Usability and Acceptance of the Embodied Conversational Agent Anne by People with Dementia and their Caregivers: an exploratory study in home environment settings (Preprint)
Bibliographic record
Abstract
BACKGROUND: Information and communication technologies are tools that are able to support cognitive functions, monitor health and movements, provide reminders to maintain residual memory abilities, and promote social support, especially among patients with dementia. Among these technologies, embodied conversational agents (ECAs) are seen as screen-based entities designed to stimulate human face-to-face conversation skills, allowing for natural human-machine interaction. Unfortunately, the evidence that such agents deliver care benefits in supporting people affected by dementia and their caregivers has not yet been well studied. Therefore, research in this area is essential for the entire scientific community. OBJECTIVE: This study aims to evaluate the usability and acceptability of the virtual agent Anne by people living with dementia. The study is also designed to assess the ability of target users to use the system independently and receive valuable information from it. METHODS: We conducted a 4-week trial that involved 20 older adults living with dementia and 14 family caregivers in home environment settings in Italy. This study used a mixed methods approach, balancing quantitative and qualitative instruments to gather data from users. Telemetry data were also collected. RESULTS: Older users were particularly engaged in providing significant responses and participating in system improvements. Some of them clearly discussed how technical problems related to speech recognition had a negative impact on the intention to use, adaptiveness, usefulness, and trust. Moreover, the usability of the system achieved an encouraging score, and half of the sample recognized a role of the agent Anne. This study confirms that the quality of automatic speech recognition and synthesis is still a technical issue and has room for improvement, whereas the touch screen modality is almost stable and positively used by patients with dementia. CONCLUSIONS: This study demonstrated the ability of target users to use the system independently in their home environment; overall, the involved participants shared good engagement with the system, approaching the virtual agents as a companion able to support memory and enjoyment needs. Therefore, this research provides data that sustain the use of ECAs as future eHealth systems that are able to address the basic and higher-level needs of people living with dementia. This specific field of research is novel and poorly discussed in the scientific community. This could be because of its novelty, yet there is an urgent need to strengthen data, research, and innovation to accelerate the implementation of ECAs as a future method to offer nonpharmacological support to community-dwelling people with dementia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".