Skip to main content
SpringerLink
Log in

Utilizing Chatbots as Predictive Tools for Anxiety and Depression: A Bibliometric Review

  • Conference paper
  • First Online:
Applied Informatics (ICAI 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1874))

Included in the following conference series:

  • 307 Accesses

Abstract

This article addresses the impact of the implementation of medical chatbots as a tool to predict mental health disorders on society, focusing on the high prevalence of depression and anxiety worldwide. The promising potential of AI and psychological software agents, such as chatbots, to improve psychological well-being in the digital environment is highlighted. In order to analyze the scientific production related to the use of virtual assistants in the prediction of anxiety and depression, a comprehensive bibliometric review was conducted using the Scopus database. Subsequently, the study reveals the growing interest in medical chatbot development and research, notably from Australia, China, and the United States, which have made significant contributions. It identifies influential articles, authors, and journals that have significantly shaped this research domain. The analysis also underscores recurring keywords, with “depression” and “anxiety” emerging as central themes. This underscores their paramount importance in chatbot-based mental health prediction efforts and their potential to address these widespread mental health challenges. In conclusion, this article emphasizes chatbots’ promising role in enhancing mental well-being through accessible, personalized support. While acknowledging inherent study limitations, it also points to prospective research directions. As technological advancements persist, chatbots are poised to play a pivotal role in promoting better global mental health outcomes.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Ahmed, A., Ali, N., Aziz, S., et al.: A review of mobile chatbot apps for anxiety and depression and their self-care features. Comput. Methods Prog. Biomed. Update 1, 100012 (2021). https://doi.org/10.1016/j.cmpbup.2021.100012

  2. Hermosa-Bosano, C., Paz, C., Hidalgo-Andrade, P., et al.: Depression, anxiety and stress symptoms experienced by the ecuadorian general population during the pandemic for covid-19. Revista Ecuatoriana de Neurologia 30, 40–47 (2021). https://doi.org/10.46997/revecuatneurol30200040

  3. Wilson, L., Marasoiu, M.: The Development and Use of Chatbots in Public Health: Scoping Review. JMIR Hum. Factors 9 (2022)

    Google Scholar 

  4. Goonesekera, Y., Donkin, L.: A cognitive behavioral therapy chatbot (OTIS) for Health anxiety management: mixed methods pilot study. JMIR Form. Res. 6, e37877 (2022). https://doi.org/10.2196/37877

    Article  Google Scholar 

  5. Bendig, E., Erb, B., Meißner, D., et al.: Feasibility of a Software agent providing a brief Intervention for Self-help to Uplift psychological wellbeing (“SISU”). A single-group pretest-posttest trial investigating the potential of SISU to act as therapeutic agent. Internet Interv. 24 (2021). https://doi.org/10.1016/j.invent.2021.100377

  6. Nicol, G., Wang, R., Graham, S., et al.: Chatbot-delivered cognitive behavioral therapy in adolescents with depression and anxiety during the COVID-19 pandemic: feasibility and acceptability study. JMIR Form. Res. 6, e40242 (2022). https://doi.org/10.2196/40242

    Article  Google Scholar 

  7. Yu, C.S., Hsu, M.H., Wang, Y.C., You, Y.J.: Designing a chatbot for helping parenting practice. Appl. Sci. (Switz.) 13, 1793 (2023). https://doi.org/10.3390/app13031793

    Article  Google Scholar 

  8. Park, D.Y., Kim, H.: Determinants of intentions to use digital mental healthcare content among university students, faculty, and staff: motivation, perceived usefulness, perceived ease of use, and parasocial interaction with AI chatbot. Sustain. (Switz.) 15, 872 (2023). https://doi.org/10.3390/su15010872

    Article  Google Scholar 

  9. Grové, C.: Co-developing a mental health and wellbeing chatbot with and for young people. Front Psychiatry 11, 606041 (2021). https://doi.org/10.3389/fpsyt.2020.606041

    Article  Google Scholar 

  10. Jiang, Q., Zhang, Y., Pian, W.: Chatbot as an emergency exist: mediated empathy for resilience via human-AI interaction during the COVID-19 pandemic. Inf. Process. Manage. 59, 103074 (2022). https://doi.org/10.1016/j.ipm.2022.103074

    Article  Google Scholar 

  11. He, Y., Yang, L., Zhu, X., et al.: Mental health chatbot for young adults with depressive symptoms during the COVID-19 pandemic: single-blind, three-arm randomized controlled trial. J. Med. Internet Res. 24, e40719 (2022). https://doi.org/10.2196/40719

    Article  Google Scholar 

  12. Kaywan, P., Ahmed, K., Ibaida, A., et al.: Early detection of depression using a conversational AI bot: a non-clinical trial. PLoS ONE 18, e0279743 (2023). https://doi.org/10.1371/journal.pone.0279743

    Article  Google Scholar 

  13. Jungmann, S.M., Klan, T., Kuhn, S., Jungmann, F.: Accuracy of a chatbot (ADA) in the diagnosis of mental disorders: comparative case study with lay and expert users. JMIR Form. Res. 3, e13863 (2019). https://doi.org/10.2196/13863

    Article  Google Scholar 

  14. Nißen, M., Rüegger, D., Stieger, M., et al.: The effects of health care chatbot personas with different social roles on the client-chatbot bond and usage intentions: development of a design codebook and web-based study. J. Med. Internet Res. 24, e32630 (2022). https://doi.org/10.2196/32630

    Article  Google Scholar 

  15. Lin, A.P.C., Trappey, C.V., Luan, C.C., et al.: A test platform for managing school stress using a virtual reality group chatbot counseling system. Appl. Sci. (Switz.) 11, 9071 (2021). https://doi.org/10.3390/app11199071

    Article  Google Scholar 

  16. Hungerbuehler, I., Daley, K., Cavanagh, K., et al.: Chatbot-based assessment of employees’ mental health: design process and pilot implementation. JMIR Form. Res. 5, e21678 (2021). https://doi.org/10.2196/21678

    Article  Google Scholar 

  17. You, Y., Gui, X.: Self-diagnosis through AI-enabled chatbot-based symptom checkers: user experiences and design considerations. AMIA Annu. Symp. Proc. 2020, 1354–1363 (2020)

    Google Scholar 

  18. Zhang, R., Li, F., Li, Y.: Design of a rehabilitation training system for older adults with mild cognitive impairment. In: Proceedings - 2018 11th International Symposium on Computational Intelligence and Design, ISCID 2018, vol. 2, pp. 107–110 (2018). https://doi.org/10.1109/ISCID.2018.10125

  19. Ollier, J., Neff, S., Dworschak, C., et al.: Elena+ care for COVID-19, a pandemic lifestyle care intervention: intervention design and study protocol. Front. Public Health 9, 625640 (2021). https://doi.org/10.3389/fpubh.2021.625640

    Article  Google Scholar 

  20. Trappey, A.J.C., Lin, A.P.C., Hsu, K.Y.K., et al.: Development of an empathy-centric counseling chatbot system capable of sentimental dialogue analysis. Processes 10, 930 (2022). https://doi.org/10.3390/pr10050930

    Article  Google Scholar 

  21. Rathnayaka, P., Mills, N., Burnett, D., et al.: A mental health chatbot with cognitive skills for personalised behavioural activation and remote health monitoring. Sensors 22, 3653 (2022). https://doi.org/10.3390/s22103653

    Article  Google Scholar 

  22. Zyoud, S.H., Shakhshir, M., Abushanab, A.S., et al.: Bibliometric mapping of the landscape and structure of nutrition and depression research: visualization analysis. J. Health Popul. Nutr. 42, 33 (2023). https://doi.org/10.1186/s41043-023-00378-2

    Article  Google Scholar 

  23. Aria, M., Cuccurullo, C.: Bibliometrix: an R-tool for comprehensive science mapping analysis. J. Informetr. 11, 959–975 (2017). https://doi.org/10.1016/j.joi.2017.08.007

    Article  Google Scholar 

  24. Hunter, J.D.: Matplotlib: a 2D graphics environment. Comput. Sci. Eng. 9, 90–95 (2007). https://doi.org/10.1109/MCSE.2007.55

    Article  Google Scholar 

  25. McKinney, W., et al.: Data structures for statistical computing in python. In: Proceedings of the 9th Python in Science Conference, pp. 51–56 (2010)

    Google Scholar 

  26. Griffiths, R.R., Johnson, M.W., Carducci, M.A., et al.: Psilocybin produces substantial and sustained decreases in depression and anxiety in patients with life-threatening cancer: a randomized double-blind trial. J. Psychopharmacol. 30, 1181–1197 (2016). https://doi.org/10.1177/0269881116675513

    Article  Google Scholar 

  27. Stanton, R., To, Q.G., Khalesi, S., et al.: Depression, anxiety and stress during COVID-19: associations with changes in physical activity, sleep, tobacco and alcohol use in Australian adults. Int. J. Environ. Res. Public Health 17, 1–13 (2020). https://doi.org/10.3390/ijerph17114065

    Article  Google Scholar 

  28. Fitzpatrick, K.K., Darcy, A., Vierhile, M.: Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully automated conversational agent (Woebot): a randomized controlled trial. JMIR Ment Health 4, e778 (2017). https://doi.org/10.2196/mental.7785

    Article  Google Scholar 

  29. Mazza, M.G., De Lorenzo, R., Conte, C., et al.: Anxiety and depression in COVID-19 survivors: role of inflammatory and clinical predictors. Brain Behav. Immun. 89, 594–600 (2020). https://doi.org/10.1016/j.bbi.2020.07.037

    Article  Google Scholar 

  30. Özdin, S., Bayrak Özdin, Ş: Levels and predictors of anxiety, depression and health anxiety during COVID-19 pandemic in Turkish society: the importance of gender. Int. J. Soc. Psychiatry 66, 504–511 (2020). https://doi.org/10.1177/0020764020927051

    Article  Google Scholar 

  31. Demirci, K., Akgönül, M., Akpinar, A.: Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students. J. Behav. Addict. 4, 85–92 (2015). https://doi.org/10.1556/2006.4.2015.010

    Article  Google Scholar 

  32. Ross, S., Bossis, A., Guss, J., et al.: Rapid and sustained symptom reduction following psilocybin treatment for anxiety and depression in patients with life-threatening cancer: a randomized controlled trial. J. Psychopharmacol. 30, 1165–1180 (2016). https://doi.org/10.1177/0269881116675512

    Article  Google Scholar 

  33. Chisholm, D., Sweeny, K., Sheehan, P., et al.: Scaling-up treatment of depression and anxiety: a global return on investment analysis. Lancet Psychiatry 3, 415–424 (2016). https://doi.org/10.1016/S2215-0366(16)30024-4

    Article  Google Scholar 

  34. Santini, Z.I., Jose, P.E., York Cornwell, E., et al.: Social disconnectedness, perceived isolation, and symptoms of depression and anxiety among older Americans (NSHAP): a longitudinal mediation analysis. Lancet Public Health 5, e62–e70 (2020). https://doi.org/10.1016/S2468-2667(19)30230-0

    Article  Google Scholar 

  35. Liu, C.H., Zhang, E., Wong, G.T.F., et al.: Factors associated with depression, anxiety, and PTSD symptomatology during the COVID-19 pandemic: Clinical implications for U.S. young adult mental health. Psychiatry Res. 290 (2020). https://doi.org/10.1016/j.psychres.2020.113172

  36. Katon, W., Russo, J., Gavin, A.: Predictors of postpartum depression. J. Womens Health 23, 753–759 (2014). https://doi.org/10.1089/jwh.2014.4824

    Article  Google Scholar 

  37. Vliegen, N., Casalin, S., Luyten, P.: The course of postpartum depression: a review of longitudinal studies. Harv. Rev. Psychiatry 22, 1–22 (2014)

    Article  Google Scholar 

  38. Croxford, A., Notley, C.J., Maskrey, V., et al.: An exploratory qualitative study seeking participant views evaluating group Cognitive Behavioral Therapy preparation for alcohol detoxification. J. Subst. Use 20, 61–68 (2015). https://doi.org/10.3109/14659891.2014.894590

    Article  Google Scholar 

  39. Kalemenev, S.V., Zubareva, O.E., Frolova, E.V., et al.: Impairment of exploratory behavior and spatial memory in adolescent rats in lithium-pilocarpine model of temporal lobe epilepsy. Dokl. Biol. Sci. 463, 175–177 (2015). https://doi.org/10.1134/S0012496615040055

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Universidad Ecotec, Samborondón, Ecuador

    María de Lourdes Díaz Carrillo, Manuel Osmany Ramírez Pírez & Gustavo Adolfo Lemos Chang

Authors
  1. María de Lourdes Díaz Carrillo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Manuel Osmany Ramírez Pírez
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gustavo Adolfo Lemos Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to María de Lourdes Díaz Carrillo .

Editor information

Editors and Affiliations

  1. Universidad Distrital Francisco Jose de Caldas, Bogota, Colombia

    Hector Florez

  2. Universidad Ecotec, Guayaquil, Ecuador

    Marcelo Leon

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Díaz Carrillo, M.d.L., Ramírez Pírez, M.O., Lemos Chang, G.A. (2024). Utilizing Chatbots as Predictive Tools for Anxiety and Depression: A Bibliometric Review. In: Florez, H., Leon, M. (eds) Applied Informatics. ICAI 2023. Communications in Computer and Information Science, vol 1874. Springer, Cham. https://doi.org/10.1007/978-3-031-46813-1_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-46813-1_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-46812-4

  • Online ISBN: 978-3-031-46813-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation