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Participants
Q2 2025
Bachelor Thesis
Our smartphones have evolved from a simple means of communication to a smart, multifunctional device that combines numerous functions in a single device. As the digitalization of our everyday lives progresses, we expect high functionality and efficiency, but is this really the case?More and more studies and social discourses are taking a critical look at the effects of intensive smartphone use. Numerous behavioral problems are being linked to our digital usage. Against this backdrop, voices from researchers are repeatedly calling for intervention programs to meet these challenges
This bachelor thesis addresses this problem and approaches it with a design focus. Based on a thorough examination of existing literature and research, an analysis of design principles and a systematic consideration of usage patterns, a conceptual design for a digital intervention system is developed. The aim is to create a methodological basis that not only combats symptoms, but also addresses the problem at its root. Namely, the structural and design mechanisms that influence our behavior in the digital space
This bachelor thesis addresses this problem and approaches it with a design focus. Based on a thorough examination of existing literature and research, an analysis of design principles and a systematic consideration of usage patterns, a conceptual design for a digital intervention system is developed. The aim is to create a methodological basis that not only combats symptoms, but also addresses the problem at its root. Namely, the structural and design mechanisms that influence our behavior in the digital space
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Concept
This project presents a conceptual design for a digital intervention system addressing problematic smartphone use. The goal was to create a broad and differentiated pool of interventions that demonstrates how digital measures can, and must be tailored to individual needs, usage patterns, and motivational states.
Rather than offering the same interventions to all users, the system is selective and personalized. Using artificial intelligence, it analyzes smartphone behavior and, based on user behavior types and their readiness to change, recommends appropriate interventions.
The full concept is visualized as matrix, which visualizes four user groups categorized by their smartphone behavior and motivation level. The matrix shows which interventions align with which user profile, serving both as a visual overview of the intervention pool and a decision-making framework for the AI system.
Interventions were assigned based on their level of invasiveness, required motivation, intended effect, and usage context. For example highly invasive interventions were matched with users who show problematic usage but are motivated to change.Reflective interventions were assigned to those with problematic usage but low motivation, aiming to build awareness and readiness. Supportive tools for maintaining healthy usage were placed with self-optimizers. Subtle, low-disruption interventions were linked to users whose smartphone habits don’t currently demand change.
Some interventions could logically fit multiple user groups. In such cases, placement was guided by which group stood to benefit most.
Finally, it’s important to note that all interventions are conceptual and based on independent research and design reasoning. Their effectiveness has not yet been empirically tested. This work is not a finished solution, but rather a design proposal—intended to spark discussion and illustrate what a responsive, user-centered intervention system could look like.
Rather than offering the same interventions to all users, the system is selective and personalized. Using artificial intelligence, it analyzes smartphone behavior and, based on user behavior types and their readiness to change, recommends appropriate interventions.
The full concept is visualized as matrix, which visualizes four user groups categorized by their smartphone behavior and motivation level. The matrix shows which interventions align with which user profile, serving both as a visual overview of the intervention pool and a decision-making framework for the AI system.
Interventions were assigned based on their level of invasiveness, required motivation, intended effect, and usage context. For example highly invasive interventions were matched with users who show problematic usage but are motivated to change.Reflective interventions were assigned to those with problematic usage but low motivation, aiming to build awareness and readiness. Supportive tools for maintaining healthy usage were placed with self-optimizers. Subtle, low-disruption interventions were linked to users whose smartphone habits don’t currently demand change.
Some interventions could logically fit multiple user groups. In such cases, placement was guided by which group stood to benefit most.
Finally, it’s important to note that all interventions are conceptual and based on independent research and design reasoning. Their effectiveness has not yet been empirically tested. This work is not a finished solution, but rather a design proposal—intended to spark discussion and illustrate what a responsive, user-centered intervention system could look like.
Conclusion & Outlook
This project aims to shift the focus in the discourse around problematic smartphone behavior from solely blaming users to holding digital product designers accountable. While individual reflection and self-regulation are important, excessive smartphone use is largely rooted in the design principles of digital systems. Designers intentionally implement mechanisms that tap into neurobiological responses to shape and sustain user behavior.
Given the smartphone's growing presence in our daily lives, it’s critical to question the digital stimuli we’re constantly exposed to and how we interact with them. To support this reflection, the project presents a conceptual design for a proactive, adaptive, and user-centered intervention system. This system identifies moments when behavioral triggers arise and intervenes directly within the context of habitual usage. It helps users interrupt impulsive behaviors, recognize digital triggers, and discover healthier alternatives. Artificial intelligence plays a key role in enabling personalized interventions by analyzing individual usage patterns and adapting support to user needs.
While this concept is grounded in theoretical and practical research as well as user insights, further empirical validation is necessary.
Given the smartphone's growing presence in our daily lives, it’s critical to question the digital stimuli we’re constantly exposed to and how we interact with them. To support this reflection, the project presents a conceptual design for a proactive, adaptive, and user-centered intervention system. This system identifies moments when behavioral triggers arise and intervenes directly within the context of habitual usage. It helps users interrupt impulsive behaviors, recognize digital triggers, and discover healthier alternatives. Artificial intelligence plays a key role in enabling personalized interventions by analyzing individual usage patterns and adapting support to user needs.
While this concept is grounded in theoretical and practical research as well as user insights, further empirical validation is necessary.
