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      Review of AI-Based Mental Health Apps

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      proceedings-article
      Author(s): ,
      Publication date (Print):
      Conference name: 36th International BCS Human-Computer Interaction Conference (BCS HCI 23)
      Conference theme: The BCS Human-Computer Interaction Conference 2023 was co-located with the INTERACT 2023 conference, the theme of which was "Design for Equlity and Justice", as increasingly, computer science as a discipline is becoming concerned about issues of justice and equality – from fake news to rights for robots, from the ethics of driverless vehicles to the gamergate controversy. The BCS HCI Conference welcomed submissions on all aspects of human-computer interaction. Topics included: User Experience, usability testing and interaction design; Education and Health; Smart Energy, Smart Transport and the Internet of Things; Interaction Technologies and Applications.
      Conference date: 28–29 August 2023
      Keywords: AI, ML, Mental health, Explainable AI, Mood, Emotion, Mobile apps, Conversational agents
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            Abstract

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            Author and article information

            Contributors
            Abeer Alotaibi
            Corina Sas
            Conference
            Publication date: August 2023
            Publication date (Print): August 2023
            Pages: 238-250
            Affiliations
            [0001]Lancaster University

            Lancaster, UK
            Article
            DOI: 10.14236/ewic/BCSHCI2023.27
            SO-VID: 13905f63-3028-48f2-97fa-fa44e187fd56
            Copyright © © Alotaibi et al. Published by BCS Learning and Development Ltd. Proceedings of BCS HCI 2023, UK
            License:

            This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

            Conference name: 36th International BCS Human-Computer Interaction Conference
            Conference acronym: BCS HCI 23
            Conference number: 36
            Conference location: University of York, UK
            Conference date: 28–29 August 2023
            Conference sponsor: Electronic Workshops in Computing (eWiC)
            Conference theme: The BCS Human-Computer Interaction Conference 2023 was co-located with the INTERACT 2023 conference, the theme of which was "Design for Equlity and Justice", as increasingly, computer science as a discipline is becoming concerned about issues of justice and equality – from fake news to rights for robots, from the ethics of driverless vehicles to the gamergate controversy. The BCS HCI Conference welcomed submissions on all aspects of human-computer interaction. Topics included: User Experience, usability testing and interaction design; Education and Health; Smart Energy, Smart Transport and the Internet of Things; Interaction Technologies and Applications.
            History
            Product

            1477-9358 BCS Learning & Development

            Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/BCSHCI2023.27
            Self URI (journal page): https://ewic.bcs.org/
            Categories
            Series title: Electronic Workshops in Computing

            ScienceOpen disciplines: Applied computer science,Computer science,Security & Cryptology,Graphics & Multimedia design,General computer science,Human-computer-interaction
            Keywords: Mental health,ML,AI,Explainable AI,Mood,Emotion,Mobile apps,Conversational agents

            REFERENCES

            1. Abd-Alrazaq, A.A., Rababeh, A., Alajlani, M., Bewick, B.M. and Househ, M (2020) Effectiveness and safety of using chatbots to improve mental health: systematic review and meta-analysis. Journal of medical Internet research, 22(7), p.e16021.

            2. Alanazi, M. and Aborokbah, M (2022) Multifactor Authentication Approach on Internet of Things: Children's Toys. In 2022 2nd International Conference on Computing and Information Technology (ICCIT) (pp. 6-9). IEEE.

            3. Alfaras, M., Tsaknaki, V., Sanches, P., Windlin, C.,Umair, M., Sas, C. and Höök, K (2020) Frombiodata to somadata. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1-14).

            4. Balkir, E., Kiritchenko, S., Nejadgholi, I. and Fraser,K.C (2022) Challenges in applying explainability methods to improve the fairness of NLP models. arXiv preprint arXiv:2206.03945.

            5. Beatty, C., Malik, T., Meheli, S. and Sinha, C (2022) Evaluating the Therapeutic Alliance with a Free-

            6. Text CBT Conversational Agent (Wysa): A MixedMethods Study. Frontiers in Digital Health, 4, p.847991.

            7. Boucher, E.M., McNaughton, E.C., Harake, N., Stafford, J.L. and Parks, A.C (2021). The impact of a digital intervention (Happify) on loneliness during COVID19: qualitative focus group. JMIR mental health, 8(2), p.e26617.

            8. Bowie-DaBreo, D., Sünram-Lea, S.I., Sas, C. and Iles-Smith, H., 2020. Evaluation of treatment descriptions and alignment with clinical guidance of apps for depression on app stores: systematic search and content analysis. JMIR formative research, 4(11), p.e14988.

            9. Chalabianloo, N., Can, Y.S., Umair, M., Sas, C. and Ersoy, C (2022) Application level performance evaluation of wearable devices for stress classification with explainable AI. Pervasive and Mobile Computing, 87, p.101703.

            10. Cheng, H.F., Wang, R., Zhang, Z., O'Connell, F., Gray, T., Harper, F.M. and Zhu, H (2019) Explaining decision-making algorithms through UI: Strategies to help non-expert stakeholders. In Proceedings of the 2019 CHI conference on human factors in computing systems (pp. 1-12).

            11. Cila, N (2022) Designing Human-Agent Collaborations: Commitment, responsiveness, and support. In CHI Conference on Human Factors in Computing Systems (pp. 1-18).

            12. Colombo, D., Fernández-Álvarez, J., Suso-Ribera, C., Cipresso, P., Valev, H., Leufkens, T., Sas, C., Garcia-Palacios, A., Riva, G. and Botella, C (2020) The need for change: Understanding emotion regulation antecedents and consequences using ecological momentary assessment. Emotion, 20(1), p.30.

            13. Danilevsky, M., Dhanorkar, S., Li, Y., Popa, L., Qian, K. and Xu, A (2021) Explainability for natural language processing. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (pp. 4033-4034).

            14. Druga, S., Christoph, F.L. and Ko, A.J (2022). Family as a Third Space for AI Literacies: How do children and parents learn about AI together?. In CHI Conference on Human Factors in Computing Systems (pp. 1-17).

            15. Ehsan, U., Liao, Q.V., Muller, M., Riedl, M.O. and Weisz, J.D (2021) Expanding explainability: Towards social transparency in ai systems. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (pp. 1-19).

            16. Ehsan, U., Tambwekar, P., Chan, L., Harrison, B. and Riedl, M.O (2019) March. Automated rationale generation: a technique for explainable AI and its effects on human perceptions. In Proceedings of the 24th International Conference on Intelligent User Interfaces (pp. 263-274).

            17. Floridi, L. and Chiriatti, M (2020) GPT-3: Its nature, scope, limits, and consequences. Minds and Machines, 30(4), pp.681-694.

            18. Garg, P., Villasenor, J. and Foggo, V (2020) December. Fairness metrics: A comparative analysis. In 2020 IEEE International Conference on Big Data (Big Data) (pp. 3662-3666). IEEE.

            19. Grové, Christine. "Co-developing a mental health and wellbeing chatbot with and for young people." Frontiers in psychiatry 11 (2021): 606041.

            20. Harrington, C.N., Garg, R., Woodward, A. and Williams, D (2022) “It’s Kind of Like Code-Switching”: Black Older Adults’ Experiences with a Voice Assistant for Health Information Seeking. In CHI Conference on Human Factors in Computing Systems (pp. 1-15).

            21. Jain, V., Agarwal, P (2017). Symptomatic diagnosis and prognosis of psychiatric disorders through personal gadgets. In Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems (pp. 118-123).

            22. Kapania, S., Siy, O., Clapper, G., SP, A.M. and Sambasivan, N (2022)” Because AI is 100% right and safe”: User Attitudes and Sources of AI Authority in India. In CHI Conference on Human Factors in Computing Systems (pp. 1-18).

            23. Khazaal, Y., Favrod, J., Sort, A., Borgeat, F. and Bouchard, S (2018) Computers and games for mental health and well-being. Frontiers in psychiatry, 9, p.141.

            24. Kim, T., Kim, H., Lee, H.Y., Goh, H., Abdigapporov, S., Jeong, M., Cho, H., Han, K., Noh, Y., Lee, S.J. and Hong, H (2022) Prediction for Retrospection: Integrating Algorithmic Stress Prediction into Personal Informatics Systems for College Students’ Mental Health. In CHI Conference on Human Factors in Computing Systems (pp. 1-20).

            25. Kroenke, Kurt, Robert L. Spitzer, and Janet BW Williams. "The PHQ-9: validity of a brief depression severity measure." Journal of general internal medicine16, no. 9 (2001): 606-613

            26. Langer, M., Hunsicker, T., Feldkamp, T., König, C.J. and Grgić-Hlača, N (2022) April. “Look! It’sa Computer Program! It’s an Algorithm! It’s AI!”: DoesTerminology Affect Human Perceptions and Evaluations of Algorithmic Decision-Making Systems?. In CHI Conference on Human Factors in Computing Systems (pp. 1-28).

            27. Lewis, N. (2020) Design and development of a soft skills acquisition application for young children in informal contexts (Doctoral dissertation, Cape Peninsula University of Technology).

            28. Liao, M., Sundar, S.S. and B. Walther, J (2022) User Trust in Recommendation Systems: A comparison of Content-Based, Collaborative and Demographic Filtering. In CHI Conference on Human Factors in Computing Systems (pp. 1-14).

            29. Loi, D., Wolf, C.T., Blomberg, J.L., Arar, R. and Brereton, M (2019) Co-designing AI futures: Integrating AI ethics, social computing, and design. In Companion publication of the 2019 on designing interactive systems conference 2019 companion (pp. 381-384).

            30. Long, D. and Magerko, B (2020) What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1-16).

            31. Lundberg, Scott M., and Su-In Lee (2017) A unified approach to interpreting model predictions." Advances in neural information processing systems 30.

            32. Mehta, A., Niles, A.N., Vargas, J.H., Marafon, T., Couto, D.D. and Gross, J.J (2021) Acceptability and Effectiveness of Artificial Intelligence Therapy for Anxiety and Depression (Youper): Longitudinal Observational Study. Journal of Medical Internet Research, 23(6), p.e26771

            33. Miri, P., Flory, R., Uusberg, A., Culbertson, H., Harvey, R.H., Kelman, A., Peper, D.E., Gross, J.J., Isbister, K. and Marzullo, K (2020) PIV: Placement, pattern, and personalization of an inconspicuous vibrotactile breathing pacer. ACM Transactions on Computer-Human Interaction (TOCHI), 27(1), pp.1-44.

            34. Mohseni, S., Zarei, N. and Ragan, E.D (2021) A multidisciplinary survey and framework for design and evaluation of explainable AI systems. ACM Transactions on Interactive Intelligent Systems (TiiS), 11(3-4), pp.1-45.

            35. Milne-Ives, M., Selby, E., Inkster, B., Lam, C. and Meinert, E., 2022. Artificial intelligence and machine learning in mobile apps for mental health: A scoping review. PLOS Digital Health, 1(8), p.e0000079.

            36. Nikiforos, S., Tzanavaris, S. and Kermanidis, K.L., (2020) Virtual learning communities (VLCs) rethinking: influence on behavior modification—bullying detection through machine learning and natural language processing. Journal of Computers in Education, 7, pp.531-551.

            37. Possati, L.M., 2022. Psychoanalyzing artificial intelligence: the case of Replika. AI & SOCIETY, pp.1-14.

            38. Qu, C., Sas, C., Roquet, C.D. and Doherty, G., 2020. Functionality of top-rated mobile apps for depression: systematic search and evaluation. JMIR mental health, 7(1), p.e15321.

            39. Razak, F.H.A., Hafit, H., Sedi, N., Zubaidi, N.A. and Haron, H., 2010, December. Usability testing with children: Laboratory vs field studies. International Conference on User Science and Engineering (i-USEr) (pp. 104-109). IEEE.

            40. Richards, D., Enrique, A., Palacios, J., Eilert, N., Duffy, D., Doherty, G., Jardine, J., Vigano, N. and Tierney, K (2023) SilverCloud Health: Online Mental Health and Wellbeing Platform. In Digital Therapeutics (pp. 307-330). Chapman and Hall/CRC.

            41. Rojat, T., Puget, R., Filliat, D., Del Ser, J., Gelin, R. and Díaz-Rodríguez, N (2021) Explainable artificial intelligence (xai) on timeseries data: A survey. arXiv preprint arXiv:2104.00950.

            42. Roli Khanna, Jonathan Dodge, Andrew Anderson, Rupika Dikkala, Jed Irvine, Zeyad Shureih, Kin-Ho Lam, Caleb R. Matthews, Zhengxian Lin, Minsuk Kahng, Alan Fern, and Margaret Burnett. (2022) Finding AI’s Faults with AAR/AI: An Empirical Study. ACM Trans. Interact. Intell. Syst. 12, 1, Article 1 (March 2022), 33 pages. https://doi.org/10.1145/3487065

            43. Romanovskyi, O., Pidbutska, N. and Knysh, A., (2021) Elomia Chatbot: The Effectiveness of Artificial Intelligence in the Fight for Mental Health. In COLINS (pp. 1215-1224).’

            44. Saha, K., Kim, S.C., Reddy, M.D., Carter, A.J., Sharma, E., Haimson, O.L. and De Choudhury, M (2019) The language of LGBTQ+ minority stress experiences on social media. Proceedings of the ACM on human-computer interaction, 3(CSCW), pp.1-22.

            45. Sampson, C.J., Arnold, R., Bryan, S., Clarke, P., Ekins, S., Hatswell, A., Hawkins, N., Langham, S., Marshall, D., Sadatsafavi, M. and Sullivan, W (2019) Transparency in decision modelling: what, why, who and how?. Pharmacoeconomics, 37(11), pp.1355-1369.

            46. Sanches, P., Janson, A., Karpashevich, P., Nadal, C., Qu, C., Daudén Roquet, C., Umair, M., Windlin, C., Doherty, G., Höök, K. and Sas, C., (2019) HCI and Affective Health: Taking stock of a decade of studies and charting future research directions. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (pp. 1-17).

            47. Simard, F., Kizuk, S.A. and Fortin, P.E (2021) Mindscape: Transforming Multimodal Physiological Signals into an Application Specific Reference Frame. In Companion Publication of the 2021 International Conference on Multimodal Interaction (pp. 334-336).

            48. Søgaard Neilsen, A. and Wilson, R.L (2019) Combining e-mental health intervention development with human computer interaction (HCI) design to enhance technology-facilitated

            49. Straw, I. and Callison-Burch, C., 2020. Artificial Intelligence in mental health and the biases of language-based models. PloS one, 15(12), p.e0240376.

            50. Terzimehić, N., Häuslschmid, R., Hussmann, H. and Schraefel, M.C (2019) A review & analysis of mindfulness research in HCI: Framing current lines of research and future opportunities. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (pp. 1-13).

            51. Thieme, A., Belgrave, D. and Doherty, G (2020) Machine learning in mental health: A systematic review of the HCI literature to support the development of effective and implementable ML systems. ACM Transactions on Computer-Human Interaction (TOCHI), 27(5), pp.1-53.

            52. Thieme, A., Hanratty, M., Lyons, M., Palacios, J.E., Marques, R., Morrison, C. and Doherty, G (2022) Designing Human-Centered AI for Mental Health: Developing Clinically Relevant Applications for Online CBT Treatment. ACM Transactions on Computer-Human Interaction.Transactions on Interactive Intelligent Systems (TiiS), 11(3-4), pp.1-45. https://doi.org/10.1007/s40692-020-00166-5

            53. Umair, M., Chalabianloo, N., Sas, C. and Ersoy, C., (2021) HRV and stress: A mixed-methods approach for comparison of wearable heart rate sensors for biofeedback. IEEE Access, 9, pp.14005-14024.

            54. Wan, E (2021) " I'm like a wise little person": Notes on the Metal Performance of Woebot the Mental Health Chatbot. Theatre Journal, 73(3), pp.E-21.

            55. Warren, G., Keane, M.T. and Byrne, R.M (2022) Features of Explainability: How users understand counterfactual and causal explanations for categorical and continuous features in XAI. arXiv preprint arXiv:2204.10152.

            56. Zając, H.D., Li, D., Dai, X., Carlsen, J.F., Kensing,F. and Andersen, T.O (2023) Clinician-facing AI in the Wild: Taking Stock of the Sociotechnical Challenges and Opportunities for HCI. ACM Transactions on Computer-Human Interaction, 30(2), pp.1-39.

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