@article {WilsonA8, author = {Sarah Wilson}, title = {12 Usability and acceptability of wearable technology in the early detection of dementia}, volume = {29}, number = {Suppl 1}, pages = {A8--A8}, year = {2022}, doi = {10.1136/bmjhci-2022-FCIASC.12}, publisher = {BMJ Specialist Journals}, abstract = {Objective Digital technology is transforming health and social care. Digital technologies, which includes smartphones and wearables, can be used to predict, diagnose, monitor, and/or develop treatments for different diseases. These technologies also have the potential to detect markers of neurodegenerative diseases at a much early stage than is currently possible.The Early Detection of Neurodegeneration (EDoN) initiative aims to use digital technologies to detect preclinical dementia, with aspirations to validate a digital toolkit for clinical practice. To enhance its development, we aimed to assess the usability and acceptability of the EDoN toolkit in people with cognitive impairments and their careers.Methods Various UK-based networks such as Join dementia research were used to recruit participants.The EDoN toolkit, which includes a smartwatch (Fitbit Charge 4),EEG headband (Dreem 3), and two smartphone applications (Longevity and Mezurio), was sent to each participant. University ethical approval was obtained (2135/12893/2020). Written and video guides were provided to support participants{\textquoteright} when using the toolkit. Participants{\textquoteright} initial perspectives of the toolkit and experiences of the setup process were explored through an initial interview, conducted approximately three days after receiving the devices. Follow-up interviews were conducted two weeks later to explore the acceptability and usability of the toolkit. NVivo enabled the thematic analysis of the interview transcripts. Emerging themes were discussed and refined by the research group.Results Sixteen semi-structured interviews were conducted with nine participants, at two-time points. Four participants had mild cognitive impairment, two had frontotemporal dementia, one had Alzheimer{\textquoteright}s disease and two were carers.Key themes were identified and centre around usability, acceptability, and inequity. Sub-themes within usability included the utility of the toolkit, experiences of setting up the devices, comfort of the wearables, and preference towards the written guides over the video guides, especially amongst those {\textquoteleft}who don{\textquoteright}t like technology{\textquoteright} (P3) and {\textquoteleft}prefer instruction booklets rather than go backward and forwards online{\textquoteright}(P1). In terms of acceptability, participants appeared to show a greater acceptance for familiar devices (e.g., previously worn a fitbit) and an initial hesitancy for the EEG Headband as it looked {\textquoteleft}cumbersome{\textquoteright}(P3). They described the importance of understanding how the device worked and obtaining feedback for {\textquoteleft}personal interest{\textquoteright} (P4), and raised fears around the implications of a high score in practice, with their {\textquoteleft}driving license being taken{\textquoteright}(P3) . Various inequities of the toolkit were uncovered such as a lack of accessibility to compatible phones and Wi-Fi connection, {\textquoteleft}sore patches{\textquoteright} (P6) caused by the wearables amongst individuals with dermatological issues, and digital exclusion regarding poor digital literacy and the view that technology is {\textquoteleft}alien{\textquoteright}(P6).Conclusion These results highlight that the EDoN toolkit was usable amongst only some individuals with cognitive impairments and their carers. Feedback on product acceptability and usability will be fed back to developers to help improve the different devices. Future work is needed to increase the inclusivity of the EDoN toolkit to support health equity and to reduce the stigma surrounding dementia.}, URL = {https://informatics.bmj.com/content/29/Suppl_1/A8.1}, eprint = {https://informatics.bmj.com/content/29/Suppl_1/A8.1.full.pdf}, journal = {BMJ Health \& Care Informatics} }