An Empirical Study on the Impact of Moral Interventions on Addictive Behavior and Psychological States in Mobile Applications
DOI:
https://doi.org/10.4108/eetpht.11.14202Keywords:
Addictive Design, Moral Intervention, User Behavior, Mobile Applications, Digital EthicsAbstract
INTRODUCTION: With the widespread use of intelligent mobile devices, addictive design in mobile applications has increasingly influenced users' behavioral patterns and psychological well-being.
OBJECTIVES: This study examines the effects of addictive interface design and the feasibility of ethical intervention through a three-stage conceptual pathway of “addictive mechanisms–moral intervention–user response.”
METHODS: A five-day controlled experiment with 72 participants compared a standard interface containing addictive mechanisms with an otherwise equivalent interface incorporating duration reminders, excessive-reading prompts, and exit guidance. Behavioral logs, GAD-7 and short-form SAS scores, a post-experiment acceptance questionnaire, and semi-structured interviews with three domain experts were used for triangulation.
RESULTS: After Holm–Bonferroni correction, the intervention group showed significantly shorter usage duration, lower scrolling frequency, and lower anxiety and dependency scores than the control group; the corresponding effects were moderate to large. The intervention received a mean acceptance rating of 4.2 out of 5.
CONCLUSION: Mild, non-coercive interventions can reduce immersive use while preserving user acceptance, providing empirical and practical guidance for ethically responsible mobile interface design.
Downloads
References
[1] Hans A, Singh NT, Kumar R, Kumar A, Choubey A, Suresh. The psychology behind addictive applications in technology. In: 2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT); 2024 Feb 9-10; Greater Noida, India. Piscataway (NJ): IEEE; 2024. p. 669-672. doi:10.1109/IC2PCT60090.2024.10486603.
[2] Khan MI, Saxena A, Samreen, Verma P. Trapped in the screen: unpacking the modern epidemic of mobile addiction. International Journal for Multidisciplinary Research. 2024;6(4):1-4. doi:10.36948/ijfmr.2024.v06i04.26254.
[3] Bandaru AKR, Fiaidhi J, Gannamani VS. FOMO, social media engagement, smartphone addiction and distraction [preprint]. TechRxiv; 2020. doi:10.36227/techrxiv.12094140.v1.
[4] Schwarz A, Winkens LHH, de Vet E, Ossendrijver D, Bouwsema K, Simons M. Design features associated with engagement in mobile health physical activity interventions among youth: systematic review of qualitative and quantitative studies. JMIR Mhealth Uhealth. 2023;11:e40898. doi:10.2196/40898.
[5] Lyons D, Kiyak C, Cetinkaya D, Hodge S, McAlaney J. Design and development of a mobile application to combat digital addiction and dissociative states during phone usage. In: 2022 IEEE International Conference on E-Business Engineering (ICEBE); 2022 Oct 14-16; Bournemouth, United Kingdom. Piscataway (NJ): IEEE; 2022. p. 204-209. doi:10.1109/ICEBE55470.2022.00043.
[6] Grahlher K, Morgenstern M, Pietsch B, Gomes de Matos E, Rossa M, Lochbühler K, et al. Mobile app intervention to reduce substance use, gambling, and digital media use in vocational school students: exploratory analysis of the intervention arm of a randomized controlled trial. JMIR Mhealth Uhealth. 2024;12:e51307. doi:10.2196/51307.
[7] Atieh P, Hammad E, Riley C. Ethical safeguards & behavioral psychology competencies: a framework for computer science capstone project design. In: 2023 IEEE Frontiers in Education Conference (FIE); 2023 Oct 18-21; College Station (TX), United States. Piscataway (NJ): IEEE; 2023. p. 1-9. doi:10.1109/FIE58773.2023.10343178.
[8] Futane PR, Wagh SD, Binnar PS, Sanap PS, Kolhe A. A comprehensive review on machine learning approaches for smartphone addiction prediction. International Journal of Scientific Research in Engineering and Management. 2025;9(2):1-5. doi:10.55041/IJSREM41291.
[9] Wang H, Chen J, Wang T, Li G. Research on social design theories and methods based on unconscious behavior data. Big.D. 2024;1(1):85-93. doi:10.64504/big.d.v1i1.23.
[10] Tiersen FJ, Calvo RA. Holdable devices: supporting mindfulness, psychological autonomy and self-regulation during smartphone use. In: Kurosu M, editor. Human-computer interaction: interaction techniques and novel applications. Cham: Springer; 2021. p. 476-495. doi:10.1007/978-3-030-78465-2_35.
[11] Singh G, Simpson E, MacGillivray M, Sawatzky B, Adams J, Mortenson WB. Expectations of a health-related mobile self-management app intervention among individuals with spinal cord injury. Top Spinal Cord Inj Rehabil. 2022;28(2):205-215. doi:10.46292/sci21-00022.
[12] Denecke K, Schmid N, Nüssli S. Implementation of cognitive behavioral therapy in e-mental health apps: literature review. J Med Internet Res. 2022;24(3):e27791. doi:10.2196/27791.
[13] Antezana G, Venning A, Smith D, Bidargaddi N. Understanding what we know so far about young people's engagement with wellbeing apps: a scoping review and narrative synthesis. Digit Health. 2022;8:20552076221144104. doi:10.1177/20552076221144104.
[14] Qu A, Liu J, Pan Z, He Y. Gamified social media assistance for children and teens: fostering ethical online behavior. In: Stephanidis C, Antona M, Ntoa S, Salvendy G, editors. HCI International 2024 posters: proceedings, Part VI. Cham: Springer; 2024. p. 121-128. doi:10.1007/978-3-031-61966-3_14.
[15] Yu Y, Chen Y, Ying H, Zhang D. Design ethics and the sharing economy: frontier explorations and innovative developments from an interdisciplinary perspective. Big.D. 2024;1(1):106-115. doi:10.64504/big.d.v1i1.25.
[16] Zucchelli F, Donnelly O, Rush E, White P, Gwyther H, Williamson H. An acceptance and commitment therapy prototype mobile program for individuals with a visible difference: mixed methods feasibility study. JMIR Form Res. 2022;6(1):e33449. doi:10.2196/33449.
[17] Muench F, Baumel A. More than a text message: dismantling digital triggers to curate behavior change in patient-centered health interventions. J Med Internet Res. 2017;19(5):e147. doi:10.2196/jmir.7463.
[18] Spitzer RL, Kroenke K, Williams JBW, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166(10):1092-1097. doi:10.1001/archinte.166.10.1092.
[19] Zung WWK. A rating instrument for anxiety disorders. Psychosomatics. 1971;12(6):371-379. doi:10.1016/S0033-3182(71)71479-0.
[20] Benartzi S, Beshears J, Milkman KL, Sunstein CR, Thaler RH, Shankar M, et al. Should governments invest more in nudging? Psychol Sci. 2017;28(8):1041-1055. doi:10.1177/0956797617702501.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Jiuyuan Zhu; Yixin Yu, Yao Chen, Xuesong Li
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
