*The authors would like to acknowledge the networking support from COST Action CA19122 (EUGAIN: European Network For Gender Balance in Informatics; https://eugain.eu/), supported by COST (European Cooperation in Science and Technology; www.cost.eu).

The Internet, an indispensable resource with its vast potential and easy accessibility, also brings negative aspects that can impact our mental, physical, and psychological well-being. Recent academic studies have focused on problematic Internet use (PIU), which refers to excessive or maladaptive use of the Internet, resulting in negative consequences in various aspects of an individual's life, including their academic performance. The consequences for young adults, including university students, who are among the most affected groups, have been explored (Caner-Yıldırım & Yıldırım, 2022; Saletti et al., 2021; Strasser, 2017). Various intervention programs have been suggested (Öztürk & Özmen, 2016), but few have been implemented (Saletti et al., 2021), and interventions targeting women's PIU are scarce (Aydin et al., 2022).

Individual well-being can be enhanced through self-control, which requires understanding self-regulation, the management of one's feelings, thoughts, and actions (Baumeister, 2018). Research has shown that PIU can negatively impact academic achievement, making it a crucial area of investigation. Kirschner and Karpinski (2010) found that students with high levels of PIU had lower grade point averages (GPAs) than their peers with lower PIU levels. Similarly, Junco (2012) discovered that excessive use of social media, a common component of PIU, was correlated with reduced academic performance. PIU, considered a behavioral addiction (Monaghan, 2014), can be mitigated using self-regulation strategies (Billieux & Van der Linden, 2012). One such strategy is mental contrasting with implementation intentions (MCII), combining two separate self-regulation strategies. Mental contrasting involves visualizing a desired future, followed by the current negative situation, creating a strong connection that motivates individuals to act (Oettingen, 2012). While mental contrasting strengthens goal commitment, implementation intentions provide a possible action plan to overcome anticipated obstacles (Gollwitzer, 1993). This approach may help address the relation between PIU and self-regulation, thereby improving academic performance. Research has shown the effectiveness of combining these strategies (Duckworth & Carlson, 2013; Gawrilow et al., 2013; Martenstyn & Grant, 2021).

This study aims to investigate the perceived academic effectiveness of the "hEp" MCII mobile app intervention, designed to improve women students' academic performance by reducing PIU. The findings of this research may have broader implications for understanding and addressing PIU and its effects on academic performance among university students across Europe. By examining the effectiveness of the "hEp" MCII mobile app intervention, this study could provide insights for policymakers, educational institutions, and mental health professionals to develop targeted interventions and support systems for students struggling with PIU.

2.1 Research Question What is the perceived academic effectiveness of the hEp, which aims to improve the academic performance of women university students by reducing their PIU? 2.2 Research Design Design-based research is the most appropriate method for designing and implementing systematic interventions that allow for continued refinement of initial designs and ultimately lead to improvements in the theoretical and practical goals that inform implementation. hEp, developed in accordance with design-based research, emerged from analyzing women university students' PIU as a problem that negatively impacts their academic performance, examining the characteristics of an intervention program designed for this problem, and developing a mobile application for this problem. The application was developed in iterative cycles and tested and improved during these cycles. 2.3 Study Group Women university students who perceived their Internet use behavior to be problematic, who perceived their academic performance to be inadequate for this reason, and who wanted to change their Internet use behavior were voluntarily enrolled in this study by purposive sampling. The demographics of the participants according to each cycle presented as follow: Cycle Age Range PIU Level of Participants 1 21 - 24 1 low, 2 moderate, 1 high 2 20 - 32 2 no PIU, 2 high 3 21 - 28 1 low, 5 moderate 4 20 -25 1 moderate, 1 high 2.4 Data Collection Instrument A semi-structured interview protocol was created to explore participants' views on the perceived academic effectiveness of hEp and updated across cycles. This protocol asked questions about academic behaviors before and after hEP, and how behaviors related to Internet use during studying changed after using hEP. 2.5 Data Analysis The qualitative content obtained in this study was analyzed using the content analysis method (Strauss & Corbin, 1998). Data analysis was conducted in accordance with data management. The interviews were transcribed and codes were searched for in the transcripts. Then, the codes for the research question were searched by close reading. In this direction, the data were divided into appropriate sections and codes were assigned to symbolize these sections. After the codes were created, they were classified into meaningful, abstract, and larger clusters called themes. The themes and codes were arranged in a hierarchical order.

The academic effectiveness theme (n= 18, f= 133) refers to participants' evaluation of hEP on various characteristics related to its academic effectiveness. Several subthemes emerged under this theme. These are: Empowering Goal Attainment, Changing Study Plans and Behavior, Changing Internet Use Behavior, Controlling Academic Procrastination, Providing Support and Guidance, and Increasing Academic Self-Efficacy (Only first three themes were explained due to the word limit). Empowering goal attainment (n= 17, f= 39) refers to hEp's support of participants in achieving their goals. Thirteen participants indicated that after completing the hEP, they felt obligated to focus on the goal, prioritized achieving the goal in their thoughts, and felt that the hEP gave them responsibility in this sense. In this way, they remained committed to their goals and achieved them efficiently. Eleven participants said they were more disciplined and determined in working toward their goals thanks to hEp. They emphasized that they work in a more planned and programmed manner, that they are able to set their steps more clearly and decisively against situations that hinder them, that they are able to work without getting up from the table (without getting busy with other things), and that they show a more willing attitude. The change in study plans and behavior sub-theme (n= 12, f= 27) reflects participants' statements about changes in their work plans and behavior after using hEp. The most common participant expression of change was overcoming resistance. Five participants stated that they had some negative habits about studying before using hEp that they were able to overcome with hEp. The sub-theme of changing Internet use behavior (n= 12, f= 24) refers to the change in participants' internet usage behavior after using hEp. Twelve participants emphasized that they reduced their internet usage time in parallel to using hEp.

Aydin, B., Misirli, Ö., & Atakan, S. (2022). Online Psycho-Instructional Model: For Women Victims of Cyber Bullying & Cyber Harassment. In Proceedings of The 7th International Academic Conference on Humanities and Social Sciences (IACHSS 2022). Paris, France: Diamond Scientific Publishing. Baumeister, R. (2018). Self-regulation and self-control: Selected works of Roy F. Baumeister. Routledge. Billieux, J., & Van der Linden, M. (2012). Problematic use of the Internet and self-regulation: A review of the initial studies. The Open Addiction Journal, 5, 24-29. Caner-Yıldırım, S., & Yıldırım, Z. (2022). Psychometric Properties of Turkish Version of Generalized Problematic Internet Use Scale-2 and the Relationship Between Internet Use Patterns and Problematic Internet Use. International Journal of Mental Health and Addiction, 1-23. Duckworth, A. L., & Carlson, S. M. (2013). “Self-regulation and school success.” Self-regulation and autonomy: Social and developmental dimensions of human conduct, 40, 208. Gollwitzer, P. M. (1993). Goal achievement: The role of intentions. European review of social psychology, 4(1), 141-185. Junco, R. (2012). Too much face and not enough books: The relationship between multiple indices of Facebook use and academic performance. Computers in Human Behavior, 28(1), 187-198. Kirschner, P. A., & Karpinski, A. C. (2010). Facebook® and academic performance. Computers in Human Behavior, 26(6), 1237-1245. Monaghan, S. C. (2014). Problematic Internet use: A unique expression of the addiction syndrome (Order No. 3626922). Available from ProQuest Dissertations & Theses Global. (1564215260). Oettingen, G. (2012). Future thought and behaviour change. European review of social psychology, 23(1), 1-63. Öztürk, E., & Özmen, S. K. (2016). The relationship of self-perception, personality and high school type with the level of problematic Internet use in adolescents. Computers in Human Behavior, 65, 501-507. Saletti, S. M. R., Van den Broucke, S., & Chau, C. (2021). The effectiveness of prevention programs for problematic Internet use in adolescents and youths: A systematic review and meta-analysis. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 15(2). Stadler, G., Oettingen, G., & Gollwitzer, P. M. (2010). Intervention effects of information and self-regulation on eating fruits and vegetables over two years. Health Psychology, 29(3), 274 Strasser IV, J. F. (2016). Internet Access, Use and Academic Achievement (Master Thesis, State University of New York at Buffalo). Strauss, A., & Corbin, J. (1998). Basics of qualitative research techniques. Thousand Oaks, CA: Sage publications.