AI가족안부전화 서비스 이용기간이 고령자 통화 응답 행동과 응답 시간대 안정성에 미치는 영향 = Effect of Service Usage Duration of an AI Check-In Call Service on Older Adults’ Call Response Behavior and Response Time Stability

다국어 초록 (Multilingual Abstract)

This study quantitatively analyzed older adults’ call response behavior using real operational logs from an AI-based family check-in call service and demonstrated the potential of AI caregiving technology for preventive safety management through a new behavioral indicator: the regularity of response time. Unlike prior studies that focused primarily on users’ subjective satisfaction or emotional effects, this research statistically examined objective behavioral patterns derived from repeated call records. Users were grouped by service duration, and connection rate and response-time variability were adopted as key indicators. Nonparametric tests and regression models accounting for repeated measurements were applied. Results showed that although long-term users had lower connection rates, their response times became significantly more stable, indicating that AI check-in calls contribute more to the formation of daily routines than to increasing response frequency. These findings provide academic evidence that non-face-to-face caregiving technologies can be interpreted as behavior-based preventive management tools.