Frontiers in public health · 2026
Trusting and staying with AI doctors: cognitive and emotional pathways driving continuance intention toward AI healthcare chatbots.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Wang Zhanyou, Han Haoran, Han Dongmei, Ma Liang, Hao Feifei
Аннотация
INTRODUCTION: AI-powered medical chatbots are increasingly used in healthcare, yet the mechanisms underlying users' continued engagement remain unclear. This study examines how AI use influences continuance intention through cognitive trust and emotional attachment and whether technology anxiety differentially moderates these pathways.
METHODS: Data were collected from 233 users of AI medical services in China. The proposed model was tested using partial least squares structural equation modeling (PLS-SEM) and bootstrapping in SmartPLS 4.0.
RESULTS: AI use positively influences both cognitive trust and emotional attachment, which in turn enhance continuance intention. Both mechanisms significantly mediate the relationship between AI use and continuance intention, with emotional attachment showing a stronger mediating effect. Technology anxiety significantly moderates the AI use-cognitive trust relationship but not the AI use-emotional attachment relationship, revealing an asymmetric moderating pattern.
DISCUSSION: This study extends cognitive-affective processing theory by revealing dual cognitive and emotional pathways linking AI use to continuance intention. It further identifies technology anxiety as a boundary condition that selectively shapes the cognitive pathway while leaving the emotional pathway relatively unaffected. The findings offer implications for designing anxiety-sensitive AI healthcare services and differentiated user engagement strategies.
METHODS: Data were collected from 233 users of AI medical services in China. The proposed model was tested using partial least squares structural equation modeling (PLS-SEM) and bootstrapping in SmartPLS 4.0.
RESULTS: AI use positively influences both cognitive trust and emotional attachment, which in turn enhance continuance intention. Both mechanisms significantly mediate the relationship between AI use and continuance intention, with emotional attachment showing a stronger mediating effect. Technology anxiety significantly moderates the AI use-cognitive trust relationship but not the AI use-emotional attachment relationship, revealing an asymmetric moderating pattern.
DISCUSSION: This study extends cognitive-affective processing theory by revealing dual cognitive and emotional pathways linking AI use to continuance intention. It further identifies technology anxiety as a boundary condition that selectively shapes the cognitive pathway while leaving the emotional pathway relatively unaffected. The findings offer implications for designing anxiety-sensitive AI healthcare services and differentiated user engagement strategies.