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AI-Supported Acne Management on Digital Platform Among Generation Z in Indonesia: A Mixed-Methods Study
ABSTRACT
Background:
Artificial intelligence (AI) has become increasingly embedded in everyday self-management, shaping how young people seek information, interpret feedback, and regulate emotional responses. Beyond its informational role, AI is often experienced as an interactive source of reassurance and guidance, particularly in health-related contexts.
Objective:
This study examines how AI-related experiences are involved in psychological coping processes during acne management among Generation Z.
Methods:
A sequential, exploratory mixed methods design was employed. Firstly, a qualitative phase involved in-depth interviews to explore how young users perceive and engage with AI in managing acne-related concerns, thereby identifying key experiential dimensions. These insights structured the development of a quantitative model, which was examined using partial least squares structural equation modeling (PLS-SEM) based on survey data from 255 Indonesian respondents aged 18–27 years.
Results:
The mixed methods analysis examined Generation Z users’ experiences with AI-supported acne management, focusing on both immediate emotional responses during AI interactions and more enduring psychological coping processes. Acne severity was incorporated as a moderating variable to explore variations in these relationships across levels of acne-related concern.
Conclusions:
This study contributes to a human factors perspective by conceptualizing AI as a psychologically meaningful element in everyday acne management and highlighting its role in user coping experiences.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.