Beyond Frequency: Latent Profiles of Problematic ChatGPT Use and Psychosocial Risk and Protective Factors Among Adults

Al Naqbi, H., Bahroun, Z., & Ahmed, V. (2024). Enhancing work productivity through generative artificial intelligence: A comprehensive literature review. Sustainability, 16(3), Article 1166. https://doi.org/10.3390/su16031166

Article  Google Scholar 

Bakk, Z., Tekle, F. B., & Vermunt, J. K. (2013). Estimating the association between latent class membership and external variables using bias-adjusted three-step approaches. Sociological Methodology, 43(1), 272–311. https://doi.org/10.1177/0081175012470644

Article  Google Scholar 

Barański, M., & Poprawa, R. (2025). Profiles of loneliness types and social support sources in emerging adulthood, and their relevance to forms of problematic Internet use: A person-centered perspective. Advance online publication. https://doi.org/10.5114/hpr/202320

Bick, A., Blandin, A., & Deming, D. J. (2025). The rapid adoption of generative AI (Federal Reserve Bank of St. Louis Working Paper No. 2024–027F). Federal Reserve Bank of St. Louis. https://doi.org/10.20955/wp.2024.027

Biernacki, C., Celeux, G., & Govaert, G. (2000). Assessing a mixture model for clustering with the integrated completed likelihood. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(7), 719–725. https://doi.org/10.1109/34.865189

Article  Google Scholar 

Brand, M., Wegmann, E., Stark, R., Müller, A., Wölfling, K., Robbins, T. W., & Potenza, M. N. (2019). The interaction of person-affect-cognition-execution (I-PACE) model for addictive behaviors: Update, generalization to addictive behaviors beyond Internet-use disorders, and specification of the process character of addictive behaviors. Neuroscience & Biobehavioral Reviews, 104, 1–10. https://doi.org/10.1016/j.neubiorev.2019.06.032

Article  Google Scholar 

Carleton, R. N., Norton, M. A. P. J., & Asmundson, G. J. G. (2007). Fearing the unknown: A short version of the intolerance of uncertainty scale. Journal of Anxiety Disorders, 21(1), 105–117. https://doi.org/10.1016/j.janxdis.2006.03.014

Article  PubMed  Google Scholar 

Chatterji, A., Cunningham, T., Deming, D. J., Hitzig, Z., Ong, C., Shan, C. Y., & Wadman, K. (2025). How people use ChatGPT (NBER Working Paper No. 34255). National Bureau of Economic Research. https://doi.org/10.3386/w34255

Ciudad-Fernández, V., von Hammerstein, C., & Billieux, J. (2025). People are not becoming “AIholic”: Questioning the “ChatGPT addiction” construct. Addictive Behaviors, 166, Article 108325. https://doi.org/10.1016/j.addbeh.2025.108325

Article  PubMed  Google Scholar 

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.

Çorak, T. (2026). Intolerance of uncertainty and smartphone addiction: Mediating effects of reappraisal, suppression and rumination. Current Psychology, 45, Article 536. https://doi.org/10.1007/s12144-026-09034-4

Article  Google Scholar 

IBM Corp. (2020). IBM SPSS statistics for windows, version 27.0. IBM Corp.

Cutuli, D. (2014). Cognitive reappraisal and expressive suppression strategies role in the emotion regulation: An overview on their modulatory effects and neural correlates. Frontiers in Systems Neuroscience, 8, Article 175. https://doi.org/10.3389/fnsys.2014.00175

Article  PubMed  PubMed Central  Google Scholar 

Duong, C. D., Dao, T. T., Vu, T. N., Ngo, T. V. N., & Tran, Q. Y. (2024). Compulsive ChatGPT usage, anxiety, burnout, and sleep disturbance: A serial mediation model based on stimulus-organism-response perspective. Acta Psychologica, 251, Article 104622. https://doi.org/10.1016/j.actpsy.2024.104622

Article  PubMed  Google Scholar 

Fang, C. M., Liu, A. R., Danry, V., Lee, E., Chan, S. W. T., Pataranutaporn, P., Maes, P., Phang, J., Lampe, M., Ahmad, L., & Agarwal, S. (2025). How AI and human behaviors shape psychosocial effects of extended chatbot use: A longitudinal randomized controlled study [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2503.17473

Finch, W. H., & Bronk, K. C. (2011). Conducting confirmatory latent class analysis using Mplus. Structural Equation Modeling: A Multidisciplinary Journal, 18(1), 132–151. https://doi.org/10.1080/10705511.2011.532732

Article  Google Scholar 

Gioia, F., Rega, V., & Boursier, V. (2021). Problematic Internet use and emotional dysregulation among young people: A literature review. Clinical Neuropsychiatry, 18(1), 41–54. https://doi.org/10.36131/cnfioritieditore20210104

Article  PubMed  PubMed Central  Google Scholar 

Gloster, A. T., Block, V. J., Klotsche, J., Villanueva, J., Rinner, M. T. B., Benoy, C., Walter, M., Karekla, M., & Bader, K. (2021). Psy-Flex: A contextually sensitive measure of psychological flexibility. Journal of Contextual Behavioral Science, 22, 13–23. https://doi.org/10.1016/j.jcbs.2021.09.001

Article  Google Scholar 

Grassini, S. (2023). Development and validation of the AI attitude scale (AIAS-4): A brief measure of general attitude toward artificial intelligence. Frontiers in Psychology, 14, Article 1191628. https://doi.org/10.3389/fpsyg.2023.1191628

Article  PubMed  PubMed Central  Google Scholar 

Gross, J. J., & John, O. P. (2003). Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being. Journal of Personality and Social Psychology, 85(2), 348–362. https://doi.org/10.1037/0022-3514.85.2.348

Article  PubMed  Google Scholar 

Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 6(2), 65–70. https://www.jstor.org/stable/4615733

Howard, M. C., & Hoffman, M. E. (2018). Variable-centered, person-centered, and person-specific approaches: Where theory meets the method. Organizational Research Methods, 21(4), 846–876. https://doi.org/10.1177/1094428117744021

Article  Google Scholar 

Hu, B., Mao, Y., & Kim, K. J. (2023). How social anxiety leads to problematic use of conversational AI: The roles of loneliness, rumination, and mind perception. Computers in Human Behavior, 145, Article 107760. https://doi.org/10.1016/j.chb.2023.107760

Article  Google Scholar 

Huang, H., Shi, L., & Pei, X. (2026). When AI becomes a friend: The “emotional” and “rational” mechanism of problematic use in generative AI chatbot interactions. International Journal of Human-Computer Interaction, 42(6), 4006–4024. https://doi.org/10.1080/10447318.2025.2536622

Article  Google Scholar 

Hwang, H. S., & Kim, S. (2026). Personality traits and the technology acceptance of ChatGPT: Mediating effects of perceived usefulness and ease of use. Digital Technologies Research and Applications, 5(2), 15–29. https://doi.org/10.54963/dtra.v5i2.1780

Article  Google Scholar 

İnanç, A., & Ekşi, H. (2022). Adaptation of RULS-6 loneliness scale (6-item short form) into Turkish: A validity and reliability study. Contemporary Educational Researches Journal, 12(4), 197–203. https://doi.org/10.18844/cerj.v12i4.7466

Kalimira, A. M., & Jazayeri, K. (2026). From social drivers to sustainable AI usage and dependency in higher education: Roles of trust, perceived competence, and perceived intelligence. Sustainability, 18(3), Article 1598. https://doi.org/10.3390/su18031598

Article  Google Scholar 

Kardefelt-Winther, D. (2014). A conceptual and methodological critique of internet addiction research: Towards a model of compensatory internet use. Computers in Human Behavior, 31, 351–354. https://doi.org/10.1016/j.chb.2013.10.059

Article  Google Scholar 

Kardefelt-Winther, D., Heeren, A., Schimmenti, A., van Rooij, A., Maurage, P., Carras, M., Edman, J., Blaszczynski, A., Khazaal, Y., & Billieux, J. (2017). How can we conceptualize behavioural addiction without pathologizing common behaviours? Addiction, 112(10), 1709–1715. https://doi.org/10.1111/add.13763

Article  PubMed  PubMed Central  Google Scholar 

Koç, H., Şimşir-Gökalp, Z., & Seki, T. (2023). The relationships between self-control and distress among the emerging adults: A serial mediating roles of fear of missing out and social media addiction. Emerging Adulthood, 11(3), 803–816. https://doi.org/10.1177/21676968231151776

Article  Google Scholar 

Liu, C., Ren, L., Li, K., Yang, W., Li, Y., Rotaru, K., Wei, X., Yücel, M., & Albertella, L. (2022). Understanding the association between intolerance of uncertainty and problematic smartphone use: A network analysis. Frontiers in Psychiatry, 13, Article 917833. https://doi.org/10.3389/fpsyt.2022.917833

Article  PubMed  PubMed Central  Google Scholar 

Liu, C., Rotaru, K., Chamberlain, S. R., Ren, L., Fontenelle, L. F., Lee, R. S. C., Suo, C., Raj, K., Yücel, M., & Albertella, L. (2022). The moderating role of psychological flexibility on the association between distress-driven impulsivity and problematic Internet use. International Journal of Environmental Research and Public Health, 19(15), Article 9592. https://doi.org/10.3390/ijerph19159592

Article  PubMed  PubMed Central  Google Scholar 

Liu, J. (2024). ChatGPT: Perspectives from human–computer interaction and psychology. Frontiers in Artificial Intelligence, 7, Article 1418869. https://doi.org/10.3389/frai.2024.1418869

Article  PubMed  PubMed Central  Google Scholar 

Luo, X., Wang, Z., Tilley, J. L., Balarajan, S., Bassey, U.-A., & Cheang, C. I. (2025). Seeking emotional and mental health support from generative AI: Mixed-methods study of ChatGPT user experiences. JMIR Mental Health, 12, Article e77951. https://doi.org/10.2196/77951

Article  PubMed  PubMed Central  Google Scholar 

Maral, S., Naycı, N., Bilmez, H., Erdemir, E. İ, & Satici, S. A. (2026). Problematic ChatGPT use scale: AI-human collaboration or unraveling the dark side of ChatGPT. International Journal of Mental Health and Addiction, 24(3), 2369–2395. https://doi.org/10.1007/s11469-025-01509-y

Article  Google Scholar 

McCutcheon, A. L. (2002). Basic concepts and procedures in single- and multiple-group latent class analysis. In J. A. Hagenaars & A. L. McCutcheon (Eds.), Applied latent class analysis (pp. 56–88). Cambridge University Press.

Menon, D., & Shilpa, K. (2023). “Chatting with ChatGPT”: Analyzing the factors influencing users’ intention to use OpenAI’s ChatGPT using the UTAUT model. Heliyon, 9(11), Article e20962. https://doi.org/10.1016/j.heliyon.2023.e20962

Merrill, K., Jr., Mikkilineni, S. D., & Dehnert, M. (2025). Artificial intelligence chatbots as a source of virtual social support: Implications for loneliness and anxiety management. Annals of the New York Academy of Sciences, 1549, 148–159. https://doi.org/10.1111/nyas.15400

Article  PubMed  PubMed Central  Google Scholar 

Meyer, J. P., & Morin, A. J. S. (2016). A person-centered approach to commitment research: Theory, research, and methodology. Journal of Organizational Behavior, 37(4), 584–612. https://doi.org/10.1002/job.2085

Article  Google Scholar 

Morin, A. J. S., Morizot, J., Boudrias, J.-S., & Madore, I. (2011). A multifoci person-centered perspective on workplace affective commitment: A latent profile/factor mixture analysis. Organizational Research Methods, 14(1), 58–90.

Comments (0)

No login
gif