This paper is in the following e-collection/theme issue:

Theme Issue 2023 - 2024 : Responsible Design, Integration, and Use of Generative AI in Mental Health (16) Artificial Intelligence (2122) Chatbots and Conversational Agents (740) Generative Language Models Including ChatGPT (707) Natural Language Processing (917) Methods and New Tools in Mental Health Research (558) Development and Evaluation of Research Methods, Instruments and Tools (743) Research Instruments, Questionnaires, and Tools (738) Data Science (357) Theory and Frameworks in Mental Health (40)

Published on in Vol 11 (2024)

This is a member publication of Imperial College London (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55988, first published .
Assessing the Alignment of Large Language Models With Human Values for Mental Health Integration: Cross-Sectional Study Using Schwartz’s Theory of Basic Values

Assessing the Alignment of Large Language Models With Human Values for Mental Health Integration: Cross-Sectional Study Using Schwartz’s Theory of Basic Values

Assessing the Alignment of Large Language Models With Human Values for Mental Health Integration: Cross-Sectional Study Using Schwartz’s Theory of Basic Values

Authors of this article:

Dorit Hadar-Shoval1 Author Orcid Image ;   Kfir Asraf1 Author Orcid Image ;   Yonathan Mizrachi2, 3 Author Orcid Image ;   Yuval Haber4 Author Orcid Image ;   Zohar Elyoseph5, 6 Author Orcid Image
Article Authors Cited by (25) Tweetations (3) Metrics

Journals

  1. Haber Y, Levkovich I, Hadar-Shoval D, Elyoseph Z. The Artificial Third: A Broad View of the Effects of Introducing Generative Artificial Intelligence on Psychotherapy. JMIR Mental Health 2024;11:e54781 View
  2. Shinan-Altman S, Elyoseph Z, Levkovich I. The impact of history of depression and access to weapons on suicide risk assessment: a comparison of ChatGPT-3.5 and ChatGPT-4. PeerJ 2024;12:e17468 View
  3. Hadar-Shoval D, Asraf K, Shinan-Altman S, Elyoseph Z, Levkovich I. Embedded values-like shape ethical reasoning of large language models on primary care ethical dilemmas. Heliyon 2024;10(18):e38056 View
  4. Elyoseph Z, Gur T, Haber Y, Simon T, Angert T, Navon Y, Tal A, Asman O. An Ethical Perspective on the Democratization of Mental Health With Generative AI. JMIR Mental Health 2024;11:e58011 View
  5. Hadar Souval D, Haber Y, Tal A, Simon T, Elyoseph T, Elyoseph Z. Transforming Perceptions: Exploring the Multifaceted Potential of Generative AI for People With Cognitive Disabilities. JMIR Neurotechnology 2025;4:e64182 View
  6. Hadar-Shoval D, Lvovsky M, Asraf K, Shimoni Y, Elyoseph Z. The Feasibility of Large Language Models in Verbal Comprehension Assessment: Mixed Methods Feasibility Study. JMIR Formative Research 2025;9:e68347 View
  7. Asman O, Torous J, Tal A. Responsible Design, Integration, and Use of Generative AI in Mental Health. JMIR Mental Health 2025;12:e70439 View
  8. Choudhury M, Elyoseph Z, Fast N, Ong D, Nsoesie E, Pavlick E. The promise and pitfalls of generative AI. Nature Reviews Psychology 2025;4(2):75 View
  9. Haber Y, Hadar Shoval D, Levkovich I, Yinon D, Gigi K, Pen O, Angert T, Elyoseph Z. The externalization of internal experiences in psychotherapy through generative artificial intelligence: a theoretical, clinical, and ethical analysis. Frontiers in Digital Health 2025;7 View
  10. Peterson A. What does AI consider praiseworthy?. AI and Ethics 2025;5(4):4091 View
  11. Greiner M, Kim J, Thor J. Political CSR: Doing Good or Doing Well?. Journal of Public Affairs 2025;25(2) View
  12. Shoval D, Gigi K, Haber Y, Itzhaki A, Asraf K, Piterman D, Elyoseph Z. A controlled trial examining large Language model conformity in psychiatric assessment using the Asch paradigm. BMC Psychiatry 2025;25(1) View
  13. Zhang W, Zhang Q, Wang P, Zhou X, Wu Y. The application of Generative Artificial Intelligence in mental health care: A bibliometric and visualized analysis. Asian Journal of Psychiatry 2025;110:104596 View
  14. Novis-Deutsch N, Elyoseph T, Elyoseph Z. How much of a pluralist is ChatGPT? A comparative study of value pluralism in generative AI chatbots. AI & SOCIETY 2025 View
  15. Figueroa C, Ramos G, Psihogios A, Ekuban E, Bansie P, de Haas M, Karnik N, Ajilore O, Anderson E, Stiles-Shields C. Advancing youth co-design of ethical guidelines for AI-powered digital mental health tools. Nature Mental Health 2025;3(8):870 View
  16. Hocherman M, Mizrachi Y, Chalutz‐BenGal H. Personality Constructs Predictions Beyond FFM/Big5: A Digital Phenotyping‐Based Exploration. Journal of Personality 2025 View
  17. Xu Y, Fang Z, Lin W, Jiang Y, Jin W, Balaji P, Wang J, Xia T. Evaluation of large language models on mental health: from knowledge test to illness diagnosis. Frontiers in Psychiatry 2025;16 View
  18. Sorin V, Korfiatis P, Collins J, Apakama D, Omar M, Glicksberg B, Yeow M, Brandeland M, Nadkarni G, Klang E. Socio-Demographic Modifiers Shape Large Language Models’ Ethical Decisions. Journal of Healthcare Informatics Research 2025;9(4):567 View
  19. Bucher A, Egger S, Vashkite I, Wu W, Schwabe G. “It’s Not Only Attention We Need”: Systematic Review of Large Language Models in Mental Health Care. JMIR Mental Health 2025;12:e78410 View
  20. Farber S. Human Experts and AI Models in Offender Risk Assessment: A Comparative Pilot Study Using the HCR‐20V3. Behavioral Sciences & the Law 2025 View
  21. Voronin A, Rafikova A. A Conceptual Framework for Exploring AI’s Quasi-Needs in User Dialogue. Minds and Machines 2025;35(4) View
  22. Liu L, Franklin R, Cheong J, Cong T, Byun J, Oh A, Torous J. H3-MOSAIC: multimodal generative AI for semantic place detection from high-frequency GPS on H3 grids in mental health geomatics. International Journal of Health Geographics 2025;24(1) View

Books/Policy Documents

  1. García-Rodríguez S, Karanik M, Pina-Zapata A. Value Engineering in Artificial Intelligence. View
  2. Pappas I, Vassilakopoulou P. Handbook of Human-Centered Artificial Intelligence. View

Conference Proceedings

  1. Manan F, Combey N, Lucky H, Suhartono D. 2025 6th International Conference on Artificial Intelligence and Data Sciences (AiDAS). Consistency in Grading Responses: GPT-4 vs. Gemini 2.5 Flash Under Different Prompt Framing View