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Attitudes of people living with dementia and their carers towards the use of generative artificial intelligence to inform structured medication reviews

Year: 2026
Type: article
Abstract: BACKGROUND: Polypharmacy is common in people living with dementia (PLwD) and associated with adverse outcomes. Although Structured Medication Reviews (SMRs) are recommended to optimise medication regimens, their delivery is often constrained by limited resources. Artificial intelligence (AI) may support SMRs, yet little is known about how it is perceived by PLwD and their carers. This study explored their experiences of polypharmacy, views on SMRs and attitudes towards use of AI tools in SMRs. METHODS: Semi-structured interviews with 12 PLwD experiencing polypharmacy and two focus groups with 14 carers were conducted via Microsoft Teams or telephone and analysed using Reflexive Thematic Analysis. RESULTS: Two themes were constructed: participants' perspectives on meaningful SMRs, and embracing AI while preserving patient safety and the human touch. Participants described challenges in managing polypharmacy, with carers playing a central role in supporting adherence and monitoring side effects. Experiences of SMRs varied. SMRs were most valued when clinicians were empathetic and able to offer personalised guidance. Participants viewed AI use in SMRs positively, provided that such tools were well validated and used to assist rather than replace healthcare professionals. AI was also seen as potentially reducing administrative burden and supporting more person-centred care. However, some had concerns regarding patient safety and data security, highlighting the need for appropriate regulation and human oversight. CONCLUSION: Participants were supportive of AI use in SMRs, despite concerns about safety, data security and disclosure of AI use, and emphasised the importance of patient-clinician interactions and lived experience involvement in AI tool development.
Language: English
Field: Medicine
Open Access status: hybrid
Estimated APC paid: $3,699
OpenAlex ID: W7167028431
FWCI:
Cites: 44
Cited by:
Related to: 10