Survey on AI Painting Tool Adoption Among Adults Aged 60–69

450 valid survey responses from adults aged 60–69 were analyzed using partial least squares structural equation modeling. The dataset, authored by Meichen Fang and last updated in May 2026, examines psychological and social factors influencing the intention to use AI painting tools. It extends the Technology Acceptance Model with factors like technological characteristics, social support, and individual motivation.

Use Cases

• Modeling technology acceptance factors like perceived usefulness and ease of use based on survey constructs.
• Analyzing the role of social support (intergenerational and peer influence) in digital tool adoption among older adults.
• Investigating the impact of individual motivational factors (hedonic motivation, personal innovativeness) on technology engagement.
• Studying the relative importance of technological characteristics (output quality, relative advantage, trialability) for user acceptance.

Strengths

• Dataset is based on 450 valid survey responses, providing a substantive sample size.
• Analysis employs a recognized theoretical framework (Technology Acceptance Model) extended with specific constructs relevant to the aging population.
• The description provides detailed results linking specific factors (e.g., output quality, intergenerational support) to model components.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for certain analyses.
• The dataset is small (209.8 KB), indicating limited scope, likely containing only survey results or analysis outputs.

Provenance

Source

Meichen Fang via figshare

Collection Method

Survey data analyzed using partial least squares structural equation modeling.

Freshness

Last updated 2026-05-26 06:01:55; freshness should be verified.