Age-Related Differences in Preferences for Using Voice Assistants

Gollasch, David; Weber, Gerhard

doi:10.1145/3473856.3473889

Cited by 10 publications

(8 citation statements)

References 26 publications

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“…Additionally, the system should clearly indicate that the usage of a CA-based system for CBT is not intended as a replacement for face-to-face therapy with mental health specialists [18]. Furthermore, as the system is intended for elderly users, guidelines for the design of VUIs for elderly people have to be taken into account [19,37]. Based on related research, three CBT tools were identifed as suitable for a VA-based CBT session: A mood journal [11], a radio play with multiple choice questions as a psycho educational component [27,40], and a short meditation practice to end the session [21,31].…”

Section: Design and Prototype Of A Va For Cbt Deliverymentioning

confidence: 99%

Investigating the Usability of Voice Assistant-Based CBT for Age-Related Depression

Striegl

Gotthardt

Loitsch

et al. 2022

Lecture Notes in Computer Science

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To combat the global shortage of mental health services, new solutions - such as computerized therapy options - have to be found. While research in this field has been ongoing for several decades and approaches such as chatbot-based cognitive behavioral therapy (CBT) have already shown to be effective in reducing symptoms of depression for younger adults, voice assistant-based (VA-based) approaches have thus far not been investigated deeply. However, especially for elderly people with depression VA-based systems could yield benefits - such as the avoidance of physical accessibility issues. Therefore, we propose the design of a VA-based system capable of delivering selected methods from CBT to elderly users with depression in order to investigate its usability. To assess the usability of the conceptualized system in comparison to a chatbot-based approach we conducted a randomized controlled A/B testing experiment with 14 participants. Results indicate a good usability and acceptance of the designed system and a preference for the delivery of CBT-methods via voice assistant rather than via chatbot, especially among elderly participants.

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Section: Design and Prototype Of A Va For Cbt Deliverymentioning

confidence: 99%

Investigating the Usability of Voice Assistant-Based CBT for Age-Related Depression

Striegl

Gotthardt

Loitsch

et al. 2022

Lecture Notes in Computer Science

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“…The resulting findings contribute to the existing research on conversational agents and older adults [5][6][7][16][17][18][19] by addressing the importance of participatory design in developing conversational agents that can be adaptive to older adults' needs, interests and preferences, and recognising participants' own perceptions and experiences in the interaction with multi-modal CAs. Furthermore, this study advances participatory design with older adults [10,11] by focusing on voice interaction in particular, and qualitative analysis of both video recordings and semi-structured interviews [8,9,19].…”

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confidence: 83%

“…Prior studies have shown that older adults perceive conversational interfaces as easier to use and learn in comparison to traditional computing devices, which indicates that conversational interfaces can improve the accessibility of digital technology [5][6][7][16][17][18]. Older adults use conversational agents most commonly to seek information related to topics of health, local businesses, and food and drink [6].…”

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confidence: 99%

“…Older adults use conversational agents most commonly to seek information related to topics of health, local businesses, and food and drink [6]. Research has covered technical requirements for voice-based interaction with older adults [7], but less is known about older adults' own preferences for certain types of conversation, such as what kind of information older adults perceive as suitable topics and in what way an agent should approach them.…”

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confidence: 99%

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Designing Multi-Modal Conversational Agents for the Kitchen with Older Adults: A Participatory Design Study

Kuoppamäki,

Jaberibraheem,

Hellstrand

et al. 2023

Int J of Soc Robotics

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Conversational agents (CA) are increasingly used to manage and coordinate household chores and everyday activities at home. However, these technologies should be adaptive to age-specific characteristics in order to be considered beneficial for the ageing population. This study presents a participatory design of a conversational agent to provide cognitive support in recipe following and nutrition advice for adults aged 65 and over. Through a qualitative thematic analysis, the study explores older adults’ expectations, interactions and experiences with the agent in order to identify age-specific challenges of interacting with CAs. Data consists of a participatory design workshop with eight older adults (aged 65 and over), followed by a Wizard of Oz study with ten older adults interacting with the agent in the kitchen environment in a laboratory setting. Results demonstrate that older adults consider conversational agents as beneficial for providing personalised recipe recommendations, advising the user to choose appropriate ingredients and reminding them of their dietary intake. When interacting with the agent older adults displayed challenges with confirmation and repetition, questioning and correcting, the lack of conversational responses, and difficulties in hearing and understanding the multi-modal interaction. Older adults experience agents as collaborators, but not as conversational partners. The study concludes that the accessibility and inclusiveness of conversational agents regarding voice interaction could be improved by further developing participatory methods with older adults.

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“…Gollasch and Weber [28] identified age-specific strategies in dialogue systems and speech recognition accuracy. To respond to the needs of older adults, conversational agents should be able to correctly recognize even unusual formulations; complex dialogues comprising multiple pieces of information should be presented as simple or guided dialogues; agent should ask only one question per dialogue with a limited set of possible answers; it should be able to keep information about the conversation context; and so on.…”

Section: Socially Assistive Robots In Elderly Carementioning

confidence: 99%

Between Reality and Delusion: Challenges of Applying Large Language Models to Companion Robots for Open-Domain Dialogues with Older Adults

Irfan

Kuoppamäki

Skantze

2023

Preprint

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This work aims to provide initial guidelines towards developing companion robots with large language models (LLMs) to be part of everyday lives of older adults. Using iterative participatory design (co-design) approaches, we analyze the challenges of applying LLMs for multi-modal open-domain dialogue, deriving from older adults' (one-to-one) interactions with a personalized companion robot, built on Furhat robot with GPT-3.5. An initial study with 6 Swedish-speaking older adults (65 and older) showed that the robot frequently interrupted the users, responded slowly and repetitively, engaged in superficial conversations, and caused a barrier in the interaction due to foreign language (English). Upon incremental technical developments to address these issues, participatory design workshops were conducted with 28 Swedish-speaking older adults. While the interactions (in Swedish) were smoother, less disrupted, and more varied in topics and responses, further challenges were observed due to hallucinations and obsolete information, and disengagement cues, causing frustration, confusion, and worry.

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Age-Related Differences in Preferences for Using Voice Assistants

Cited by 10 publications

References 26 publications

Investigating the Usability of Voice Assistant-Based CBT for Age-Related Depression

Investigating the Usability of Voice Assistant-Based CBT for Age-Related Depression

Designing Multi-Modal Conversational Agents for the Kitchen with Older Adults: A Participatory Design Study

Between Reality and Delusion: Challenges of Applying Large Language Models to Companion Robots for Open-Domain Dialogues with Older Adults

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