Does Prompting Matter? A Comparative Study on Task-Technology Fit and Psychological Wellbeing in AI-Assisted Reflective Venting

Abstract

As conversational AI becomes a tool for emotional support, understanding the mechanisms that convert technological interaction into psychological benefits is crucial. Traditional Task-Technology Fit (TTF) models often overlook the internal cognitive-emotional processes required in affective use cases. This study investigates whether the "fit" of AI directly impacts psychological wellbeing or if it requires the mediation of emotional regulation. Furthermore, it examines the role of "Prompting AI as Professional Psychologist" to determine if structured user input enhances the effectiveness of AI-assisted venting.This research utilizes a quantitative approach with PLS-SEM (Partial Least Squares Structural Equation Modeling). Data was collected from 259 young professionals and users of conversational AI. A Multi-Group Analysis (MGA) was conducted to compare users who utilized structured prompting versus those who engaged in non-prompting interaction.The findings reveal that TTF does have a significant direct effect on psychological wellbeing, and its impact is further strengthened when partially mediated by Emotional Regulation, proving that AI functions as cognitive scaffolding, it provides a suitable environment for venting, but the maximal psychological benefit supported when users engage in active emotional regulation. MGA further indicates that professional psychologist-oriented prompting significantly strengthens the indirect effect of TTF on psychological wellbeing. These findings indicate that framing AI interactions through prompting play a critical role in translating technological fit into effective emotional regulation and subsequent wellbeing outcomes. It indicates that the psychological value of AI is supported only when users possess the skill to direct the technology through intentional prompting, which facilitates deeper emotional processing.