Towards Responsible Implementation of Monitoring Technologies in Institutional Care

Sharing patient technology preferences with care networks: Stakeholders' views of the "Let's Talk Tech" decision aid for dementia care

BackgroundLet's Talk Tech (LTT) is a self-administered web intervention for people with memory loss and their care partners that supports decision-making about digital health technologies. In past work, dyads wanted to share LTT preference reports with their larger care networks.ObjectiveThis study aims to understand with whom care dyads want to share their technology preference reports and why, and if and how clinicians want to receive them.MethodsTogether, fifteen dyads of people living with mild cognitive impairment (MCI) or early-stage dementia (n = 15) and a care partner (n = 15) completed LTT and two survey questions. Care partners completed independent follow-up interviews, and 32 clinicians at four Alzheimer's Disease Research Center-affiliated clinics viewed an LTT report and completed a 10-question survey. We used descriptive statistics for survey responses and thematic analysis for interviews.ResultsTwo-thirds of care partners (n = 10) wanted to share the report with family members. Half (n = 8) wanted to share it with clinicians to keep them informed about the dyad's planning and facilitate conversations about technology options. 30 of 32 clinicians reported they would want their patients' technology preferences reports, with 25 wanting to access it via the electronic health record (EHR).ConclusionsFindings demonstrate potential value to both family dyads and providers of sharing technology preferences beyond the care dyad. Clinicians were highly receptive to accessing technology preference reports in EHRs and to having discussions about technology be a part of advance care planning. Future research should test integration in the EHR and the potential of sharing technology preferences to support person-centered technology choices.

Ethical and legal implications of health monitoring wearable devices: A scoping review

BACKGROUND

health monitoring wearable devices (HMWDs) are increasingly implemented for personalized and preventive care. This review aims to summarize the existing literature on the ethical and legal implications of HMWDs in healthcare.

METHODS

the study design is a scoping review and narrative synthesis of scientific literature. The literature search was conducted in May 2023, and updated on March 15th, 2024, from the following databases: PubMed, EBSCO (including CINAHL, PsycInfo, Index to Legal Periodicals & Books, Philosopher's Index), HeinOnline, Engineering Village, Nexis Uni and Cochrane Library. Pairs of blinded authors independently screened articles using Rayyan software, and manually checked reference lists of included articles. Peer-reviewed articles in English discussing ethical and/or legal implications of HMWDs in healthcare were included. A thematic synthesis approach was used to identify and summarize ethical and legal issues and recommendations.

PROTOCOL REGISTRATION

https://osf.io/kfuh4/.

FINDINGS

overall, out of 7767 records retrieved, 405 full texts were assessed, and 12 articles, published between 2017 and 2024, were included. We identified 6 main themes: the use of HMWDs may adversely affect and reshape care relationships and the healthcare system; the use of HMWDs raises a variety of justice-related concerns; there are ethical issues related to personal data; HMWDs present several risks but the benefits are still uncertain; there are ethical issues regarding clinical research on HMWDs; and the current regulatory framework is inadequate.

INTERPRETATION

the use of HMWDs in clinical and research settings raises several ethical and legal concerns, ranging from patient safety to autonomy, justice, and data protection. Implementing HMWDs without addressing these concerns may lead to dehumanization and datafication of care relationships and further marginalization of vulnerable populations.

Use of a Real-Time Locating System in Infection Control

Real-Time Locating Systems (RTLS) have emerged as powerful tools for revolutionizing healthcare by improving patient safety, optimizing workflow efficiency, and enhancing resource management. From patient tracking to infection control and emergency response, RTLS offer a plethora of applications. Although challenges such as privacy and integration need to be addressed, the benefits of RTLS in healthcare remain undeniable. As technology continues to evolve, the future holds exciting possibilities for RTLS, paving the way for smarter, more efficient, and patient-centered care.

Aging enacted in practice: How unloved objects thrive in the shadows of care

In this paper, we explore the seeming stability of aging. More precisely, we offer an empirical account of how aging - images of aging, embodiments of aging, feelings about aging - is enacted in company practice, both in place and across time. Drawing on ethnographic fieldwork conducted at SMCare, a small-to-medium sized company active in the care technology sector, we show how aging achieves its stability not through practices that are characterized by affection, or purposefully targeted at maintaining or caring for aging, but due to ongoing re-enactments in the shadows of other care practices. In so doing, we mobilize STS care literature that foregrounds the often-invisible relationships among objects that are otherwise neglected, marginalized and excluded. In particular, we interrogate the interlinkages between aging and caring practices as emerging in the shadows of care. In these blind spots, we find, certain unloved and disliked objects such as aging may aggregate and grow, becoming stable and durable as they are incidentally brought into existence, drawing energy from, and feeding off, other care practices.

Scoping Review Shows the Dynamics and Complexities Inherent to the Notion of "Responsibility" in Artificial Intelligence within the Healthcare Context

The increasing integration of artificial intelligence (AI) in healthcare presents a host of ethical, legal, social, and political challenges involving various stakeholders. These challenges prompt various studies proposing frameworks and guidelines to tackle these issues, emphasizing distinct phases of AI development, deployment, and oversight. As a result, the notion of responsible AI has become widespread, incorporating ethical principles such as transparency, fairness, responsibility, and privacy. This paper explores the existing literature on AI use in healthcare to examine how it addresses, defines, and discusses the concept of responsibility. We conducted a scoping review of literature related to AI responsibility in healthcare, searching databases and reference lists between January 2017 and January 2022 for terms related to "responsibility" and "AI in healthcare", and their derivatives. Following screening, 136 articles were included. Data were grouped into four thematic categories: (1) the variety of terminology used to describe and address responsibility; (2) principles and concepts associated with responsibility; (3) stakeholders' responsibilities in AI clinical development, use, and deployment; and (4) recommendations for addressing responsibility concerns. The results show the lack of a clear definition of AI responsibility in healthcare and highlight the importance of ensuring responsible development and implementation of AI in healthcare. Further research is necessary to clarify this notion to contribute to developing frameworks regarding the type of responsibility (ethical/moral/professional, legal, and causal) of various stakeholders involved in the AI lifecycle.

Relational Solidarity and Conflicting Ethics in Dementia Care in Urban India

OBJECTIVES

Using the concept of relational solidarity, we examine how autonomy, equality, dignity, and personhood are practiced in the care of people living with dementia at home in urban India.

METHODS

Video interviews with 19 family carers and 25 health providers conducted in English, Hindi, and Kannada in Bengaluru between March and July 2022. Data were translated into English and thematically analyzed.

RESULTS

Family carers and providers unanimously agreed that people with dementia should be respected and cared for. Concurrently, they perceived people with dementia as being "like a kid" and used the analogy of a parent-child relationship to understand their care responsibilities. This analogy informed how ethical principles such as personhood and equality were reframed in the relationships between family carers and people with dementia, as well as how carers and providers maintained the safety but undermined the autonomy of people with dementia through restricting their movements inside and outside the home.

DISCUSSION

There can be relational solidarity in dementia care at home in urban India but also contradictions in the interpretations and applications of the ethical principles of autonomy, equality, dignity, and personhood. As such, a more organic, grassroots model of ethical practice is needed to frame care and provide material support to families in India.

Addressing the Black Box of AI-A Model and Research Agenda on the Co-constitution of Aging and Artificial Intelligence

Algorithmic technologies and (large) data infrastructures, often referred to as Artificial Intelligence (AI), have received increasing attention from gerontological research in the last decade. Although there is much literature that dissects and explores the development, application, and evaluation of AI relevant to gerontology, this study makes a novel contribution by critically engaging with the theorizing in this growing field of research. We observe that gerontology's engagement with AI is shaped by an interventionist logic that situates AI as a black box for gerontological research. We demonstrate how this black box logic has neglected many aspects of AI as a research topic for gerontology and discuss three classical concepts in gerontology to show how they can be used to open various black boxes of aging and AI in the areas: (a) the datafication of aging, (b) the political economy of AI and aging, and (c) everyday engagements and embodiments of AI in later life. In the final chapter, we propose a model of the co-constitution of aging and AI that makes theoretical propositions to study the relational terrain between aging and AI and hence aims to open the black box of AI in gerontology beyond interventionist logic.

Rehabilitation professionals' perspectives and experiences with the use of technologies for violence prevention: a qualitative study

BACKGROUND

There is growing public policy and research interest in the development and use of various technologies for managing violence in healthcare settings to protect the health and well-being of patients and workers. However, little research exists on the impact of technologies on violence prevention, and in particular in the context of rehabilitation settings. Our study addresses this gap by exploring the perceptions and experiences of rehabilitation professionals regarding how technologies are used (or not) for violence prevention, and their perceptions regarding their efficacy and impact.

METHODS

This was a descriptive qualitative study with 10 diverse professionals (e.g., physical therapy, occupational therapy, recreation therapy, nursing) who worked across inpatient and outpatient settings in one rehabilitation hospital. Data collection consisted of semi-structured interviews with all participants. A conventional approach to content analysis was used to identify key themes.

RESULTS

We found that participants used three types of technologies for violence prevention: an electronic patient flagging system, fixed and portable emergency alarms, and cameras. All of these were perceived by participants as being largely ineffective for violence prevention due to poor design features, malfunction, limited resources, and incompatibility with the culture of care. Our analysis further suggests that professionals' perception that these technologies would not prevent violence may be linked to their focus on individual patients, with a corresponding lack of attention to structural factors, including the culture of care and the organizational and physical environment.

CONCLUSIONS

Our findings suggest an urgent need for greater consideration of structural factors in efforts to develop effective interventions for violence prevention in rehabilitation settings, including the design and implementation of new technologies.

Toward Responsible Artificial Intelligence in Long-Term Care: A Scoping Review on Practical Approaches

BACKGROUND AND OBJECTIVES

Artificial intelligence (AI) is widely positioned to become a key element of intelligent technologies used in the long-term care (LTC) for older adults. The increasing relevance and adoption of AI has encouraged debate over the societal and ethical implications of introducing and scaling AI. This scoping review investigates how the design and implementation of AI technologies in LTC is addressed responsibly: so-called responsible innovation (RI).

RESEARCH DESIGN AND METHODS

We conducted a systematic literature search in 5 electronic databases using concepts related to LTC, AI, and RI. We then performed a descriptive and thematic analysis to map the key concepts, types of evidence, and gaps in the literature.

RESULTS

After reviewing 3,339 papers, 25 papers were identified that met our inclusion criteria. From this literature, we extracted 3 overarching themes: user-oriented AI innovation; framing AI as a solution to RI issues; and context-sensitivity. Our results provide an overview of measures taken and recommendations provided to address responsible AI innovation in LTC.

DISCUSSION AND IMPLICATIONS

The review underlines the importance of the context of use when addressing responsible AI innovation in LTC. However, limited empirical evidence actually details how responsible AI innovation is addressed in context. Therefore, we recommend expanding empirical studies on RI at the level of specific AI technologies and their local contexts of use. Also, we call for more specific frameworks for responsible AI innovation in LTC to flexibly guide researchers and innovators. Future frameworks should clearly distinguish between RI processes and outcomes.

Electronic Tracking Devices for People With Dementia: Content Analysis of Company Websites

Background

Electronic tracking devices, also known as locators, monitors, or surveillance devices, are increasingly being used to manage dementia-related wandering and, subsequently, raising various ethical questions. Despite the known importance technology design has on the ethics of technologies, little research has focused on the companies responsible for the design and development of electronic tracking devices. This paper is the first to perform a qualitative analysis of the ethically related content of the websites of companies that design and develop electronic tracking devices.

Objective

The aim of this study was to understand how companies that design, develop, and market electronic tracking devices for dementia care frame, through textual marketing content, the vulnerabilities and needs of persons with dementia and caregivers, the way in which electronic tracking devices respond to these vulnerabilities and needs, and the ethical issues and values at stake.

Methods

Electronic tracking device company websites were identified via a Google search, 2 device recommendation lists (Alzheimer’s Los Angeles and the Canadian Agency for Drugs and Technologies in Health), and the 2 recent reviews of wander management technology by Neubauer et al and Ray et al. To be included, websites must be official representations of companies (not market or third-party websites) developing and selling electronic tracking devices for use in dementia care. The search was conducted on December 22, 2020, returning 199 websites excluding duplicates. Data synthesis and analysis were conducted on the textual content of the included websites using a modified form of the Qualitative Analysis Guide of Leuven.

Results

In total, 29 websites met the inclusion criteria. Most (15/29, 52%) companies were in the United States. The target audience of the websites was largely caregivers. A range of intertwined vulnerabilities facing persons with dementia and their caregivers were identified, and the companies addressed these via care tools that centered on certain values such as providing information while preserving privacy. Life after device implementation was characterized as a world aspired to that sees increased safety for persons with dementia and peace of mind for caregivers.

Conclusions

The way electronic tracking device content is currently conveyed excludes persons with dementia as a target audience. In presenting their products as a response to vulnerabilities, particular values are linked to design elements. A limitation of the results is the opaque nature of website content origins. How or when values arise in the process of design, development, and marketing is unknown. Therefore, further research should explore the process companies use to identify vulnerabilities, how values are decided upon and integrated into the design of products, and the perceptions of developers regarding the ethics of electronic tracking devices.

Algorithmic harms and digital ageism in the use of surveillance technologies in nursing homes

Ageism has not been centered in scholarship on AI or algorithmic harms despite the ways in which older adults are both digitally marginalized and positioned as targets for surveillance technology and risk mitigation. In this translation paper, we put gerontology into conversation with scholarship on information and data technologies within critical disability, race, and feminist studies and explore algorithmic harms of surveillance technologies on older adults and care workers within nursing homes in the United States and Canada. We start by identifying the limitations of emerging scholarship and public discourse on "digital ageism" that is occupied with the inclusion and representation of older adults in AI or machine learning at the expense of more pressing questions. Focusing on the investment in these technologies in the context of COVID-19 in nursing homes, we draw from critical scholarship on information and data technologies to deeply understand how ageism is implicated in the systemic harms experienced by residents and workers when surveillance technologies are positioned as solutions. We then suggest generative pathways and point to various possible research agendas that could illuminate emergent algorithmic harms and their animating force within nursing homes. In the tradition of critical gerontology, ours is a project of bringing insights from gerontology and age studies to bear on broader work on automation and algorithmic decision-making systems for marginalized groups, and to bring that work to bear on gerontology. This paper illustrates specific ways in which important insights from critical race, disability and feminist studies helps us draw out the power of ageism as a rhetorical and analytical tool. We demonstrate why such engagement is necessary to realize gerontology's capacity to contribute to timely discourse on algorithmic harms and to elevate the issue of ageism for serious engagement across fields concerned with social and economic justice. We begin with nursing homes because they are an understudied, yet socially significant and timely setting in which to understand algorithmic harms. We hope this will contribute to broader efforts to understand and redress harms across sectors and marginalized collectives.

Predicting age and gender from network telemetry: Implications for privacy and impact on policy

The systematic monitoring of private communications through the use of information technology pervades the digital age. One result of this is the potential availability of vast amount of data tracking the characteristics of mobile network users. Such data is becoming increasingly accessible for commercial use, while the accessibility of such data raises questions about the degree to which personal information can be protected. Existing regulations may require the removal of personally-identifiable information (PII) from datasets before they can be processed, but research now suggests that powerful machine learning classification methods are capable of targeting individuals for personalized marketing purposes, even in the absence of PII. This study aims to demonstrate how machine learning methods can be deployed to extract demographic characteristics. Specifically, we investigate whether key demographics—gender and age—of mobile users can be accurately identified by third parties using deep learning techniques based solely on observations of the user’s interactions within the network. Using an anonymized dataset from a Latin American country, we show the relative ease by which PII in terms of the age and gender demographics can be inferred; specifically, our neural networks model generates an estimate for gender with an accuracy rate of 67%, outperforming decision tree, random forest, and gradient boosting models by a significant margin. Neural networks achieve an even higher accuracy rate of 78% in predicting the subscriber age. These results suggest the need for a more robust regulatory framework governing the collection of personal data to safeguard users from predatory practices motivated by fraudulent intentions, prejudices, or consumer manipulation. We discuss in particular how advances in machine learning have chiseled away a number of General Data Protection Regulation (GDPR) articles designed to protect consumers from the imminent threat of privacy violations.

Moving towards the promise of participatory engagement of older adults in gerotechnology

Limited uptake and use of developed technologies by older adults have prompted interest in participatory design and related approaches in the gerotechnology field. Despite this, recent systematic reviews suggest that researchers continue to passively engage older adults in research projects, often only providing advice or feedback in the early or later phases of research. A key barrier to more meaningful and active engagement of older adults is a lack of understanding as to how participatory design differs from other participatory approaches, and in particular, participatory action research. We address this gap in understanding by exploring the theoretical similarities and differences of participatory design and participatory action research, including their scope, goals, and the nature of the involvement of older adults in each. We conclude with key barriers that are critical to address in order to achieve greater involvement of older adults in gerotechnology and to broaden and enrich the goals of this field.

Factors Affecting the Implementation, Use, and Adoption of Real-Time Location System Technology for Persons Living With Cognitive Disabilities in Long-term Care Homes: Systematic Review

BACKGROUND

As the aging population continues to grow, the number of adults living with dementia or other cognitive disabilities in residential long-term care homes is expected to increase. Technologies such as real-time locating systems (RTLS) are being investigated for their potential to improve the health and safety of residents and the quality of care and efficiency of long-term care facilities.

OBJECTIVE

The aim of this study is to identify factors that affect the implementation, adoption, and use of RTLS for use with persons living with dementia or other cognitive disabilities in long-term care homes.

METHODS

We conducted a systematic review of the peer-reviewed English language literature indexed in MEDLINE, Embase, PsycINFO, and CINAHL from inception up to and including May 5, 2020. Search strategies included keywords and subject headings related to cognitive disability, residential long-term care settings, and RTLS. Study characteristics, methodologies, and data were extracted and analyzed using constant comparative techniques.

RESULTS

A total of 12 publications were included in the review. Most studies were conducted in the Netherlands (7/12, 58%) and used a descriptive qualitative study design. We identified 3 themes from our analysis of the studies: barriers to implementation, enablers of implementation, and agency and context. Barriers to implementation included lack of motivation for engagement; technology ecosystem and infrastructure challenges; and myths, stories, and shared understanding. Enablers of implementation included understanding local workflows, policies, and technologies; usability and user-centered design; communication with providers; and establishing policies, frameworks, governance, and evaluation. Agency and context were examined from the perspective of residents, family members, care providers, and the long-term care organizations.

CONCLUSIONS

There is a striking lack of evidence to justify the use of RTLS to improve the lives of residents and care providers in long-term care settings. More research related to RTLS use with cognitively impaired residents is required; this research should include longitudinal evaluation of end-to-end implementations that are developed using scientific theory and rigorous analysis of the functionality, efficiency, and effectiveness of these systems. Future research is required on the ethics of monitoring residents using RTLS and its impact on the privacy of residents and health care workers.