approaches for performing activities of daily living. Most studies were feasibility studies, with little active involvement of people with dementia during the research process. Most AI-based approaches were monitoring systems targeting Lawton's behavioural competence (capacity for independent functioning) domain.

CONCLUSION

This review highlights that AI applications for enhancing QoL in people with dementia are still in early development, with research largely limited to small-scale feasibility studies rather than demonstrating clinical effectiveness. While AI holds promise, further exploration and rigorous real-world validation are needed before AI can meaningfully impact the daily lives of people with dementia.

Smart Home Technologies for Enhancing Independence of Living and Reducing Care Dependence in Older Adults: A Systematic Review

AIM

To systematically review the potential of smart home technology to enhance the independence of older adults and reduce their dependence on care. Additionally, it sought to examine the positive impacts of such technology on their golden years.

DESIGN

A systematic review based on Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA).

DATA SOURCES

The search was conducted on 8 April 2024. Peer-reviewed studies in PubMed, Embase, Web of Science, IEEE Xplore, Scopus, The Cochrane Library, CINAHL, CNKI, WANFANG DATA and VIP from 1 January 2000 to 8 April 2024 were searched.

METHODS

The methodological quality assessment used the Mixed Methods Appraisal Tool (MMAT). Positive findings relevant to this study were extracted from the literature and analysed using thematic synthesis.

RESULTS

After meticulously examining 3404 studies, we identified 21 relevant sources for in-depth analysis, including qualitative studies (n = 10), experimental studies (n = 9) and mixed method studies (n = 2). These sources were grouped into five core themes based on the pivotal role of smart home technologies in enabling ageing in place: daily monitoring, assisted living activities, life reminders, functional improvement and emotional companionship. The study found that smart home technology offers numerous benefits to the lives of older adults, including increased independence, psychological support, improved cognitive functioning, enhanced self-management, increased mobility, support for caregivers, promoted social engagement and enhanced quality of life.

CONCLUSION

Smart home technology can enhance the independence of older adults' lives, reduce their dependence on care, alleviate the burden on caregivers and promote home-based elderly care.

IMPACT

This systematic review contributes to understanding the capability of smart home technology to promote elderly care at home and help better utilise smart home technology to benefit older adults. Older adults and their caregivers should be encouraged to adopt this technology to improve older adults' quality of life.

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution.

Comparative evaluation of responses from DeepSeek-R1, ChatGPT-o1, ChatGPT-4, and dental GPT chatbots to patient inquiries about dental and maxillofacial prostheses

BACKGROUND

Artificial intelligence chatbots have the potential to inform and guide patients by providing human-like responses to questions about dental and maxillofacial prostheses. Information regarding the accuracy and qualifications of these responses is limited. This in-silico study aimed to evaluate the accuracy, quality, readability, understandability, and actionability of the responses from DeepSeek-R1, ChatGPT-o1, ChatGPT-4, and Dental GPT chatbots.

METHODS

Four chatbots were queried about 35 of the most frequently asked patient questions about their prostheses. The accuracy, quality, understandability, and actionability of the responses were assessed by two prosthodontists using five-point Likert scale, Global Quality Score, and Patient Education Materials Assessment Tool for Printed Materials scales, respectively. Readability was scored using the Flesch-Kincaid Grade Level and Flesch Reading Ease. The agreement was assessed using the Cohen Kappa test. Differences between chatbots were analyzed using the Kruskal-Wallis test, one-way ANOVA, and post-hoc tests.

RESULTS

Chatbots showed a significant difference in accuracy and readability (p <.05). Dental GPT recorded the highest accuracy score, whereas ChatGPT-4 had the lowest. DeepSeek-R1 performed best, while Dental GPT had the lowest performance in readability. Quality, understandability, actionability, and reader education scores did not show significant differences.

CONCLUSIONS

While accuracy may vary among chatbots, the domain-specific trained AI tool and ChatGPT-o1 demonstrated superior accuracy. Even if accuracy is high, misinformation in health care can have significant consequences. Enhancing the readability of the responses is essential, and chatbots should be chosen accordingly. The accuracy and readability of information from chatbots should be monitored for public health.

Digital Creative Art Interventions on Health Promotion Among Older Adults: A Scoping Review

BACKGROUND

Digital Creative Art Interventions (DCAIs) are innovative approaches to art interventions using digital technology, which can improve older adults' health. However, a comprehensive summary of the implementation of this intervention among older adults is lacking.

AIMS

To summarise the deliveries and categories of DCAIs, review their feasibility and roles in older adults' healthcare, and explore the barriers and facilitators to implementing DCAIs in older adults.

DESIGN

Scoping review.

METHOD

This scoping review followed Arksey and O'Malley's framework, and PRISMA-ScR was used to guide the report.

DATA SOURCES

PubMed, Embase, EBSCOhost, Web of Science and Cochrane Library on 26 February 2024.

RESULTS

Thirty-one studies were selected in this review. We summarised the deliveries and categories of DCAIs in older adults. Besides, we cleared DCAIs to offer music, dance, museum, photo collage, drama, visual art interaction and mixed art intervention to older adults, primarily through videoconferencing or mobile applications. The five health promotion roles were physiological health enhancer, psychological caregiver, socialisation supporter, cognitive promoter and life optimiser. Most older adults believed DCAIs were not only feasible and acceptable, but they also met some barriers such as technological problems, problems brought about by older adults' decline in functioning, experience and privacy.

CONCLUSION

Despite the unique advantages of DCAIs, continuous improvements are needed. In the future, researchers and healthcare workers should focus on platform improvements, increasing interactivity, diversifying formats and ensuring security and privacy.

IMPACT

This review found that DCAIs offered new approaches to treatment options for older adults' physical and mental health. Therefore, it is recommended that they be continuously optimised and put into clinical practice.

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution.

CONTRIBUTE

This study summarised the DCAIs and provides the new approach for health promotion in older adults.

TRIAL REGISTRATION

OSF (https://osf.io/m62x9/, registration DOI: https://doi.org/10.17605/OSF.IO/4ZGE6).

An artificial intelligence perspective on geriatric syndromes: assessing the information accuracy and readability of ChatGPT

PURPOSE

ChatGPT, a comprehensive language processing model, provides the opportunity for supportive and professional interactions with patients. However, its use to address patients' frequently asked questions (FAQs) and the readability of the text generated by ChatGPT remain unexplored, particularly in geriatrics. We identified the FAQs about common geriatric syndromes and assessed the accuracy and readability of the responses provided by ChatGPT.

METHODS

Two geriatricians with extensive knowledge and experience in geriatric syndromes independently reviewed the 28 responses provided by ChatGPT. The accuracy of the responses generated by ChatGPT was categorized on a rating scale from 0 (harmful) to 4 (excellent) based on current guidelines and approaches. The readability of the text generated by ChatGPT was assessed by administering two tests: the Flesch-Kincaid Reading Ease (FKRE) and the Flesch-Kincaid Grade Level (FKGL).

RESULTS

ChatGPT-generated responses with an overall mean accuracy score of 88% (3.52/4). Responses generated for sarcopenia diagnosis and depression treatment in older adults had the lowest accuracy scores (2.0 and 2.5, respectively). The mean FKRE score of the texts was 25.2, while the mean FKGL score was 14.5.

CONCLUSION

The accuracy scores of the responses generated by ChatGPT were high in most common geriatric syndromes except for sarcopenia diagnosis and depression treatment. Moreover, the text generated by ChatGPT was very difficult to read and best understood by college graduates. ChatGPT may reduce the uncertainty many patients face. Nevertheless, it remains advisable to consult with subject matter experts when undertaking consequential decision-making.

Health Care Social Robots in the Age of Generative AI: Protocol for a Scoping Review

BACKGROUND

Social robots (SR), sensorimotor machines designed to interact with humans, can help to respond to the increasing demands in the health care sector. To ensure the successful use of this technology, acceptance is paramount. Generative artificial intelligence (AI) is an emerging technology with the potential to enhance the functionality of SR and promote user acceptance by further improving human-robot interaction.

OBJECTIVE

We present a protocol for a scoping review of the literature on the implementation of generative AI in SR in the health care sector. The aim of this scoping review is to map out the intersection of SR and generative AI in the health care sector; to explore if generative AI is applied in SR in the health care sector; to outline which models of generative AI and SR are used for these implementations; and to explore whether user acceptance is reported as an outcome following these implementations. This scoping review supports future research by providing an overview of the state of connectedness of 2 emerging technologies and by mapping out research gaps.

METHODS

We follow the methodological framework developed by Arksey and O'Malley and the recommendations by the Joanna Briggs Institute. Our protocol was drafted using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews). We will conduct a systematic literature search of the online databases MEDLINE, Embase, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Science, and IEEE Xplore, aiming to retrieve relevant data items via tabular data charting from references meeting specific inclusion criteria which are studies published from 2010 onwards, set in the health care sector, focusing on SR with physical bodies and implemented generative AI. There are no restrictions on study types. Results will be categorized, clustered, and summarized using tables, graphs, visual representations, and narratives.

RESULTS

After conducting a preliminary search and deduplication in the second quarter of 2024, we retrieved 3176 preliminary results. This scoping review will be supplemented with the next methodological steps, including retrieving the results in a reference management tool as well as screening titles, abstracts, and full text regarding specific inclusion criteria. The completion of these steps is scheduled for the second quarter of 2025. Limitations based on the heterogeneity of the included studies and the general breadth of a scoping review compared to a systematic review are to be expected. To reduce bias, we adopted a system of dual reviews and thorough documentation of the study selection.

CONCLUSIONS

The conducted preliminary search implies that there are a sufficient number of heterogeneous references to complete this scoping review. To our knowledge, this is the first scoping review on generative AI in health care SR.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/63017.

Identifying Contextual Factors That Shape Cybersecurity Risk Perception for Assisted Living and Health Care Technologies and Wearables: Mixed Methods Study

BACKGROUND

Over the last decade, the health care technology landscape has expanded significantly, introducing new and innovative solutions to address health care needs. The implications of cybersecurity incidents in the health care context extend beyond data breaches to potentially harming individuals' health and safety. Risk perception is influenced by various contextual factors, contributing to cybersecurity concerns that technological safeguards alone cannot address. Thus, it is imperative to study risk perceptions, contextual factors, and technological benefits to guide policy development, risk management, education, and implementation strategies.

OBJECTIVE

This study aims to investigate the differences in cybersecurity risk perception among various stakeholders in the health care sector in Norway and British Columbia (BC), Canada, and identify specific contextual factors that shape these perceptions. We expect to identify differences in risk perceptions for the explored health care technologies.

METHODS

We used a mixed methods approach comprising surveys and semistructured interviews to sample health care-related wearable technology stakeholders, including health care workers, patients (adults and adolescents) and their families, health authorities and hospital staff (biomedical engineers, information technology support, research staff), and device vendors/industry professionals in Norway and BC. Surveys explored information security scenarios based on the Behavioral-Cognitive Internet Security Questionnaire (BCISQ), risk perception, and contextualizing variables. We analyzed both survey data sets to summarize participants' characteristics and responses to questions related to the BCISQ (behavior and attitude) and risk perception. Interviews were analyzed thematically using an inductive-deductive approach to explore risk perception and contextual factors.

RESULTS

Data from 274 survey respondents were available for analysis: 185 from Norway, including 139 (75.1%) females, and 89 from BC, including 57 (64%) females. A total of 45 respondents (31 in Norway and 14 in BC) participated in interviews. The BCISQ showed minor differences between locations; respondents demonstrated generally low-risk behavior and robust information security awareness. However, password simulation demonstrated discrepancies between self-assessed and "real" behavior by sharing or willingness to share passwords. Perceived risk is generally considered low, yet consequences of cybersecurity risks were evaluated as major but unlikely. Risk perception was stronger for assisted living and diabetes technologies than for smartwatches. The most important contextual factors shaping risk perceptions are human factors encompassing knowledge, competence, familiarity, feelings of dread, perceived benefit, and trust, as well as the technological factor of device functionality. Organizational and technological factors had lesser effects.

CONCLUSIONS

We found minimal differences in behavior and risk perception among Norwegian and BC participants. Human factors and device functionality were most influential in shaping cybersecurity risk perceptions. Considering the rising need for assisted living technologies and wearables, insights into risk perceptions can strengthen risk management, awareness, and competence building. Further, it can address potential concerns among stakeholders to enable quicker technology adoption.

AI-Powered Transformation of Healthcare: Enhancing Patient Safety Through AI Interventions with the Mediating Role of Operational Efficiency and Moderating Role of Digital Competence-Insights from the Gulf Cooperation Council Region

Background/Objectives: The purpose of this study is to investigate the role of the adoption of artificial intelligence technology in improving patient safety in hospitals working in gulf Cooperation Council (GCC) countries, with a focus on the mediating role of operational efficiency and moderating effect of digital competence. Methods: Applying a quantitative, cross-sectional, and explanatory research design, data were gathered from 300 healthcare professionals across five hospitals in the GCC region. Results: The results show that AI interventions improve patient safety by improving operational efficiency, while the digital competence of healthcare professionals further enhances the effectiveness of AI interventions. The findings exhibit that AI interventions enhance patient safety through high diagnostic accuracy at 95.2%, combined with 1.8% low medication errors and 92.4% efficient timely interventions. Based on previous research, the proposed approach achieves 5.7% better diagnostic accuracy and 1.4% fewer medication errors, together with 4.9% enhanced timely interventions. Conclusions and Implications: These findings highlight the importance of adopting AI technologies and enhancing digital competence among healthcare professionals to optimize operational efficiency and ensure safer healthcare delivery. This study offers actionable insights for healthcare managers and policymakers, emphasizing the need for AI-driven training programs and infrastructure investments.

Perspectives of Older Adults on Self-Care of Chronic Diseases Utilizing Online Health Resources: An Exploratory Descriptive Qualitative Study

As the aging population grows rapidly, older adults are living longer with multiple chronic diseases. Coupled with the rise of the digital era, older adults are experiencing the brunt of the global aging phenomenon. The study aims to explore the perspectives of older adults on self-care for chronic diseases with the application of online resources. An exploratory qualitative study with focus group discussions was conducted to shed light on the insights of older adults from senior activity centers. Purposive sampling was used to include older adults with at least one chronic disease and living in the community. Twenty older adults were interviewed face-to-face in four focused-group discussions, led by a semi-structured interview guide that thematic analysis was then applied to. Four overarching themes and 14 subthemes emerged. The four major themes were (1) Barriers to a Healthier Life; (2) Proactively Acquiring Knowledge for Health Management; (3) Socially-influenced Health Decision-Making, and (4) Conducive Ecosystem Encourages Health-Promoting Behaviors. Older adults often face challenges in navigating the evolving digital landscape, yet they are receptive to learning from social networks and online resources, which help them make healthier self-care choices. Hence, a supportive environment is essential to empower older adults to effectively utilize online resources for managing their chronic diseases.

Effectiveness of Robot-Assisted Board Games on Cognitive Function and Mental Health for Older Adults with Mild Cognitive Impairment: A Cluster Randomized Trial

The effectiveness of robot-assisted board games targeting older adults with mild cognitive impairment was investigated to improve their cognitive function, general self-efficacy, and life satisfaction and reduce depression. A quasiexperimental research design was adopted with 109 older adults from 8 long-term care facilities and day-care centers assigned to the experimental (n = 52) and comparison groups (n = 57). The experimental group underwent a 12-week cognitive training program. Both groups completed before-and-after and 3-month follow-up measurements for outcome variables, including cognitive function (scores of mini-mental state examination [MMSE] and Alzheimer's Disease Assessment Scale Cognitive Subscale [ADAS-Cog]), depression, general self-efficacy, and life satisfaction. The data were analyzed using the generalized estimating equation (GEE). The program's usability was assessed using the system usability scale (SUS). The GEE analyses revealed significant postintervention improvements in the experimental group's MMSE, ADAS-Cog, depression, general self-efficacy, and satisfaction with life scores. These effects persisted for the 3-month follow-up. The mean SUS score was 87.50, indicating the feasibility of robot-assisted interventions among older adults. These findings confirmed that interactive robot-assisted board games can improve cognitive function, general self-efficacy, and life satisfaction and reduce depression among older adults. The administration of long-term care facilities or day-care centers can adopt robot-assisted board games as a training tool to supplement health promotion activities to prevent cognitive deterioration and enhance mental health among older adults.

Virtual reality-based fine motor skills training in paediatric rehabilitation: a protocol for a scoping review

INTRODUCTION

Fine motor skill (FMS) development during childhood is essential to many learning processes, especially in school. FMS impairment can have a major impact on children's quality of life. Developing effective and engaging rehabilitation solutions to train FMS that engage children in the abundant practice required for motor learning can be challenging. Virtual reality (VR) is a promising intervention option offering engaging FMS training tasks and environments that align with evidence-based motor learning principles. Other potential advantages of VR for rehabilitation include accessibility for home-based use and adaptability to individual needs. The objective of this scoping review is to map the extent, range and nature of VR applications focused on FMS training in paediatric rehabilitation, including hardware, software and interventional parameters.

METHODS AND ANALYSIS

We are following methodological guidelines for scoping review conduct and reporting from the Joanna Briggs Institute (JBI) Manual for Evidence Synthesis and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews recommendations. We will search four databases (Pubmed, Web of Science, PsycInfo and Scopus) for articles that meet inclusion criteria defined by the Population, Concept, Context method; specifically studies focused on development or evaluation of immersive or non-immersive VR applications to deliver FMS training in paediatric rehabilitation. Different populations of children with FMS impairments will be included (such as children with cerebral palsy, children with developmental coordination disorder or attention deficit hyperactivity disorder). The first search took place in December 2023, and a second is planned for February 2025. One reviewer will complete title, abstract and full paper screening, with consultation by a second reviewer in case of uncertainty. A data extraction framework will be tested by two reviewers on five randomly selected studies to ensure inter-rater reliability, and one reviewer will complete data extraction. Quantitative and qualitative extraction will follow JBI guideline recommendations. Results will be presented in a descriptive and tabular format, including a narrative summary. Results will enhance understanding of the potential of FMS training in VR and inform subsequent directions for research and clinical practice.

ETHICS AND DISSEMINATION

Data for this review will be collected from the published literature. Ethical approval is not required. We will present our findings at scientific conferences and submit this review to a peer-reviewed journal for publication.

The feasibility and effectiveness of telecare consultations in a nurse-led post-acute stroke clinic

BACKGROUND

Telecare may provide an alternative to maintaining post-acute stroke care services in making benefit to both the providers and the stroke survivors, although study is needed to investigate its feasibility and effectiveness in integrating this innovative delivery mode into a routine.

OBJECTIVES

The objectives of this study are to assess the feasibility and effectiveness of telecare consultations in a nurse-led post-acute stroke clinic.

METHODS

A pre- and post-test one group quasi-experimental design was adopted. Subjects were recruited in the clinic and received three secondary stroke care consultations in 3 months via telecare from stroke nurses. Data were collected at pre- and post-intervention. A Wilcoxon signed-rank test was used to compare the two time-points for differences in effectiveness.

RESULTS

Ninety-two stroke survivors participated. The drop-out rate was 27%. The majority perceived the programme as time-friendly and cost-saving and as alleviating their health-related worries. At the 3-month follow-up, notable improvements were observed in the activities of daily living and the strength domain of stroke-specific quality of life.

CONCLUSIONS

Integrating telecare consultations within nurse-led stroke clinics is a feasible and acceptable strategy for monitoring the health and fostering the self-care abilities of individuals following their discharge from hospital after an acute stroke episode.

Exploring geriatric nurses' perspectives on the adoption of AI in elderly care a qualitative study

This phenomenological study explored the perspectives of geriatric nurses on the adoption of artificial intelligence (AI) in elderly care. Thematic analysis of semi-structured interviews with 17 nurses revealed perceived benefits, challenges, ethical considerations, and practical implications. Participants acknowledged AI's potential for improving diagnostic accuracy, personalized care, continuous monitoring, and data pattern insights. However, concerns were raised regarding workflow integration, cost barriers, resistance to change, data privacy, diminishment of human elements, and the need for ethical guidelines. A cautious optimism was expressed, emphasizing the importance of addressing practical challenges, maintaining the human touch, and fostering a collaborative approach. The findings highlight the need for comprehensive training, user-centered design, ethical frameworks, and strategies to overcome financial and implementation barriers. Future research should focus on evaluating the impact of AI implementation on patient outcomes and nursing experiences.

Students perspectives on the development and deployment of an AI-enabled service robot in long-term care

The need for Artificial Intelligence (AI) in gerontology education is underscored by the potential benefits it offers in addressing loneliness and supporting social connection among older adults in long-term care (LTC) homes. While the workforce in LTC is often overburdened, AI-enabled service robots present possible solutions to enhance residents' quality of life. However, the incorporation of AI and service robots in current gerontology curricula is lacking, and the views of students on this subject remain largely unexamined. This study aims to fill this gap by capturing the perspectives of university students regarding the deployment of an AI robot, Aether, in LTC environments. In this qualitative study, we conducted focus groups with 22 university students. Our thematic analysis identified three themes: (1) Aether's anticipated usage in geriatric care: companionship support and complementing the work of staff; (2) Challenges in using Aether: technical and emotional challenges; and (3) Solutions and future possibilities: expanding functionalities and integrating personalization features. Students expressed a positive outlook on the role of AI-enabled robots while also highlighting the necessity of addressing ethical and practical considerations. To effectively integrate AI technology in gerontology education, it is essential to understand and incorporate student perspectives, attitudes, and opinions.

Is androstadienone a human male pheromone? More research is needed

Androsta-4,16‑dien-3-one (androstadienone, AND), a steroid predominantly found in male secretions, has been associated with a variety of sex-specific effects on emotion, physiological states, cognition, and neural activity. An expanding body of literature has explored the influence of AND on human behavior and perception, leading to its frequent description as a "putative human sex pheromone." This article reviews the existing research on the physiological, cognitive, and neuroimaging effects of AND, critically assessing the evidence regarding its classification as a human sex pheromone. Additionally, it underscores the need for methodological standardization and rigor in future studies to establish clearer conclusions. Based on current evidence, the categorization of AND as a "human sex pheromone" remains inconclusive, highlighting the necessity for continued investigation. Future research directions are suggested to further elucidate AND's potential effects and applications.

Machine learning methods to discover hidden patterns in well-being and resilience for healthy aging

BACKGROUND

A whole person approach to healthy aging can provide insight into social factors that may be critical. Digital technologies, such as mobile health (mHealth) applications, hold promise to provide novel insights for healthy aging and the ability to collect data between clinical care visits. Machine learning/artificial intelligence methods have the potential to uncover insights into healthy aging. Nurses and nurse informaticians have a unique lens to shape the future use of this technology.

METHODS

The purpose of this research was to apply machine learning methods to MyStrengths+MyHealth de-identified data (N = 988) for adults 45 years of age and older. An exploratory data analysis process guided this work.

RESULTS

Overall (n = 988), the average Strength was 66.1% (SD = 5.1), average Challenges 66.5% (SD = 7.5), and average Needs 60.06% (SD = 3.1). There was a significant difference between Strengths and Needs (p < 0.001), between Challenges and Needs (p < 0.001), and no significant differences between average Strengths and Challenges. Four concept groups were identified from the data (Thinking, Moving, Emotions, and Sleeping). The Thinking group had the most statistically significant challenges (11) associated with having at least one Thinking Challenge and the highest average Strengths (66.5%) and Needs (83.6%) compared to the other groups.

CONCLUSION

This retrospective analysis applied machine learning methods to de-identified whole person health resilience data from the MSMH application. Adults 45 and older had many Strengths despite numerous Challenges and Needs. The Thinking group had the highest Strengths, Challenges, and Needs, which aligns with the literature and highlights the co-occurring health challenges experienced by this group. Machine learning methods applied to consumer health data identify unique insights applicable to specific conditions (e.g., cognitive) and healthy aging. The next steps involve testing personalized interventions with nurses leading artificial intelligence integration into clinical care.

Health technology assessment framework for artificial intelligence-based technologies

OBJECTIVES

Artificial intelligence (AI)-based health technologies (AIHTs) have already been applied in clinical practice. However, there is currently no standardized framework for evaluating them based on the principles of health technology assessment (HTA).

METHODS

A two-round Delphi survey was distributed to a panel of experts to determine the significance of incorporating topics outlined in the EUnetHTA Core Model and twenty additional ones identified through literature reviews. Each panelist assigned scores to each topic. Topics were categorized as critical to include (scores 7-9), important but not critical (scores 4-6), and not important (scores 1-3). A 70 percent cutoff was used to determine high agreement.

RESULTS

Our panel of 46 experts indicated that 48 out of the 65 proposed topics are critical and should be included in an HTA framework for AIHTs. Among the ten most crucial topics, the following emerged: accuracy of the AI model (97.78 percent), patient safety (95.65 percent), benefit-harm balance evaluated from an ethical standpoint (95.56 percent), and bias in data (91.30 percent). Importantly, our findings highlight that the Core Model is insufficient in capturing all relevant topics for AI-based technologies, as 14 out of the additional 20 topics were identified as crucial.

CONCLUSION

It is imperative to determine the level of agreement on AI-relevant HTA topics to establish a robust assessment framework. This framework will play a foundational role in evaluating AI tools for the early diagnosis of dementia, which is the focus of the European project AI-Mind currently being developed.

Protecting older consumers in the digital age: a commentary on ChatGPT, helplines and the way to prevent accessible fraud

Older people are often targeted by fraudsters due to their unique characteristics and vulnerabilities. Being a victim of exploitation can lead to negative emotional and financial consequences. The purpose of this commentary is to present ChatGPT's potential to provide accessible information and support, helping older consumers protect themselves when confronted with exploitation, address the limitations of ChatGPT and propose solutions to overcome these limitations. Integrating tailored human and technological solutions, such as helplines, AI chatbots, and involving older adults in development, is crucial. By providing adequate training and support, the goal of ensuring accessibility for all users can be achieved.

Digital social media expression and social adaptability of the older adult driven by artificial intelligence

Introduction

This study examines the impact of digital new media art on the health literacy and digital health literacy of older adults. It explores how digital new media art influences the social adaptability of the older adult, with a focus on variations in their engagement with digital technologies and community activities.

Methods

The research employed interviews and observations of older adult participants from communities A and B. Data were collected on their smartphone usage, community engagement, and access to technological infrastructure. The study also assessed their interaction with digital new media across various domains, including interpersonal communication, information retrieval, entertainment, practical applications, and mobile payments.

Results

The study found significant differences in engagement with digital new media art among the older adult. Participants with prior computer experience were generally more skilled in using smartphones and more active in community events. In contrast, individuals in community B showed lower acceptance of digital new media art and no clear association with community participation. There was substantial variability in their use of digital media for information retrieval, entertainment, practical applications, and mobile payments. Some older adult individuals demonstrated proficiency with these technologies, while others were more reserved.

Discussion

The findings suggest that digital new media art can enhance community participation and social adaptability among older adults, particularly those with prior computer experience. However, disparities in digital media usage highlight the need for targeted interventions to improve digital health literacy and engagement across different community settings. The study underscores the importance of addressing these disparities to ensure that all older adults can benefit from digital advancements, thereby improving their overall well-being and health literacy.

Theologizing on Artificial Intelligence in Elderly Care

As the number of elderly persons rises, there is a gradual increase in reliance on artificial intelligence (AI) to augment healthcare systems. How do we interpret AI in elderly care (EC) in light of the Catholic theological tradition? As far as the literature goes to date, there is still much room for discourse. For this reason, this article hopes to contribute in that regard and, more importantly, to encourage others to further the discourse. In the present commentary, I first examine some aging trends in the world population. Afterward, I briefly describe AI use in healthcare, especially for EC. I then explore prominent ethical concerns related to it. Finally, I theologically reflect on using AI for EC vis-à-vis the magisterial teachings on aging and AI.

Transforming the discharge conversation through support and structure: A scoping review

Background

System level demands and interpersonal barriers can disrupt nurse delivery of high-quality information at discharge, which can contribute to a lack of caregiver preparedness to manage care of the patient and ultimately affect patient health.

Objective

To synthesize evidence on effective nurse communication with informal caregivers during hospital discharge of adult patients with cognitive decline or Alzheimer's disease and related dementia.

Design

A scoping review of inpatient nurse communication with informal caregivers.

Methods

Collected research (published between 2011 and 2023) from three databases (MEDLINE, PsycINFO, and CINAHL), along with a separate search for gray literature (N = 18), to extract and synthesize recommended communication practices evidenced to improve the nurse care experience and support caregiver activation and preparedness.

Results

Extraction synthesis of strategies resulted in two themes with corresponding sub-themes: Support (Information exchange, Space and time to determine preparedness, and Positive reinforcement of caregiver efforts) and Structure (Setting shared expectations, Informational resources, and Standardization).

Conclusions

We offer practical recommendations for both interpersonal and policy level facilitation of nurse delivery of high-quality information at discharge to caregivers of patients with serious illness.

Association of smart elderly care and quality of life among older adults: the mediating role of social support

BACKGROUND

In the current context of ageing, the field of smart elderly care has gradually developed, contributing to the promotion of health among older adults. While the positive impact on health has been established, there is a scarcity of research examining its impact on the quality of life (QoL). This study aims to investigate the mediating role of social support in the relationship between smart elderly care and QoL among older adults.

METHODS

A total of 1313 older adults from Zhejiang Province, China, participated in the study. Questionnaires were used to collect data on participants' basic demographic information, smart elderly care, social support, and QoL. The descriptive analyses of the demographic characteristics and correlation analyses of the three variables were calculated. Indirect effects were tested using bootstrapped confidence intervals (CI).

RESULTS

The analysis revealed a positive association between smart elderly care and social support (β = 0.42, p < 0.01), as well as a positive correlation between social support and QoL (β = 0.65, p < 0.01). Notably, social support emerged as an important independent mediator (effect size = 0.28, 95% bootstrap CI 0.24 to 0.32) in the relationship between smart elderly care and QoL.

CONCLUSIONS

The results of this study underscore the importance of promoting the utilization of smart elderly care and improving multi-faceted social support for older adults, as these factors positively contribute to the overall QoL.

Artificial intelligence based on falling in older people: A bibliometric analysis

Objectives

This study aimed to analyze publications on artificial intelligence (AI) for falls in older people from a bibliometric perspective.

Methods

The Web of Science database was searched for titles of English-language articles containing the words "artificial intelligence," "deep learning," "machine learning," "natural language processing,", "neural artificial network," "fall," "geriatric," "elderly," "aging," "older," and "old age." An R-based application (Biblioshiny for bibliometrics) and VOSviewer software were used for analysis.

Results

Thirty-seven English articles published between 2018 and 2024 were included. The year 2023 is the year with the most publications with 16 articles. The most productive research field was "Engineering Electrical Electronic" with seven articles. The most productive country was the United States, followed by China. The most common words were "injuries," "people," and "risk factors."

Conclusion

Publications on AI and falls in the elderly are both few in number and the number of publications has increased in recent years. Future research should include relevant analyses in scientific databases, such as Scopus and PubMed.

The expectations and acceptability of a smart nursing home model among Chinese older adults: a mixed methods study

BACKGROUND

Smart nursing homes (SNHs) integrate advanced technologies, including IoT, digital health, big data, AI, and cloud computing to optimise remote clinical services, monitor abnormal events, enhance decision-making, and support daily activities for older residents, ensuring overall well-being in a safe and cost-effective environment. This study developed and validated a 24-item Expectation and Acceptability of Smart Nursing Homes Questionnaire (EASNH-Q), and examined the levels of expectations and acceptability of SNHs and associated factors among older adults in China.

METHODS

This was an exploratory sequential mixed methods study, where the qualitative case study was conducted in Hainan and Dalian, while the survey was conducted in Xi'an, Nanjing, Shenyang, and Xiamen. The validation of EASNH-Q also included exploratory and confirmatory factor analyses. Multinomial logistic regression analysis was used to estimate the determinants of expectations and acceptability of SNHs.

RESULTS

The newly developed EASNH-Q uses a Likert Scale ranging from 1 (strongly disagree) to 5 (strongly agree), and underwent validation and refinement from 49 items to the final 24 items. The content validity indices for relevance, comprehensibility, and comprehensiveness were all above 0.95. The expectations and acceptability of SNHs exhibited a strong correlation (r = 0.85, p < 0.01), and good test-retest reliability for expectation (0.90) and acceptability (0.81). The highest tertile of expectations (X2=28.89, p < 0.001) and acceptability (X2=25.64, p < 0.001) towards SNHs were significantly associated with the willingness to relocate to such facilities. Older adults with self-efficacy in applying smart technologies (OR: 28.0) and those expressing a willingness to move to a nursing home (OR: 3.0) were more likely to have the highest tertile of expectations compared to those in the lowest tertile. Similarly, older adults with self-efficacy in applying smart technologies were more likely to be in the highest tertile of acceptability of SNHs (OR: 13.8).

CONCLUSIONS

EASNH-Q demonstrated commendable validity, reliability, and stability. The majority of Chinese older adults have high expectations for and accept SNHs. Self-efficacy in applying smart technologies and willingness to relocate to a nursing home associated with high expectations and acceptability of SNHs.

The leading global health challenges in the artificial intelligence era

Millions of people's health is at risk because of several factors and multiple overlapping crises, all of which hit the vulnerable the most. These challenges are dynamic and evolve in response to emerging health challenges and concerns, which need effective collaboration among countries working toward achieving Sustainable Development Goals (SDGs) and securing global health. Mental Health, the Impact of climate change, cardiovascular diseases (CVDs), diabetes, Infectious diseases, health system, and population aging are examples of challenges known to pose a vast burden worldwide. We are at a point known as the "digital revolution," characterized by the expansion of artificial intelligence (AI) and a fusion of technology types. AI has emerged as a powerful tool for addressing various health challenges, and the last ten years have been influential due to the rapid expansion in the production and accessibility of health-related data. The computational models and algorithms can understand complicated health and medical data to perform various functions and deep-learning strategies. This narrative mini-review summarizes the most current AI applications to address the leading global health challenges. Harnessing its capabilities can ultimately mitigate the Impact of these challenges and revolutionize the field. It has the ability to strengthen global health through personalized health care and improved preparedness and response to future challenges. However, ethical and legal concerns about individual or community privacy and autonomy must be addressed for effective implementation.

Using Interoperability between Mobile Robot and KNX Technology for Occupancy Monitoring in Smart Home Care

It is important for older and disabled people who live alone to be able to cope with the daily challenges of living at home. In order to support independent living, the Smart Home Care (SHC) concept offers the possibility of providing comfortable control of operational and technical functions using a mobile robot for operating and assisting activities to support independent living for elderly and disabled people. This article presents a unique proposal for the implementation of interoperability between a mobile robot and KNX technology in a home environment within SHC automation to determine the presence of people and occupancy of occupied spaces in SHC using measured operational and technical variables (to determine the quality of the indoor environment), such as temperature, relative humidity, light intensity, and CO2 concentration, and to locate occupancy in SHC spaces using magnetic contacts monitoring the opening/closing of windows and doors by indirectly monitoring occupancy without the use of cameras. In this article, a novel method using nonlinear autoregressive Neural Networks (NN) with exogenous inputs and nonlinear autoregressive is used to predict the CO2 concentration waveform to transmit the information from KNX technology to mobile robots for monitoring and determining the occupancy of people in SHC with better than 98% accuracy.

Tablet-Based Puzzle Game Intervention for Cognitive Function and Well-Being in Healthy Adults: Pilot Feasibility Randomized Controlled Trial

Background

Promoting cognitive health is key to maintaining cognitive and everyday functions and preventing the risk of cognitive impairment or dementia. Existing scientific evidence shows the benefits of various training modalities on cognition. One way to promote cognitive health is through engagement in cognitive activities (eg, board and video games).

Objective

This study aims to investigate the benefits of dynamic adaptive casual puzzle games on cognitive function and well-being in healthy adults and older people.

Methods

A total of 12 adults and older people (female participants: n=6; mean age 58.92, SD 10.28 years; range 46-75 years) were included in this pilot randomized controlled trial. This study used a crossover design with two phases (8 weeks each) and three measurement waves (pretest, midtest, and posttest). The participants were randomly allocated either to the control or experimental group. In the control group, participants read newspapers between the pre- and midtest, then switched to cognitive training with puzzle games. In the experimental group, the interventions were reversed. Baseline measurements (pretest) were collected before the intervention. The interventions were delivered on tablet computers and took place unsupervised at participants' homes.

Results

The outcome measures included global cognitive function, higher cognitive function, and emotional well-being at 3 time points (pretest, midtest, and posttest) using standardized neuropsychological tests. The participants showed improvements in their visual attention and visuospatial measures after the puzzle game intervention.

Conclusions

The study showed that digital games are a feasible way to train cognition in healthy adults and older people. The algorithm-based dynamic adaption allows accommodations for persons with different cognitive levels of skill. The results of the study will guide future prevention efforts and trials in high-risk populations.

Characteristics of RCTs focusing on health promotion in community samples: a scoping review protocol based on the d-CoSPICO framework

INTRODUCTION

Developing the capabilities of individuals, groups and communities to enhance their health has received a great deal of attention in the literature. One essential source of results is evidence-based intervention programmes, which often involve a number of different variables. This paper describes a methodology for carrying out a scoping review that maps available evidence on randomised controlled trials focusing on health promotion intervention programmes.

METHODS AND ANALYSIS

The scoping review protocol follows the general Preferred Reporting Items for Systematic Reviews and Meta-Analyses and Joanna Briggs Institute guidelines. It also incorporates some modifications to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Review flowchart and complements its methodological framework. This new format, called documents, Concept, Studies, Participants, Interventions, Comparator, and Outcomes (d-CoSPICO), guides the review sequence, which is represented in a flowchart. The search will focus on different sources of information using formal (searches in thematic -PubPsych, ERIC, MedLine, PsychINFO- and multidisciplinary databases -Academic Search Ultimate, Core Collection Web of Science, Scopus and ProQuest-, repositories and other websites), informal (contact with researchers), and retrospective (previous reviews on this topic) strategies to identify relevant publications until 2021, including grey literature. Coding, identification, selection, and data extraction will be carried out following the generation of a database in which each retrieved record's content (abstract and/or full text) can be analysed. The review is expected to be completed in 2023.

ETHICS AND DISSEMINATION

Ethical approval is not required for this review. The d-CoSPICO framework and the results will be disseminated through (a) peer-reviewed publications; (b) presentations at scientific dissemination events and (c) training activities for applying this protocol.

Nursing in a posthuman era: Towards a technology-integrated ecosystem of care

The healthcare sector has undergone significant transformation due to the rapid advancements in artificial intelligence and biotechnologies, presenting both opportunities and threats to the nursing profession. Posthumanism, as a critical perspective challenging anthropocentrism and emphasizing the increasingly blurred boundaries between humans and nonhumans, provides a novel lens to comprehend these technological advancements. In this commentary paper, I draw on the posthuman discourse to argue that in light of these technological forces, we need to contemplate the core values and fundamental patterns of knowing within the nursing discipline, reconfigure nursing scope, redefine its relations with other agents, and embrace a technology-integrated ecosystem of care.

Impact of Virtual Reality Cognitive and Motor Exercises on Brain Health

Innovative technologies of the 21st century have an extremely significant impact on all activities of modern humans. Among them, virtual reality (VR) offers great opportunities for scientific research and public health. The results of research to date both demonstrate the beneficial effects of using virtual worlds, and indicate undesirable effects on bodily functions. This review presents interesting recent findings related to training/exercise in virtual environments and its impact on cognitive and motor functions. It also highlights the importance of VR as an effective tool for assessing and diagnosing these functions both in research and modern medical practice. The findings point to the enormous future potential of these rapidly developing innovative technologies. Of particular importance are applications of virtual reality in basic and clinical neuroscience.