Identifying Preferred Appearance and Functional Requirements of Aged Care Robots Among Older Chinese Immigrants: Cross-Sectional Study
Bibliographic record
Abstract
Background: Older Chinese immigrants constitute the largest older Asian ethnic population in New Zealand. Aging in a foreign land can be complex, presenting increasing challenges for gerontology scholars, practitioners, and policy makers. Older Chinese immigrants are more susceptible to experiencing loneliness and social isolation compared to native older people, primarily due to language, transportation, and cultural barriers. These factors subsequently impact their physical and mental health. With advancements in robotic technology, aged care robots are being applied to support older people with their daily living needs. However, studies on using robots with older immigrants living in the community are sparse. Their preferences for the appearance and function of aged care robots are unclear, which impacts the acceptance and usability of robots, highlighting the need for a user-centered design approach. Objective: This study aims to explore older Chinese immigrants' needs and preferences toward the appearance and function of aged care robots and to examine their relationships with the demographic characteristics of participants. Methods: A cross-sectional design was used in this study, which was undertaken between March and May 2020. A total of 103 participants completed a web-based survey. Results: The average age of participants was 68.7 (SD 5.5) years. The results suggest that 41.7% (n=43) of the 103 participants preferred a humanlike adult appearance, while 32% (n=33) suggested an animallike appearance. These participants reported higher scores in both rigorousness and friendliness compared to others who preferred different robot appearances. Participants expressed a greater preference for the functions of housework assistance (n=86, 83.5%), language translation (n=79, 76.7%), health monitoring (n=78, 75.7%), facial expressions (n=77, 74.8%), news reading (n=66, 64.1%), and security monitoring (n=65, 63.1%). These preferences were found to be significantly associated with marital status, financial status, and duration of immigration. Conclusions: To support immigrant populations to age well in a foreign country and address the growing shortage of health and social professionals, it is important to develop reliable robotic technology services that are tailored based on the needs and preferences of individuals. We collected and compared the perspectives of immigrant and nonimmigrant participants on using robots to support aging in place. The results on users' needs and preferences inform robotic technology services, indicating a need to prioritize older Chinese immigrants' preference toward aged care robots that perform housework assistance, language translation, and health and safety monitoring, and robots with humanlike features.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".