Social Robot Design Preferences Surveyed from Dementia Stakeholders

An online survey conducted with 116 participants, including people with dementia, informal carers, formal carers, and healthcare providers, investigated design preferences for social robots in dementia care. The study used Bayesian regression and inductive content analysis to examine preferred robot features and design attributes. The dataset was authored by Matthew Green and last updated on 2026-05-18.

Use Cases

• Analyze stakeholder preferences for robot aesthetics (animal-like vs. humanoid) based on survey responses
• Investigate perceived acceptability of data capture features (face recognition, camera monitoring) for safety and personalization
• Model relationships between robot capabilities and audio outputs using Bayesian regression results
• Compare design concerns across stakeholder groups (people with dementia, carers, providers) from qualitative content analysis

Strengths

• Multi-method design combining quantitative and qualitative analysis
• Survey includes 116 participants across four distinct stakeholder groups
• Analysis employs Bayesian regression and inductive content analysis

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download
• Data may reflect bias inherent to the survey methodology and participant sample

Provenance

Source

Matthew Green

Collection Method

Online survey with Bayesian regression and inductive content analysis

Freshness

Last updated 2026-05-18 04:17:05; freshness should be verified