EFFECT OF PARENTAL MOBILE PHONE ADDICTION ON CHILD DEVELOPMENT: A COMPUTATIONAL FRAMEWORK FOR BEHAVIORAL ANALYSIS

The rapid proliferation of digital technology has fundamentally transformed the domestic environment, introducing new variables into the complex equation of child-rearing. Among these variables, parental mobile phone addiction—often characterized by continuous partial attention and digital distraction—poses a significant risk to the quality of parent-child interactions. These interactions are foundational for healthy cognitive and socio-emotional maturation. Traditional observational methods in developmental psychology struggle to capture the real-time nuances of this digital interference and face severe ethical limitations when attempting to study the long-term impacts of neglectful behaviors. This paper proposes a novel computational framework that leverages large language models (LLMs) and advanced text mining techniques to safely simulate, quantify, and analyze the developmental consequences of parental mobile phone addiction. By decoupling conversational intent from attentional capacity, the proposed pipeline allows researchers to map simulated digital distraction to predicted developmental trajectories, offering a scalable, ethically sound approach to understanding modern family dynamics in the artificial intelligence era.