Advanced Assistive Technologies for Elderly People: A Psychological Perspective on Seniors’ Needs and Preferences (part A)

Troncone, Alda; Amorese, Terry; Cuciniello, Marialucia; Saturno, Raffaele; Pugliese, Luca; Cordasco, Gennaro; Vogel, Carl; Esposito, Anna

doi:10.12700/aph.17.2.2020.2.10

Cited by 23 publications

(22 citation statements)

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“…After daily use, the older adults might have realized that the content of ECAs' dialogues was not as extensive, smart and personal as they expected. Little personalization and inferior or stigmatized content seen as a threat to their autonomy, might have affected the older adults' satisfaction with the ECAs Panico et al, 2020;Troncone et al, 2020). Since the amount and the content of dialogues differed across the ECAs, this adaptation gap might have been larger for some ECAs than for others, which might have affected our results.…”

Section: Discussionmentioning

confidence: 94%

Look who's talking: appearance of embodied conversational agents in eHealth

Stal¹

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Section: Discussionmentioning

confidence: 94%

Look who's talking: appearance of embodied conversational agents in eHealth

Stal¹

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“…The full list of items and constructs used are reported in Appendix A , Table A1 . The AMQ was designed with the aim of being applicable to vulnerable people such as older adults [ 38 ]. The training evaluation was performed using the Training Evaluation Inventory (TEI) developed by Ritzmann et al [ 30 ].…”

Section: Pre-validation Methodology Of the Italian Systemmentioning

confidence: 99%

Design and Evaluation of Personalized Services to Foster Active Aging: The Experience of Technology Pre-Validation in Italian Pilots

Lorusso

Mosmondor

Grguric

et al. 2023

Sensors

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Assistive devices could promote independent living and support the active and healthy aging of an older population; however, several factors can badly influence the long-term use of new technologies. In this context, this paper presents a two-step methodology called “pre-validation” that aims to identify the factors that can bias the use of new services, thus minimizing the risk of an unsuccessful longer trial. The proposed pre-validation methodology is composed of two main phases that aim to assess the usability and the reliability of the technology assessed in a laboratory environment and the usability, acceptability, user experience, and reliability of the technology in real environments. The tested services include the socialization scenario, in which older adults are better connected to the community via technological solutions (i.e., socialization applications), and the monitoring scenario, which allows for the introduction of timely interventions (technologies involved include environmental monitoring sensors, a telepresence robot, wearable sensors, and a personalized dashboard). The obtained results underline an acceptable usability level (average System Usability Scale score > 65) for the tested technologies (i.e., socialization applications and a telepresence robot). Phase Two also underlines the good acceptability, user experience, and usability of the tested services. The statistical analysis underlines a correlation between the stress related to the use of technology, digital skills, and intention of use, among other factors. Qualitative feedback also remarks on a correlation between older adults with low digital skills and an anxiety about using technology. Positive correlation indexes were highlighted between the trust and usability scores. Eventually, future long-term trials with assistive technology should rely on motivated caregivers, be founded on a strong recruitment process, and should reassure older adults—especially the ones with low digital literacy—about the use of technology by proposing personalized training and mentoring, if necessary, to increase the trust.

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“…That is, older adults will not likely adopt a soft service robot when they fear that they will break something or make mistakes while using it or when they find it intimidating or scary (Fridin & Belokopytov, 2014;Heerink et al, 2010). Perceived likability refers to the degree to which one believes that a soft service robot is likable (Haring et al, 2016;Troncone et al, 2020). That is, older adults will likely adopt a soft service robot when they like its appearance, design, or look (Haring et al, 2016;Krägeloh, Bharatharaj, Kutty, Nirmala, & Huang, 2019;Mohammad & Nishida, 2015).…”

Section: Technology Acceptance Modelmentioning

confidence: 99%

Untitled

2020

THCI

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As the world's population increasingly ages, we need technological solutions such as robotics technology to assist older adults in their daily tasks. In this regard, we examine soft service robots' potential to help care for the elderly. To do so, we developed and tested the degree to which they would accept a soft service robot that catered to their functional needs in the home environment. We used embodied artificial to develop an in-house teleoperated human-sized soft service robot that performed object-retrieval tasks with a soft gripper. Using an extended technology acceptance model as a theoretical lens, we conducted a study with 79 older adults to examine the degree to which they would accept a soft service robot in the home environment. We found perceived ease of use, perceived usefulness, and subjective norms as significant predictors that positively influenced older adults' intention to adopt and use soft service robots. However, we also found that perceived anxiety and perceived likability did not significantly predict older adults' intention to adopt and use soft service robots. We discuss the implications, limitations, and future research directions that arise from these findings.

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Advanced Assistive Technologies for Elderly People: A Psychological Perspective on Seniors’ Needs and Preferences (part A)

Cited by 23 publications

References 0 publications

Look who's talking: appearance of embodied conversational agents in eHealth

Look who's talking: appearance of embodied conversational agents in eHealth

Design and Evaluation of Personalized Services to Foster Active Aging: The Experience of Technology Pre-Validation in Italian Pilots

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