Methods and baseline characteristics for a social engagement technology-based randomized controlled trial for older adults.

Background: Growing evidence suggests that increasing opportunities for social engagement has the potential to support successful aging. However, many older adults may have limited access to in-person social engagement opportunities due to barriers such as transportation. We outline the development, design, methodology, and baseline characteristics of a randomized controlled trial that assessed the benefits of a social engagement intervention delivered through the OneClick video conferencing platform to older adults with varying levels of cognitive functioning. Methods: Community-dwelling older adults with and without cognitive challenges were randomly assigned to a social engagement intervention group or a waitlist control group. Participants were asked to attend twice-weekly social engagement events for 8 weeks via OneClick. Outcomes included social engagement and technology acceptance for both groups at baseline, week-4, and week-8 assessments. As an extension, the waitlist control group had an opportunity to participate in the intervention, with outcomes assessed at weeks 12 and 16. Results: We randomly assigned 99 participants (mean age = 74.1 ± 6.7, range: 60-99), with 50 in the immediate intervention group and 49 in the waitlist control group. About half of the participants reported living alone (53.5%), with a third (31%) falling into the cognitively impaired range on global cognitive screening. The groups did not differ at baseline on any of the outcome measures. Conclusions: Outcomes from this study will provide important information regarding the feasibility and efficacy of providing technology-based social engagement interventions to older adults with a range of cognitive abilities.

The Benefits of Technology for Engaging Aging Adults: Findings From the PRISM 2.0 Trial.

Background and Objectives: Technology has potential for providing support for aging adults. This study evaluated the Personal Reminder Information and Social Management 2.0 (PRISM 2.0) software, in terms of enhancing social engagement and quality of life, and decreasing loneliness among older adults. Research Design and Methods: The randomized field trial conducted in diverse living contexts (rural locations, senior housing, and assisted living communities [ALC]). Two hundred and forty-five adults, aged 64 to 99 years, were randomly assigned to the PRISM 2.0 (integrated software system designed for aging through an iterative design process) or a Standard Tablet (without PRISM) Control condition, where participants received the same amount of contact and training as those in the PRISM 2.0 condition. Primary outcomes included measures of loneliness, social support, social connectedness, and quality of life. Secondary outcomes included measures of social isolation, mobile device proficiency, and technology readiness. Data were collected at baseline and 6 and 9 months postrandomization. This article focuses on the 6-month outcomes due to coronavirus disease 2019-related data challenges at 9 months. Results: Contrary to our hypothesis, participants in rural locations and senior housing in both conditions reported less loneliness and social isolation, and greater social support and quality of life at 6 months, and an increase in mobile device proficiency. Participants in the ALCs in both conditions also evidenced an increase in mobile device proficiency. Improvements in quality of life and health-related quality of life were associated with decreases in loneliness. Discussion and Implications: This study provides compelling evidence about the benefits of technology for older adults in terms of enhancing social outcomes and quality of life. However, the findings also underscore that for technology applications to be successful, they need to be adapted to the abilities and needs of the user group and instructional support needs to be provided. Clinical Trials Registration #: NCT03116399.

Cost-Related Non-Adherence to Prescribed Medicines: What Are Physicians' Moral Duties?

As the price of pharmaceuticals and biologicals rises so does the number of patients who cannot afford them. In this article, we argue that physicians have a moral duty to help patients access affordable medicines. We offer three grounds to support our argument: (i) the aim of prescribing is to improve health and well-being which can only be realized with secure access to treatment; (ii) there is no morally significant difference between medicines being unavailable and medicines being unaffordable, so the steps physicians are willing to take in the first case should extend to the second; and (iii) as the primary stakeholder with a duty to put the individual patient's interests first, the medical professional has a duty to address cost-barriers to patient care. In articulating this duty, we take account of important epistemic and control conditions that must be met for the attribution of this duty to be justified.

How should artificial intelligence be used in Australian health care? Recommendations from a citizens' jury.

OBJECTIVE: To support a diverse sample of Australians to make recommendations about the use of artificial intelligence (AI) technology in health care. STUDY DESIGN: Citizens' jury, deliberating the question: "Under which circumstances, if any, should artificial intelligence be used in Australian health systems to detect or diagnose disease?" SETTING, PARTICIPANTS: Thirty Australian adults recruited by Sortition Foundation using random invitation and stratified selection to reflect population proportions by gender, age, ancestry, highest level of education, and residential location (state/territory; urban, regional, rural). The jury process took 18 days (16 March - 2 April 2023): fifteen days online and three days face-to-face in Sydney, where the jurors, both in small groups and together, were informed about and discussed the question, and developed recommendations with reasons. Jurors received extensive information: a printed handbook, online documents, and recorded presentations by four expert speakers. Jurors asked questions and received answers from the experts during the online period of the process, and during the first day of the face-to-face meeting. MAIN OUTCOME MEASURES: Jury recommendations, with reasons. RESULTS: The jurors recommended an overarching, independently governed charter and framework for health care AI. The other nine recommendation categories concerned balancing benefits and harms; fairness and bias; patients' rights and choices; clinical governance and training; technical governance and standards; data governance and use; open source software; AI evaluation and assessment; and education and communication. CONCLUSIONS: The deliberative process supported a nationally representative sample of citizens to construct recommendations about how AI in health care should be developed, used, and governed. Recommendations derived using such methods could guide clinicians, policy makers, AI researchers and developers, and health service users to develop approaches that ensure trustworthy and responsible use of this technology.

Translation of a Successful Behavioral Intervention to a Digital Therapeutic Self-Management System for Older Adults.

Feature at a Glance: Nonadherence to hypertension medications is associated with negative health outcomes, which is of particular importance for older adults because of the high prevalence of hypertension in this population. To promote medication adherence among this group, we translated a behavioral intervention that improved adherence by 36% into a digital therapeutic self-management system. Design strategies included interviewing older adults, conducting usability evaluations after each iteration, and engaging a team of experts from nursing, cognitive psychology, pharmacy, human factors in aging, and software development. We outline our design process that can guide translation of other behavioral interventions into digital therapeutic platforms.

Best practices for implementing a technology-based intervention protocol: Participant and researcher considerations.

Technology-based interventions present a promising approach to support health and wellness for older adults with a range of cognitive abilities. Technology can enhance access to interventions and support scaling of programs to reach more people. However, the use of technology for intervention delivery requires particular attention to users' needs and preferences and ensuring the materials are adaptable and supportive of a diverse range of technology proficiency levels. We share best practices based on lessons learned from the deployment of a randomized controlled trial (RCT) wherein we delivered an 8-week social engagement intervention through a video technology platform called OneClick for older adults with varying cognitive abilities. We developed a set of best practices and guidelines informed by the lessons learned through this RCT implementation. Technology-based interventions require attention to the application (e.g., video calls), system requirements (e.g., system memory, broadband internet), training (e.g., adaptability based on user competency), and support (e.g., handouts, live contact). These best practices relate to user needs; training design; personnel responsibility; structuring delivery and content; and evaluating success. These research-based best practices can guide the design, development, and implementation of technology-based interventions to support older adults with varying cognitive abilities.

Immersive participatory design of assistive robots to support older adults.

Assistive robots have the potential to support independence, enhance safety, and lower healthcare costs for older adults, as well as alleviate the demands of their care partners. However, ensuring that these robots will effectively and reliably address end-user needs in the long term requires user-specific design factors to be considered during the robot development process. To identify these design factors, we embedded Stretch, a mobile manipulator created by Hello Robot Inc., in the home of an older adult with motor impairments and his care partner for four weeks to support them with everyday activities. An occupational therapist and a robotics engineer lived with them during this period, employing an immersive participatory design approach to co-design and customise the robot with them. We highlight the benefits of this immersive participatory design experience and provide insights into robot design that can be applied broadly to other assistive technologies.

Understanding Wheelchair Use in Older Adults From the National Health and Aging Trends Study.

OBJECTIVE: To identify the trends of wheelchair use and physical characteristics among older people who used wheelchairs relative to those who did not. DESIGN: Cohort and survey. SETTING: General community. PARTICIPANTS: 7026 participants (N=7026) were selected from the 2011 cohort of the National Health and Aging Trends Study (NHATS), which is made up of Medicare beneficiaries over the age of 65. Repeated observations among participants in the 2011 cohort were analyzed in the 4 following rounds: 2013 (N=4454), 2015 (N=3327), 2017 (N=2623), and 2019 (N=2091). Participants were divided into 2 groups: those who used and did not use wheelchairs. INTERVENTIONS: Not applicable. MAIN OUTCOMES MEASURES: Physical characteristics, including pain, strength limitation, balance problems, mobility disability, as well as the frequency of going outside. RESULTS: The number of older adults who use wheelchairs had increased significantly from 4.7 per 100 people in 2011 to 7.1 in 2019 (P<.001). The logistic regression analysis indicated that participants who reported less frequently going out were at least 4.27 times more likely to be wheelchair users than non-wheelchair users (P<.01). Participants who reported health and physical problems were at least 2.48 times more likely to be wheelchair users than non-wheelchair users from 2011 to 2017 (P<.0001). Balance or coordination problems increased (24%-38%) significantly among non-wheelchair users from 2011 to 2019 (all P<.05). CONCLUSIONS: Current wheelchair users reported more physical difficulties and were much less likely to go outside. This lower outdoor mobility could be due to physical difficulties or potential barriers in physical and socio-cultural environments. In addition, older adults who do not use wheelchairs showed increasing physical problems over time (including balance or coordination problems). Clinicians should consider older wheelchair users' health and physical limitations when prescribing wheelchairs.

Everyday Challenges for Individuals Aging With Vision Impairment: Technology Implications.

BACKGROUND AND OBJECTIVES: There are growing numbers of older adults with long-term vision impairment who are likely to experience everyday activity challenges from their impairment in conjunction with age-related changes. Technology has potential to support activity engagement. To develop effective technologies and interventions, we need to understand the context of activity challenges and identify unmet support needs. RESEARCH DESIGN AND METHODS: The Aging Concerns, Challenges, and Everyday Solution Strategies (ACCESS) study is a mixed-method approach to explore everyday challenges of people aging with long-term disabilities. Participants included 60 adults aging with long-term vision impairment (63% female; M age = 67, SD = 4.6) who completed in-depth, structured interviews exploring the nature of everyday challenges and their unmet support needs for activity engagement. We conducted a content analysis using a deductive and inductive approach to build a detailed coding scheme of challenge codes and subcodes. RESULTS: The analyses provided detailed insights about the nature of challenges people aging with vision impairment experience when performing specific instrumental activities of daily living (IADLs) in the context of home maintenance, transportation, shopping/finance, and managing health. Vision-related challenges and participation restrictions were identified for several activities that require reading, navigation, and identification (e.g., shopping, medication management, public transportation). Emergent challenge themes for performing IADLs included personal limitations (e.g., physical, cognitive, financial) and environmental barriers (e.g., accessibility, technology, transportation). DISCUSSION AND IMPLICATIONS: Contextual examples of IADL challenges among individuals aging with vision impairment highlight opportunities for technology design and innovation to support participation in everyday activities.

Scientists' Views on the Ethics, Promises and Practices of Synthetic Biology: A Qualitative Study of Australian Scientific Practice.

Synthetic biology is a broad term covering multiple scientific methodologies, technologies, and practices. Pairing biology with engineering, synbio seeks to design and build biological systems, either through improving living cells by adding in new functions, or creating new structures by combining natural and synthetic components. As with all new technologies, synthetic biology raises a number of ethical considerations. In order to understand what these issues might be, and how they relate to those covered in ethics literature on synbio, we conducted an interview study with practicing synthetic biologists affiliated with a synthetic biology centre in Australia. Scientists identified a range of ethical challenges germane to the field, including precarious employment, pressures from industry, gender inequity, and the negative effects of the hyping of synbio. These challenges differed markedly from those identified in the ethics literature, whose treatment of the harms and benefits of synbio remains largely speculative and abstract. In our discussion of the pragmatic, every day ethical issues synthetic biologists face, we illustrate how issues of waste or research integrity play pivotal roles in everything from lived experiences in the laboratory, to long-term research trajectories guiding the field. In a confirmation of the ethical relevance of our participant's views on the field, we argue that the subjects they raise must be included in any ethical analysis of synbio as a field.

The incidence of personal importation of prescription medicines among Australians 45 and older: a cross-sectional survey.

Objective This study is the first to investigate the incidence of personal importation of prescription medicines among Australians aged 45 years or older, and the reasons driving this behaviour. Methods An online survey was distributed to Australians, aged 45 years or older, who were taking prescription medicines. Recruitment was conducted via Qualtrics. The survey was completed by 1180 respondents. Results In our sample, 1.8% of respondents had imported prescription medicines in the previous 12 months, 21.9% had not taken, or had delayed taking, a prescribed medicine due to cost, 21.9% described medicines as unaffordable/very unaffordable, and 17.7% took some budgetary measure to pay for their medicines. The most significant predictors (P < 0.001) of importation were doctors raising it as an option (1.0% vs 42.9%), awareness of the Personal Importation Scheme (0.8% vs 22.6%), believing that importing was safe (1.6% vs 20.9%), paying more than the maximum PBS co-payment for any individual medicine (0.4% vs 8.1%), higher monthly spend on medicines (1.0% vs 6%), and delaying or not taking a medicine due to cost (0.9% vs 5.0%). Almost half (44.4%) would consider importing medicines to save money. Conclusions Potentially hundreds of thousands of Australians are importing prescription medicines from abroad, and many Australians indicate they are willing to import medicines to save money.

Australian women's judgements about using artificial intelligence to read mammograms in breast cancer screening.

Objective: Mammographic screening for breast cancer is an early use case for artificial intelligence (AI) in healthcare. This is an active area of research, mostly focused on the development and evaluation of individual algorithms. A growing normative literature argues that AI systems should reflect human values, but it is unclear what this requires in specific AI implementation scenarios. Our objective was to understand women's values regarding the use of AI to read mammograms in breast cancer screening. Methods: We ran eight online discussion groups with a total of 50 women, focused on their expectations and normative judgements regarding the use of AI in breast screening. Results: Although women were positive about the potential of breast screening AI, they argued strongly that humans must remain as central actors in breast screening systems and consistently expressed high expectations of the performance of breast screening AI. Women expected clear lines of responsibility for decision-making, to be able to contest decisions, and for AI to perform equally well for all programme participants. Women often imagined both that AI might replace radiographers and that AI implementation might allow more women to be screened: screening programmes will need to communicate carefully about these issues. Conclusions: To meet women's expectations, screening programmes should delay implementation until there is strong evidence that the use of AI systems improves screening performance, should ensure that human expertise and responsibility remain central in screening programmes, and should avoid using AI in ways that exacerbate inequities.

Developing a Healthcare Technology Acceptance Model (H-TAM) for Older Adults with Hypertension.

Older adults with a chronic health condition (e.g., hypertension) use various self-management methods. Healthcare technologies have the potential to support health self-management. However, it is necessary to understand the acceptance of these technologies as a precursor to older adults' adoption and integration into their health plan. Our focus was on the factors older adults with hypertension initially consider when introduced to three new healthcare technologies that might support their health self-management. We compared their considerations for a blood pressure monitor, an electronic pillbox, and a multifunction robot to simulate incrementally more complex technologies. Twenty-three participants (aged 65-84) completed four questionnaires and a semi-structured interview. The interview transcripts were analyzed using a thematic analysis approach. We identified the factors that were frequently mentioned among the participants for each of the three healthcare technologies. The factors that older adults initially considered were familiarity, perceived benefits, perceived ease of use, perceived need for oneself, relative advantage, complexity, and perceived need for others. Upon further reflection, participants considered advice acceptance, compatibility, convenience, facilitating conditions, perceived usefulness, privacy, subjective norm, and trust. We integrated the factors that older adults considered into the Healthcare Technology Acceptance Model (H-TAM), which elucidates the complexity of healthcare technology acceptance and provides guidance for future explorations.

Practical, epistemic and normative implications of algorithmic bias in healthcare artificial intelligence: a qualitative study of multidisciplinary expert perspectives.

BACKGROUND: There is a growing concern about artificial intelligence (AI) applications in healthcare that can disadvantage already under-represented and marginalised groups (eg, based on gender or race). OBJECTIVES: Our objectives are to canvas the range of strategies stakeholders endorse in attempting to mitigate algorithmic bias, and to consider the ethical question of responsibility for algorithmic bias. METHODOLOGY: The study involves in-depth, semistructured interviews with healthcare workers, screening programme managers, consumer health representatives, regulators, data scientists and developers. RESULTS: Findings reveal considerable divergent views on three key issues. First, views on whether bias is a problem in healthcare AI varied, with most participants agreeing bias is a problem (which we call the bias-critical view), a small number believing the opposite (the bias-denial view), and some arguing that the benefits of AI outweigh any harms or wrongs arising from the bias problem (the bias-apologist view). Second, there was a disagreement on the strategies to mitigate bias, and who is responsible for such strategies. Finally, there were divergent views on whether to include or exclude sociocultural identifiers (eg, race, ethnicity or gender-diverse identities) in the development of AI as a way to mitigate bias. CONCLUSION/SIGNIFICANCE: Based on the views of participants, we set out responses that stakeholders might pursue, including greater interdisciplinary collaboration, tailored stakeholder engagement activities, empirical studies to understand algorithmic bias and strategies to modify dominant approaches in AI development such as the use of participatory methods, and increased diversity and inclusion in research teams and research participant recruitment and selection.

Utopia versus dystopia: Professional perspectives on the impact of healthcare artificial intelligence on clinical roles and skills.

BACKGROUND: Alongside the promise of improving clinical work, advances in healthcare artificial intelligence (AI) raise concerns about the risk of deskilling clinicians. This purpose of this study is to examine the issue of deskilling from the perspective of diverse group of professional stakeholders with knowledge and/or experiences in the development, deployment and regulation of healthcare AI. METHODS: We conducted qualitative, semi-structured interviews with 72 professionals with AI expertise and/or professional or clinical expertise who were involved in development, deployment and/or regulation of healthcare AI. Data analysis using combined constructivist grounded theory and framework approach was performed concurrently with data collection. FINDINGS: Our analysis showed participants had diverse views on three contentious issues regarding AI and deskilling. The first involved competing views about the proper extent of AI-enabled automation in healthcare work, and which clinical tasks should or should not be automated. We identified a cluster of characteristics of tasks that were considered more suitable for automation. The second involved expectations about the impact of AI on clinical skills, and whether AI-enabled automation would lead to worse or better quality of healthcare. The third tension implicitly contrasted two models of healthcare work: a human-centric model and a technology-centric model. These models assumed different values and priorities for healthcare work and its relationship to AI-enabled automation. CONCLUSION: Our study shows that a diverse group of professional stakeholders involved in healthcare AI development, acquisition, deployment and regulation are attentive to the potential impact of healthcare AI on clinical skills, but have different views about the nature and valence (positive or negative) of this impact. Detailed engagement with different types of professional stakeholders allowed us to identify relevant concepts and values that could guide decisions about AI algorithm development and deployment.

Designing Feedback Visualizations for Anti-Hypertensive Medication Adherence for Older Adults.

Adhering to anti-hypertensive medications contributes to control of blood pressure and improved health outcomes. However, adherence rates among older adults are low. Patient monitoring of medication taking helps increase adherence and technology has great potential to support self-monitoring, in part by providing visual feedback about medication taking performance. However, little attention has been paid to designing feedback visualizations in medication-monitoring technology for older adults. In this research, we identified guidelines for designing understandable and effective adherence visualizations for older adults from existing theories and literature. With the guidelines in mind, we designed, refined, and evaluated visualizations that provided adherence feedback for a smartphone application with 17 older participants. Based on theory and evidence, we identified design guidelines for feedback visualizations. These guidelines can support design of useful feedback visualizations that may improve medication adherence among older adults.

Understanding Home Activities Challenges of Older Adults Aging with Long-term Mobility Disabilities: Recommendations for Home Environment Design.

As age-related changes progress, individuals with long-term mobility disabilities experience more challenges in engaging with everyday activities. This archival analysis identified common activity challenges older adults with long-term mobility disabilities report and the type of strategies they employed to respond to these challenges, using the interview data (n=60) from the ACCESS Study. We discovered that activity challenges come from intrinsic factors (i.e., mobility limitations, strength, health conditions) as well as extrinsic factors (transferring and physical access). With these challenges in mind, we constructed home environment design strategies that could meet the needs of people aging with mobility disabilities.