skip to main content
10.1145/3510606.3550209acmconferencesArticle/Chapter ViewAbstractPublication PagescprConference Proceedingsconference-collections
research-article

Artificial Intelligence in Mental Health: A Qualitative Expert Study on Realistic Application Scenarios and Future Directions

Published: 17 January 2023 Publication History

Abstract

What can we do to address the rising numbers of people suffering from mental health problems facing the lack of mental health professionals? This study uses 15 qualitative expert interviews to identify six realistic application scenarios for artificial intelligence in mental health that reduce mental health professionals' workload and improve treatment. We classify the application scenarios concerning the type of intelligence they embed (mechanical, analytical, emotional) and the type of task they support (automation, decision support, engagement) to assess their implementation readiness and success. Based on this classification, we develop four application scenarios with the potential for immediate implementation and two possible future directions. Our results contribute to the research stream of artificial intelligence in general and in mental health.1

References

[1]
Alison Abbott. 2021. COVID's mental-health toll: how scientists are tracking a surge in depression. Nature 590, 7845, 194--195.
[2]
Felwah Alqahtani and Rita Orji. 2020. Insights from user reviews to improve mental health apps. Health informatics journal 26, 3, 2042--2066.
[3]
Adnan Asar. 2020. Five Ways AI Can Help Revolutionize Mental Healthcare. Forbes (Aug. 2020).
[4]
Marat Bakpayev, Tae H. Baek, Patrick van Esch, and Sukki Yoon. 2020. Programmatic creative: AI can think but it cannot feel. Australasian Marketing Journal, j.ausmj.2020.04.
[5]
Roberto E. Balmer, Stanford L. Levin, and Stephen Schmidt. 2020. Artificial Intelligence Applications in Telecommunications and other network industries. Telecommunications Policy 44, 6, 101977.
[6]
Gro H. Brundtland. 2000. Mental health in the 21st century. Bull World Health Organ 78, 411.
[7]
K. S. M. Charan, Alenkar K. Aswin, K. S. A. Varshini, and S. Kirthica. 2022. Implementation of Pupil Dilation in AI-Based Emotion Recognition. In Artificial Intelligence and Technologies. Springer, Singapore, 447--454.
[8]
Yang Cheng and Hua Jiang. 2020. AI-Powered mental health chatbots: Examining users' motivations, active communicative action and engagement after mass-shooting disasters. J Contingencies and Crisis Management 28, 3, 339--354.
[9]
Tiffany Chenneville and Rebecca Schwartz-Mette. 2020. Ethical considerations for psychologists in the time of COVID-19. The American psychologist 75, 5, 644--654.
[10]
Emil Chiauzzi and Amy Newell. 2019. Mental Health Apps in Psychiatric Treatment: A Patient Perspective on Real World Technology Usage. JMIR mental health 6, 4, e12292.
[11]
Roger Collier. 2017. Physician burnout a major concern. CMAJ: Canadian Medical Association Journal 189, 39, E1236-7.
[12]
Kathleen M. Collins, Anthony J. Onwuegbuzie, and Qun G. Jiao. 2006. Prevalence of Mixed-methods Sampling Designs in Social Science Research. Evaluation & Research in Education 19, 2, 83--101.
[13]
Thomas H. Davenport and Rajeey Ronanki. 2018. Artificial Intelligence for the Real World. (cover story). Harvard Business Review 96, 1, 108--116.
[14]
Kathleen K. Fitzpatrick, Alison Darcy, and Molly Vierhile. 2017. 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 mental health 4, 2, e19.
[15]
Joseph L. Fleiss, Bruce Levin, and Myunghee C. Paik. 1981. The measurement of interrater agreement. Statistical methods for rates and proportions 2, 212--236, 22--23.
[16]
Nico H. Frijda, Antony S. R. Manstead, and Sacha Bem. 2010. Emotions and Beliefs. Cambridge University Press.
[17]
Ulrich Gnewuch, Stefan Morana, and Alexander Mädche. 2017. Towards Designing Cooperative and Social Conversational Agents for Customer Service. ICIS 2017 Proceedings.
[18]
Dale L. Goodhue and Ronald L. Thompson. 1995. Task-Technology Fit and Individual Performance. MIS Quarterly 19, 2, 213.
[19]
GPT-3. 2022. 300+ GPT-3 Examples, Demos, Apps, Showcase, and NLP Use-cases / GPT-3 Demo (2022). Retrieved March 2, 2022 from https://gpt3demo.com/.
[20]
Sarah Graham, Colin Depp, Ellen E. Lee, Camille Nebeker, Xin Tu, Ho-Cheol Kim, and Dilip V. Jeste. 2019. Artificial Intelligence for Mental Health and Mental Illnesses: an Overview. Current psychiatry reports 21, 11, 116.
[21]
Tad Hirsch, Kritzia Merced, Shrikanth Narayanan, Zac E. Imel, and David C. Atkins. 2017. Designing Contestability: Interaction Design, Machine Learning, and Mental Health. DIS. Designing Interactive Systems (Conference) 2017, 95--99.
[22]
Ming-Hui Huang, Roland Rust, and Vojislav Maksimovic. 2019. The Feeling Economy: Managing in the Next Generation of Artificial Intelligence (AI). California Management Review 61, 4, 43--65.
[23]
Ming-Hui Huang and Roland T. Rust. 2018. Artificial Intelligence in Service. Journal of Service Research 21, 2, 155--172.
[24]
Gretchen Irwin and Daniel Turk. 2005. An Ontological Analysis of Use Case Modeling Grammar. JAIS 6, 1, 1--36.
[25]
Mihir Kamdar, Amanda J. Centi, Stephen Agboola, Nils Fischer, Simone Rinaldi, Jacob J. Strand, Lara Traeger, Jennifer S. Temel, Joseph Greer, Areej El-Jawahri, Vicki Jackson, Joseph Kvedar, and Kamal Jethwani. 2019. A randomized controlled trial of a novel artificial intelligence-based smartphone application to optimize the management of cancer-related pain. JCO 37, 15_suppl, 11514.
[26]
Udo Kuckartz. 2012. Qualitative Inhaltsanalyse. Methoden, Praxis, Computerunterstützung. Beltz Juventa, Weinheim.
[27]
McKinsey. 2020. Transforming healthcare with AI: The impact on the workforce and organizations (2020). Retrieved June 8, 2020 from https://www.mckinsey.com/~/media/McKinsey/Industries/Healthcare%20Systems%20and%20Services/Our%20Insights/Transforming%20healthcare%20with%20AI/Transforming-healthcare-with-AI.pdf.
[28]
Mental Health America. 2021. The State of Mental Health in America (November 2021). Retrieved November 11, 2021 from https://mhanational.org/issues/state-mental-health-america.
[29]
Madison Milne-Ives, Ching Lam, Caroline De Cock, Michelle H. van Velthoven, and Edward Meinert. 2020. Mobile Apps for Health Behavior Change in Physical Activity, Diet, Drug and Alcohol Use, and Mental Health: Systematic Review. JMIR mHealth and uHealth 8, 3, e17046.
[30]
Michael D. Myers and Michael Newman. 2007. The qualitative interview in IS research: Examining the craft. Information and organization 17, 1, 2--26.
[31]
Adam C. Powell, John B. Torous, Joseph Firth, and Kenneth R. Kaufman. 2020. Generating value with mental health apps. BJPsych open 6, 2, e16.
[32]
Martin Prince, Vikram Patel, Shekhar Saxena, Mario Maj, Joanna Maselko, Michael R. Phillips, and Atif Rahman. 2007. No health without mental health. The Lancet 370, 9590, 859--877.
[33]
Arun Rai. 2020. Explainable AI: from black box to glass box. j acad market sci 48, 1, 137--141.
[34]
Lea Reis, Christian Maier, Jens Mattke, Marcus Creutzenberg, and Tim Weitzel. 2020. Addressing User Resistance Would Have Prevented a Healthcare AI Project Failure. MIS Quarterly Executive 19, 4.
[35]
Roland T. Rust and Ming-Hui Huang. 2021. AI for Feeling. In The feeling economy. How artificial intelligence is creating the era of empathy, Roland T. Rust and Ming-Hui Huang, Eds. Palgrave Macmillan, Basingstoke, 151--162.
[36]
R. Sathya, R. Manivannan, and K. Vaidehi. 2022. Vision-Based Personal Face Emotional Recognition Approach Using Machine Learning and Tree-Based Classifier. In Inventive Computation and Information Technologies. Springer, Singapore, 561--573.
[37]
Ulrike Schultze and Michel Avital. 2011. Designing interviews to generate rich data for information systems research. Information and organization 21, 1, 1--16.
[38]
Mohammed Y. Shaheen. 2021. Applications of Artificial Intelligence (AI) in healthcare: A review. ScienceOpen Preprints.
[39]
Monideepa Tarafdar, Christian Maier, Sven Laumer, and Tim Weitzel. 2020. Explaining the link between technostress and technology addiction for social networking sites: A study of distraction as a coping behavior. Info Systems J 30, 1, 96--124.
[40]
United Nations. 2020. Policy Brief: COVID-19 and the Need for Action on Mental Health (2020). Retrieved from https://www.un.org/sites/un2.un.org/files/un_policy_brief-covid_and_mental_health_final.pdf.
[41]
Pei Wang. 2019. On Defining Artificial Intelligence. Journal of Artificial General Intelligence 10, 2, 1--37.
[42]
Kevin Warwick. 2012. Artificial intelligence. The basics. The basics. Routledge, London.
[43]
Akash R. Wasil, Sarah Gillespie, Tiffany Schell, Lorenzo Lorenzo-Luaces, and Robert J. DeRubeis. 2021. Estimating the real-world usage of mobile apps for mental health: development and application of two novel metrics. World psychiatry : official journal of the World Psychiatric Association (WPA) 20, 1, 137--138.
[44]
R. Whittaker. 2019. Mobile phonetext messaging and app-based interventions for smokingcessation. Cochrane Database of Systematic Reviews 10, CD006611.
[45]
WHO. 2020. Info sheet mental health (2020). Retrieved from https://www.who.int/mental_health/management/info_sheet.pdf.
[46]
World Health Organization. 2001. The World health report : 2001 : Mental health : new understanding, new hope. 1020--3311.
[47]
World Health Organization. 2021. Mental health and COVID-19 (August 2021). Retrieved October 7, 2021 from https://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-covid-19/publications-and-technical-guidance/noncommunicable-diseases/mental-health-and-covid-19.

Cited By

View all
  • (2024)Health Care Professionals’ Views on the Use of Passive Sensing, AI, and Machine Learning in Mental Health Care: Systematic Review With Meta-SynthesisJMIR Mental Health10.2196/4957711(e49577)Online publication date: 23-Jan-2024

Index Terms

  1. Artificial Intelligence in Mental Health: A Qualitative Expert Study on Realistic Application Scenarios and Future Directions

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    SIGMIS-CPR '22: Proceedings of the 2022 Computers and People Research Conference
    June 2022
    126 pages
    ISBN:9781450392310
    DOI:10.1145/3510606
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Sponsors

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 17 January 2023

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. AI
    2. classification
    3. healthcare
    4. mental health professionals
    5. psychologists
    6. use cases

    Qualifiers

    • Research-article

    Conference

    SIGMIS-CPR '22
    Sponsor:

    Acceptance Rates

    Overall Acceptance Rate 300 of 480 submissions, 63%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)120
    • Downloads (Last 6 weeks)9
    Reflects downloads up to 17 Jan 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Health Care Professionals’ Views on the Use of Passive Sensing, AI, and Machine Learning in Mental Health Care: Systematic Review With Meta-SynthesisJMIR Mental Health10.2196/4957711(e49577)Online publication date: 23-Jan-2024

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media