Reliability and acceptability of using a social robot to carry out cognitive tests for community‐dwelling older adults

Takaeda, Kana; Kamimura, Tomoko; Inoue, Takenobu; Nishiura, Yuko

doi:10.1111/ggi.13655

Cited by 5 publications

(4 citation statements)

References 24 publications

(27 reference statements)

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“…This enhanced telepresence robot, as assessed by users for its suitability for supporting social interaction and providing motivational feedback on health-related aspects, was judged to be usable and interactively pleasing [37]. It is thus not surprising that a robot-administered cognitive testing has been well accepted by community-dwelling older adults [38]. Contrary to expectations, older people seem to accept and respond well to the use of these novel enabling technologies for remote assistance, social communication and medical care, highlighting the importance of incorporating their needs and preferences in developing effective technological solutions.…”

Section: Assisted Technology In Geriatric Care and Rehabilitation: Romentioning

confidence: 99%

Artificial Intelligence in the healthcare of older people

Makaetova-Ladinska¹,

Harwood²,

Maltby³

2020

Arch Psychiatr Ment Health

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Clinical applications of Artifi cial Intelligence (AI) in healthcare are relatively rare. The high expectations in relation to data analysis infl uencing general healthcare have not materialized, with few exceptions, and then predominantly in the fi eld of rare diseases, oncology and pathology, and interpretation of laboratory results. While electronic health records, introduced over the last decade or so in the UK have increased access to medical and treatment histories of patients, diagnoses, medications, treatment plans, immunization dates, allergies, radiology images, laboratory and test results, these have potential for evidence-based tools that providers can use to make decisions about a patient's care, as well as streamline workfl ow. In the following text, we review the advances achieved using machine learning and deep learning technology, as well as robot use and telemedicine in the healthcare of older people. Key points: 1. Artifi cial Intelligence use is extensively explored in prevention, diagnosis, novel drug designs and after-care. 2. AI studies on older adults include a small number of patients and lack reproducibility needed for their wider clinical use in different clinical settings and larger populations. 3. Telemedicine and robot assisted technology are well received by older service users. 4. Ethical concerns need to be resolved prior to wider AI use in routine clinical setting. seem to face a number of barriers in contacting communitybased primary health care, such as limited access, lack of standardized information systems and care pathways [3], all necessary to address their complex health care and social care needs. Indeed, older adults have much higher prevalence of nearly all major chronic and long-term conditions. In addition, they are more likely to succumb to adverse health events, such as a falls or infections, and these can lead to dramatic changes in their physical and mental wellbeing even after an apparently minor incident [4]. However, person and familyfocused care, self-management resources, and successful collaborative practice have been all highlighted as facilitators of good health care provision both by older people and their families [3]. All the above places the importance of diagnosis, monitoring of disease risks and their prevention, as well as management and optimizing of geriatric syndromes in the community for both older people living independenly or in 24h care facilities. In particular, identi ication of health issues/ diagnosis, support/treatment needs evaluation, development

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Section: Assisted Technology In Geriatric Care and Rehabilitation: Romentioning

confidence: 99%

Artificial Intelligence in the healthcare of older people

Makaetova-Ladinska¹,

Harwood²,

Maltby³

2020

Arch Psychiatr Ment Health

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“…This study used a short cognitive task of language fluency, as well as a more narrative speech task, and is a helpful indicator of the likely acceptability of collecting speech biomarkers on the phone. Automated testing in the form of social robot administration and smartphone applications have previously been reported to be most feasible and acceptable to participants (Takaeda et al, 2019 ; Taylor et al, 2023 ), although in-person human cognitive testing remains mainstream in most clinical and research settings. The recent paradigm shift to digital neuropsychology warrants consideration from validity and ethical perspectives.…”

Section: Introductionmentioning

confidence: 99%

Remote data collection speech analysis in people at risk for Alzheimer's disease dementia: usability and acceptability results

Gregory,

Harrison,

Herrmann

et al. 2023

Front. Dement.

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IntroductionDigital cognitive assessments are gathering importance for the decentralized remote clinical trials of the future. Before including such assessments in clinical trials, they must be tested to confirm feasibility and acceptability with the intended participant group. This study presents usability and acceptability data from the Speech on the Phone Assessment (SPeAk) study.MethodsParticipants (N = 68, mean age 70.43 years, 52.9% male) provided demographic data and completed baseline and 3-month follow-up phone based assessments. The baseline visit was administered by a trained researcher and included a spontaneous speech assessment and a brief cognitive battery (immediate and delayed recall, digit span, and verbal fluency). The follow-up visit repeated the cognitive battery which was administered by an automatic phone bot. Participants were randomized to receive their cognitive test results acer the final or acer each study visit. Participants completed acceptability questionnaires electronically acer each study visit.ResultsThere was excellent retention (98.5%), few technical issues (n = 5), and good interrater reliability. Participants rated the assessment as acceptable, confirming the ease of use of the technology and their comfort in completing cognitive tasks on the phone. Participants generally reported feeling happy to receive the results of their cognitive tests, and this disclosure did not cause participants to feel worried.DiscussionThe results from this usability and acceptability analysis suggest that completing this brief battery of cognitive tests via a telephone call is both acceptable and feasible in a midlife-to-older adult population in the United Kingdom, living at risk for Alzheimer's disease.

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“…For older adults, assessments mediated by robots with sociability are more enjoyable and accessible than other remote assessment methods [11]. Growing evidence suggests that it is feasible to implement cognitive assessments (traditionally conducted by human experimenters) using social robots and to collect data via human-robot interaction (HRI) by targeting older adults and those with mild cognitive impairment [12] for robot-administered screening for global cognitive functions [13,14].…”

Section: Introductionmentioning

confidence: 99%

Social Robots for Evaluating Attention State in Older Adults

Chen

Yeh

Huang

et al. 2021

Sensors

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Sustained attention is essential for older adults to maintain an active lifestyle, and the deficiency of this function is often associated with health-related risks such as falling and frailty. The present study examined whether the well-established age-effect on reducing mind-wandering, the drift to internal thoughts that are seen to be detrimental to attentional control, could be replicated by using a robotic experimenter for older adults who are not as familiar with online technologies. A total of 28 younger and 22 older adults performed a Sustained Attention to Response Task (SART) by answering thought probes regarding their attention states and providing confidence ratings for their own task performances. The indices from the modified SART suggested a well-documented conservative response strategy endorsed by older adults, which were represented by slower responses and increased omission errors. Moreover, the slower responses and increased omissions were found to be associated with less self-reported mind-wandering, thus showing consistency with their higher subjective ratings of attentional control. Overall, this study demonstrates the potential of constructing age-related cognitive profiles with attention evaluation instruction based on a social companion robot for older adults at home.

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Reliability and acceptability of using a social robot to carry out cognitive tests for community‐dwelling older adults

Cited by 5 publications

References 24 publications

Artificial Intelligence in the healthcare of older people

Artificial Intelligence in the healthcare of older people

Remote data collection speech analysis in people at risk for Alzheimer's disease dementia: usability and acceptability results

Social Robots for Evaluating Attention State in Older Adults

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