Examining public acceptance of AI versus human-centric dementia care across NHS England's dementia pathway stages
O'Fee, T.; Vijaykumar, S.; Craig, M.
Show abstract
With dementia diagnoses in the UK projected to exceed one million in 2025, there is an urgent need for scalable and effective care solutions to ease pressure on health and social care systems. Artificial Intelligence (AI)-enabled smart home systems are emerging as promising digital health innovations, offering cognitive support, real-time monitoring, and decision-making assistance. However, concerns around trust, user agency, and misconceptions about AI continue to limit acceptance and may hinder adoption. This study examined how stage of dementia care, system design, and level of system involvement shape public attitudes towards AI-driven care technologies. A repeated-measures design was employed, using vignettes that varied across three dimensions: stage of care (aligned with NHS Englands Dementia Well Pathway), system centrism (AI-based versus human-based), and level of involvement (moderate support versus full control). Participants aged 55-64 years - a group at elevated risk of developing dementia or encountering these technologies within the next decade - rated each scenario on both acceptability and likelihood of use. Findings showed that acceptability was sensitive to both care stage and system type. A significant interaction indicated that full human involvement was consistently rated as more acceptable, while AI involvement was viewed more favourably only at moderate levels. This interaction effect intensified across the dementia care pathway, with the largest discrepancies observed in later stages such as Living well and Dying well, where full-control AI was rated least acceptable. In terms of perceived likelihood, scenarios were generally judged more likely under conditions of moderate involvement, with human-centric scenarios rated as more likely than AI-centric ones, particularly in later stages. These results highlight the importance of trust, autonomy, and public understanding in AI adoption. Acceptance was highest when AI was positioned to augment rather than replace human input, supporting hybrid models that preserve agency while enhancing scalability. Author SummaryDementia diagnoses are increasing rapidly, creating an urgent need for innovative care solutions. Artificial Intelligence (AI) and AI-integrated smart-homes offer a promising way to provide cognitive care and support through remote monitoring, but public trust and acceptance remain a challenge. Here, we explored peoples affective attitudes towards AI for dementia care by presenting scenarios that varied based on stage of dementia (from preventative to end-of-life care), whether the system was AI or human-based, and the level of control the system had over the care (moderate or full). We surveyed a sample of older adults, a group of potential future users of this technology. Our findings show that peoples attitudes are highly dependent on factors such as stage of care, level of system control/involvement, and system centricity, human-centric systems were consistently rated as the most acceptable option, while AI was most favourable when offering moderate support rather than taking full control. This preference for human-centric, moderate support grew stronger in the later stages of dementia care. In summary, people are more open to adopting AI when it is used to enhance human care, rather than replace it. This suggests that hybrid healthcare models, where AI is used to support and supplement caregivers, will be the most effective way to integrate these scalable technologies into dementia care.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Top-funded digital health companies offering lifestyle interventions for dementia prevention: Company overview and evidence analysis 93%
- Aging in Place - A mixed methods study protocol of how care providers in Sweden organise and adapt granted home care services to the preferences and needs of people living with dementia 92%
- Intentional and unintentional non-adherence to social distancing measures during COVID-19: A mixed-methods analysis 92%
Similar papers in this journal
- Variation in real world dementia risk profiles in 6171 adults drawn from the Australian CogDrisk website according to demographic characteristics 91%
- Acceptability and feasibility of strategies to shield the vulnerable during the COVID-19 outbreak: a qualitative study in six Sudanese communities 91%
- The impact of the COVID-19 pandemic on mental health and well-being of people living with a long-term physical health condition: a qualitative study 90%
Similar papers in this journal
- How, Why And Under What Circumstances Does A Quality Improvement Collaborative Build Knowledge And Skills In Clinicians Working With People With Dementia? A Realist Informed Process Evaluation 93%
- Exploring the potential of geospatial mapping of emergency call data to improve ambulance services for older adults: a feasibility study in the South Central region of England 91%
- Improving local authority financial support services for users with complex health needs: a mixed-method economic evaluation of Social Navigators in South Tyneside, UK 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.