Engaging Older Adults and Staff in the Co-Design and Evaluation of Socially Assistive Robot and Virtual Reality Activities for Long-Term Care: User-Centered Study
Bibliographic record
Abstract
BACKGROUND: Apathy is common among older adults residing in long-term care (LTC) and impairs quality of life for both older adults and care providers. Few pharmacological remedies exist, and nonpharmacologic approaches that engage those with apathy require extensive personnel time. Thus, technological approaches have been encouraged, including virtual reality (VR) and socially assistive robots (SAR). Despite a growing interest in their use, input from older adults and staff is often absent in their design. Involving older adults in the development of interactive health technologies is necessary to enhance the functionality, usability, and likelihood of promoting the intended health outcomes. OBJECTIVE: We aimed to design and evaluate SAR and nonimmersive VR (SAR-VR) activities for pairs of older adults that would encourage human-to-human interaction, an essential activity to mitigate apathy. METHODS: We implemented a multistep, user-centered design. A humanoid and dog SAR were used in combination with nonimmersive VR activities for pairs of older adults. An interdisciplinary team of engineers, nurses, and physicians collaborated with older adults and staff to create 4 activity prototypes, 3 with the humanoid robot and 1 with the dog robot. A total of 14 older adults at 2 sites participated in the design and evaluation of the different components of the system throughout all stages. Site 1 participants were instrumental in the development, and Site 2 participants validated the prototype activities. Data were collected at each session via observations, interviews, and a 6-item questionnaire that rated their degree of comfort and confidence in (1) using the wands, (2) interacting with the robot, and (3) interacting with the nonimmersive VR environment using a 5-point Likert response. Additionally, 5 staff from Site 2 were recruited to evaluate the ease of setting up and running the system at 2 different sessions. After each session, the system setup and interface were refined based on their feedback. RESULTS: A total of 4 of 6 older adults (mean age 85, SD 9.3 years; 2 male) at Site 1 completed field testing development, and 8 residents (mean age 80, SD 4.7 years; 2 male) at Site 2 completed field testing validation. Participant comfort and confidence increased significantly over successive iterations of the system across most categories (Site 1: Wilcoxon signed rank test P=.03; Site 2: Wilcoxon signed rank test P<.001). Additionally, 5 LTC staff members successfully set up the system with minimal cueing from the researchers, demonstrating the usability of the system for caregivers. Iterative design changes incorporated hardware, software, and activity domains. CONCLUSIONS: These initial results demonstrate that LTC older adults and staff are capable and critical to the development and implementation of SAR-VR activities. Future studies are needed to evaluate the feasibility of implementation and effectiveness in reducing apathy. TRIAL REGISTRATION: ClinicalTrials.gov NCT05178992; https://clinicaltrials.gov/study/NCT05178992.
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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 | 0.001 | 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".